Patrick McGuire: 2017-03-12

Saturday, March 18, 2017

Ravens: Free agent King Dunlap might end up being good, cheap fit at RT despite struggles in pass protection, age - Jamison Hensley (ESPN)

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Anonymous (Original Mix)

Check out Anonymous (Original Mix) by Serg 24 on Beatport.

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Museo Vigili del Fuoco Mantova

[New] Robocide hack Metal, Energy, Crystals Generator ~> anonymous ~> iOS ~> pc => source -> anonymous ~> Robocide pirater pc sans ...

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WikiLeaks Won't Disclose CIA Exploits To Companies Until Certain Demands Are Met

It's been over a week since Wikileaks promised to hand over more information on hacking tools and tactics of the Central Intelligence Agency (CIA) to the affected tech companies, following a leak of a roughly 8,761 documents that Wikileaks claimed belonged to CIA hacking units. "We have decided to work with them, to give them some exclusive access to some of the technical details we have, so

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[FD] TS Session Hijacking / Privilege escalation all windows versions

Terminal Services / Console Session Hijacking can lead to Privilege Escalation. Vulnerability Details. A privileged user, which can gain command execution with NT AUTHORITY/SYSTEM rights can hijack any currently logged in user's session, without any knowledge about his credentials. Terminal Services session can be either in connected or disconnected state. This is high risk vulnerability which allows any local admin to hijack a session and get access to: 1. Domain admin TS session. 2. Any unsaved documents, that hijacked user works on. 3. Any other systems/applications in which hijacked user previously logged in (May include another Remote Desktop sessions, Network Share mappings, applications which require another credentials, E-mail etc.) Tested on: Windows 2012 R2 Windows 2008 Windows 10 Windows 7 Proof of Concept: http://www.korznikov.com/2017/03/0-day-or-feature-privilege-escalation.html @nopernik

Source: Gmail -> IFTTT-> Blogger

[FD] [CVE-2017-6878]:MetInfo5.3.15 Stored Cross Site Scripting

Hello: The following is my application vulnerabilities. －－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－ [CVE-2017-6878]:MetInfo5.3.15 Stored Cross Site Scripting Application: MetInfo Versions Affected: 5.3.15 Vendor URL: http://www.metinfo.cn/ Software Link:http://ift.tt/2ny1gyz Bugs: Stored XSS Author:Arice.chen(DBAPPSecurity Ltd) Description: MetInfo was established in March 2009, is a enterprise CMS, more than 40 m enterprises in the use of MeInfo build their own enterprise website. Vulnerability details： To modify, add a message in problem position insert JavaScript test code

Then the background access to relevant pages, or other users access to the front desk page will make the attack code is executed.

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Gamblers Anonymous

Gamblers Anonymous Has gambling taken over.... Gamblers Anonymous Community classified ad. Browse Community classified ads and free ads.

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Phases of Venus

Just as the Moon goes through phases, Venus' visible sunlit hemisphere waxes and wanes. This composite of telescopic images illustrates the steady changes for the inner planet, seen in the west as the evening star, as Venus grows larger but narrows to a thin crescent from December 20, 2016 through March 10. Gliding along its interior orbit between Earth and Sun, Venus grows larger during that period because it is approaching planet Earth. Its crescent narrows, though, as Venus swings closer to our line-of-sight to the Sun. Closest to the Earth-Sun line but passing about 8 degrees north of the Sun on March 25, Venus will reach a (non-judgmental) inferior conjunction. Soon after, Venus will shine clearly above the eastern horizon in predawn skies as planet Earth's morning star. via NASA http://ift.tt/2mQjhot

Friday, March 17, 2017

Ravens: Brandon Carr signing \"stabilizes a cornerback position that has been in flux for years\" - Jamison Hensley (ESPN)

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Let's make it look just like the instructions.

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Prevent anonymous callers on OpenVoice conferences

When using OpenVoice, the post-call information email lists the calling party with their phone number. Some of the participants appear as "anonymous ...

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I have a new follower on Twitter

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March 17, 2017 at 01:12PM via Twitter http://twitter.com/RandolphNext

Orioles release P Logan Ondrusek, who was due to have his elbow examined next week by Dr. James Andrews (ESPN)

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Business cards!

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ISS Daily Summary Report – 3/16/2017

Rodent Research (RR) Habitat Stow: Following Tuesday’s completion of operations, today the crew stowed the RR habitats. The habitats were cleaned and sealed prior to their next use, planned for RR-5 scheduled for SpX-11. Advanced Plant Experiments (APEX)-04 Harvest: The crew removed the APEX-04 petri plate from the Light Microscopy Module (LMM) facility and harvested the plants. The crew photographed the plants within the petri plate on the Advanced Biology Research Facility (ABRS) photogrid then all plants were inserted into a single Kennedy Space Center (KSC) Fixation Tube (KFT) with RNAlater. The APEX-04 (Epigenetic change in Arabidopsis thaliana in response to spaceflight – differential cytosine DNA methylation of plants on the ISS) experiment investigates how spaceflight can affect an organism on a molecular level without altering its outward appearance. Previous research has demonstrated that large numbers of plant genes are expressed differently in space compared to plants on Earth, which can alter how plants grow. This investigation studies the entire genome of thale cress plants grown in space, creating maps of spaceflight-specific changes in certain groups of genes. Results give new insight into plants’ molecular responses to spaceflight, which benefits efforts to grow plants in space for food and oxygen. TangoLab Card Removal and Cold/Conditioned Stowage Transfer: The crew removed several experiments from the TangoLab Facility and then stowed them in the returning General Laboratory Active Cryogenic ISS Experiment Refrigerators (GLACIERs). Additionally, the crew transferred conditioned stowage samples from Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI) to the GLACIERs and Polar facilities that will be returning on SpX-10. Aquapad Analysis: The crew performed the analysis for the water samples taken on Tuesday. Using the EveryWear application, the crew captured images of the Aquapad Containment Boxes which will be downlinked for analysis. After image capture, the Aquapad Containment Boxes were packed for SpX-10 return. Aquapad is a new approach developed by France’s CNES space agency: paper impregnated with powdered growth medium creates a 3D petri dish. When water is added, the microbes form colored spots revealing their locations. Using a tablet computer application the crew will photograph the dots to calculate precisely how many bacteria are present. Extravehicular Mobility Unit (EMU) Suit Maintenance: The crew performed routine maintenance tasks on EMU 3006 and EMU 3008 including a water recharge, loop scrub, a post-loop scrub water sample and an EMU conductivity test. Mobile Servicing System (MSS) Operations: Overnight, the Robotics Ground Controllers stowed the Special Purpose Dexterous Manipulator (SPDM) on Mobile Base System (MBS) Power Data Grapple Fixture #2 (PDGF2). After Space Station Remote Manipulator System (SSRMS) had released SPDM, SSRMS Latching End Effector (LEE) diagnostics and checkouts as well as SSRMS Joint Diagnostics were performed on the prime and redundant strings. Finally, SSRMS grappled the SpX-10 Flight Releasable Grapple Fixture (FRGF) in preparation of the SpX-10 release. MSS performance was nominal. Tracking and Data Relay Satellite (TDRS) 275 Failure: White Sands Facility reported a timeout of the 275 satellite. Specialist are working the issue and expect a return to service no earlier than 18:30 GMT. Depress Pump Test: Today the crew turned on the airlock depress pump for 44 minutes in order to verify proper Node 3 to Airlock Moderate Temperature Loop (MTL) cooling. This test was performed because when the Airlock cooling was switched from Lab MTL to Node 3 MTL the team realized the flow is in reverse. Temperatures during the test confirmed better cooling to the depress pump and downstream hardware than predicted. Today’s Planned Activities All activities were completed unless otherwise noted. Crew Prep for PAO ISS HAM Video Power Down Rodent Research Habitat Bag Retrieval Review of Polar transfer to Dragon Overview TV PAO Conference with the Participants of the Russian Schoolchildren Olympiad Step into the Future, Cosmonautics Extravehicular Mobility Unit (EMU) Water Recharge Aquapad Water double Analysis ALGOMETRIYA. Pressure and Thermal Algometry preparation for and measurement session. FGB (ГА) Vacuum Cleaning AQUAPAD Packing Extravehicular Mobility Unit (EMU) Cooling Loop Maintenance Scrub Initiation Manufacturing Device Dragon to ISS Stow Depress Pump cooling test with MTL cooling reversed. Coliform Water Sample Analysis 44 +/- 4 hours post processing Depress Pump cooling test with MTL cooling reversed. Polar Transfer To Dragon Overview Review Extravehicular Mobility Unit (EMU) Post Scrub Cooling Loop Water (H2O) Sample Google Street View Dragon Photo Operations Dose Tracker Data Entry Subject EVA Extravehicular Mobility Unit (EMU) Cooling Loop Scrub Deconfiguration APEX-04 Hardware Gather #3 Rodent Research. Stowage of Habitat Module Water Recovery System Waste Water Tank Drain Termination Dose Tracker Data Entry Subject SODI Flash Disk Wrap On-Orbit Hearing Assessment (O-OHA) with EarQ Software Setup and Test Extravehicular Mobility Unit (EMU) Conductivity Test Fluids Integrated Rack Doors Open LMM APEX-04 LMM Petri Plate Remove ALGOMETRIYA. Pressure Algometry Measurement Ops Preparing For Upcoming MagVector Science Run Metal Oxide (METOX) Regeneration Termination Video Recording of Greetings Fluids Integrated Rack Doors Close ESA Weekly crew conference APEX-04 LMM Petri Plate Harvest Fluid Shifts CCFP Setup IMS Update Fluid Shifts CCFP Data Transfer MOTOCARD. Operator Assistance with the Experiment Fluid Shifts CCFP Baseline Stow Rodent Research. Stowage of Habitat Module COTS UHF Communication Unit (CUCU) Crew Command Panel (CCP) Checkout TangoLab Card Cube Remove СОЖ maintenance TangoLab Glacier Sample Insertion Inventory Management System (IMS) Conference Wastewater Storage Tank Assembly (WSTA) Fill Rodent Research Habitat Stow MELFI to Glacier Sample Transfer Countermeasures System (CMS) Advanced Resistive Exercise Device (ARED) Set Screw Tightening MELFI to POLAR Sample Transfer Stow Syringes used in H2O Conductivity Test ALGOMETRIYA. Pressure and Thermal Algometry Measurement Session. Closeout Ops RELAKSATSIYA Charging battery for Relaksatstiya experiment (initiate) Completed Task List Items Replace KTO when full Recorded Greeting – SCH 25th Anniversary Recorded Greeting – RNASA Ground Activities All activities were completed unless otherwise noted. SSRMS Dragon Grapple CUCU Checkout Three-Day Look Ahead: Friday, 03/17: At Home In Space, Dragon Depart OBT, Dragon Transfers, Rodent Research Stow, Conclude PMA3 Fine Leak Check, WVE R&R Prep Saturday, 03/17: Dragon Unberth Prep (Coldbag Packing, Center Stack […]

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[FD] HumHub 0.20.1 / 1.0.0-beta.3: Code Execution

Security Advisory - Curesec Research Team 1. Introduction Affected Product: HumHub 0.20.1 / 1.0.0-beta.3 Fixed in: 1.0.0 Fixed Version http://ift.tt/2mz6d5n Link: &type=zip Vendor Website: https://www.humhub.org/ Vulnerability Code Execution Type: Remote Yes Exploitable: Reported to 01/10/2016 vendor: Disclosed to 03/17/2017 public: Release mode: Coordinated Release CVE: n/a Credits Tim Coen of Curesec GmbH 2. Overview HumHub is a social media platform written in PHP. In version 0.20.1 as well as 1.0.0-beta.3, it is vulnerable to Code Execution as some functionality allows the uploading of PHP files. Successfull exploitation requires specific server settings. A user account is required as well, but registration is open by default. 3. Details CVSS: High 7.6 AV:N/AC:H/Au:N/C:C/I:C/A:C Most of the file uploads of HumHub check the file extension or file type before uploading a file. However, the file upload of the "What's on your mind?"-text box allows upload of arbitrary files. A htaccess file forbids the execution of PHP code in uploaded files, but some servers are configured to not read htaccess files. This is for example the case with default Apache configurations. Because of this, uploaded files should be checked to not have dangerous file extensions. An account is needed, but the registration is open by default. An admin does have the option to configure what files are allowed here: http:// localhost/humhub-0.20.0/index.php?r=admin%2Fsetting%2Ffile. But by default, all files are allowed (although .htaccess is renamed). It should also be noted that the documentation specifically mentions that the upload directory needs to be protected. However, it is to be assumed that not all users follow this suggestion, especially as there is no warning in the installation process itself. Proof of Concept: POST /humhub-0.20.1/index.php?r=file%2Ffile%2Fupload&objectModel=&objectId= HTTP/1.1 Host: localhost Accept: application/json, text/javascript, */*; q=0.01 Accept-Language: en-US,en;q=0.5 Accept-Encoding: gzip, deflate X-CSRF-Token: TzMwdHgxWkcafVg5EHsjKyBeQS0fUCMBeHdxPg1wDiV2cEZZN3xrDw== X-Requested-With: XMLHttpRequest Content-Length: 1080 Content-Type: multipart/form-data; boundary

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[FD] HumHub 1.0.1: XSS

Security Advisory - Curesec Research Team 1. Introduction Affected Product: HumHub 1.0.1 and earlier Fixed in: 1.1.1 Fixed Version http://ift.tt/2nuk69J Link: &type=zip Vendor Website: https://www.humhub.org/ Vulnerability XSS Type: Remote Yes Exploitable: Reported to 01/10/2016 vendor: Disclosed to 03/17/2017 public: Release mode: Coordinated Release CVE: n/a Credits Tim Coen of Curesec GmbH 2. Overview HumHub is a social media platform written in PHP. In version 1.0.1 and earlier, it is vulnerable to a reflected XSS attack if debugging is enabled, as well as a self-XSS attack. This allows an attacker to steal cookies, inject JavaScript keyloggers, or bypass CSRF protection. 3. Details XSS 1: Reflected XSS CVSS: Medium 4.3 AV:N/AC:M/Au:N/C:N/I:P/A:N Description: When the debug mode is enabled, which it is by default, the UserSearch parameter is vulnerable to reflected XSS. Additionally, the resulting error page discloses all cookies - even httpOnly cookies -, and the contents of the $_SERVER array. Proof of Concept: http://localhost/humhub-0.20.0/index.php?UserSearch[last_login]=&r=admin%2Fuser XSS 2: DOM-based Self-XSS CVSS: Low 2.6 AV:N/AC:H/Au:N/C:N/I:P/A:N There is a reflected DOM-based self-XSS vulnerability in HumHub. It may be possible to exploit this issue via ClickJacking in some browsers. Proof of Concept: Visit the profile of a user: http://localhost/humhub-0.20.0/index.php?r= space%2Fspace&sguid=d2f06d0a-47e1-4549-b469-c8a1df48faca In the "What's on your mind?"-text box enter: '">

4. Solution To mitigate this issue please upgrade at least to version 1.1.1: http://ift.tt/2nLSDwj Please note that a newer version might already be available. 5. Report Timeline 01/10/2016 Informed Vendor about Issue 01/12/2016 Vendor confirms issue 02/10/2016 Vendor requests more time 08/16/2016 Vendor releases partial fix 09/26/2016 Vendor releases fix 03/27/2017 Disclosed to public Blog Reference: http://ift.tt/2m95AUy

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[FD] phplist 3.2.6: XSS

To trigger the payload, visit - Add new subscribers to list: http://localhost/lists/admin/?page=importsimple&list=84&tk =c - Overview of all lists: http://localhost/lists/admin/?page=list&tk=c - List members of list: http://localhost/lists/admin/?page=members&id=3&tk=c - View member (loaded as part of the lists tab): http://localhost/lists/admin/?page= user&id=4 - Creating a Campaign (in step 4): http://localhost/lists/admin/?page =send&id=2&tk=c&tab=Lists Persistent XSS: Subscribe Page Various parameters of the subscribe page - such as the title - are vulnerable to persistent XSS. An account with the privilege to edit the subscribe page is required. Add a new subscribe page: http://localhost/lists/admin/?page=spage as title use: subscribe'">

To trigget the payload: - Visit the subscribe page: http://localhost/lists/index.php?p=subscribe&id=1 - Visit the subscribe page overview: http://localhost/lists/admin/?page=spage Persistent XSS: Bounce Rule The expression parameter of bounce rules is vulnerable to persistent XSS. An account with the privilege to edit bounce rules is required. Add a new bounce rule:http://localhost/lists/admin/?page=bouncerules&type= active as regular expression use: test'"&ht;

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[FD] phplist 3.2.6: SQL Injection

Security Advisory - Curesec Research Team 1. Introduction Affected phplist 3.2.6 Product: Fixed in: 3.3.1 Fixed Version http://ift.tt/2mzkxuq Link: http://ift.tt/2nuFV9t Vendor Website: http://ift.tt/1Gss40X Vulnerability SQL Injection Type: Remote Yes Exploitable: Reported to 01/10/2017 vendor: Disclosed to 02/20/2017 public: Release mode: Coordinated Release CVE: n/a (not requested) Credits Tim Coen of Curesec GmbH 2. Overview phplist is an application to manage newsletters, written in PHP. In version 3.2.6, it is vulnerable to SQL injection. The application contains two SQL injections, one of which is in the administration area and one which requires no credentials. Additionally, at least one query is not properly protected against injections. Furthermore, a query in the administration area discloses some information on the password hashes of users. 3. Details SQL Injection 1: Edit Subscription CVSS: High 7.1 CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L It is possible for an unauthenticated user to perform an SQL injection when updating the subscription information of an already subscribed user. The protection against SQL injection relies on a combination of a custom magic quotes function which applies addslashes to all input values and a function which applies htmlspecialchars to all inputs. Additionally, some input values are cast to integers to prevent injections. addslashes protects against injections into arguments which are placed into single quotes, while htmlspecialchars protects against injections into double quotes. It should be noted that neither addslashes nor htmlspecialchars are recommended to prevent SQL Injection. The update functionality is vulnerable to SQL Injection as it uses the key of POST data, while only values of POST data are escaped via addslashes, but not keys. Proof of Concept: POST /lists/index.php?p=subscribe&uid=f8082b7cc4da7f94ba42d88ebfb5b1e2&email= foo%40example.com HTTP/1.1 Host: localhost Connection: close Content-Length: 209 email=foo%40example.com&emailconfirm=foo%40example.com&textemail=1&list%5B2 or extractvalue(1,version()) %5D=signup&listname%5B2%5D=newsletter& VerificationCodeX=&update=Subscribe+to+the+selected+newsletters%27 The proof of concept is chosen for simplicity and will only work if error messages are displayed to the user. If this is not the case, other techniques can be used to extract data from the database. Code: /lists/admin/subscribelib2.php $lists = ''; if (is_array($_POST['list'])) { while (list($key, $val) = each($_POST['list'])) { if ($val == 'signup') { $result = Sql_query("replace into {$GLOBALS['tables']['listuser']} (userid,listid,entered) values($userid,$key,now())"); # $lists .= " * ".$_POST ["listname"][$key]."\n"; } } } SQL Injection 2: Sending Campaign (Admin) CVSS: Medium 4.7 CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L When sending a campaign, the sendformat parameter is vulnerable to SQL injection. The injection takes place into an UPDATE, so the easiest way to extract data is via error based SQL injection. An account with the right to send campaigns is required to exploit this issue. Proof of Concept: POST /lists/admin/?page=send&id=2&tk=c&tab=Format HTTP/1.1 Host: localhost Cookie: PHPSESSID=k6m0jgl4niq7643hohik5jgm12 Connection: close Content-Length: 323 formtoken=27211e65922b95d986bfaf706ccd2ca0&workaround_fck_bug=1&followupto= http%3A%2F%2Flocalhost%2Flists%2Fadmin%2F%3Fpage%3Dsend%26id%3D2%26tk%3Dc%26tab%3DScheduling &htmlformatted=auto&sendformat=HTML" or extractvalue(1,version()) -- - &id=2& status=draft&id=2&status=draft&campaigntitle=campaign+meta%27%22%3E&testtarget= Code: // /lists/admin/send_core.php:198 $result = Sql_Query( sprintf('update %s set subject = "%s", fromfield = "%s", tofield = "%s", replyto ="%s", embargo = "%s", repeatinterval = "%s", repeatuntil = "%s", message = "%s", textmessage = "%s", footer = "%s", status = "%s", htmlformatted = "%s", sendformat = "%s", template = "%s" where id = %d', $tables['message'], sql_escape(strip_tags ($messagedata['campaigntitle'])), /* we store the title in the subject field. Better would be to rename the DB column, but this will do for now */ sql_escape ($messagedata['fromfield']), sql_escape($messagedata['tofield']), sql_escape ($messagedata['replyto']), sprintf('d-d-d d:d', $messagedata['embargo'] ['year'], $messagedata['embargo']['month'], $messagedata['embargo']['day'], $messagedata['embargo']['hour'], $messagedata['embargo']['minute']), $messagedata['repeatinterval'], sprintf('d-d-d d:d', $messagedata ['repeatuntil']['year'], $messagedata['repeatuntil']['month'], $messagedata ['repeatuntil']['day'], $messagedata['repeatuntil']['hour'], $messagedata ['repeatuntil']['minute']), sql_escape($messagedata['message']), sql_escape ($messagedata['textmessage']), sql_escape($messagedata['footer']), sql_escape ($messagedata['status']), $htmlformatted ? '1' : '0', $messagedata ['sendformat'], sql_escape($messagedata['template']), $id ) ); Sort By: Password (Admin) CVSS: Low 2.2 CVSS:3.0/AV:N/AC:H/PR:H/UI:N/S:U/C:L/I:N/A:N When viewing users, the sortby parameter can be used to sort the list. The drop down list allows sorting by email, dates, and so on. All non-word characters are removed, but there are no further checks. It is possible to gather some information on the password of users via this parameter, as it is possible to set it to sort by password. By repeatedly changing the password of an existing user, the characters of a password hash could be bruteforced by looking at the position of the user the attacker controls. An account with the right to view users is required to exploit this issue. Proof of Concept: http://localhost//lists/admin/?page=users&start=0&find=&findby=&sortby=password &sortorder=desc&change=Go&id=0&find=&findby=email Insufficient Protection against SQL Injection CVSS: n/a When subscribing a user, metadata is saved in the database. When saving this data in the database, it is neither properly escaped nor are prepared statements used, but the input is HTML encoded. Because of this, an unauthenticated user has control over part of the query. This issue is not currently exploitable, but may be exploitable if changes are made to the query. The approach of HTML encoding instead of using prepared statements to defend against SQL injection is also more error prone and may result in further queries which are vulnerable. A user can create a database error with the following request: POST /lists/index.php?p=subscribe&id=a\ HTTP/1.1 Host: localhost Cookie: PHPSESSID=8h5fh18cqe41a2l1t6224tf9v4 Connection: close formtoken= 5bf7774ff0f2e396081dc1478cd92201&makeconfirmed=0&email=foo%40example.com& emailconfirm=foo%40example.com&textemail=1&list%5B2%5D=signup&listname%5B2%5D= newsletter&VerificationCodeX=&subscribe= Subscribe+to+the+selected+newsletters%27 The resulting query is: insert into phplist_user_user_history (ip,userid,date,summary,detail,systeminfo) values("127.0.0.1",2,now (),"Re-Subscription","[...]"," HTTP_USER_AGENT = [...] REQUEST_URI = /lists/ index.php?p=subscribe&id=a\") It can be seen that the slash in the request escapes the quote of the query which causes an error. 4. Solution To mitigate this issue please upgrade at least to version 3.3.1: http://ift.tt/2m8X2wV download Please note that a newer version might already be available. 5. Report Timeline 01/10/2017 Informed Vendor about Issue 01/16/2017 Vendor confirms 02/15/2017 Asked Vendor to confirm that new release fixes issues 02/15/2017 Vendor confirms 02/20/2017 Disclosed to public Blog Reference: http://ift.tt/2mBySrr

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NCIS: Hidden Crimes [hack]

[New] NCIS: Hidden Crimes [hack] Coins, Cash Generator ~> anonymous => iPhone => tips -> anonymous -> no jailbreak => cheats om meer ...

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Museo Vigili del Fuoco Mantova

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I have a new follower on Twitter

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Sony Is Working On Mobile-to-Mobile Wireless Charging Technology

So you are in a party with your friends, and your phone is running low on battery. Oops! The ideal solution is to charge your phone using a charger or a power bank, but not everyone carries power banks or chargers with them all the time, especially in a party. What if you can charge your phone wirelessly using another phone when it runs out of battery? Isn't that great? Well, thanks to Sony

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Anonymous

Anonymous - Products | crunchbase. ... Anonymous · Overview · Timeline · Contributors. ADD TO LIST. Top Contributors. Add to this Profile. Contribute ...

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The Simpson Tapped Out (cheat)

[image] [image] [image] This is The Simpson Tapped Out Cash, Donuts generator. Enter your username,... (1/1) - Italian (IT)

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I have a new follower on Twitter

Ramesh Padala
Founder @flexheroapp, @yogatailor, ex @Saavn, Meditator,Yogi,Chai Maker, Stanford, Angel , Advisor, Snowboarder, HuffPost Writer & Poop Picker / @akirathedoggie
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I have a new follower on Twitter

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Mimas in Saturnlight

Peering from the shadows, the Saturn-facing hemisphere of Mimas lies in near darkness alongside a dramatic sunlit crescent. The mosaic was captured near the Cassini spacecraft's final close approach on January 30, 2017. Cassini's camera was pointed in a nearly sunward direction only 45,000 kilometers from Mimas. The result is one of the highest resolution views of the icy, crater-pocked, 400 kilometer diameter moon. An enhanced version better reveals the Saturn-facing hemisphere of the synchronously rotating moon lit by sunlight reflected from Saturn itself. To see it, slide your cursor over the image (or follow this link). Other Cassini images of Mimas include the small moon's large and ominous Herschel Crater. via NASA http://ift.tt/2nr9Tec

Rumors: Anonymous Warriors player says the team has problems

The Golden State Warriors are in a dogfight at the top of the Western Conference standings as they only own a one-game lead over the San Antonio ...

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Museo Vigili del Fuoco Mantova

Flip Diving hack Coins, Tickets Generator => tool ~> mobile ~> anonymous -> anonymous => tips -> Flip Diving latest tricks 1 week 6 days ago #5704 ...

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Book Review: The Lean Startup

Errebody said I should read The Lean Startup, so I did. Then I went to a "startup fair" to ask if people have been using the ideas. They are.

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Thursday, March 16, 2017

Parameterize function without anonymous or nested functions

Parameterize function without anonymous or... Learn more about parameterize, anonymous, nested, function, global, variable MATLAB Coder, ...

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Legal Question Answering using Ranking SVM and Deep Convolutional Neural Network. (arXiv:1703.05320v1 [cs.CL])

This paper presents a study of employing Ranking SVM and Convolutional Neural Network for two missions: legal information retrieval and question answering in the Competition on Legal Information Extraction/Entailment. For the first task, our proposed model used a triple of features (LSI, Manhattan, Jaccard), and is based on paragraph level instead of article level as in previous studies. In fact, each single-paragraph article corresponds to a particular paragraph in a huge multiple-paragraph article. For the legal question answering task, additional statistical features from information retrieval task integrated into Convolutional Neural Network contribute to higher accuracy.

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Concentration Bounds for Two Timescale Stochastic Approximation with Applications to Reinforcement Learning. (arXiv:1703.05376v1 [cs.AI])

Two-timescale Stochastic Approximation (SA) algorithms are widely used in Reinforcement Learning (RL). In such methods, the iterates consist of two parts that are updated using different stepsizes. We develop the first convergence rate result for these algorithms; in particular, we provide a general methodology for analyzing two-timescale linear SA. We apply our methodology to two-timescale RL algorithms such as GTD(0), GTD2, and TDC.

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Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting. (arXiv:1703.05390v1 [cs.CL])

Keyword spotting (KWS) constitutes a major component of human-technology interfaces. Maximizing the detection accuracy at a low false alarm (FA) rate, while minimizing the footprint size, latency and complexity are the goals for KWS. Towards achieving them, we study Convolutional Recurrent Neural Networks (CRNNs). Inspired by large-scale state-of-the-art speech recognition systems, we combine the strengths of convolutional layers and recurrent layers to exploit local structure and long-range context. We analyze the effect of architecture parameters, and propose training strategies to improve performance. With only ~230k parameters, our CRNN model yields acceptably low latency, and achieves 97.71% accuracy at 0.5 FA/hour for 5 dB signal-to-noise ratio.

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Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing. (arXiv:1703.05446v1 [cs.CV])

Human parsing has recently attracted a lot of research interests due to its huge application potentials. However existing datasets have limited number of images and annotations, and lack the variety of human appearances and the coverage of challenging cases in unconstrained environment. In this paper, we introduce a new benchmark "Look into Person (LIP)" that makes a significant advance in terms of scalability, diversity and difficulty, a contribution that we feel is crucial for future developments in human-centric analysis. This comprehensive dataset contains over 50,000 elaborately annotated images with 19 semantic part labels, which are captured from a wider range of viewpoints, occlusions and background complexity. Given these rich annotations we perform detailed analyses of the leading human parsing approaches, gaining insights into the success and failures of these methods. Furthermore, in contrast to the existing efforts on improving the feature discriminative capability, we solve human parsing by exploring a novel self-supervised structure-sensitive learning approach, which imposes human pose structures into parsing results without resorting to extra supervision (i.e., no need for specifically labeling human joints in model training). Our self-supervised learning framework can be injected into any advanced neural networks to help incorporate rich high-level knowledge regarding human joints from a global perspective and improve the parsing results. Extensive evaluations on our LIP and the public PASCAL-Person-Part dataset demonstrate the superiority of our method.

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Minimax Regret Bounds for Reinforcement Learning. (arXiv:1703.05449v1 [stat.ML])

We consider the problem of efficient exploration in finite horizon MDPs.We show that an optimistic modification to model-based value iteration, can achieve a regret bound $\tilde{O}( \sqrt{HSAT} + H^2S^2A+H\sqrt{T})$ where $H$ is the time horizon, $S$ the number of states, $A$ the number of actions and $T$ the time elapsed. This result improves over the best previous known bound $\tilde{O}(HS \sqrt{AT})$ achieved by the UCRL2 algorithm.The key significance of our new results is that when $T\geq H^3S^3A$ and $SA\geq H$, it leads to a regret of $\tilde{O}(\sqrt{HSAT})$ that matches the established lower bounds of $\Omega(\sqrt{HSAT})$ up to a logarithmic factor. Our analysis contain two key insights. We use careful application of concentration inequalities to the optimal value function as a whole, rather than to the transitions probabilities (to improve scaling in $S$), and we use "exploration bonuses" based on Bernstein's inequality, together with using a recursive -Bellman-type- Law of Total Variance (to improve scaling in $H$).

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Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. (arXiv:1703.05452v1 [cs.AI])

We consider the optimal value of information (VoI) problem, where the goal is to sequentially select a set of tests with a minimal cost, so that one can efficiently make the best decision based on the observed outcomes. Existing algorithms are either heuristics with no guarantees, or scale poorly (with exponential run time in terms of the number of available tests). Moreover, these methods assume a known distribution over the test outcomes, which is often not the case in practice. We propose an efficient sampling-based online learning framework to address the above issues. First, assuming the distribution over hypotheses is known, we propose a dynamic hypothesis enumeration strategy, which allows efficient information gathering with strong theoretical guarantees. We show that with sufficient amount of samples, one can identify a near-optimal decision with high probability. Second, when the parameters of the hypotheses distribution are unknown, we propose an algorithm which learns the parameters progressively via posterior sampling in an online fashion. We further establish a rigorous bound on the expected regret. We demonstrate the effectiveness of our approach on a real-world interactive troubleshooting application and show that one can efficiently make high-quality decisions with low cost.

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Database Learning: Toward a Database that Becomes Smarter Every Time. (arXiv:1703.05468v1 [cs.DB])

In today's databases, previous query answers rarely benefit answering future queries. For the first time, to the best of our knowledge, we change this paradigm in an approximate query processing (AQP) context. We make the following observation: the answer to each query reveals some degree of knowledge about the answer to another query because their answers stem from the same underlying distribution that has produced the entire dataset. Exploiting and refining this knowledge should allow us to answer queries more analytically, rather than by reading enormous amounts of raw data. Also, processing more queries should continuously enhance our knowledge of the underlying distribution, and hence lead to increasingly faster response times for future queries.

We call this novel idea---learning from past query answers---Database Learning. We exploit the principle of maximum entropy to produce answers, which are in expectation guaranteed to be more accurate than existing sample-based approximations. Empowered by this idea, we build a query engine on top of Spark SQL, called Verdict. We conduct extensive experiments on real-world query traces from a large customer of a major database vendor. Our results demonstrate that database learning supports 73.7% of these queries, speeding them up by up to 23.0x for the same accuracy level compared to existing AQP systems.

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ParaGraphE: A Library for Parallel Knowledge Graph Embedding. (arXiv:1703.05614v1 [cs.AI])

Knowledge graph embedding aims at translating the knowledge graph into numerical representations by transforming the entities and relations into con- tinuous low-dimensional vectors. Recently, many methods [1, 5, 3, 2, 6] have been proposed to deal with this problem, but existing single-thread implemen- tations of them are time-consuming for large-scale knowledge graphs. Here, we design a unified parallel framework to parallelize these methods, which achieves a significant time reduction without in uencing the accuracy. We name our framework as ParaGraphE, which provides a library for parallel knowledge graph embedding. The source code can be downloaded from https: //github.com/LIBBLE/LIBBLE-MultiThread/tree/master/ParaGraphE.

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Semantic Change Detection with Hypermaps. (arXiv:1604.07513v2 [cs.CV] UPDATED)

Change detection is the study of detecting changes between two different images of a scene taken at different times. By the detected change areas, however, a human cannot understand how different the two images. Therefore, a semantic understanding is required in the change detection research such as disaster investigation. The paper proposes the concept of semantic change detection, which involves intuitively inserting semantic meaning into detected change areas. We mainly focus on the novel semantic segmentation in addition to a conventional change detection approach. In order to solve this problem and obtain a high-level of performance, we propose an improvement to the hypercolumns representation, hereafter known as hypermaps, which effectively uses convolutional maps obtained from convolutional neural networks (CNNs). We also employ multi-scale feature representation captured by different image patches. We applied our method to the TSUNAMI Panoramic Change Detection dataset, and re-annotated the changed areas of the dataset via semantic classes. The results show that our multi-scale hypermaps provided outstanding performance on the re-annotated TSUNAMI dataset.

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Improving Policy Gradient by Exploring Under-appreciated Rewards. (arXiv:1611.09321v3 [cs.LG] UPDATED)

This paper presents a novel form of policy gradient for model-free reinforcement learning (RL) with improved exploration properties. Current policy-based methods use entropy regularization to encourage undirected exploration of the reward landscape, which is ineffective in high dimensional spaces with sparse rewards. We propose a more directed exploration strategy that promotes exploration of under-appreciated reward regions. An action sequence is considered under-appreciated if its log-probability under the current policy under-estimates its resulting reward. The proposed exploration strategy is easy to implement, requiring small modifications to an implementation of the REINFORCE algorithm. We evaluate the approach on a set of algorithmic tasks that have long challenged RL methods. Our approach reduces hyper-parameter sensitivity and demonstrates significant improvements over baseline methods. Our algorithm successfully solves a benchmark multi-digit addition task and generalizes to long sequences. This is, to our knowledge, the first time that a pure RL method has solved addition using only reward feedback.

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Optimal Detection of Faulty Traffic Sensors Used in Route Planning. (arXiv:1702.02628v2 [cs.AI] UPDATED)

In a smart city, real-time traffic sensors may be deployed for various applications, such as route planning. Unfortunately, sensors are prone to failures, which result in erroneous traffic data. Erroneous data can adversely affect applications such as route planning, and can cause increased travel time. To minimize the impact of sensor failures, we must detect them promptly and accurately. However, typical detection algorithms may lead to a large number of false positives (i.e., false alarms) and false negatives (i.e., missed detections), which can result in suboptimal route planning. In this paper, we devise an effective detector for identifying faulty traffic sensors using a prediction model based on Gaussian Processes. Further, we present an approach for computing the optimal parameters of the detector which minimize losses due to false-positive and false-negative errors. We also characterize critical sensors, whose failure can have high impact on the route planning application. Finally, we implement our method and evaluate it numerically using a real-world dataset and the route planning platform OpenTripPlanner.

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Asymmetric Tri-training for Unsupervised Domain Adaptation. (arXiv:1702.08400v2 [cs.CV] UPDATED)

Deep-layered models trained on a large number of labeled samples boost the accuracy of many tasks. It is important to apply such models to different domains because collecting many labeled samples in various domains is expensive. In unsupervised domain adaptation, one needs to train a classifier that works well on a target domain when provided with labeled source samples and unlabeled target samples. Although many methods aim to match the distributions of source and target samples, simply matching the distribution cannot ensure accuracy on the target domain. To learn discriminative representations for the target domain, we assume that artificially labeling target samples can result in a good representation. Tri-training leverages three classifiers equally to give pseudo-labels to unlabeled samples, but the method does not assume labeling samples generated from a different domain.In this paper, we propose an asymmetric tri-training method for unsupervised domain adaptation, where we assign pseudo-labels to unlabeled samples and train neural networks as if they are true labels. In our work, we use three networks asymmetrically. By asymmetric, we mean that two networks are used to label unlabeled target samples and one network is trained by the samples to obtain target-discriminative representations. We evaluate our method on digit recognition and sentiment analysis datasets. Our proposed method achieves state-of-the-art performance on the benchmark digit recognition datasets of domain adaptation.

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Entreprenuers Anonymous

Entreprenuers Anonymous. Posted on 16th March 2017 | 16th March 2017 by. The Monthly Meetup is an Informal Meetup for Early Stage and Aspiring ...

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Overeaters Anonymous (OA) Newcomers Weekly Meeting

Are you having a problem controlling your eating? Is your eating affecting your health or the way you live your life? Do your eating behaviors make you ...

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DG Comp encourages anonymous tip-offs

The EU's competition watchdog today launched a new programme that will allow whistleblowers to remain anonymous – a move some observers say ...

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Heretofore Anonymous Reservoir Becomes Latest Crack in California's Water System

The epic Winter of 2017 giveth, and taketh away. How an overworked pumping system is forcing California to reshuffle water deliveries, and dip into ...

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Anonymous Jobs

Look at Anonymous profile and browse the latest full & part-time jobs and vacancies in the UK - 290902 - CV-Library.

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Display help text to anonymous

Hi, My site allows anonymous to add content. The problem is that only registered users can see the help text I entered with the back office. "Instructions ...

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Greater Atlanta Overeaters Anonymous Convention

Stay on Track with Recovery! Convention of Overeaters Anonymous see atlantaoa.org.

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Presenting a anonymous call with CallKit

How to indicate to CallKit that those calls are anonymous (I would like to have a localized message for "Anonymous" and that the call list is properly ...

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[FD] Skype Insecure Library Loading Vulnerability (api-ms-win-core-winrt-string-l1-1-0.dll)

Vulnerability Title: Skype Insecure Library Loading Vulnerability (api-ms-win-core-winrt-string-l1-1-0.dll) Affected Product: Skype Vendor Homepage: http://ift.tt/1NIUrge MSRC Case 32355 TRK:0001002846 CVE-ID : CVE-2017-6517 Severity: Medium *Description:* Microsoft Skype contains a DLL hijacking vulnerability that could allow an unauthenticated attacker to execute arbitrary code on the targeted system. This vulnerability exists due to some DLL file loaded by ‘Skype.exe’ improperly. And it allows an attacker to load (api-ms-win-core-winrt-string-l1-1-0.dll) this DLL file of the attacker’s choosing that could execute arbitrary code without the user's knowledge. *Affected Product:* Skype 7.16.0.102 *Impact:* Attacker can exploit the vulnerability to load a DLL file of the attacker's choosing that could execute arbitrary code. This may help attacker to successful exploits the system if user creates shell as a DLL. *Proof-Of-Concept :* 1. Create malicious dll file and save it as 'api-ms-win-core-winrt-string-l1-1-0.dll' in your "Downloads" directory. 2. Download Skype 7.16.0.102 and save it in your "Downloads" directory. 3. Execute Skype.exe from your "Downloads" directory. 4. Malicious dll file gets executed. *Credit:* *Sachin Wagh (tiger_tigerboy)*

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[FD] USB Pratirodh Insecure Password Storage Information Disclosure Vulnerability

Vulnerability Title: USB Pratirodh Insecure Password Storage Information Disclosure Vulnerability Affekted Product: USB resistance Product Homepage: http://ift.tt/2l88gO0 CVE-ID : CVE-2017-6911 Severity: Medium *Description:* USB Pratirodh is prone to sensitive information disclosure. Its Store sensitive information such as username and password hash in usb.xml file. An attacker with physical access to the system can modify the file according his own requirements that may aid in further attack. *Affected Product:* USB resistance *Credit:* *Sachin Wagh (tiger_tigerboy)*

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[FD] USB Pratirodh XML External Entity Injection Vulnerability

[FD] Axis Camera Multiple Vulnerabilities

Introduction ============ Vulnerabilities were identified in the camera software by Axis. These were discovered during a black box assessment and therefore the vulnerability list should not be considered exhaustive; observations suggest that it is likely that further vulnerabilities exist. Affected Software And Versions ============================== Model P1204, software versions <= 5.50.4 Model P3225, software versions <= 6.30.1 Model P3367, software versions <= 6.10.1.2 Model M3045, software versions <= 6.15.4.1 Model M3005, software versions <= 5.50.5.7 Model M3007, software versions <= 6.30.1.1 CVE === No CVEs have been assigned to these vulnerabilities. Vulnerability Overview ====================== 1. Axis01: No cross-site request forgery protections 2. Axis02: Bypass manual checks for XSS 3. Axis03: Web services run as root 4. Axis04: Script editor function allows for arbitrary write as root on successful CSRF attack 5. Axis05: root setuid .CGI scripts and binaries present 6. Axis06: Inability to disable the http interface Vulnerability Details =====================

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[FD] Windows DVD Maker XML External Entity File Disclosure

[FD] Microsoft Windows "LoadUvsTable()" Buffer Overflow Vulnerability

Hello, The details of this vulnerability can be found here if interested: http://ift.tt/2huPkaw Microsoft initially tried to fixed the issue in MS16-147, but the fix was incomplete and the issue remained unpatched til Microsoft March 2017 patch release. https://twitter.com/hosselot/status/809059287037251584 It appears MS17-013 finally fixed the vulnerability properly. http://ift.tt/2mG409W cheers. @hosselot

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Ravens receive B+ grade for free agency moves; \"bolstered their defense with two major investments\" - Jamison Hensley (ESPN)

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Linux Kernel Gets Patch For Years-Old Serious Vulnerability

Another dangerous vulnerability has been discovered in Linux kernel that dates back to 2009 and affects a large number of Linux distros, including Red Hat, Debian, Fedora, OpenSUSE, and Ubuntu. The latest Linux kernel flaw (CVE-2017-2636), which existed in the Linux kernel for the past seven years, allows a local unprivileged user to gain root privileges on affected systems or cause a denial

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ISS Daily Summary Report – 3/15/2017

Mobile Servicing System (MSS) Operations: Overnight, the Robotics Ground Controllers unstowed the Robotic Refueling Mission (RRM) Payload from the Special Purpose Dexterous Manipulator (SPDM) Enhanced Orbit Replaceable Unit (ORU) Temporary Platform (EOTP). They then stowed the RRM on the Dragon Trunk Site 1 Passive Flight Releasable Attachment Mechanism (PFRAM). Next they released the RRM and withdrew SPDM Arm1 from the Dragon Trunk. Finally the Robotics Ground Controllers rotated the SPDM EOTP to its nominal park position. MSS performance was nominal. Manufacturing Device Feedstock Exchange: The crew replaced the Feedstock Canister for the Manufacturing Device, resupplying the 3-D printer with Acrylonitrile Butadiene Styrene (ABS) for future prints. The Manufacturing Device-Additive Manufacturing Facility (AMF) enables the production of components on the ISS for both NASA and commercial objectives. Parts, entire experiments, and tools can be created on demand utilizing the AMF that is installed into an Express Rack locker location. The AMF is capable of producing parts out of a wide variety of thermopolymers including engineered plastics. NanoRacks Multi-Gas Monitor (MGM): This morning the crew removed the MGM from EXpedite PRocessing of Experiments to Space Station (EXPRESS) Rack 4, and packed it for return on SpX10. The ground teams elected to return the MGM as they have been unable to command to it and hope to retrieve saved data during ground troubleshooting. The Nanoracks MGM is a proof of concept sniffer type payload mounted in a Nanoracks platform that continuously monitors oxygen, carbon dioxide, ammonia and water gases in the ISS cabin air. NanoRacks Module 9 Operations: The crew is scheduled to perform the Return minus 5 days (R-5) operations in support of the NanoRacks Module 9 experiments for the Student Spaceflight Experiments Program (SSEP)/National Center for Earth and Space Science Education (NCESSE) experiments. Supporting various schools and student designed experiments studying a range of objectives, the SSEP lets students design experiments that address real challenges of living and working in space. The program also is a key initiative for U.S. science, technology, engineering and math (STEM) education, educating and inspiring the next generation of scientists and engineers to work on the space program. Arabidopsis Germination in Martian Soil Simulant (Open Window School, Bellevue, WA) The experiment determines if Arabidopsis thaliana germinates in Martian soil simulant in microgravity. Other researchers have shown A. thaliana grows in Martian soil simulant, but the lower gravity of Mars cannot be simulated on Earth. The microgravity environment on the ISS allows for testing of plant growth in an environment closer to the gravity on Mars than that of Earth. Living Water Filters: Triops in Microgravity (North Star Charter School, Boise, ID) This student experiment investigates the capability of Triops longicaudatus to filter bacteria out of pond water in microgravity as well as they do on Earth. After the experiment returns to Earth, analysis will be conducted in cooperation with Boise Waste Water Treatment facility to determine which kinds of bacteria remain, using a Heterotrophic Plate Count method. Also to be measured is the mass of the Triops that were hatched in microgravity and compare it to the mass of the Triops that were hatched on Earth. Shells of Glass Capsules, Covered with Different Substances Reacting in Regular Water (Langevin Science School, Calgary, Alberta, Canada) The focus of this investigation is to determine how three different capsule shells dissolve in water when coated in cornstarch (carbohydrates), gum Arabic (gum) or sucrose (carbohydrates) in a microgravity environment. Research indicates that these substances dissolve in water and that certain coatings may react “faster” or ”slower” resulting from a lack of gravity. After the test is completed aboard the ISS, observations are made to determine which substances can be completely dissolved, which can’t be dissolved at all, or which were approaching their dissolving point. Based on this information, astronauts can be sent encapsulated medication with a certain substance covering the outer shell for more effective treatment. Knowing the differences may improve how a medication is produced and delivered into space. SLIPS in Microgravity (Arts and Technology Academy, Eugene, OR) The investigation tests Slippery Liquid-Infused Porous Surfaces (SLIPS) in a microgravity environment to find out if the change in gravitational environment changes its properties as comparted to Earth. If it does it could possibly solve frost-over for rockets at launch and in microgravity. Using three volumes with various surfaces and tubes coated on the inside with SLIPS in both volume 2 and 3. In this experiment the hope is to solve frost-over on the ISS with SLIPS by finding if SLIPS cannot only stay on the face of a solid but also still make liquids slip off of the solid in microgravity. Streptococcus mutans Production of Lactic Acid in Microgravity (Montachusett Regional Vocational Technical High School, Fitchburg, MA). This experiment hopes to find a more efficient dental care regimen for astronauts. The factor observed in the experiment is whether or not Streptococcus mutans (S. mutans) produce more lactic acid in microgravity and if the reproduction rate of the previously stated bacteria is affected in space. Improper oral hygiene is a factor that contributes to poor health in the rest of the body. If the S. mutans prove to be a greater force in space than they do on Earth, then the aseptic habits of astronauts may need to be modified. Germination of Quinoa in Space (Mabry Elementary School, Hillsborough County, FL) The investigation studies how microgravity affects the germination of quinoa seeds by comparing the number of seeds that germinate on Earth with the number of seeds that germinate in microgravity. The MixStix is loaded with Chenopodium quinoa seeds on a growth substrate and water separated by a clamp. The crew is requested to open the clamp and shake the tube gently to introduce the seeds to water beginning germination, 14 days before undock. Testing the Effectiveness of Tobramycin and Loteprednol Etabonate (Zylet) on Staphylococcus Epidermidis Type of Bacterial Conjunctivitis in Microgravity (Bearden Middle School, Knox County, TN) Bacterial conjunctivitis is a common infection and can affect astronauts during space travel. As space travel progresses bacterial conjunctivitis could […]

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[FD] SEC Consult SA-20170316-0 :: Authenticated command injection in multiple Ubiquiti Networks products

SEC Consult Vulnerability Lab Security Advisory < 20170316-0 > ======================================================================= title: Authenticated Command Injection product: Multiple Ubiquiti Networks products, e.g. TS-16-CARRIER, TS-5-POE, TS-8-PRO, AG-HP-2G16, AG-HP-2G20, AG-HP-5G23, AG-HP-5G27, AirGrid M, AirGrid M2, AirGrid M5, AR, AR-HP, BM2HP, BM2-Ti, BM5HP, BM5-Ti, LiteStation M5, locoM2, locoM5, locoM9, M2, M3, M365, M5, M900, NB-2G18, NB-5G22, NB-5G25, NBM3, NBM365, NBM9, NSM2, NSM3, NSM365, NSM5, PBM10, PBM3, PBM365, PBM5, PICOM2HP, Power AP N vulnerable version: v1.3.3 (SW), v5.6.9/v6.0 (XM) fixed version: - CVE number: - impact: Critical homepage: https://www.ubnt.com found: 2016-11-22 by: T. Weber (Office Vienna) SEC Consult Vulnerability Lab An integrated part of SEC Consult Bangkok - Berlin - Linz - Luxembourg - Montreal - Moscow Kuala Lumpur - Singapore - Vienna (HQ) - Vilnius - Zurich http://ift.tt/1mGHMNR ======================================================================= Vendor description:

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Yahoo! Hack! How It Took Just One-Click to Execute Biggest Data Breach in History

In the digital world, it just takes one click to get the keys to the kingdom. Do you know spear-phishing was the only secret weapon behind the biggest data breach in the history? It’s true, as one of the Yahoo employees fell victim to a simple phishing attack and clicked one wrong link that let the hackers gain a foothold in the company's internal networks. You may be familiar with phishing

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The Cone Nebula from Hubble

Stars are forming in the gigantic dust pillar called the Cone Nebula. Cones, pillars, and majestic flowing shapes abound in stellar nurseries where natal clouds of gas and dust are buffeted by energetic winds from newborn stars. The Cone Nebula, a well-known example, lies within the bright galactic star-forming region NGC 2264. The Cone was captured in unprecedented detail in this close-up composite of several observations from the Earth-orbiting Hubble Space Telescope. While the Cone Nebula, about 2,500 light-years away in Monoceros, is around 7 light-years long, the region pictured here surrounding the cone's blunted head is a mere 2.5 light-years across. In our neck of the galaxy that distance is just over half way from our Sun to its nearest stellar neighbors in the Alpha Centauri star system. The massive star NGC 2264 IRS, seen by Hubble's infrared camera in 1997, is the likely source of the wind sculpting the Cone Nebula and lies off the top of the image. The Cone Nebula's reddish veil is produced by glowing hydrogen gas. via NASA http://ift.tt/2mqrwGk

It's Fappening Again! Private Photos of Emma Watson and Others Leaked Online

Are you clicking nude selfies? That is fine and not any criminal act, but this act can land you in trouble — here's how! Almost three years after a wave of private photographs of celebrities leaked online, "The Fappening 2.0" appears to be underway with the circulation of alleged naked pictures of female celebrities, including Emma Watson and Amanda Seyfried on Reddit and 4chan. Back in 2014

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Leaky Radiation Belts

Since their discovery at the dawn of the Space Age, Earth's radiation belts continue to reveal new complex structures and behaviors. During a particularly intense event in late June 2015, the inner edge of the region of trapped electrons moved closer to Earth. As the region retreated outward, it left behind a population of high-energy electrons forming another radiation belt inside the L=2 shell (The 'L-shell' value identifies a field line in a magnetic dipole. The numerical value corresponds to the furthest distance from Earth in Earth radii, in this case two Earth radii). This flux of high-energy electrons persisted considerably longer than expected, the relativistic electrons slowly leaking away. It took over a year for the relativistic electron flux in the belt to decline below the level of detectability for the instruments on the Van Allen Probes. The 3-dimensional radiation belt model in the visualizations above was constructed by propagating electron flux measurements, corresponding to a given time and distance from Earth measured by the Van Allen Probes, along a 3-dimensional structure of magnetic dipole field lines.

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Wednesday, March 15, 2017

Anonymous hack instagram

SubscribeSubscribedUnsubscribeNov 19, 2015 Anonymous hackers want the public's help in hunting out and shutting down social media accounts ...

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Fuzzy Model Tree For Early Effort Estimation. (arXiv:1703.04565v1 [cs.SE])

Use Case Points (UCP) is a well-known method to estimate the project size, based on Use Case diagram, at early phases of software development. Although the Use Case diagram is widely accepted as a de-facto model for analyzing object oriented software requirements over the world, UCP method did not take sufficient amount of attention because, as yet, there is no consensus on how to produce software effort from UCP. This paper aims to study the potential of using Fuzzy Model Tree to derive effort estimates ...

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Learning best K analogies from data distribution for case-based software effort estimation. (arXiv:1703.04567v1 [cs.SE])

Case-Based Reasoning (CBR) has been widely used to generate good software effort estimates. The predictive performance of CBR is a dataset dependent and subject to extremely large space of configuration possibilities. Regardless of the type of adaptation technique, deciding on the optimal number of similar cases to be used before applying CBR is a key challenge. In this paper we propose a new technique based on Bisecting k-medoids clustering algorithm to better understanding the structure of a dataset and discovering the ...

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Minimizing Maximum Regret in Commitment Constrained Sequential Decision Making. (arXiv:1703.04587v1 [cs.AI])

In cooperative multiagent planning, it can often be beneficial for an agent to make commitments about aspects of its behavior to others, allowing them in turn to plan their own behaviors without taking the agent's detailed behavior into account. Extending previous work in the Bayesian setting, we consider instead a worst-case setting in which the agent has a set of possible environments (MDPs) it could be in, and develop a commitment semantics that allows for probabilistic guarantees on the agent's behavior in any of the environments it could end up facing. Crucially, an agent receives observations (of reward and state transitions) that allow it to potentially eliminate possible environments and thus obtain higher utility by adapting its policy to the history of observations. We develop algorithms and provide theory and some preliminary empirical results showing that they ensure an agent meets its commitments with history-dependent policies while minimizing maximum regret over the possible environments.

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A computational investigation of sources of variability in sentence comprehension difficulty in aphasia. (arXiv:1703.04677v1 [cs.CL])

We present a computational evaluation of three hypotheses about sources of deficit in sentence comprehension in aphasia: slowed processing, intermittent deficiency, and resource reduction. The ACT-R based Lewis & Vasishth 2005 model is used to implement these three proposals. Slowed processing is implemented as slowed default production-rule firing time; intermittent deficiency as increased random noise in activation of chunks in memory; and resource reduction as reduced goal activation. As data, we considered subject vs. object relatives presented in a self-paced listening modality to 56 individuals with aphasia (IWA) and 46 matched controls. The participants heard the sentences and carried out a picture verification task to decide on an interpretation of the sentence. These response accuracies are used to identify the best parameters (for each participant) that correspond to the three hypotheses mentioned above. We show that controls have more tightly clustered (less variable) parameter values than IWA; specifically, compared to controls, among IWA there are more individuals with low goal activations, high noise, and slow default action times. This suggests that (i) individual patients show differential amounts of deficit along the three dimensions of slowed processing, intermittent deficient, and resource reduction, (ii) overall, there is evidence for all three sources of deficit playing a role, and (iii) IWA have a more variable range of parameter values than controls. In sum, this study contributes a proof of concept of a quantitative implementation of, and evidence for, these three accounts of comprehension deficits in aphasia.

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Understanding Black-box Predictions via Influence Functions. (arXiv:1703.04730v1 [stat.ML])

How can we explain the predictions of a black-box model? In this paper, we use influence functions -- a classic technique from robust statistics -- to trace a model's prediction through the learning algorithm and back to its training data, identifying the points most responsible for a given prediction. Applying ideas from second-order optimization, we scale up influence functions to modern machine learning settings and show that they can be applied to high-dimensional black-box models, even in non-convex and non-differentiable settings. We give a simple, efficient implementation that requires only oracle access to gradients and Hessian-vector products. On linear models and convolutional neural networks, we demonstrate that influence functions are useful for many different purposes: to understand model behavior, debug models and detect dataset errors, and even identify and exploit vulnerabilities to adversarial training-set attacks.

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Towards Moral Autonomous Systems. (arXiv:1703.04741v1 [cs.AI])

Both the ethics of autonomous systems and the problems of their technical implementation have by now been studied in some detail. Less attention has been given to the areas in which these two separate concerns meet. This paper, written by both philosophers and engineers of autonomous systems, addresses a number of issues in machine ethics that are located at precisely the intersection between ethics and engineering. We first discuss different approaches towards the conceptual design of autonomous systems and their implications on the ethics implementation in such systems. Then we examine problematic areas regarding the specification and verification of ethical behavior in autonomous systems, particularly with a view towards the requirements of future legislation. We discuss transparency and accountability issues that will be crucial for any future wide deployment of autonomous systems in society. Finally we consider the, often overlooked, possibility of intentional misuse of AI systems and the possible dangers arising out of deliberately unethical design, implementation, and use of autonomous robots.

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Weighted Voting Via No-Regret Learning. (arXiv:1703.04756v1 [cs.GT])

Voting systems typically treat all voters equally. We argue that perhaps they should not: Voters who have supported good choices in the past should be given higher weight than voters who have supported bad ones. To develop a formal framework for desirable weighting schemes, we draw on no-regret learning. Specifically, given a voting rule, we wish to design a weighting scheme such that applying the voting rule, with voters weighted by the scheme, leads to choices that are almost as good as those endorsed by the best voter in hindsight. We derive possibility and impossibility results for the existence of such weighting schemes, depending on whether the voting rule and the weighting scheme are deterministic or randomized, as well as on the social choice axioms satisfied by the voting rule.

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FastQA: A Simple and Efficient Neural Architecture for Question Answering. (arXiv:1703.04816v1 [cs.CL])

Recent development of large-scale question answering (QA) datasets triggered a substantial amount of research into end-to-end neural architectures for QA. Increasingly complex systems have been conceived without comparison to a simpler neural baseline system that would justify their complexity. In this work, we propose a simple heuristic that guided the development of FastQA, an efficient end-to-end neural model for question answering that is very competitive with existing models. We further demonstrate, that an extended version (FastQAExt) achieves state-of-the-art results on recent benchmark datasets, namely SQuAD, NewsQA and MsMARCO, outperforming most existing models. However, we show that increasing the complexity of FastQA to FastQAExt does not yield any systematic improvements. We argue that the same holds true for most existing systems that are similar to FastQAExt. A manual analysis reveals that our proposed heuristic explains most predictions of our model, which indicates that modeling a simple heuristic is enough to achieve strong performance on extractive QA datasets. The overall strong performance of FastQA puts results of existing, more complex models into perspective.

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Exploring the Combination Rules of D Numbers From a Perspective of Conflict Redistribution. (arXiv:1703.04862v1 [cs.AI])

Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and completeness constraint, limit the development and application of that theory to a large extend. To overcome the shortcomings and enhance its capability of representing the uncertainty, a novel model, called D numbers, has been proposed recently. However, many key issues, for example how to implement the combination of D numbers, remain unsolved. In the paper, we have explored the combination of D Numbers from a perspective of conflict redistribution, and proposed two combination rules being suitable for different situations for the fusion of two D numbers. The proposed combination rules can reduce to the classical Dempster's rule in Dempster-Shafer theory under a certain conditions. Numerical examples and discussion about the proposed rules are also given in the paper.

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Emergence of Grounded Compositional Language in Multi-Agent Populations. (arXiv:1703.04908v1 [cs.AI])

By capturing statistical patterns in large corpora, machine learning has enabled significant advances in natural language processing, including in machine translation, question answering, and sentiment analysis. However, for agents to intelligently interact with humans, simply capturing the statistical patterns is insufficient. In this paper we investigate if, and how, grounded compositional language can emerge as a means to achieve goals in multi-agent populations. Towards this end, we propose a multi-agent learning environment and learning methods that bring about emergence of a basic compositional language. This language is represented as streams of abstract discrete symbols uttered by agents over time, but nonetheless has a coherent structure that possesses a defined vocabulary and syntax. We also observe emergence of non-verbal communication such as pointing and guiding when language communication is unavailable.

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Syntax-Preserving Belief Change Operators for Logic Programs. (arXiv:1703.04912v1 [cs.AI])

Recent methods have adapted the well-established AGM and belief base frameworks for belief change to cover belief revision in logic programs. In this study here, we present two new sets of belief change operators for logic programs. They focus on preserving the explicit relationships expressed in the rules of a program, a feature that is missing in purely semantic approaches that consider programs only in their entirety. In particular, operators of the latter class fail to satisfy preservation and support, two important properties for belief change in logic programs required to ensure intuitive results.

We address this shortcoming of existing approaches by introducing partial meet and ensconcement constructions for logic program belief change, which allow us to define syntax-preserving operators that satisfy preservation and support. Our work is novel in that our constructions not only preserve more information from a logic program during a change operation than existing ones, but they also facilitate natural definitions of contraction operators, the first in the field to the best of our knowledge.

In order to evaluate the rationality of our operators, we translate the revision and contraction postulates from the AGM and belief base frameworks to the logic programming setting. We show that our operators fully comply with the belief base framework and formally state the interdefinability between our operators. We further propose an algorithm that is based on modularising a logic program to reduce partial meet and ensconcement revisions or contractions to performing the operation only on the relevant modules of that program. Finally, we compare our approach to two state-of-the-art logic program revision methods and demonstrate that our operators address the shortcomings of one and generalise the other method.

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Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. (arXiv:1703.04940v1 [cs.LG])

We introduce a criterion, resilience, which allows properties of a dataset (such as its mean or best low rank approximation) to be robustly computed, even in the presence of a large fraction of arbitrary additional data. Resilience is a weaker condition than most other properties considered so far in the literature, and yet enables robust estimation in a broader variety of settings, including the previously unstudied problem of robust mean estimation in $\ell_p$-norms.

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Neural Programming by Example. (arXiv:1703.04990v1 [cs.AI])

Programming by Example (PBE) targets at automatically inferring a computer program for accomplishing a certain task from sample input and output. In this paper, we propose a deep neural networks (DNN) based PBE model called Neural Programming by Example (NPBE), which can learn from input-output strings and induce programs that solve the string manipulation problems. Our NPBE model has four neural network based components: a string encoder, an input-output analyzer, a program generator, and a symbol selector. We demonstrate the effectiveness of NPBE by training it end-to-end to solve some common string manipulation problems in spreadsheet systems. The results show that our model can induce string manipulation programs effectively. Our work is one step towards teaching DNN to generate computer programs.

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Fuzzy Rankings: Properties and Applications. (arXiv:1703.05201v1 [cs.AI])

In practice, a ranking of objects with respect to given set of criteria is of considerable importance. However, due to lack of knowledge, information of time pressure, decision makers might not be able to provide a (crisp) ranking of objects from the top to the bottom. Instead, some objects might be ranked equally, or better than other objects only to some degree. In such cases, a generalization of crisp rankings to fuzzy rankings can be more useful. The aim of the article is to introduce the notion of a fuzzy ranking and to discuss its several properties, namely orderings, similarity and indecisiveness. The proposed approach can be used both for group decision making or multiple criteria decision making when uncertainty is involved.

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On Inconsistency Indices and Inconsistency Axioms in Pairwise Comparisons. (arXiv:1703.05204v1 [cs.AI])

Pairwise comparisons are an important tool of modern (multiple criteria) decision making. Since human judgments are often inconsistent, many studies focused on the ways how to express and measure this inconsistency, and several inconsistency indices were proposed as an alternative to Saaty inconsistency index and inconsistency ratio for reciprocal pairwise comparisons matrices. This paper aims to: firstly, introduce a new measure of inconsistency of pairwise comparisons and to prove its basic properties; secondly, to postulate an additional axiom, an upper boundary axiom, to an existing set of axioms; and the last, but not least, the paper provides proofs of satisfaction of this additional axiom by selected inconsistency indices as well as it provides their numerical comparison.

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InScript: Narrative texts annotated with script information. (arXiv:1703.05260v1 [cs.CL])

This paper presents the InScript corpus (Narrative Texts Instantiating Script structure). InScript is a corpus of 1,000 stories centered around 10 different scenarios. Verbs and noun phrases are annotated with event and participant types, respectively. Additionally, the text is annotated with coreference information. The corpus shows rich lexical variation and will serve as a unique resource for the study of the role of script knowledge in natural language processing.

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Recurrent Orthogonal Networks and Long-Memory Tasks. (arXiv:1602.06662v2 [cs.NE] UPDATED)

Although RNNs have been shown to be powerful tools for processing sequential data, finding architectures or optimization strategies that allow them to model very long term dependencies is still an active area of research. In this work, we carefully analyze two synthetic datasets originally outlined in (Hochreiter and Schmidhuber, 1997) which are used to evaluate the ability of RNNs to store information over many time steps. We explicitly construct RNN solutions to these problems, and using these constructions, illuminate both the problems themselves and the way in which RNNs store different types of information in their hidden states. These constructions furthermore explain the success of recent methods that specify unitary initializations or constraints on the transition matrices.

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A Logic of Knowing Why. (arXiv:1609.06405v2 [cs.AI] UPDATED)

When we say "I know why he was late", we know not only the fact that he was late, but also an explanation of this fact. We propose a logical framework of "knowing why" inspired by the existing formal studies on why-questions, scientific explanation, and justification logic. We introduce the Ky_i operator into the language of epistemic logic to express "agent i knows why phi" and propose a Kripke-style semantics of such expressions in terms of knowing an explanation of phi. We obtain two sound and complete axiomatizations w.r.t. two different model classes depending on different assumptions about introspection.

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Find Your Own Way: Weakly-Supervised Segmentation of Path Proposals for Urban Autonomy. (arXiv:1610.01238v2 [cs.RO] UPDATED)

We present a weakly-supervised approach to segmenting proposed drivable paths in images with the goal of autonomous driving in complex urban environments. Using recorded routes from a data collection vehicle, our proposed method generates vast quantities of labelled images containing proposed paths and obstacles without requiring manual annotation, which we then use to train a deep semantic segmentation network. With the trained network we can segment proposed paths and obstacles at run-time using a vehicle equipped with only a monocular camera without relying on explicit modelling of road or lane markings. We evaluate our method on the large-scale KITTI and Oxford RobotCar datasets and demonstrate reliable path proposal and obstacle segmentation in a wide variety of environments under a range of lighting, weather and traffic conditions. We illustrate how the method can generalise to multiple path proposals at intersections and outline plans to incorporate the system into a framework for autonomous urban driving.

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Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence. (arXiv:1611.03218v4 [cs.AI] UPDATED)

Acquiring your first language is an incredible feat and not easily duplicated. Learning to communicate using nothing but a few pictureless books, a corpus, would likely be impossible even for humans. Nevertheless, this is the dominating approach in most natural language processing today. As an alternative, we propose the use of situated interactions between agents as a driving force for communication, and the framework of Deep Recurrent Q-Networks for evolving a shared language grounded in the provided environment. We task the agents with interactive image search in the form of the game Guess Who?. The images from the game provide a non trivial environment for the agents to discuss and a natural grounding for the concepts they decide to encode in their communication. Our experiments show that the agents learn not only to encode physical concepts in their words, i.e. grounding, but also that the agents learn to hold a multi-step dialogue remembering the state of the dialogue from step to step.

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Deep Learning of Robotic Tasks using Strong and Weak Human Supervision. (arXiv:1612.01086v2 [cs.AI] UPDATED)

We propose a scheme for training a computerized agent to perform complex human tasks such as highway steering. The scheme is designed to follow a natural learning process whereby a human instructor teaches a computerized trainee. The learning process consists of five elements: (i) unsupervised feature learning; (ii) supervised imitation learning; (iii) supervised reward induction; (iv) supervised safety module construction; and (v) reinforcement learning. We implemented the last four elements of the scheme using deep convolutional networks and applied it to successfully create a computerized agent capable of autonomous highway steering over the well-known racing game Assetto Corsa. We demonstrate that the use of the last four elements is essential to effectively carry out the steering task using vision alone, without access to a driving simulator internals, and operating in wall-clock time. This is made possible also through the introduction of a safety network, a novel way for preventing the agent from performing catastrophic mistakes during the reinforcement learning stage.

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Highway and Residual Networks learn Unrolled Iterative Estimation. (arXiv:1612.07771v3 [cs.NE] UPDATED)

The past year saw the introduction of new architectures such as Highway networks and Residual networks which, for the first time, enabled the training of feedforward networks with dozens to hundreds of layers using simple gradient descent. While depth of representation has been posited as a primary reason for their success, there are indications that these architectures defy a popular view of deep learning as a hierarchical computation of increasingly abstract features at each layer.

In this report, we argue that this view is incomplete and does not adequately explain several recent findings. We propose an alternative viewpoint based on unrolled iterative estimation -- a group of successive layers iteratively refine their estimates of the same features instead of computing an entirely new representation. We demonstrate that this viewpoint directly leads to the construction of Highway and Residual networks. Finally we provide preliminary experiments to discuss the similarities and differences between the two architectures.

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Application of Fuzzy Logic in Design of Smart Washing Machine. (arXiv:1701.01654v2 [cs.SY] UPDATED)

Washing machine is of great domestic necessity as it frees us from the burden of washing our clothes and saves ample of our time. This paper will cover the aspect of designing and developing of Fuzzy Logic based, Smart Washing Machine. The regular washing machine (timer based) makes use of multi-turned timer based start-stop mechanism which is mechanical as is prone to breakage. In addition to its starting and stopping issues, the mechanical timers are not efficient with respect of maintenance and electricity usage. Recent developments have shown that merger of digital electronics in optimal functionality of this machine is possible and nowadays in practice. A number of international renowned companies have developed the machine with the introduction of smart artificial intelligence. Such a machine makes use of sensors and smartly calculates the amount of run-time (washing time) for the main machine motor. Realtime calculations and processes are also catered in optimizing the run-time of the machine. The obvious result is smart time management, better economy of electricity and efficiency of work. This paper deals with the indigenization of FLC (Fuzzy Logic Controller) based Washing Machine, which is capable of automating the inputs and getting the desired output (wash-time).

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Residual LSTM: Design of a Deep Recurrent Architecture for Distant Speech Recognition. (arXiv:1701.03360v2 [cs.LG] UPDATED)

In this paper, a novel architecture for a deep recurrent neural network, residual LSTM is introduced. A plain LSTM has an internal memory cell that can learn long term dependencies of sequential data. It also provides a temporal shortcut path to avoid vanishing or exploding gradients in the temporal domain. The residual LSTM provides an additional spatial shortcut path from lower layers for efficient training of deep networks with multiple LSTM layers. Compared with the previous work, highway LSTM, residual LSTM separates a spatial shortcut path with temporal one by using output layers, which can help to avoid a conflict between spatial and temporal-domain gradient flows. Furthermore, residual LSTM reuses the output projection matrix and the output gate of LSTM to control the spatial information flow instead of additional gate networks, which effectively reduces more than 10% of network parameters. An experiment for distant speech recognition on the AMI SDM corpus shows that 10-layer plain and highway LSTM networks presented 13.7% and 6.2% increase in WER over 3-layer aselines, respectively. On the contrary, 10-layer residual LSTM networks provided the lowest WER 41.0%, which corresponds to 3.3% and 2.8% WER reduction over plain and highway LSTM networks, respectively.

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Actor-Critic Reinforcement Learning with Simultaneous Human Control and Feedback. (arXiv:1703.01274v2 [cs.AI] UPDATED)

This paper contributes a first study into how different human users deliver simultaneous control and feedback signals during human-robot interaction. As part of this work, we formalize and present a general interactive learning framework for online cooperation between humans and reinforcement learning agents. In many human-machine interaction settings, there is a growing gap between the degrees-of-freedom of complex semi-autonomous systems and the number of human control channels. Simple human control and feedback mechanisms are required to close this gap and allow for better collaboration between humans and machines on complex tasks. To better inform the design of concurrent control and feedback interfaces, we present experimental results from a human-robot collaborative domain wherein the human must simultaneously deliver both control and feedback signals to interactively train an actor-critic reinforcement learning robot. We compare three experimental conditions: 1) human delivered control signals, 2) reward-shaping feedback signals, and 3) simultaneous control and feedback. Our results suggest that subjects provide less feedback when simultaneously delivering feedback and control signals and that control signal quality is not significantly diminished. Our data suggest that subjects may also modify when and how they provide feedback. Through algorithmic development and tuning informed by this study, we expect semi-autonomous actions of robotic agents can be better shaped by human feedback, allowing for seamless collaboration and improved performance in difficult interactive domains.

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A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation. (arXiv:1703.04071v1 [cs.CV] CROSS LISTED)

Recently, DNN model compression based on network architecture design, e.g., SqueezeNet, attracted a lot attention. No accuracy drop on image classification is observed on these extremely compact networks, compared to well-known models. An emerging question, however, is whether these model compression techniques hurt DNN's learning ability other than classifying images on a single dataset. Our preliminary experiment shows that these compression methods could degrade domain adaptation (DA) ability, though the classification performance is preserved. Therefore, we propose a new compact network architecture and unsupervised DA method in this paper. The DNN is built on a new basic module Conv-M which provides more diverse feature extractors without significantly increasing parameters. The unified framework of our DA method will simultaneously learn invariance across domains, reduce divergence of feature representations, and adapt label prediction. Our DNN has 4.1M parameters, which is only 6.7% of AlexNet or 59% of GoogLeNet. Experiments show that our DNN obtains GoogLeNet-level accuracy both on classification and DA, and our DA method slightly outperforms previous competitive ones. Put all together, our DA strategy based on our DNN achieves state-of-the-art on sixteen of total eighteen DA tasks on popular Office-31 and Office-Caltech datasets.

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Orioles: Chris Tillman (sore right shoulder) won't start 4th consecutive season opener; Buck Showalter yet to decide who gets gets the nod (ESPN)

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Bob Bury

I am a first time self publisher! How can I get my book to out to people. writerbn. Posts: 3,506. Registered: 05/12/12. Re: $1000-A-Day by B.

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McShay Mock Draft 3.0: Ravens grab Washington WR John Ross at No. 16; \"Wide receiver has become a priority\" - Jamison Hensley (ESPN)

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US Charges Two Russian Spies & Two Hackers For Hacking 500 Million Yahoo Accounts

The 2014 Yahoo hack disclosed late last year that compromised over 500 million Yahoo user accounts was believed to be carried out by a state-sponsored hacking group. Now, two Russian intelligence officers and two criminal hackers have been charged by the US government in connection with the 2014 Yahoo hack that compromised about 500 million Yahoo user accounts, the Department of Justice

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Ravens will release C Jeremy Zuttah Thursday after not being able to trade him - multiple reports; creates $2.392M in cap space (ESPN)

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I have a new follower on Twitter

Anna Puopolo
Host of the Anna Show - CEO/Founder @Kidviewed Daughter of @jpuopolo and @laurapuopolo. Entrepreneur in training an Princess Leia wannabe!
Cambridge, Ontario
https://t.co/KOnVoDFGG7
Following: 4861 - Followers: 2714

March 15, 2017 at 11:48AM via Twitter http://twitter.com/annapuopolo

How One Photo Could Have Hacked Your WhatsApp and Telegram Accounts

Next time when someone sends you a photo of a cute cat or a hot chick on WhatsApp or Telegram then be careful before you click on the image to view — it might hack your account within seconds. A new security vulnerability has recently been patched by two popular end-to-end encrypted messaging services — WhatsApp and Telegram — that could have allowed hackers to completely take over user account

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ISS Daily Summary Report – 3/14/2017

2A Direct Current to Direct Current Converter Unit (DDCU) Trips: Today, all of the DDCUs on the 2A power bus tripped off simultaneously due to a bus undervoltage. This included DDCU 2A, DDCU LA2A, DDCU N2P2A, and DDCU N32A. The trip of DDCU 2A removed power from the 2A Pump Flow Control Subassembly (PFCS). Loads from the other DDCUs were picked up by parallel DDCUs and did not unpower hardware. Ground controllers stopped the 2A battery capacity test that was in progress and reactivated DDCU 2A and the 2A PFCS. Cooling has been re-established to the 2A Batteries. There were no thermal clock exceedances. Ground teams are reconfiguring the EPS system back to nominal and investigating the cause, suspecting that an unexpected power load during the battery capacity test triggered the bus undervoltage. Mobile Servicing System (MSS) Operations: Overnight, Robotics Ground Controllers stowed the Materials International Space Station Experiment (MISSE) payload inside the SpX-10 Dragon trunk. The Robotics Ground Controllers then configured the Space Station Remote Manipulator System (SSRMS) and the Special Purpose Dexterous Manipulator (SPDM) for the start of the Robotic Refueling Mission (RRM) payload stow in the Dragon trunk later tonight. MSS performance was nominal. Rodent Research-4: Today, the crew performed the last day of operations for Rodent Research-4. In coordination with ground specialists, the crew collected samples and stowed them in Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI) for return on SpX-10. The Tissue Regeneration-Bone Defect (RR-4) investigation studies what prevents vertebrates such as rodents and humans from regrowing lost bone and tissue, and how the microgravity extraterrestrial condition impacts the process. Results could lead to tissue regeneration efforts in space and a better understanding of limitations of limb regrowth at wound sites. Water Sampling: Today the crew performed nominal Environmental Health System (EHS) Potable Water Dispenser (PWD) sampling for in-flight and post-flight analysis. In-flight Total Organic Carbon Analyzer (TOCA) samples were also performed. In coordination with the water sampling, the crew initiated the ESA sponsored Aquapad (Paper Analytical Device) technological demonstration and sampling using the Microbial Monitoring System (MMS) portion of the WMS experiment. By using the same water collected for the EHS sample, ground teams can evaluate the capabilities of the new hardware. For the MMS analysis, the crew configured the hardware to sample a low and high DNA concentration sample using the Razor Polymerase Chain Reaction (PCR) Microbial Monitoring System. The WMS is a set of hardware that monitors microbes, silica and organic material in the water supply on the ISS. The hardware ensures crew members can test and monitor the safety of their water supplies on future space missions, especially on long-duration missions to Mars, asteroids or other destinations where Earth-based testing would be difficult or impossible. Aquapad is a new approach developed by France’s CNES space agency: paper impregnated with powdered growth medium creates a 3D petri dish. When water is added, the microbes form colored spots revealing their locations. Using a tablet computer application the crew will photograph the dots to calculate precisely how many bacteria are present. Advanced Plant Experiments (APEX)-04: The crew checked the status of the APEX-04 Petri Plate for condensation, then photographed the plate on the Advanced Biology Research Facility (ABRS) photogrid. The LMM Biophysics plate that was in the Light Microscopy Module (LMM) facility was inserted into the Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI) and APEX-04 petri plate was installed. The APEX-04 (Epigenetic change in Arabidopsis thaliana in response to spaceflight – differential cytosine DNA methylation of plants on the ISS) experiment investigates how spaceflight can affect an organism on a molecular level without altering its outward appearance. Previous research has demonstrated that large numbers of plant genes are expressed differently in space compared to plants on Earth, which can alter how plants grow. This investigation studies the entire genome of thale cress plants grown in space, creating maps of spaceflight-specific changes in certain groups of genes. Results give new insight into plants’ molecular responses to spaceflight, which benefits efforts to grow plants in space for food and oxygen. Local Bus (LB) Mech Bus Checkout – Yesterday, in preparation for the Enhanced Processor Integrated Communications (EPIC) EXT Multiplexer/DeMultiplexer (MDM) upgrade, ground controllers performed a checkout of the LB-MECH-P1, P2, S1, and S2 buses. This checkout serves as a baseline assessment of the health of the buses before the new EPIC EXT MDMs are installed. There were no issues with the buses. When the Payload Attach System (PAS) 3 Umbilical Mechanism Assembly (UMA) was powered in the checkout, the mated switch did not show mated. This is thought to be caused by an already-known issue in which the UMA springs backdrove the active connector enough to lose the mated indication from the switch but did not demate the connector. External Stowage Platform (ESP)-3, which is on PAS 3, is receiving power nominally. Today’s Planned Activities All activities were completed unless otherwise noted. Environmental Health System (EHS) Potable Water Dispenser (PWD) Sample Collect Photo T/V (P/TV) Advanced Resistive Exercise Device (ARED) Exercise Video Setup ASEPTIC. Glovebox-C Hardware Power On ALGOMETRIA. Measurement Prep & Ops in the strain-gauge and thermal algometry modes Fluids Integrated Rack Rack Doors Open ASEPTIC. Taking samples from Glovebox-C surface after sterilization. Air Sample Collection Prep. H/W set up. Pump Activation. APEX-04 Petri Plate Check Verification of ИП-1 Flow Sensor Position Total Organic Carbon Analyzer (TOCA) Potable Water Dispenser (PWD) Sample Analysis Medical Kits Inventory Check Light Microscopy Module APEX-04 change out of Petri Plates Microbial Monitoring System Hardware Gather DAN. Experiment Ops. Microbial Monitoring System MWA Preparation Urine Processor Assembly (UPA) EDV Transfer Hose Remove and Replace (R&R) Fluids Integrated Rack Rack Doors Close Photo/TV Camcorder Setup Verification Rodent Research Node 2 Camcorder Video Setup Rodent Research 4 Pink Habitat Transfer Coliform Water Processing Kurs-P Cable Reconnection from DC1 AFD to MRM2 AFD and photography of the connection location Aquapad Double Water Sampling Rodent Research 4 Green Habitat Transfer ASEPTIC. Monitoring Automatic Pump Power off OTKLIK. Hardware Monitoring […]

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