2 Valses

Naxos Search. Search key: anonymous valses (Top 10 results below) [more results] ... TN - Anonymous - 2 Valses (TM).jpg ...

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Crime Stoppers of Halton

A citizen and media co-operative organized to involve the public in the fight against crime, giving the opportunity to anonymously supply information ...

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Anonymous Woman by Patty Carroll

Description: Anonymous Women is about becoming the dwelling itself: experiencing joys and terrors of domesticity; challenging the idea of home and ...

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Anonymous user 480107

Name, Anonymous user 480107. User since, August 21, 2016. Number of add-ons developed, 0 add-ons. Average rating of developer's add-ons, Not ...

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Alcoholics Anonymous plays important role in society

Alcoholics Anonymous, which is most often just called the Big Book, was first published in 1939. Since then it has sold millions of copies throughout ...

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How can I change front-end form for anonymous

I have a forum on my website, where anonymous can write a new post like below. http://ift.tt/2drr3nh. Even though I want to hide ...

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Anonymous ECC-Authentication and Intrusion Detection Based on Execution Tracing for Mobile ...

In this paper, we propose a new security scheme based on two techniques: anonymous authentication and intrusion detection. In the first one, we ...

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I have a new follower on Twitter

Grant Maloy Smith
Singer-songwriter of American Roots music. Voting member of the Grammys®, The CMA, AMA & BMI recording artist. New record coming 4/17!
Rhode Island, USA
http://t.co/pUFgNG8vcZ
Following: 44977 - Followers: 104440

September 24, 2016 at 06:27AM via Twitter http://twitter.com/GrantMaloySmith

First Columbus District Convention

Date/Time Date(s) - Dec 30, 2016 - Jan 01, 2017. Location Holiday Inn Columbus-Worthington. Categories. Area convention. The First Columbus Ohio ...

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Hacker Who Helped ISIS to Build 'Hit List' Of US Military Personnel Jailed for 20 Years

A computer hacker who allegedly helped the terrorist organization ISIS by handing over data for 1,351 US government and military personnel has been sentenced to 20 years in a U.S. prison. Ardit Ferizi, aka Th3Dir3ctorY, from Kosovo was sentenced in federal court in Alexandria, for "providing material support to the Islamic State of Iraq and the Levant (ISIL) and accessing a protected computer

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Google WiFi Router — Combine Multiple Routers to Boost WiFi Signal

Can you rely on a single loudspeaker in your living room for great sound throughout your home? Nah! In the same way, you can not expect a single WiFi router to provide stable range throughout your home. To solve this issue, Google will soon power your home's wireless internet network with its own-brand new WiFi router called Google WiFi, according to a new report. <!-- adsense --> Google is

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Harvest Moon Eclipse

A Harvest Moon rises over Sesimbra Castle south of Lisbon in this impressive series of telephoto exposures. Captured at its full phase, the golden Moon was also gliding through the Earth's more diffuse outer shadow during September's penumbral lunar eclipse. The eclipse shading is subtle compared to a total lunar eclipse. Still, the penumbral shadow does darken the Moon's upper limb, the pale shadow receding as the Moon climbs into Portugal's evening sky. In this eclipse timelapse the effect of sunlight and earthshadow on the Moon looks remarkably like the coloring of light and shadow along the illuminated castle walls. via NASA http://ift.tt/2dfYw5e

can i publish a book as anonymous or

hi, i was planning to publish a book but it is of a very personal nature and i would be uncomfortable using my real name..is it acceptable to make up a ...

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Orioles trail Tigers for the final AL wild-card spot by 0.5 game after defeating Diamondbacks 3-2 in 12 innings (ESPN)

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Joseph M Erhardt

can i publish a book as anonymous or change my name and get royalties to me. Posted: Sep 23, 2016 4:29 PM. Click to report abuse... Click to reply to ...

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Apple Weakens iOS 10 Backup Encryption; Now Can Be Cracked 2,500 Times Faster

After the iPhone encryption battle between Apple and the FBI, Apple was inspired to work toward making an unhackable future iPhones by implementing stronger security measures even the company can't hack. Even at that point the company hired one of the key developers of Signal — one of the world's most secure, encrypted messaging apps — its core security team to achieve this goal. But it

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anonymous 11

Tinkercad user anonymous 11. ... 3D printed, 0. anonymous 11's Things. the rocket that goes around earth. anonymous 11 12 minutes ago. Public ...

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Anonymous 4 – 3 Decades of Anonymous 4: 1986 – 2016 (Bonus Track Version)

Anonymous 4 – 3 Decades of Anonymous 4: 1986 – 2016 (Bonus Track Version). By Thom Kennon. 23 songs. Play on Spotify. 1. GloriaAnonymous ...

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Ravens Video: Justin Tucker raps about fried chicken, uses drumstick as mic in commercial for regional convenience store (ESPN)

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ISS Daily Summary Report – 09/22/2016

Story Time From Space: FE-6 completed the video recording that was started yesterday that demonstrates how a balance scale can be used to exhibit balance in microgravity.  Story Time From Space combines science literacy outreach with simple demonstrations recorded aboard the ISS. Crew members read five science, technology, engineering and mathematics-related children’s books in orbit, and complete simple science concept experiments. Crew members videotape themselves reading the books and completing demonstrations. Video and data collected during the demonstrations are downlinked to the ground and posted in a video library with accompanying educational materials.  Water Monitoring Suite – Microbial Monitoring System (WMS-MMS): FE-6 performed two MMS runs today.  Both runs were obtained from the Total Organic Carbon Analyzer (TOCA) water analysis sample bag, and analysis will be performed on ISS unfiltered water.  The first utilized a low DNA concentration pouch, the second the high DNA concentration pouch. 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.  Waste and Hygiene Compartment (WHC) Urine Hydraulic Components Remove & Replace (R&R): The crew performed preventive maintenance to R&R the urine valve block, urine lines, urine pressure sensors and WHC flush water tank empty pressure sensor. Ocular Ultrasounds:  FE-5 and FE-6 assisted each other in performing routine medical eye imaging ultrasound.  The ultrasound images will be used to identify changes in globe morphology and document optic nerve sheath diameter, optic nerve sheath tortuosity, globe axial measurements, and choroidal engorgement. Today’s Planned Activities All activities were completed unless otherwise noted. In Flight Maintenance Starboard Crew Quarters Light Installation JAXA Video Taking Part 6 Habitability Human Factors Directed Observations EHS Carbon Dioxide Monitor Data Download SPLANKH. SPLANHOGRAF Setup, Initiate EGEG Recording SEISMOPROGNOZ. Downlink data from Control and Data Acquisition Module (МКСД) Hard Drive (start) Story Time from Space Balance Demonstration Story Time From Space  Historical Photo In-Flight Maintenance (IFM) Waste and Hygiene Compartment (WHC) Tool Gather Progress 432 [AO] Stowage Ops with IMS Support Microbial Monitoring System MWA Preparation Waste and Hygiene Compartment (WHC) Water Hydraulics Components R&R Environmental Health System (EHS) Total Organic Carbon Analyzer (TOCA) Water Recovery System (WRS) Sample Analysis Microbial Monitoring System Sample Setup Environmental Health System (EHS) – Intravehicular Tissue Equivalent Proportional Counter (IV-TEPC) Relocate Increment 49 Safety Video Follow-Up Health Maintenance System (HMS) Food Frequency Questionnaire (FFQ) SPLANKH. Terminate EGEG Recording. Closeout Ops Microbial Monitoring System Sample SEISMOPROGNOZ. Download data from Control and Data Acquisition Module (МКСД) HDD (end) and start backup В3 Fan Screen Cleaning in MRM2 Ultrasound 2 HRF Rack 1 Power On Regenerative Environmental Control and Life Support System (RGN) WSTA Fill OTKLIK. Hardware Monitoring Verification of ИП-1 Flow Sensor Position Health Maintenance System (HMS) Ultrasound 2 Scan СОЖ maintenance IMS Delta File Prep Ultrasound 2 Guided Data Export Health Maintenance System (HMS) Ultrasound 2 Post Exam Microbial Monitoring System Sample Setup Photo/TV Camcorder Setup Verification Public Affairs Office (PAO) High Definition (HD) Config LAB Setup Public Affairs Office (PAO) Event in High Definition (HD) – Lab Regenerative Environmental Control and Life Support System (RGN) WSTA Fill Environmental Health System (EHS) Total Organic Carbon Analyzer (TOCA) Sample Data Record Microbial Monitoring System Sample Flight Director/ISS CREW CONFERENCE Microbial Monitoring System Data Transfer  Completed Task List Items EVA Tool Stow Part 4 CO2 Monitor Data Download Capillary Flow Experiment (CFE) Procedure Review MWA Preparations for CFE Experiment Ground Activities All activities were completed otherwise noted. Data bus characterization Test (LB_PMCU_2 and LB_PMCU_4) Battery 2B1 Capacity Test Three-Day Look Ahead: Friday, 09/23: Plant RNA, Cubesat Deployer Removal from MPEP, HRF Resupply, Lab MCA Pumpout Saturday, 09/24: Weekly Housekeeping, Crew Off Duty, Finemotor test Sunday, 09/25: Crew Off Duty  QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off [СКВ] 2 – SM Air Conditioner System (“SKV2”) On Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Idle Major Constituent Analyzer (MCA) Node 3 Operate Oxygen Generation Assembly (OGA) Standby Urine Processing Assembly (UPA) Process Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

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Critical DoS Flaw found in OpenSSL — How It Works

The OpenSSL Foundation has patched over a dozen vulnerabilities in its cryptographic code library, including a high severity bug that can be exploited for denial-of-service (DoS) attacks. OpenSSL is a widely used open-source cryptographic library that provides encrypted Internet connections using Secure Sockets Layer (SSL) or Transport Layer Security (TLS) for the majority of websites, as well

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[FD] 3GP Player 4.7.0 - DLL Hijacking Vulnerability

[FD] DllHijackAuditor 3.5 - Stack Buffer Overflow Vulnerability

Document Title: =============== DllHijackAuditor 3.5 - Stack Buffer Overflow Vulnerability References (Source): ==================== http://ift.tt/2cGUuiQ Release Date: ============= 2016-09-21 Vulnerability Laboratory ID (VL-ID): ==================================== 1954 Common Vulnerability Scoring System: ==================================== 6.3 Product & Service Introduction: =============================== DLL Hijack Auditor is the smart tool to Audit against the Dll Hijacking Vulnerability in any Windows application. This is one of the critical security issue affecting almost all Windows systems. Though most of the apps have been fixed, but still many Windows applications are susceptible to this vulnerability which can allow any attacker to completely take over the system. DllHijackAuditor helps in discovering all such Vulnerable Dlls in a Windows application which otherwise can lead to successful exploitation resulting in total compromise of the system. (Copy of the Homepage: http://ift.tt/1nS1wSd) Abstract Advisory Information: ============================== An independent vulnerability laboratory researcher discovered a stack buffer overflow vulnerability in the DllHijackAuditor v3.5 software. Vulnerability Disclosure Timeline: ================================== 2016-09-21: Public Disclosure (Vulnerability Laboratory) Discovery Status: ================= Published Affected Product(s): ==================== SecurityXploded Product: DllHijackAuditor - Software 3.5 Exploitation Technique: ======================= Local Severity Level: =============== High Technical Details & Description: ================================ A local stack buffer overflow vulnerability has been discovered in the official DllHijackAuditor v3.5 software. The overflow vulnerability allows remote attackers to take-over the process by overwrite of the active registers. The stack buffer overflow vulnerability is located in the `Specify Extension Entry` module of the software. Local attackers are able to include unicode as malicious payload to crash software via stack overflow. Thus allows the local attacker to overwrite for example the eip register to take control of the vulnerable software process. The security risk of the issue is estimated as high with a cvss (common vulnerability scoring system) count of 6.1. Exploitation of the vulnerability requires a low privileged system user account or restricted access without user interaction. Successful exploitation of the vulnerability results in computer system manipulation and compromise of the computer system. Vulnerable Input(s): [+] Specify Extension - (Entry) Proof of Concept (PoC): ======================= A local stack overflow vulnerability can be exploited by local attackers without user interaction and with privileged system user account. For security demonstration or to reproduce the sofwtare vulnerability follow the provided information and steps below to continue. Manual steps to reproduce the vulnerability ... 1. Launch the DllHijackAuditors.exe software process 2. Run the code in perl and a file format (.txt) will create 3. Copy the AAAAAAAAA+... string from DllHijackAuditor.txt to clipboard 4. Paste it to the input Specify Extension AAAAAAAAA+... string and click `Start Audit` to process 5. Software crash permanently by a stack overflow 6. Successfully reproduce of the local stack buffer overflow vulnerability! PoC: Exploit Code (Perl) #!/usr/bin/perl my $Buff = "x41" x 3000; open(MYFILE,'>>DllHijackAuditor.txt'); print MYFILE $Buff; close(MYFILE); print " POC Created by ZwXn";

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Leaked NSA Hacking Tools Were 'Mistakenly' Left By An Agent On A Remote Server

If you are a hacker, you might have enjoyed the NSA's private zero-day exploits, malware and hacking tools that were leaked last month. But the question is: How these hacking tools ended up into the hands of hackers? It has been found that the NSA itself was not directly hacked, but a former NSA employee carelessly left those hacking tools on a remote server three years ago after an

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Yahoo Confirms 500 Million Accounts Were Hacked by 'State Sponsored' Hackers

500 million accounts — that's half a Billion users! That's how many Yahoo accounts were compromised in a massive data breach dating back to 2014 by what was believed to be a "state sponsored" hacking group. <!-- adsense --> Over a month ago, a hacker was found to be selling login information related to 200 million Yahoo accounts on the Dark Web, although Yahoo acknowledged that the breach was

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How Does Crimestoppers Keep You Anonymous?

Sangamon and Menard County Crimestoppers Director Mike Badger says he gets more than 1000 tips every year, with more than 100 leading to ...

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Sunset at Edmontonhenge

On September 18, the setting Sun illuminated both sides of the steep brick and steel canyon otherwise known as Jasper Avenue in downtown Edmonton, Alberta, Canada, planet Earth. The Stonehenge-like alignment is captured from the middle of the road in this daring snapshot. In Edmonton streets are laid out on a grid almost oriented along the cardinal directions, so aligned Edmonton sunsets (and sunrises) occur along the nearly east-west streets twice a year, close to the Equinox. In fact, at today's Equinox, the Sun crosses the celestial equator at 1421 UT and on this day the Sun will rise due east and set due west, bringing approximately equal hours of day and night to denizens of planet Earth. The September Equinox marks the astronomical beginning of Fall in the north and Spring in the southern hemisphere. via NASA http://ift.tt/2cTwMRD

Orioles fall one-half game behind Tigers for 2nd wild card; swept in 4-game series by Red Sox after 5-3 loss (ESPN)

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I have a new follower on Twitter

Max Stewart
Director of Software Engineering at @cybLdn. #startup #leanstartup #programming #nodejs #java #reactjs #angularjs
London
https://t.co/oTQSZ0mWry
Following: 18222 - Followers: 20300

September 22, 2016 at 10:44PM via Twitter http://twitter.com/superafroman

Deep-Learned Collision Avoidance Policy for Distributed Multi-Agent Navigation. (arXiv:1609.06838v1 [cs.AI])

High-speed, low-latency obstacle avoidance that is insensitive to sensor noise is essential for enabling multiple decentralized robots to function reliably in cluttered and dynamic environments. While other distributed multi-agent collision avoidance systems exist, these systems require online geometric optimization where tedious parameter tuning and perfect sensing are necessary.

We present a novel end-to-end framework to generate reactive collision avoidance policy for efficient distributed multi-agent navigation. Our method formulates an agent's navigation strategy as a deep neural network mapping from the observed noisy sensor measurements to the agent's steering commands in terms of movement velocity. We train the network on a large number of frames of collision avoidance data collected by repeatedly running a multi-agent simulator with different parameter settings. We validate the learned deep neural network policy in a set of simulated scenarios with noisy measurements and demonstrate that our method is able to generate a robust navigation strategy that is insensitive to imperfect sensing and works reliably in all situations. We also show that our method can be well generalized to scenarios that do not appear in our training data, including scenes with static obstacles and agents with different shapes. A video is available at https://youtu.be/uMcdMmcR67A.

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The Digital Synaptic Neural Substrate: Size and Quality Matters. (arXiv:1609.06953v1 [cs.AI])

We investigate the 'Digital Synaptic Neural Substrate' (DSNS) computational creativity approach further with respect to the size and quality of images that can be used to seed the process. In previous work we demonstrated how combining photographs of people and sequences taken from chess games between weak players can be used to generate chess problems or puzzles of higher aesthetic quality, on average, compared to alternative approaches. In this work we show experimentally that using larger images as opposed to smaller ones improves the output quality even further. The same is also true for using clearer or less corrupted images. The reasons why these things influence the DSNS process is presently not well-understood and debatable but the findings are nevertheless immediately applicable for obtaining better results.

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Semiring Programming: A Framework for Search, Inference and Learning. (arXiv:1609.06954v1 [cs.AI])

To solve hard problems, AI relies on a variety of disciplines such as logic, probabilistic reasoning, machine learning and mathematical programming. Although it is widely accepted that solving real-world problems requires an integration amongst these, contemporary representation methodologies offer little support for this.

In an attempt to alleviate this situation, we introduce a new declarative programming framework that provides abstractions of well-known problems such as SAT, Bayesian inference, generative models, and convex optimization. The semantics of programs is defined in terms of first-order structures with semiring labels, which allows us to freely combine and integrate problems from different AI disciplines.

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NdFluents: A Multi-dimensional Contexts Ontology. (arXiv:1609.07102v1 [cs.AI])

Annotating semantic data with metadata is becoming more and more important to provide information about the statements being asserted. While initial solutions proposed a data model to represent a specific dimension of meta-information (such as time or provenance), the need for a general annotation framework which allows representing different context dimensions is needed. In this paper, we extend the 4dFluents ontology by Welty and Fikes---on associating temporal validity to statements---to any dimension of context, and discuss possible issues that multidimensional context representations have to face and how we address them.

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Social Network Processes in the Isabelle and Coq Theorem Proving Communities. (arXiv:1609.07127v1 [cs.SI])

We identify the main actors in the Isabelle and Coq communities and describe how they affect and influence their peers. This work explores selected foundations of social networking analysis that we expect to be useful in the context of the ProofPeer project, which is developing a new model for interactive theorem proving based on collaboration and social interactions.

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Focused Model-Learning and Planning for Non-Gaussian Continuous State-Action Systems. (arXiv:1607.07762v2 [cs.AI] UPDATED)

We introduce a framework for model learning and planning in stochastic domains with continuous state and action spaces and non-Gaussian transition models. It is efficient because (1) local models are estimated only when the planner requires them; (2) the planner focuses on the most relevant states to the current planning problem; and (3) the planner focuses on the most informative and/or high-value actions. Our theoretical analysis shows the validity and asymptotic optimality of the proposed approach. Empirically, we demonstrate the effectiveness of our algorithm on a simulated multi-modal pushing problem.

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Bi-directional Attention with Agreement for Dependency Parsing. (arXiv:1608.02076v2 [cs.CL] UPDATED)

We develop a novel bi-directional attention model for dependency parsing, which learns to agree on headword predictions from the forward and backward parsing directions. The parsing procedure for each direction is formulated as sequentially querying the memory component that stores continuous headword embeddings. The proposed parser makes use of {\it soft} headword embeddings, allowing the model to implicitly capture high-order parsing history without dramatically increasing the computational complexity. We conduct experiments on English, Chinese, and 12 other languages from the CoNLL 2006 shared task, showing that the proposed model achieves state-of-the-art unlabeled attachment scores on 6 languages.

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Empirically Grounded Agent-Based Models of Innovation Diffusion: A Critical Review. (arXiv:1608.08517v3 [cs.SI] UPDATED)

Innovation diffusion has been studied extensively in a variety of disciplines, including sociology, economics, marketing, ecology, and computer science. Traditional literature on innovation diffusion has been dominated by models of aggregate behavior and trends. However, the agent-based modeling (ABM) paradigm is gaining popularity as it captures agent heterogeneity and enables fine-grained modeling of interactions mediated by social and geographic networks. While most ABM work on innovation diffusion is theoretical, empirically grounded models are increasingly important, particularly in guiding policy decisions. We present a critical review of empirically grounded agent-based models of innovation diffusion, developing a categorization of this research based on types of agent models as well as applications. By connecting the modeling methodologies in the fields of information and innovation diffusion, we suggest that the maximum likelihood estimation framework widely used in the former is a promising paradigm for calibration of agent-based models for innovation diffusion. Although many advances have been made to standardize ABM methodology, we identify four major issues in model calibration and validation, and suggest potential solutions. Finally, we discuss open problems that are critical for the future development of empirically grounded agent-based models of innovation diffusion that enable reliable decision support for stakeholders.

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Change Existing Registration from Anonymous to User

When an existing registration that has been assigned to an anonymous user (i.e. by providing an email address only), and when changing the ...

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Ravens: LB Elvis Dumervil (foot) says he hopes to play Sunday vs. Jaguars; "it's heading in the right direction" (ESPN)

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iPhone 7 Jailbreak Has Already Been Achieved In Just 24 Hours!

It has only been a few days since the launch of Apple's brand new iPhone 7 and iPhone 7 Plus, but it appears that the new iPhone has already been jailbroken. That didn't take long. Right? <!-- adsense --> Security researcher and well-known hacker Luca Tedesco shared an image of his jailbroken smartphone on his Twitter account to show off the world that the new iPhone 7 has been jailbroken.

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Ravens: LB Elvis Dumervil (foot) practiced for 2nd straight day Thu.; LT Ronnie Stanley (foot) back after missing 1 day (ESPN)

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Anonymous user b30463

Name, Anonymous user b30463. User since, June 18, 2016. Number of add-ons developed, 1 theme. Average rating of developer's add-ons, Not yet ...

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ISS Daily Summary Report – 09/21/2016

Multi-Purpose Small Payload Rack (MSPR) Combustion Chamber Adapter Plate Attachment: FE-5 installed the Combustion Chamber adapter plate in the MSPR Work Volume.  Next week, the crew will be installing and with ground support, initiating the Group Combustion experiment. The Group Combustion investigation tests a theory that fuel sprays change from partial to group combustion as flames spread across a cloud of droplets. In the Multi-purpose Small Payload Rack in the Kibo module, droplets of decane, a component of gasoline or kerosene, are arranged randomly on thin-fiber lattice points, and the flame and droplet positions and temperature distribution are measured as the flame spreads. Microgravity blocks convection, which on Earth would quickly disperse the droplets and combustion products before such measurements could be made. Personal Carbon Dioxide (CO2) Monitor: FE-6 donned four Personal CO2 Monitors, wearing them for several hours attached to various locations on the crew’s clothes.  The crewmember then doffed the monitors, downloaded the data, powered off and stowed the monitors.  The Personal CO2 Monitor demonstrates a new capability to continuously monitor the astronauts’ immediate surroundings on the ISS.  All human spacecraft must be designed with environmental control systems that remove CO2 from the air that their crews breathe, but the space environment can still lead to “pockets” of CO2 that are difficult to detect and remove. The Personal CO2 Monitor demonstrates a system capable of unobtrusively collecting and downlinking individual crew members’ CO2 exposure for weeks to months.  The Personal CO2 Monitor also demonstrates Modular Wearable Architecture Base Board, allowing rapid certification of future wearable devices.  Story Time From Space: FE-6 was scheduled to record a demonstration using a balance scale to show how a balance can be used to compare mass in a free-fall/microgravity environment.  The setup of the activity ran longer than expected, and the crew will perform the actual experiment in the morning.  Story Time From Space combines science literacy outreach with simple demonstrations recorded aboard the ISS. Crew members read five science, technology, engineering and mathematics-related children’s books in orbit, and complete simple science concept experiments. Crew members videotape themselves reading the books and completing demonstrations. Video and data collected during the demonstrations are downlinked to the ground and posted in a video library with accompanying educational materials. Eye Exams:  FE-5 and FE-6 assisted each other in performing routine eye exams using Optical Coherence Tomography (OCT) and fundoscopy hardware. OCT is used to measure retinal thickness, volume, and retinal nerve fiber layer, and the fundoscope is used to obtain images of the retinal surface.   Today’s Planned Activities All activities are on schedule unless otherwise noted. In Flight Maintenance Starboard Crew Quarters Light Installation JAXA Video Taking Part 6 JEM OA-5 Trash Preparation Habitability Human Factors Directed Observations – Subject EHS Carbon Dioxide Monitor Data Download Biochemical urine test Regenegation of Micropurification unit (БМП) Ф2 cartridge (begin) Manufacturing Device Print Removal, Clean and Stow Multi Omics FOS Preparation Meteor Hard Drive Swapout PILOT-T. Preparation for the experiment Multi-purpose Small Payload Rack (MSPR) Combustion Chamber Adapter Plate Attachment. PILOT-T. Experiment Ops. Manufacturing Device Velcro Attach Environmental Health System (EHS) – Coliform Water Sample Analysis Crew Arrival Prep PILOT-Т. Closeout Health Maintenance System (HMS) OCT Setup Filling ЕДВ (KOВ) for Elektron Story Time from Space Balance Demonstration Story Time From Space  Historical Photo Clean Bench (CB) Valve Checkout (Deferred) СОЖ maintenance Nitrogen/Oxygen Recharge System O2 Repress Part 1 Health Maintenance System (HMS) – OCT Exam Cleaning of ЦВ1 circulation fan mesh screen Health Maintenance System (HMS) OCT Stow Personal CO2 Monitor Crew Survey Nitrogen/Oxygen Recharge System O2 Repress Part 2 Health Maintenance System (HMS) Eye Exam – Fundoscope SPLANH. Preparation for experiment Health Maintenance System (HMS) CMO – Fundoscope Health Maintenance System (HMS) Fundoscope Tear Down and Stow Completed Task List Items Node 1 Dragon Unpack EVA Tool Stow Part 4 (Active) Ground Activities All activities are on schedule unless otherwise noted. PCA Repress from NORS O2 Tank BEAM SSC software update TRRJ Survey  Three-Day Look Ahead: Thursday, 09/22: Ultrasound Scan, Water Hydraulics Components R&R, MMS sample, Increment 48 Safety Video Follow-Up Friday, 09/23: Plant RNA, Cubesat Deployer Removal from MPEP, HRF Resupply, Lab MCA Pumpdown Saturday, 09/24: Weekly Housekeeping, Crew Off Duty QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off [СКВ] 2 – SM Air Conditioner System (“SKV2”) On Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Idle Major Constituent Analyzer (MCA) Node 3 Operate Oxygen Generation Assembly (OGA) Standby Urine Processing Assembly (UPA) Standby Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

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Beware — Someone is dropping Malware-infected USB Sticks into People's Letterbox

Hey! Wait! Wait! Wait! Don't plug in that USB stick into your laptop. It could infect your computer with malware and viruses. Australia's Victoria Police Force has issued a warning regarding unmarked USB flash drives containing harmful malware being dropped inside random people's letterboxes in the Melbourne suburb of Pakenham. It seems to one of the latest tactics of cyber criminals to

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Anonymous worker Free Vector

Anonymous worker. Download thousands of free vectors on Freepik, the finder with more than a million free graphic resources.

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Russian Media Watchdog May Ban Anonymous Wi-Fi Access

Roskomnadzor subsequently opened administrative cases for unlicensed entrepreneurial activity against operators offering anonymous access and ...

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[FD] SEC Consult SA-20160922-0 :: Potential backdoor access through multiple vulnerabilities in Kerio Control Unified Threat Management

SEC Consult has also released a blog post describing the attack scenarios of the vulnerabilities within this advisory in detail and a video which shows the remote attack. Exploit code has been developed as well but will not be released for now. Blog: http://ift.tt/2dlqCuw Video: https://www.youtube.com/watch?v=y_OWz25sHMI SEC Consult Vulnerability Lab Security Advisory < 20160922-0 > ======================================================================= title: Potential backdoor access through multiple vulnerabilities product: Kerio Control Unified Threat Management vulnerable version: <9.1.3, verified in version 9.1.0 build 1087 and 9.1.1 build 1324 fixed version: 9.1.3 (partially fixed, see vendor statement below) CVE number: - impact: critical homepage: http://www.kerio.com/ found: 2016-08-24 by: R. Freingruber (Office Vienna) R. Tavakoli (Office Vienna) SEC Consult Vulnerability Lab An integrated part of SEC Consult Bangkok - Berlin - Linz - Montreal - Moscow Singapore - Vienna (HQ) - Vilnius - Zurich http://ift.tt/1mGHMNR ======================================================================= Vendor description:

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Anonymous function with summation of parameters

Anonymous function with summation of parameters. Learn more about @ function, anonymous function.

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Orioles remain 1 game behind Blue Jays for AL's top wild card following 5-1 loss to the Red Sox (ESPN)

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Recognizing Detailed Human Context In-the-Wild from Smartphones and Smartwatches. (arXiv:1609.06354v1 [cs.AI])

We demonstrate that a person's behavioral and environmental context can be automatically recognized by harnessing the sensors built into smartphones and smartwatches. We propose a generic system that can simultaneously recognize many contextual attributes from diverse behavioral domains. By fusing complementary information from different types of sensors our system successfully recognizes fine details of work and leisure activities, body movement, transportation, and more. Health monitoring, clinical intervention, aging care, personal assistance and many more applications will benefit from automatic, frequent and detailed context recognition.

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A Consumer BCI for Automated Music Evaluation Within a Popular On-Demand Music Streaming Service - Taking Listener's Brainwaves to Extremes. (arXiv:1609.06374v1 [cs.AI])

We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener's subjective experience of music into scores that can be used for the automated annotation of music in popular on-demand streaming services. Based on the established -neuroscientifically sound- concepts of brainwave frequency bands, activation asymmetry index and cross-frequency-coupling (CFC), we introduce a Brain Computer Interface (BCI) system that automatically assigns a rating score to the listened song. Our research operated in two distinct stages: i) a generic feature engineering stage, in which features from signal-analytics were ranked and selected based on their ability to associate music induced perturbations in brainwaves with listener's appraisal of music. ii) a personalization stage, during which the efficiency of ex- treme learning machines (ELMs) is exploited so as to translate the derived pat- terns into a listener's score. Encouraging experimental results, from a pragmatic use of the system, are presented.

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A Theory of Interactive Debugging of Knowledge Bases in Monotonic Logics. (arXiv:1609.06375v1 [cs.AI])

A broad variety of knowledge-based applications such as recommender, expert, planning or configuration systems usually operate on the basis of knowledge represented by means of some logical language. Such a logical knowledge base (KB) enables intelligent behavior of such systems by allowing them to automatically reason, answer queries of interest or solve complex real-world problems. Nowadays, where information acquisition comes at low costs and often happens automatically, the applied KBs are continuously growing in terms of size, information content and complexity. These developments foster the emergence of errors in these KBs and thus pose a significant challenge on all people and tools involved in KB evolution, maintenance and application.

If some minimal quality criteria such as logical consistency are not met by some KB, it becomes useless for knowledge-based applications. To guarantee the compliance of KBs with given requirements, (non-interactive) KB debuggers have been proposed. These however often cannot localize all potential faults, suggest too large or incorrect modifications of the faulty KB or suffer from poor scalability due to the inherent complexity of the KB debugging problem.

As a remedy to these issues, based on a well-founded theoretical basis this work proposes complete, sound and optimal methods for the interactive debugging of KBs that suggest the one (minimally invasive) error correction of the faulty KB that yields a repaired KB with exactly the intended semantics. Users, e.g. domain experts, are involved in the debugging process by answering automatically generated queries whether some given statements must or must not hold in the domain that should be modeled by the problematic KB at hand.

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Recognizing Implicit Discourse Relations via Repeated Reading: Neural Networks with Multi-Level Attention. (arXiv:1609.06380v1 [cs.CL])

Recognizing implicit discourse relations is a challenging but important task in the field of Natural Language Processing. For such a complex text processing task, different from previous studies, we argue that it is necessary to repeatedly read the arguments and dynamically exploit the efficient features useful for recognizing discourse relations. To mimic the repeated reading strategy, we propose the neural networks with multi-level attention (NNMA), combining the attention mechanism and external memories to gradually fix the attention on some specific words helpful to judging the discourse relations. Experiments on the PDTB dataset show that our proposed method achieves the state-of-art results. The visualization of the attention weights also illustrates the progress that our model observes the arguments on each level and progressively locates the important words.

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A Logic of Knowing Why. (arXiv:1609.06405v1 [cs.AI])

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.

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Document Image Coding and Clustering for Script Discrimination. (arXiv:1609.06492v1 [cs.CV])

The paper introduces a new method for discrimination of documents given in different scripts. The document is mapped into a uniformly coded text of numerical values. It is derived from the position of the letters in the text line, based on their typographical characteristics. Each code is considered as a gray level. Accordingly, the coded text determines a 1-D image, on which texture analysis by run-length statistics and local binary pattern is performed. It defines feature vectors representing the script content of the document. A modified clustering approach employed on document feature vector groups documents written in the same script. Experimentation performed on two custom oriented databases of historical documents in old Cyrillic, angular and round Glagolitic as well as Antiqua and Fraktur scripts demonstrates the superiority of the proposed method with respect to well-known methods in the state-of-the-art.

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Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks. (arXiv:1609.06666v1 [cs.RO])

This paper proposes a computationally efficient approach to detecting objects natively in 3D point clouds using convolutional neural networks (CNNs). In particular, this is achieved by leveraging a feature-centric voting scheme to implement novel convolutional layers which explicitly exploit the sparsity encountered in the input. To this end we examine the trade-off between accuracy and speed for different architectures and additionally propose to use an L1 penalty on the filter activations to further encourage sparsity in the intermediate representations. To the best of our knowledge, this is the first work to propose sparse convolutional layers and L1 regularisation for efficient large-scale processing of 3D data. We demonstrate the efficacy of our approach on the KITTI object detection benchmark and show that Vote3Deep models with as few as three layers outperform the previous state of the art in both laser and laser-vision based approaches across the board by margins of up to 40% while remaining highly competitive in terms of processing time.

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How Relevant Are Chess Composition Conventions?. (arXiv:1309.3039v2 [cs.AI] UPDATED)

Composition conventions are guidelines used by human composers in composing chess problems. They are particularly significant in composition tournaments. Examples include, not having any check in the first move of the solution and not dressing up the board with unnecessary pieces. Conventions are often associated or even directly conflated with the overall aesthetics or beauty of a composition. Using an existing experimentally-validated computational aesthetics model for three-move mate problems, we analyzed sets of computer-generated compositions adhering to at least 2, 3 and 4 comparable conventions to test if simply conforming to more conventions had a positive effect on their aesthetics, as is generally believed by human composers. We found slight but statistically significant evidence that it does, but only to a point. We also analyzed human judge scores of 145 three-move mate problems composed by humans to see if they had any positive correlation with the computational aesthetic scores of those problems. We found that they did not. These seemingly conflicting findings suggest two main things. First, the right amount of adherence to composition conventions in a composition has a positive effect on its perceived aesthetics. Second, human judges either do not look at the same conventions related to aesthetics in the model used or emphasize others that have less to do with beauty as perceived by the majority of players, even though they may mistakenly consider their judgements beautiful in the traditional, non-esoteric sense. Human judges may also be relying significantly on personal tastes as we found no correlation between their individual scores either.

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Length bias in Encoder Decoder Models and a Case for Global Conditioning. (arXiv:1606.03402v2 [cs.AI] UPDATED)

Encoder-decoder networks are popular for modeling sequences probabilistically in many applications. These models use the power of the Long Short-Term Memory (LSTM) architecture to capture the full dependence among variables, unlike earlier models like CRFs that typically assumed conditional independence among non-adjacent variables. However in practice encoder-decoder models exhibit a bias towards short sequences that surprisingly gets worse with increasing beam size.

In this paper we show that such phenomenon is due to a discrepancy between the full sequence margin and the per-element margin enforced by the locally conditioned training objective of a encoder-decoder model. The discrepancy more adversely impacts long sequences, explaining the bias towards predicting short sequences.

For the case where the predicted sequences come from a closed set, we show that a globally conditioned model alleviates the above problems of encoder-decoder models. From a practical point of view, our proposed model also eliminates the need for a beam-search during inference, which reduces to an efficient dot-product based search in a vector-space.

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anonymous-sums

anonymous-sums. Anonymous sum types http://ift.tt/1ZRRZuaanonymous-sums. Version on this page: 0.4.0.0. LTS Haskell 7.0: 0.4.0.0.

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I have a new follower on Twitter

Lenovo Fan



Following: 1879 - Followers: 850

September 21, 2016 at 07:54PM via Twitter http://twitter.com/LenovoFan1

Narcotics Anonymous in Galapagos

No AA on Isla Santa Cruz but there's a centrally located NA meeting three times a week that's open to all Friends of Bill W. Spanish spoken but English ...

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MLB: Red Sox's magic number down to 8 as they host Orioles, who hold 1 AL wild-card spot; watch live in the ESPN App (ESPN)

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Orioles: Adam Jones says \"it's sad\" when asked about poor attendance (19,422 average) in first two games vs. Red Sox (ESPN)

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Allow anonymous submission to be updated using a secure token

Follow-up to #2801881: Anonymous users edit their submissions identified by email or phone number Problem/Motivation In certain situations ...

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[FD] CVE-2016-5725 - JCraft/JSch Java Secure Channel <= 0.1.53 recursive sftp-get path traversal (client-side, windows)

Ref: http://ift.tt/2dbE9Gh Version: 0.3 Date: Aug 31st, 2016 Tag: jsch recursive sftp get client-side windows path traversal Overview

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[FD] XSS Wordpress W3 Total Cache <= 0.9.4.1

[+] Description: Cross-Site Scripting vulnerability was found on Wordpress W3 Total Cache (w3tc) plugin. [+] Plugin Version tested: <= 0.9.4.1 (latest) [+] Wordpress version tested: 4.0.0 - 4.6.1 (latest)

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Orioles Video: Rookie Trey Mancini hits HR in 2nd career AB Tuesday night and his mom goes crazy with excitement (ESPN)

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News: Icarus: 10 most downloaded papers in 2016

Discover the 10 most popular downloaded papers in 2016* from Icarus’ homepage.

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Warning — You Can't Install Linux On Microsoft Signature Edition PCs from Lenovo

In past few months, Microsoft opened the source code of a lot of its projects, convincing people that the company loves Linux. But a new report shows that Microsoft is not really a big supporter of Linux. Microsoft has banned Linux on some Windows 10 powered Signature Edition PCs, which provides the cleanest Windows experience on the market. <!-- adsense --> Signature Edition PCs are

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ISS Daily Summary Report – 09/20/2016

Japanese Experiment Module Airlock (JEMAL) Repressurization: This morning, FE-5 initiated a repress of the JEMAL then performed a leak check of the airlock.  Later this week, the crew will remove the NRCSD from the airlock.  Water Monitoring Suite – Microbial Monitoring System (WMS – MMS): FE-6 began operations with the MMS subset of the WMS experiment.  The crew reviewed an On-Board Training (OBT) video then 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. Electrostatic Levitation Furnace (ELF) Sample Removal: FE-5 removed a sample from the ELF Experiment Volume and replaced it with a new sample.  Ground controllers will use the new sample to continue the checkout of the software and facility.  The next planned use of the ELF facility is the Group Combustion experiment, currently scheduled for next week. The Group Combustion investigation tests a theory that fuel sprays change from partial to group combustion as flames spread across a cloud of droplets. In the Multi-purpose Small Payload Rack in the Kibo module, droplets of decane, a component of gasoline or kerosene, are arranged randomly on thin-fiber lattice points, and the flame and droplet positions and temperature distribution are measured as the flame spreads. Microgravity blocks convection, which on Earth would quickly disperse the droplets and combustion products before such measurements could be made.  Eli Lilly Hard To Wet Surfaces: FE-6 set up the Hard to Wet Surfaces Sample Module image, injected buffer solutions into the sample vials then mixed all six sample vials inside the Sample Module.  The crew aligned and focused the D2Xs Camera and took manual photos utilizing EarthKAM software on the SSC. Automated photography was then initiated using the D2Xs Camera’s intervalometer. The Hard to Wet Surfaces (Eli Lilly-Hard to Wet Surfaces) investigation studies how certain materials used in the pharmaceutical industry dissolve in water while in microgravity. Results from this investigation could help improve the design of tablets that dissolve in the body to deliver drugs, thereby improving drug design for medicines used in space and on Earth. Cell Biology Experiment Facility (CBEF) Closeout: The crew performed closeout following the Mouse Epigenetics experiment.  FE-5 removed, cleaned, and stowed the Mouse Habitat Unit, Glovebox, and Backup Power units.  CBEF is a JAXA subrack facility located in the Saibo (living cell) Experiment Rack. The CBEF is used in various life science experiments, such as cultivating cells and plants in the Japanese Experiment Module (JEM). The CBEF consists of an incubator and control equipment for control and communications. The incubator unit consists of a microgravity compartment and a 1-G compartment. The 1-G compartment has a centrifuge that can control gravity from 0.1 to 2.0 G during gravity contrast experiments with the microgravity compartment. The CBEF incubator can control temperature, humidity, and carbon dioxide concentration for cultivation of cells and plants.  Today’s Planned Activities All activities are on schedule unless otherwise noted. ВКС Laptops Antivirus software checkout Health Maintenance System (HMS) Vision Test Regeneration of Micropurification unit (БМП) Ф1cartridge (begin) JEM Airlock Press Health Maintenance System (HMS) Vision Questionnaire Health Maintenance System (HMS) Vision Test Microbial Monitoring System On-Board Training Review Laptop vent grills maintenance Microbial Monitoring System Hardware Gather Health Maintenance System (HMS) Vision Questionnaire Microbial Monitoring System MWA Preparation JEM Airlock Leak Check KOSMOKARD. Closeout XF305 Camcorder Setup Electrostatic Levitation Furnace(ELF) Sample Removal Laptop vent grills maintenance Microbial Monitoring System Sample Setup Regenerative Environmental Control and Life Support System (RGN) WSTA Fill Flushing of БВ1, БВ2 connectors of Progress #432 (Aft) Rodnik system Dose Tracker Data Entry Subject Public Affairs Office (PAO) High Definition (HD) Config JEM Setup Microbial Monitoring System Sample PAO Preparation Public Affairs Office (PAO) Event in High Definition (HD) – JEM Mouse Epigenetics Closeout Part2 Microbial Monitoring System Data Transfer Glove Box Closeout 5 Hard To Wet Surfaces Sample Processing ТГК 63P stowage operations with the use of IMS (СИ) Cell Biology Experiment Facility (CBEF) Configuration Change 2 Plug-in Plan Universal Serial Bus Charger Deploy Cell Biology Experiment Facility (CBEF) Backup Power Retrieve Hard To Wet Surfaces Sample Remix. 48 Soyuz Wireless Station Support Computer (SSC) Connect Regenerative Environmental Control and Life Support System (RGN) WSTA Fill Hard To Wet Surfaces Sample Remix. Habitability Walk-through Video – Subject Hard To Wet Surfaces Sample Remix. Delta file prep СОЖ maintenance Hard To Wet Surfaces Sample Remix Set 2 Hard To Wet Surfaces OBT Review Hard To Wet Surfaces Sample Remix. Crew Medical Officer (CMO) On Board Training (OBT) Hard To Wet Surfaces Sample Remix Set 3 Hard To Wet Surfaces Sample Remix Set 4 CONTENT. Experiment Ops URISYS Hardware Setup Hard To Wet Surfaces Image Transfer SPLANKH. Diet Restrictions Reminder Regeneration of Micropurification unit (БМП) Ф1 cartridge (finish) Completed Task List Items Manufacturing Device Print Removal, Clean and Stow Orbital Trash Prep  Ground Activities All activities are on schedule unless otherwise noted. Battery 4B1 Reconditioning Plasma Contactor Unit (PCU) Annual Checkout Three-Day Look Ahead: Wednesday, 09/21: Ocular Health, Personal CO2 Monitor, Clean Bench Valve Checkout, MSPR Combustion Chamber Adapter Plate Thursday, 09/22: Ultrasound Scan, Water Hydraulics Components R&R, MMS sample Friday, 09/23: Plant RNA, Cubesat Deployer Removal from MPEP QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) On [СКВ] 2 – SM Air Conditioner System (“SKV2”) Off Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Idle Major Constituent Analyzer (MCA) Node 3 Operate Oxygen Generation Assembly (OGA) Standby Urine Processing Assembly (UPA) Process Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) […]

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This Wi-Fi Router can read your Emotions; Maybe of your Girl's too!

Are you good at hiding your feelings? No issues, your Wi-Fi router may soon be able to tell how you feel, even if you have a good poker face. A team of researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a device that can measure human inner emotional states using wireless signals. Dubbed EQ-Radio, the new device measures heartbeat, and

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Valse in C major

TN - Anonymous - Valse in C major (Tygodnik Muzyczny).jpg ... Composer, Anonymous. Key, C major. Movements/SectionsMov'ts/Sec's, 2 sections.

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Notification emails for subscribed content types for anonymous users

Hello, on my site I need the ability for anonymous users to subscribe (with their email address) to a content type. Then when new content is created, ...

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Photos On Dark Web Reveal Geo-locations Of 229 Drug Dealers — Here's How

It's a Fact! No matter how smart the criminals are, they always leave some trace behind. Two Harvard students have unmasked around 229 drug and weapon dealers with the help of pictures taken by criminals and used in advertisements placed on dark web markets. Do you know each image contains a range of additional hidden data stored within it that can be a treasure to the investigators fighting

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The Helix Nebula in Infrared

What makes this cosmic eye look so red? Dust. The featured image from the robotic Spitzer Space Telescope shows infrared light from the well-studied Helix Nebula (NGC 7293) a mere 700 light-years away in the constellation of the Water Carrier Aquarius. The two light-year diameter shroud of dust and gas around a central white dwarf has long been considered an excellent example of a planetary nebula, representing the final stages in the evolution of a Sun-like star. But the Spitzer data show the nebula's central star itself is immersed in a surprisingly bright infrared glow. Models suggest the glow is produced by a dust debris disk. Even though the nebular material was ejected from the star many thousands of years ago, the close-in dust could have been generated by collisions in a reservoir of objects analogous to our own solar system's Kuiper Belt or cometary Oort cloud. Had the comet-like bodies formed in the distant planetary system, they would have survived even the dramatic late stages of the star's evolution. via NASA http://ift.tt/2d57iOX

GPM scans hurricane Hermine

On September 6 at 2:06 p.m. EDT (1806 UTC), NASA's Global Precipitation Measurement mission or GPM core observatory satellite flew above Post-Tropical Cyclone Hermine. At that time, Hermine still had maximum sustained winds of about 58 mph (50 knots). The GPM Core Observatory carries two instruments that show the location and intensity of rain and snow, which defines a crucial part of the storm structure - and how it will behave. The GPM Microwave Imager sees through the tops of clouds to observe how much and where precipitation occurs, and the Dual-frequency Precipitation Radar observes precise details of precipitation in 3-dimensions. GPM data is part of the toolbox of satellite data used by forecasters and scientists to understand how storms behave. GPM is a joint mission between NASA and the Japan Aerospace Exploration Agency. Current and future data sets are available with free registration to users from NASA Goddard's Precipitation Processing Center website.

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WFIRST: The Road to L2

Wide-Field Infrared Survey Telescope (WFIRST) is a next-generation space telescope. It will observe the infrared universe from a halo orbit located at the Sun-Earth Lagrange Point two, located beyond the orbit of the Moon. This visualization follows along the trajectory to this halo orbit.

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WFIRST: The Road to L2. The view from above

Wide-Field Infrared Survey Telescope (WFIRST) is a next-generation space telescope. It will observe the infrared universe from a halo orbit located at the Sun-Earth Lagrange Point two, located beyond the orbit of the Moon. This visualization views the trajectory from above the ecliptic plane.

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WFIRST: The Road to L2. Oblique view

Wide-Field Infrared Survey Telescope (WFIRST) is a next-generation space telescope. It will observe the infrared universe from a halo orbit located at the Sun-Earth Lagrange Point two, located beyond the orbit of the Moon. This visualization views the trajectory offset from above the ecliptic plane.

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Orioles fall to Red Sox 5-2, trail Boston by 5 games in AL East; lead Tigers by 1.5 games for final AL wild-card spot (ESPN)

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Mazurek and Anglaise

Movements/SectionsMov'ts/Sec's, 2 pieces. Mazurek in E minor. Con espressione; Anglaise from the overture to Tankred (Rossini's Tancredi?) ...

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Incremental Sampling-based Motion Planners Using Policy Iteration Methods. (arXiv:1609.05960v1 [cs.RO])

Recent progress in randomized motion planners has led to the development of a new class of sampling-based algorithms that provide asymptotic optimality guarantees, notably the RRT* and the PRM* algorithms. Careful analysis reveals that the so-called "rewiring" step in these algorithms can be interpreted as a local policy iteration (PI) step (i.e., a local policy evaluation step followed by a local policy improvement step) so that asymptotically, as the number of samples tend to infinity, both algorithms converge to the optimal path almost surely (with probability 1). Policy iteration, along with value iteration (VI) are common methods for solving dynamic programming (DP) problems. Based on this observation, recently, the RRT$^{\#}$ algorithm has been proposed, which performs, during each iteration, Bellman updates (aka "backups") on those vertices of the graph that have the potential of being part of the optimal path (i.e., the "promising" vertices). The RRT$^{\#}$ algorithm thus utilizes dynamic programming ideas and implements them incrementally on randomly generated graphs to obtain high quality solutions. In this work, and based on this key insight, we explore a different class of dynamic programming algorithms for solving shortest-path problems on random graphs generated by iterative sampling methods. These class of algorithms utilize policy iteration instead of value iteration, and thus are better suited for massive parallelization. Contrary to the RRT* algorithm, the policy improvement during the rewiring step is not performed only locally but rather on a set of vertices that are classified as "promising" during the current iteration. This tends to speed-up the whole process. The resulting algorithm, aptly named Policy Iteration-RRT$^{\#}$ (PI-RRT$^{\#}$) is the first of a new class of DP-inspired algorithms for randomized motion planning that utilize PI methods.

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Macro-optimization of email recommendation response rates harnessing individual activity levels and group affinity trends. (arXiv:1609.05989v1 [cs.AI])

Recommendation emails are among the best ways to re-engage with customers after they have left a website. While on-site recommendation systems focus on finding the most relevant items for a user at the moment (right item), email recommendations add two critical additional dimensions: who to send recommendations to (right person) and when to send them (right time). It is critical that a recommendation email system not send too many emails to too many users in too short of a time-window, as users may unsubscribe from future emails or become desensitized and ignore future emails if they receive too many. Also, email service providers may mark such emails as spam if too many of their users are contacted in a short time-window. Optimizing email recommendation systems such that they can yield a maximum response rate for a minimum number of email sends is thus critical for the long-term performance of such a system. In this paper, we present a novel recommendation email system that not only generates recommendations, but which also leverages a combination of individual user activity data, as well as the behavior of the group to which they belong, in order to determine each user's likelihood to respond to any given set of recommendations within a given time period. In doing this, we have effectively created a meta-recommendation system which recommends sets of recommendations in order to optimize the aggregate response rate of the entire system. The proposed technique has been applied successfully within CareerBuilder's job recommendation email system to generate a 50\% increase in total conversions while also decreasing sent emails by 72%

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Modelling Stock-market Investors as Reinforcement Learning Agents [Correction]. (arXiv:1609.06086v1 [cs.CE])

Decision making in uncertain and risky environments is a prominent area of research. Standard economic theories fail to fully explain human behaviour, while a potentially promising alternative may lie in the direction of Reinforcement Learning (RL) theory. We analyse data for 46 players extracted from a financial market online game and test whether Reinforcement Learning (Q-Learning) could capture these players behaviour using a risk measure based on financial modeling. Moreover we test an earlier hypothesis that players are "na\"ive" (short-sighted). Our results indicate that a simple Reinforcement Learning model which considers only the selling component of the task captures the decision-making process for a subset of players but this is not sufficient to draw any conclusion on the population. We also find that there is not a significant improvement of fitting of the players when using a full RL model against a myopic version, where only immediate reward is valued by the players. This indicates that players, if using a Reinforcement Learning approach, do so na\"ively

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An Efficient Method of Partitioning High Volumes of Multidimensional Data for Parallel Clustering Algorithms. (arXiv:1609.06221v1 [cs.AI])

An optimal data partitioning in parallel & distributed implementation of clustering algorithms is a necessary computation as it ensures independent task completion, fair distribution, less number of affected points and better & faster merging. Though partitioning using Kd Tree is being conventionally used in academia, it suffers from performance drenches and bias (non equal distribution) as dimensionality of data increases and hence is not suitable for practical use in industry where dimensionality can be of order of 100s to 1000s. To address these issues we propose two new partitioning techniques using existing mathematical models & study their feasibility, performance (bias and partitioning speed) & possible variants in choosing initial seeds. First method uses an n dimensional hashed grid based approach which is based on mapping the points in space to a set of cubes which hashes the points. Second method uses a tree of voronoi planes where each plane corresponds to a partition. We found that grid based approach was computationally impractical, while using a tree of voronoi planes (using scalable K-Means++ initial seeds) drastically outperformed the Kd-tree tree method as dimensionality increased.

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An Ensemble Blocking Scheme for Entity Resolution of Large and Sparse Datasets. (arXiv:1609.06265v1 [cs.AI])

Entity Resolution, also called record linkage or deduplication, refers to the process of identifying and merging duplicate versions of the same entity into a unified representation. The standard practice is to use a Rule based or Machine Learning based model that compares entity pairs and assigns a score to represent the pairs' Match/Non-Match status. However, performing an exhaustive pair-wise comparison on all pairs of records leads to quadratic matcher complexity and hence a Blocking step is performed before the Matching to group similar entities into smaller blocks that the matcher can then examine exhaustively. Several blocking schemes have been developed to efficiently and effectively block the input dataset into manageable groups. At CareerBuilder (CB), we perform deduplication on massive datasets of people profiles collected from disparate sources with varying informational content. We observed that, employing a single blocking technique did not cover the base for all possible scenarios due to the multi-faceted nature of our data sources. In this paper, we describe our ensemble approach to blocking that combines two different blocking techniques to leverage their respective strengths.

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Semantic Similarity Strategies for Job Title Classification. (arXiv:1609.06268v1 [cs.AI])

Automatic and accurate classification of items enables numerous downstream applications in many domains. These applications can range from faceted browsing of items to product recommendations and big data analytics. In the online recruitment domain, we refer to classifying job ads to pre-defined or custom occupation categories as job title classification. A large-scale job title classification system can power various downstream applications such as semantic search, job recommendations and labor market analytics. In this paper, we discuss experiments conducted to improve our in-house job title classification system. The classification component of the system is composed of a two-stage coarse and fine level classifier cascade that classifies input text such as job title and/or job ads to one of the thousands of job titles in our taxonomy. To improve classification accuracy and effectiveness, we experiment with various semantic representation strategies such as average W2V vectors and document similarity measures such as Word Movers Distance (WMD). Our initial results show an overall improvement in accuracy of Carotene[1].

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The Digital Synaptic Neural Substrate: A New Approach to Computational Creativity. (arXiv:1507.07058v2 [cs.AI] UPDATED)

We introduce a new artificial intelligence (AI) approach called, the 'Digital Synaptic Neural Substrate' (DSNS). It uses selected attributes from objects in various domains (e.g. chess problems, classical music, renowned artworks) and recombines them in such a way as to generate new attributes that can then, in principle, be used to create novel objects of creative value to humans relating to any one of the source domains. This allows some of the burden of creative content generation to be passed from humans to machines. The approach was tested in the domain of chess problem composition. We used it to automatically compose numerous sets of chess problems based on attributes extracted and recombined from chess problems and tournament games by humans, renowned paintings, computer-evolved abstract art, photographs of people, and classical music tracks. The quality of these generated chess problems was then assessed automatically using an existing and experimentally-validated computational chess aesthetics model. They were also assessed by human experts in the domain. The results suggest that attributes collected and recombined from chess and other domains using the DSNS approach can indeed be used to automatically generate chess problems of reasonably high aesthetic quality. In particular, a low quality chess source (i.e. tournament game sequences between weak players) used in combination with actual photographs of people was able to produce three-move chess problems of comparable quality or better to those generated using a high quality chess source (i.e. published compositions by human experts), and more efficiently as well. Why information from a foreign domain can be integrated and functional in this way remains an open question for now. The DSNS approach is, in principle, scalable and applicable to any domain in which objects have attributes that can be represented using real numbers.

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ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning. (arXiv:1605.02097v2 [cs.LG] UPDATED)

The recent advances in deep neural networks have led to effective vision-based reinforcement learning methods that have been employed to obtain human-level controllers in Atari 2600 games from pixel data. Atari 2600 games, however, do not resemble real-world tasks since they involve non-realistic 2D environments and the third-person perspective. Here, we propose a novel test-bed platform for reinforcement learning research from raw visual information which employs the first-person perspective in a semi-realistic 3D world. The software, called ViZDoom, is based on the classical first-person shooter video game, Doom. It allows developing bots that play the game using the screen buffer. ViZDoom is lightweight, fast, and highly customizable via a convenient mechanism of user scenarios. In the experimental part, we test the environment by trying to learn bots for two scenarios: a basic move-and-shoot task and a more complex maze-navigation problem. Using convolutional deep neural networks with Q-learning and experience replay, for both scenarios, we were able to train competent bots, which exhibit human-like behaviors. The results confirm the utility of ViZDoom as an AI research platform and imply that visual reinforcement learning in 3D realistic first-person perspective environments is feasible.

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Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering. (arXiv:1605.05359v2 [cs.LG] UPDATED)

This paper introduces an automated skill acquisition framework in reinforcement learning which involves identifying a hierarchical description of the given task in terms of abstract states and extended actions between abstract states. Identifying such structures present in the task provides ways to simplify and speed up reinforcement learning algorithms. These structures also help to generalize such algorithms over multiple tasks without relearning policies from scratch. We use ideas from dynamical systems to find metastable regions in the state space and associate them with abstract states. The spectral clustering algorithm PCCA+ is used to identify suitable abstractions aligned to the underlying structure. Skills are defined in terms of the sequence of actions that lead to transitions between such abstract states. The connectivity information from PCCA+ is used to generate these skills or options. These skills are independent of the learning task and can be efficiently reused across a variety of tasks defined over the same model. This approach works well even without the exact model of the environment by using sample trajectories to construct an approximate estimate. We also present our approach to scaling the skill acquisition framework to complex tasks with large state spaces for which we perform state aggregation using the representation learned from an action conditional video prediction network and use the skill acquisition framework on the aggregated state space.

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Alternating Optimisation and Quadrature for Robust Reinforcement Learning. (arXiv:1605.07496v2 [cs.LG] UPDATED)

Bayesian optimisation has been successfully applied to a variety of reinforcement learning problems. However, the traditional approach for learning optimal policies in simulators does not utilise the opportunity to improve learning by adjusting certain environment variables - state features that are randomly determined by the environment in a physical setting but are controllable in a simulator. This paper considers the problem of finding an optimal policy while taking into account the impact of environment variables. We present alternating optimisation and quadrature (ALOQ), which uses Bayesian optimisation and Bayesian quadrature to address such settings. ALOQ is robust to the presence of significant rare events, which may not be observable under random sampling, but have a considerable impact on determining the optimal policy. We provide experimental results demonstrating our approach learning more efficiently than existing methods.

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Exploiting Vagueness for Multi-Agent Consensus. (arXiv:1607.05540v2 [cs.MA] UPDATED)

A framework for consensus modelling is introduced using Kleene's three valued logic as a means to express vagueness in agents' beliefs. Explicitly borderline cases are inherent to propositions involving vague concepts where sentences of a propositional language may be absolutely true, absolutely false or borderline. By exploiting these intermediate truth values, we can allow agents to adopt a more vague interpretation of underlying concepts in order to weaken their beliefs and reduce the levels of inconsistency, so as to achieve consensus. We consider a consensus combination operation which results in agents adopting the borderline truth value as a shared viewpoint if they are in direct conflict. Simulation experiments are presented which show that applying this operator to agents chosen at random (subject to a consistency threshold) from a population, with initially diverse opinions, results in convergence to a smaller set of more precise shared beliefs. Furthermore, if the choice of agents for combination is dependent on the payoff of their beliefs, this acting as a proxy for performance or usefulness, then the system converges to beliefs which, on average, have higher payoff.

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I have a new follower on Twitter

Asset TV U.S.
Online TV channel for financial advisors and institutional investors, with an audience of 190,000 investment professionals.
United States
https://t.co/nTPBbmCIGl
Following: 5605 - Followers: 5096

September 20, 2016 at 07:54PM via Twitter http://twitter.com/AssetTVUS

Ravens Image: Players greet drivers at the Fort McHenry toll booth, bring pizza to firefighters after defeating Browns (ESPN)

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Not work for anonymous

Hello! It peferctly work for admin user. But it dont want save image into file input. Just create a node without image (empty field) Please tell me how to ...

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[FD] Blind SQL Injection in Exponent CMS <= v2.3.9

============================================= MGC ALERT 2016-005 - Original release date: September 09, 2016 - Last revised: September 20, 2016 - Discovered by: Manuel García Cárdenas - Severity: 7,1/10 (CVSS Base Score) - CVE-ID: CVE-2016-7400 ============================================= I. VULNERABILITY

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[FD] Joomla! session id not hashed.

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Anonymous webform results tied to specific user

Anonymous webform results tied to specific user. Posted by cmsrm on September 20, 2016 at 2:33pm. I'm not sure if this can be done, but before I go ...

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[FD] Critical Vulnerabilities in Sparkassen Bank Server discovered by German Security Researchers

Title: Critical Vulnerabilities in the Sparkassen Newsletter, Emails & Paydirect Online Service Web-Application Source: http://ift.tt/2cOpLzR

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ISS Daily Summary Report – 09/19/2016

Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI)-2 Auto-Stop Transition: On Sunday, ground teams received notification that MELFI-2 in the Japanese Experiment Module (JEM) transitioned to Auto-stop.  The Brayton Motor powered off, and the rack maintained power and good Low Temperature Loop (LTL) flow.  The Cold Stowage team noted that the way the MELFI monitoring software is coded that the software may pick up on an Auto-Stop condition and take action before it’s reported in telemetry that is broadcast to the ground. Based on the state of the rack prior to the Auto-Stop, Cold Stowage is confident that is what happened.  Due to all other rack parameters being in a good state, the Brayton Motor was repowered and the total time for the Brayton Motor to be off was 1 hour 16 minutes 5 seconds. Body Measures: FE-6, with the assistance of FE-5 as the operator, conducted a Body Measures data collection session. The crew configured still cameras and video, then collected the Neutral Body Posture video and stow the equipment. NASA is collecting in-flight anthropometric data (body measurements) to assess the impact of physical body shape and size changes on suit sizing. Still and video imagery is captured and a tape measure is used to measure segmental length, height, depth, and circumference data for all body segments (chest, waist, hip, arms, legs, etc.) from astronauts before, during and after their flight missions. Fine Motor Skills (FMS): Both FE-5 and FE-6 performed their weekly FMS sessions. The crew each performed a series of interactive tasks on a touchscreen tablet were completed for the Fine Motor Skills investigation. This investigation is critical during long-duration space missions, particularly those skills needed to interact with technologies required in next-generation space vehicles, spacesuits, and habitats. The crewmember’s fine motor skills are also necessary for performing tasks in transit or on a planetary surface, such as information access, just-in-time training, subsystem maintenance, and medical treatment. Microgravity Science Laboratory (MSL) Sample Cartridge Assembly (SCA) Exchange:  The crew changed out the SCA in the Solidification Quenching Furnace (SQF), removing the calibration cartridge and inserting the first test sample.  Ground teams will initiate the runs next week. The Batch-2b of the Materials Science Laboratory Sample Cartridge Assemblies serves two projects investigating how different phases organize in a structure when metallic alloys are solidified. The project Metastable Solidification of Composites (METCOMP) studies the phase formed by the reaction of the remaining liquid phase with an already formed solid, to form a second solid phase on cooling. For this purpose, Bronze (Copper-Tin Alloys) of different compositions will be processed. The other project, Solidification along a Eutectic path in Ternary Alloys (SETA), looks at how two phases that form together organize into lamellar, or fibre, structures when cooling Aluminum (Copper-Silver Alloys). Both projects will provide benchmark samples that will enable to test numerical models that aim to predict these structures. Eli Lily Hard to Wet Surfaces: FE-6 charged batteries in support of the Hard to Wet Surfaces experiment.  After the battery charging, the crew verified the setup of the camera and flash that will be used in the experiment run starting tomorrow.  In chemistry, wetting refers to spreading of a liquid over a solid material’s surface, and is a key aspect of the material’s ability to dissolve. The Hard to Wet Surfaces (Eli Lilly-Hard to Wet Surfaces) investigation studies how certain materials used in the pharmaceutical industry dissolve in water while in microgravity. Results from this investigation could help improve the design of tablets that dissolve in the body to deliver drugs, thereby improving drug design for medicines used in space and on Earth. Hatch Seal Inspection:  FE-5 cleaned and inspected the COL, N2 port, N2 Stbd, A/L, N2 Stbd, JLP, JPM Stbd, JPM Zenith and PMM hatch seals, hatch plate sealing surface and hatch handle mechanism for FOD or damage.  This is standard preventative maintenance performed every 180 day.  Space Station Remote Manipulator System (SSRMS) Latching End Effector (LEE) Survey:  The SSRMS was powered up and maneuvered to allow for an inspection of the LEE B using the new High Definition cameras.  Today’s Planned Activities All activities completed unless otherwise noted. Fine Motor Skills Experiment Test Electrostatic Levitation Furnace (ELF) Ground Connection Auxiliary Laptop Computer System (ВКС) Virus Definition File Update Hard To Wet Surfaces D2Xs Battery Charge CO Partial Pressure Measurement on ISS RS (SM Central Post) using USOS Portable Gas Analyzer CSA-CP (located on the SM Central Post, Panel 208). Battery replacement (as necessary) Body Measures Equipment Gather COSMOCARD. Setup. 24-Hour EKG Recording (start) Body Measures Experiment Operations EML Reprogramming Cable installation Transfer of Brine and Urine from EDV-U into DC1 Progress 433 Rodnik БВ2 Water Tank Hatch Seal Inspection Habitability Narrated Task Video Setup – Subject Potable Water Dispenser (PWD) Sample Collect Quick Disconnect Screw Clamps Tightening on DC1-Progress 433 Interface Habitability Narrated Task Video End – Subject Soyuz 731 Samsung Tablet Charging (start) Total Organic Carbon Analyzer (TOCA) Potable Water Dispenser (PWD) Sample Analysis Material Science Laboratory SCA ExchangeA2 #5 СОЖ maintenance Environmental Health System (EHS) Coliform Water Processing Soyuz 731 Samsung Tablet Charging (term) IMS Delta File Prep Metal Oxide (METOX) Regeneration Termination EML Reprogramming Cable removal Hard To Wet Surfaces Hardware Gather Profile of Mood States (POMS) Questionnaire TV Downlink Test via Ku-band in MPEG-2 Prior to Soyuz 732 Docking to the ISS (Ku+S-band). Hard To Wet Surfaces Set Up Check Exercise Data Downlink via OCA Environmental Health System (EHS) Total Organic Carbon Analyzer (TOCA) Sample Data Record Completed Task List Items JAXA Try Zero G Experiment (Completed Saturday) Personal CO2 Monitor Payload On Board Training (Completed Saturday) Personal CO2 Monitor iPad Application Install (Completed Saturday) Personal CO2 Monitor Sensor Calibration (Completed Saturday) Remove and replace the Solid Waste Container [KTO]. (Completed Saturday) Remove and Replace Waste Hygiene Compartment (WHC) ЕДВ-Y (Completed Saturday) A/L Equipment Procedure Print (Completed Sunday) JAXA Video Taking Part 5 (Completed Sunday) Plug-in Plan USB Charger Deploy to NOD2 UOP1 and NOD3 UOP1 (Completed Sunday) Personal CO2 Monitor […]

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Hackers take Remote Control of Tesla's Brakes and Door locks from 12 Miles Away

Next time when you find yourself hooked up behind the wheel, make sure your car is actually in your control. Hackers can remotely hijack your car and even control its brakes from 12 miles away. Car hacking is a hot topic. Today many automobiles companies have been offering vehicles with the majority of functions electronically controlled, from instrument cluster to steering, brakes, and

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Cisco finds new Zero-Day Exploit linked to NSA Hackers

Network equipment vendor Cisco is finally warning its customers of another zero-day vulnerability the company discovered in the trove of NSA's hacking exploits and implants leaked by the group calling itself "The Shadow Brokers." Last month, the Shadow Brokers published firewall exploits, implants, and hacking tools allegedly stolen from the NSA's Equation Group, which was designed to target

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50000 Kilometers over the Sun

What's happening at the edge of the Sun? Although it may look like a monster is rampaging, what is pictured is actually only a monster prominence -- a sheath of thin gas held above the surface by the Sun's magnetic field. The solar event was captured just this past weekend with a small telescope, with the resulting image then inverted and false-colored. As indicated with illustrative lines, the prominence rises over 50,000 kilometers above the Sun's surface, making even our 12,700-diameter Earth seem small by comparison. Below the monster prominence is active region 12585, while light colored filaments can be seen hovering over a flowing solar carpet of fibrils. Filaments are actually prominences seen against the disk of the Sun, while similarly, fibrils are actually spicules seen against the disk. Energetic events like this are becoming less common as the Sun evolves toward a minimum in its 11-year activity cycle. via NASA http://ift.tt/2d5Ewlt

Anonymous Group

Anonymous Group's story. This client, Kahambu, is a micro-entrepreneur. She is 36 years old, married, and the mother of three. The owner of a store, ...

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Orioles fall to Red Sox 5-2, trail AL East leaders by 4 games with 12 left to play this season; hold 0.5-game lead in WC (ESPN)

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Burgers Anonymous

Burgers Anonymous - Online Delivery Menu. Order takeaway online with fast delivery service provided by Deliveroo.

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Prioritised Default Logic as Argumentation with Partial Order Default Priorities. (arXiv:1609.05224v1 [cs.AI])

We express Brewka's prioritised default logic (PDL) as argumentation using ASPIC+. By representing PDL as argumentation and designing an argument preference relation that takes the argument structure into account, we prove that the conclusions of the justified arguments correspond to the PDL extensions. We will first assume that the default priority is total, and then generalise to the case where it is a partial order. This provides a characterisation of non-monotonic inference in PDL as an exchange of argument and counter-argument, providing a basis for distributed non-monotonic reasoning in the form of dialogue.

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Continuous occurrence theory. (arXiv:1609.05228v1 [cs.AI])

Usually gradual and continuous changes in entities will lead to appear events. But usually it is supposed that an event is occurred at once. In this research an integrated framework called continuous occurrence theory (COT) is presented to investigate respective path leading to occurrence of the events in the real world. For this purpose initially fundamental concepts are defined. Afterwards, the appropriate tools such as occurrence variables computations, occurrence dependency function and occurrence model are introduced and explained in a systematic manner. Indeed, COT provides the possibility to: (a) monitor occurrence of events during time; (b) study background of the events; (c) recognize the relevant issues of each event; and (d) understand how these issues affect on the considered event. The developed framework (COT) provides the necessary context to analyze accurately continual changes of the issues and the relevant events in the various branches of science and business. Finally, typical applications of COT and an applied modeling example of it have been explained and a mathematical programming example is modeled in the occurrence based environment.

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The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research. (arXiv:1609.05258v1 [cs.RO])

Robotic challenges like the Amazon Picking Challenge (APC) or the DARPA Challenges are an established and important way to drive scientific progress as they make research comparable on a well-defined benchmark with equal test conditions for all participants. However, such challenge events occur only occasionally, are limited to a small number of contestants, and the test conditions are very difficult to replicate after the main event. We present a new physical benchmark challenge for robotic picking. The ACRV Picking Benchmark is designed to be reproducible by using a set of 42 common objects, a widely available shelf, and exact guidelines for object arrangement using stencils. A well-defined evaluation protocol enables the comparability of complete robotic systems -- including perception and manipulation -- instead of sub-systems only. Our paper describes this new benchmark challenge and presents results acquired by a baseline system based on a Baxter robot.

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NPCs Vote! Changing Voter Reactions Over Time Using the Extreme AI Personality Engine. (arXiv:1609.05315v1 [cs.AI])

Can non-player characters have human-realistic personalities, changing over time depending on input from those around them? And can they have different reactions and thoughts about different people? Using Extreme AI, a psychology-based personality engine using the Five Factor model of personality, I answer these questions by creating personalities for 100 voters and allowing them to react to two politicians to see if the NPC voters' choice of candidate develops in a realistic-seeming way, based on initial and changing personality facets and on their differing feelings toward the politicians (in this case, across liking, trusting, and feeling affiliated with the candidates). After 16 test runs, the voters did indeed change their attitudes and feelings toward the candidates in different and yet generally realistic ways, and even changed their attitudes about other issues based on what a candidate extolled.

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Solving the Wastewater Treatment Plant Problem with SMT. (arXiv:1609.05367v1 [cs.AI])

In this paper we introduce the Wastewater Treatment Plant Problem, a real-world scheduling problem, and compare the performance of several tools on it. We show that, for a naive modeling, state-of-the-art SMT solvers outperform other tools ranging from mathematical programming to constraint programming. We use both real and randomly generated benchmarks.

From this and similar results, we claim for the convenience of developing compiler front-ends being able to translate from constraint programming languages to the SMT-LIB standard language.

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Applications of Data Mining (DM) in Science and Engineering: State of the art and perspectives. (arXiv:1609.05401v1 [cs.AI])

The continuous increase in the availability of data of any kind, coupled with the development of networks of high-speed communications, the popularization of cloud computing and the growth of data centers and the emergence of high-performance computing does essential the task to develop techniques that allow more efficient data processing and analyzing of large volumes datasets and extraction of valuable information. In the following pages we will discuss about development of this field in recent decades, and its potential and applicability present in the various branches of scientific research. Also, we try to review briefly the different families of algorithms that are included in data mining research area, its scalability with increasing dimensionality of the input data and how they can be addressed and what behavior different methods in a scenario in which the information is distributed or decentralized processed so as to increment performance optimization in heterogeneous environments.

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SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient. (arXiv:1609.05473v1 [cs.LG])

As a new way of training generative models, Generative Adversarial Nets (GAN) that uses a discriminative model to guide the training of the generative model has enjoyed considerable success in generating real-valued data. However, it has limitations when the goal is for generating sequences of discrete tokens. A major reason lies in that the discrete outputs from the generative model make it difficult to pass the gradient update from the discriminative model to the generative model. Also, the discriminative model can only assess a complete sequence, while for a partially generated sequence, it is non-trivial to balance its current score and the future one once the entire sequence has been generated. In this paper, we propose a sequence generation framework, called SeqGAN, to solve the problems. Modeling the data generator as a stochastic policy in reinforcement learning (RL), SeqGAN bypasses the generator differentiation problem by directly performing gradient policy update. The RL reward signal comes from the GAN discriminator judged on a complete sequence, and is passed back to the intermediate state-action steps using Monte Carlo search. Extensive experiments on synthetic data and real-world tasks demonstrate significant improvements over strong baselines.

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Towards Deep Symbolic Reinforcement Learning. (arXiv:1609.05518v1 [cs.AI])

Deep reinforcement learning (DRL) brings the power of deep neural networks to bear on the generic task of trial-and-error learning, and its effectiveness has been convincingly demonstrated on tasks such as Atari video games and the game of Go. However, contemporary DRL systems inherit a number of shortcomings from the current generation of deep learning techniques. For example, they require very large datasets to work effectively, entailing that they are slow to learn even when such datasets are available. Moreover, they lack the ability to reason on an abstract level, which makes it difficult to implement high-level cognitive functions such as transfer learning, analogical reasoning, and hypothesis-based reasoning. Finally, their operation is largely opaque to humans, rendering them unsuitable for domains in which verifiability is important. In this paper, we propose an end-to-end reinforcement learning architecture comprising a neural back end and a symbolic front end with the potential to overcome each of these shortcomings. As proof-of-concept, we present a preliminary implementation of the architecture and apply it to several variants of a simple video game. We show that the resulting system -- though just a prototype -- learns effectively, and, by acquiring a set of symbolic rules that are easily comprehensible to humans, dramatically outperforms a conventional, fully neural DRL system on a stochastic variant of the game.

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