NFL Video: Lions K Matt Prater one-ups Ravens K Justin Tucker, boots 76-yard FG at Pro Bowl practice (ESPN)

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[FD] Persistent Cross-Site Scripting vulnerability in User Access Manager WordPress Plugin

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[FD] Multiple blind SQL injection vulnerabilities in FormBuilder WordPress Plugin

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[FD] Cross-Site Request Forgery vulnerability in FormBuilder WordPress Plugin allows plugin permissions modification

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Anonymous donor pays students' lunch debt

An anonymous donor has paid off lunch debts for 148 Johnston elementary school students whose accounts were in the red by $10 or more.

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Police Arrest 5 Cyber Thieves Who Stole 3.2 Million From ATMs Using Malware

Law enforcement authorities from Europe and Russia have arrested five members of an international cyber criminal gang for stealing $3.2 million cash from ATMs using malware. Three of the suspects, Andrejs Peregudovs (41), of Latvia, Niklae Penkov (34) of Moldova, and Mihail Colibaba (30) of Romania, were arrested in Taiwan by the Taiwanese Criminal Investigation Bureau last summer, have

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Google becomes its own Root Certificate Authority

In an effort to expand its certificate authority capabilities and build the "foundation of a more secure web," Google has finally launched its root certificate authority. In past few years, we have seen Google taking many steps to show its strong support for sites using HTTPS, like: Giving more preference to HTTPS websites in its search rankings than others. Warning users that all HTTP

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Andrea Condividi (@EducateForYou) liked one of your Tweets!

@mistermcguire: [FD] Call for Papers: DigitalSec2017 in Kuala Lumpur, Malaysia on July 11-13, 2017   Andrea Condividi liked your Tweet. View   Patrick McGuire @mistermcguire =   [FD] Call for Papers: DigitalSec2017 in Kuala Lumpur, Malaysia on July 11-13, 2017 ift.tt/2jBMgKq   Settings | Help | Opt-out | Download app Twitter, Inc. 1355 Market Street, Suite 900 San Francisco, CA 94103

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new support group - clutterers anonymous

What is clutter? Possessions not needed, wanted, or used that takes time, energy, or space and destroys serenity. Also known as hoarding. Meeting ...

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I have a new follower on Twitter

Andrea Condividi
Promoting calls for paper (#CFP). Just to make sure that I do not miss anything :-) feel free to DM me if you have a #CFP to share.
Switzerland
https://t.co/HbgJnheHJK
Following: 335 - Followers: 190

January 28, 2017 at 12:49AM via Twitter http://twitter.com/EducateForYou

I have a new follower on Twitter

Brian Wood
I'm a reviewer of products on Amazon U.K. Click here to see my profile,. https://t.co/6e7i4BFi1d
Stockton-on-Tees, England
https://t.co/DRLF01hhFL
Following: 443 - Followers: 325

January 27, 2017 at 10:09PM via Twitter http://twitter.com/woodb180

Anonymous Peer Review Assignments also anonymous in SpeedGrader

I have professors using Anonymous Peer Reviews for an assignment so that students cannot see names of reviewers or reviewees; however, this also ...

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Ravens: S Eric Weddle voted by teammates to be one of four captains for AFC's Pro Bowl team; was added to roster as an alternate (ESPN)

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[FD] Privilege Escalation in VirtualBox (CVE-2017-3316)

[FD] Digital Ocean ssh key authentication security risk -- password authentication is re-enabled

Regarding digitalocean.com cloud computing. PasswordAuthentication is reset to yes in /etc/ssh/sshd_config when using ssh key authentication given the following scenario: When creating a new droplet from a snapshot where ssh key authentication "PasswordAuthentication" in /etc/ssh/sshd_config was previosly set to no, "PasswordAuthentication" is reset to yes. I am not sure how common this scenario is but for me I often create a base snapshot that is pre-configured with firewall settings, sudo user, ssh key authentication, various apps, hardening etc. that I can then use when spinning up a new server so I don't have to start from scratch. By doing this I was unaware that PasswordAuthentication was automatically re-enabled and that these servers were no longer secure via ssh key authentication only, leaving them open to Brute Force attacks. Steps to reproduce: Tested using an Ubuntu 16.04 droplet image 1. Create a new Ubuntu 16.04 droplet and secure it using ssh key authentication 2. Edit /etc/ssh/sshd_config and set PasswordAuthentication no 3. Reload ssh 4. Verify that you can log in using key authentication only, trying via password should be rejected. 5. Create a snapshot of this droplet 6. Create a new droplet from this snapshot 7. Open /etc/ssh/sshd_config and PasswordAuthentication will be reset to yes You will now be able to log in via ssh using passwords instead of key authentication only.

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Facebook Adds FIDO U2F Security Keys Feature For Secure Logins

Hacking password for a Facebook account is not easy, but also not impossible. We have always been advising you to enable two-factor authentication — or 2FA — to secure your online accounts, a process that requires users to manually enter, typically a six-digit secret code generated by an authenticator app or received via SMS or email. So even if somehow hackers steal your login credentials,

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I have a new follower on Twitter

FullAI
FullAI is the world's first NGO advocating human decisions over machine decisions. Artificial Intelligence is not science fiction. #AI
Amsterdam, Nederland
https://t.co/IC2c2dy0Of
Following: 1531 - Followers: 516

January 27, 2017 at 11:24AM via Twitter http://twitter.com/FullArtIntel

ISS Daily Summary Report – 1/26/2017

Fluid Shifts Chibis Imaging Day 2: Due to yesterday’s issues with the Joint Station LAN (JSL), the final Flight Day 45 Chibis session for the 49S crew was rescheduled and performed this morning. The subject donned the Chibis device, and while the crewmember was exposed to the negative pressure (pulling the fluid feetward), then with ground and onboard operator support they configured the Optical Coherence Tomography (OCT) and the Distortion Product Otoacoustic Emission (DPOAE) hardware, before completing a DPOAE test, OCT exam, and a Tonometry exam. The purpose of this investigation is to characterize the space flight-induced fluid shift, including intra- and extravascular shifts, intra- and extracellular shifts, changes in total body water and lower vs. upper body shifts. Noninvasive techniques are used to assess arterial and venous dimensions and flow parameters, ocular pressure and structure, and changes in intracranial pressure. Lower body negative pressure is being investigated for its ability to mitigate some of the effects of the space flight-induced fluid shift. Results from this investigation are expected to help define the causes of the ocular structure and vision changes associated with long duration space flight, and assist in the development of countermeasures. Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) On-Board Training (OBT): Prior to participating in the SPHERES Zero Robotic Challenge activities on Friday, the crew viewed an OBT video to familiarize themselves with the SPHERES facility. The SPHERES Zero Robotics investigation establishes an opportunity for high school students to design research for the ISS. As part of a competition, students write algorithms for the SPHERES satellites to accomplish tasks relevant to future space missions. The algorithms are tested by the SPHERES team and the best designs are selected for the competition to operate the SPHERES satellites on board the ISS. H-II Transfer Vehicle 6 (HTV6) Departure Preparations:  Earlier today, the crew completed final cargo loading and egressed HTV6. The crew configured the vestibule for demate by removing Air Revitalization System (ARS) jumper, Intermodular Ventilation (IMV) supply jumper, 1553/ENET A and B jumper, and disconnecting the Node 2 HTV channel 2 power jumper.  The also installed the Common Berthing Mechanism (CBM) Controller Panel Assemblies (CPAs).  HTV-6 unberth activities are scheduled to start tomorrow morning at ~5:30 am CST with vehicle release at ~9:30 am CST. Today’s Planned Activities All activities were completed unless otherwise noted. FLUID SHIFTS. Comm configuration for the experiment Fluid Shifts Laptop RSOS Transfer FLUID SHIFTS. Gathering and Connecting Equipment for TV coverage Fluid Shifts OCT Service Module Setup HTV Hatch Stowage Latch Override Knob Scavenge FLUID SHIFTS. Connecting OCT Laptop to BRI and HRF PC to ППС-26 (in lieu of RSE-MED) HTV General Luminaire Assembly (GLA) Scavenge Life On The Station Photo and Video Fluid Shifts OCT Service Module Power On Fluid Shifts CCFP Service Module Configuration Fluid Shifts DPOAE Service Module Setup FLUID SHIFTS. Don Chibis FLUID SHIFTS. Assistance during Operation with CHIBIS and GAMMA-1M. FLUID SHIFTS. TONOMETRY Hardware setup in SM HTV Smoke Detector Scavenge FLUID SHIFTS. Gathering Data in SM, Operator Fluid Shifts Experiment Service Module Data Collection – Subject Node 2 Nadir Vestibule Outfitting Kit (VOK) Gather Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill WIRELESS LEAK DETECTOR ULTRASONIC SENSOR DEPLOYMENT FLUID SHIFTS. Doff Chibis FLUID SHIFTS. Copying Data from CCFP/DPOAE devices and their deactivation in RS Fluid Shifts Tonometry Service Module Stow AQM Sieve Cartridge Remove and Replace Fluid Shifts OCT Service Module Power Off FLUID SHIFTS. Disconnecting of Laptop OCT, HRF and connecting RSE-Med. ISS HAM Service Module Pass Dose Tracker Data Entry Subject FLUID SHIFTS. Deactivation of КСПЭ Equipment and Closing Applications on Central Post SSC Fluid Shifts OCT Service Module Stow On-board Training (OBT) HTV Departure Review ESA Nutritional Assessment EveryWear Application Conference FLUID SHIFTS. DROUTE Fluid Shifts CCFP HRF PC Service Module Stow Habitability Human Factors Directed Observations – Subject SPHERES Payload OBT FLUID SHIFTS. Comm Reconfiguration to nominal on RS Fluid Shifts Hardware Final Gather Fluid Shifts Hardware USOS Transfer H-II Transfer Vehicle (HTV) Egress Fluid Shifts OCT Laptop US Lab Setup Advanced Resistive Exercise Device (ARED) Detent Remove and Replace [Aborted] ESA Weekly crew conference Public Affairs Office (PAO) High Definition (HD) Config JEM Setup HTV Vestibule Configure for Demate – Part 1 Crew Prep for PAO TV conference with RAN-TV journalists (Ku + S-band) Node 2 Nadir CBM Control Panel Assembly (CPA) Installation Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill Recharging Soyuz 732 Samsung PC Battery (if charge level is below 80%) Public Affairs Office (PAO) High Definition (HD) Config LAB Setup MOTOCARD. Experiment Ops Verification of ИП-1 Flow Sensor Position PAO Preparation MOTOCARD. Operator Assistance with the Experiment Public Affairs Office (PAO) Event in High Definition (HD) – Lab Packed Bed Reactor Experiment Lab Video Setup Ultrasound 2 HRF Rack 1 Power On Habitability Walk-through Video – Subject Life On The Station Photo and Video Inventory Management System (IMS) Conference Fluid Shifts HRF PC 2 Reconnect Fluid Shifts Hardware Stow Dose Tracker Data Entry Subject Health Maintenance System (HMS) Ultrasound 2 Scan Prep Terminate Soyuz 732 Samsung PC Battery Recharge (as necessary) Health Maintenance System (HMS) Ultrasound 2 Scan Ultrasound2 Scan, Ground Guided Data Export Ultrasound2 Scan, Post-exam ops Packed Bed Reactor Experiment Lab Video Return  Completed Task List Items Manufacturing Device Print Removal, Clean and Stow NOD1D2 Cleanup Ground Activities All activities were completed unless otherwise noted. Sabatier Troubleshooting N2N CBM Prep for Demate S-Band String 2 activation Three-Day Look Ahead: Friday, 01/27: HTV Release and Departure, SPHERES Zero Robotics Run Saturday, 01/28: Weekly Housekeeping, Crew Off Duty Sunday, 01/29: Crew Off Duty  QUICK ISS Status – Environmental Control Group:     Component Status Elektron Off Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off          [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 Operate Major Constituent Analyzer (MCA) Node 3 Startup Oxygen Generation […]

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Breach Database Site 'LeakedSource' Goes Offline After Alleged Police Raid

The biggest mistake companies make with data security is leaving all their secrets unprotected at one place, which if attacked, they are all gone in one shot. An unnamed law enforcement agency has reportedly accessed billions of compromised usernames, email IDs, and their passwords, collected by LeakedSource, a popular breach notification service. LeakedSource that exposed some of the

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Commercials

Anonymous Content. Alejandro G Iñárritu · Alfonso Cuarón · Armando Bo · Autumn de Wilde · Brett Morgen · Cary Fukunaga · Casey Storm · Chris ...

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I have a new follower on Twitter

Dr Morten Middelfart

Tampa, Florida
https://t.co/bpoICsyaBo
Following: 45578 - Followers: 54044

January 27, 2017 at 03:14AM via Twitter http://twitter.com/dr_morton_

I have a new follower on Twitter

SEO For Growth
SEO for Growth: The Ultimate Guide for Marketers, Web Designers & Entrepreneurs, a search engine optimization book by John Jantsch & Phil Singleton.

https://t.co/GRp3tyjskY
Following: 3458 - Followers: 3819

January 27, 2017 at 03:14AM via Twitter http://twitter.com/seoforgrowth

President Trump's @POTUS Twitter Linked To A Private Gmail Account

It seems like the new American President's Twitter account could easily be hacked due to security blunders he made with the most powerful Twitter account in the world, experts warned. Days after we got to know that the newly inaugurated President Donald Trump was still using his old, insecure Android smartphone, it has now been revealed that the official @POTUS Twitter account was linked to a

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NCIIPC: It's Time to Step Forward And Protect Our Critical Infrastructures from Cyber Attacks

The IT threat landscape has changed dramatically over the last three-four years. With no shortage of threat actors, from hacktivists to nation-states, criminals to terrorists, all of them are now after something new. It's no more just about stealing your money, credit cards and defacing websites, as now they are after the intellectual property, mass attacks and most importantly, our critical

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Logic Programming Petri Nets. (arXiv:1701.07657v1 [cs.AI])

With the purpose of modeling, specifying and reasoning in an integrated fashion with procedural and declarative aspects (both commonly present in cases or scenarios), the paper introduces Logic Programming Petri Nets (LPPN), an extension to the Petri Net notation providing an interface to logic programming constructs. Two semantics are presented. First, a hybrid operational semantics that separates the process component, treated with Petri nets, from the constraint/terminological component, treated with Answer Set Programming (ASP). Second, a denotational semantics maps the notation to ASP fully, via Event Calculus. These two alternative specifications enable a preliminary evaluation in terms of reasoning efficiency.

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Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery. (arXiv:1701.07696v1 [cs.AI])

Existing algorithms for subgroup discovery with numerical targets do not optimize the error or target variable dispersion of the groups they find. This often leads to unreliable or inconsistent statements about the data, rendering practical applications, especially in scientific domains, futile. Therefore, we here extend the optimistic estimator framework for optimal subgroup discovery to a new class of objective functions: we show how tight estimators can be computed efficiently for all functions that are determined by subgroup size (non-decreasing dependence), the subgroup median value, and a dispersion measure around the median (non-increasing dependence). In the important special case when dispersion is measured using the average absolute deviation from the median, this novel approach yields a linear time algorithm. Empirical evaluation on a wide range of datasets shows that, when used within branch-and-bound search, this approach is highly efficient and indeed discovers subgroups with much smaller errors.

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Dynamic time warping distance for message propagation classification in Twitter. (arXiv:1701.07756v1 [cs.AI])

Social messages classification is a research domain that has attracted the attention of many researchers in these last years. Indeed, the social message is different from ordinary text because it has some special characteristics like its shortness. Then the development of new approaches for the processing of the social message is now essential to make its classification more efficient. In this paper, we are mainly interested in the classification of social messages based on their spreading on online social networks (OSN). We proposed a new distance metric based on the Dynamic Time Warping distance and we use it with the probabilistic and the evidential k Nearest Neighbors (k-NN) classifiers to classify propagation networks (PrNets) of messages. The propagation network is a directed acyclic graph (DAG) that is used to record propagation traces of the message, the traversed links and their types. We tested the proposed metric with the chosen k-NN classifiers on real world propagation traces that were collected from Twitter social network and we got good classification accuracies.

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Ethical Considerations in Artificial Intelligence Courses. (arXiv:1701.07769v1 [cs.AI])

The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be artificial intelligence practitioners, but also to understand the moral, ethical, and philosophical impacts that artificial intelligence will have on society. In this article we provide practical case studies and links to resources for use by AI educators. We also provide concrete suggestions on how to integrate AI ethics into a general artificial intelligence course and how to teach a stand-alone artificial intelligence ethics course.

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Ancestral Causal Inference. (arXiv:1606.07035v3 [cs.LG] UPDATED)

Constraint-based causal discovery from limited data is a notoriously difficult challenge due to the many borderline independence test decisions. Several approaches to improve the reliability of the predictions by exploiting redundancy in the independence information have been proposed recently. Though promising, existing approaches can still be greatly improved in terms of accuracy and scalability. We present a novel method that reduces the combinatorial explosion of the search space by using a more coarse-grained representation of causal information, drastically reducing computation time. Additionally, we propose a method to score causal predictions based on their confidence. Crucially, our implementation also allows one to easily combine observational and interventional data and to incorporate various types of available background knowledge. We prove soundness and asymptotic consistency of our method and demonstrate that it can outperform the state-of-the-art on synthetic data, achieving a speedup of several orders of magnitude. We illustrate its practical feasibility by applying it on a challenging protein data set.

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Improving Policy Gradient by Exploring Under-appreciated Rewards. (arXiv:1611.09321v2 [cs.LG] UPDATED)

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

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Dating / Relationship podcast seeks anonymous guests (audio only)

Hey there! I'm Billy Procida, a stand-up comedian and sex podcaster in Brooklyn. I host The Manwhore Podcast: A Sex-Positive Quest for Love.

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DuckDuckGo Celebrates 10 Billion Anonymous Searches

Worldwide downloads of secure messaging app Signal grew 70 percent in the last quarter of 2016, and anonymous search engine DuckDuckGo ...

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[FD] Call for Papers: DigitalSec2017 in Kuala Lumpur, Malaysia on July 11-13, 2017

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Proposal: Convert anonymous objects to known types

gulshan changed the title from Proposal: Convert anonymous objects to know types to Proposal: Convert anonymous objects to known types 39 ...

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ISS Daily Summary Report – 1/25/2017

Fluid Shifts Chibis Imaging Day 2: The Flight Day 45 Chibis session for the 49S crew was planned this morning, however due to Joint Station LAN (JSL) network issues the session had to be cancelled.  This Fluid Shifts session will be replanned for tomorrow.  Lighting Effects Vision Test: The crew performed a Numerical Verification and a Color Discrimination test in their Crew Quarters with illumination from the Solid State Lighting Assembly (SSLA). The Lighting Effects experiment hopes to better quantify and qualify how lighting can effect habitability of spacecraft. The light bulbs on the ISS are being replaced with a new system designed for improved crew health and wellness. The Lighting Effects investigation studies the impact of the change from fluorescent light bulbs to solid-state light-emitting diodes (LEDs) with adjustable intensity and color and aims to determine if the new lights can improve crew circadian rhythms, sleep, and cognitive performance. Results from this investigation also have major implications for people on Earth who use electric lights. Habitability Software Update: The crew installed updated software on their tablets in support of the Habitability experiment. The iQ&A iPad application will be used to collect questionnaire data for Habitability Experiment. The Habitability investigation collects observations about the relationship between crew members and their environment on the ISS. Observations can help spacecraft designers understand how much habitable volume is required, and whether a mission’s duration impacts how much space crew members need.  Internal Thermal Control System (ITCS) Sample Collection: The crew conducted ITCS fluid sampling from the Node 2 (N2) Moderate Temperature Loop (MTL) and Low Temperature Loop (LTL) sample ports. They also sampled Columbus ITCS water using the Columbus Coolant Fluid Servicer. These samples will be returned to the ground on SpX-10 for analysis. The return to ground samples are taken once a year to monitor the quality of the water in the ITCS loops. Major Constituent Analyzer (MCA) Mass Spectrometer Assembly Remove and Replace (R&R): On GMT 2016/286, the Node 3 MCA experienced a shutdown due to a failure in its Mass Spectrometer Assembly. A spare Mass Spectrometer Assembly was launched on HTV-6, and it was used today to replace the failed MCA Mass Spectrometer Assembly in Node 3 (N3). Mobile Servicing System (MSS) Cupola Artificial Vision Unit (AVU) Troubleshooting: Crew set up a video camcorder such that Cupola Remote Workstation (RWS) Mon 1 and 2 are in the video frame. Ground specialists routed the camcorder and AVU video output to the ground, the Cupola AVU was then commanded from the ground to power-up perform a checkout. Several different inputs to the AVU (test pattern, external cameras, both SCU sources) were tried during the checkout, and all resulted in mostly blank displays with small portions of the display occasionally flickering into view. It was concluded that the input to the AVU is not the issue. The problem is likely in the AVU itself. This checkout was to determine the viability of utilizing the computing capacity of this MSS equipment last used for ISS operations in 2007.  H-II Transfer Vehicle 6 (HTV6) Departure Preparation:  Yesterday the crew completed loading more than 1450 kg of trash into the HTV vehicle. Today they performed a review of the HTV6 departure profile, procedures, and crew interfaces for monitoring and commanding HTV6. They also performed Robotics training which consisted of HTV6 release scenarios to allow them to practice techniques for nominal and off nominal situations. Additionally, they removed General Luminaire Assemblies (GLAs) from the forward side of HTV, and Light Emitting Diode (LED) Lights from the aft side of HTV in preparation for HTV Departure. These will all be stowed on ISS and used as spares. HTV6 is scheduled to unberth from the ISS on Friday 27-January. Today’s Planned Activities All activities were completed unless otherwise noted. Fine Motor Skills Experiment Test – Subject FLUID SHIFTS. Comm configuration on RS A/C Inverter Swap in SM FLUID SHIFTS. Camcorder setup & switch on Crew Prep for PAO Event Ultrasound 2 HRF Rack 1 Power On Total Organic Carbon Analyzer (TOCA) Water Recovery System (WRS) Sample Analysis Fluid Shifts Ultrasound 2 Data Export Alternate TV-session with the participants of the 11th All-Russia Youth Readings named after S.P. Korolev Habitability iPad App Update [Deferred] Fluid Shifts OCT Service Module Setup Alternate Atmosphere Control and Supply (ACS) Nitrogen Manual Valve Close FLUID SHIFTS. Подключение Laptop OCT к БРИ и HRF РС к ППС-26 (вместо RSE-Med) [Deferred] Node 2 Low Temperature Loop (LTL) Internal Thermal Control System (ITCS) Sample Collection СОЖ maintenance Fluid Shifts OCT Service Module Power On Fluid Shifts CCFP Service Module Configuration Fluid Shifts DPOAE Service Module Setup Node 2 Moderate Temperature Loop (MTL) Internal Thermal Control System (ITCS) Sample Collection FLUID SHIFTS. Don Chibis [Deferred] FLUID SHIFTS. Assistance with Chibis  & Gamma-1 [Deferred] Fluid Shifts Tonometry Service Module Setup Fluid Shifts Experiment Service Module Data Collection [Deferred] Lab Low Temperature Loop (LTL) Internal Thermal Control System (ITCS) Sample Collection FLUID SHIFTS. Doff Chibis [Deferred] FLUID SHIFTS. Disconnection & disassembly [Deferred] Fluid Shifts CCFP DPOAE Service Module End [Deferred] FLUID SHIFTS. Comm Reconfiguration to nominal on RS Fluid Shifts Tonometry Service Module Stow Delta file prep Fluid Shifts OCT Service Module Power Off FLUID SHIFTS. Отключение Laptop OCT, HRF и подключение RSE-Med [Deferred] Total Organic Carbon Analyzer (TOCA) Sample Data Record FLUID SHIFTS. DROUTE [Deferred] Fluid Shifts OCT Service Module Stow Fluid Shifts CCFP HRF PC Service Module Stow Fluid Shifts Hardware Final Gather [Deferred] Node 3 Major Constituent Analyzer (MCA) Mass Spectrometer (MS) Assembly Remove and Replace Fluid Shifts Hardware USOS Transfer [Deferred] Actiwatch Spectrum HRF1 Configuration Alternate 2 Life On The Station Photo and Video WIRELESS LEAK DETECTOR ULTRASONIC SENSOR REMOVAL, FILE TRANSFER, AND STOW Health Maintenance System (HMS) OCT Setup Taking Pille dosimeter readings Robotic Workstation (RWS) High Definition (HD) Monitor Downlink Stow CWSA samples, units and tools. Robotic Workstation (RWS) Setup Lighting Effects Visual Performance Tests Light Setting – Subject Restoring COL1D1 configuration Marrow Breath And Ambient Air Sample Setup – Subject Columbus ITCS […]

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I have a new follower on Twitter

McNeil
A Twitter account about nothing. Divorced. Dad Tweets for days. Browns Cavs Indians CBJ Buckeyes Miami RedHawks #LoveAndHonor
Granville, OH
https://t.co/aIaBFKwQat
Following: 31687 - Followers: 38958

January 26, 2017 at 03:42AM via Twitter http://twitter.com/Reflog_18

NFL Video: Justin Tucker boots 75-yard field goal that hooks inside upright during Pro Bowl practice (ESPN)

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Monitoring and Forecasting Chimpanzee Habitat Health in Africa

In partnership with the Jane Goodall Institute (JGI), NASA scientists have provided assistance in the monitoring, forecasting and conservation of natural resources in regions surrounding the Gombe National Forest in Tanzania. Between 1972 and 1999, significant deforestation had occurred in the regions outside the boundary of the Gombe National Forest to the detriment of the park's chimpanzee population as well as to the that of the villagers living in the region. In 2005, JGI initiated a forest monitoring program training and equipping community members with GPS-enabled Android smart phones and tablets for capturing observances of forest use. Combining NASA remote sensing data with citizen science observations facititated villages to develop land use plans, leading to improved decision making and facilitating the establishment of conservation areas. In 2016, the Metropolitan Group developed a 3-minute video detailing the motivation of this cooperative project between NASA and JGI. The viedo shows footage of project activities in Tanzania along with planning meetings using NASA satellite data. The animations shown here were developed to support this production.

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CATS studies volcanic plumes, wildfires, and hurricanes

NASA's Cloud-Aerosol Transport System, or CATS, is a lidar remote-sensing instrument taking measurements of atmospheric aerosols and clouds from the International Space Station (ISS). Launched to the ISS in January 2015, CATS is specifically intended to demonstrate a low-cost, streamlined approach to developing ISS science payloads. The CATS mission extends the data record of space-based aerosol and cloud measurements to ensure the continuity of lidar climate observation. Data from CATS will help scientists model the structure of dust plumes and other atmospheric features, which can travel far distances and impact air quality. Climate scientists will also use the CATS data, along with data from other Earth-observing instruments, to look at trends and interactions in clouds and aerosols over time. Calbco Eruption CATS and the ISS provide critical measurements of volcanic plume heights. In late April 2015, the Calbuco Volcano in Chile erupted multiple times; sending plumes of sulfur dioxide and ash into the upper troposphere. Volcanic plumes pose a substantial risk to aviation safety, leading to prolonged flight cancellations that cause ripple effects in the airline industry's economy and on personal travel. Rerouting air traffic requires accurate forecasts of volcanic plume transport from models such as the NASA GEOS-5 shown here. Utilizing the near-real-time data downlinking capabilities on ISS the CATS team can produce useful data products within six hours of data collection. Oregon Wildfires In addition to the aviation industry, fire management and air quality agencies use data from CATS mounted on the ISS. This visualization shows smoke that reached as high as 5 km. from wildfires in Oregon on August 18 2015. CATS has demonstrated the ability to detect the vertical structure of smoke plumes within an unprecedented 6 hour window of data collection. Accurate monitoring and forecasting of air quality requires these CATS vertical profiles measurements. Smoke plumes from wildfires are common over North America in summer months, causing deadly respiratory illnesses. Aerosols near the Earth's surface contribute to an annual death toll of 68,000 Americans and 3.3 million people globally. Hurricane Matthew CATS measurements at different local times over the tropics and mid-latitudes provide comprehensive spatial and temporal coverage of clouds associated with mid-latitude storms and convective systems. In this example, CATS observed outflow anvil cirrus and convective clouds near the core of Hurricane Matthew, which wreaked havoc on the Southeast U.S. and Caribbean in October this year. African Dust The CATS instrument uses different wavelengths which reflect differently when they hit aerosols, so comparing the returns from multiple wavelengths allows the scientists to distinguish dust from ice, smoke or other airborne particles. Over northern Africa, particles - likely dust kicked up by Saharan windstorms - reach heights of 2.5 to 3 miles (4 to 5 kilometers). Data from CATS will help scientists model the structure of dust plumes and other atmospheric features, which can travel far distances and impact air quality. Climate scientists will also use the CATS data, along with data from other Earth-observing instruments, to look at trends and interactions in clouds and aerosols over time.

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Artificial Intelligence Approaches To UCAV Autonomy. (arXiv:1701.07103v1 [cs.AI])

This paper covers a number of approaches that leverage Artificial Intelligence algorithms and techniques to aid Unmanned Combat Aerial Vehicle (UCAV) autonomy. An analysis of current approaches to autonomous control is provided followed by an exploration of how these techniques can be extended and enriched with AI techniques including Artificial Neural Networks (ANN), Ensembling and Reinforcement Learning (RL) to evolve control strategies for UCAVs.

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Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code. (arXiv:1701.07123v1 [cs.PL])

The current trends in next-generation exascale systems go towards integrating a wide range of specialized (co-)processors into traditional supercomputers. Due to the efficiency of heterogeneous systems in terms of Watts and FLOPS per surface unit, opening the access of heterogeneous platforms to a wider range of users is an important problem to be tackled. However, heterogeneous platforms limit the portability of the applications and increase development complexity due to the programming skills required. Program transformation can help make programming heterogeneous systems easier by defining a step-wise transformation process that translates a given initial code into a semantically equivalent final code, but adapted to a specific platform. Program transformation systems require the definition of efficient transformation strategies to tackle the combinatorial problem that emerges due to the large set of transformations applicable at each step of the process. In this paper we propose a machine learning-based approach to learn heuristics to define program transformation strategies. Our approach proposes a novel combination of reinforcement learning and classification methods to efficiently tackle the problems inherent to this type of systems. Preliminary results demonstrate the suitability of this approach.

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Fast Exact k-Means, k-Medians and Bregman Divergence Clustering in 1D. (arXiv:1701.07204v1 [cs.DS])

The $k$-Means clustering problem on $n$ points is NP-Hard for any dimension $d\ge 2$, however, for the 1D case there exist exact polynomial time algorithms. The current state of the art is a $O(kn^2)$ dynamic programming algorithm that uses $O(nk)$ space. We present a new algorithm improving this to $O(kn \log n)$ time and optimal $O(n)$ space. We generalize our algorithm to work for the absolute distance instead of squared distance and to work for any Bregman Divergence as well.

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Learn&Fuzz: Machine Learning for Input Fuzzing. (arXiv:1701.07232v1 [cs.AI])

Fuzzing consists of repeatedly testing an application with modified, or fuzzed, inputs with the goal of finding security vulnerabilities in input-parsing code. In this paper, we show how to automate the generation of an input grammar suitable for input fuzzing using sample inputs and neural-network-based statistical machine-learning techniques. We present a detailed case study with a complex input format, namely PDF, and a large complex security-critical parser for this format, namely, the PDF parser embedded in Microsoft's new Edge browser. We discuss (and measure) the tension between conflicting learning and fuzzing goals: learning wants to capture the structure of well-formed inputs, while fuzzing wants to break that structure in order to cover unexpected code paths and find bugs. We also present a new algorithm for this learn&fuzz challenge which uses a learnt input probability distribution to intelligently guide where to fuzz inputs.

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Hadith Web Browser Verification Extension. (arXiv:1701.07382v1 [cs.CY])

Internet users are more likely to ignore Internet content verification and more likely to share the content. When it comes to Islamic content, it is crucial to share and spread fake or inaccurate content. Even if the verification process of Islamic content is becoming easier every day, the Internet users generally ignore the verification step and jump into sharing the content. How many clicks away from users results? , this is the common question that is considered as a rule in modern website design. Internet users prefer the results to come to their page rather than to navigate it on their own. This paper presents a simple method of bringing hadith verification to the user web browser using web browser plugin.

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LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books. (arXiv:1701.07396v1 [cs.CV])

A semi-automatic open-source tool for layout analysis on early printed books is presented. LAREX uses a rule based connected components approach which is very fast, easily comprehensible for the user and allows an intuitive manual correction if necessary. The PageXML format is used to support integration into existing OCR workflows. Evaluations showed that LAREX provides an efficient and flexible way to segment pages of early printed books.

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Learning an attention model in an artificial visual system. (arXiv:1701.07398v1 [cs.CV])

The Human visual perception of the world is of a large fixed image that is highly detailed and sharp. However, receptor density in the retina is not uniform: a small central region called the fovea is very dense and exhibits high resolution, whereas a peripheral region around it has much lower spatial resolution. Thus, contrary to our perception, we are only able to observe a very small region around the line of sight with high resolution. The perception of a complete and stable view is aided by an attention mechanism that directs the eyes to the numerous points of interest within the scene. The eyes move between these targets in quick, unconscious movements, known as "saccades". Once a target is centered at the fovea, the eyes fixate for a fraction of a second while the visual system extracts the necessary information. An artificial visual system was built based on a fully recurrent neural network set within a reinforcement learning protocol, and learned to attend to regions of interest while solving a classification task. The model is consistent with several experimentally observed phenomena, and suggests novel predictions.

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Adaptive ADMM with Spectral Penalty Parameter Selection. (arXiv:1605.07246v4 [cs.LG] UPDATED)

The alternating direction method of multipliers (ADMM) is a versatile tool for solving a wide range of constrained optimization problems, with differentiable or non-differentiable objective functions. Unfortunately, its performance is highly sensitive to a penalty parameter, which makes ADMM often unreliable and hard to automate for a non-expert user. We tackle this weakness of ADMM by proposing a method to adaptively tune the penalty parameters to achieve fast convergence. The resulting adaptive ADMM (AADMM) algorithm, inspired by the successful Barzilai-Borwein spectral method for gradient descent, yields fast convergence and relative insensitivity to the initial stepsize and problem scaling.

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Query Complexity of Tournament Solutions. (arXiv:1611.06189v3 [cs.DS] UPDATED)

A directed graph where there is exactly one edge between every pair of vertices is called a {\em tournament}. Finding the "best" set of vertices of a tournament is a well studied problem in social choice theory. A {\em tournament solution} takes a tournament as input and outputs a subset of vertices of the input tournament. However, in many applications, for example, choosing the best set of drugs from a given set of drugs, the edges of the tournament are given only implicitly and knowing the orientation of an edge is costly. In such scenarios, we would like to know the best set of vertices (according to some tournament solution) by "querying" as few edges as possible. We, in this paper, precisely study this problem for commonly used tournament solutions: given an oracle access to the edges of a tournament T, find $f(T)$ by querying as few edges as possible, for a tournament solution f. We first show that the set of Condorcet non-losers in a tournament can be found by querying $2n-\lfloor \log n \rfloor -2$ edges only and this is tight in the sense that every algorithm for finding the set of Condorcet non-losers needs to query at least $2n-\lfloor \log n \rfloor -2$ edges in the worst case, where $n$ is the number of vertices in the input tournament. We then move on to study other popular tournament solutions and show that any algorithm for finding the Copeland set, the Slater set, the Markov set, the bipartisan set, the uncovered set, the Banks set, and the top cycle must query $\Omega(n^2)$ edges in the worst case. On the positive side, we are able to circumvent our strong query complexity lower bound results by proving that, if the size of the top cycle of the input tournament is at most $k$, then we can find all the tournament solutions mentioned above by querying $O(nk + \frac{n\log n}{\log(1-\frac{1}{k})})$ edges only.

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Overcoming catastrophic forgetting in neural networks. (arXiv:1612.00796v2 [cs.LG] UPDATED)

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Neural networks are not, in general, capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks which they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on the MNIST hand written digit dataset and by learning several Atari 2600 games sequentially.

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Ravens Image: FB Kyle Juszczyk's last name misspelled on back of Pro Bowl jersey; led the position with 37 catches for 266 yards (ESPN)

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anonymous tip lends hope

Diana Rojas said goodbye to her little girl and left for a meeting, and was never seen again. Now police say an anonymous phone call may finally help ...

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reflect: rename StructField.Anonymous into Embedded

reflect: rename StructField.Anonymous into Embedded #18786. Open. sbinet opened this Issue an hour ago · 0 comments ...

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[FD] InfiniteWP Client WordPress Plugin unauthenticated PHP Object injection vulnerability

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I'm a Signed Professional Musician currently working on my second retail album! All my thanks & love to family, friends and fans!
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January 25, 2017 at 12:24PM via Twitter http://twitter.com/IamDavidGuitard

Nodes wrongly marked as not accessible by anonymous user in wmlsitemap table and not ...

I checked the xmlsitemap table in the database and I found out that many nodes which are accessible by anonymous user have 0 in the access ...

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New Trojan Turns Thousands Of Linux Devices Into Proxy Servers

"Linux doesn't get viruses" — It's a Myth. A new Trojan has been discovered in the wild that turns Linux-based devices into proxy servers, which attackers use to protect their identity while launching cyber attacks from the hijacked systems. Dubbed Linux.Proxy.10, the Trojan was first spotted at the end of last year by the researchers from Russian security firm Doctor Web, who later

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Anonymous donor helps nearly 150 Iowa students

Communication Director Laura Sprague of the Johnston Community School District is grateful to the anonymous donor. "We can't thank you enough ...

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ISS Daily Summary Report – 1/24/2017

Story Time From Space Meniscus Demonstration: The crew narrated and recorded a video demonstration exploring how a fluid behaves in free fall (microgravity) and how acceleration compared to free fall will make fluid behave the same as it would on the ground (1-G environment). 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. Today’s demonstration was based on the children’s book Max Goes to the Space Station. Multi-user Droplet Combustion Apparatus (MDCA) Hardware Reconfiguration Part 2: Today the crew successfully completed the MDCA reconfiguration to the Cool Flames Investigation (CFI) setup.  The crew replaced the MDCA Needles, Igniters, Fiber Arm, and replace the fuel reservoirsThe crew then reinstalled the MDCA Chamber Insert Assembly (CIA) and reconnect Moderate Temperature Loop (MTL).  .  During the igniter exchange, a pin broke and remained in the receptacle.  The crewmember was able to extract the stuck pin and continue with the remaining operations. The CFI provides new insight into the phenomenon where some types of fuels initially burn very hot, then appear to go out — but they continue burning at a much lower temperature, with no visible flames (cool flames). Understanding cool flame combustion helps scientists develop new engines and fuels that are more efficient and less harmful to the environment.  Fluid Shifts Chibis Imaging Day 2: The 48S subject performed their Chibis imaging part 2 session. The subject donned the Chibis device, and while the crewmember was exposed to the negative pressure (pulling the fluid feetward), Cerebral and Cochlear Fluid Pressure (CCFP), Optical Coherence Tomography (OCT), Distortion Product Otoacoustic Emissions (DPOAE), and Tonometry exams were performed by an operator. During the DPOAE test, the crew had issues obtaining a good seal on the DPOAE probe tip in order to perform the test.  After troubleshooting, the crew attached a backup and was able to proceed.  Only one of the two DPOAE tests was able to be completed during the subject’s allowable time in Chibis.  Additionally, during data transfer power supplied by a 28 Volt DC to 120 Volt AC inverter was lost.  The loss of power resulted in the loss of the OCT data.  Due to the change in 48S landing, this session was considered a bonus data collection, and the loss of one DPOAE test point and OCT data is considered no impact.  A repeat of the R-45 Day Fluid Shifts activities will be scheduled within the necessary window.  The purpose of this investigation is to characterize the space flight-induced fluid shift, including intra- and extravascular shifts, intra- and extracellular shifts, changes in total body water and lower vs. upper body shifts. Noninvasive techniques are used to assess arterial and venous dimensions and flow parameters, ocular pressure and structure, and changes in intracranial pressure. Lower body negative pressure is being investigated for its ability to mitigate some of the effects of the space flight-induced fluid shift. Results from this investigation are expected to help define the causes of the ocular structure and vision changes associated with long duration space flight, and assist in the development of countermeasures.  Condensate Water Separator Assembly (CWSA) Maintenance:  During Columbus Desiccant Module inspection and replacement, executed in February of 2016, possible contamination was found on CWSA1 debris screen and residues on the CWSA1 cover.  Earlier today, the crew inspected, took samples and cleaned-up contamination found on various locations of the CWSA1 in Columbus. They also replaced the core of CWSA2.  The following ORU(s) were removed and replaced during the activity: Condensate Filter, Inlet Debris Screen, Fan Sub-Assembly, Air Check Valve, and Electronic Unit. CWSA2 failed at the end of July 2016 when the underspeed protection stopped the motor automatically. Internal Thermal Control System (ITCS) Sample Collection: The crew conducted ITCS fluid sampling from the Japanese Pressurized Module (JPM) and Node 3 (N3) Moderate Temperature Loop (MTL) sample ports. These samples will be returned to the ground on SpX-10 for analysis.  The return to ground samples are taken once a year to monitor the quality of the water in the ITCS loops.  Nitrogen Oxygen Recharge System (NORS) Nitrogen Transfer:  Today the crew installed a NORS Nitrogen recharge tank into the Airlock manifold and initiating Nitrogen transfer to the Airlock tanks. This is the first time the NORS has been used to transfer Nitrogen. Today’s Planned Activities All activities were completed unless otherwise noted. Biochemical urine test URISYS Hardware Stowage High Definition Video Camera Assembly 1 Activation in High Definition Mode Story Time from Space Meniscus Demonstration Setup ALGOMETRIYA. Pressure and Thermal Mode Algometry preparation for and measurement session CWSA sampling and cleaning. Story Time From Space Historical Photo Fluid Shifts Laptop RSOS Transfer Initiate water transfer from CWC-I to ЕДВ Fluid Shifts OCT Service Module Setup Alternate Progress 433 (DC1) Stowage and IMS Ops Fluid Shifts OCT Service Module Power On Fluid Shifts CCFP Service Module Configuration MELFI 3 Nitrogen Pressure Check Terminate water transfer from CWC-I to ЕДВ MELFI 2 Nitrogen Pressure Check Fluid Shifts DPOAE Service Module Setup MELFI 1 Nitrogen Pressure Check Columbus CWSA2 ORU Removal and Replace. FLUID SHIFTS. CHIBIS Setup Fluid Shifts Tonometry Service Module Setup Fluid Shifts Experiment Service Module Data Collection – Operator FLUID SHIFTS. Gathering Data in SM, Subject FLUID SHIFTS. Chibis Closeout Ops Fluid Shifts CCFP DPOAE Service Module End Story Time from Space Meniscus Experiment Photography and Stow Fluid Shifts Tonometry Service Module Stow Search for missing equipment in the RS (CTB with СЭП, КСПЭ, АСРД, ТВС equipment) Fluid Shifts OCT Service Module Power Off Fluid Shifts OCT Service Module Stow Alternate JEM Internal Thermal Control System (ITCS) Sample Collection Columbus CWSA2 Electronic Unit R&R Airlock Flexible Ventilation Duct configured to exchange air with Node 1 Nitrogen Oxygen Recharge System (NORS) […]

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A chat with the anonymous curator behind Scenic Simpsons

Scenic Simpsons is the work of an anonymous curator, whose knowledge of the Springfield area is second to none. The individual behind the account ...

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AlphaBay Dark Web Marketplace Hacked; Exposes Over 200,000 Private Messages

AlphaBay, possibly the largest active dark web marketplace at the moment, has paid a hacker after he successfully exploited vulnerabilities in the internal mailing system of the website and hijacked over 200,000 private unencrypted messages from several users. The hacker, using the pseudonym Cipher0007, disclosed two "high-risk bugs" two days ago on Reddit that allowed him to gain access to

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Ravens: G John Urschel says his passion for football outweighs risks of head trauma, recognizes it's "somewhat irrational" - HBO's Real Sports (ESPN)

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Last 6 Months, Anonymous

Last 6 Months, Anonymous. ... Access All Areas (The Secret Footballer, Bk. 4) · Anonymous · Faber & Faber. (Paperback): Biography & Autobiography ...

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Women with hairy legs, arms, underarms, etc. wanted

I'm looking for natural (unshaven) women to pose for very anonymous photos. This is a retro project focusing on hair (arms, legs, pubic, underarms, etc ...

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I have a new follower on Twitter

Aranca IP
Providing technology intelligence, #intellectualproperty (#patent) strategy and litigation support to enterprise and law firms.
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https://t.co/8TyxPZf5nr
Following: 1217 - Followers: 1677

January 24, 2017 at 09:54PM via Twitter http://twitter.com/Aranca_IP

Admin-Mandated Anonymous Link Expiration

We are interested in hearing from other K-12 school districts or higher education entities regarding their use of admin-mandated anonymous link.

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Space-Time Graph Modeling of Ride Requests Based on Real-World Data. (arXiv:1701.06635v1 [cs.AI])

This paper focuses on modeling ride requests and their variations over location and time, based on analyzing extensive real-world data from a ride-sharing service. We introduce a graph model that captures the spatial and temporal variability of ride requests and the potentials for ride pooling. We discover these ride request graphs exhibit a well known property called densification power law often found in real graphs modelling human behaviors. We show the pattern of ride requests and the potential of ride pooling for a city can be characterized by the densification factor of the ride request graphs. Previous works have shown that it is possible to automatically generate synthetic versions of these graphs that exhibit a given densification factor. We present an algorithm for automatic generation of synthetic ride request graphs that match quite well the densification factor of ride request graphs from actual ride request data.

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Perceptually Optimized Image Rendering. (arXiv:1701.06641v1 [cs.CV])

We develop a framework for rendering photographic images, taking into account display limitations, so as to optimize perceptual similarity between the rendered image and the original scene. We formulate this as a constrained optimization problem, in which we minimize a measure of perceptual dissimilarity, the Normalized Laplacian Pyramid Distance (NLPD), which mimics the early stage transformations of the human visual system. When rendering images acquired with higher dynamic range than that of the display, we find that the optimized solution boosts the contrast of low-contrast features without introducing significant artifacts, yielding results of comparable visual quality to current state-of-the art methods with no manual intervention or parameter settings. We also examine a variety of other display constraints, including limitations on minimum luminance (black point), mean luminance (as a proxy for energy consumption), and quantized luminance levels (halftoning). Finally, we show that the method may be used to enhance details and contrast of images degraded by optical scattering (e.g. fog).

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Imitating Driver Behavior with Generative Adversarial Networks. (arXiv:1701.06699v1 [cs.AI])

The ability to accurately predict and simulate human driving behavior is critical for the development of intelligent transportation systems. Traditional modeling methods have employed simple parametric models and behavioral cloning. This paper adopts a method for overcoming the problem of cascading errors inherent in prior approaches, resulting in realistic behavior that is robust to trajectory perturbations. We extend Generative Adversarial Imitation Learning to the training of recurrent policies, and we demonstrate that our model outperforms rule-based controllers and maximum likelihood models in realistic highway simulations. Our model both reproduces emergent behavior of human drivers, such as lane change rate, while maintaining realistic control over long time horizons.

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Proceedings of the 12th Workshop on User Interfaces for Theorem Provers. (arXiv:1701.06745v1 [cs.HC])

The UITP workshop series brings together researchers interested in designing, developing and evaluating user interfaces for automated reasoning tools, such as interactive proof assistants, automated theorem provers, model finders, tools for formal methods, and tools for visualising and manipulating logical formulas and proofs. The twelth edition of UITP took place in Coimbra, Portugal, and was part of the International Joint Conference on Automated Reasoning (IJCAR'16). The workshop consisted of an invited talk, six presentations of submitted papers and lively hands-on session for reasoning tools and their user-interface. These post-proceedings contain four contributed papers accepted for publication after a second round of reviewing after the workshop as well as the invited paper.

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Incorporating Prior Information in Compressive Online Robust Principal Component Analysis. (arXiv:1701.06852v1 [cs.IT])

We consider an online version of the robust Principle Component Analysis (PCA), which arises naturally in time-varying source separations such as video foreground-background separation. This paper proposes a compressive online robust PCA with prior information for recursively separating a sequences of frames into sparse and low-rank components from a small set of measurements. In contrast to conventional batch-based PCA, which processes all the frames directly, the proposed method processes measurements taken from each frame. Moreover, this method can efficiently incorporate multiple prior information, namely previous reconstructed frames, to improve the separation and thereafter, update the prior information for the next frame. We utilize multiple prior information by solving $n\text{-}\ell_{1}$ minimization for incorporating the previous sparse components and using incremental singular value decomposition ($\mathrm{SVD}$) for exploiting the previous low-rank components. We also establish theoretical bounds on the number of measurements required to guarantee successful separation under assumptions of static or slowly-changing low-rank components. Using numerical experiments, we evaluate our bounds and the performance of the proposed algorithm. The advantage of incorporating prior information is illustrated by adding in the comparision the performance of our algorithm without using prior information.

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Deep Network Guided Proof Search. (arXiv:1701.06972v1 [cs.AI])

Deep learning techniques lie at the heart of several significant AI advances in recent years including object recognition and detection, image captioning, machine translation, speech recognition and synthesis, and playing the game of Go. Automated first-order theorem provers can aid in the formalization and verification of mathematical theorems and play a crucial role in program analysis, theory reasoning, security, interpolation, and system verification. Here we suggest deep learning based guidance in the proof search of the theorem prover E. We train and compare several deep neural network models on the traces of existing ATP proofs of Mizar statements and use them to select processed clauses during proof search. We give experimental evidence that with a hybrid, two-phase approach, deep learning based guidance can significantly reduce the average number of proof search steps while increasing the number of theorems proved. Using a few proof guidance strategies that leverage deep neural networks, we have found first-order proofs of 7.36% of the first-order logic translations of the Mizar Mathematical Library theorems that did not previously have ATP generated proofs. This increases the ratio of statements in the corpus with ATP generated proofs from 56% to 59%.

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A Hierarchical Genetic Optimization of a Fuzzy Logic System for Flow Control in Micro Grids. (arXiv:1604.04789v2 [cs.AI] UPDATED)

Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are nowadays widely adopted as hybrid techniques in commercial and industrial environment. In this paper, we present an interesting application of the fuzzy-GA paradigm to Smart Grids. The main aim consists in performing decision making for power flow management tasks in the proposed microgrid model equipped by renewable sources and an energy storage system, taking into account the economical profit in energy trading with the main-grid. In particular, this study focuses on the application of a Hierarchical Genetic Algorithm (HGA) for tuning the Rule Base (RB) of a Fuzzy Inference System (FIS), trying to discover a minimal fuzzy rule set in a Fuzzy Logic Controller (FLC) adopted to perform decision making in the microgrid. The HGA rationale focuses on a particular encoding scheme, based on control genes and parametric genes applied to the optimization of the FIS parameters. This approach will be referred in the following as fuzzy-HGA. Results are compared with a simpler approach based on a classic fuzzy-GA scheme, where FIS parameters and rule weights are tuned, while the number of fuzzy rules is fixed in advance. Experiments show how the fuzzy-HGA approach adopted for the synthesis of the proposed controller outperforms the classic fuzzy-GA scheme, increasing the economic return of 67\% in the considered energy trading problem.

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Options Discovery with Budgeted Reinforcement Learning. (arXiv:1611.06824v2 [cs.LG] UPDATED)

We consider the problem of learning hierarchical policies for Reinforcement Learning able to discover options, an option corresponding to a sub-policy over a set of primitive actions. Different models have been proposed during the last decade that usually rely on a predefined set of options. We specifically address the problem of automatically discovering options in decision processes. We describe a new learning model called Budgeted Option Neural Network (BONN) able to discover options based on a budgeted learning objective. The BONN model is evaluated on different classical RL problems, demonstrating both quantitative and qualitative interesting results.

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BliStrTune: Hierarchical Invention of Theorem Proving Strategies. (arXiv:1611.08733v1 [cs.LO] CROSS LISTED)

Inventing targeted proof search strategies for specific problem sets is a difficult task. State-of-the-art automated theorem provers (ATPs) such as E allow a large number of user-specified proof search strategies described in a rich domain specific language. Several machine learning methods that invent strategies automatically for ATPs were proposed previously. One of them is the Blind Strategymaker (BliStr), a system for automated invention of ATP strategies.

In this paper we introduce BliStrTune -- a hierarchical extension of BliStr. BliStrTune allows exploring much larger space of E strategies by interleaving search for high-level parameters with their fine-tuning. We use BliStrTune to invent new strategies based also on new clause weight functions targeted at problems from large ITP libraries. We show that the new strategies significantly improve E's performance in solving problems from the Mizar Mathematical Library.

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Anonymous Youth

Anonymous Youth. Download Spotify. Popular. #, Song. Related Artists. Singles. · Hold On To Me. Do you have the Spotify app? No, get the ...

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Anonymous

Profile for: Anonymous. ... Anonymous's Offers. nyce short sleeve hoodie. $20. Fremont, CA. SELLER. Anonymous. Member Since January, 2017.

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Anonymous post support. ... sdlyu/flarum-ext-anonymous. Anonymous post support. http://ift.tt/2keTeWoanonymous · Source · Issues.

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Best anonymous image board

Futaba Channel (ふたば☆ちゃんねる), or "Futa. See more about Anonymous.. Anonymous · AnonIB // Best Anonymous Image Board. Save Learn more ...

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Different anonymous users cannot vote separately

Problem/Motivation I am working on a site using the Voting API module and the Like & Dislike module. I would like to allow anonymous users to vote.

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Cloud-AI: Artificially Intelligent System Found 10 Security Bugs in LinkedIn

2017 is the year of Artificial Intelligence (A.I.), Big Data, Virtual Reality (VR) and Cyber Security with major companies like Google, Facebook, Apple, IBM and Salesforce and technology pioneers like SpaceX founder Elon Musk investing in these hot technologies. Since everyone seems to be talking about the hottest trend — artificial intelligence and machine learning — broadly, 62 percent of

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What the Language You Tweet Says About Your Occupation. (arXiv:1701.06233v1 [cs.CY])

Many aspects of people's lives are proven to be deeply connected to their jobs. In this paper, we first investigate the distinct characteristics of major occupation categories based on tweets. From multiple social media platforms, we gather several types of user information. From users' LinkedIn webpages, we learn their proficiencies. To overcome the ambiguity of self-reported information, a soft clustering approach is applied to extract occupations from crowd-sourced data. Eight job categories are extracted, including Marketing, Administrator, Start-up, Editor, Software Engineer, Public Relation, Office Clerk, and Designer. Meanwhile, users' posts on Twitter provide cues for understanding their linguistic styles, interests, and personalities. Our results suggest that people of different jobs have unique tendencies in certain language styles and interests. Our results also clearly reveal distinctive levels in terms of Big Five Traits for different jobs. Finally, a classifier is built to predict job types based on the features extracted from tweets. A high accuracy indicates a strong discrimination power of language features for job prediction task.

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ISS Daily Summary Report – 1/23/2017

Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI)-1 Autostop and Recovery: MELFI-1 went to Autostop mode Friday evening (during crew sleep). The Cold Stowage team performed troubleshooting including a rack reboot but remained in autostop.   Failure signature had anomalous values on the 120 and 28 volt inputs, as well as failure statuses on multiple Motor Drive Electronics (MDE) status bits. This is similar to the power supply failures seen in previous Electronic Unit failures (Failures #2, 3 & 5). The decision was made to perform an Electronic Unit swap.  The failed unit (S/N 15) was replaced by the MELFI 1 Spare (S/N 11).  During the repair activity, the crew released a small amount of ITCS fluid when removing the return line QD from the UIP. The crew corrected the QD with the standard rotate and tap steps. They also noted significant moisture around the water connections at the Brayton motor QDs in the coldbox, however this is expected as the cold lines collect condensate. The crew commented on corrosion around one of the electrical connections in the coldbox area.  Photos were taken for review.  When installing the Spare EU in the Prime position, the crew was unable to seat the bottom right fastener (#2 in the procedure).  The remaining 7 fasteners were connected and the EU is secure in the rack.  The warmest temperatures seen per Dewar were: Dewar 1: -75C, Dewar 2: -73.9C, Dewar 3: -76.4C, Dewar 4: +3.5C, and ground teams do not anticipate any loss of science from this EU failure.  Light Microscopy Module (LMM) Biophysics 1 Configuration: Earlier today the crew configured the LMM for the Biophysics science runs in the Fluids Integrated Rack (FIR). The Advanced Colloids Experiment-Temperature-1 (ACE-T-1) Module was removed from the FIR then the LMM Control Base and LMM objective lenses were installed and configured inside the LMM Auxiliary Fluids Container (AFC). Finally the LMM Petri Base was installed into the AFC. LMM Biophysics 1 (The Effect of Macromolecular Transport of Microgravity Protein Crystallization) will launch on SpaceX-10. When installed, investigators will use the results from LMM Biophysics 1 to examine the movement of single protein molecules in microgravity. By studying the crystals of a higher quality that can be grown in microgravity, scientists will be able to better understand their structure and how they work.  Fluid Shifts Chibis Imaging Day 2: One of the 49S subjects performed their second portion of Chibis imaging. The subject donned the Chibis device, and while the crewmember was exposed to the negative pressure (pulling the fluid feetward), then with ground and onboard operator support they configured the Optical Coherence Tomography (OCT) and the Distortion Product Otoacoustic Emission (DPOAE) hardware, before completing a DPOAE test, OCT exam, and a Tonometry exam. The purpose of this investigation is to characterize the space flight-induced fluid shift, including intra- and extravascular shifts, intra- and extracellular shifts, changes in total body water and lower vs. upper body shifts. Noninvasive techniques are used to assess arterial and venous dimensions and flow parameters, ocular pressure and structure, and changes in intracranial pressure. Lower body negative pressure is being investigated for its ability to mitigate some of the effects of the space flight-induced fluid shift. Results from this investigation are expected to help define the causes of the ocular structure and vision changes associated with long duration space flight, and assist in the development of countermeasures.  Multi-user Droplet Combustion Apparatus (MDCA) Reconfiguration: After the successful removal of the MDCA from the Combustion Integration Rack (CIR) last week, the crew began the reconfiguration to the Cool Flames Investigation (CFI). Today, the crew removed the MDCA Chamber Insert Assembly (CIA) from the Combustion Chamber and restrained it to the MWA. The crew then disabled the ignitor pressure switch and replaced the MDCA internal components. The Combustion Chamber was then reinstalled in the CIR. Reconfiguration activities will continue tomorrow.  CFI provides new insight into the phenomenon where some types of fuels initially burn very hot, then appear to go out — but they continue burning at a much lower temperature, with no visible flames (cool flames). Understanding cool flame combustion helps scientists develop new engines and fuels that are more efficient and less harmful to the environment. Node 3 (N3) Carbon Dioxide Removal Assembly (CDRA) Research Valve Install:  The crew removed the Air Selector Valve (ASV)-104 valve from the N3 CDRA and install a new CDRA Developmental Research Valve.  This new Research Valve was developed to improve CDRA valve operational lifetime.  The valve was delivered on HTV-6 and has the same interfaces, form, fit and function as the existing valve design.  The removed ASV-104 valve will be stowed as an on-orbit spare.  Space Station Remote Manipulator System (SSRMS) Operations:  Overnight, the Robotics Ground Controllers powered on the SSRMS and maneuvered it to grapple the H-II Transfer Vehicle 6 (HTV6) External Platform (EP) grappled by the Mobile Base System (MBS) Payload/Orbital Replacement Unit (ORU) Accommodation (POA).  After the POA released the EP, they maneuvered SSRMS to move and insert EP in the HTV6 Unpressurized Logistics Carrier (ULC) where it was latched and SSRMS was maneuvered to release the EP.   Finally, SSRMS was maneuvered to perform a survey of the HTV6 Earth Sensor Assembly (ESA) unit B before grappling HTV6 Flight Releasable Grapple Fixture (FRGF) in preparation of HTV6 release and re-entry scheduled for Friday 27-January.  Internal Thermal Control System (ITCS) Sample Collection: The crew conducted ITCS fluid sampling from the Lab Low Temperature Loop (LTL) sample port. This maintenance is performed periodically to monitor the quality of the water in the ITCS loops. Today’s Planned Activities All activities were compelted unless otherwise noted. Fine Motor Skills Experiment Test Fluid Shifts Ultrasound 2 HRF Rack 1 Setup Power On From Cargo Transfer Bag Multi-purpose Small Payload Rack (MSPR) /Group Combustion Module (GCM) Component Activation Regeneration of Micropurification unit (БМП) Ф1cartridge (begin) Combustion Integrated Rack Hardware Gather FLUID SHIFTS. Comm configuration on RS Fluid Shifts Ultrasound 2 Data Export Alternate FLUID SHIFTS. Gathering and Connecting Equipment for […]

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ENIGMA: Efficient Learning-based Inference Guiding Machine. (arXiv:1701.06532v1 [cs.LO])

ENIGMA is a learning-based method for guiding given clause selection in saturation-based theorem provers. Clauses from many proof searches are classified as positive and negative based on their participation in the proofs. An efficient classification model is trained on this data, using fast feature-based characterization of the clauses . The learned model is then tightly linked with the core prover and used as a basis of a new parameterized evaluation heuristic that provides fast ranking of all generated clauses. The approach is evaluated on the E prover and the CASC 2016 AIM benchmark, showing a large increase of E's performance.

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I have a new follower on Twitter

scott page
Musician +Technologist + Business #Saxophonist for #PinkFloyd #Toto #Supertramp Passions: #CrowdSourcing , #growthhacking #BrandBuilding

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Following: 398140 - Followers: 412834

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Gamblers anonymous step workbook

The 21 Steps to STOP Gambling System and Workbooks will navigate you. .. survey of Gamblers Anonymous members found 48 percent had ...

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Nasty Android Malware that Infected Millions Returns to Google Play Store

HummingBad – an Android-based malware that infected over 10 million Android devices around the world last year and made its gang an estimated US$300,000 per month at its peak – has made a comeback. Security researchers have discovered a new variant of the HummingBad malware hiding in more than 20 Android apps on Google Play Store. The infected apps were already downloaded by over 12 Million

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Re: [FD] Executable installers are vulnerable^WEVIL (case 46): Pelles C allows arbitrary code execution

[FD] APPLE-SA-2017-01-23-7 iTunes for Windows 12.5.5

-----BEGIN PGP SIGNED MESSAGE-

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[FD] WD My Cloud Mirror 2.11.153 RCE and Authentication Bypass

# Exploit Title: WD My Cloud Mirror 2.11.153 RCE and Authentication Bypass # Date: 24.01.2017 # Software Link: https://www.wdc.com # Exploit Author: Kacper Szurek # Contact: https://twitter.com/KacperSzurek # Website: http://ift.tt/2iHZPtU # Category: local 1. Description It’s possible to execute arbitrary commands using login form because `exec()` function is used without `escapeshellarg()`. It's possible to bypass login form because function only check if `$_COOKIE['username']` and `$_COOKIE['isAdmin']` exist. http://ift.tt/2j8SP6e 2. Proof of Concept For RCE simply use as username: a" || your_command_to_execute || " For authentication bypass set COOKIES: username=1; isAdmin=1 and then visit for example php/users.php

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China makes VPNs illegal to tighten its Great Firewall

China is long known for its strict Internet censorship laws through the Great Firewall of China – China's Golden Shield project that employs a variety of tricks to censor Internet and block access to various foreign websites in the country by its government. The Great Firewall has blocked some 171 out of the world's 1,000 top websites, including Google, Facebook, Twitter, Tumblr, Dropbox, and

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Anonymous proxy

An anonymizer or an anonymous proxy is a tool that attempts to make activity on the Internet untraceable. It is a proxy server computer that acts as an .

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Anonymous user 27f4bc

Name, Anonymous user 27f4bc. User since, January 23, 2017. Number of add-ons developed, 1 theme. Average rating of developer's add-ons, Not ...

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Atmospheric River Slams California

After more than four years of drought, Californians may wonder where the current rain is coming from. Using satellites, NASA scientists have a unique view of the sources of precipitation, and how it reaches the western United States. Rain is often carried by narrow tendrils of moisture called atmospheric rivers that occur all over the world, shown here in white. The atmospheric rivers that affect the western United States are known as the Pineapple Express because they transport water vapor from as far south as Hawaii to California. When the moisture reaches land, it is forced up over the hills and mountains where it cools, producing significant rainfall. This type of precipitation provides about 40 percent of the state's annual water supply.

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Monitoring Hurricane Matthew

Hurricane Matthew ravaged the Caribbean and United States from late September to early October 2016. Earth observing satellites provide insights into Matthew's rapid intensification and fast decline. This show was designed for the NASA Hyperwall to be shown at the 2017 American Meteorlogical Society (AMS) Conference. The show highlight's NASA's GPM Core System that works hand-in-hand with numerous other datasets, including model runs.

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Category 4 Hurricane Matthew on October 2, 2016

NASA's Global Precipitation Measurement mission or GPM core observatory satellite flew over Hurricane Matthew as the category 4 hurricane on October 2, 2016 shortly after it downgraded from a category 5 hurricane. 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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Ravens LB C.J. Mosley decides against playing in 2017 Pro Bowl; has been replaced by Steelers LB Ryan Shazier (ESPN)

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I have a new follower on Twitter

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Following: 98 - Followers: 145

January 23, 2017 at 11:19PM via Twitter http://twitter.com/AutoHomeIO

I have a new follower on Twitter

IIoT, AI & Big Data
Articles\Insights on #IIoT,#IoT,#ML,#BigData,#Energy,#Industry40,#DataScience,#Python,#Predictive,#AI,#InfoSec,#Blockchain & #Middleware
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Following: 833 - Followers: 2523

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I have a new follower on Twitter

Out-Smarts
Making digital marketing easy for small to mid size businesses. We provide Strategy, Social Media, Websites, SEO, Email Marketing Services.
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January 23, 2017 at 10:15PM via Twitter http://twitter.com/OutSmarts

I have a new follower on Twitter

Bobby Kraft
Entrepreneur, relationship builder, multichannel expert...Founder of @NewEdgeMktgLLC and CEO of @OmniViewSports. Make it happen!
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January 23, 2017 at 09:45PM via Twitter http://twitter.com/bobbykraft

I have a new follower on Twitter

Growth AI
Get 1 new actionable growth opportunity per day https://t.co/Ik2HICFW4y
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Following: 2565 - Followers: 2565

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Interactive Learning from Policy-Dependent Human Feedback. (arXiv:1701.06049v1 [cs.AI])

For agents and robots to become more useful, they must be able to quickly learn from non-technical users. This paper investigates the problem of interactively learning behaviors communicated by a human teacher using positive and negative feedback. Much previous work on this problem has made the assumption that people provide feedback for decisions that is dependent on the behavior they are teaching and is independent from the learner's current policy. We present empirical results that show this assumption to be false---whether human trainers give a positive or negative feedback for a decision is influenced by the learner's current policy. We argue that policy-dependent feedback, in addition to being commonplace, enables useful training strategies from which agents should benefit. Based on this insight, we introduce Convergent Actor-Critic by Humans (COACH), an algorithm for learning from policy-dependent feedback that converges to a local optimum. Finally, we demonstrate that COACH can successfully learn multiple behaviors on a physical robot, even with noisy image features.

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Label Propagation on K-partite Graphs with Heterophily. (arXiv:1701.06075v1 [cs.LG])

In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption. Homophily label propagation (i.e., two connected nodes share similar labels) in homogeneous graph (with same types of vertices and relations) has been extensively studied before. Unfortunately, real-life networks are heterogeneous, they contain different types of vertices (e.g., users, images, texts) and relations (e.g., friendships, co-tagging) and allow for each node to propagate both the same and opposite copy of labels to its neighbors. We propose a $\mathcal{K}$-partite label propagation model to handle the mystifying combination of heterogeneous nodes/relations and heterophily propagation. With this model, we develop a novel label inference algorithm framework with update rules in near-linear time complexity. Since real networks change over time, we devise an incremental approach, which supports fast updates for both new data and evidence (e.g., ground truth labels) with guaranteed efficiency. We further provide a utility function to automatically determine whether an incremental or a re-modeling approach is favored. Extensive experiments on real datasets have verified the effectiveness and efficiency of our approach, and its superiority over the state-of-the-art label propagation methods.

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Binary Matrix Guessing Problem. (arXiv:1701.06167v1 [cs.AI])

We introduce the Binary Matrix Guessing Problem and provide two algorithms to solve this problem. The first algorithm we introduce is Elementwise Probing Algorithm (EPA) which is very fast under a score which utilizes Frobenius Distance. The second algorithm is Additive Reinforcement Learning Algorithm which combines ideas from perceptron algorithm and reinforcement learning algorithm. This algorithm is significantly slower compared to first one, but less restrictive and generalizes better. We compare computational performance of both algorithms and provide numerical results.

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A Multichannel Convolutional Neural Network For Cross-language Dialog State Tracking. (arXiv:1701.06247v1 [cs.CL])

The fifth Dialog State Tracking Challenge (DSTC5) introduces a new cross-language dialog state tracking scenario, where the participants are asked to build their trackers based on the English training corpus, while evaluating them with the unlabeled Chinese corpus. Although the computer-generated translations for both English and Chinese corpus are provided in the dataset, these translations contain errors and careless use of them can easily hurt the performance of the built trackers. To address this problem, we propose a multichannel Convolutional Neural Networks (CNN) architecture, in which we treat English and Chinese language as different input channels of one single CNN model. In the evaluation of DSTC5, we found that such multichannel architecture can effectively improve the robustness against translation errors. Additionally, our method for DSTC5 is purely machine learning based and requires no prior knowledge about the target language. We consider this a desirable property for building a tracker in the cross-language context, as not every developer will be familiar with both languages.

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Constraint programming for planning test campaigns of communications satellites. (arXiv:1701.06388v1 [cs.AI])

The payload of communications satellites must go through a series of tests to assert their ability to survive in space. Each test involves some equipment of the payload to be active, which has an impact on the temperature of the payload. Sequencing these tests in a way that ensures the thermal stability of the payload and minimizes the overall duration of the test campaign is a very important objective for satellite manufacturers. The problem can be decomposed in two sub-problems corresponding to two objectives: First, the number of distinct configurations necessary to run the tests must be minimized. This can be modeled as packing the tests into configurations, and we introduce a set of implied constraints to improve the lower bound of the model. Second, tests must be sequenced so that the number of times an equipment unit has to be switched on or off is minimized. We model this aspect using the constraint Switch, where a buffer with limited capacity represents the currently active equipment units, and we introduce an improvement of the propagation algorithm for this constraint. We then introduce a search strategy in which we sequentially solve the sub-problems (packing and sequencing). Experiments conducted on real and random instances show the respective interest of our contributions.

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Identification of Unmodeled Objects from Symbolic Descriptions. (arXiv:1701.06450v1 [stat.ML])

Successful human-robot cooperation hinges on each agent's ability to process and exchange information about the shared environment and the task at hand. Human communication is primarily based on symbolic abstractions of object properties, rather than precise quantitative measures. A comprehensive robotic framework thus requires an integrated communication module which is able to establish a link and convert between perceptual and abstract information.

The ability to interpret composite symbolic descriptions enables an autonomous agent to a) operate in unstructured and cluttered environments, in tasks which involve unmodeled or never seen before objects; and b) exploit the aggregation of multiple symbolic properties as an instance of ensemble learning, to improve identification performance even when the individual predicates encode generic information or are imprecisely grounded.

We propose a discriminative probabilistic model which interprets symbolic descriptions to identify the referent object contextually w.r.t.\ the structure of the environment and other objects. The model is trained using a collected dataset of identifications, and its performance is evaluated by quantitative measures and a live demo developed on the PR2 robot platform, which integrates elements of perception, object extraction, object identification and grasping.

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Detecting Falls with X-Factor Hidden Markov Models. (arXiv:1504.02141v5 [cs.LG] UPDATED)

Identification of falls while performing normal activities of daily living (ADL) is important to ensure personal safety and well-being. However, falling is a short term activity that occurs infrequently. This poses a challenge to traditional classification algorithms, because there may be very little training data for falls (or none at all). This paper proposes an approach for the identification of falls using a wearable device in the absence of training data for falls but with plentiful data for normal ADL. We propose three `X-Factor' Hidden Markov Model (XHMMs) approaches. The XHMMs model unseen falls using "inflated" output covariances (observation models). To estimate the inflated covariances, we propose a novel cross validation method to remove "outliers" from the normal ADL that serve as proxies for the unseen falls and allow learning the XHMMs using only normal activities. We tested the proposed XHMM approaches on two activity recognition datasets and show high detection rates for falls in the absence of fall-specific training data. We show that the traditional method of choosing a threshold based on maximum of negative of log-likelihood to identify unseen falls is ill-posed for this problem. We also show that supervised classification methods perform poorly when very limited fall data are available during the training phase.

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The Parallel Knowledge Gradient Method for Batch Bayesian Optimization. (arXiv:1606.04414v3 [stat.ML] UPDATED)

In many applications of black-box optimization, one can evaluate multiple points simultaneously, e.g. when evaluating the performances of several different neural network architectures in a parallel computing environment. In this paper, we develop a novel batch Bayesian optimization algorithm --- the parallel knowledge gradient method. By construction, this method provides the one-step Bayes optimal batch of points to sample. We provide an efficient strategy for computing this Bayes-optimal batch of points, and we demonstrate that the parallel knowledge gradient method finds global optima significantly faster than previous batch Bayesian optimization algorithms on both synthetic test functions and when tuning hyperparameters of practical machine learning algorithms, especially when function evaluations are noisy.

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Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates. (arXiv:1607.08316v2 [cs.AI] UPDATED)

Automatically searching for optimal hyperparameter configurations is of crucial importance for applying deep learning algorithms in practice. Recently, Bayesian optimization has been proposed for optimizing hyperparameters of various machine learning algorithms. Those methods adopt probabilistic surrogate models like Gaussian processes to approximate and minimize the validation error function of hyperparameter values. However, probabilistic surrogates require accurate estimates of sufficient statistics (e.g., covariance) of the error distribution and thus need many function evaluations with a sizeable number of hyperparameters. This makes them inefficient for optimizing hyperparameters of deep learning algorithms, which are highly expensive to evaluate. In this work, we propose a new deterministic and efficient hyperparameter optimization method that employs radial basis functions as error surrogates. The proposed mixed integer algorithm, called HORD, searches the surrogate for the most promising hyperparameter values through dynamic coordinate search and requires many fewer function evaluations. HORD does well in low dimensions but it is exceptionally better in higher dimensions. Extensive evaluations on MNIST and CIFAR-10 for four deep neural networks demonstrate HORD significantly outperforms the well-established Bayesian optimization methods such as GP, SMAC, and TPE. For instance, on average, HORD is more than 6 times faster than GP-EI in obtaining the best configuration of 19 hyperparameters.

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A Novel Progressive Learning Technique for Multi-class Classification. (arXiv:1609.00085v2 [cs.LG] UPDATED)

In this paper, a progressive learning technique for multi-class classification is proposed. This newly developed learning technique is independent of the number of class constraints and it can learn new classes while still retaining the knowledge of previous classes. Whenever a new class (non-native to the knowledge learnt thus far) is encountered, the neural network structure gets remodeled automatically by facilitating new neurons and interconnections, and the parameters are calculated in such a way that it retains the knowledge learnt thus far. This technique is suitable for real-world applications where the number of classes is often unknown and online learning from real-time data is required. The consistency and the complexity of the progressive learning technique are analyzed. Several standard datasets are used to evaluate the performance of the developed technique. A comparative study shows that the developed technique is superior.

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