Orioles Video: Mark Trumbo sends a 2-run homer to left, becomes 1st in majors to hit 30 HRs in 5-2 win over Indians (ESPN)

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Trumps Anonymous – a 12 Step Program

Trump supporters: It's been a four day hate-binge, and right now we're guessing you feel pretty hung-over. The rants, the controversies, the endless ...

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Ravens Video: QB Joe Flacco tries his luck as a car salesman, finds out his skills are better suited for football (ESPN)

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Orioles: P Ubaldo Jimenez placed on the paternity leave list, P Tyler Wilson recalled from Triple-A Norfolk (ESPN)

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Ravens: LB Terrell Suggs, LB Elvis Dumervil, WR Steve Smith Sr., WR Breshad Perriman among 6 placed on PUP list Saturday (ESPN)

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Ready for a sunny day

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Last of the first potato harvest, apparently some decided to grow out of container, and are still doing good.

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Force login for Anonymous users

git clone --branch 8.x-1.x http://ift.tt/29UnyjX force_login_for_anonymous_users cd force_login_for_anonymous_users.

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Anonymous Posting: Error posting

I am run a very successful bbPress forum where I allow anonymous posting. I have never seen this error before so I am a bit confused. About a week ...

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Galaxy Cluster Abell S1063 and Beyond

Some 4 billion light-years away, galaxies of massive Abell S1063 cluster near the center of this sharp Hubble Space Telescope snapshot. But the fainter bluish arcs are magnified images of galaxies that lie far beyond Abell S1063. About twice as distant, their otherwise undetected light is magnified and distorted by the cluster's largely unseen gravitational mass, approximately 100 trillion times the mass of the Sun. Providing a tantalizing glimpse of galaxies in the early universe, the effect is known as gravitational lensing. A consequence of warped spacetime it was first predicted by Einstein a century ago. The Hubble image is part of the Frontier Fields program to explore the Final Frontier. via NASA http://ift.tt/2alHNLW

Orioles Video: Mark Trumbo uncorks his league-leading 29th homer to left field, brings in 3 runs in 5-1 win vs. Indians (ESPN)

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Anonymous mask

Anonymous mask in Oakland, CA. ... a simpler way to buy and sell locally. Get the free app. OfferUp for Android · OfferUp for iPhone. Anonymous mask.

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Orioles: OF Joey Rickard (right thumb) placed on the 15-day DL, OF Dariel Alvarez recalled from Triple-A Norfolk (ESPN)

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Anonymous Twirling Dancers Arrive to Ease Tensions at the Republican National Convention

Anonymous Twirling Dancers Arrive to Ease Tensions at the Republican ... Luckily, some anonymous twirling dancers arrived on the scene to help ...

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Verizon Set to Buy Yahoo for $5 Billion — Here's Why a Telecom is so Interested!

Finally, Someone has come forward to buy Yahoo! Guess Who? The telecommunication giant Verizon. Yes, Verizon Communications Inc. is reportedly closing in on a deal to acquire Yahoo’s core business for about $5 Billion, according to a report from Bloomberg. <!-- adsense --> Since the agreement between the companies has not been finalized, it is unclear at this moment that which Yahoo's assets

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Just made the bed....

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Force login for Anonymous users

So you want to always redirect anonymous users to login page a.k.a. mandatory login for all unauthorized users. Look no further. You can also ...

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The VPPA and PII: Is Geolocation Another Anonymous Identifier?

An article by Reed Freeman and Joseph Jerome, published in Bloomberg BNA's Privacy and Security Law Report, explores how personally ...

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Hillary Leaks Series: Wikileaks releases 20,000 DNC Emails

Today, whistleblowing website Wikileaks has finally published around 20,000 e-mails, which contains more than 8,000 attachments from the US Democratic National Committee (DMC). The new trove of documents apparently pilfered from the DMC released after Wikileaks yesterday announced via its official Twitter account that a "series" about Hillary Clinton is coming soon. <!-- adsense --> The

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ISS Daily Summary Report – 07/21/16

Dragon Operations:  The crew was scheduled to ingress and configure Dragon for on-orbit operations today, however, these tasks were completed yesterday. Today they transferred critical cargo and unpacked double cold bags to retrieve science as well as transferring 2 “Polar” freezers from Dragon into the EXPRESS rack locations that had been prepared for them.  Mouse Epigenetics Setup Operations: Crewmembers reconfigured the Cell Biology Experiment Facility (CBEF) to establish an alternate power resource from the Utility Outlet Panel (UOP) and transferred the mice from the Transportation Cage Unit (which was used to house them during launch) into the Mouse Habitat Cage Units onboard ISS. The Mouse Epigenetics investigation studies altered gene expression patterns in the organs of male mice that spend one month in space and also examines changes in the deoxyribonucleic acid (DNA) of their offspring. Results from the investigation identify genetic alterations that happen after exposure to the microgravity environment of space. Heart Cells Habitat Preparation and Sample Installation: Today, the Heart Cells samples were removed from the SpaceX-9 Dragon capsule and transferred to SABL 2.  The crew then prepared for operations in SABL 1 by configuring the carbon dioxide (CO2) Incubator Controller and installing hardware inside.  The samples were placed in active temperature and CO2 control when they were transferred from SABL 2 into SABL 1. The Heart Cells investigation studies the human heart, specifically how heart muscle tissue contracts, grows and changes (gene expression) in microgravity and how those changes vary between subjects. Understanding how heart muscle cells, or cardiomyocytes, change in space improves efforts for studying disease, screening drugs and conducting cell replacement therapy for future space missions. NanoRacks Platform-1 Module Install: Six NanoRack Modules were installed on NanoRacks Platform 1. NanoRacks Modules 41 (Awty-BE-HDPE Rad Shielding), 43 (Slime Mold), and 44 (Awty-Yeast Cell Growth in a Microgravity Environment) were configured on the left side of the NanoRack Platform and Modules 45 (Duchesne-Light Wavelengths on Algae Production), 46 (Duchesne-Plant Growth Chamber), and 69 (Silver Electrolysis/ Eagelcrest) were configured on the right side. The NanoRack Platform is a multipurpose research facility that supports NanoRacks Modules by providing power and data transfer capabilities to operate investigations in microgravity. NanoRacks Module 9: The crew performed tasks for the NanoRack Module-9 experiment by activating, deactivating, and shaking the mixture tubes. This experiment is a collection of student research projects utilizing the NanoRacks Mixsticks. Student teams from across the United States design their own experiments using flight approved fluids and materials.  Fluids Integration Rack (FIR) RPC trip troubleshooting – RPCM LA2A3B-G RPC-2 (FIR Main Power) tripped in late June.  The payload that was running inside FIR at the time (MicroChannel Diffusion) was able to complete their operations on auxiliary power.  Troubleshooting on the RPC trip was completed today.  FIR was initially powered using auxiliary power, but gradually transitioned to main power. FIR was then deactivated and re-activated in a nominal configuration. No RPC trips were seen throughout the troubleshooting. FIR was deactivated upon completion. There are currently no liens on future use of FIR main power. Today’s Planned Activities All activities were completed unless otherwise noted. NEUROIMMUNITET. Saliva Sample Psychological Testing (Session 1) r/g 2857 CORRECTSIYA. NEUROIMMUNITET. Blood Collection r/g 2857 NEUROIMMUNITET. Venous blood sample processing (smear)  r/g 2857 CORRECTSIYA. NEUROIMMUNITET. Venous blood sample processing using Plasma-03 centrifuge / r/g 2857 RUEXP Blood Sample Insertion into MELFI CORRECTSIYA. NEUROIMMUNITET. Handover to USOS for MELFI Insertion / r/g 2857 CORRECTSIYA. NEUROIMMUNITET. Closeout Ops / r/g 2857 Crew Quarters Closing Doors On MCC Go Regeneration of БМП Ф1 Micropurification Cartridge (start) DRAGON Ingress SpX9 Air Sampling using АК-1М sampler prior to Air Duct Installation r/g 2858 24-hour BP monitoring (start) / r/g 2856 NEUROIMMUNITET. Psychological Test / r/g 2857 Sprint Exercise, Optional 24-hour ECG Monitoring (start) / r/g 2855 Dragon Arrival Photos Dragon Center Stack Transfers NEUROIMMUNITET. Hair Sample / r/g 2857 CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2822 Familiarization with Auxiliary Computer System r/g 2863 PRODUTSENT. Removal from ТБУ-В No.02 (+30 deg C), switching to +26 deg C and transfer to ТБУ-В No.04 r/g 2865 SEISMOPROGNOZ. Downlink data from Control and Data Acquisition Module (МКСД) HDD (start) r/g 2224 Crew time for ISS adaptation and orientation Photography of Plume Impingement and Deposit Monitoring Unit (БКДО) position on MRM2 through SM window No.13  (after Progress 433 docking) / r/g 1348 IDENTIFICATION. Copy ИМУ-Ц micro-accelerometer data to laptop / r/g 1589 XF305 Camcorder Settings Adjustment Early unstow items CBEF Backup power reconfig CARDIOVECTOR. Experiment Ops r/g 2859 Preventive Maintenance of Docking Assembly (АСП)/ Hatch Sealing Mechanisms (DC1) and Progress 433 Hatch CASKAD. Completion of Anabioz P/L battery charge / r/g 2848 Dragon Double Cold Bag Unpack BODYM  Equipment Setup MOUSE. Item gathering STEM CELL Insertion of bio-dosimeters into MELFI UOP. Activation HRTCEL. Installation of СО2 Controller in SABL IMS Delta File Prep UOP. Activation XF305 Camcorder Settings Adjustment GLOVE BOX. Installation of Glove Box CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2822 Filling (separation) of EDV [KOB] for Elektron Multi-Purpose Small Payload Rack (MSPR) Hard Drive Exchange Restow Dragon Vestibule Outfitting Kit (VOK) Polar Transfer and Installation in EXPRESS rack СОЖ Maintenance MSG Installation of Gloves in the Glove Box Polar Transfer and Installation in EXPRESS rack OTKLIK. Hardware Monitoring / r/g 1588 SEISMOPROGNOZ. Download data from Control and Data Acquisition Module (МКСД) HDD (end) and start backup r/g 2224 NANO Viewing OBT materials for MODULE-9 NANO Experiment ops and video. CORRECTSIYA. NEUROIMMUNITET. Experiment setup / r/g 2864 MOUSE. Module Transfer to JPM INTERACTION-2. Experiment Ops / r/g 2861 NANO – Module installation Dragon Double Cold Bag Unpack Vacuum Cleaning area behind panels 405, 406 and MRM1 Interior CASKAD. Glovebox-S hardware prep r/g 2866 RWS Power Down POLAR sample transfer 1 Dragon Cargo Operations Conference CEVIS Exercise INTERACTION-2. . Experiment Ops / r/g 2862 POLAR sample transfer 1 GLOVE. Close-out ops with the Glove Box HRTCEL. Experiment Setup On MCC Go Regeneration of БМП Ф1 Absorption Cartridge (end) NEUROIMMUNITET. Saliva Sample. Psychological Test / r/g 2857 NEUROIMMUNITET. End of […]

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girls needed for anonymous job

... need fluffers to work behind the scenes on adult movie sets. This is totally anonymous: you never appear on any footage. No sex, no nudity required.

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Committers for Force login for Anonymous users

Issues for Force login for Anonymous users. To avoid duplicates, please search before submitting a new issue. Search. Advanced search ...

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Edward Snowden Designs an iPhone Case to Detect & Block Wireless Snooping

We just cannot imagine our lives without smartphones, even for a short while, and NSA whistleblower Edward Snowden had not owned a smartphone since 2013 when he began leaking NSA documents that exposed the government's global surveillance program. Snowden fears that cellular signals of the smartphone could be used to locate him, but now, to combat this, he has designed an iPhone case that

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Anonymous Calls

This app allow to making phone calls in anonymous. It just adds #31# before the number to call. It's useful because when you select a number from the ...

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Falcon 9: Launch and Landing

Shortly after midnight on July 18 a SpaceX Falcon 9 rocket launched from Space Launch Complex 40 at Cape Canaveral Air Force Station, Florida, planet Earth. About 9 minutes later, the rocket's first stage returned to the spaceport. This single time exposure captures the rocket's launch arc and landing streak from Jetty Park only a few miles away. Along a climbing, curving trajectory the launch is traced by the initial burn of the first stage, ending near the top of the bright arc before stage separation. Due to perspective the next bright burn appears above the top of the launch arc in the photo, the returning first stage descending closer to the Cape. The final landing burn creates a long streak as the first stage slows and comes to rest at Landing Zone 1. Yesterday the Dragon cargo spacecraft delivered to orbit by the rocket's second stage was attached to the International Space Station. via NASA http://ift.tt/2adChLr

Can I have this survey be anonymous?

Hi,. Can you please provide us with more details about your question. We will look for a solution for you once we have a better understanding of your ...

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Applying Interval Type-2 Fuzzy Rule Based Classifiers Through a Cluster-Based Class Representation. (arXiv:1607.06186v1 [cs.AI])

Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, i.e. classifiers which can be introspective, understood, validated and augmented by human experts by relying on fuzzy-set based rules. This paper builds on prior work for interval type-2 fuzzy set based FRBCs where the fuzzy sets and rules of the classifier are generated using an initial clustering stage. By introducing Subtractive Clustering in order to identify multiple cluster prototypes, the proposed approach has the potential to deliver improved classification performance while maintaining good interpretability, i.e. without resulting in an excessive number of rules. The paper provides a detailed overview of the proposed FRBC framework, followed by a series of exploratory experiments on both linearly and non-linearly separable datasets, comparing results to existing rule-based and SVM approaches. Overall, initial results indicate that the approach enables comparable classification performance to non rule-based classifiers such as SVM, while often achieving this with a very small number of rules.

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Exploring Differences in Interpretation of Words Essential in Medical Expert-Patient Communication. (arXiv:1607.06187v1 [cs.AI])

In the context of cancer treatment and surgery, quality of life assessment is a crucial part of determining treatment success and viability. In order to assess it, patients completed questionnaires which employ words to capture aspects of patients well-being are the norm. As the results of these questionnaires are often used to assess patient progress and to determine future treatment options, it is important to establish that the words used are interpreted in the same way by both patients and medical professionals. In this paper, we capture and model patients perceptions and associated uncertainty about the words used to describe the level of their physical function used in the highly common (in Sarcoma Services) Toronto Extremity Salvage Score (TESS) questionnaire. The paper provides detail about the interval-valued data capture as well as the subsequent modelling of the data using fuzzy sets. Based on an initial sample of participants, we use Jaccard similarity on the resulting words models to show that there may be considerable differences in the interpretation of commonly used questionnaire terms, thus presenting a very real risk of miscommunication between patients and medical professionals as well as within the group of medical professionals.

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Supervised Adverse Drug Reaction Signalling Framework Imitating Bradford Hill's Causality Considerations. (arXiv:1607.06198v1 [cs.AI])

Big longitudinal observational medical data potentially hold a wealth of information and have been recognised as potential sources for gaining new drug safety knowledge. Unfortunately there are many complexities and underlying issues when analysing longitudinal observational data. Due to these complexities, existing methods for large-scale detection of negative side effects using observational data all tend to have issues distinguishing between association and causality. New methods that can better discriminate causal and non-causal relationships need to be developed to fully utilise the data. In this paper we propose using a set of causality considerations developed by the epidemiologist Bradford Hill as a basis for engineering features that enable the application of supervised learning for the problem of detecting negative side effects. The Bradford Hill considerations look at various perspectives of a drug and outcome relationship to determine whether it shows causal traits. We taught a classifier to find patterns within these perspectives and it learned to discriminate between association and causality. The novelty of this research is the combination of supervised learning and Bradford Hill's causality considerations to automate the Bradford Hill's causality assessment. We evaluated the framework on a drug safety gold standard know as the observational medical outcomes partnership's nonspecified association reference set. The methodology obtained excellent discriminate ability with area under the curves ranging between 0.792-0.940 (existing method optimal: 0.73) and a mean average precision of 0.640 (existing method optimal: 0.141). The proposed features can be calculated efficiently and be readily updated, making the framework suitable for big observational data.

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Left/Right Hand Segmentation in Egocentric Videos. (arXiv:1607.06264v1 [cs.HC])

Wearable cameras allow people to record their daily activities from a user-centered (First Person Vision) perspective. Due to their favorable location, wearable cameras frequently capture the hands of the user, and may thus represent a promising user-machine interaction tool for different applications. Existent First Person Vision methods handle hand segmentation as a background-foreground problem, ignoring two important facts: i) hands are not a single "skin-like" moving element, but a pair of interacting cooperative entities, ii) close hand interactions may lead to hand-to-hand occlusions and, as a consequence, create a single hand-like segment. These facts complicate a proper understanding of hand movements and interactions. Our approach extends traditional background-foreground strategies, by including a hand-identification step (left-right) based on a Maxwell distribution of angle and position. Hand-to-hand occlusions are addressed by exploiting temporal superpixels. The experimental results show that, in addition to a reliable left/right hand-segmentation, our approach considerably improves the traditional background-foreground hand-segmentation.

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Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering. (arXiv:1607.06275v1 [cs.CL])

While question answering (QA) with neural network, i.e. neural QA, has achieved promising results in recent years, lacking of large scale real-word QA dataset is still a challenge for developing and evaluating neural QA system. To alleviate this problem, we propose a large scale human annotated real-world QA dataset WebQA with more than 42k questions and 556k evidences. As existing neural QA methods resolve QA either as sequence generation or classification/ranking problem, they face challenges of expensive softmax computation, unseen answers handling or separate candidate answer generation component. In this work, we cast neural QA as a sequence labeling problem and propose an end-to-end sequence labeling model, which overcomes all the above challenges. Experimental results on WebQA show that our model outperforms the baselines significantly with an F1 score of 74.69% with word-based input, and the performance drops only 3.72 F1 points with more challenging character-based input.

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Modelling Office Energy Consumption: An Agent Based Approach. (arXiv:1607.06332v1 [cs.AI])

In this paper, we develop an agent-based model which integrates four important elements, i.e. organisational energy management policies/regulations, energy management technologies, electric appliances and equipment, and human behaviour, based on a case study, to simulate the energy consumption in office buildings. With the model, we test the effectiveness of different energy management strategies, and solve practical office energy consumption problems. This paper theoretically contributes to an integration of four elements involved in the complex organisational issue of office energy consumption, and practically contributes to an application of agent-based approach for office building energy consumption study.

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On the Prior Sensitivity of Thompson Sampling. (arXiv:1506.03378v2 [cs.LG] UPDATED)

The empirically successful Thompson Sampling algorithm for stochastic bandits has drawn much interest in understanding its theoretical properties. One important benefit of the algorithm is that it allows domain knowledge to be conveniently encoded as a prior distribution to balance exploration and exploitation more effectively. While it is generally believed that the algorithm's regret is low (high) when the prior is good (bad), little is known about the exact dependence. In this paper, we fully characterize the algorithm's worst-case dependence of regret on the choice of prior, focusing on a special yet representative case. These results also provide insights into the general sensitivity of the algorithm to the choice of priors. In particular, with $p$ being the prior probability mass of the true reward-generating model, we prove $O(\sqrt{T/p})$ and $O(\sqrt{(1-p)T})$ regret upper bounds for the bad- and good-prior cases, respectively, as well as \emph{matching} lower bounds. Our proofs rely on the discovery of a fundamental property of Thompson Sampling and make heavy use of martingale theory, both of which appear novel in the literature, to the best of our knowledge.

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Funnel Libraries for Real-Time Robust Feedback Motion Planning. (arXiv:1601.04037v2 [cs.RO] UPDATED)

We consider the problem of generating motion plans for a robot that are guaranteed to succeed despite uncertainty in the environment, parametric model uncertainty, and disturbances. Furthermore, we consider scenarios where these plans must be generated in real-time, because constraints such as obstacles in the environment may not be known until they are perceived (with a noisy sensor) at runtime. Our approach is to pre-compute a library of "funnels" along different maneuvers of the system that the state is guaranteed to remain within (despite bounded disturbances) when the feedback controller corresponding to the maneuver is executed. We leverage powerful computational machinery from convex optimization (sums-of-squares programming in particular) to compute these funnels. The resulting funnel library is then used to sequentially compose motion plans at runtime while ensuring the safety of the robot. A major advantage of the work presented here is that by explicitly taking into account the effect of uncertainty, the robot can evaluate motion plans based on how vulnerable they are to disturbances.

We demonstrate and validate our method using extensive hardware experiments on a small fixed-wing airplane avoiding obstacles at high speed (~12 mph), along with thorough simulation experiments of ground vehicle and quadrotor models navigating through cluttered environments. To our knowledge, the resulting hardware demonstrations on a fixed-wing airplane constitute one of the first examples of provably safe and robust control for robotic systems with complex nonlinear dynamics that need to plan in realtime in environments with complex geometric constraints.

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Neighborhood Mixture Model for Knowledge Base Completion. (arXiv:1606.06461v2 [cs.CL] UPDATED)

Knowledge bases are useful resources for many natural language processing tasks, however, they are far from complete. In this paper, we define a novel entity representation as a mixture of its neighborhood in the knowledge base and apply this technique on TransE-a well-known embedding model for knowledge base completion. Experimental results show that the neighborhood information significantly helps to improve the results of the TransE, leading to better performance than obtained by other state-of-the-art embedding models on three benchmark datasets for triple classification, entity prediction and relation prediction tasks.

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STransE: a novel embedding model of entities and relationships in knowledge bases. (arXiv:1606.08140v2 [cs.CL] UPDATED)

Knowledge bases of real-world facts about entities and their relationships are useful resources for a variety of natural language processing tasks. However, because knowledge bases are typically incomplete, it is useful to be able to perform link prediction, i.e., predict whether a relationship not in the knowledge base is likely to be true. This paper combines insights from several previous link prediction models into a new embedding model STransE that represents each entity as a low-dimensional vector, and each relation by two matrices and a translation vector. STransE is a simple combination of the SE and TransE models, but it obtains better link prediction performance on two benchmark datasets than previous embedding models. Thus, STransE can serve as a new baseline for the more complex models in the link prediction task.

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Algebraic foundations for qualitative calculi and networks. (arXiv:1606.09140v2 [cs.AI] UPDATED)

A qualitative representation $\phi$ is like an ordinary representation of a relation algebra, but instead of requiring $(a; b)^\phi = a^\phi | b^\phi$, as we do for ordinary representations, we only require that $c^\phi\supseteq a^\phi | b^\phi \iff c\geq a ; b$, for each $c$ in the algebra. A constraint network is qualitatively satisfiable if its nodes can be mapped to elements of a qualitative representation, preserving the constraints. If a constraint network is satisfiable then it is clearly qualitatively satisfiable, but the converse can fail. However, for a wide range of relation algebras including the point algebra, the Allen Interval Algebra, RCC8 and many others, a network is satisfiable if and only if it is qualitatively satisfiable.

Unlike ordinary composition, the weak composition arising from qualitative representations need not be associative, so we can generalise by considering network satisfaction problems over non-associative algebras. We prove that computationally, qualitative representations have many advantages over ordinary representations: whereas many finite relation algebras have only infinite representations, every finite qualitatively representable algebra has a finite qualitative representation; the representability problem for (the atom structures of) finite non-associative algebras is NP-complete; the network satisfaction problem over a finite qualitatively representable algebra is always in NP; the validity of equations over qualitative representations is co-NP-complete. On the other hand we prove that there is no finite axiomatisation of the class of qualitatively representable algebras.

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Orioles: P Hunter Harvey (2013 1st-rd pick) to undergo Tommy John surgery Tuesday; has made just 30 minor league starts (ESPN)

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NFL: Former Ravens RB Ray Rice says he would donate his entire 2016 salary to charity if signed by a team this season (ESPN)

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MXJ in M4L and anonymous classes

I'm trying to use an MXJ instance in an m4l device but I'm having trouble with anonymous classes. Compiled anonymous classes in java look like this: ...

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Police Unlock Dead Man's Phone by 3D-Printing his Fingerprint

Now no more fight with Apple or any smartphone maker, as federal authorities have discovered a new tool for unlocking phones, as far as your phone is using any biometric sensor… 3D Printing! Yes, Police in Michigan is considering 3D printing a dead man’s fingers so they could unlock smartphones in investigation crimes using their biometric sensors. <!-- adsense --> A new report published

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Ravens: 2016 projected starting lineup features 1st-round pick Ronnie Stanley at LT, Eric Weddle at S - Jamison Hensley (ESPN)

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I have a new follower on Twitter

will.dymond@mail.com



Following: 570 - Followers: 6

July 21, 2016 at 11:32AM via Twitter http://twitter.com/will_dymond

ISS Daily Summary Report – 07/20/16

SpaceX (SpX)-9 Capture: The Dragon vehicle was successfully captured by the SSRMS at 5:56AM CDT today. Ground teams then berthed the vehicle to the Node 2 Nadir (N2N) port at approximately 9 AM, after which the crew performed vestibule pressurization and outfitting.  Thanks to the crew and ground operators getting ahead of the timeline, they were able to ingress the vehicle today instead of waiting until tomorrow as previously planned. Thermolab Instrumentation for Circadian Rhythms: The crew began the first of a three-day European Space Agency (ESA) Circadian Rhythms experiment by performing instrumentation with the Thermolab Double sensors, mounting the Thermolab Unit in a belt and connecting and powering on the Thermolab Unit before beginning a 36 hour continuous measurement. After the measurement is complete, the data will be transferred and the hardware will be stowed. The objective of the experiment is to get a better understanding of any alterations in circadian rhythms in humans during long-term space flights. Such knowledge will not only provide important insights into the adaptations of the human autonomic nervous system in space over time, but also has significant practical implications by helping to improve physical exercise, rest and work shifts, as well as fostering adequate workplace illumination in the sense of occupational healthcare in future space missions. Mouse Epigenetics Pre-experiment Transfer Overview: In preparation for the Mouse Epigenetics experiment that arrived on SpX-9, the crew reviewed reference material on transferring mice from the transportation Cage Unit to the Mouse Habitat Cage Unit and installing the Mouse Habitat Cage Unit to Cell Biology Experiment Facility (CBEF) Incubator Unit (IU).  Double Coldbag Unpack and Polar Transfer Overview: The crew reviewed reference material and procedures to understand the timing and choreography of unpacking the Double Coldbags from SpX-9 and transferring and installing the Polars from Dragon into the Expedite the Processing of Experiments to Space Station (EXPRESS) racks. Today’s Planned Activities All activities were completed unless otherwise noted. Crew Command Panel (CCP) Cable Route and Checkout Hematocrit  Test r/g 2813 Hematocrit Hardware Stowage USOS Window Shutter Closure Photo/TV Video recording on Ghost Camera plugged to SSC Laptop power Camcorder Setup to View LAB RWS Monitor 3 CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2811 MOUSE. Sample Transfer Review Closing window 6,8,9,12,13,14 shutters / r/g 6965 CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2822 Soyuz 720 Samsung Tablet Recharge, initiate Soyuz 731 Samsung Tablet Recharge, Initiate Robotic Work Station (RWS) Dragon Configuration ELECTRONIC NOSE. Experiment Part 1 r/g 2846 ISS Crew/SSIPC (Space Station Integration and Promotion Center) Conference Progress 433 (DC1) Transfers and IMS ops / r/g 2834, 2835 EXPRESS Rack 5, Locker Move Dragon, R-bar Approach CARDIOVECTOR Experiment r/g 2850 MATRYOSHKA-R. Transfer of Tritel from Progress to SM / r/g 2844 MATRYOSHKA-R. Deployment of Tritel Passive Detectors at Exposure Location. Photography / r/g 2844 Dragon SSRMS Capture CASKAD. Starting Anabioz Battery Charge / r/g 2848 Video Downlink End Gecko Gripper Operations Ghost Camera Teardown in Cupola High Definition (HD) Encoder Setup in Node 2 to capture Dragon Hatch Opening Dragon – Node 2 pressurization and leak check CALCIUM. Experiment Session 5 / r/g 2843 PLR Sample Transfer Double Coldbag (DCB) Unpacking Review Node 2 Port CBM Pre-mate Status Verification DOSETRK iPad data entry DOSETRK Questionnaire Completion CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2811 Life On The Station Photo and Video / r/g 2747 Common Berthing Mechanism (CBM), Capture and Acquire Bolts Crew time for ISS adaptation and orientation Secure at crew discretion. Soyuz 720 Samsung tablet recharging, end CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2822 Soyuz 731 Samsung tablet recharging, end Verification of ИП-1 Flow Sensor Position / SM Pressure Control & Atmosphere Monitoring System СОЖ Maintenance Crew time for ISS adaptation and orientation ELECTRONIC NOSE. Experiment Part 2 r/g 2847 Software installation on FS1 for [ТВМ1-Н] data copying r/g 2849 Crew Command Panel (CCP) Cable Routing Dragon – Node 2 pressurization and leak check Dragon Vestibule Outfitting IMS Delta File Prep CORRECTSIYA. NEUROIMMUNITET. Experiment setup / r/g 2845 Crew time for ISS adaptation and orientation Node 2 CBM Controller Panel Assemblies (CPAs) Removal CIRCADIAN RHYTHMS – Trash faulty sensor Thermolab, Instrumentation Ops for Circadian Rhythms NEUROIMMUNITET. Starting 24-hr ECG Recording r/g 2845 CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2811 NEUROIMMUNITET. Saliva Collection / r/g 2845 REMINDER – LKR – Reminder CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2822 Completed Task List Items None Ground Activities All activities were completed unless otherwise noted. Dragon capture/berth Nominal ground commanding. Three-Day Look Ahead: Thursday, 07/21: Mouse Epigenetics reconfig and setup, Heart Cell CO2 insert, NanoRacks Module 9 hardware retrieval, Polar and DCB transfers Friday, 07/22: Polar 3 hardware install, Heart Cells media change, Biological Rhythms 48 start Circadian Rhythms, OBT Dragon emergency review Saturday, 07/23: Crew off duty, housekeeping, NanoRacks Module 9 hardware retrieval QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) On [СКВ] 2 – SM Air Conditioner System (“SKV2”) Off Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Idle Major Constituent Analyzer (MCA) Node 3 Operate Oxygen Generation Assembly (OGA) Process Urine Processing Assembly (UPA) Norm Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

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Can an anonymous social network ever work?

Silicon Valley is strewn with the corpses of dead anonymous social networks like Secret, PostSecret and Rumr. Many were unprepared to deal with ...

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Ravens: Free-agent OT Eugene Monroe plans to retire - Josina Anderson; released in June, played 17 games last 2 years (ESPN)

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Female model for anonymous videos up to $12000

NYC studio seeks open minded female models with attractive bodies for anonymous adult videos. Anonymous means you will be wearing a wig and ...

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France warns Microsoft to Stop Collecting Windows 10 Users' Personal Data

We have heard a lot about privacy concerns surrounding Windows 10 and accusations on Microsoft of collecting too much data about users without their consent. Now, the French data protection authority has ordered Microsoft to stop it. France's National Data Protection Commission (CNIL) issued a formal notice on Wednesday, asking Microsoft to "stop collecting excessive data" as well as "

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Alcoholics Anonymous: Iceberg

Alcoholics Anonymous: Skyline ... Alcoholics Anonymous: Jack Daniel&#039;s ... Alcoholics Anonymous: The “One Day At A Time” Calendar.

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Santas & Esks

Santas & Esks. Date/Time Date(s) - Saturday November 5, 2016 2 pm. Santas Elves will be outside Commonwealth Stadium collecting donations from ...

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KickassTorrents — Domain Names Seized! Owner Arrested! Website Goes Down!

The federal authorities have finally arrested the alleged mastermind behind the world's largest and most notorious BitTorrent distribution site KickassTorrents (KAT), the US Justice Department announced on Wednesday. After The Pirate Bay had suffered copyright infringement hardship, KickassTorrents (KAT) became the biggest and most-used pirate site on the Internet, attracting millions of

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Dark Dunes on Mars

How does wind affect sand on Mars? To help find out if it differs significantly from Earth, the robotic Curiosity rover on Mars was directed to investigate the dark Namib Dune in the Bagnold Dune Field in Gale Crater. Namib is the first active sand dune investigated up close outside of planet Earth. Wind-created ripples on Earth-bound sand dunes appear similar to ripples on Mars, with one exception. The larger peaks visible on dark Namib dune, averaging about 3 meters apart, are of a type seen only underwater on Earth. They appear to arise on Mars because of the way the thin Martian wind drags dark sand particles. The featured image was taken last December and is horizontally compressed to show context. In the distance, a normal dusty Martian landscape slopes up in light orange, while a rock-strewn landscape is visible on the far right. Curiosity unexpectedly went into safe mode in early July, but it was brought out last week and has now resumed exploring the once lake-filled interior of Gale Crater for further signs that it was once habitable by microbial life. via NASA http://ift.tt/29UT4xX

Model for Art, Be Anonymous, Have Fun, Make Money

Artist, Photographer, Painter is looking for a Model (Amateur / No Experience fine) for conceptual art pieces. Art is Gallery grade and in private ...

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Rumor Central: Orioles among teams interested in Padres SP Andrew Cashner (4-7, 5.05 ERA) - MLB Network (ESPN)

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Large Anonymous Donation to Christian County Animal Control

An anonymous donor recently gave the shelter $50000.The animal control warden wants to use that money to build the very first dog park in Christian ...

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Neural Contextual Conversation Learning with Labeled Question-Answering Pairs. (arXiv:1607.05809v1 [cs.CL])

Neural conversational models tend to produce generic or safe responses in different contexts, e.g., reply \textit{"Of course"} to narrative statements or \textit{"I don't know"} to questions. In this paper, we propose an end-to-end approach to avoid such problem in neural generative models. Additional memory mechanisms have been introduced to standard sequence-to-sequence (seq2seq) models, so that context can be considered while generating sentences. Three seq2seq models, which memorize a fix-sized contextual vector from hidden input, hidden input/output and a gated contextual attention structure respectively, have been trained and tested on a dataset of labeled question-answering pairs in Chinese. The model with contextual attention outperforms others including the state-of-the-art seq2seq models on perplexity test. The novel contextual model generates diverse and robust responses, and is able to carry out conversations on a wide range of topics appropriately.

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You want to survive the data deluge: Be careful, Computational Intelligence will not serve you as a rescue boat. (arXiv:1607.05810v1 [cs.AI])

We are at the dawn of a new era, where advances in computer power, broadband communication and digital sensor technologies have led to an unprecedented flood of data inundating our surrounding. It is generally believed that means such as Computational Intelligence will help to outlive these tough times. However, these hopes are improperly high. Computational Intelligence is a surprising composition of two mutually exclusive and contradicting constituents that could be coupled only if you disregard and neglect their controversies: "Computational" implies reliance on data processing and "Intelligence" implies reliance on information processing. Only those who are indifferent to data-information discrepancy can believe that such a combination can be viable. We do not believe in miracles, so we will try to share with you our reservations.

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Identifying Candidate Risk Factors for Prescription Drug Side Effects using Causal Contrast Set Mining. (arXiv:1607.05845v1 [cs.AI])

Big longitudinal observational databases present the opportunity to extract new knowledge in a cost effective manner. Unfortunately, the ability of these databases to be used for causal inference is limited due to the passive way in which the data are collected resulting in various forms of bias. In this paper we investigate a method that can overcome these limitations and determine causal contrast set rules efficiently from big data. In particular, we present a new methodology for the purpose of identifying risk factors that increase a patients likelihood of experiencing the known rare side effect of renal failure after ingesting aminosalicylates. The results show that the methodology was able to identify previously researched risk factors such as being prescribed diuretics and highlighted that patients with a higher than average risk of renal failure may be even more susceptible to experiencing it as a side effect after ingesting aminosalicylates.

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Indebted households profiling: a knowledge discovery from database approach. (arXiv:1607.05869v1 [cs.AI])

A major challenge in consumer credit risk portfolio management is to classify households according to their risk profile. In order to build such risk profiles it is necessary to employ an approach that analyses data systematically in order to detect important relationships, interactions, dependencies and associations amongst the available continuous and categorical variables altogether and accurately generate profiles of most interesting household segments according to their credit risk. The objective of this work is to employ a knowledge discovery from database process to identify groups of indebted households and describe their profiles using a database collected by the Consumer Credit Counselling Service (CCCS) in the UK. Employing a framework that allows the usage of both categorical and continuous data altogether to find hidden structures in unlabelled data it was established the ideal number of clusters and such clusters were described in order to identify the households who exhibit a high propensity of excessive debt levels.

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Juxtaposition of System Dynamics and Agent-based Simulation for a Case Study in Immunosenescence. (arXiv:1607.05888v1 [cs.AI])

Advances in healthcare and in the quality of life significantly increase human life expectancy. With the ageing of populations, new un-faced challenges are brought to science. The human body is naturally selected to be well-functioning until the age of reproduction to keep the species alive. However, as the lifespan extends, unseen problems due to the body deterioration emerge. There are several age-related diseases with no appropriate treatment; therefore, the complex ageing phenomena needs further understanding. Immunosenescence, the ageing of the immune system, is highly correlated to the negative effects of ageing, such as the increase of auto-inflammatory diseases and decrease in responsiveness to new diseases. Besides clinical and mathematical tools, we believe there is opportunity to further exploit simulation tools to understand immunosenescence. Compared to real-world experimentation, benefits include time and cost effectiveness due to the laborious, resource-intensiveness of the biological environment and the possibility of conducting experiments without ethic restrictions. Contrasted with mathematical models, simulation modelling is more suitable for representing complex systems and emergence. In addition, there is the belief that simulation models are easier to communicate in interdisciplinary contexts. Our work investigates the usefulness of simulations to understand immunosenescence by employing two different simulation methods, agent-based and system dynamics simulation, to a case study of immune cells depletion with age.

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Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. (arXiv:1607.05906v1 [cs.AI])

Purpose: To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. Methods: We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. Results The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranked the drug families known to be true adverse drug reactions above those.

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Supervised Anomaly Detection in Uncertain Pseudoperiodic Data Streams. (arXiv:1607.05909v1 [cs.AI])

Uncertain data streams have been widely generated in many Web applications. The uncertainty in data streams makes anomaly detection from sensor data streams far more challenging. In this paper, we present a novel framework that supports anomaly detection in uncertain data streams. The proposed framework adopts an efficient uncertainty pre-processing procedure to identify and eliminate uncertainties in data streams. Based on the corrected data streams, we develop effective period pattern recognition and feature extraction techniques to improve the computational efficiency. We use classification methods for anomaly detection in the corrected data stream. We also empirically show that the proposed approach shows a high accuracy of anomaly detection on a number of real datasets.

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Simulating user learning in authoritative technology adoption: An agent based model for council-led smart meter deployment planning in the UK. (arXiv:1607.05912v1 [cs.AI])

How do technology users effectively transit from having zero knowledge about a technology to making the best use of it after an authoritative technology adoption? This post-adoption user learning has received little research attention in technology management literature. In this paper we investigate user learning in authoritative technology adoption by developing an agent-based model using the case of council-led smart meter deployment in the UK City of Leeds. Energy consumers gain experience of using smart meters based on the learning curve in behavioural learning. With the agent-based model we carry out experiments to validate the model and test different energy interventions that local authorities can use to facilitate energy consumers' learning and maintain their continuous use of the technology. Our results show that the easier energy consumers become experienced, the more energy-efficient they are and the more energy saving they can achieve; encouraging energy consumers' contacts via various informational means can facilitate their learning; and developing and maintaining their positive attitude toward smart metering can enable them to use the technology continuously. Contributions and energy policy/intervention implications are discussed in this paper.

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Optimising Rule-Based Classification in Temporal Data. (arXiv:1607.05913v1 [cs.AI])

This study optimises manually derived rule-based expert system classification of objects according to changes in their properties over time. One of the key challenges that this study tries to address is how to classify objects that exhibit changes in their behaviour over time, for example how to classify companies' share price stability over a period of time or how to classify students' preferences for subjects while they are progressing through school. A specific case the paper considers is the strategy of players in public goods games (as common in economics) across multiple consecutive games. Initial classification starts from expert definitions specifying class allocation for players based on aggregated attributes of the temporal data. Based on these initial classifications, the optimisation process tries to find an improved classifier which produces the best possible compact classes of objects (players) for every time point in the temporal data. The compactness of the classes is measured by a cost function based on internal cluster indices like the Dunn Index, distance measures like Euclidean distance or statistically derived measures like standard deviation. The paper discusses the approach in the context of incorporating changing player strategies in the aforementioned public good games, where common classification approaches so far do not consider such changes in behaviour resulting from learning or in-game experience. By using the proposed process for classifying temporal data and the actual players' contribution during the games, we aim to produce a more refined classification which in turn may inform the interpretation of public goods game data.

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On the estimation of stellar parameters with uncertainty prediction from Generative Artificial Neural Networks: application to Gaia RVS simulated spectra. (arXiv:1607.05954v1 [astro-ph.IM])

Aims. We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in this case) to the given inputs (spectra). Such a model can be integrated in a Bayesian framework to estimate the posterior distribution of the outputs. Methods. The architecture of the GANN follows the same scheme as a normal ANN, but with the inputs and outputs inverted. We train the network with the set of atmospheric parameters (Teff, logg, [Fe/H] and [alpha/Fe]), obtaining the stellar spectra for such inputs. The residuals between the spectra in the grid and the estimated spectra are minimized using a validation dataset to keep solutions as general as possible. Results. The performance of both conventional ANNs and GANNs to estimate the stellar parameters as a function of the star brightness is presented and compared for different Galactic populations. GANNs provide significantly improved parameterizations for early and intermediate spectral types with rich and intermediate metallicities. The behaviour of both algorithms is very similar for our sample of late-type stars, obtaining residuals in the derivation of [Fe/H] and [alpha/Fe] below 0.1dex for stars with Gaia magnitude Grvs<12, which accounts for a number in the order of four million stars to be observed by the Radial Velocity Spectrograph of the Gaia satellite. Conclusions. Uncertainty estimation of computed astrophysical parameters is crucial for the validation of the parameterization itself and for the subsequent exploitation by the astronomical community. GANNs produce not only the parameters for a given spectrum, but a goodness-of-fit between the observed spectrum and the predicted one for a given set of parameters. Moreover, they allow us to obtain the full posterior distribution...

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Robust Natural Language Processing - Combining Reasoning, Cognitive Semantics and Construction Grammar for Spatial Language. (arXiv:1607.05968v1 [cs.AI])

We present a system for generating and understanding of dynamic and static spatial relations in robotic interaction setups. Robots describe an environment of moving blocks using English phrases that include spatial relations such as "across" and "in front of". We evaluate the system in robot-robot interactions and show that the system can robustly deal with visual perception errors, language omissions and ungrammatical utterances.

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Constructing a Natural Language Inference Dataset using Generative Neural Networks. (arXiv:1607.06025v1 [cs.AI])

Natural Language Inference is an important task for Natural Language Understanding. It is concerned with classifying the logical relation between two sentences. In this paper, we propose several text generative neural networks for constructing Natural Language Inference datasets suitable for training classifiers. To evaluate the models, we propose a new metric - the accuracy of the classifier trained on the generated dataset. The accuracy obtained with our best generative model is only 2.7% lower than the accuracy of the classifier trained on the original, manually constructed dataset. The model learns a mapping embedding for each training example. By comparing various metrics we show that datasets that obtain higher ROUGE or METEOR scores do not necessarily yield higher classification accuracies. We also provide analysis of what are the characteristics of a good dataset including the distinguishability of the generated datasets from the original one.

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Harnessing Deep Neural Networks with Logic Rules. (arXiv:1603.06318v3 [cs.LG] UPDATED)

Combining deep neural networks with structured logic rules is desirable to harness flexibility and reduce uninterpretability of the neural models. We propose a general framework capable of enhancing various types of neural networks (e.g., CNNs and RNNs) with declarative first-order logic rules. Specifically, we develop an iterative distillation method that transfers the structured information of logic rules into the weights of neural networks. We deploy the framework on a CNN for sentiment analysis, and an RNN for named entity recognition. With a few highly intuitive rules, we obtain substantial improvements and achieve state-of-the-art or comparable results to previous best-performing systems.

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Deep Cross Residual Learning for Multitask Visual Recognition. (arXiv:1604.01335v2 [cs.CV] UPDATED)

Residual learning has recently surfaced as an effective means of constructing very deep neural networks for object recognition. However, current incarnations of residual networks do not allow for the modeling and integration of complex relations between closely coupled recognition tasks or across domains. Such problems are often encountered in multimedia applications involving large-scale content recognition. We propose a novel extension of residual learning for deep networks that enables intuitive learning across multiple related tasks using cross-connections called cross-residuals. These cross-residuals connections can be viewed as a form of in-network regularization and enables greater network generalization. We show how cross-residual learning (CRL) can be integrated in multitask networks to jointly train and detect visual concepts across several tasks. We present a single multitask cross-residual network with >40% less parameters that is able to achieve competitive, or even better, detection performance on a visual sentiment concept detection problem normally requiring multiple specialized single-task networks. The resulting multitask cross-residual network also achieves better detection performance by about 10.4% over a standard multitask residual network without cross-residuals with even a small amount of cross-task weighting.

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TensorLog: A Differentiable Deductive Database. (arXiv:1605.06523v2 [cs.AI] UPDATED)

Large knowledge bases (KBs) are useful in many tasks, but it is unclear how to integrate this sort of knowledge into "deep" gradient-based learning systems. To address this problem, we describe a probabilistic deductive database, called TensorLog, in which reasoning uses a differentiable process. In TensorLog, each clause in a logical theory is first converted into certain type of factor graph. Then, for each type of query to the factor graph, the message-passing steps required to perform belief propagation (BP) are "unrolled" into a function, which is differentiable. We show that these functions can be composed recursively to perform inference in non-trivial logical theories containing multiple interrelated clauses and predicates. Both compilation and inference in TensorLog are efficient: compilation is linear in theory size and proof depth, and inference is linear in database size and the number of message-passing steps used in BP. We also present experimental results with TensorLog and discuss its relationship to other first-order probabilistic logics.

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Orioles without 3B Manny Machado and Buck Showalter for Wednesday's game at Yankees due to illness sweeping team (ESPN)

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I have a new follower on Twitter

BLACK LIVES MATTER✊
#BlackLivesMatterMemphis ✊ ! We have this username so it won't get misused. Follow us if you support the #blacklivesmatter movement, & we will follow you back!
Memphis, TN
https://t.co/QRciOtepAF
Following: 210013 - Followers: 191949

July 20, 2016 at 05:06PM via Twitter http://twitter.com/AIlLivesMatter

I have a new follower on Twitter

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July 20, 2016 at 04:49PM via Twitter http://twitter.com/psierp

What is Strictly Enforced Verified Boot in Android 7.0 Nougat?

As far as security is concerned, Google is going very strict with the newest version of its mobile operating system. Until now, Google has not done more than just alerting you of the potential threats when your Android device runs the check as part of the boot process. Android Marshmallow 6.0 does nothing more than just warning you that your device has been compromised, though it continues

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ISS Daily Summary Report – 07/19/16

64 Progress (64P) Docking: 64P docked successfully to the ISS Docking Compartment (DC)-1 nadir port last night at 7:22PM CDT. Following hatch opening the crew transferred early unstow and US cargo items. Skin-B Operations: The crew performed Corneometer, Tewameter and Visioscan measurements on his forearm for this experiment. The Corneometer measures the hydration level of the stratus coreum (outer layer of the skin), the Tewameter measures the skin barrier function, and the Visioscan measures the skin surface topography. Skin B is a European Space Agency (ESA) investigation that aims to improve the understanding of skin aging, which is greatly accelerated in space. The data will also be used to verify the results from previous testing for the SkinCare investigation on the ISS.  Cardio Ox Ultrasound Operations: With remote guidance from the Cardio Ox ground teams, the crew conducted an ultrasound scan after configuring the VOX, attaching the ECG Electrodes, and marking the arteries followed by blood pressure measurements using the Cardiolab Holter Arterial Blood Pressure Unit. The goal of the Cardio Ox investigation is to determine whether biological markers of oxidative and inflammatory stress are elevated during and after space flight and whether this results in an increased, long-term risk of atherosclerosis risk in astronauts. Twelve crewmembers provide blood and urine samples to assess biomarkers before launch, 15 and 60 days after launch, 15 days before returning to Earth, and within days after landing. Ultrasound scans of the carotid and brachial arteries are obtained at the same time points, as well as through 5 years after landing, as an indicator of cardiovascular health. Human Research Program (HRP) Generic Urine and Frozen Blood Collection Double Spin: The crew continued HRP operations by collecting urine samples for a 24-hour period, configuring the Refrigerated Centrifuge for sample load operations, then collecting and processing a set of blood samples for double spin operations using the Refrigerated Centrifuge. The samples will be stowed in the Minus Eighty-degree Freezer for ISS (MELFI). Personal Carbon Dioxide (CO2) Monitor Installation and Operations: Before performing data collections from the Personal CO2 Monitor, the crewmember first performed a single point calibration of the Personal CO2 Monitor using the iPad app and readings from the minimum circuit amps (MCA) sample port. The Personal CO2 Monitor was then paired to the iPad, before being attached to the crewmember’s clothing, and worn for several hours. The data collected will be uploaded to the Space Station Computer via the iPad app before being powered off and stowed. The Personal CO2 Monitor demonstrates a system capable of unobtrusively collecting and downlinking individual crew members’ CO2 exposure for weeks to months. This investigation evaluates wearability principles in microgravity and also demonstrates Modular Wearable Architecture Base Board, allowing rapid certification of future wearable devices. Marrow Blood, Breath, and Ambient Air Sample Collection: Upon waking this morning, the crew took breath and ambient air samples to measure carbon monoxide concentration for the Canadian Space Agency (CSA) Marrow experiment which investigates the effect of microgravity on human bone marrow. It is believed that microgravity, like long-duration bed rest on Earth, has a negative effect on bone marrow and the blood cells that are produced in the marrow. The extent of this effect and its recovery are of interest to space research and healthcare providers on Earth. Space Headaches: The crew completed a European Space Agency (ESA) Space Headaches questionnaire to provide information that may help in the development of methods to alleviate associated symptoms and improvement in the well-being and performance of crew members in space. Headaches during space flight can negatively affect mental and physical capacities of crew members which can influence performance during a space mission. Minus Eighty Degree Laboratory Freezer for ISS (MELFI) 2 & 3 Nitrogen (N2) Pressure Checks: The crew completed nitrogen checks on MELFIs 2 and 3 to verify that the nitrogen pressure in both MELFIs is within acceptable range. The MELFI is a cold storage unit that maintains experiment samples at ultra-cold temperatures throughout a mission. It supports a wide range of life science experiments by preserving biological samples (such as blood, saliva, urine, microbial or plant samples) collected aboard ISS for later return and analysis on Earth.  Today’s Planned Activities All activities were completed unless otherwise noted. HABIT Task Video End Water Resource System (WRS) – Distillate Sample Inspection HRF- Blood collection setup WRS Maintenance CARDOX  Material Review MARROW  Breath And Ambient Air Sample Setup WRS Maintenance HRF Urine Sample Collection HRF Urine Sample MELFI Insertion Water Resource System (WRS) Distillate Sample Inspection ISS HAM RADIO Deactivation USOS Window Shutter Closure CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2811 Closing window 6,8,9,12,13,14 shutters/ r/g 6965 MPEG2 Multicast Video Streaming Test Preparation for Progress 433 Docking / Motion Control and Navigation System r/g 2812 Progress 433 Docking to DC1 / Motion Control and Navigation System (СУДН) r/g 2812 Comm Reconfig for Nominal Ops after Docking / Communications System [РТК] Activation of MPEG2 Multicast TV Monitoring On MCC Go Activation of MPEG2 Multicast Recording Mode on CP SSC CASKAD. ТБУ-В No.4 Activation at + 04 deg С setting / r/g 2806 CORRECTSIYA. Logging Liquid and Food (Medicine) Intake / r/g 2811 Close Applications and Downlink MPEG2 Multicast Video via OCA / Communications System [РТК] PRODUTSENT. Activate thermostat at +30 deg C setting / r/g 2807 On MCC Go Progress 433 and DC1 Interface Leak Check / IRS Activation/Deactivation DC1-СУ Hatch Opening / IRS Activation/Deactivation On MCC Go Opening of Progress-СУ Transfer Hatch Installation of Quick Release Screw Clamps (ЗВБ) on DC1-Progress 433 Interface Deactivation of Progress 433 (DC1), Air duct Installation Progress 433 (DC1) Air Sampling using АК-1М sampler  r/g 2810 Photo of a scuffmark left by the Active Docking Mechanism Probe on DC1 АСП Receiving Cone after Progress 433 Docking / r/g 2688 Downlink Photos of Docking Cone Internal Surface via OCA IDENTIFICATION. Copy ИМУ-Ц micro-accelerometer data to laptop / r/g 1589 Progress 433 (DC1) Early Unstow and US Cargo Items Transfers and IMS Ops / r/g 2834, 2835, […]

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Contact user should be blank for anonymous submissions

Development Notes Branch Name: 2769809-user-blank-anonymous-submissions Commit message: Issue #2769809: Contact user should be blank ...

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[FD] Persistent Cross-Site Scripting in WooCommerce using image metadata (EXIF)

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[FD] Cross-Site Scripting vulnerability in Paid Memberships Pro WordPress Plugin

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Beware! Your iPhone Can Be Hacked Remotely With Just A Message

In Brief Do you own an iPhone? Mac? Or any Apple device? Just one specially-crafted message can expose your personal information, including your authentication credentials stored in your device's memory, to a hacker. The vulnerability is quite similar to the Stagefright vulnerabilities, discovered a year ago in Android, that allowed hackers to silently spy on almost a Billion phones with

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403 error on anonymous form submission

I get a 403 error on form submission by anonymous users. The user fills the form, then is dedirected to ...

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Why Are So Many Artists Choosing To Be Anonymous?

"The anonymous buyer, an art dealer, had a hunch. Real Constables were often painted over during the 19th century, when their rough, seemingly ...

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Arctic Sea Ice Extent: January - June 2016

Satellite-based passive microwave images of the sea ice have provided a reliable tool for continuously monitoring changes in the Arctic ice since 1979. Every summer the Arctic ice cap melts down to what scientists call its "minimum" before colder weather begins to cause ice cover to increase. The first six months of 2016 have been the warmest first half of any year in our recorded history of surface temperature (which go back to 1880). Data shows that the Arctic temperature increases are much bigger, relatively, than the rest of the globe. The Japan Aerospace Exploration Agency (JAXA) provides many water-related products derived from data acquired by the Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument aboard the Global Change Observation Mission 1st-Water "SHIZUKU" (GCOM-W1) satellite. Two JAXA datasets used in this animation are the 10-km daily sea ice concentration and the 10 km daily 89 GHz Brightness Temperature. In this animation, the daily Arctic sea ice and seasonal land cover change progress through time, from January 18, 2016, through July 7, 2016. Over the water, Arctic sea ice changes from day to day showing a running 3-day minimum sea ice concentration in the region where the concentration is greater than 15. The blueish white color of the sea ice is derived from a 3-day running minimum of the AMSR2 89 GHz brightness temperature. Over the terrain, monthly data from the seasonal Blue Marble Next Generation fades slowly from month to month.

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Color the Universe

Wouldn't it be fun to color in the universe? If you think so, please accept this famous astronomical illustration as a preliminary substitute. You, your friends, your parents or children, can print it out or even color it digitally. While coloring, you might be interested to know that even though this illustration has appeared in numerous places over the past 100 years, the actual artist remains unknown. Furthermore, the work has no accepted name -- can you think of a good one? The illustration, first appearing in a book by Camille Flammarion in 1888, is used frequently to show that humanity's present concepts are susceptible to being supplanted by greater truths. via NASA http://ift.tt/29LI9pW

Lambda (anonymous/first class procedures) and custom reporters

http://ift.tt/29Md4Db Please try to give clear reasons for your opinions instead of postcounting.

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Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version). (arXiv:1607.05351v1 [cs.AI])

Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data.

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Generating Images Part by Part with Composite Generative Adversarial Networks. (arXiv:1607.05387v1 [cs.AI])

Image generation remains a fundamental problem in artificial intelligence in general and deep learning in specific. The generative adversarial network (GAN) was successful in generating high quality samples of natural images. We propose a model called composite generative adversarial network, that reveals the complex structure of images with multiple generators in which each generator generates some part of the image. Those parts are combined by alpha blending process to create a new single image. It can generate, for example, background and face sequentially with two generators, after training on face dataset. Training was done in an unsupervised way without any labels about what each generator should generate. We found possibilities of learning the structure by using this generative model empirically.

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Exploiting Vagueness for Multi-Agent Consensus. (arXiv:1607.05540v1 [cs.MA])

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

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An Event Grouping Based Algorithm for University Course Timetabling Problem. (arXiv:1607.05601v1 [cs.AI])

This paper presents the study of an event grouping based algorithm for a university course timetabling problem. Several publications which discuss the problem and some approaches for its solution are analyzed. The grouping of events in groups with an equal number of events in each group is not applicable to all input data sets. For this reason, a universal approach to all possible groupings of events in commensurate in size groups is proposed here. Also, an implementation of an algorithm based on this approach is presented. The methodology, conditions and the objectives of the experiment are described. The experimental results are analyzed and the ensuing conclusions are stated. The future guidelines for further research are formulated.

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Hybrid Collaborative Filtering with Autoencoders. (arXiv:1603.00806v3 [cs.IR] UPDATED)

Collaborative Filtering aims at exploiting the feedback of users to provide personalised recommendations. Such algorithms look for latent variables in a large sparse matrix of ratings. They can be enhanced by adding side information to tackle the well-known cold start problem. While Neu-ral Networks have tremendous success in image and speech recognition, they have received less attention in Collaborative Filtering. This is all the more surprising that Neural Networks are able to discover latent variables in large and heterogeneous datasets. In this paper, we introduce a Collaborative Filtering Neural network architecture aka CFN which computes a non-linear Matrix Factorization from sparse rating inputs and side information. We show experimentally on the MovieLens and Douban dataset that CFN outper-forms the state of the art and benefits from side information. We provide an implementation of the algorithm as a reusable plugin for Torch, a popular Neural Network framework.

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A topological insight into restricted Boltzmann machines. (arXiv:1604.05978v2 [cs.NE] UPDATED)

Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep artificial neural networks for automatic features extraction, unsupervised weights initialization, but also as density estimators. Thus, their generative and discriminative capabilities, but also their computational time are instrumental to a wide range of applications. Our main contribution is to look at RBMs from a topological perspective, bringing insights from network science. Firstly, here we show that RBMs and Gaussian RBMs (GRBMs) are bipartite graphs which naturally have a small-world topology. Secondly, we demonstrate both on synthetic and real-world datasets that by constraining RBMs and GRBMs to a scale-free topology (while still considering local neighborhoods and data distribution), we reduce the number of weights that need to be computed by a few orders of magnitude, at virtually no loss in generative performance. Thirdly, we show that, for a fixed number of weights, our proposed sparse models (which by design have a higher number of hidden neurons) achieve better generative capabilities than standard fully connected RBMs and GRBMs (which by design have a smaller number of hidden neurons), at no additional computational costs.

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Policy Networks with Two-Stage Training for Dialogue Systems. (arXiv:1606.03152v2 [cs.CL] UPDATED)

In this paper, we propose to use deep policy networks which are trained with an advantage actor-critic method for statistically optimised dialogue systems. First, we show that, on summary state and action spaces, deep Reinforcement Learning (RL) outperforms Gaussian Processes methods. Summary state and action spaces lead to good performance but require pre-engineering effort, RL knowledge, and domain expertise. In order to remove the need to define such summary spaces, we show that deep RL can also be trained efficiently on the original state and action spaces. Dialogue systems based on partially observable Markov decision processes are known to require many dialogues to train, which makes them unappealing for practical deployment. We show that a deep RL method based on an actor-critic architecture can exploit a small amount of data very efficiently. Indeed, with only a few hundred dialogues collected with a handcrafted policy, the actor-critic deep learner is considerably bootstrapped from a combination of supervised and batch RL. In addition, convergence to an optimal policy is significantly sped up compared to other deep RL methods initialized on the data with batch RL. All experiments are performed on a restaurant domain derived from the Dialogue State Tracking Challenge 2 (DSTC2) dataset.

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Orioles place OF Hyun Soo Kim (hamstring strain) on the 15-day DL, select contract of OF Julio Borbon from Double-A (ESPN)

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[FD] Multiple SQL injection vulnerabilities in WordPress Video Player

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[FD] Cross-Site Request Forgery in Icegram WordPress Plugin

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Anonymous bottom

Looking for an anonymous hung top to come fill me up! I'm alone for a few of hours in my hotel starting at about 2ish pm and horny and ready to be ...

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Ozarks "Inventors Anonymous" Forges Ideas in Secret

"Inventors Anonymous" holds a summer open meeting--complete with watermelon. Credit J. Froelich / KUAF. A diverse group of inventors, based in ...

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[FD] Multiple Cross-Site Scripting vulnerabilities in Ninja Forms WordPress Plugin

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VPN Dilemma: Anonymous Expression Vs. Anonymous Defamation

VPN Dilemma: Anonymous Expression Vs. Anonymous Defamation. Since the general public started using the internet, it has made people feel ...

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ISS Daily Summary Report – 07/18/16

64 Progress (64P) Launch: 64P launched successfully from Baikonur, Kazakhstan on Saturday at 4:41PM CDT with nominal ascent. Docking is scheduled for this evening at 7:22PM CDT. SpaceX (SpX)-9 Launch: SpX-9 launched successfully on Sunday at 11:45PM CDT. Capture is scheduled on Wednesday, July 20 at 6:00AM CDT with berthing approximately 3.5 hours later. Ingress will occur on Thursday, July 21. EarthKAM Service Module (SM) De-activation Removal: Over the weekend, Russian crewmembers shut down the EarthKAM payload components before disconnecting and stowing the equipment, concluding a week of imagery sessions in the SM. The objective of Sally Ride EarthKAM is to integrate Earth images with inquiry-based learning to enhance curricula in support of national and state education standards; to provide students and educators the opportunity to participate in a space mission and to develop teamwork, communication, and problem solving skills; to engage teams of students, educators, and researchers in collaborative investigations using remotely-sensed data; and to incorporate the active use of Web-based tools and resources in support of the learning process. Marrow Blood, Breath, and Ambient Air Sample Collection: The crew completed the blood collection double spin overviews this weekend to prepare for scheduled Marrow activities today and tomorrow. Upon waking this morning, the crew measured the effects of microgravity-induced marrow fat accumulation on red and white blood cell metabolism using breath and ambient air samples to measure carbon monoxide concentration. The Canadian Space Agency (CSA) Marrow experiment investigates the effect of microgravity on human bone marrow. It is believed that microgravity, like long-duration bed rest on Earth, has a negative effect on bone marrow and the blood cells that are produced in the marrow. The extent of this effect and its recovery are of interest to space research and healthcare providers on Earth. Human Research Program (HRP) Blood and Urine Collection: The crew collected blood and urine samples and stowed them into the Minus Eighty-degree Freezer for ISS (MELFI).  The samples will be used to support the HRP: Biochem Profile, Repository, and Cardio Ox investigations.  Cardio Ox Overview: In preparation for Cardio Ox operations planned for tomorrow, the crew will review reference material for ultrasound scanning activities and blood pressure measurements. Crewmembers provide blood and urine samples to assess biomarkers before launch, 15 and 60 days after launch, 15 days before returning to Earth, and within days after landing. Ultrasound scans of the carotid and brachial arteries are obtained at the same time points, as well as through 5 years after landing, as an indicator of cardiovascular health. Mouse Epigenetics Setup Operations: The crew continued setup activities for the Mouse Epigenetics experiment by replacing MSPR VRU SSD installed in Multi-purpose Small Payload Rack (MSPR) Video Compression and Recording Unit (VRU). The Mouse Epigenetics investigation studies altered gene expression patterns in the organs of male mice that spend one month in space, and also examines changes in the DNA of their offspring. Results from the investigation identify genetic alterations that happen after exposure to the microgravity environment of space. Strata-1 Card Change-out: Four Strata secure digital (SD) cards were replaced and the data was downlinked.  The Strata-1 experiment investigates the properties and behavior of regolith on small, airless bodies.  Regolith is the impact-shattered “soil” found on asteroids, comets, the Moon, and other airless worlds, but it is different from soil here on Earth in that it contains no living material. Strata-1’s goal is to give us answers about how regolith behaves and moves in microgravity, how easy or difficult it is to anchor a spacecraft in regolith, how it interacts with spacecraft and spacesuit materials, and other important properties.  Habitability Human Factors Directed Observations: The crew recorded and submitted a walk-through video documenting observations of life onboard ISS providing insight related to human factors and habitability. The Habitability investigation collects observations about the relationship between crew members and their environment on the International Space Station. 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.  Fine Motor Skills: A series of interactive tasks on a touchscreen tablet were completed over the weekend for the Fine Motor Skills investigation. This investigation is critical during long-duration space missions, particularly those skills needed to interact with technologies required in next-generation space vehicles, spacesuits, and habitats. Crew fine motor skills are also necessary for performing tasks in transit or on a planetary surface, such as information access, just-in-time training, subsystem maintenance, and medical treatment. Urine Processing Assembly (UPA) Separator Plumbing Assembly (SPA) Samples: Last week the crew configured the system with the SPA output disconnected to obtain distillate samples for return to ground to better understand the recent UPA high conductivity. The UPA will continue to process in this configuration for at least a week. A longer term configuration to connect a CWC-I to the SPA output is in work. Waste & Hygiene Compartment (WHC) Pump Separator Remove & Replace (R&R): On July 11, the WHC Check Separator fault light illuminated. Subsequent troubleshooting steps led ground teams to conclude that the separator, which has been in operation since January of this year, was at its end of life. Today the Check Separator fault light illuminated again and the crew was directed to R&R the unit.  After completion of that activity, the WHC was successfully recovered and is go for nominal use. Today’s Planned Activities All activities were completed unless otherwise noted. MARROW –  Air Samples Collection  REMINDER2 –  Reading Reminder МО-8. Body Mass Measurement. H/W set up Body Mass Measurement.  / R/G 2809 HRF. Centrifuge activation and Blood Samples Collection   FE-5 МО-8.  Close-out Ops HRF- Blood Sample Collection (assistance)  CETNTRIFUGE1 CONFIGURATION WSTA Fill KORREKTSIA. Taking food and liquids (medicine) registration in flight log / R/G 2811 HRF – Centrifuge 2 Configuration HRF- Generic Sample MELFI Insertion Operations HRF. Urine Samples Collection HRF- Blood Samples Removal and Stowage in Preparation for Cold Stowage Insertion HRF- Generic Sample MELFI Insertion Operations PRODUTSENT. ТБУ-[В] No. 02 Thermostat Setup / R/G 2804 HRF- Close-out Ops […]

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Core Tor Contributor Leaves Project; Shutting Down Important Tor Nodes

Another blow to the Tor Project: One of the Tor Project's earliest contributors has decided to quit the project and shut down all of the important Tor nodes under his administration. Lucky Green was part of the Tor Project before the anonymity network was known as TOR. He probably ran one of the first 5 nodes in the TOR network at its inception and managed special nodes inside the anonymity

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[FD] Django CMS v3.3.0 - (Editor Snippet) Persistent Web Vulnerability (CVE-2016-6186)

Document Title: =============== Django CMS v3.3.0 - (Editor Snippet) Persistent Web Vulnerability (CVE-2016-6186) References (Source): ==================== http://ift.tt/2a71N5e Security Release: http://ift.tt/29QeFHQ http://ift.tt/29QE3P0 CVE-ID: ======= CVE-2016-6186 Release Date: ============= 2016-07-19 Vulnerability Laboratory ID (VL-ID): ==================================== 1869 Common Vulnerability Scoring System: ==================================== 3.5 Product & Service Introduction: =============================== django CMS is a modern web publishing platform built with Django, the web application framework for perfectionists with deadlines. django CMS offers out-of-the-box support for the common features you’d expect from a CMS, but can also be easily customised and extended by developers to create a site that is tailored to their precise needs. (Copy of the Homepage: http://ift.tt/29QFBMX ) Abstract Advisory Information: ============================== The vulnerability laboratory core research team discovered an application-side vulnerability (CVE-2016-6186) in the official Django v3.3.0 Content Management System. Vulnerability Disclosure Timeline: ================================== 2016-07-03: Researcher Notification & Coordination (Benjamin Kunz Mejri - Evolution Security GmbH) 2016-07-04 Vendor Notification (Django Security Team) 2016-07-07: Vendor Response/Feedback (Django Security Team) 2016-07-18: Vendor Fix/Patch (Django Service Developer Team) 2016-07-19: Public Disclosure (Vulnerability Laboratory) Discovery Status: ================= Published Affected Product(s): ==================== Divio AG Product: Django Framework - Content Management System 3.3.0 Divio AG Product: Django Framework - Content Management System MDB, 1.10, 1.9, 1.8 and 1.7 Exploitation Technique: ======================= Remote Severity Level: =============== Medium Technical Details & Description: ================================ A persistent input validation web vulnerability has been discovered in the official Django v3.3.0 Content Management System. The security vulnerability allows remote attackers or privileged user accounts to inject own malicious script codes to the application-side of the vulnerable modules web context. The persistent web vulnerability is located in the `Name` value of the `Editors - Code Snippet` module POST method request. Remote attackers are able to inject own malicious script code to the snippets name input field to provoke a persistent execution. The injection point is the snippets add module of the editor. The execution point occurs in the `./djangocms_snippet/snippet/` data listing after the add. The data context is not escaped or parsed on add to select and thus results in an execute of any payload inside of the option tag. The attacker vector of the vulnerability is persistent because of the data is stored on add and request method to inject is POST. The vulnerability can be exploited against other privileged user accounts of the django application by interaction with already existing snippets on add. Already added elements become visible for the other user accounts as well on add interaction. The unescaped data is stored in the database of the web-application but when rendered in the frontend or in the edit mode, it's properly escaped. The security risk of the vulnerability is estimated as medium with a cvss (common vulnerability scoring system) count of 3.5. Exploitation of the vulnerability requires a low privileged web-application user account and only low user interaction. Successful exploitation of the vulnerability results in session hijacking, persistent phishing attacks, persistent external redirects to malicious source and persistent manipulation of affected or connected application modules. Request Method(s): [+] POST Vulnerable Module(s): [+] Editor - Snippets (Add) Vulnerable Input(s): [+] Name Parameter(s): [+] select Affected Module(s): [+] Snippets Options Listing [./djangocms_snippet/snippet/] - option Proof of Concept (PoC): ======================= The application-side validation web vulnerability can be exploited by low and high privileged web-application user accounts with low user interaction. For security demonstration or to reproduce the application-side web vulnerability follow the provided information and steps below to continue. Manual steps to reproduce the vulnerability ... 1. Login to your django cms website with version 3.3.0 2. Open the structure module 3. Click to edit a page module Note: Now the editor opens with the main default plugins 4. Mark a text passage and click to the code snippets plugin that is configured by default installation 5. Click the plus to add a new snippet of code 6. Inject a script code payload in java-script to the input field of the Name 7. Save the entry iva POST method request 8. Now click the box to choose the vulnerable injected payload 9. The script code payload executes in the box listing without secure parse or filter to encode 10. Successful reproduce of the application-side validation vulnerability in the editors snippet module! Note: Multiple accounts can be exploited by the inject of snippets. When another privileged user account includes a snippet the stable saved categories provoke the execution of the payload. PoC: Snippet Module [./djangocms_snippet/snippet/] (Execution Point) ... Source: Gmail -> IFTTT-> Blogger

The Orion Nebula in Infrared from HAWK I

The deepest infrared image of the Orion Nebula has uncovered a bonanza of previously unknown low-mass stars and -- quite possibly -- free floating planets. The picturesque nebula is best known in visible light where it shows a many bright stars and bright glowing gas. Catalogued as M42, the Orion Nebula at a distance of 1300 light years is the closest major star forming region to Earth. One can peer into Orion's pervasive dust in infrared light, as was done again recently with the sophisticated HAWK-I camera attached to one of the European Southern Observatory's Very Large Telescopes in the high mountains of Chile. High resolution versions of the featured infrared deep image show many points of light, many of which are surely brown dwarf stars but some of which are best fit by an unexpectedly high abundance of free-floating planets. Understanding how these low mass objects formed is important to understanding star formation generally and may even help humanity to better understand the early years of our Solar System. via NASA http://ift.tt/29OAIA0

Design flaws of “an anonymous two-factor authenticated key agreement scheme for session ...

Design flaws of “an anonymous two-factor authenticated key agreement scheme for session initiation protocol using elliptic curve cryptography” ...

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Knowledge Representation on the Web revisited: Tools for Prototype Based Ontologies. (arXiv:1607.04809v1 [cs.AI])

In recent years RDF and OWL have become the most common knowledge representation languages in use on the Web, propelled by the recommendation of the W3C. In this paper we present a practical implementation of a different kind of knowledge representation based on Prototypes. In detail, we present a concrete syntax easily and effectively parsable by applications. We also present extensible implementations of a prototype knowledge base, specifically designed for storage of Prototypes. These implementations are written in Java and can be extended by using the implementation as a library. Alternatively, the software can be deployed as such. Further, results of benchmarks for both local and web deployment are presented. This paper augments a research paper, in which we describe the more theoretical aspects of our Prototype system.

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Global Continuous Optimization with Error Bound and Fast Convergence. (arXiv:1607.04817v1 [math.OC])

This paper considers global optimization with a black-box unknown objective function that can be non-convex and non-differentiable. Such a difficult optimization problem arises in many real-world applications, such as parameter tuning in machine learning, engineering design problem, and planning with a complex physics simulator. This paper proposes a new global optimization algorithm, called Locally Oriented Global Optimization (LOGO), to aim for both fast convergence in practice and finite-time error bound in theory. The advantage and usage of the new algorithm are illustrated via theoretical analysis and an experiment conducted with 11 benchmark test functions. Further, we modify the LOGO algorithm to specifically solve a planning problem via policy search with continuous state/action space and long time horizon while maintaining its finite-time error bound. We apply the proposed planning method to accident management of a nuclear power plant. The result of the application study demonstrates the practical utility of our method.

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Piecewise convexity of artificial neural networks. (arXiv:1607.04917v1 [cs.LG])

Although artificial neural networks have shown great promise in applications ranging from computer vision to speech recognition, there remains considerable practical and theoretical difficulty in optimizing their parameters. The seemingly unreasonable success of gradient descent methods in minimizing these non-convex functions remains poorly understood. In this work we offer some theoretical guarantees concerning networks with continuous piecewise affine activation functions, which have in recent years become the norm. We prove three main results. Firstly, that the network is piecewise convex as a function of the input data. Secondly, that the network, considered as a function of the parameters in a single layer, all others held constant, is again piecewise convex. Finally, that the network as a function of all its parameters is piecewise multi-convex, a generalization of biconvexity. Accordingly, we show that any point to which gradient descent converges is a local minimum of some piece. Thus gradient descent converges to non-minima only at the boundaries of pieces. These results might offer some insights into the effectiveness of gradient descent methods in optimizing this class of networks.

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