Anonymous

Showing 1-8 of 8 results for “Anonymous”. Sorted by date added, Popularity, Relevance, Release date, Title, Author. Filters. Filter search results.

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I have a new follower on Twitter

Viptela
Viptela provides Enterprise Grade SD-WAN technology that allows global companies to build cloud-aware, secure and policy-driven WAN infrastructure.
San Jose, CA
http://t.co/WOkqjt1XPh
Following: 6077 - Followers: 5590

December 24, 2016 at 07:28PM via Twitter http://twitter.com/Viptela

Not working with anonymous post

I allowed anonymous post. With this condition author email stored in custom fields but its send approval email to admin(Registered User). custom field ...

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Cheaters Anonymous Lacey Silks $3.99

Lees Cheaters Anonymous door Lacey Silks met Kobo. We're both addicted to sex, just not with each other. High school friends - nothing more.

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Anonymous

Showing 1-10 of 10 results for “Anonymous”. Sorted by date added, Popularity, Relevance, Release date, Title, Author. Filters. Filter search results.

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Hackers threaten to take down Xbox Live and PSN on Christmas Day

Bad news for gamers! It's once again the time when most of you will get new PlayStations and XBoxes that continue to be among the most popular gifts for Christmas, but possibilities are you'll not be able to log into the online gaming console, just like what happens on every Christmas holidays. On 2014 Christmas holidays, the notorious hacker group Lizard Squad knocked the PlayStation

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Once Upon a Solstice Eve

Once upon a solstice eve a little prince gazed across a frozen little planet at the edge of a large galaxy. The little planet was planet Earth of course, seen in this horizon to horizon, nadir to zenith projection, a digitally stitched mosaic from the shores of the Sec reservoir in the Czech Republic. So the large galaxy must be the Milky Way, and the brightest beacon on the planet's horizon Venus, visible around the globe as this season's brilliant evening star. Celestial treasures in surrounding dark skies include the Pleiades star cluster, and the North America nebula found along a dusty galactic rift. Embracing Venus, Zodiacal light traces a faint band across the night, but the more colorful pillars of light shine above streets a little closer to home. via NASA http://ift.tt/2ik6RWz

Ravens: WR Steve Smith Sr. (thigh) listed as questionable for Sunday's game vs. Steelers; CB Jimmy Smith (ankle) out (ESPN)

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Anonymous Mask Icon

Free flat Anonymous Mask icon of Color; available for download in PNG, SVG and as a font.

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[FD] [RT-SA-2016-001] Padding Oracle in Apache mod_session_crypto

Advisory: Padding Oracle in Apache mod_session_crypto During a penetration test, RedTeam Pentesting discovered a Padding Oracle vulnerability in mod_session_crypto of the Apache web server. This vulnerability can be exploited to decrypt the session data and even encrypt attacker-specified data. Details ======= Product: Apache HTTP Server mod_session_crypto Affected Versions: 2.3 to 2.5 Fixed Versions: 2.4.25 Vulnerability Type: Padding Oracle Security Risk: high Vendor URL: http://ift.tt/2inbjjq Vendor Status: fixed version released Advisory URL: http://ift.tt/2hPnwAx Advisory Status: published CVE: CVE-2016-0736 CVE URL: http://ift.tt/2inciA4 Introduction ============ The module mod_session_crypto of the Apache HTTP Server can be used in conjunction with the modules mod_session and mod_session_cookie to store session data in an encrypted cookie within the users' browsers. This avoids server-side session state so that incoming HTTP requests can be easily distributed amongst a number of application web servers which do not need to share session state. More Details ============ The module mod_session_crypto uses symmetric cryptography to encrypt and decrypt session data and uses mod_session to store the encrypted data in a cookie (usually called "session") within the user's browser. The decrypted session is then made available to the application in an environment variable (in case of a CGI script) or in a custom HTTP request header. The application can add a custom HTTP response header (usually "X-Replace-Session") which instructs the HTTP server to replace the session's content with the value of the header. Detailed instructions to set up mod_session and mod_session_crypto can be found in the documentation: http://ift.tt/2hPgHib The module mod_session_crypto is configured to use either 3DES or AES with various key sizes, defaulting to AES256. Encryption is handled by the function "encrypt_string": modules/session/mod_session_crypto.c

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BIX Certificates: Cryptographic Tokens for Anonymous Transactions Based on Certificates Public ...

With the widespread use of Internet, Web, and mobile technologies, a new category of applications and transactions that requires anonymity is gaining ...

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Anonymous donor puts $10000 check in Salvation Army kettle

GREENSBURG, Pa. (AP) — A donor who wishes to remain anonymous dropped a $10,000 check into a Salvation Army kettle in western ...

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An Airplane Glory

Looking out the window of an airplane, you might be lucky enough to see "the glory" in the direction directly opposite the Sun. Before airplanes, the phenomenon, known to some as the heiligenschein or the Specter of the Brocken, was sometimes seen from mountaintops. There, when conditions were right, one could look away from the Sun and see what appeared to be the shadow of a giant surrounded by a bright halo. The giant turns out to be the observer, as in the modern version a silhouette of an plane frequently occupies the glory's center. This bright glory was photographed two weeks ago over Michigan from an airplane on approach to O'Hare International Airport. The cause of the glory is still being researched and is relatively complex. Surely, small droplets of water in some way reflect, refract, and diffract sunlight backwards towards the Sun. The phenomenon has similar counterparts in other branches of science including astronomy, where looking out from the Earth in the direction opposite the Sun yields a bright spot called the gegenschein. via NASA http://ift.tt/2hVAYR2

Moon Phase and Libration, 2017

Dial-A-MoonMonth: Day: UT Hour: init_user_date();show_moon_image(); show_moon_info();Click on the image to download a high-resolution version with labels for craters near the terminator.The animation archived on this page shows the geocentric phase, libration, position angle of the axis, and apparent diameter of the Moon throughout the year 2017, at hourly intervals. Until the end of 2017, the initial Dial-A-Moon image will be the frame from this animation for the current hour.More in this series:North 2016 | 2015 | 2014 | 2013 | 2012 | 2011South 2017 | 2016 | 2015 | 2014 | 2013Lunar Reconnaissance Orbiter (LRO) has been in orbit around the Moon since the summer of 2009. Its laser altimeter (LOLA) and camera (LROC) are recording the rugged, airless lunar terrain in exceptional detail, making it possible to visualize the Moon with unprecedented fidelity. This is especially evident in the long shadows cast near the terminator, or day-night line. The pummeled, craggy landscape thrown into high relief at the terminator would be impossible to recreate in the computer without global terrain maps like those from LRO.The Moon always keeps the same face to us, but not exactly the same face. Because of the tilt and shape of its orbit, we see the Moon from slightly different angles over the course of a month. When a month is compressed into 24 seconds, as it is in this animation, our changing view of the Moon makes it look like it's wobbling. This wobble is called libration.The word comes from the Latin for "balance scale" (as does the name of the zodiac constellation Libra) and refers to the way such a scale tips up and down on alternating sides. The sub-Earth point gives the amount of libration in longitude and latitude. The sub-Earth point is also the apparent center of the Moon's disk and the location on the Moon where the Earth is directly overhead.The Moon is subject to other motions as well. It appears to roll back and forth around the sub-Earth point. The roll angle is given by the position angle of the axis, which is the angle of the Moon's north pole relative to celestial north. The Moon also approaches and recedes from us, appearing to grow and shrink. The two extremes, called perigee (near) and apogee (far), differ by about 14.The most noticed monthly variation in the Moon's appearance is the cycle of phases, caused by the changing angle of the Sun as the Moon orbits the Earth. The cycle begins with the waxing (growing) crescent Moon visible in the west just after sunset. By first quarter, the Moon is high in the sky at sunset and sets around midnight. The full Moon rises at sunset and is high in the sky at midnight. The third quarter Moon is often surprisingly conspicuous in the daylit western sky long after sunrise.Celestial north is up in these images, corresponding to the view from the northern hemisphere. The descriptions of the print resolution stills also assume a northern hemisphere orientation. (There is also a south-up version of this page.)The Moon's OrbitFrom this birdseye view, it's somewhat easier to see that the phases of the Moon are an effect of the changing angles of the sun, Moon and Earth. The Moon is full when its orbit places it in the middle of the night side of the Earth. First and Third Quarter Moon occur when the Moon is along the day-night line on the Earth.The First Point of Aries is at the 3 o'clock position in the image. The sun is in this direction at the March equinox. You can check this by freezing the animation at the 1:03 mark, or by freezing the full animation with the time stamp near March 20 at 10:00 UTC. This direction serves as the zero point for both ecliptic longitude and right ascension.The north pole of the Earth is tilted 23.5 degrees toward the 12 o'clock position at the top of the image. The tilt of the Earth is important for understanding why the north pole of the Moon seems to swing back and forth. In the full animation, watch both the orbit and the "gyroscope" Moon in the lower left. The widest swings happen when the Moon is at the 3 o'clock and 9 o'clock positions. When the Moon is at the 3 o'clock position, the ground we're standing on is tilted to the left when we look at the Moon. At the 9 o'clock position, it's tilted to the right. The tilt itself doesn't change. We're just turned around, looking in the opposite direction.The subsolar and sub-Earth points are the locations on the Moon's surface where the sun or the Earth are directly overhead, at the zenith. A line pointing straight up at one of these points will be pointing toward the sun or the Earth. The sub-Earth point is also the apparent center of the Moon's disk as observed from the Earth.In the animation, the blue dot is the sub-Earth point, and the yellow dot is the subsolar point. The lunar latitude and longitude of the sub-Earth point is a measure of the Moon's libration. For example, when the blue dot moves to the left of the meridian (the line at 0 degrees longitude), an extra bit of the Moon's western limb is rotating into view, and when it moves above the equator, a bit of the far side beyond the north pole becomes visible.At any given time, half of the Moon is in sunlight, and the subsolar point is in the center of the lit half. Full Moon occurs when the subsolar point is near the center of the Moon's disk. When the subsolar point is somewhere on the far side of the Moon, observers on Earth see a crescent phase.The Moon's orbit around the Earth isn't a perfect circle. The orbit is slightly elliptical, and because of that, the Moon's distance from the Earth varies between 28 and 32 Earth diameters, or about 356,400 and 406,700 kilometers. In each orbit, the smallest distance is called perigee, from Greek words meaning "near earth," while the greatest distance is called apogee. The Moon looks largest at perigee because that's when it's closest to us.The animation follows the imaginary line connecting the Earth and the Moon as it sweeps around the Moon's orbit. From this vantage point, it's easy to see the variation in the Moon's distance. Both the distance and the sizes of the Earth and Moon are to scale in this view. In the HD-resolution frames, the Earth is 50 pixels wide, the Moon is 14 pixels wide, and the distance between them is about 1500 pixels, on average.Note too that the Earth appears to go through phases just like the Moon does. For someone standing on the surface of the Moon, the sun and the stars rise and set, but the Earth doesn't move in the sky. It goes through a monthly sequence of phases as the sun angle changes. The phases are the opposite of the Moon's. During New Moon here, the Earth is full as viewed from the Moon.

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Moon Phase and Libration, 2017 South Up

Dial-A-MoonMonth: Day: UT Hour: init_user_date();show_moon_image(); show_moon_info();Click on the image to download a high-resolution version with labels for craters near the terminator.The animation archived on this page shows the geocentric phase, libration, position angle of the axis, and apparent diameter of the Moon throughout the year 2017, at hourly intervals. Until the end of 2017, the initial Dial-A-Moon image will be the frame from this animation for the current hour.More in this series:North 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011South 2016 | 2015 | 2014 | 2013Lunar Reconnaissance Orbiter (LRO) has been in orbit around the Moon since the summer of 2009. Its laser altimeter (LOLA) and camera (LROC) are recording the rugged, airless lunar terrain in exceptional detail, making it possible to visualize the Moon with unprecedented fidelity. This is especially evident in the long shadows cast near the terminator, or day-night line. The pummeled, craggy landscape thrown into high relief at the terminator would be impossible to recreate in the computer without global terrain maps like those from LRO.The Moon always keeps the same face to us, but not exactly the same face. Because of the tilt and shape of its orbit, we see the Moon from slightly different angles over the course of a month. When a month is compressed into 24 seconds, as it is in this animation, our changing view of the Moon makes it look like it's wobbling. This wobble is called libration.The word comes from the Latin for "balance scale" (as does the name of the zodiac constellation Libra) and refers to the way such a scale tips up and down on alternating sides. The sub-Earth point gives the amount of libration in longitude and latitude. The sub-Earth point is also the apparent center of the Moon's disk and the location on the Moon where the Earth is directly overhead.The Moon is subject to other motions as well. It appears to roll back and forth around the sub-Earth point. The roll angle is given by the position angle of the axis, which is the angle of the Moon's north pole relative to celestial north. The Moon also approaches and recedes from us, appearing to grow and shrink. The two extremes, called perigee (near) and apogee (far), differ by more than 10.The most noticed monthly variation in the Moon's appearance is the cycle of phases, caused by the changing angle of the Sun as the Moon orbits the Earth. The cycle begins with the waxing (growing) crescent Moon visible in the west just after sunset. By first quarter, the Moon is high in the sky at sunset and sets around midnight. The full Moon rises at sunset and is high in the sky at midnight. The third quarter Moon is often surprisingly conspicuous in the daylit western sky long after sunrise.Celestial south is up in these images, corresponding to the view from the southern hemisphere. The descriptions of the print resolution stills also assume a southern hemisphere orientation. (There is also a north-up version of this page.)The Moon's OrbitFrom this birdseye view, it's somewhat easier to see that the phases of the Moon are an effect of the changing angles of the sun, Moon and Earth. The Moon is full when its orbit places it in the middle of the night side of the Earth. First and Third Quarter Moon occur when the Moon is along the day-night line on the Earth.The First Point of Aries is at the 3 o'clock position in the image. The sun is in this direction at the March equinox. You can check this by freezing the animation at the 1:03 mark, or by freezing the full animation with the time stamp near March 20 at 10:00 UTC. This direction serves as the zero point for both ecliptic longitude and right ascension.The south pole of the Earth is tilted 23.5 degrees toward the 12 o'clock position at the top of the image. The tilt of the Earth is important for understanding why the north pole of the Moon seems to swing back and forth. In the full animation, watch both the orbit and the "gyroscope" Moon in the lower left. The widest swings happen when the Moon is at the 3 o'clock and 9 o'clock positions. When the Moon is at the 3 o'clock position, the ground we're standing on is tilted to the left when we look at the Moon. At the 9 o'clock position, it's tilted to the right. The tilt itself doesn't change. We're just turned around, looking in the opposite direction.The subsolar and sub-Earth points are the locations on the Moon's surface where the sun or the Earth are directly overhead, at the zenith. A line pointing straight up at one of these points will be pointing toward the sun or the Earth. The sub-Earth point is also the apparent center of the Moon's disk as observed from the Earth.In the animation, the blue dot is the sub-Earth point, and the yellow dot is the subsolar point. The lunar latitude and longitude of the sub-Earth point is a measure of the Moon's libration. For example, when the blue dot moves to the left of the meridian (the line at 0 degrees longitude), an extra bit of the Moon's eastern limb is rotating into view, and when it moves above the equator, a bit of the far side beyond the south pole becomes visible.At any given time, half of the Moon is in sunlight, and the subsolar point is in the center of the lit half. Full Moon occurs when the subsolar point is near the center of the Moon's disk. When the subsolar point is somewhere on the far side of the Moon, observers on Earth see a crescent phase.The Moon's orbit around the Earth isn't a perfect circle. The orbit is slightly elliptical, and because of that, the Moon's distance from the Earth varies between 28 and 32 Earth diameters, or about 356,400 and 406,700 kilometers. In each orbit, the smallest distance is called perigee, from Greek words meaning "near earth," while the greatest distance is called apogee. The Moon looks largest at perigee because that's when it's closest to us.The animation follows the imaginary line connecting the Earth and the Moon as it sweeps around the Moon's orbit. From this vantage point, it's easy to see the variation in the Moon's distance. Both the distance and the sizes of the Earth and Moon are to scale in this view. In the HD-resolution frames, the Earth is 50 pixels wide, the Moon is 14 pixels wide, and the distance between them is about 1500 pixels, on average.Note too that the Earth appears to go through phases just like the Moon does. For someone standing on the surface of the Moon, the sun and the stars rise and set, but the Earth doesn't move in the sky. It goes through a monthly sequence of phases as the sun angle changes. The phases are the opposite of the Moon's. During New Moon here, the Earth is full as viewed from the Moon.

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I have a new follower on Twitter

Jeannie Hill


http://t.co/XwnXKkxlh4
Following: 508 - Followers: 766

December 22, 2016 at 11:08PM via Twitter http://twitter.com/essentialskill

Causal Effect Identification in Acyclic Directed Mixed Graphs and Gated Models. (arXiv:1612.07512v1 [stat.ML])

We introduce a new family of graphical models that consists of graphs with possibly directed, undirected and bidirected edges but without directed cycles. We show that these models are suitable for representing causal models with additive error terms. We provide a set of sufficient graphical criteria for the identification of arbitrary causal effects when the new models contain directed and undirected edges but no bidirected edge. We also provide a necessary and sufficient graphical criterion for the identification of the causal effect of a single variable on the rest of the variables. Moreover, we develop an exact algorithm for learning the new models from observational and interventional data via answer set programming. Finally, we introduce gated models for causal effect identification, a new family of graphical models that exploits context specific independences to identify additional causal effects.

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Non-Deterministic Policy Improvement Stabilizes Approximated Reinforcement Learning. (arXiv:1612.07548v1 [cs.AI])

This paper investigates a type of instability that is linked to the greedy policy improvement in approximated reinforcement learning. We show empirically that non-deterministic policy improvement can stabilize methods like LSPI by controlling the improvements' stochasticity. Additionally we show that a suitable representation of the value function also stabilizes the solution to some degree. The presented approach is simple and should also be easily transferable to more sophisticated algorithms like deep reinforcement learning.

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The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine. (arXiv:1612.07555v1 [cs.AI])

This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence.

The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from bioinformatics. This concept has the potential to be the "double helix" of intelligence, with as much significance for human-level intelligence as has DNA for biological sciences.

Strengths of the SP system include: versatility in the representation of diverse kinds of knowledge; versatility in aspects of intelligence (including: strengths in unsupervised learning; the processing of natural language; pattern recognition at multiple levels of abstraction that is robust in the face of errors in data; several kinds of reasoning (including: one-step `deductive' reasoning; chains of reasoning; abductive reasoning; reasoning with probabilistic networks and trees; reasoning with 'rules'; nonmonotonic reasoning and reasoning with default values; Bayesian reasoning with 'explaining away'; and more); planning; problem solving; and more); seamless integration of diverse kinds of knowledge and diverse aspects of intelligence in any combination; and potential for application in several areas (including: helping to solve nine problems with big data; helping to develop human-level intelligence in autonomous robots; serving as a database with intelligence and with versatility in the representation and integration of several forms of knowledge; serving as a vehicle for medical knowledge and as an aid to medical diagnosis; and several more).

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Solving Set Optimization Problems by Cardinality Optimization via Weak Constraints with an Application to Argumentation. (arXiv:1612.07589v1 [cs.AI])

Optimization - minimization or maximization - in the lattice of subsets is a frequent operation in Artificial Intelligence tasks. Examples are subset-minimal model-based diagnosis, nonmonotonic reasoning by means of circumscription, or preferred extensions in abstract argumentation. Finding the optimum among many admissible solutions is often harder than finding admissible solutions with respect to both computational complexity and methodology. This paper addresses the former issue by means of an effective method for finding subset-optimal solutions. It is based on the relationship between cardinality-optimal and subset-optimal solutions, and the fact that many logic-based declarative programming systems provide constructs for finding cardinality-optimal solutions, for example maximum satisfiability (MaxSAT) or weak constraints in Answer Set Programming (ASP). Clearly each cardinality-optimal solution is also a subset-optimal one, and if the language also allows for the addition of particular restricting constructs (both MaxSAT and ASP do) then all subset-optimal solutions can be found by an iterative computation of cardinality-optimal solutions. As a showcase, the computation of preferred extensions of abstract argumentation frameworks using the proposed method is studied.

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Counting Answer Sets via Dynamic Programming. (arXiv:1612.07601v1 [cs.LO])

While the solution counting problem for propositional satisfiability (#SAT) has received renewed attention in recent years, this research trend has not affected other AI solving paradigms like answer set programming (ASP). Although ASP solvers are designed to enumerate all solutions, and counting can therefore be easily done, the involved materialization of all solutions is a clear bottleneck for the counting problem of ASP (#ASP). In this paper we propose dynamic programming-based #ASP algorithms that exploit the structure of the underlying (ground) ASP program. Experimental results for a prototype implementation show promise when compared to existing solvers.

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Jointly Extracting Relations with Class Ties via Effective Deep Ranking. (arXiv:1612.07602v1 [cs.AI])

In distant supervised relation extraction, the connection between relations of one entity tuple, which we call class ties, is common. Exploiting this connection may be promising for relation extraction. However, this property is seldom considered by previous work. In this work, to leverage class ties, we propose to make joint relation extraction with a unified model that integrates convolutional neural network with a general pairwise ranking framework, in which two novel ranking loss functions are introduced. Besides, an effective method is proposed to relieve the impact of relation NR (not relation) for model training and test. Experimental results on a widely used dataset show that: (1) Our model is much more superior than the baselines, achieving state-of-the-art performance; (2) Leveraging class ties, joint extraction is indeed better than separated extraction; (3) Relieving the impact of NR will significantly boost our model performance; (4) Our model can primely deal with wrong labeling problem.

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Difficulty Adjustable and Scalable Constrained Multi-objective Test Problem Toolkit. (arXiv:1612.07603v1 [cs.NE])

In order to better understand the advantages and disadvantages of a constrained multi-objective evolutionary algorithm (CMOEA), it is important to understand the nature of difficulty of a constrained multi-objective optimization problem (CMOP) that the CMOEA is going to deal with. In this paper, we first propose three primary types of difficulty to characterize the constraints in CMOPs, including feasibility-hardness, convergence-hardness and diversity-hardness. We then develop a general toolkit to construct difficulty adjustable CMOPs with three types of parameterized constraint functions according to the proposed three primary types of difficulty. In fact, combination of the three primary constraint functions with different parameters can lead to construct a large variety of CMOPs and CMaOPs, whose difficulty can be uniquely defined by a triplet with each of its parameter specifying the level of each primary difficulty type respectively. Based on this toolkit, we suggest fifteen difficulty adjustable CMOPs named DAC-MOP1-15 with different types and levels of difficulty. To study the effectiveness of DAC-MOP1-15, two popular CMOEAs - MOEA/D-CDP and NSGA-II-CDP are adopted to test their performances on them. Furthermore, this toolkit also has the ability to scale the number of objectives. Nine difficulty adjustable constrained many-objective optimization problems (DAC-MaOPs) named DAC-MaOP1-9 with the scalability to the number of objectives are also proposed using this toolkit. Two constrained many-objective evolutionary algorithms (CMaOEAs) - CNSGA-III and CMOEA/DD are applied to test their performances on three, five, seven and ten-objective DAC-MaOP1-9 with different difficulty levels and types.

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Highway and Residual Networks learn Unrolled Iterative Estimation. (arXiv:1612.07771v1 [cs.NE])

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

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

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Facial Expression Recognition Using a Hybrid CNN-SIFT Aggregator. (arXiv:1608.02833v4 [cs.CV] UPDATED)

Recognizing facial expression has remained a challenging task in computer vision. Deriving an effective facial expression recognition is an important step for successful human-computer interaction systems. This paper describes a novel approach towards facial expression recognition task. It is motivated by the success of Convolutional Neural Networks (CNN) on face recognition problems. Unlike other works, we focus on getting good accuracy results while requiring only a small sample data to train the model by merging the CNN and SIFT features. The proposed classification model is an aggregation of multiple deep convolutional neural networks and a hybrid CNN-SIFT classifiers. The goal of using SIFT features is to increase the performance on small data as SIFT does not require large training data to generate useful features. The model has been tested on FER-2013, CK+ and SFEW 2.0 datasets. The results showed how CNN-SIFT feature improve the accuracy when added as a voting member in an ensemble classifier. It generates state-of-art results on FER-2013 and CK+ datasets, where it achieved 73.58% on FER-2013 and 99.35% on CK+.

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Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge. (arXiv:1611.04146v2 [cs.AI] UPDATED)

In this paper, we propose commonsense knowledge enhanced embeddings (KEE) for solving the Pronoun Disambiguation Problems (PDP). The PDP task we investigate in this paper is a complex coreference resolution task which requires the utilization of commonsense knowledge. This task is a standard first round test set in the 2016 Winograd Schema Challenge. In this task, traditional linguistic features that are useful for coreference resolution, e.g. context and gender information, are no longer effective anymore. Therefore, the KEE models are proposed to provide a general framework to make use of commonsense knowledge for solving the PDP problems. Since the PDP task doesn't have training data, the KEE models would be used during the unsupervised feature extraction process. To evaluate the effectiveness of the KEE models, we propose to incorporate various commonsense knowledge bases, including ConceptNet, WordNet, and CauseCom, into the KEE training process. We achieved the best performance by applying the proposed methods to the 2016 Winograd Schema Challenge. In addition, experiments conducted on the standard PDP task indicate that, the proposed KEE models could solve the PDP problems by achieving 66.7% accuracy, which is a new state-of-the-art performance.

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NewsQA: A Machine Comprehension Dataset. (arXiv:1611.09830v2 [cs.CL] UPDATED)

We present NewsQA, a challenging machine comprehension dataset of over 100,000 question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting in spans of text from the corresponding articles. We collect this dataset through a four-stage process designed to solicit exploratory questions that require reasoning. A thorough analysis confirms that NewsQA demands abilities beyond simple word matching and recognizing entailment. We measure human performance on the dataset and compare it to several strong neural models. The performance gap between humans and machines (25.3% F1) indicates that significant progress can be made on NewsQA through future research. The dataset is freely available at http://ift.tt/2gDWBrf.

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Famously Anonymous: Tor Social Networks

Humans are social creatures. So it should come as no surprise that there are almost as many social networks on Tor as there are on the clearnet.

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ARES: Adaptive Receding-Horizon Synthesis of Optimal Plans. (arXiv:1612.07059v1 [cs.AI])

We introduce ARES, an efficient approximation algorithm for generating optimal plans (action sequences) that take an initial state of a Markov Decision Process (MDP) to a state whose cost is below a specified (convergence) threshold. ARES uses Particle Swarm Optimization, with adaptive sizing for both the receding horizon and the particle swarm. Inspired by Importance Splitting, the length of the horizon and the number of particles are chosen such that at least one particle reaches a next-level state, that is, a state where the cost decreases by a required delta from the previous-level state. The level relation on states and the plans constructed by ARES implicitly define a Lyapunov function and an optimal policy, respectively, both of which could be explicitly generated by applying ARES to all states of the MDP, up to some topological equivalence relation. We also assess the effectiveness of ARES by statistically evaluating its rate of success in generating optimal plans. The ARES algorithm resulted from our desire to clarify if flying in V-formation is a flocking policy that optimizes energy conservation, clear view, and velocity alignment. That is, we were interested to see if one could find optimal plans that bring a flock from an arbitrary initial state to a state exhibiting a single connected V-formation. For flocks with 7 birds, ARES is able to generate a plan that leads to a V-formation in 95% of the 8,000 random initial configurations within 63 seconds, on average. ARES can also be easily customized into a model-predictive controller (MPC) with an adaptive receding horizon and statistical guarantees of convergence. To the best of our knowledge, our adaptive-sizing approach is the first to provide convergence guarantees in receding-horizon techniques.

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Anonymous proxy ip address

Anonymous proxy ip address Proxy servers have a number of limitations.. Flash Player can be used to reveal the web surfer's IP address even if .

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Climate scientists swing back, launch anonymous hotline for gov't employees to report Trump ...

Donald Trump and his cabal of climate change deniers, and enablers, will unleash an assault on everything this country holds dear in less than a ...

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Anonymous donor pays off lunch balances at Maple Grove High

The woman, who asked to be anonymous, donated $3,227 to cover all overdue lunch accounts plus an additional $2,000 for future unpaid balances.

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Anonymous function versus File in matlabfunction

Anonymous function versus File in matlabfunction. Learn more about optimization.

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Anonymous Hacks Thailand Navy Site to Protest Censorship

Anonymous Hacks Thailand Navy Site to Protest Censorship. Tweet ... CyberGuerrilla Anonymous Nexus » Way's to connect to Cyberguerrilla IRC.

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Russia Wants Apple to Unlock iPhone belonging to Killer of Russian Ambassador

You might have also seen a viral video of the assassination of the Russian ambassador to Turkey that quickly spread through the Internet worldwide. Russian Ambassador Andrei Karlov was shot dead by an off-duty police officer in Ankara on December 19 when the ambassador was giving a speech at an art gallery. The shooter managed to pretend himself as his official bodyguard and later shot to

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Raspberry Pi launches PIXEL OS for Mac and Windows PCs

Here's the Raspberry Pi's Christmas treat for tech community! The Raspberry Pi Foundation has released an experimental version of its lightweight Linux-based Debian operating system called PIXEL OS that can run on most standard desktop computers ships with Windows and Mac OS X without the need of a Raspberry Pi. <!-- adsense --> Initially launched in September this year, the PIXEL operating

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ISS Daily Summary Report – 12/21/2016

Myotendinous and Neuromuscular Adaptation to Long-term Spaceflight Sarcolab-3: Today’s second operational day for the Sarcolab-3 experiment began with converting the Muscle Atrophy Research & Exercise System (MARES) from the ankle measurement configuration to the knee measurement configuration. The subject donned Percutaneus Electrical Muscle Stimulator (PEMS) and Electromyography (EMG) electrodes to stimulate and measure calf muscle and tendon response at the back of the knee (calf muscle origin). During the knee joint evaluation, the subject sat on the MARES dynamometer with the chair and pantograph set to obtain knee flexion and extension from 90 degree knee angle to full extension with the knee torque adapter securely fixed to the shin. The inflight data will be compared to pre and post flight measurements to measure the impact of a hypothesized microgravity induced muscle loss. Sarcolab investigates the adaptation and deterioration of the soleus, or calf muscle, where it joins the Achilles tendon which links it to the heel and carries loads from the entire body. Muscle fiber samples are taken from crew members before and after flight and analyzed for changes in structural and chemical properties. MRI and ultrasound tests and electrode stimulation are conducted to help assess muscle and tendon changes caused by microgravity exposure. Packed Bed Reactor Experiment (PBRE) Module Exchange: The crew exchanged PBRE modules, removing Test Module/Wetting and installing the Test Module/Non-Wetting into the PBRE located in the Microgravity Science Glovebox (MSG) Work Volume (WV).  The activity, originally scheduled for two days was successfully completed in one day. The PBRE investigation studies the behavior of gases and liquids when they flow simultaneously through a column filled with fixed porous media. The porous media or “packing” can be made of different shapes and materials and are used widely in chemical engineering as a means to enhance the contact between two immiscible fluid phases (e.g., liquid-gas, water-oil, etc.). Packed columns can serve as reactors, scrubbers, strippers, etc. in systems where efficient interphase contact is desired, both on Earth and in space.  Electrostatic Levitation Furnace (ELF): During yesterday’s cartridge exchange, a bolt floated away. It was subsequently found and the exchange activities were rescheduled for today. The crew successfully removed the calibration cartridge and installed the test cartridge in the ELF. The Japanese Aerospace Exploration Agency’s (JAXA) ELF is located in Multi-Purpose Small Payload Rack (MSPR)-2. It is an experimental facility designed to levitate/melt/solidify materials by containerless processing techniques using the Electrostatic Levitation method. With this facility, thermophysical properties of high temperature melts can be measured, and solidification from deeply undercooled melts can be achieved. Japanese Experiment Module (JEM) Inter Module Ventilation (IMV) Cleaning: The crew cleaned the JEM Pressurized Module (JPM) starboard forward fan and IMV grille. The fan and grille were temporarily removed during the cleaning process.  Medical Emergency On-Board Training (OBT): The 49S crew reviewed medical emergency procedures and rescuer roles during a medical event requiring Cardiopulmonary Resuscitation (CPR) as follows: Review emergency medical hardware configuration and determine desired deployed locations. Determine individual preference for performing chest compressions in microgravity. Discuss crew communication and coordination of care during an emergency medical event. Today’s Planned Activities All activities were completed unless otherwise noted. Crew Evaluation of New Food Items Calf Volume Measurement Personal CO2 Monitor iPad Application Restart HMS PHS Evaluation Setup HMS PHS – Subject HMS PHS – CMO XF305 Camcorder Setup MSPR2 ELF Retrieve SARCOLAB. MARES knee configuration installation MSPR2 ELF Retrieve Sub JEM Airlock Press Combustion Integrated Rack Hardware Return Cleaning of TV System LIV voltage converter vent grille MARES Knee Shaving Preparation Study of veins in lower extremities MRM2 comm config to support the P/L Ops JEM Airlock Leak Check Kulonovskiy Kristall Experiment Run Electrostatic Levitation Furnace (ELF) Ground Connection EMG electrodes installation and Sarcolab knee protocol execution SARCOLAB. subject electrodes equipment assistance Electrostatic Levitation Photodetector(PD) Amplifier setting MRM2 Comm Reconfig for Nominal Ops Inspection of SM space behind panels for contamination Study of veins in lower extremities MSPR2 ELF Install MSPR2 ELF Install Sub KULONOVSKYI KRISTALL. Copying data to removable hard drive Verification of ИП-1 Flow Sensor Position SARCOLAB. MARES Laptop and Hardware Powerdown TIMER.  Battery Charge Health Maintenance System (HMS) Periodic Health Status (PHS) Stow Hardware Personal CO2 Monitor Power Cycle ISS HAM Service Module Pass Packed Bed Reactor Experiment Test Module Exchange Greetings Video Footage ESA ACTIVE DOSIMETER MOBILE UNIT SWAP CheCS OBT ТМ168-04 Sensor Inspection and Photography Nikon D3 Camera Digital Image Sensor Cleaning TIMER. Setup and Initiate Experiment Ops Video Packed Bed Reactor Experiment Test Module Exchange Perform SSC Server-1 Primary Hard Drive Reseat VIZIR. Experiment Ops JEM Inter Module Ventilation (IMV) Cleaning Tightening QD Screw Clamps on MRM2-Soyuz 732 Docking Mechanism Interface TIMER. Experiment Ops Video Termination and Cleanup MOTOCARD. Experiment Ops MOTOCARD. Operator Assistance with the Experiment IMS Update Early Mission Debrief Conference Extravehicular Mobility Unit (EMU) Long Life Battery (LLB) Charge Initiate Health Maintenance System (HMS) – ESA Nutritional Assessment Personal CO2 Monitor Power Cycle Completed Task List Items EHS Dosimeter stow SLM data transfer TOCA WRS analysis VEG03 pillow water Ground Activities All activities were completed unless otherwise noted. MSS powerdown Three-Day Look Ahead: Thursday, 12/22: EVA Tool Config, PBRE Module Exchange, J-SSOC Removal, EVA C&W OBT, Sarcolab Friday, 12/23: EVA loop scrub, VEG03, Galley rack data cable install, Fluid Shifts Saturday, 12/24: Crew off duty, housekeeping QUICK ISS Status – Environmental Control Group:     Component Status Elektron Off Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off          [СКВ] 2 – SM Air Conditioner System (“SKV2”) Off Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Idle Oxygen Generation Assembly (OGA) Process Urine Processing Assembly (UPA) Process Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

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Wired, “Anonymous' Barrett Brown Is Free—and Ready to Pick New Fights”

Of all those books, he found particular inspiration in the autobiography of Emma Goldman, the anarcho-communist agitator who served two prison ...

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NIST Calls Development of Quantum-Proof Encryption Algorithms

Quantum Computers – Boon or Bane? Quantum computers can perform operations much more quickly and efficiently even with the use of less energy than conventional computers, but that's bad news for encryption — a process which scrambles data according to a massively complex mathematical code. In theory, quantum computers can break almost all the existing encryption algorithms used on the

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'Anonymous Billionaire' in the Spotlight After 1000% Rally

Luiz Alves Paes de Barros is something of an enigma in Sao Paulo's financial circles. At 69, he's known around town as the “anonymous billionaire” ...

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App combats online bullying by sending anonymous compliments

App combats online bullying by sending anonymous compliments. Daily Dashboard | Dec 21, 2016. Facebook; Twitter; Google; LinkedIn; Comment ...

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I have a new follower on Twitter

Kelly Williams
https://t.co/4JW9jxB4Ng
Cornelius, NC, United States
https://t.co/RARdZ64e8K
Following: 1343 - Followers: 1033

December 21, 2016 at 09:20PM via Twitter http://twitter.com/DaintyDots

AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. (arXiv:1612.06915v1 [cs.AI])

Evaluating agent performance when outcomes are stochastic and agents use randomized strategies can be challenging when there is limited data available. The variance of sampled outcomes may make the simple approach of Monte Carlo sampling inadequate. This is the case for agents playing heads-up no-limit Texas hold'em poker, where man-machine competitions have involved multiple days of consistent play and still not resulted in statistically significant conclusions even when the winner's margin is substantial. In this paper, we introduce AIVAT, a low variance, provably unbiased value assessment tool that uses an arbitrary heuristic estimate of state value, as well as the explicit strategy of a subset of the agents. Unlike existing techniques which reduce the variance from chance events, or only consider game ending actions, AIVAT reduces the variance both from choices by nature and by players with a known strategy. The resulting estimator in no-limit poker can reduce the number of hands needed to draw statistical conclusions by more than a factor of 10.

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Stochastic Runtime Analysis of a Cross Entropy Algorithm for Traveling Salesman Problems. (arXiv:1612.06962v1 [cs.DS])

This article analyzes the stochastic runtime of a Cross-Entropy Algorithm on two classes of traveling salesman problems. The algorithm shares main features of the famous Max-Min Ant System with iteration-best reinforcement.

For simple instances that have a $\{1,n\}$-valued distance function and a unique optimal solution, we prove a stochastic runtime of $O(n^{6+\epsilon})$ with the vertex-based random solution generation, and a stochastic runtime of $O(n^{3+\epsilon}\ln n)$ with the edge-based random solution generation for an arbitrary $\epsilon\in (0,1)$. These runtimes are very close to the known expected runtime for variants of Max-Min Ant System with best-so-far reinforcement. They are obtained for the stronger notion of stochastic runtime, which means that an optimal solution is obtained in that time with an overwhelming probability, i.e., a probability tending exponentially fast to one with growing problem size.

We also inspect more complex instances with $n$ vertices positioned on an $m\times m$ grid. When the $n$ vertices span a convex polygon, we obtain a stochastic runtime of $O(n^{3}m^{5+\epsilon})$ with the vertex-based random solution generation, and a stochastic runtime of $O(n^{2}m^{5+\epsilon})$ for the edge-based random solution generation. When there are $k = O(1)$ many vertices inside a convex polygon spanned by the other $n-k$ vertices, we obtain a stochastic runtime of $O(n^{4}m^{5+\epsilon}+n^{6k-1}m^{\epsilon})$ with the vertex-based random solution generation, and a stochastic runtime of $O(n^{3}m^{5+\epsilon}+n^{3k}m^{\epsilon})$ with the edge-based random solution generation. These runtimes are better than the expected runtime for the so-called $(\mu\!+\!\lambda)$ EA reported in a recent article, and again obtained for the stronger notion of stochastic runtime.

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Disjunctive Boolean Kernels for Collaborative Filtering in Top-N Recommendation. (arXiv:1612.07025v1 [cs.IR])

In many personalized recommendation problems available data consists only of positive interactions (implicit feedback) between users and items. This problem is also known as One-Class Collaborative Filtering (OC-CF). Linear models usually achieves state-of-the-art performances on OC-CF problems and many efforts have been devoted to build more expressive and complex representations able to improve the recommendations but with no much success. Recent analysis shows that collaborative filtering (CF) datasets have peculiar characteristics such as high sparsity and a long tailed distribution of the ratings. In this paper we propose a boolean kernel, called Disjunctive Kernel, which is less expressive than the linear one but it is able to alleviate the sparsity issue in CF contexts. The embedding of this kernel is composed by all the combinations of a certain degree $d$ of the input variables, and these combined features are semantically interpreted as disjunctions of the input variables. Experiments on several CF datasets show the effectiveness and the efficiency of the proposed kernel.

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Deep-learning in Mobile Robotics - from Perception to Control Systems: A Survey on Why and Why not. (arXiv:1612.07139v1 [cs.RO])

Deep-learning has dramatically changed the world overnight. It greatly boosted the development of visual perception, object detection, and speech recognition, etc. That was attributed to the multiple convolutional processing layers for abstraction of learning representations from massive data. The advantages of deep convolutional structures in data processing motivated the applications of artificial intelligence methods in robotic problems, especially perception and control system, the two typical and challenging problems in robotics. This paper presents a survey of the deep-learning research landscape in mobile robotics. We start with introducing the definition and development of deep-learning in related fields, especially the essential distinctions between image processing and robotic tasks. We described and discussed several typical applications and related works in this domain, followed by the benefits from deep-learning, and related existing frameworks. Besides, operation in the complex dynamic environment is regarded as a critical bottleneck for mobile robots, such as that for autonomous driving. We thus further emphasize the recent achievement on how deep-learning contributes to navigation and control systems for mobile robots. At the end, we discuss the open challenges and research frontiers.

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Understanding Error Correction and its Role as Part of the Communication Channel in Environments composed of Self-Integrating Systems. (arXiv:1612.07294v1 [cs.AI])

The raise of complexity of technical systems also raises knowledge required to set them up and to maintain them. The cost to evolve such systems can be prohibitive. In the field of Autonomic Computing, technical systems should therefore have various self-healing capabilities allowing system owners to provide only partial, potentially inconsistent updates of the system. The self-healing or self-integrating system shall find out the remaining changes to communications and functionalities in order to accommodate change and yet still restore function. This issue becomes even more interesting in context of Internet of Things and Industrial Internet where previously unexpected device combinations can be assembled in order to provide a surprising new function. In order to pursue higher levels of self-integration capabilities I propose to think of self-integration as sophisticated error correcting communications. Therefore, this paper discusses an extended scope of error correction with the purpose to emphasize error correction's role as an integrated element of bi-directional communication channels in self-integrating, autonomic communication scenarios.

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Yum-me: A Personalized Nutrient-based Meal Recommender System. (arXiv:1605.07722v2 [cs.HC] UPDATED)

Nutrient-based meal recommendations have the potential to help individuals prevent or manage conditions such as diabetes and obesity. However, learning people's food preferences and making recommendations that simultaneously appeal to their palate and satisfy nutritional expectations are challenging. Existing approaches either only learn high-level preferences or require a prolonged learning period. We propose Yum-me, a personalized nutrient-based meal recommender system designed to meet individuals' nutritional expectations, dietary restrictions, and fine-grained food preferences. Yum-me enables a simple and accurate food preference profiling procedure via a visual quiz-based user interface, and projects the learned profile into the domain of nutritionally appropriate food options to find ones that will appeal to the user. We present the design and implementation of Yum-me, and further describe and evaluate two innovative components: 1) An open source state-of-the-art food image analysis model, named FoodDist. We demonstrate FoodDist's superior performance through careful benchmarking, and discuss its applicability across a wide array of dietary applications. 2) A novel online learning framework that learns food preference from itemwise and pairwise image comparisons. We evaluate the framework in a field study of 227 anonymous users and demonstrate that it outperforms other baselines by a significant margin. Finally, we conduct an end-to-end validation of the feasibility and effectiveness of Yum-me through a 60-person user study, in which Yum-me improves the recommendation acceptance rate by 42.63%.

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Revisiting Causality Inference in Memory-less Transition Networks. (arXiv:1608.02658v3 [stat.ML] UPDATED)

Several methods exist to infer causal networks from massive volumes of observational data. However, almost all existing methods require a considerable length of time series data to capture cause and effect relationships. In contrast, memory-less transition networks or Markov Chain data, which refers to one-step transitions to and from an event, have not been explored for causality inference even though such data is widely available. We find that causal network can be inferred from characteristics of four unique distribution zones around each event. We call this Composition of Transitions and show that cause, effect, and random events exhibit different behavior in their compositions. We applied machine learning models to learn these different behaviors and to infer causality. We name this new method Causality Inference using Composition of Transitions (CICT). To evaluate CICT, we used an administrative inpatient healthcare dataset to set up a network of patients transitions between different diagnoses. We show that CICT is highly accurate in inferring whether the transition between a pair of events is causal or random and performs well in identifying the direction of causality in a bi-directional association.

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Anonymous Donor Gives Mass. Church $100k Winning Lottery Ticket

Conway said of the anonymous donor “He's really really touched people and inspired them and made them feel better about humanity to tell you the ...

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Drafts for anonymous users

Hehe, we shouldn't be so racist about anonymous guys :) As inspired in http://ift.tt/2ihbtJa it should be ...

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Eric Weddle and Dennis Pitta among Ravens' snubs for 2017 Pro Bowl - Jamison Hensley (ESPN)

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Sharpless 308: Star Bubble

Blown by fast winds from a hot, massive star, this cosmic bubble is huge. Cataloged as Sharpless 2-308 it lies some 5,200 light-years away toward the constellation of the Big Dog (Canis Major) and covers slightly more of the sky than a full moon. That corresponds to a diameter of 60 light-years at its estimated distance. The massive star that created the bubble, a Wolf-Rayet star, is the bright one near the center of the nebula. Wolf-Rayet stars have over 20 times the mass of the Sun and are thought to be in a brief, pre-supernova phase of massive star evolution. Fast winds from this Wolf-Rayet star create the bubble-shaped nebula as they sweep up slower moving material from an earlier phase of evolution. The windblown nebula has an age of about 70,000 years. Relatively faint emission captured in the expansive image is dominated by the glow of ionized oxygen atoms mapped to a blue hue. via NASA http://ift.tt/2gXLXYn

Ravens Image: WR Steve Smith Jr. wears elf costume to his Wednesday media session; wore a Yoda outfit a few weeks ago (ESPN)

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Ravens: CB Jimmy Smith (sprained ankle) not practicing Wednesday; missed 1 game after sustaining injury in Week 14 (ESPN)

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Search results not coming for anonymous users

I have a view which displays the search results with full text search exposed. The results are coming for authenticated user but for anonymous user its ...

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ISS Daily Summary Report – 12/20/2016

Myotendinous and Neuromuscular Adaptation to Long-term Spaceflight (Sarcolab)-3: Yesterday, the crew configured the Muscle Atrophy Research & Exercise System (MARES) in the Columbus module.  Today they completed the second of three in-flight sessions of joint-NASA-ESA-Russia Sarcolab experiment. The subject ingressed MARES, followed by the operator performing ultrasound measurements of the right calf muscle with remote guidance and direction assistance from ground specialists. Subject then donned Percutaneus Electrical Muscle Stimulator (PEMS) for electrical stimulation at rest and during voluntary muscle contraction, and Electromyography (EMG) electrodes to measure calf muscle and tendon response at the ankle (calf muscle insertion). The MARES equipment and software is used to measure calf strength during spaceflight. The inflight data will then be compared to preflight and postflight measurements to measure the impact of a hypothesized microgravity induced muscle loss. The goal of the Sarcolab investigation is to advance the understanding of muscle function and atrophy in space. Results will contribute to further improvement of countermeasures for long duration spaceflight. Fluids Integrated Rack (FIR) Image Processing and Storage Unit (IPSU) Remove and Replace (R&R): The crew removed the degraded IPSU from the FIR and replaced it with a spare unit.  Next week, the ACE-T-1 module delivered on HTV-6 will be installed and will run for 6 weeks.  SpaceX-10 will deliver the Light Microscopy Module (LMM) Biophysics experiment which requires full IPSU capabilities, however, based on scheduling constraints, the IPSU was replaced prior to the ACE-T-1 exchange.  The Effect of Macromolecular Transport of Microgravity Protein Crystallization (LMM Biophysics-1) studies why Proteins crystallized in microgravity are often higher quality than those grown on Earth, examining the movement of single protein molecules in microgravity. Advanced Colloids Experiment-Temperature control-1 (ACE-T-1) studies tiny suspended particles which were designed by scientists to connect themselves in a specific way to form organized structures within water. Materials having complex structures and unique properties potentially can be made with more knowledge of how these particles are joined together and the conditions which control their behaviors. FIR is a complementary fluid physics research facility designed to host investigations in areas such as colloids, gels, bubbles, wetting and capillary action, and phase changes, including boiling and cooling. Combustion Integration Rack (CIR) Operations: The crew performed planned maintenance and troubleshooting on the CIR.  In preparation for installation of the Cool Flames Investigation (CFI), the crew replaced a failed Fluids and Combustion Facility (FCF) IPSU and removed the CIR Low Light Level – Ultraviolet (LLL-UV) Imaging Package which was replaced with a CIR Intensived Camera Package. Results from the inspection were provided to ground teams for further troubleshooting procedure development.  CFI provides new insight into the phenomenon where some types of fuels initially burn very hot, then appear to go out but they continue burning at a much lower temperature with no visible flames (cool flames). Understanding cool flame combustion assists scientists in developing new engines and fuels that are more efficient and less harmful to the environment. Electrostatic Levitation Furnace (ELF) Cartridge Exchange: The crew attempted to perform the first of two days of cartridge exchange operations in Japan Aerospace Exploration Agency’s (JAXA) ELF located in Multi-Purpose Small Payload Rack (MSPR)-2. During the activity a bolt required for operations floated away.  The bolt was recovered, however, due to scheduling constraints, remaining activities will require being rescheduled.  ELF is an experimental facility designed to levitate/melt/solidify materials by containerless processing techniques using the Electrostatic Levitation method. With this facility, thermophysical properties of high temperature melts can be measured and solidification from deeply undercooled melts can be achieved.  48S Emergency Egress On-Board Training (OBT): The 48S crew completed this OBT to practice exiting the ISS in case of an emergency. The training is scheduled for 12-14 weeks aboard the ISS and every 2.5 months thereafter. Mobile Servicing System (MSS) Operations: Overnight, ground teams removed the failed Camera Light and Pan Assembly (CLPA) from the Space Station Remote Manipulator System (SSRMS) Tip Elbow (Boom B) and installed it onto the Mobile Transporter Relay Assembly (MTRA) wedge interface located on the Mobile Base System (MBS). A spare CLPA was flown on H-II Transfer Vehicle 6 (HTV-6) and installation on the SSRMS is scheduled as a get ahead task during the second Lithium Ion Battery replacement EVA in January. Following CLPA removal, the SSRMS and SPDM were configured in a park configuration. H-2 Transfer Vehicle (HTV) Cargo Operations: The crew has completed ~29 hours of cargo transfer. There are ~13 hours of transfer remaining to be completed. Today’s Planned Activities All activities were completed unless otherwise noted. ESA PAO Recorded Message St.Exupery Writing Contest Crew Evaluation of New Food Items Video Footage of Greetings Preparation of Reports for Roscosmos Web Site and Social Media URAGAN. Observation and photography EKON-M. Observations and photography Reminder HRF Generic Urine Collection End Reminder ESA Nutritional Assessment Measuring Hematocrit Number. Hematocrit Hardware Stowage Virus Definition File Update on Auxiliary Computer System (ВКС) Laptops Personal CO2 Monitor iPad Application Restart Fine Motor Skills Experiment Test – Subject Fluids Integrated Rack Hardware Gather XF305 Camcorder Setup Electrostatic Levitation Furnace(ELF) Cartridge exchange [Aborted] Human Research Facility Ultrasound 2 set up and power on COSMOCARD. Closeout Ops MARES Ankle Shaving Preparation MARES Ultrasound Session Assistance Recharging Soyuz 733 Samsung PC Battery (if charge level drops below 80%) MARES Ultrasound session Recharging Soyuz 732 Samsung PC Battery (if charge level drops below 80%) Inspection of FGB space behind panels for contamination Ultrasound 2 Guided Data Export MARES subject electrodes equipment and start of Crew Guided Procedure MARES subject electrodes equipment assistance Photography of SM Windows No.01, No.12 Photo/TV Camcorder Setup Verification Fluids Integrated Rack Session Review Fluids Integrated Rack Rack Doors Open Replacement of СО2 Filter Unit (БФ) ИК0501 Fluids Integrated Rack Hardware Replacement MRM2 comm config to support the P/L Ops Kulonovskiy Kristall Experiment Run HRF Generic Urine Collection Male – Subject HRF Generic Sample MELFI Insertion Operations MSPR Group Combustion Module (GCM) Component Deactivation Fluids Integrated Rack Rack Doors Close HRF Generic Urine Collection Stow Private Medical Conference (PMC) Kulonovskiy Kristall Experiment […]

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Advice- Anonymous and Free

Could you use some anonymous advice on any issue or problem? I am skilled at giving practical advice on many topics. If it helps, great. If it doesn't, ...

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Google 'Android Things' — An Operating System for the Internet of Things

Google announced a Developers Preview of "Android Things" — an Android-based operating system platform for smart devices and Internet of Things (IoT) products. The Android-based Internet of Things OS is designed to make it easier for developers to build a smart appliance since they will be able to work with Android APIs and Google Services they're already familiar with. As the Developers

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Hackers Suspected of Causing Second Power Outage in Ukraine

The same group of hackers that caused the power outage across several regions in Ukraine last Christmas holidays might have once again shut down power supply in northern Ukraine during the weekend. According to Ukrainian energy provider Ukrenergo, a cyber attack on Kyiv's power grid may have caused the power outages in the country on Saturday, December 17, near midnight. The blackout

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Sharpless 308: Star Bubble

Blown by fast winds from a hot, massive star, this cosmic bubble is huge. Cataloged as Sharpless 2-308 it lies some 5,200 light-years away toward the constellation of the Big Dog (Canis Major) and covers slightly more of the sky than a full moon. That corresponds to a diameter of 60 light-years at its estimated distance. The massive star that created the bubble, a Wolf-Rayet star, is the bright one near the center of the nebula. Wolf-Rayet stars have over 20 times the mass of the Sun and are thought to be in a brief, pre-supernova phase of massive star evolution. Fast winds from this Wolf-Rayet star create the bubble-shaped nebula as they sweep up slower moving material from an earlier phase of evolution. The windblown nebula has an age of about 70,000 years. Relatively faint emission captured in the expansive image is dominated by the glow of ionized oxygen atoms mapped to a blue hue. via NASA http://ift.tt/2gXLXYn

I have a new follower on Twitter

Vasayo byZodiac
Ground Floor Opportunity NEW Disruptive Nanotechnology Micro Nutritionals Delivery System.
Cheyenne, WY
https://t.co/z0hvTDe0Xk
Following: 626 - Followers: 518

December 20, 2016 at 11:55PM via Twitter http://twitter.com/VasayoZodiac

Anonymous Donor Gives Church $100k Winning Lottery Ticket

You could call it a Christmas miracle.WBZ-TV's Chantee Lans reports.

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I have a new follower on Twitter

Tutan Ramon
Film izlemek, müzik dinlemek, bir de seninle sohbet etmek


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Gerçekliğin Efendisi
Master of Reality


Following: 22 - Followers: 10

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Ravens: G Marshal Yanda (7th selection), K Justin Tucker (3rd selection) among four players named to 2017 Pro Bowl (ESPN)

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Computational Complexity of Testing Proportional Justified Representation. (arXiv:1612.06476v1 [cs.GT])

We consider a committee voting setting in which each voter approves of a subset of candidates and based on the approvals, a target number of candidates are selected. Aziz et al. (2015) proposed two representation axioms called justified representation and extended justified representation. Whereas the former can be tested as well as achieved in polynomial time, the latter property is coNP-complete to test and no polynomial-time algorithm is known to achieve it. Interestingly, S{\'a}nchez-Fern{\'a}ndez et~al. (2016) proposed an intermediate property called proportional justified representation that admits a polynomial-time algorithm to achieve. The complexity of testing proportional justified representation has remained an open problem. In this paper, we settle the complexity by proving that testing proportional justified representation is coNP-complete. We complement the complexity result by showing that the problem admits efficient algorithms if any of the following parameters are bounded: (1) number of voters (2) number of candidates (3) maximum number of candidates approved by a voter (4) maximum number of voters approving a given candidate.

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Parallelized Tensor Train Learning For Polynomial Pattern Classification. (arXiv:1612.06505v1 [cs.LG])

In pattern classification, polynomial classifiers are well-studied methods as they are capable of generating complex decision surfaces. Unfortunately, the use of multivariate polynomials is limited to support vector machine kernels, as polynomials quickly become impractical for high-dimensional problems. In this paper, we effectively overcome the curse of dimensionality by employing the tensor train format to represent a polynomial classifier. Based on the structure of tensor trains, two learning algorithms are proposed which involve solving different optimization problems of low computational complexity. Furthermore, we show how both regularization to prevent overfitting and parallelization, which enables the use of large training sets, are incorporated into these methods. Both the efficiency and efficacy of our tensor-based polynomial classifier are then demonstrated on the two popular datasets USPS and MNIST.

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Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs. (arXiv:1612.06528v1 [cs.AI])

We investigate solving discrete optimisation problems using the estimation of distribution (EDA) approach via a novel combination of deep belief networks(DBN) and inductive logic programming (ILP).While DBNs are used to learn the structure of successively better feasible solutions,ILP enables the incorporation of domain-based background knowledge related to the goodness of solutions.Recent work showed that ILP could be an effective way to use domain knowledge in an EDA scenario.However,in a purely ILP-based EDA,sampling successive populations is either inefficient or not straightforward.In our Neuro-symbolic EDA,an ILP engine is used to construct a model for good solutions using domain-based background knowledge.These rules are introduced as Boolean features in the last hidden layer of DBNs used for EDA-based optimization.This incorporation of logical ILP features requires some changes while training and sampling from DBNs: (a)our DBNs need to be trained with data for units at the input layer as well as some units in an otherwise hidden layer, and (b)we would like the samples generated to be drawn from instances entailed by the logical model.We demonstrate the viability of our approach on instances of two optimisation problems: predicting optimal depth-of-win for the KRK endgame,and jobshop scheduling.Our results are promising: (i)On each iteration of distribution estimation,samples obtained with an ILP-assisted DBN have a substantially greater proportion of good solutions than samples generated using a DBN without ILP features, and (ii)On termination of distribution estimation,samples obtained using an ILP-assisted DBN contain more near-optimal samples than samples from a DBN without ILP features.These results suggest that the use of ILP-constructed theories could be useful for incorporating complex domain-knowledge into deep models for estimation of distribution based procedures.

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A Latent-class Model for Estimating Product-choice Probabilities from Clickstream Data. (arXiv:1612.06589v1 [cs.AI])

This paper analyzes customer product-choice behavior based on the recency and frequency of each customer's page views on e-commerce sites. Recently, we devised an optimization model for estimating product-choice probabilities that satisfy monotonicity, convexity, and concavity constraints with respect to recency and frequency. This shape-restricted model delivered high predictive performance even when there were few training samples. However, typical e-commerce sites deal in many different varieties of products, so the predictive performance of the model can be further improved by integration of such product heterogeneity. For this purpose, we develop a novel latent-class shape-restricted model for estimating product-choice probabilities for each latent class of products. We also give a tailored expectation-maximization algorithm for parameter estimation. Computational results demonstrate that higher predictive performance is achieved with our latent-class model than with the previous shape-restricted model and common latent-class logistic regression.

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Action-Driven Object Detection with Top-Down Visual Attentions. (arXiv:1612.06704v1 [cs.CV])

A dominant paradigm for deep learning based object detection relies on a "bottom-up" approach using "passive" scoring of class agnostic proposals. These approaches are efficient but lack of holistic analysis of scene-level context. In this paper, we present an "action-driven" detection mechanism using our "top-down" visual attention model. We localize an object by taking sequential actions that the attention model provides. The attention model conditioned with an image region provides required actions to get closer toward a target object. An action at each time step is weak itself but an ensemble of the sequential actions makes a bounding-box accurately converge to a target object boundary. This attention model we call AttentionNet is composed of a convolutional neural network. During our whole detection procedure, we only utilize the actions from a single AttentionNet without any modules for object proposals nor post bounding-box regression. We evaluate our top-down detection mechanism over the PASCAL VOC series and ILSVRC CLS-LOC dataset, and achieve state-of-the-art performances compared to the major bottom-up detection methods. In particular, our detection mechanism shows a strong advantage in elaborate localization by outperforming Faster R-CNN with a margin of +7.1% over PASCAL VOC 2007 when we increase the IoU threshold for positive detection to 0.7.

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Data Centroid Based Multi-Level Fuzzy Min-Max Neural Network. (arXiv:1608.05513v2 [cs.AI] UPDATED)

Recently, a multi-level fuzzy min max neural network (MLF) was proposed, which improves the classification accuracy by handling an overlapped region (area of confusion) with the help of a tree structure. In this brief, an extension of MLF is proposed which defines a new boundary region, where the previously proposed methods mark decisions with less confidence and hence misclassification is more frequent. A methodology to classify patterns more accurately is presented. Our work enhances the testing procedure by means of data centroids. We exhibit an illustrative example, clearly highlighting the advantage of our approach. Results on standard datasets are also presented to evidentially prove a consistent improvement in the classification rate.

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Quantum Machine Learning without Measurements. (arXiv:1612.05535v1 [quant-ph] CROSS LISTED)

We propose a quantum machine learning algorithm for efficiently solving a class of problems encoded in quantum controlled unitary operations. The central physical mechanism of the protocol is the iteration of a quantum time-delayed equation that introduces feedback in the dynamics and eliminates the necessity of intermediate measurements. The performance of the quantum algorithm is analyzed by comparing the results obtained in numerical simulations with the outcome of classical machine learning methods for the same problem. The use of time-delayed equations enhances the toolbox of the field of quantum machine learning, which may enable unprecedented applications in quantum technologies.

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[FD] NEW VMSA-2016-0023 VMware ESXi updates address a cross-site scripting issue

-----BEGIN PGP SIGNED MESSAGE-

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[FD] New BlackArch Linux ISOs (2016.12.20) released!

[FD] CVE-2014-1785: MSIE 11 MSHTML CSpliceTreeEngine::RemoveSplice use-after-free

Since November I have been releasing details on all vulnerabilities I found that I have not released before. This is the 36th entry in the series. This information is available in more detail on my blog at http://ift.tt/2hPspaE. There you can find a repro that triggered this issue in addition to the information below, as well as a Proof-of-Concept exploit that attempts to prove exploitability. If you find these releases useful, and would like to help me make time to continue releasing this kind of information, you can make a donation in bitcoin to 183yyxa9s1s1f7JBp­PHPmz­Q346y91Rx5DX. Follow me on http://twitter.com/berendjanwever for daily browser bugs. MSIE 11 MSHTML CSpliceTreeEngine::RemoveSplice use-after-free ============================================================= (MS14-035, CVE-2014-1785) Synopsis

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Anonymous

... Audio Edition, Audio CD. 4 out of 5 stars 341. FREE Shipping on eligible orders. See search results for author "Anonymous" in Books ...

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'MethBot' Ad Fraud Operators Making $5 Million Revenue Every Day

The biggest advertising fraud ever! A group of hackers is making between $3 Million to $5 Million per day from United States brands and media companies in the biggest digital ad fraud ever discovered. Online fraud-prevention firm White Ops uncovered this new Ad fraud campaign, dubbed "Methbot," that automatically generates more than 300 Million fraudulent video ad impressions every day. The

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Ravens (8-6) up 2 spots to No. 10 in the Week 16 NFL Power Rankings; next game Sunday at the Steelers (ESPN)

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Hacker Demonstrates How Easy In-flight Entertainment System Can Be Hacked

Next time when you hear an announcement in the flight, “Ladies and gentlemen, this is your captain speaking…," the chances are that the announcement is coming from a hacker controlling your flight. Dangerous vulnerabilities in an in-flight entertainment system used by the leading airlines, including Emirates, United, American Airlines, Virgin, and Qatar, could let hackers hijack several

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Entityform anonymous requires this module

Just to let you know that the module entityform (http://ift.tt/UWpoZ7) requires this module to allow for anonymous form ...

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ISS Daily Summary Report – 12/19/2016

Lighting Effects Meter Reading: The crew set up and configured the Light Meter hardware and took readings in the Node 1 and Crew Quarters (CQ). The Node 1 light is the legacy General Luminaire Assembly (GLA), while the CQ light has been upgraded to the newly installed Solid State Lighting Assemblies (SSLAs). The Lighting Effects experiment aims to better quantify and qualify how lighting can effect habitability of spacecraft. The light bulbs on the ISS are being replaced with a new system designed for improved crew health and wellness. The investigation studies the impact of the change from fluorescent light bulbs to solid-state light-emitting diodes (LEDs) with adjustable intensity and color and aims to determine if the new lights can improve crew circadian rhythms, sleep, and cognitive performance. Results from this investigation also have major implications for people on Earth who use electric lights.  Sarcolab-3: Over the next four days (setup, two days of operations, tear-down), the crew will perform the second session (Flight Day 30-60 timeframe) of the joint-NASA-ESA-Russia Sarcolab experiment. Today, the crew deployed and configured the Muscle Atrophy Research & Exercise System (MARES) in Columbus. Myotendinous and Neuromuscular Adaptation to Long-term Spaceflight (Sarcolab) investigates the adaptation and deterioration of the soleus, or calf muscle, where it joins the Achilles tendon which links it to the heel and carries loads from the entire body. Muscle fiber samples are taken from crew members before and after flight and are analyzed for changes in structural and chemical properties. MRI and ultrasound tests and electrode stimulation are conducted to assess muscle and tendon changes caused by microgravity exposure. Japanese-Small Satellite Orbital Deployer (J-SSOD) Release: Using the Japanese Experiment Module Remote Manipulator System (JEMRMS), ground controllers grappled the J-SSOD from the Slide Table and maneuvered it to the deployment position. The crew successfully commanded the deploy of the satellite, then ground controllers returned the deployer back to the Multi-Purpose Experiment Platform (MPEP) on the slide table. J-SSOD #5 contains one Cubesat, STARS-C(2U) which will conduct a technical demonstration of a tether extending system using a mother and daughter satellite. J-SSOD #5 will be removed and J-SSOD #6 will be installed on Thursday, December 22. NanoRacks modules 63 and 72 (CubeRider) Status: On Friday, the crew installed the two modules into the NanoRacks Platform-1 facility. Ground teams did not receive telemetry from Module 72, however they did receive data from Module 63 (a radiation-tolerant computer). Ground controllers performed a power cycle of CubeRider, but were unable to recover. The Payload Developer is working on further troubleshooting steps, including possibly reseating the connections. CubeRider is an Australian educational module utilizing a Raspberry Pi, internal camera, sensors that monitors internal environment variables, some radiation, ISS dynamics and movement, and runs computer code written by 9th and 10th graders. Camera Light Pan & Tilt Assembly (CLPA) Operations: Robotics ground controllers are in the process of relocating the failed Boom B CLPA from the Space Station Remote Manipulator System (SSRMS) to the wedge interface on the Mobile Transporter Relay Assembly (MTRA). This activity is advance of the HTV-6 battery EVAs, during which the CLPA will be swapped for a new unit at that location. This will allow the SSRMS to install the new CLPA in the future. SSRMS Troubleshooting: On Saturday, Robotics ground controllers resumed troubleshooting of the anomaly (Aborted SSRMS and Special Purpose Dexterous Manipulator (SPDM) Transitions to Operational Due to Binary Data Transfer (BDT) Load Fail), focusing on testing the current power configuration where SSRMS is based on Mobile Base System (MBS). After releasing Node 2 Power Data Grapple Fixture (PDGF), the SSRMS was tested in a variety of power configurations with Latch End Effector (LEE) B unloaded. Tests consisted of SSRMS power cycle on both strings commanded on Mobile Servicing System (MSS) Local Bus A and B while both SSRMS payload power feed channels were on and all power up sequences completed nominally. ROBOs then maneuvered SSRMS to grapple SPDM. When SPDM was based on SSRMS (based on MBS PDGF1) but still grappled to Lab PDGF, tests were performed where all SPDM units were powered on with multiple power configurations (Prime and Redundant, MSS LB A and B). As no anomalies occurred throughout the troubleshooting, SPDM LEE released Lab PDGF and SSRMS holding SPDM and SPDM Arm2 was configured for translation. Finally, Mobile Transporter (MT) was translated from Worksite #5 (WS5) to WS2, in position for today’s SSRMS CLPA operations and Battery R&R operations later this month.  On Board Training (OBT) ISS Emergency Simulation: All crew members, with support from ground teams, completed a training exercise and completed the following objectives: Practiced ISS emergency response with crew and ground roles based on information provided by simulator displays. Physically translated through ISS to the appropriate response locations to visualize the use of Station equipment and interfaces. Practiced procedure execution and associated decision making based on cues provided by simulator. Practiced communication and coordination with Houston and Moscow Control Centers as required for a given emergency scenario. Upon completion of the training session, the crew and ground teams completed a debrief to discuss results.  H-2 Transfer Vehicle (HTV) Cargo Operations: The crew has completed ~25.5 hours of cargo transfer. There are ~10 hours of transfer remaining to be completed. Today’s Planned Activities All activities were completed unless otherwise noted. Measuring Hematocrit Number. Hematocrit equipment stowage Personal CO2 Monitor iPad Application Restart ВКС Laptops Antivirus software checkout Fine Motor Skills Experiment Test – Subject Fluids Integrated Rack Hardware Gather XF305 Camcorder Setup Electrostatic Levitation Furnace(ELF) Cartridge exchange HRF Generic Urine Collection Male – Subject Human Research Facility Ultrasound 2 set up and power on KOSMOKARD. Closeout MARES Ankle Shaving Preparation HRF Generic Sample MELFI Insertion Operations MARES Ultrasound Session Assistance Recharging Samsung tablet in 49S MARES Ultrasound session Multi-purpose Small Payload Rack (MSPR) /Group Combustion Module (GCM) Component Deactivation Recharging Samsung tablet in 48S FGB-ПАНЕЛИ-VIEW Ultrasound 2 Guided Data Export MARES subject electrodes equipment and start of Crew Guided Procedure MARES subject electrodes equipment assistance Inspection and photo […]

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RansomFree Tool Detects Never-Seen-Before Ransomware Before It Encrypts Your Data

Ransomware has risen dramatically since last few years, so rapidly that it might have already hit you or someone you know. With hundred of thousands of ransomware variants emerging every day, it is quite difficult for traditional signature-based antivirus tools to keep their signature database up-to-date. So, if signature-based techniques are not enough to detect ransomware infection, then

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[FD] Hotlinking Vulnerability in Glype (All Versions)

A vulnerability exists in the hotlinking feature of Glype on all versions that allow the bypass and makes possible to link directly to proxified files or develop aplications that integrate direct linking into the url. This was found while trying to build a DDOS tool that take advantage of installed copies of Glype worldwide. Since it wasn't possible to develop a fast tool using common libraries such as jQuery this note was been released. Tested on version 1.4.4 but affects all version based on the Proof Of Concept. For people that doesn't know what is Glype, Glype is the stable and fastest php script to act as a web proxy. If you have blocked access to a site and you want to access it, using a site with Glype installed can bypass that restriction. Glype by default has hotlinking active to prevent linking to banned pages or to save bandwidth on the servers. At this point since Glype owner is probably broke, Glype servers administrator are striving for advertising revenue, Glype users aren't tech savy or they were using VPNs i'm not disclosing anymore details. $$$ ============================================================================= This release note has only the purpose of reaching a wider audience. So do not spam my inbox or request the POC or request for comments or ask me for anything related to this vulnerability. =============================================================================

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Anonymous Donor Gives Thousands For Animal Rescue's New Shelter

A Westmoreland County animal rescue organization has itself been rescued, and it's all thanks to an anonymous donor; KDKA's Ross Guidotti reports.

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Greenwald: Anonymous leaks not evidence in Russian hacking

Journalist calls The Washington Post's reported about the CIA's beliefs about alleged Russian hacking in the election 'classic American journalism of ...

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A User Simulator for Task-Completion Dialogues. (arXiv:1612.05688v1 [cs.LG])

Despite widespread interests in reinforcement-learning for task-oriented dialogue systems, several obstacles can frustrate research and development progress. First, reinforcement learners typically require interaction with the environment, so conventional dialogue corpora cannot be used directly. Second, each task presents specific challenges, requiring separate corpus of task-specific annotated data. Third, collecting and annotating human-machine or human-human conversations for task-oriented dialogues requires extensive domain knowledge. Because building an appropriate dataset can be both financially costly and time-consuming, one popular approach is to build a user simulator based upon a corpus of example dialogues. Then, one can train reinforcement learning agents in an online fashion as they interact with the simulator. Dialogue agents trained on these simulators can serve as an effective starting point. Once agents master the simulator, they may be deployed in a real environment to interact with humans, and continue to be trained online. To ease empirical algorithmic comparisons in dialogues, this paper introduces a new, publicly available simulation framework, where our simulator, designed for the movie-booking domain, leverages both rules and collected data. The simulator supports two tasks: movie ticket booking and movie seeking. Finally, we demonstrate several agents and detail the procedure to add and test your own agent in the proposed framework.

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Optimal Target Assignment and Path Finding for Teams of Agents. (arXiv:1612.05693v1 [cs.AI])

We study the TAPF (combined target-assignment and path-finding) problem for teams of agents in known terrain, which generalizes both the anonymous and non-anonymous multi-agent path-finding problems. Each of the teams is given the same number of targets as there are agents in the team. Each agent has to move to exactly one target given to its team such that all targets are visited. The TAPF problem is to first assign agents to targets and then plan collision-free paths for the agents to their targets in a way such that the makespan is minimized. We present the CBM (Conflict-Based Min-Cost-Flow) algorithm, a hierarchical algorithm that solves TAPF instances optimally by combining ideas from anonymous and non-anonymous multi-agent path-finding algorithms. On the low level, CBM uses a min-cost max-flow algorithm on a time-expanded network to assign all agents in a single team to targets and plan their paths. On the high level, CBM uses conflict-based search to resolve collisions among agents in different teams. Theoretically, we prove that CBM is correct, complete and optimal. Experimentally, we show the scalability of CBM to TAPF instances with dozens of teams and hundreds of agents and adapt it to a simulated warehouse system.

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Quantum Reinforcement Learning. (arXiv:1612.05695v1 [quant-ph])

We investigate whether quantum annealers with select chip layouts can outperform classical computers in reinforcement learning tasks. We associate a transverse field Ising spin Hamiltonian with a layout of qubits similar to that of a deep Boltzmann machine (DBM) and use simulated quantum annealing (SQA) to numerically simulate quantum sampling from this system. We design a reinforcement learning algorithm in which the set of visible nodes representing the states and actions of an optimal policy are the first and last layers of the deep network. In absence of a transverse field, our simulations show that DBMs train more effectively than restricted Boltzmann machines (RBM) with the same number of weights. Since sampling from Boltzmann distributions of a DBM is not classically feasible, this is evidence of supremacy of a non-Turing sampling oracle. We then develop a framework for training the network as a quantum Boltzmann machine (QBM) in the presence of a significant transverse field for reinforcement learning. The latter method further improves the reinforcement learning method using DBMs.

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Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation. (arXiv:1612.05729v1 [cs.IR])

The increasing availability of implicit feedback datasets has raised the interest in developing effective collaborative filtering techniques able to deal asymmetrically with unambiguous positive feedback and ambiguous negative feedback. In this paper, we propose a principled kernel-based collaborative filtering method for top-N item recommendation with implicit feedback. We present an efficient implementation using the linear kernel, and we show how to generalize it to kernels of the dot product family preserving the efficiency. We also investigate on the elements which influence the sparsity of a standard cosine kernel. This analysis shows that the sparsity of the kernel strongly depends on the properties of the dataset, in particular on the long tail distribution. We compare our method with state-of-the-art algorithms achieving good results both in terms of efficiency and effectiveness.

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Web-based Semantic Similarity for Emotion Recognition in Web Objects. (arXiv:1612.05734v1 [cs.AI])

In this project we propose a new approach for emotion recognition using web-based similarity (e.g. confidence, PMI and PMING). We aim to extract basic emotions from short sentences with emotional content (e.g. news titles, tweets, captions), performing a web-based quantitative evaluation of semantic proximity between each word of the analyzed sentence and each emotion of a psychological model (e.g. Plutchik, Ekman, Lovheim). The phases of the extraction include: text preprocessing (tokenization, stop words, filtering), search engine automated query, HTML parsing of results (i.e. scraping), estimation of semantic proximity, ranking of emotions according to proximity measures. The main idea is that, since it is possible to generalize semantic similarity under the assumption that similar concepts co-occur in documents indexed in search engines, therefore also emotions can be generalized in the same way, through tags or terms that express them in a particular language, ranking emotions. Training results are compared to human evaluation, then additional comparative tests on results are performed, both for the global ranking correlation (e.g. Kendall, Spearman, Pearson) both for the evaluation of the emotion linked to each single word. Different from sentiment analysis, our approach works at a deeper level of abstraction, aiming at recognizing specific emotions and not only the positive/negative sentiment, in order to predict emotions as semantic data.

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A Comment on Argumentation. (arXiv:1612.05756v1 [math.LO])

We use the theory of defaults and their meaning of [GS16] to develop (the outline of a) new theory of argumentation.

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