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Saturday, September 19, 2015
Releases for Anonymous unpublished nope
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Orioles Highlight: Adam Jones drives in both Baltimore runs, Wei-Yin Chen 7 strong IP in 2-1 win over Rays (ESPN)
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[FD] New release of testssl.sh
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Estoril wins 1-0 at Tondela to move into 4th in Portugal
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Chelsea beats Arsenal, Man City loses to West Ham
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Empoli beats 10-man Udinese 2-1 for 1st win of season
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With Its First Android app, Apple tried to Kill Android Community, But Failed Badly!
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Cavani scores equalizer as PSG drops points at Reims
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Costa's actions anger Arsenal as Chelsea wins London derby
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Leicester stages another comeback to draw at Stoke 2-2
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Watford beats Newcastle 2-1 in Premier League
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Bournemouth beats Sunderland 2-0 in Premier League
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AVG Antivirus Plans to Collect & Sell Your Personal Data to Advertisers
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Benzema goal gives Madrid 1-0 win over Granada in Spain
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Bayern beats Darmstadt 3-0 away to go top in Bundesliga
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I have a new follower on Twitter
Hektor
I tweet about digital, #bitcoin #tech, #andoid #iOS and other cool stuff, follow me for more. Also, proud father of 2 !
Philadelphia
Following: 4105 - Followers: 4927
September 19, 2015 at 09:55AM via Twitter http://twitter.com/HektorTuring
What does "anonymous function" mean when in the context of the console?
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Kashima wins to keep pressure on J-League leaders Hiroshima
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When a 'Hacker News' Reader Tricked Me into visiting this Amazing Site (Don't Click at Work)
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Is This Security-Focused Linux Kernel Really UnHackable?
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Google to Disable Weak SSLv3 and RC4 Protocols to Boost Internet Security
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Performance Today
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Ocean City, MD's surf is at least 6.63ft high
Ocean City, MD Summary
At 4:00 AM, surf min of 6.63ft. At 10:00 AM, surf min of 6.22ft. At 4:00 PM, surf min of 5.62ft. At 10:00 PM, surf min of 5.0ft.
Surf maximum: 7.62ft (2.32m)
Surf minimum: 6.63ft (2.02m)
Tide height: 3.36ft (1.03m)
Wind direction: SSW
Wind speed: 4.57 KTS
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Tracking Kilo from Hurricane to Typhoon
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Hurricane Kilo's Precipitation Trail
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A Plutonian Landscape
Friday, September 18, 2015
Anonymous Egg Donors Wanted. Earn up to $7500
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Getafe beats Malaga 1-0 in Spanish league
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Rennes held to 1-1 draw by Lille in French league
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Malli hat trick puts Mainz 3rd in Bundesliga
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UEFA punishes Hungary for fan racism in Euro 2016 qualifier
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I have a new follower on Twitter
Boxless
A better solution is here. It is time to raise the bar and bring business a solution for all of the interconnected knowledge throughout an enterprise.
San Francisco
http://t.co/TLghbtPXMc
Following: 3504 - Followers: 3185
September 18, 2015 at 03:51PM via Twitter http://twitter.com/boxless_com
D-Link Accidentally Publishes Its Private Code-Signing Keys on the Internet
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Thousands of Hacked WordPress Sites Abused to Infect Millions of Visitors
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Q&A: What's ahead for FIFA after week of turmoil
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UEFA donates $2.3m to help kids affected by migrant crisis
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Microsoft has Built its own Linux Operating System
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Clubs opt out of German tabloid's 'refugees welcome' action
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Croatia loses 1 point in qualifying for swastika incident
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Ibrahimovic hires Malmo square for fans to enjoy his return
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Blatter rallies FIFA staff after cutting ties with Valcke
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Otamendi to get Man City debut as Aguero returns
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Election favorite Platini silent as FIFA crisis escalates
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No drones please, Albania tells fans
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Anonymous access with Shield
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Ben Arfa loses CAS appeal against FIFA
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Beware Coffee Lovers! StarBucks Exposed you to 3 Critical Vulnerabilities
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Former Bayern coach Dettmar Cramer dies at 90
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Researchers to Develop Long-Lasting Solid-State Batteries
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ISS Daily Summary Report – 09/17/15
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ISS Daily Summary Report – 09/16/15
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ISS Daily Summary Report – 09/15/15
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Brazil appeals Neymar ban from 2 World Cup qualifiers
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Putin marks 1,000 days to World Cup without Valcke
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New Bug in Bugzilla Software Could Expose Zero-Day Vulnerabilities
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Ocean City, MD's surf is at least 5.13ft high
Ocean City, MD Summary
At 4:00 AM, surf min of 5.13ft. At 10:00 AM, surf min of 4.62ft. At 4:00 PM, surf min of 3.48ft. At 10:00 PM, surf min of 3.03ft.
Surf maximum: 6.13ft (1.87m)
Surf minimum: 5.13ft (1.56m)
Tide height: 3.49ft (1.06m)
Wind direction: NE
Wind speed: 15.86 KTS
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Pickering's Triangle in the Veil
Thursday, September 17, 2015
Orioles Highlight: Adam Jones' 2-run single caps 4-run eighth inning in 4-3 victory over Rays (ESPN)
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Lloyd's hat trick leads US over Haiti 5-0
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Angry Anonymous Dude
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Performance Analysis and Prediction in Educational Data Mining: A Research Travelogue. (arXiv:1509.05176v1 [cs.CY])
In this era of computerization, education has also revamped itself and is not limited to old lecture method. The regular quest is on to find out new ways to make it more effective and efficient for students. Nowadays, lots of data is collected in educational databases, but it remains unutilized. In order to get required benefits from such a big data, powerful tools are required. Data mining is an emerging powerful tool for analysis and prediction. It is successfully applied in the area of fraud detection, advertising, marketing, loan assessment and prediction. But, it is in nascent stage in the field of education. Considerable amount of work is done in this direction, but still there are many untouched areas. Moreover, there is no unified approach among these researches. This paper presents a comprehensive survey, a travelogue (2002-2014) towards educational data mining and its scope in future.
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Efficient Task Collaboration with Execution Uncertainty. (arXiv:1509.05181v1 [cs.AI])
We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to them (known as execution uncertainty). The goal is to choose an allocation that maximises social welfare while taking their execution uncertainty into account. We show that this can be achieved by using the post-execution verification (PEV)-based mechanism if and only if agents' valuations satisfy a multilinearity condition. We then consider a more complex setting where an agent's execution uncertainty is not completely predictable by the agent alone but aggregated from all agents' private opinions (known as trust). We show that PEV-based mechanism with trust is still truthfully implementable if and only if the trust aggregation is multilinear.
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Extraction of evidence tables from abstracts of randomized clinical trials using a maximum entropy classifier and global constraints. (arXiv:1509.05209v1 [cs.CL])
Systematic use of the published results of randomized clinical trials is increasingly important in evidence-based medicine. In order to collate and analyze the results from potentially numerous trials, evidence tables are used to represent trials concerning a set of interventions of interest. An evidence table has columns for the patient group, for each of the interventions being compared, for the criterion for the comparison (e.g. proportion who survived after 5 years from treatment), and for each of the results. Currently, it is a labour-intensive activity to read each published paper and extract the information for each field in an evidence table. There have been some NLP studies investigating how some of the features from papers can be extracted, or at least the relevant sentences identified. However, there is a lack of an NLP system for the systematic extraction of each item of information required for an evidence table. We address this need by a combination of a maximum entropy classifier, and integer linear programming. We use the later to handle constraints on what is an acceptable classification of the features to be extracted. With experimental results, we demonstrate substantial advantages in using global constraints (such as the features describing the patient group, and the interventions, must occur before the features describing the results of the comparison).
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A Simulated Annealing Approach to Bayesian Inference. (arXiv:1509.05315v1 [stat.CO])
A generic algorithm for the extraction of probabilistic (Bayesian) information about model parameters from data is presented. The algorithm propagates an ensemble of particles in the product space of model parameters and outputs. Each particle update consists of a random jump in parameter space followed by a simulation of a model output and a Metropolis acceptance/rejection step based on a comparison of the simulated output to the data. The distance of a particle to the data is interpreted as an energy and the algorithm is reducing the associated temperature of the ensemble such that entropy production is minimized. If this simulated annealing is not too fast compared to the mixing speed in parameter space, the parameter marginal of the ensemble approaches the Bayesian posterior distribution. Annealing is adaptive and depends on certain extensive thermodynamic quantities that can easily be measured throughout run-time. In the general case, we propose annealing with a constant entropy production rate, which is optimal as long as annealing is not too fast. For the practically relevant special case of no prior knowledge, we derive an optimal fast annealing schedule with a non-constant entropy production rate. The algorithm does not require the calculation of the density of the model likelihood, which makes it interesting for Bayesian parameter inference with stochastic models, whose likelihood functions are typically very high dimensional integrals.
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I have a new follower on Twitter
WNST
We Never Stop Talking Baltimore Sports...Ravens, Orioles, Terps, Caps news, info, blogs & text FIRST at http://t.co/L3IJuTol!
Baltimore, MD USA
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Following: 1994 - Followers: 12708
September 17, 2015 at 08:43PM via Twitter http://twitter.com/WNST
Orioles: Rafael Palmeiro, 50, signs with Sugar Land Skeeters, will play alongside his son for rest of season (ESPN)
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Dortmund gets perfect 10th win, beats Krasnodar in Europa
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Anonymous unpublished nope
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13 women dropped from FIFA 16 because of NCAA eligibility
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FIFA suspends secretary general Jerome Valcke from duty
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Soccer officials still eye US for centennial Copa America
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FIFA suspends secretary general Jerome Valcke from duty after World Cup ticket allegations
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Brazil names World Cup qualifying team without banned Neymar
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UEFA wants new president by Euros if Platini gets FIFA job
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Problem with website - 16 September
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Italian league launches streaming service to show games
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Romania to play 1 qualifier in empty stadium for fan racism
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Ocean City, MD's surf is at least 5.32ft high
Ocean City, MD Summary
At 4:00 AM, surf min of 4.36ft. At 10:00 AM, surf min of 5.32ft. At 4:00 PM, surf min of 3.16ft. At 10:00 PM, surf min of 3.81ft.
Surf maximum: 6.32ft (1.93m)
Surf minimum: 5.32ft (1.62m)
Tide height: 0.63ft (0.19m)
Wind direction: NNE
Wind speed: 13.04 KTS
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FIFA slaps transfer ban on Belgian club for 3rd-party deals
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Hall of Fame UConn soccer coach Joe Morrone dies at 79
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[FD] KL-001-2015-005 : VBox Satellite Express Arbitrary Write Privilege Escalation
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Switzerland grants US request to extradite former FIFA VP
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Roma, Juventus turn back to Serie A after European success
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For Better Privacy, Change these iOS 9 Settings Immediately
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Spanish league returns with all eyes on Cristiano Ronaldo
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ISS Daily Summary Report – 09/16/15
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World's 9 Biggest Banks to adopt Bitcoin's Blockchain Technology
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Mourinho faces big decision for Chelsea against Arsenal
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Barcelona's Rafinha to miss most of season with knee injury
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Bayern chasing record-setting Dortmund in Bundesliga
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Rennes grabbing the spotlight in French league
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I have a new follower on Twitter
Sean McClure
Connecting #DataScience approaches to real-world challenges. Sean McClure, PhD. Senior Data Scientist, Public Speaker and Writer.
San Francisco, California
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Following: 671 - Followers: 1510
September 17, 2015 at 06:09AM via Twitter http://twitter.com/WorldOfDataSci
SYNful Knock: Backdoor Malware Found in Cisco Routers
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How to Detect IE Zero-day Exploit Used to Deploy Korplug Malware
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Lots Of Comets - Long trail version
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Sixteen Comets Touring the Inner Solar System
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Lots Of Comets - Short trail version
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LRO and the September 27-28, 2015 Lunar Eclipse: Telescopic View
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Bright Spots Resolved in Occator Crater on Ceres
Wednesday, September 16, 2015
I have a new follower on Twitter
Radek Paklikowski
There is nothing wrong in the possession of great dreams.
http://t.co/CgfuZaCwdb
Following: 346 - Followers: 53
September 16, 2015 at 10:46PM via Twitter http://twitter.com/paklikowski
Linear Embedding of Large-Scale Brain Networks for Twin fMRI. (arXiv:1509.04771v1 [cs.AI])
In many human brain network studies, we do not have sufficient number (n) of images relative to the number (p) of voxels due to the prohibitively expensive cost of scanning enough subjects. Thus, brain network models usually suffer the small-n large-p problem. Such a problem is often remedied by sparse network models, which are usually solved numerically by optimizing L1-penalties. Unfortunately, due to the computational bottleneck associated with optimizing L1-penalties, it is not practical to apply such methods to learn large-scale brain networks. In this paper, we introduce a new sparse network model based on cross-correlations that bypass the computational bottleneck. Our model can build the sparse brain networks at voxel level with p > 25000. Instead of using a single sparse parameter that may not be optimal in other studies and datasets, we propose to analyze the collection of networks at every possible sparse parameter in a coherent mathematical framework using graph filtrations. The method is subsequently applied in determining the extend of genetic effects on functional brain networks at voxel-level for the first time using twin fMRI.
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Causal Model Analysis using Collider v-structure with Negative Percentage Mapping. (arXiv:1509.04904v1 [cs.AI])
A major problem of causal inference is the arrangement of dependent nodes in a directed acyclic graph (DAG) with path coefficients and observed confounders. Path coefficients do not provide the units to measure the strength of information flowing from one node to the other. Here we proposed the method of causal structure learning using collider v-structures (CVS) with Negative Percentage Mapping (NPM) to get selective thresholds of information strength, to direct the edges and subjective confounders in a DAG. The NPM is used to scale the strength of information passed through nodes in units of percentage from interval from 0 to 1. The causal structures are constructed by bottom up approach using path coefficients, causal directions and confounders, derived implementing collider v-structure and NPM. The method is self-sufficient to observe all the latent confounders present in the causal model and capable of detecting every responsible causal direction. The results are tested for simulated datasets of non-Gaussian distributions and compared with DirectLiNGAM and ICA-LiNGAM to check efficiency of the proposed method.
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Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture. (arXiv:1509.05016v1 [cs.CV])
Anticipating the future actions of a human is a widely studied problem in robotics that requires spatio-temporal reasoning. In this work we propose a deep learning approach for anticipation in sensory-rich robotics applications. We introduce a sensory-fusion architecture which jointly learns to anticipate and fuse information from multiple sensory streams. Our architecture consists of Recurrent Neural Networks (RNNs) that use Long Short-Term Memory (LSTM) units to capture long temporal dependencies. We train our architecture in a sequence-to-sequence prediction manner, and it explicitly learns to predict the future given only a partial temporal context. We further introduce a novel loss layer for anticipation which prevents over-fitting and encourages early anticipation. We use our architecture to anticipate driving maneuvers several seconds before they happen on a natural driving data set of 1180 miles. The context for maneuver anticipation comes from multiple sensors installed on the vehicle. Our approach shows significant improvement over the state-of-the-art in maneuver anticipation by increasing the precision from 77.4% to 90.5% and recall from 71.2% to 87.4%.
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Improving image watermarking based on Tabu search by Chaos. (arXiv:1501.01576v3 [cs.MM] UPDATED)
With the fast development of communication and multimedia technology, the rights of the owners of multimedia products is vulnerable to the unauthorized copies and watermarking is one of the best known methods for proving the ownership of a product. In this paper we prosper the previous watermarking method which was based on Tabu search by Chaos. The modification applied in the permutation step of watermarking and the initial population generation of the Tabu search. We analyze our method on some well known images and experimental results shows the improvement in the quality and speed of the proposed watermarking method.
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Release Early, Release Often: Predicting Change in Versioned Knowledge Organization Systems on the Web. (arXiv:1505.03101v2 [cs.AI] UPDATED)
The Semantic Web is built on top of Knowledge Organization Systems (KOS) (vocabularies, ontologies, concept schemes) that provide a structured, interoperable and distributed access to Linked Data on the Web. The maintenance of these KOS over time has produced a number of KOS version chains: subsequent unique version identifiers to unique states of a KOS. However, the release of new KOS versions pose challenges to both KOS publishers and users. For publishers, updating a KOS is a knowledge intensive task that requires a lot of manual effort, often implying deep deliberation on the set of changes to introduce. For users that link their datasets to these KOS, a new version compromises the validity of their links, often creating ramifications. In this paper we describe a method to automatically detect which parts of a Web KOS are likely to change in a next version, using supervised learning on past versions in the KOS version chain. We use a set of ontology change features to model and predict change in arbitrary Web KOS. We apply our method on 139 varied datasets systematically retrieved from the Semantic Web, obtaining robust results at correctly predicting change. To illustrate the accuracy, genericity and domain independence of the method, we study the relationship between its effectiveness and several characterizations of the evaluated datasets, finding that predictors like the number of versions in a chain and their release frequency have a fundamental impact in predictability of change in Web KOS. Consequently, we argue for adopting a release early, release often philosophy in Web KOS development cycles.
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Learning Regular Languages over Large Ordered Alphabets. (arXiv:1506.00482v2 [cs.LO] UPDATED)
This work is concerned with regular languages defined over large alphabets, either infinite or just too large to be expressed enumeratively. We define a generic model where transitions are labeled by elements of a finite partition of the alphabet. We then extend Angluin's L* algorithm for learning regular languages from examples for such automata. We have implemented this algorithm and we demonstrate its behavior where the alphabet is a subset of the natural or real numbers. We sketch the extension of the algorithm to a class of languages over partially ordered alphabets.
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NH Public Library Reconsiders Support For Anonymous Internet Network Tor
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Re: [FD] Use After Free Vulnerabilities in unserialize()
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[FD] APPLE-SA-2015-09-16-4 OS X Server 5.0.3
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[FD] APPLE-SA-2015-09-16-3 iTunes 12.3
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[FD] APPLE-SA-2015-09-16-2 Xcode 7.0
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Dinamo Zagreb beats 10-man Arsenal 2-1 in Champions League
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2 men down, rookie AA Ghent still gets 1-1 draw against Lyon
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Chelsea hammers Maccabi Tel Aviv 4-0 in the Champions League
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Hulk hammers 2 goals, Zenit beats Valencia 3-2 in CL
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Leverkusen beats BATE Borisov 4-1 in Champions League
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Ravens Video: Stephen A. Smith on T. Suggs' injury - \"You don't just lose Suggs and have things remain the same\" (ESPN)
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2nd edition + Hardcopies of Practical Python and OpenCV now online!
The 2nd edition of Practical Python and OpenCV + Case Studies is officially online!
This 2nd edition is a MAJOR UPDATE to the book and includes:
Hardcopy editions.
I’ve wanted to offer Practical Python and OpenCV in print ever since I wrote the book a year ago, but I struggled to find to publisher — that’s all changed now, the hardcopy editions are ready to go and available for purchase right now!
Full compatibility with OpenCV 3 and Python 3.
Over the past few months, I have been hard at work updating all source code and explanations in Practical Python and OpenCV + Case Studies to ensure full compatibility with both the newly released OpenCV 3.0 library and the Python 3 programming language. Now you’ll be able to learn the differences between OpenCV 2.4 and OpenCV 3 — and use the Python 3 as well!
Raspberry Pi Support.
Own a Raspberry Pi and want to use it to detect faces in video streams? Track objects in video? Or recognize handwriting? No problem! The new source code downloads for all chapters in Practical Python and OpenCV + Case Studies will work on the Raspberry Pi out of the box, no modifications required.
Video tutorials.
Come code alongside me — I’ve recorded 16 video tutorials covering over 4+ hours of content from Practical Python and OpenCV. These videos are a fantastic asset to help you learn OpenCV and computer vision.
An updated virtual machine.
One of my favorite features of the 2nd edition of the book is the brand new, freshly rebuilt Ubuntu VirtualBox virtual machine. This VM has been re-engineered from the ground up and includes installations of both Python 2.7 and Python 3 with OpenCV 3!
Grab your copy.
Ready to pickup your own copy 2nd edition copy of Practical Python and OpenCV + Case Studies?
Just click here to learn more and grab your copy.
The post 2nd edition + Hardcopies of Practical Python and OpenCV now online! appeared first on PyImageSearch.
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Syrian tripped by Hungarian journalist heading to Spain
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After investigating Platini smears, FIFA says staffer quits
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UEFA explores creating third European club competition
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AirDrop Bug in Apple iOS and OSX allows Hackers to Install Malware Silently
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This Computer Chip Self-Destructs in 10 Seconds (On Command) to keep Secrets Safe
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ISS Daily Summary Report – 09/15/15
from ISS On-Orbit Status Report http://ift.tt/1OXIyEj
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