Query: Real-Time Online Action Detection Forests Using Spatio-Temporal Contexts

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View invariant human action recognition using histograms of 3D joints <=SEP=> In this paper, we present a novel approach for human action recognition with histograms of 3D joint locations (HOJ3D) as a compact representation of postures. We extract the 3D skeletal joint locations from Kinect depth maps using Shotton et al.'s method [6]. The HOJ3D computed from the action depth sequences are reprojected using LDA and then clustered into k posture visual words, which represent the prototypical poses of actions. The temporal evolutions of those visual words are modeled by discrete hidden Markov models (HMMs). In addition, due to the design of our spherical coordinate system and the robust 3D skeleton estimation from Kinect, our method demonstrates significant view invariance on our 3D action dataset. Our dataset is composed of 200 3D sequences of 10 indoor activities performed by 10 individuals in varied views. Our method is real-time and achieves superior results on the challenging 3D action dataset. We also tested our algorithm on the MSR Action 3D dataset and our algorithm outperforms Li et al. [25] on most of the cases.

Classification and Regression Trees <=SEP=> 

Sparse solutions to linear inverse problems with multiple measurement vectors <=SEP=> We address the problem of finding sparse solutions to an underdetermined system of equations when there are multiple measurement vectors having the same, but unknown, sparsity structure. The single measurement sparse solution problem has been extensively studied in the past. Although known to be NP-hard, many single-measurement suboptimal algorithms have been formulated that have found utility in many different applications. Here, we consider in depth the extension of two classes of algorithms-Matching Pursuit (MP) and FOCal Underdetermined System Solver (FOCUSS)-to the multiple measurement case so that they may be used in applications such as neuromagnetic imaging, where multiple measurement vectors are available, and solutions with a common sparsity structure must be computed. Cost functions appropriate to the multiple measurement problem are developed, and algorithms are derived based on their minimization. A simulation study is conducted on a test-case dictionary to show how the utilization of more than one measurement vector improves the performance of the MP and FOCUSS classes of algorithm, and their performances are compared.

Action recognition from a distributed representation of pose and appearance <=SEP=> We present a distributed representation of pose and appearance of people called the “poselet activation vector”. First we show that this representation can be used to estimate the pose of people defined by the 3D orientations of the head and torso in the challenging PASCAL VOC 2010 person detection dataset. Our method is robust to clutter, aspect and viewpoint variation and works even when body parts like faces and limbs are occluded or hard to localize. We combine this representation with other sources of information like interaction with objects and other people in the image and use it for action recognition. We report competitive results on the PASCAL VOC 2010 static image action classification challenge.

Random Forests <=SEP=> Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, ***, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.

Low-voltage low-power CMOS full adder - Circuits, Devices and Systems, IEE Proceedings- <=SEP=> Low-power design of VLSI circuits has been identified as a critical technological need in recent years due to the high demand for portable consumer electronics products. In this regard many innovative designs for basic logic functions using pass transistors and transmission gates have appeared in the literature recently. These designs relied on the intuition and cleverness of the designers, without involving formal design procedures. Hence, a formal design procedure for realising a minimal transistor CMOS pass network XOR-XNOR cell, that is fully compensated for threshold voltage drop in MOS transistors, is presented. This new cell can reliably operate within certain bounds when the power supply voltage is scaled down, as long as due consideration is given to the sizing of the MOS transistors during the initial design step. A low transistor count full adder cell using the new XOR-XNOR cell is also presented.

Associations between online friendship and Internet addiction among adolescents and emerging adults. <=SEP=> The past decades have witnessed a dramatic increase in the number of youths using the Internet, especially for communicating with peers. Online activity can widen and strengthen the social networks of adolescents and emerging adults (Subrahmanyam & Smahel, 2011), but it also increases the risk of Internet addiction. Using a framework derived from Griffiths (2000a), this study examined associations between online friendship and Internet addiction in a representative sample (n = 394) of Czech youths ages 12-26 years (M = 18.58). Three different approaches to friendship were identified: exclusively offline, face-to-face oriented, Internet oriented, on the basis of the relative percentages of online and offline associates in participants' friendship networks. The rate of Internet addiction did not differ by age or gender but was associated with communication styles, hours spent online, and friendship approaches. The study revealed that effects between Internet addiction and approaches to friendship may be reciprocal: Being oriented toward having more online friends, preferring online communication, and spending more time online were related to increased risk of Internet addiction; on the other hand, there is an alternative causal explanation that Internet addiction and preference for online communication conditions young people's tendency to seek friendship from people met online.

Constructing a Hermitian Matrix from Its Diagonal Entries and Eigenvalues <=SEP=> Given two vectors a R the Schur Horn theorem states that a majorizes if and only if there exists a Hermitian matrix H with eigenvalues and diagonal entries a While the theory is regarded as classical by now the known proof is not constructive To construct a Hermitian matrix from its diagonal entries and eigenvalues therefore becomes an interesting and challenging inverse eigenvalue problem Two algorithms for determining the matrix numerically are proposed in this paper The lift and pro jection method is an iterative method which involves an interesting application of the Wielandt Ho man theorem The projected gradient method is a continuous method which besides its easy implementation o ers a new proof of existence because of its global convergence property

Pisotriquetral joint disorders: an under-recognized cause of ulnar side wrist pain <=SEP=> Pisotriquetral joint disorders are often under-recognized in routine clinical practice. They nevertheless represent a significant cause of ulnar side wrist pain. The aim of this article is to present the main disorders of this joint and discuss the different imaging modalities that can be useful for its assessment.

Automatic Feature Engineering for Answer Selection and Extraction <=SEP=> This paper proposes a framework for automatically engineering features for two important tasks of question answering: answer sentence selection and answer extraction. We represent question and answer sentence pairs with linguistic structures enriched by semantic information, where the latter is produced by automatic classifiers, e.g., question classifier and Named Entity Recognizer. Tree kernels applied to such structures enable a simple way to generate highly discriminative structural features that combine syntactic and semantic information encoded in the input trees. We conduct experiments on a public benchmark from TREC to compare with previous systems for answer sentence selection and answer extraction. The results show that our models greatly improve on the state of the art, e.g., up to 22% on F1 (relative improvement) for answer extraction, while using no additional resources and no manual feature engineering.

Active SLAM using Model Predictive Control and Attractor based Exploration <=SEP=> Active SLAM poses the challenge for an autonomous robot to plan efficient paths simultaneous to the SLAM process. The uncertainties of the robot, map and sensor measurements, and the dynamic and motion constraints need to be considered in the planning process. In this paper, the active SLAM problem is formulated as an optimal trajectory planning problem. A novel technique is introduced that utilises an attractor combined with local planning strategies such as model predictive control (a.k.a. receding horizon) to solve this problem. An attractor provides high level task intentions and incorporates global information about the environment for the local planner, thereby eliminating the need for costly global planning with longer horizons. It is demonstrated that trajectory planning with an attractor results in improved performance over systems that have local planning alone

Domestic food and sustainable design: a study of university student cooking and its impacts <=SEP=> In four university student kitchens over twenty-one days, we captured participants' food preparation activity, quantified the greenhouse gas emissions and direct energy connected to the food and cooking, and talked to participants about their food practices. Grounded in this uniquely detailed micro-account, our findings inform sustainable design for cooking and eating at home and quantify the potential impacts. We outline the relation of the impacts to our participants' approaches to everyday food preparation, the organisation of their time, and the role of social meals. Our technique allows evaluation of opportunities for sustainable intervention design: at the appliance, in the digitally-mediated organisation of meals and inventory management, and more broadly in reflecting upon and reshaping diet.

TAaaS: Trustworthy Authentication as a Service Based on Trusted Path <=SEP=> Authentication as a Service (AaaS) provides on-demand delivery of multi-factor authentication (MFA). However, current AaaS has left out of consideration the trustworthiness of user inputs at client evices and the risk of privacy exposure at the AaaS providers. To solve these concerns, we present TAaaS, Trustworthy Authentication as a Service, which offers a trusted path-based MFA service to the service provider in the cloud. TAaaS leverages the hypervisor-based trusted path to ensure the trustworthiness of user inputs, and addresses privacy concerns in the cloud by storing only the irreversible user account information. We implement two end-to-end prototypes and evaluate our work to show its feasibility and security.

Bayesian Neural Networks for Internet Traffic Classification <=SEP=> Internet traffic identification is an important tool for network management. It allows operators to better predict future traffic matrices and demands, security personnel to detect anomalous behavior, and researchers to develop more realistic traffic models. We present here a traffic classifier that can achieve a high accuracy across a range of application types without any source or destination host-address or port information. We use supervised machine learning based on a Bayesian trained neural network. Though our technique uses training data with categories derived from packet content, training and testing were done using features derived from packet streams consisting of one or more packet headers. By providing classification without access to the contents of packets, our technique offers wider application than methods that require full packet/payloads for classification. This is a powerful advantage, using samples of classified traffic to permit the categorization of traffic based only upon commonly available information

A VLSI Implementation of an Analog Neural Network Suited for Genetic Algorithms <=SEP=> The usefulness of an artificial analog neural network is closely bound to its trainability. This paper introduces a new analog neural network architecture using weights determined by a genetic algorithm. The first VLSI implementation presented in this paper achieves 200 giga connections per second with 4096 synapses on less than 1 mm silicon area. Since the training can be done at the full speed of the network, several hundred individuals per second can be tested by the genetic algorithm. This makes it feasible to tackle problems that require large multi-layered networks.

Relationship Banking : What Do We Know ? <=SEP=> This paper briefly reviews the contemporary literature on relationship banking. We start out with a discussion of the raison d’ˆ etre of banks in the context of the financial intermediation literature. From there we discuss how relationship banking fits into the core economic services provided by banks and point at its costs and benefits. This leads to an examination of the interrelationship between the competitive environment and relationship banking as well as a discussion of the empirical evidence. Journal of Economic LiteratureClassification Numbers: G20, G21, L10. C © 2000 Academic Press

Microalgae as a raw material for biofuels production <=SEP=> Biofuels demand is unquestionable in order to reduce gaseous emissions (fossil CO2, nitrogen and sulfur oxides) and their purported greenhouse, climatic changes and global warming effects, to face the frequent oil supply crises, as a way to help non-fossil fuel producer countries to reduce energy dependence, contributing to security of supply, promoting environmental sustainability and meeting the EU target of at least of 10% biofuels in the transport sector by 2020. Biodiesel is usually produced from oleaginous crops, such as rapeseed, soybean, sunflower and palm. However, the use of microalgae can be a suitable alternative feedstock for next generation biofuels because certain species contain high amounts of oil, which could be extracted, processed and refined into transportation fuels, using currently available technology; they have fast growth rate, permit the use of non-arable land and non-potable water, use far less water and do not displace food crops cultures; their production is not seasonal and they can be harvested daily. The screening of microalgae (Chlorella vulgaris, Spirulina maxima, Nannochloropsis sp., Neochloris oleabundans, Scenedesmus obliquus and Dunaliella tertiolecta) was done in order to choose the best one(s), in terms of quantity and quality as oil source for biofuel production. Neochloris oleabundans (fresh water microalga) and Nannochloropsis sp. (marine microalga) proved to be suitable as raw materials for biofuel production, due to their high oil content (29.0 and 28.7%, respectively). Both microalgae, when grown under nitrogen shortage, show a great increase (~50%) in oil quantity. If the purpose is to produce biodiesel only from one species, Scenedesmus obliquus presents the most adequate fatty acid profile, namely in terms of linolenic and other polyunsaturated fatty acids. However, the microalgae Neochloris oleabundans, Nannochloropsis sp. and Dunaliella tertiolecta can also be used if associated with other microalgal oils and/or vegetable oils.

Evaluating enterprise resource planning ( ERP ) post-implementation problems in Egypt <=SEP=> The aim of the research is to identify and evaluate the main problems experienced in the ERP postimplementation stage of multinational, privately-owned Egyptian and governmental organizations in Egypt. Data gathering was achieved by means of a set of interviews and online questionnaire conducted to 50 companies implementing ERP in Egypt. The paper presents a descriptive analysis of the difficulties and problems encountered by organizations in Egypt following ERP implementation and how these have contributed to unsuccessful implementation overall.

Error-Correcting Codes for Semiconductor Memory Applications: A State-of-the-Art Review <=SEP=> This paper presents a state-of-the-art review of error-correcting codes for computer semiconductor memory applications. The construction of four classes of error-correcting codes appropriate for semiconductor memory designs is described, and for each class of codes the number of check bits required for commonly used data lengths is provided. The implementation aspects of error correction and error detection are also discussed, and certain algorithms useful in extending the error-correcting capability for the correction of soft errors such as a-particle-induced errors are examined in some detail.

Smarter Presentations: Exploiting Homography in Camera-Projector Systems <=SEP=> Standard presentation systems consisting of a laptop connected to a projector suffer from two problems: (1) the projected image appears distorted (keystoned) unless the projector is precisely aligned to the projection screen; (2) the speaker is forced to interact with the computer rather than the audience. This paper shows how the addition of an uncalibrated camera, aimed at the screen, solves both problems. Although the locations, orientations and optical parameters of the camera and projector are unknown, the projector-camera system calibrates itself by exploiting the homography between the projected slide and the camera image. Significant improvements are possible over passively calibrating systems since the projector actively manipulates the environment by placing feature points into the scene. For instance, using a low-resolution (160x120) camera, we can achieve an accuracy of ±3 pixels in a 1024x768 presentation slide. The camera-projector system infers models for the projector-to-camera and projector-to-screen mappings in order to provide two major benefits. First, images sent to the projector are pre-warped in such a way that the distortions induced by the arbitrary projector-screen geometry are precisely negated. This enables projectors to be mounted anywhere in the environment – for instance, at the side of the room, where the speaker is less likely to cast shadows on the screen, and where the projector does not occlude the audience’s view. Second, the system detects the position of the user’s laser pointer dot in the camera image at 20Hz, allowing the laser pointer to emulate the pointing actions of a mouse. This enables the user to activate virtual buttons in the presentation (such as “next slide”) and draw on the projected image. The camera-assisted presentation system requires no special hardware (aside from the cheap camera) Rahul Sukthankar (rahuls@cs.cmu.edu) is now affiliated with Compaq Cambridge Research Lab and Carnegie Mellon; Robert Stockton and Matthew Mullin ({rstock,mmullin}@whizbang.com) are now with WhizBang! Labs. and runs on a standard laptop as a Java application. It is now used by the authors for all of their conference presentations.

Scholarly paper recommendation via user's recent research interests <=SEP=> We examine the effect of modeling a researcher's past works in recommending scholarly papers to the researcher. Our hypothesis is that an author's published works constitute a clean signal of the latent interests of a researcher. A key part of our model is to enhance the profile derived directly from past works with information coming from the past works' referenced papers as well as papers that cite the work. In our experiments, we differentiate between junior researchers that have only published one paper and senior researchers that have multiple publications. We show that filtering these sources of information is advantageous -- when we additionally prune noisy citations, referenced papers and publication history, we achieve statistically significant higher levels of recommendation accuracy.

Collecting Large, Richly Annotated Facial-Expression Databases from Movies <=SEP=> Two large facial-expression databases depicting challenging real-world conditions were constructed using a semi-automatic approach via a recommender system based on subtitles.

The role of the inferior frontal junction area in cognitive control <=SEP=> Cognitive control processes refer to our ability to coordinate thoughts and actions in accordance with internal goals. In the fronto-lateral cortex such processes have been primarily related to mid-dorsolateral prefrontal cortex (mid-DLPFC). However, recent brain-imaging and meta-analytic studies suggest that a region located more posterior in the fronto-lateral cortex plays a pivotal role in cognitive control as well. This region has been termed the inferior frontal junction area and can be functionally and structurally distinguished from mid-DLPFC.

Self processes in interdependent relationships Partner affirmation and the Michelangelo phenomenon <=SEP=> This essay reviews theory and research regarding the “Michelangelo phenomenon,” which describes the manner in which close partners shape one another’s dispositions, values, and behavioral tendencies. Individuals are more likely to exhibit movement toward their ideal selves to the degree that their partners exhibit affirming perception and behavior, exhibiting confidence in the self ’s capacity and enacting behaviors that elicit key features of the self ’s ideal. In turn, movement towards the ideal self yields enhanced personal well-being and couple well-being. We review empirical evidence regarding this phenomenon and discuss self and partner variables that contribute to the process.

Agile Flight Control Techniques for a Fixed-Wing Aircraft by Frantisek Michal Sobolic <=SEP=> As unmanned aerial vehicles (UAVs) become more involved in challenging mission objectives, the need for agility controlled flight becomes more of a necessity. The ability to navigate through constrained environments as well as quickly maneuver to each mission target is essential. Currently, individual vehicles are developed with a particular mission objective, whether it be persistent surveillance or fly-by reconnaissance. Fixed-wing vehicles with a high thrust-to-weight ratio are capable of performing maneuvers such as take-off or perch style landing and switch between hover and conventional flight modes. Agile flight controllers enable a single vehicle to achieve multiple mission objectives. By utilizing the knowledge of the flight dynamics through all flight regimes, nonlinear controllers can be developed that control the aircraft in a single design. This thesis develops a full six-degree-of-freedom model for a fixed-wing propellerdriven aircraft along with methods of control through nonconventional flight regimes. In particular, these controllers focus on transitioning into and out of hover to level flight modes. This maneuver poses hardships for conventional linear control architectures because these flights involve regions of the post-stall regime, which is highly nonlinear due to separation of flow over the lifting surfaces. Using Lyapunov backstepping control stability theory as well as quaternion-based control methods, control strategies are developed that stabilize the aircraft through these flight regimes without the need to switch control schemes. The effectiveness of each control strategy is demonstrated in both simulation and flight experiments. Thesis Supervisor: Jonathan P. How Title: Professor

Receiver Design for Downlink Non-Orthogonal Multiple Access (NOMA) <=SEP=> Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for further cellular enhancements toward 5G. Compared to orthogonal multiple access (OMA) such as orthogonal frequency-division multiple access (OFDMA), large performance gains were confirmed via system-level simulations. However, NOMA link-level simulations and the design of the receiver remain of great importance to validate NOMA performance gains. In this paper, we evaluate downlink NOMA link-level performance with multiple receiver designs and propose a novel NOMA transmitter and receiver design, where the signals of multi-users are jointly modulated at transmitter side and detected at receiver side. The predominant advantage of the proposed scheme is that at receiver side interference cancellation to the interference signal is not needed, thus low complexity is achieved. The performances of codeword-level SIC, symbol-level SIC and the proposed receiver are evaluated and compared with ideal SIC. Simulation results show that compared with ideal SIC, downlink NOMA link-level performance depends on actual receiver design and the difference in the power ratio split between the cell edge user and cell center user. In particular, it is shown that codeword-level SIC and the proposed receiver can both provide a good performance even when the power ratio difference between the cell center user and cell edge user is small and with real channel estimation.

Sovrin : digital identities in the blockchain era <=SEP=> In this paper we describe a practical digital identity project of a global scale, which solves a number of privacy and scalability problems using the concepts of anonymous credentials and permissioned blockchains. Even though both ideas have been known and developed for a number of years, our system appears to be the first amalgamation. The prototype has been developed, tested, and published as open source. I. DIGITAL IDENTITY: HISTORY AND CHALLENGES The idea of digital identity can be traced to the beginning of the computer era, when the user profiles were first transferred across networks. In the real world, different authorities issue licenses, passports, identification cards, credit cards, checks, etc., generally called credentials, to ordinary users for their presentation to various service or goods providers. This brings the concept of Issuer, User, and Verifier as subjects of the identity system. It immediately became clear that issuance, storage, and presentation procedures must follow a number of security requirements to be competitive with the traditional paper credentials: • Compatibility. Credentials issued by different Issuers can be combined for a single presentation by User who is required to prove several properties simultaneously: e.g. that he is at least age 18 employed by XYZ Corp. with a driver license and good eyesight (does not require corrective lenses). • Unforgeability. A malicious User is unable to present a credential not issued by a legitimate Issuer. • Scalability. A system must handle hundreds of Issuers and billions of Users, such as an international passport system. It might be required to handle thousands of transactions per second like the Visa system [1]. • Performance/Low latency. Verification of credentials must be almost instant and not require broadband network connectivity per credential, even if it is issued by a previously unknown Issuer. Credentials can be stored and processed easily by the User even if he is offline. • Revocation. An Issuer can revoke any credential such that a User and any Verifiers can know within a reasonable amount of time that credential was revoked. Additionally, a digital identity system could provide features impossible or difficult to implement in a paper identity system: • Minimal dependencies. Aside from an earlier issuance, an Issuer should not be involved during the preparation and presentation of proofs, and the verification of credentials, including proof of nonrevocation. • Privacy/Anonymity. The real identity of a User can be kept secret from Verifiers who do not need it. • Unlinkability. Different presentations of the same credential cannot be linked together. • Selective disclosure. Any subset of attributes embedded in a credential can be kept secret from Verifiers. The latter group of properties is particularly attractive for Users from authoritarian countries or those who are concerned about leaks of their data from careless Issuers or Verifiers. The privacy-oriented digital identity schemes have been proposed as U-Prove [2] (mainly Microsoft, primarily based on Brands’ credentials [3]) and Idemix [4] (mainly IBM, primarily based on the Camenisch-Lysyanskaya credentials [5]), with the ABC4Trust and FIDO [6] projects encompassing these two. Despite significant effort expended on both projects, neither is in widespread use today. We deduce that all these systems lack compatibility and scalability, as an actual implementation would require a meta-system that congregates multiple Issuers and Verifiers and manages credential schemas. Before recently, all such system would require a (trusted) global third party for the exchange and distribution of Issuers’ data and parameters. It seems that such a centralized party on a global scale could not exist. II. OUR CONTRIBUTIONS We designed and implemented a system called Sovrin, which integrates anonymous credentials with revocation [7], [8] for privacy, unforgeability, performance, unlinkability and a distributed ledger, taking best practices from Ethereum [9] and BFT protocols. The implementation is mostly finished and will go live in the near future. A. Anonymous credentials for privacy It is well known that the anonymity and unlinkability properties are provided by various kinds of anonymous credentials, the concept dating back to seminal works by David Chaum in 1980s [10] and refined in a number of follow-up papers including well-known [3], [7], [11]. Zeroknowledge proofs allow a User to prove the possession of a credential without showing the credential itself, thus providing unlinkability. Additional features include delegation [11] and revocation [8]. We reference the Idemix specification [4], [12] as the basis for our anonymous credential module as it provides unlinkability by default (in contrast to U-Prove). Although Idemix is available as a Java library, for portability and fast prototyping we select the Charm framework [13], which provides a Python API for large integers, signature schemes, and pairings. It also allows us to integrate the pairing-based revocation module easily. B. Our treatment of the revocation feature The revocation feature was missing in the original papers behind U-Prove and Idemix and was added later in different ways. The revocation procedure assumes that each credential has special Revocation-ID attribute with value iR, and Issuer can at any moment revoke a particular iR. For Verifiers this means that if a User with a revoked iR presents his credential, this can be detected by the Verifier. We observe that in addition to various drawbacks described above, the revocation feature provides quite a privacy leak. Indeed, consider a typical attack setting: a Verifier colludes with an Issuer to disclose the identity of a User. The Issuer then revokes half of the issued credentials, and the Verifier asks the User to update his revocation data. If the User succeeds in presenting a valid non-revocation proof, he is among the users with non-revoked iR. Then the Issuer reinstates the earlier revocations and revokes another group of revocation IDs of equal size. Repeating this procedure logN times, the Issuer-Verifier team can uniquely identify one of N users. C. Our selection of revocation methods Since 2001, the following revocation methods have been proposed: • Signature lists [14]. Issuer regularly releases a list of signatures, one per non-revoked iR. User proves that his credential has the same ID as in some signature. Verification is fast, but the amount of data retrieved by User and computation he does is huge, and multiple presentations are linkable. • Cryptographic accumulators [7], [8]. The issued iR is added to (or removed from) a constant-size accumulator A, and a User must prove that his (non-disclosed) ID is still contained in A. This approach is reasonably fast for all parties. • Forward revocation lists [15]. For each revoked iR, an Issuer generates a revocation entry f(iR). A User presents a non-revocation proof to a Verifier, who then tests the proof against every entry in the list. If all matches fail, the credential is deemed valid. This method requires significant computational resources from the Verifier. We decided to use accumulators based on bilinear maps [8] for performance reasons. The small order of the target group allows for short accumulators and witnesses. We have our own implementation of accumulators, which is based on a corrected version of paper [8]. The drawback is that the User must be aware of all revoked credentials, as the proof is updated every time another credential is revoked and needs (public) Issuer-specific data for the update. If User has small capacity, the data he needs to update the nonrevocation proof reveals his ID. Existing research papers suggest User connecting to Issuer every time before creating a non-revocation proof [8], which is privacy-vulnerable if Issuer or his agent colludes with Verifier. D. Revocation with attribute-based sharding. The accumulator-based revocation procedure requires the User to maintain his non-revocation data w using the indices {iR} of the credentials revoked and issued from the last update. To update w the User also needs to access a global set G = {gi} of validity tails, published by Issuer. The tail set G is immutable but should be generated in advance and occupy quite big space (256 bytes per credential). Even though the number of tails needed for the update is proportional to the number of revoked credentials in the period, the tails retrieved by the User effectively disclose his own index iR and thus his identity. For a global Issuer the User would be unable to carry the entire set of tails at his device, as they would require GBytes of storage. To prevent the privacy leak, we propose to partition the credential IDs I into shards I1, I2, . . . , Is of limited size so that the tail set G(Ij) for each shard would be feasible to download and carry (say, a dozen of MBytes). Together with the credential to present, the User will then inform the Verifier of his shard number j so that the Verifier uses the corresponding accumulator data Aj . To make the shard index privacy-oblivious, we suggest attribute-based sharding, when Issuer selects q attributes {ai} of necessary granularity (year of birth, zip code, etc.) and partitions the credential set by each ai independently. For each attribute ai and each shard an accumulator Ai,j will be published. Nevertheless, since accumulators are of constant size, the total amount of space consumed by q× s accumulators is negligible. At the time of presentation the User selects the attribute on which he will prove the nonrevocation. This attribute should be among those that are already disclosed to the Verifier. Before presentation, User downloads the entire set Gi,j of tails that correspond to his share j at attribute i. As the tails are signed, he ask the Verifier to download, and this does not reduce the privacy. We also implement the revocati

Retrieval-Based Learning: Positive Effects of Retrieval Practice in Elementary School Children <=SEP=> A wealth of research has demonstrated that practicing retrieval is a powerful way to enhance learning. However, nearly all prior research has examined retrieval practice with college students. Little is known about retrieval practice in children, and even less is known about possible individual differences in retrieval practice. In three experiments, 88 children (mean age 10 years) studied a list of words and either restudied the items or practiced retrieving them. They then took a final free recall test (Experiments 1 and 2) or recognition test (Experiment 3). In all experiments, children showed robust retrieval practice effects. Although a range of individual differences in reading comprehension and processing speed were observed among these children, the benefits of retrieval practice were independent of these factors. The results contribute to the growing body of research supporting the mnemonic benefits of retrieval practice and provide preliminary evidence that practicing retrieval may be an effective learning strategy for children with varying levels of reading comprehension and processing speed.

Human posture recognition using curved segments for image retrieval <=SEP=> This paper presents a human posture recognition method from a single image. We rst segment an image into homogeneous regions and extract curve segments corresponding to human body parts. Each body part is considered as a 2D ribbon. From the smooth curve segments in skin regions, 2D ribbons are extracted and a human body model is constructed. We assign a predeened posture type to the image according to the constructed body model. For the user input query to retrieve images containing human of speciic posture, the system convert the query to a body model. The body model is compared to other body models saved in the local storage of target images and images of good matches are retrieved. When a face detection result is available for the given image, it is also used to increase the reliability of body model. For the query human posture, our system retrieves images of the corresponding posture. As another application, the proposed method provides an initial location of a human body to track in a video sequence.

A Study Investigating Typical Concepts and Guidelines for Ontology Building <=SEP=> In semantic technologies, the shared common understanding of the structure of information among artifacts (people or software agents) can be realized by building an ontology. To do this, it is imperative for an ontology builder to answer several questions: a) what are the main components of an ontology? b) How an ontology look likes and how it works? c) Verify if it is required to consider reusing existing ontologies or not? c) What is the complexity of the ontology to be developed? d) What are the principles of ontology design and development? e) How to evaluate an ontology? This paper answers all the key questions above. The aim of this paper is to present a set of guiding principles to help ontology developers and also inexperienced users to answer such questions.