Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Sphere Size Using the PHANToM: Towards a Set of Building Blocks for Rendering Haptic Environment

This paper presents an approach to developing building blocks for rendering synthetic haptic environments using force-reflective haptic interfaces. The task of sphere size identification is used to explore an accurate and efficient way of estimating human performance using the absolute identification paradigm. The results show that subjects can reliably identify 3 to 4 sphere sizes with a set of spheres ranging from 10 to 80 mm in radius. Subjects with prior experience with force-reflective haptic interfaces exhibit higher performance levels. The results also indicate that gradually increasing stimulus complexity yields more accurate measurements of information transmission at little additional cost in terms of total number of experimental trials. Subsequent studies will utilize the new experimental protocol developed in this study.
Switching by agents between two trading behaviors and the stylized facts of financial markets.

I propose an agent-based model of a single-asset financial market, described in terms of a small number of parameters. I show that switching by agents between two trading behaviors (informed vs. liquidity traders) leads to a market price that fluctuates endlessly and a volatility that displays a mean-reverting behavior. This agent-based model generically leads to price returns having statistical properties similar to the stylized facts observed in financial time series: an absence of autocorrelation in returns, stochastic volatility, excess volatility, volatility clus-
Creating a Collaborative B 2 B Environment in the Classroom : Evaluation of Methods Utilized in an International Simulation over a 4-Year Period

As businesses of the 21st century continue to expand their relationships with partners and customers enabled by information technologies, Universities need to prepare and expose students to the organizational and technical issues that enterprises encounter when developing business-to-business (B2B) systems. Understanding the issues and the ability to establish, develop, and manage B2B environments are skills needed in this 21st century spirit of eBusiness. This paper explains how to create and conduct a collaborative B2B environment in the classroom based on the experiences of a 4-year cooperative curriculum between two Universities. In addition, the analyses results of the collaboration methods utilized over that 4year period are presented. These results have implications on what collaboration methods may be or may not be successful in conducting a B2B simulation in your curriculum.
A REVIEW OF AUTOMATED DIABETIC RETINOPATHY DIAGNOSIS FROM FUNDUS IMAGE

A fundus camera provides digitised data in the form of a fundus image that can be effectively used for the computerised automated detection of diabetic retino pathy. A completely automated screening system for the disease can largely reduces the burden of the speci alist and saves cost. Noise and other disturbances that occur during image acquisition may lead to false de tection of the disease and this is overcome by vari ous image processing techniques. Following this differe nt features are extracted which serves as the guide line to identify and grade the severity of the disease. Bas ed on the extracted features classification of the retinal image as normal or abnormal is brought about. In li terature various techniques for feature extraction and different types of classifiers have been used to im prove sensitivity and specificity. FROC analysis an d confusion matrix are used to evaluate the system pe rformance. In this paper critical analysis of vari ous algorithms and classifiers is done that have been used for the automated diagnosis.
Hydrodynamic limits for kinetic equations and the diffusive approximation of radiative transport for acoustic waves

We consider a class of kinetic equations, equipped with a single conservation law, which generate L 1 -contractions. We discuss the hydrodynamic limit to a scalar conservation law and the diffusive limit to a (possibly) degenerate parabolic equation. The limits are obtained in the "dissipative" sense, equivalent to the notion of entropy solutions for conservation laws, which permits the use of the perturbed test function method and allows for simple proofs. A general compactness framework is obtained for the diffusive scaling in L 1 . The radiative transport equations, satisfied by the Wigner function for random acoustic waves, present such a kinetic model that is endowed with conservation of energy. The general theory is used to validate the diffusive approximation of the radiative transport equation.
Secondary Teachers' Reflections From a Year of Professional Learning Related to Academic Language

This article explores the changing beliefs and practices of 25 secondary teachers participating in a yearlong professional learning (PL) partnership. To demonstrate differences in teachers' approaches to and understandings resulting from that PL, the authors looked more closely at three teachers and found that their ideas about academic language instruction and their related pedagogy progressed in ways that were consistent with the stated PL objectives. However, the teachers varied in the way they situated the learning within their practice. The cases presented highlight the aspects of PL that resonated most with the teachers participating in the yearlong initiative.
New FMO type to flag ROI in H.264/AVC

This paper presents a new type of Flexible Macroblock Ordering (FMO) type for the H.264 Advanced Video Coding (AVC) standard, which can more efficiently flag the position and shape of regions of interest (ROIs) in each frame. In H.264/AVC, 7 types of FMO have been defined, all of which are designed for error resilience. Most previous work related to ROI processing has adopted Type-2 (foreground & background), or Type-6 (explicit), to flag the position and shape of the ROI. However, only rectangular shapes are allowed in Type-2 and for non-rectangular shapes, the non-ROI macroblocks may be wrongly flagged as being within the ROI, which could seriously affect subsequent processing of the ROI. In Type-6, each macroblock in a frame uses fixed-length bits to indicate to its slice group. In general, each ROI is assigned to one slice group identity. Although this FMO type can more accurately flag the position and shape of the ROI, it incurs a significant bitrate overhead. The proposed new FMO type uses the smallest rectangle that covers the ROI to indicate its position and a spiral binary mask is employed within the rectangle to indicate the shape of the ROI. This technique can accurately flag the ROI and provide significantly savings in the bitrate overhead. Compared with Type-6, an 80% to 90% reduction in the bitrate overhead can be obtained while achieving the same accuracy.
OPTIMALITY AND SENSITIVITY FOR SEMILINEAR BANG-BANG TYPE OPTIMAL CONTROL PROBLEMS

In optimal control problems with quadratic terminal cost functionals and systems dynamics linear with respect to control, the solution often has a bang-bang character. Our aim is to investigate structural solution stability when the problem data are subject to perturbations. Throughout the paper, we assume that the problem has a (possibly local) optimum such that the control is piecewise constant and almost everywhere takes extremal values. The points of discontinuity are the switching points. In particular, we will exclude the so-called singular control arcs, see Assumptions 1 and 2, Section 2. It is known from the results by Agrachev et al. (2002) stating that regularity assumptions, together with a certain strict second-order condition for the optimization problem formulated in switching points, are sufficient for strong local optimality of a statecontrol solution pair. This finite-dimensional problem is analyzed in Section 3 and optimality conditions are formulated (Lemma 2). Using well-known results concerning solution sensitivity for mathematical programs in R n (Fiacco, 1983) one may further conclude that, under parameter changes in the problem data, the switching points will change Lipschitz continuously. The last section completes these qualitative statements by calculating sensitivity differentials (Theorem 2, Lemma 6). The method requires a simultaneous solution of certain linearized multipoint boundary value problems.
Tachyon Condensation and Non-BPS D-branes in a Ramond-Ramond Plane Wave Background

We consider string theory in maximally supersymmetric type IIB plane wave background with constant five form Ramond-Ramond flux (RR plane wave). It is argued that there exists a universal sector of string configurations independent of the null coordinate x − such that the space-time action evaluated at such a configuration is same in the RR plane wave and flat background. By naturally assuming its validity for the open strings we further argue that the D-branes extending along x ± are universal in these two backgrounds. Moreover, a universal D-brane which is BPS in flat space must be tachyon-free in RR plane wave and a non-BPS D-brane should have a real tachyon whose potential is universal. Given the above observation we then proceed to describe open string theories for the non-BPS D-branes in RR plane wave. It is suggested that the light-cone GreenSchwarz fermions on the world-sheet satisfy certain bi-local boundary condition similar to that corresponding to flat space. We attempt a canonical quantisation with this boundary condition which gives rise to an open string spectrum similar to that in flat space containing an R and NS sectors of states. In this process we encounter certain subtleties involving the R sector zero modes. Although the derivation of the R sector zero mode spectrum using the open string theory has not been completely settled, we suggest definite answer by requiring consistency with the relevant space-time interpretation. We finally generalise the above basic features of universality to all the exact pp-wave backgrounds with the same dilaton profile in a given string theory.
Tech . Report : Matrix dimensionality reduction for LSI using Spherical K-means

In this paper, we propose using Spherical K-means algorithm as a preprocessing step to using Latent Semantic Indexing (LSI). LSI is a well known approach in Information Retrieval (IR). Spherical K-means is a fast clustering algorithm that puts similar documents together, thus forming K clusters. We propose using Spherical Kmeans to form the matrix of normalized concept vectors yields high reduction in time and space complexity. The results obtained by proposed approach are compared with those using LSI. We obtained comparable results using only 10% of the original size (column-wise) matrix.
MP-PIPE: a massively parallel protein-protein interaction prediction engine

Interactions among proteins are essential to many biological functions in living cells but experimentally detected interactions represent only a small fraction of the real interaction network. Computational protein interaction prediction methods have become important to augment the experimental methods; in particular sequence based prediction methods that do not require additional data such as homologous sequences or 3D structure information which are often not available. Our Protein Interaction Prediction Engine (PIPE) method falls into this category. Park has recently compared PIPE with the other competing methods and concluded that our method "significantly outperforms the others in terms of recall-precision across both the yeast and human data". Here, we present MP-PIPE, a new massively parallel PIPE implementation for large scale, high throughput protein interaction prediction. MP-PIPE enabled us to perform the first ever complete scan of the entire human protein interaction network; a massively parallel computational experiment which took three months of full time 24/7 computation on a dedicated SUN UltraSparc T2+ based cluster with 50 nodes, 800 processor cores and 6,400 hardware supported threads. The implications for the understanding of human cell function will be significant as biologists are starting to analyze the 130,470 new protein interactions and possible new pathways in Human cells predicted by MP-PIPE.
An Online Sparsity-Cognizant Loop-Closure Algorithm for Visual Navigation

It is essential for a robot to be able to detect revisits or loop closures for long-term visual navigation. A key insight is that the loop-closing event inherently occurs sparsely, i.e., the image currently being taken matches with only a small subset (if any) of previous observations. Based on this observation, we formulate the problem of loop-closure detection as a sparse, convex `1-minimization problem. By leveraging on fast convex optimization techniques, we are able to efficiently find loop closures, thus enabling real-time robot navigation. This novel formulation requires no offline dictionary learning, as required by most existing approaches, and thus allows online incremental operation. Our approach ensures a global, unique hypothesis by choosing only a single globally optimal match when making a loop-closure decision. Furthermore, the proposed formulation enjoys a flexible representation, with no restriction imposed on how images should be represented, while requiring only that the representations be close to each other when the corresponding images are visually similar. The proposed algorithm is validated extensively using public real-world datasets.
The Optimal Policy of Production for Perishable Products during the Renewing Process

In this paper, we deal with the problem how to determine the optimal production quantity of the perishable products during the renewing process. The perishable products such as the mobile phones, CPUs as well as the computers often face the condition in which two generations of products coexist in the market. So the producer must make a production decision for two generation products. Considering the salvage values of products, the production quantity control model is proposed so as to maximize the enterprise revenues with the assumption of stochastic demand. We show that the optimal solution to the proposed model can be put forward. Furthermore a numerical example proves that the greater the demand for products during the renewing process is, the greater the optimal production quantity is.
Quadratic optimal control for discrete-time infinite-dimensional stochastic bilinear systems

In this paper, we consider the class of infinite-dimensional discrete-time linear systems with multiplicative random disturbances (i.e. with the state multiplied by a random sequence), also known as stochastic bilinear systems. We formulate and solve the quadratic optimal-control problem for this class of systems subject to an arbitrary additive stochastic £2 input disturbance. Under assumptions that guarantee the existence of a solution to an algebraic Riccati-like operator equation (derived previously by the authors), we characterize a bounded linear operator that takes the additive stochastic (. 2 input disturbance and the initial condition into the optimal control law. Such a result generalizes, to the infinite-dimensional bilinear stochastic case, some known results for the deterministic linear case.
Closing the gap: gender parity in political engagement on social media

ABSTRACT Historically, major gender differences exist in both political engagement and online content creation. Expanding on these literatures, this study considers the extent to which men and women engage in politics specifically in social media. Novel survey data are employed to test for any gendered differences in encountering and responding to political content via social media. Despite measuring a robust set of political behaviors within social media, few gender differences emerge. Where differences do emerge, they are most likely among the most visible political behaviors, suggesting that women may strategically engage in less visible or less-likely-to-offend political behaviors, as compared to men. This poses important questions regarding political participation, representation, and gender.
Leveraging Partially Faulty Links Usage for Enhancing Yield and Performance in Networks-on-Chip

The communication infrastructure of a complex multicore system-on-a-chip is getting an increasing fraction of the overall chip area. According to the International Technology Roadmap for Semiconductors, killer defect density does not decrease over successive technology generations. For this reason, the probability that a manufacturing defect affects the communication system is predicted to increase. In this paper, we deal with manufacturing defects which affect the links in a network-on-chip-based interconnection system. The goal of this paper is to show that by using effective routing functions, supported by appropriate selection policies and with a limited amount of extra logic in the router, it is easy to exploit partially faulty links to improve the performance of the system. We show that, instead of discarding partially faulty links, they can be used at reduced capacity to improve the distribution of the traffic over the network, yielding performance and power improvements. We couple an application-specific routing function with a set of selection policies which are aware of link fault distribution and evaluate them on both synthetic traffic and a real complex multimedia application. We also present an implementation of the router, augmented with the extra logic, to support both the proposed selection functions and the transmission of messages over partially faulty links. We analyze the router in terms of silicon area, timing, and power dissipation.
Adolescent drinking behavior:A mediated moderation analysis of the roles of alcohol expectancy and drinking refusal efficacy

A sample of 544 7th,8th,10th,and 11th graders was recruited in the study to explore the mediated moderation pathways among positive alcohol expectancy,negative alcohol expectancy,drinking refusal efficacy and adolescent drinking behavior after controlling for several demographic variables.Results showed(1) of all the participants,about 28.31% reported ever drinking,13.60% binge drinking and 8.27% drunk at least once in the past 30 days;(2) positive alcohol expectancy could significantly predict adolescent drinking behavior,and negative alcohol expectancy was the moderator of the relationship between positive alcohol expectancy and adolescent drinking behavior;(3) drinking refusal efficacy completely mediated the effect of positive alcohol expectancy on adolescent drinking behavior,as well as the moderated effect of negative alcohol expectancy on association of positive alcohol expectancy with adolescent drinking behavior;(4) mediated moderating effect analysis indicated that negative drinking expectancy buffered the risk of positive drinking expectancy on adolescent drinking behavior.The implication of the results for designing prevention and intervention programs was further discussed.
On rounding error resilience, maximal attainable accuracy and parallel performance of the pipelined Conjugate Gradients method for large-scale linear systems in PETSc

Pipelined Krylov solvers typically display better strong scaling compared to standard Krylov methods for large linear systems. The synchronization bottleneck is mitigated by overlapping time-consuming global communications with computations. To achieve this hiding of communication, pipelined methods feature additional recurrence relations on auxiliary variables. This paper analyzes why rounding error effects have a significantly larger impact on the accuracy of pipelined algorithms. An algebraic model for the accumulation of rounding errors in the (pipelined) CG algorithm is derived. Furthermore, an automated residual replacement strategy is proposed to reduce the effect of rounding errors on the final solution. MPI parallel performance tests implemented in PETSc on an Intel Xeon X5660 cluster show that the pipelined CG method with automated residual replacement is more resilient to rounding errors while maintaining the efficient parallel performance obtained by pipelining.
Optimum Resistive Type Fault Current Limiter: An Efficient Solution to Achieve Maximum Fault Ride-Through Capability of Fixed-Speed Wind Turbines During Symmetrical and Asymmetrical Grid Faults

This paper proposes an optimum resistive type fault current limiter (OR-FCL) as an efficient solution to achieve maximum fault ride-through (FRT) capability of fixed-speed wind turbines (FSWT) during various grid faults. In this paper, a dedicated control circuit is designed for the OR-FCL that enables it to insert an optimum value of resistance in the FSWT's fault current's path for improving transient behavior of the FSWT. The optimum resistance value depends on fault location and prefault active power. The control circuit of the proposed OR-FCL is capable of calculating the optimum resistance value for all the prefault conditions. By using the proposed control circuit, the FSWT can achieve its maximum FRT capability during symmetrical and asymmetrical faults, even at zero grid voltage. Analysis is provided in detail to highlight the process of calculating the optimum resistance of the OR-FCL. Moreover, the effect of the resistance value of the OR-FCL on the FRT behavior of FSWT is investigated. To show the efficiency of the proposed OR-FCL, its performance during various operation conditions of the FSWT is studied. It can be proved that each operation condition needs its own optimum resistance value, which can be obtained by using the proposed control circuit during the fault to achieve the maximum FRT capability of the FSWT. Comprehensive sets of simulations are carried out in PSCAD/EMTDC software and the results prove the effectiveness of the proposed approach.
KCFA-based missing area restoration including new priority estimation

A kernel cross-modal factor analysis (KCFA) based missing area restoration method including a new priority estimation scheme is presented in this paper. The proposed method estimates latent relationship between missing areas and their neighboring areas by deriving projection matrices minimizing their errors in the latent space based on KCFA. This latent relationship represented by the derived projection matrices is optimal for accurately restoring missing areas within the target image. Furthermore, the proposed method adopts a new priority estimation scheme which determines the restoration order of missing areas. Specifically, this priority is estimated based on the criterion representing the restoration performance derived from KCFA, and it enables adaptive selection of missing areas successfully restored by our method. Consequently, it becomes feasible to accurately perform the restoration of missing areas by using the proposed KCFA-based method. Experimental results show subjective and quantitative improvements of the proposed method over previously reported restoration methods.
A User-Centered Perspective on Algorithmic Personalization

Much has been written and discussed regarding the rise of personalization in online services. The Internet is now unique to every user, from advertising to search to pricing. Personalization has multiple benefits to users, as it can save time by extrapolating unstated details like location to enrich the online experience. However, personalization may not benefit all users equally. Some users may perceive it as unfair, depending on what characteristics are identified to create individually personalized experiences. Personalization can disadvantage some users when it is predicated on negative assumptions. Moreover, it is often hidden from users, limiting their opinion to object (or express any opinion on) its results.