Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinemic Wave: A Mobile Freehand Gesture And Text-Entry System

We present and demonstrate Kinemic Wave, a fully freehand and mobile interaction system, which allows gesture control and text-entry on-the-go. We use wrist-worn inertial sensors which are almost independent of environmental influences. The system is therefore especially suited to interact with smart- and augmented-reality glasses. Simple commands like scrolling or confirmation can be input with short gestures, more complex commands, search terms, small messages or annotations can be input by writing text continuously in the air. Interaction integrates seamlessly in other activities as gestures and Airwriting are spotted automatically in the continuous data stream.
Identity-based Threshold Signature from the Bilinear Pairings

In this paper, we formalize the concept of identity-based threshold signature and give the first provably secure scheme based on the bilinear pairings. An important feature of our scheme is that a private associated with an identity rather than a master key of the Public Key Generator is shared among signature generation servers, which, we claim, is more important in practice. From a theoretical point of view, an interesting aspect of our results is that the security of one of the verifiable secret sharing schemes used to construct the identity-based threshold signature scheme is relative to the modified Generalized Bilinear Inversion (mGBI) problem, which is a slight modification of the Generalized Tate Inversion (GTI) problem that Joux recently proposed and called for applying it to cryptographic protocols. Hence, our result gives a partial solution to Joux's question.
The Productivity Paradox: The Role of Quality and Technology Type in the Investment Decision

Many researchers have noted that large information technology (IT) investments in the United States have not been accompanied by gains in productivity. This phenomenon has been termed the "productivity paradox". The assumption underlying this paradox is that IT should enable individuals and organizations to become more productive. The purpose of this paper is to provide insight into the results of some of the widely cited studies on the productivity paradox. In particular, we examine the conditions under which organizations should not expect investments in IT to lead to productivity gains. In fact, there are times when companies should invest in technology that will decrease overall productivity, because doing so will increase organizational profits. In the model we developed, a profit maximizing, rather than a productivity maximizing, monopolist chooses the quality (i.e. performance, features, etc.) and the price for a single product. We show how the impact of IT on the profitability and productivity of the monopolist depends on the type of technology implemented in the firm. For example, automation of overhead tasks always improves both profits and productivity, but technological tools which enhance the capabilities of workers can result in improved profits yet lower productivity. Several implications for both managers and researchers are also discussed. 3 "We see computers everywhere except in the productivity statistics. " – Robert Solow
Valuation and optimal strategies of convertible bonds

This article presents a contingent claim valuation of a callable convertible bond with the issuer's credit risk. The optimal call, voluntary conversion, and bankruptcy strategies are jointly determined by shareholders and bondholders to maximize the equity value and the bond value, respectively. This model not only incorporates tax benefits, bankruptcy costs, refunding costs, and a call notice period, but also takes account of the issuer's debt size and structure. The numerical results show that the predicted optimal call policies are generally consistent with recent empirical findings; therefore, calling convertible bonds too late or too early can be rational. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:895–922, 2006
Use Of Non-verbal Tools To Express Self And Enhance Hope

The purpose of this article is to introduce non-verbal tools as a way to initiate the psychosocial support response after a major disaster. The psychosocial interventions that follow the application of the Non Verbal Tool in its different configurations are based on the principle of fostering and strengthening the social and psychological attributes among the community members. The various psychosocial support techniques can be grouped into five categories according to the use of the Non Verbal Tool and frequency of usage. The article presents the development methods, cross cultural validation and the psychometric qualities of the original non-verbal tool. The article concludes that these type of intervention should be included in the repertoire of strategies used to develop and implement a psychosocial support program.
Efficient Computation of Chebyshev Polynomials in Computer Algebra

In this article, we give an overview about the efficiency of theabove methods in the general purpose computer algebra systems Axiom, Macsyma, Maple, Mathematica, MuPAD and REDUCE. Primarily we study the implementation of the Chebyshev polynomials of the first kind as an example case. First, we consider the builtin implementations of the Chebyshev polynomials in these systems. Next we study the classical algorithms beginning with the slow ones, and leading to the efficient ones. Finally, we finish with an algorithm based on a divide and conquer approach which has a remarkable complexity. In particular, we will show that
Nutritional Factors Affecting Abdominal Fat Deposition in Poultry: A Review

The major goals of the poultry industry are to increase the carcass yield and to reduce carcass fatness, mainly the abdominal fat pad. The increase in poultry meat consumption has guided the selection process toward fast-growing broilers with a reduced feed conversion ratio. Intensive selection has led to great improvements in economic traits such as body weight gain, feed efficiency, and breast yield to meet the demands of consumers, but modern commercial chickens exhibit excessive fat accumulation in the abdomen area. However, dietary composition and feeding strategies may offer practical and efficient solutions for reducing body fat deposition in modern poultry strains. Thus, the regulation of lipid metabolism to reduce the abdominal fat content based on dietary composition and feeding strategy, as well as elucidating their effects on the key enzymes associated with lipid metabolism, could facilitate the production of lean meat and help to understand the fat-lowering effects of diet and different feeding strategies.
Effect of Deep Brain Stimulation on Speech Performance in Parkinson's Disease

Deep brain stimulation (DBS) has been reported to be successful in relieving the core motor symptoms of Parkinson's disease (PD) and motor fluctuations in the more advanced stages of the disease. However, data on the effects of DBS on speech performance are inconsistent. While there are some series of patients documenting that speech function was relatively unaffected by DBS of the nucleus subthalamicus (STN), other investigators reported on improvements of distinct parameters of oral control and voice. Though, these ameliorations of single speech modalities were not always accompanied by an improvement of overall speech intelligibility. On the other hand, there are also indications for an induction of dysarthria as an adverse effect of STN-DBS occurring at least in some patients with PD. Since a deterioration of speech function has more often been observed under high stimulation amplitudes, this phenomenon has been ascribed to a spread of current-to-adjacent pathways which might also be the reason for the sporadic observation of an onset of dysarthria under DBS of other basal ganglia targets (e.g., globus pallidus internus/GPi or thalamus/Vim). The aim of this paper is to review and evaluate reports in the literature on the effects of DBS on speech function in PD.
Information Hiding for Text by Paraphrasing

Digital fingerprinting becomes paid growing attention as a technology resolving copyright problems. Previously, researchers have been only interested in image based digital fingerprinting where secret information is hidden in images, and text have not been the main target of hiding information. In this paper, we propose an information hiding method for text. Our information hiding method is based on paraphrasing that preserves the meaning. By paraphrasing or not, pieces of information are embedded. We experimentally evaluated the proposed method with Japanese manuals and user agreement forms of software, and found the paraphrased text, namely information hidden text, is preserving the meaning of original contents and very natural as language.
Entertainment Games for Teaching English as a Second Language

This article explores the use of entertainment games for teaching English as a second language. It is a narrative literature review of theories of motivation and learning. To facilitate the choice of didactic resources to be used in the English classroom by teachers, this study brings to light the characteristics relevant to teaching that can be found in games, associated with different genres. In this sense, 14 researches involving digital games of entertainment were analyzed, using as basis Gardner’s theories of motivation in the teaching, games and the active learner of Gee, zone of proximal development of Vygotsky, tangential learning model of Portnow and Brown, model of the monitor, Krashen’s input hypothesis, Schumann’s acculturation model, and the hypothesis of the interaction proposed by several authors such as Gass and Larsen-Freeman and Long. The results obtained were the definition of the relevant characteristics to teaching and learning in games and the identification of the genres associated to these characteristics. The discussion used the following characteristics found in the analyzed texts: motivation, classroom interaction, social interaction in the game, tangential learning, grades, complementary material, vocabulary, repetitive written content, big written content, need for text interpretation, audio and text.
Sum-rate optimized power allocation for the OFDM multiple access relay channel

We1 consider transmission over a set of parallel MARCs (multiple-access relay channel) based on the OFDM (Orthogonal Frequency Division Multiplexing) modulation. Two users communicate to a common destination (D) with the help of a relay (R) over a set of parallel channels. The relay operates in decode and forward (repetition coding type) and half duplex modes. The problem considered is the maximization of the total sum rate at the destination by optimal allocation of the power to the different carriers for the users and the relay. The problem is investigated for a sum power constraint. We show that for each carrier only one user should be relayed at most, and the other user should communicate over the direct link. Unlike the classical MAC, we show that there exist cases where both users should share the same carrier to transmit symbols and this increases the rate. For these carriers, there exist, considering both the relay and the destination, four possible decoding orders. As the problem is non-convex and non-linear, it is not easy to a-priori select the best decoding order (at the relay and the destination), and which user should be relayed. An algorithm is proposed to solve the global optimization problem. The theoretical results are illustrated by computational results.
A Bayesian approach to conceptualization using reinforcement learning

Abstraction provides cognition economy and generalization skill in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction which maps the continuous state and action spaces into entities called concepts. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the Bayesian framework is proposed. This approach exploits and extends the mirror neuron's role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, an agent sequentially learns the concepts from both of its successes and its failures through interaction with the environment. These characteristics as a whole distinguish the proposed learning algorithm from positive sample learning. Simulation results show the correct formation of concepts' distributions in perceptual space in addition to benefits of utilizing both successes and failures in terms of convergence speed as well as asymptotic behavior. Experimental results, on the other hand, show the applicability and effectiveness of our method for a real robotic task such as wall-following.
Transient Congestion Avoidance in Software Distributed Shared Memory Systems

OpenMP applications executed on top of software distributed shared memory (SDSM) systems show peaks in network traffic. In these scenarios, synchronization points are used to maintain memory consistency and improve performance, and network traffic is highly increased due to data being exchanged between different nodes in the system. This behaviour generates network congestion which may limit or degrade applications performance. In this paper we present a technique to avoid these peaks by sending data producing the congestion earlier in time. Our proposal is to introduce virtual synchronization points between the real ones, and use them to automatically distribute the network traffic. This technique is evaluated with a synthetic benchmark, and with the classes A and B of two OpenMP codes from the NAS benchmarks (BT and CG), on top of NanosDSM, a page-based DSM implementing sequential consistency. The results show a16% performance improvement on average over the traditional methods.
Rationality and Rationalistic Choice in the California Recall

The California recall election of 2003 provides an excellent setting for investigating voter rationality and certain forms of sophisticated voting. In a pre-election telephone survey, 1,500 registered voters were asked to make pairwise comparisons between the major candidates, and their responses were combined to infer preferences. Individuals' preference orderings over the major candidates rarely exhibited intransitivity. The patterns of tactical voting observed in the replacement part of the recall election were consistent with the declining rate hypothesis. Voters also engaged in 'hedge voting' on the recall question itself. The results suggest that voters' decisions are 'rationalistic': while voters are consistent in forming utility-based preference rankings and choosing on that basis, their voting strategies do not incorporate probability assessments in a realistic, consistent fashion, if at all.
Context-Driven Resource Over-Provisioning Approach for Rich Networking

Mobile users are increasingly demanding multimedia content created specifically or at least tailored to cater for their needs and preferences. The limitations of current Internet challenge a lot the design of such sessions, and require embedding innovations beyond standards to achieve rich networking. In this scope, the Context Casting (C-CAST) project designed a context-sensitive network architecture to support value-added multimedia sessions with Quality of Service (QoS) guaranteed towards multiple users simultaneously, and in their wireless technologies. However, the per-flow driven signalling approach of Legacy C-CAST exponentially increases with the number of flow admissions, which jeopardize the system performance. Thus, this paper proposes the Advanced C-CAST, which re-architects the Legacy C-CAST to support context-driven over-provisioning of per-class bandwidth and overlay trees. The evaluation of Advanced C-CAST demonstrated its benefits against Legacy C-CAST by significantly optimizing overall signalling load and latency experience.
Joint Argument Inference in Chinese Event Extraction with Argument Consistency and Event Relevance

Event extraction in Chinese suffers greatly from the frequent missing of arguments. Statistical analysis of the automatic content extraction (ACE) 2005 Chinese corpus shows that nearly 55% of arguments do not occur in their corresponding event mentions. This problem greatly hinders the wide deployment of event extraction in real applications. This paper proposes a novel joint argument inference model to recover those missing arguments in event mentions from a semantic perspective. In particular, this model employs various types of argument consistencies to reveal intra-event argument semantics in multiple dimensions, such as argument-argument, argument-role and argument-trigger. Moreover, this model explores several linguistic-driven event relevance phenomena, such as Coreference, Sequence, and Parallel, to unveil inter-event argument semantics in various layers, such as sentence, discourse, and document. An evaluation of the ACE 2005 Chinese corpus justifies the effectiveness of our joint argument inference model compared to a state-of-the-art baseline.
Src kinase‐mediated signaling in leukocytes

A concert of antigens, antibodies, cytokines, adhesion molecules, lipid factors, and their different receptors mediate leukocyte development and inflammatory responses. Regardless of the stimulus and receptor type, members of the Src family of protein tyrosine kinases (PTKs) play a critical role in initiating the numerous intracellular signaling pathways. Recruited and activated by the receptor, these Src PTKs amplify and diversify the signal. Multiple pathways arise, which affect cell migration, adhesion, phagocytosis, cell cycle, and cell survival. Essential nonredundant properties of Src PTKs have been identified through the use of gene targeting in mice or in the somatic cell line DT40. Because of their role in mediating leukocyte proliferation and activation, Src PTKs serve as excellent drug targets. Inhibitors of Src family members and dependent pathways may be useful in the treatment of human diseases similar to drugs known to inhibit other signal transduction pathways.
The Material Well-Being of the Poor and the Middle Class since 1980

*This paper was prepared for the American Enterprise Institute monograph series on Prosperity and Economic Inequality. We would like to thank Steve Davis and seminar participants at the American Enterprise Institute, the Centre for Microdata Methods and Practice Workshop on Measuring Material Well-Being, and the Wharton School for their comments and Charlie Jiang and Julieta Yung for excellent research assistance.
The influence of nonrandom extra‐pair paternity on heritability estimates derived from wild pedigrees

Quantitative genetic analysis is often fundamental for understanding evolutionary processes in wild populations. Avian populations provide a model system due to the relative ease of inferring relatedness among individuals through observation. However, extra‐pair paternity (EPP) creates erroneous links within the social pedigree. Previous work has suggested this causes minor underestimation of heritability if paternal misassignment is random and hence not influenced by the trait being studied. Nevertheless, much literature suggests numerous traits are associated with EPP and the accuracy of heritability estimates for such traits remains unexplored. We show analytically how nonrandom pedigree errors can influence heritability estimates. Then, combining empirical data from a large great tit (Parus major) pedigree with simulations, we assess how heritability estimates derived from social pedigrees change depending on the mode of the relationship between EPP and the focal trait. We show that the magnitude of the underestimation is typically small (<15%). Hence, our analyses suggest that quantitative genetic inference from pedigrees derived from observations of social relationships is relatively robust; our approach also provides a widely applicable method for assessing the consequences of nonrandom EPP.
A Proposal of Privacy-Preserving Data Aggregation on the Cloud Computing

In recent years, the evolution of the cloud computing increases the demand of the services which provides profitable information analyzed from huge data from heterogeneous information sources. In order to reduce the user's anxiety to store the private and confidential information in the cloud, various Privacy Preserving Data Mining (PPDM) techniques are developed, which enable the cloud to perform data mining from secured data. In this paper, we propose a PPDM technique specialized in data aggregation that satisfies following two requirements: (1)The information stored in the cloud is guaranteed against information leakage, because no profitable information is obtained from the secured data without the users' secret information, which is not stored in the cloud. (2)The cloud provides multi-level granularity of the aggregation results according to the user's authority.
Design, Implementation, and Performance of the V2 Temporal Document Database System

The advent of large amounts of data on the web has closed the gap between the document storage and the database communities. In this paper, this work is continued by the description of the foundations for temporal document databases. We describe functionality and operations/operators to be supported by such systems, and more specifically we describe the architecture for management of temporal documents used in the prototype of the V2 temporal document database system, which supports storage, retrieval, and querying of temporal documents. We also give some performance results from a mini-benchmark run on the V2 prototype.
Can Bank Supervisors Rely on Market Data ? A Critical Assessment from a Swiss Perspective

Banking supervision has become more difficult in the course of internationalization, financial innovation and concentration in the banking industry. Particularly the bigger, internationally active banks are financially, legally, and organizationally complex institutions. Timely identification of problems at individual banks and of disequilibria building up in the banking system has become a daunting task. A crucial factor in these developments is the market. Markets play an ambiguous role. On the one hand, financial markets are a driving force behind the increasing complexity of banks: They offer an unprecedented choice of sophisticated instruments to manage, diversify, but also to conceal risks. On the other hand, markets may facilitate the tasks of supervisors in two ways. First, markets exert direct market discipline: Risky banks may find it difficult or expensive to refinance. Second, for bank supervisors market data may be a source of indirect discipline: The terms at which banks borrow may reveal to supervisors valuable information on investors’ perception of bank quality. Indeed, it is well known that markets process and aggregate information available to investors. H (1945), in his classic article, defines a society’s main