Miracle-dz/UniFAR-FTUs huggingface dataset:
An evolutionary central pattern generator for stable bipedal walking by the increased double support time

Central pattern generator (CPG) consisting of neural oscillators, generates rhythmic signals using simple input signal. It can modify motor patterns to handle environmental perturbations by sensory feedback. In this paper, an evolutionary CPG for stable bipedal walking by the increased double support time is proposed. The proposed CPG generates swing motion of arms as well as ankle and the center of pelvis (COP) motions in Cartesian coordinate system. Sensory feedback pathways in the proposed CPG use force sensing resistor (FSR) signals. The sensory feedback maintains humanoid robot's balance and prevents it from falling down to the ground. To optimize the parameters of the proposed CPG, evolutionary algorithm is employed. The effectiveness of the scheme is demonstrated by simulations with the Webot model of a small-sized humanoid robot, HSR-IX, developed in the RIT Lab. , KAIST.
Ncode: an Open Source Bilingual N-gram SMT Toolkit

Ncode: an Open Source Bilingual N-gram SMT Toolkit This paper describes Ncode, an open source statistical machine translation (SMT) toolkit for translation models estimated as n-gram language models of bilingual units (tuples). This toolkit includes tools for extracting tuples, estimating models and performing translation. It can be easily coupled to several other open source toolkits to yield a complete SMT pipeline. In this article, we review the main features of the toolkit and explain how to build a translation engine with Ncode. We also report a short comparison with the widely known Moses system. Results show that Ncode outperforms Moses in terms of memory requirements and translation speed. Ncode also achieves slightly higher accuracy results.
Depth functions based on a number of observations of a random vector

We present two statistical depth functions given in terms of the random variable defined as the minimum number of observations of a random vector that are needed to include a fixed given point in their convex hull. This random variable measures the degree of outlyingness of a point with respect to a probability distribution. We take advantage of this in order to define the new depth functions. Further, a technique to compute the probability that a point is included in the convex hull of a given number of i.i. d. random vectors is presented. Consider the sequence of random sets whose n-th element is the convex hull of $n$ independent copies of a random vector. Their sequence of selection expectations is nested and we derive a depth function from it. The relation of this depth function with the linear convex stochastic order is investigated and a multivariate extension of the Gini mean difference is defined in terms of the selection expectation of the convex hull of two independent copies of a random vector.
Fabrication and Characterization of Polysaccharide Ion Gels with Ionic Liquids and Their Further Conversion into Value-Added Sustainable Materials

A review of the fabrication of polysaccharide ion gels with ionic liquids is presented. From various polysaccharides, the corresponding ion gels were fabricated through the dissolution with ionic liquids. As ionic liquids, in the most cases, 1-butyl-3-methylimidazolium chloride has been used, whereas 1-allyl-3methylimidazolium acetate was specifically used for chitin. The resulting ion gels have been characterized by suitable analytical measurements. Characterization of a pregel state by viscoelastic measurement provided the molecular weight information. Furthermore, the polysaccharide ion gels have been converted into value-added sustainable materials by appropriate procedures, such as exchange with other disperse media and regeneration.
Adaptive Algorithms for Neural Network Supervised Learning: a Deterministic Optimization Approach

Networks of neurons can perform computations that even modern computers find very difficult to simulate. Most of the existing artificial neurons and artificial neural networks are considered biologically unrealistic, nevertheless the practical success of the backpropagation algorithm and the powerful capabilities of feedforward neural networks have made neural computing very popular in several application areas. A challenging issue in this context is learning internal representations by adjusting the weights of the network connections. To this end, several first-order and second-order algorithms have been proposed in the literature. This paper provides an overview of approaches to backpropagation training, emphazing on first-order adaptive learning algorithms that build on the theory of nonlinear optimization, and proposes a framework for their analysis in the context of deterministic optimization.
Linear embedding of binary hierarchies and its applications

The discrete binary hierarchy (DBH) is a concept underlyingmany important issues in analysis of complex systems: knowledge structures, testand-search organization, evolutionary trees, taxonomy, data handling, etc. It appears that any DBH corresponds to an orthonormal basis of the Euclidean space related to the hierarchy leaves. The properties of these bases form a mathematical framework which can be applied to such problems as clustering and multiresolution image/signal processing. Clustering applications are based on a DBH-based analogue of the singular-value-decomposition of data matrices. A theoretical support for a method in divisive clustering is provided along with some decomposition-based interpretation aids. Data processing applications appear parallel to those involving the concepts of wavelets and quadtrees. However, DBH-based techniques seem to offer some potential improvements based on relaxing “continuity and homogeneity” restrictions of classical theories.
Série Scientifique Scientific Series the Survival and Success of Canadian Penny Stock Ipos the Survival and Success of Canadian Penny Stock Ipos

(Ce document est une mise à jour du cahier scientifique 2007s-28 paru en novembre 2007 sous le titre « The Survival and Success of Penny Stock IPOs: Canadian Evidence » CIRANO Le CIRANO est un organisme sans but lucratif constitué en vertu de la Loi des compagnies du Québec. Le financement de son infrastructure et de ses activités de recherche provient des cotisations de ses organisations-membres, d'une subvention d'infrastructure du Ministère du Développement économique et régional et de la Recherche, de même que des subventions et mandats obtenus par ses équipes de recherche. CIRANO is a private non-profit organization incorporated under the Québec Companies Act. Its infrastructure and research activities are funded through fees paid by member organizations, an infrastructure grant from the Ministère du Développement économique et régional et de la Recherche, and grants and research mandates obtained by its research teams. Le CIRANO collabore avec de nombreux centres et chaires de recherche universitaires dont on peut consulter la liste sur son site web. Les cahiers de la série scientifique (CS) visent à rendre accessibles des résultats de recherche effectuée au CIRANO afin de susciter échanges et commentaires. Ces cahiers sont écrits dans le style des publications scientifiques. Les idées et les opinions émises sont sous l'unique responsabilité des auteurs et ne représentent pas nécessairement les positions du CIRANO ou de ses partenaires. This paper presents research carried out at CIRANO and aims at encouraging discussion and comment. The observations and viewpoints expressed are the sole responsibility of the authors. They do not necessarily represent positions of CIRANO or its partners. Mots clés : Financement des petites entreprises, émissions initiales d'actions, survie, succès, normes minimales d'entrée en Bourse. We analyze the survival and success of a large sample of Canadian penny stock initial public offerings (IPOs), launched mostly by small and unprofitable firms from 1986 to 2003. The failure rate of these IPOs is lower than the one observed in the U.S. for larger IPOs, probably because of lax delisting rules and the market's capacity to refinance non-profitable firms. The survival of new issuers is significantly associated with their characteristics at the IPO and with the level of initial listing requirement they meet. The involvement of reputable intermediaries in the IPO process mitigates this effect. Success, estimated by the graduation to a senior exchange, is not linked to the financial conditions at the IPO. Overall, Canada seems to have …
Analyses of Characteristics of U-Healthcare System Based on Wireless Communication

The medical industries are integrated with information technology with mobile devices and wireless communication. The advent of mobile healthcare systems can benefit patients and hospitals, by not only providing better quality of patient care, but also by reducing administrative and medical costs for both patients and hospitals. Security issues present an interesting research topic in wireless and pervasive healthcare networks. As information technology is developed, many organizations such as government agencies, public institutions, and corporations have employed an information system to enhance the efficiency of their work processes. For the past few years, healthcare organizations throughout the world have been adopting health information systems (HIS) based on the wireless network infrastructure. As a part of the wireless network, a mobile agent has been employed at a large scale in hospitals due to its outstanding mobility. Several vulnerabilities and security requirements related to mobile devices should be considered in implementing mobile services in the hospital environment. Secure authentication and protocols with a mobile agent for applying ubiquitous sensor networks in a healthcare system environment is proposed and analyzed in this paper.
Lessons Learned in Health Care Research: Four IS Case Studies

Much attention has been paid recently to the need for information systems research in healthcare. Premiere IS journals have called for research addressing the interoperability, implementation, adoption, diffusion and clinical data standards needs of our ailing US health care system. Because of the IS community has much to offer the unique healthcare environment, collaborative research is a necessity; however the dynamic and often times guarded nature of health care organizations make conducting theoretical and applied research a complicated and slow-going process; yet always rewarding. The Purpose of this research report is threefold: (1) to provide an overview of current and ongoing information systems research in health care; (2) to present case examples from a variety of health care and IS research that demonstrate diverse methods, approaches and objectives for conducting IS research in the health care environment; and (3) to present challenges and lessons learned from these four care research cases.
Scalability bottlenecks discovery in MPSoC platforms using data mining on simulation traces

Nowadays, a challenge faced by many developers is the profiling of parallel applications so that they can scale over more and more cores. This is especially critical for embedded systems powered by Multi-Processor System-on-Chip (MPSoC), where ever demanding applications have to run smoothly on numerous cores, each with modest power budget. The reasons for the lack of scalability of parallel applications are numerous, and it can be time consuming for a developer to pinpoint the correct one. In this paper, we propose a fully automatic method which detects the instructions of the code which lead to a lack of scalability. The method is based on data mining techniques exploiting low level execution traces produced by MPSoC simulators. Our experiments show the accuracy of the proposed technique on five different kinds of applications, and how the information reported can be exploited by application developers.
Mining Named Entity Translation from Non Parallel Corpora

In this paper, we address the problem of mining named entity translation such as names of persons, organizations, and locations, from non parallel corpora. First, our study concentrates of different forms of named entity translation. Then, we introduce a new framework to extract all named entity translation types from a non parallel corpus. The proposed framework combines surface and linguistic-based approaches. It is language independent and do not rely on any external parallel resources such as bilingual lexicons or parallel corpora. Evaluations show that our approach for mining named entity translations from a non parallel corpus is highly effective and consistently improves the translation quality of Arabic to French machine translation system.
Multilevel preconditioners for solving eigenvalue problems occuring in the design of resonant cavities

We investigate eigensolvers for computing a few of the smallest eigenvalues of a generalized eigenvalue problem resulting from the finite element discretization of the time independent Maxwell equation. Various multilevel preconditioners are employed to improve the convergence and memory consumption of the JacobiDavidson algorithm and of the locally optimal block preconditioned conjugate gradient (LOBPCG) method. We present numerical results of very large eigenvalue problems originating from the design of resonant cavities of particle accelerators.
On the construction of polar codes

We consider the problem of efficiently constructing polar codes over binary memoryless symmetric (BMS) channels. The complexity of designing polar codes via an exact evaluation of the polarized channels to find which ones are “good” appears to be exponential in the block length. In [3], Tal and Vardy show that if instead the evaluation if performed approximately, the construction has only linear complexity. In this paper, we follow this approach and present a framework where the algorithms of [3] and new related algorithms can be analyzed for complexity and accuracy. We provide numerical and analytical results on the efficiency of such algorithms, in particular we show that one can find all the “good” channels (except a vanishing fraction) with almost linear complexity in block-length (except a polylogarithmic factor).
Development and Validation of a Multi-Dimensional Leadership Style Questionnaire

This paper examined perception of boss leadership-behaviours among organizational workers in human service organizations in Nigeria. Employees’ perceptions constituted the central features of a model underlying the study, as they were believed to be related to the individual level of change outcomes. Data was collected from 504 middle management workers comprising of 285 males and 219 females from some selected human service private and public sector organizations in Lagos metropolis (Nigeria). The result of component factoring and the Varimax option of Kaiser Normalisation revealed that the respondents identified five dimensions of managerial leadership instead of two or three that was widely suggested by Fleishman’s Supervisory Behaviour Description Scale. Tests show that the instrument meets reliability standards. Keywords: Leadership behaviour: Interpersonal relations, Emancipatory, Autocratic, Productive, Patriotic
Efficient Methods for Conversion and Solution of Sparse Systems of Low-Degree Multivariate Polynomials over GF(2) via SAT-Solvers

The computational hardness of solving large systems of sparse and low-degree multivariate equations is a necessary condition for the security of most modern symmetric cryptographic schemes. Notably, most cryptosystems can be implemented with inexpensive hardware, and have a low gate counts, resulting in a sparse system of equations, which in turn renders such attacks feasible. On one hand, numerous recent papers on the XL algorithm and more sophisticated Grobner-bases techniques [5, 7, 13, 14] demonstrate that systems of equations are efficiently solvable when they are sufficiently overdetermined or have a hidden internal algebraic structure that implies the existence of some useful algebraic relations. On the other hand, most of this work, as well as most successful algebraic attacks, involve dense, not sparse systems, at least until linearization by XL or a similar algorithm. No polynomial-system-solving algorithm we are aware of, demonstrates that a significant benefit is obtained from the extreme sparsity of some systems of equations. In this paper, we study methods for efficiently converting systems of low-degree sparse multivariate equations into a conjunctive normal form satisfiability (CNF-SAT) problem, for which excellent heuristic algorithms have been developed in recent years. A direct application of this method gives very efficient results: we show that sparse multivariate quadratic systems (especially if over-defined) can be solved much faster than by exhaustive search if β ≤ 1/100. In particular, our method requires no additional memory beyond that required to store the problem, and so often terminates with an answer for problems that cause Magma and Singular to crash. On the other hand, if Magma or Singular do not crash, then they tend to be faster than our method, but this case includes only the smallest sample problems.
Subcellular Localization of Arabidopsis Pathogenesis-Related 1 (PR1) Protein

The Arabidopsis thaliana pathogenesis-related 1 (PR1) is an important defense protein, so far it has only been detected in extracellular space and its subcellular sorting and transport remain unexplained. Using a green fluorescent protein (GFP) tagged full length, as well as a C-terminus truncated version of PR1, we observed that when expressed ectopically in Nicotiana benthamiana leaves, PR1 co-localizes only partially with Golgi markers, and much more prominently with the late endosome (LE)/multivesicular body (MVB) FYVE marker. The C-truncated version PR1ΔC predominantly localized to the endoplasmic reticulum (ER). The same localizations were found for stable Arabidopsis transformants with expression of PR1 and PR1ΔC driven by the native promoter. We conclude that the A. thaliana PR1 (AtPR1) undergoes an unconventional secretion pathway, starting from the C-terminus-dependent sorting from the ER, and utilizing further transportation via phosphatidyl-inositol-3-phosphate (PI(3)P) positive LE/MVB-like vesicles. The homology model of the PR1 structure shows that the cluster of positively charged amino acid residues (arginines 60, 67, 137, and lysine 135) could indeed interact with negatively charged phospholipids of cellular membranes. It remains to be resolved whether Golgi and LE/MVB localization reflects an alternative sorting or trafficking succession, and what the role of lipid interactions in it will be.
Stability and stabilization of positive systems with delays

This paper addresses stability analysis and controller design for discrete-time positive systems with multiple delays. The control is under positivity constraint, which means that the resulting closed-loop systems are not only stable, but also positive. The contribution lies in two aspects. First, a set of necessary and sufficient stability conditions is established for delayed discrete-time positive systems. Second, several necessary and sufficient conditions are presented for the existence of controllers under the positivity constraint. All the controllers are explicitly constructed if existent, and all the results are formulated as linear programming or linear matrix inequality problems, hence easy to be verified.
Discipline in the Secondary Classroom: A Positive Approach to Behavior Management

The Author. Acknowledgments. How to Use This Book. Foreword by Donald D. Deshler. Preface. Introduction. Chapter 1: Vision: Understand Key Concepts About Managing Student Behavior. Chapter 2: Grading: Design Instruction and Evaluation Systems. Chapter 3: Organization: Prepare Routines and Procedures. Chapter 4: Expectations: Plan to Teach Students How to Be Successful. Chapter 5: Rules and Consequences: Plan to Respond Consistently to Student Misbehavior. Chapter 6: Motivation: Enhance Students' Desire to Succeed. Chapter 7: Preparation and Launch: Pull It All Together for the First Day. Chapter 8: Implementation: Monitor and Adjust Your Plan Throughout the Year. Chapter 9: Proactive Planning for Chronic Misbehavior. Appendix A: CHAMPs and ACHIEVE versus Daily Reality Rating Scales. Appendix B: Ratio of Interactions Monitoring Forms. Appendix C: Misbehavior Recording Sheet. Appendix D: Grade Book Analysis Worksheet. Appendix E: On-Task Behavior Observation Sheet. Appendix F: Opportunities to Respond Observation Sheet. Appendix G: Student Satisfaction Survey. References. Index.
Emotional experience and perception in the absence of facial feedback

The facial feedback hypothesis suggests that facial expressions are either necessary or sufficient to produce emotional experience. Researchers have noted that the ideal test of the necessity aspect of this hypothesis would be an evaluation of emotional experience in a patient suffering from a bilateral facial paralysis; however, this condition is rare and no such report has been documented. We examined the role of facial expressions in the determination of emotion by studying a patient (F.P.) suffering from a bilateral facial paralysis. Despite her inability to convey emotions through facial expressions, F.P. reported normal emotional experience. When F.P. viewed emotionally evocative slides her reactions were not dampened relative to the normative sample. F.P. retained her ability to detect, discriminate, and image emotional expressions. These findings are not consistent with theories stating that feedback from an active face is necessary to experience emotion, or to process emotional facial expressions. (JINS, 2002, 8, 130–135.)
A View to a Kill: WebView Exploitation

WebView is a technique to mingle web and native applications for mobile devices. The fact that its main incentive requires making data stored on, as well as the functionality of mobile devices, directly accessible to active web content, is not without consequences to security. In this paper, we present a threat scenario that targets WebView apps and show its practical applicability in a case study of selected apps. We further show results of our examination of over 287,000 apps in regard to WebView-related vulnerabilities.
Recommending Music to Groups in Fitness Classes

Research in the fitness domain proves that music has an important motivating effect on the athletes’ performance. This effect is even stronger when music is used in sport synchronously like, for instance, in fitness classes. Indoor cycling is one of these activities in which music is a key issue of success during the lesson, providing a high motivational mean for the instructor towards the classroom. In this paper we present the result of a study in which we tested a group recommender system aiming at supporting the instructor music choice when preparing the lesson. This is done aggregating data present in the individual profiles of each user in the class that are built by combining explicit and implicit gathering of information about their music tastes. In order to refine the profiling process, users may express their feedback on the proposed music tracks after the workout, thus improving the quality of the future music recommendations.
Race, Colour and the Processes of Racialization: New Perspectives from Group Analysis, Psychoanalysis and Sociology

Introduction. Rethinking Race. Psychoanalysis and Racism. Peeking into the Consulting Room. Other Psychoanalytic Theories of Racism. Fanon: The Colonial Context. Foulkesian Group Analysis. Power: The Generator of Difference. Black and White. Categorization: The Vicissitudes of Difference. Racism: The Vicissitudes of Racialized Differences.