Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating natural language and program structure information to improve software search and exploration

Today's software is large and complex, with systems consisting of millions of lines of code. New developers to a software project face significant challenges in locating code related to their maintenance tasks of fixing bugs or adding new features. Developers can simply be assigned a bug and told to fix it—even when they have no idea where to begin. In fact, research has shown that a developer typically spends more time locating and understanding code during maintenance than modifying it. We can significantly reduce the cost of software maintenance by reducing the time and effort to find and understand the code relevant to a software maintenance task. In this dissertation, we demonstrate how textual and structural information in source code can be used to improve software search and exploration tools. To facilitate integration of this information into additional software tools, we present a novel model of word usage in software. This model provides software engineering tool designers access to both structural and linguistic information about the source code, where previously only structural information was available. We utilize textual and structural information to improve software search and program exploration tools, and evaluate against competing state of the art approaches. Our evaluations show that combining textual and structural information can outperform competing state of the art techniques. Finally, we outline uses of the model to improve software engineering tools beyond program search and exploration.
High level strategy to control the dynamic evolutions of bipedal postures

In this paper, we propose a high level control strategy of the dynamic evolutions of a biped robot called BIPMAN. For that, a multi-chain mechanical model of a human body is proposed with a general control architecture. Our approach is based on preliminary studies of the parameters influencing the dynamic behaviour of a mechanical model during free fall in the gravity field. This lead to a "reconfigurable" control strategy composed of three levels: the "supervisor" level, the "coordinator" level and the "legs and arms" level. The "coordinator" level and the "legs and arms" levels insure the dynamic stability of the "human" robot. According to changes of specific parameters, the "supervisor" level reactively determines the overall behaviour of the biped robot. In this article, we present behavioral rules, limiting conditions and "equilibrium classes" inferred from biomechanical studies which are involved in the design of the "supervisor" level.
Simulation and Gaming:Introduction to the Art and Science of Design

The main purpose of this special issue is to examine simulation/gaming as a transdisciplinary field of inquiry and practice from the perspective of the science of design. The principle of indeterminacy applied to the social and human realm stipu-lates that the only way we can know human reality is by engaging it. Gaming repre - sents a particularly powerful approach to engage people in shaping learning communities and in enhancing communities of practice. Principles and methods for designing gaming/simulations as such are well documented in the literature. In the 1970s and 1980s, the communities of gamers paid special attention to the methods and techniques of game design and model building. For example, the proceedings of the annual international conferences of the International Simulation and Gaming Association (ISAGA) of 1979 focused on “How to build a simulation/game” (Bruin, De Haan, Teijken, & Veeman, 1979). It is out of the scope of this special issue to discuss in detail the specifications of simulation/game design or to assess particular design methods. Focus is on the ramifications of simulation/game design and its effect on the broader social context of use. Simulation/game design does not happen in a social vacuum. It is part of a common understanding of associations such as ISAGA, North American Simulation and Gaming Association (NASAGA), Society for the Advancement of Games and Simulations in Education and Training (SAGSET), Association for Business Simulation and Experiential Learning (ABSEL), Japan Association of Simulation and Gaming (JASAG)
Artificial neural network for ECG arrhythmia monitoring

The application of a multilayer perceptron artificial neural network model to detect the QRS complex in the electrocardiographic (ECG) signal processing is presented. The objective is to improve the heart beat detection rate under the presence of severe background noise. An adaptively tuned multi-layer perceptron structure is used to model the nonlinear, time varying background noise. The noise is removed by subtracting the predicted noise from the original signal. Preliminary experiment results indicate that the artificial neural network (ANN)-based approach consistently out-performs the conventional bandpass filtering approach and the linear adaptive filtering approach. Such performance enhancement is critical in the development of a practical automated online ECG arrhythmia monitoring system. <<ETX>>
Scheduling partitioned algorithms on processor arrays with limited communication supports

It is important that array designs, especially the scheduling of partitioned arrays, must cope with various kinds of communication constraints such as interconnection topology, channel bandwidth, and inhomogeneous communication delay. The interprocessor communication requirements can be dictated by the dependence vectors and size of the partitioned tiles. A folded constraint graph is created to describe timing constraints between computation and communication events. An integer-programming based method can then be adopted to find an optimal execution schedule, including offset between the start times of processors, which satisfies these constraints. <<ETX>>
Pénalisation des mots fréquents pour la classification de sentiments

Nous abordons dans cet article le probleme de la classification de sentiments en utilisant des techniques d’apprentissage statistique supervise. Nous etudions differentes combinaisons de fonctions couts et de regularisations. Le principal probleme de la classification de sentiments par rapport a la classification thematique se trouve au niveau de l’extraction de caracteristiques discriminantes. Nous montrons dans cet article que la regularisation classique (L1 ou L2) selectionne des caracteristiques qui ne sont pas adaptees aux sentiments. Nous presentons une nouvelle methode de regularisation en penalisant les mots frequents : cette methode nous a permis d’obtenir de tres bons resultats en detection de sentiment ainsi qu’en classification multidomaine sur plusieurs jeux de donnees de reference. Nous fournissons des analyses detaillees des resultats et des interpretations des modeles appris.
Collaborative Interactivity and Integrated Thinking in Brazilian Business Schools Using Cognitive Flexibility Hypertexts: The Panteon Project

In this article, we discuss how the Harvard Method of case study, Interactive Communication Technologies, and Cognitive Flexibility Theory may contribute to case-based learning about business decision-making. In particular, we are interested in designing learning environments that foster critical thinking, creativity, and reasoning that entertains multiple hypotheses from multiple perspectives. We posit a framework for implementation and evaluation based upon Jonassen, Peck, and Wilson's “Meaningful Learning” model and Iowa's “Integrated Thinking Model. ” Based upon this framework, we describe the design and features of Panteon, a Web-based system for diagnosing complex business cases. We report the results of an evaluation of Panteon, utilizing focus group interviews, observations, and questionnaires to investigate participants' assessment of Panteon in comparison to the Harvard Case approach. Results indicate that both students and business experts favored Panteon for its affordances to stimulate higher order cognitive skills. The implications and limitations of the evaluation are discussed.
Rāga Recognition based on Pitch Distribution Methods

Abstract Rāga forms the melodic framework for most of the music of the Indian subcontinent. Thus automatic rāga recognition is a fundamental step in the computational modelling of the Indian art-music traditions. In this work, we investigate the properties of rāga and the natural processes by which people identify it. We bring together and discuss the previous computational approaches to rāga recognition correlating them with human techniques, in both Karṇāṭaka (south Indian) and Hindustānī (north Indian) music traditions. The approaches which are based on first-order pitch distributions are further evaluated on a large comprehensive dataset to understand their merits and limitations. We outline the possible short and mid-term future directions in this line of work.
FPGA-based real-time anisotropic diffusion filtering of 3D ultrasound images

Three-dimensional ultrasonic imaging, especially the emerging real-time version of it, is particularly valuable in medical applications such as echocardiography, obstetrics and surgical navigation. A known problem with ultrasound images is their high level of speckle noise. Anisotropic diffusion filtering has been shown to be effective in enhancing the visual quality of 3D ultrasound images and as preprocessing prior to advanced image processing. However, due to its arithmetic complexity and the sheer size of 3D ultrasound images, it is not possible to perform online, real-time anisotropic diffusion filtering using standard software implementations. We present an FPGA-based architecture that allows performing anisotropic diffusion filtering of 3D images at acquisition rates, thus enabling the use of this filtering technique in real-time applications, such as visualization, registration and volume rendering.
ARE OBSOLESCENCE AND SCATTERING RELATED

Considerable attention has been paid, in this journal and elsewhere, to each of two aspects of the use of literature. One of these is the relative decrease in use of material as it ages (‘obsolescence’) which has been discussed by Brookes and many others. The other aspect is the extent to which the use of material tends to be concentrated in a few titles (‘Bradford's Law of scattering’), which has been treated by Bradford, Leimkuhler, Brookes, and Fairthorne.
Introduction to Partial Least Square: Common Criteria and Practical Considerations

In the social science research area, there are two important statistical methodologies, one is covariance-based structural equation modeling (CBSEM), and the other one is variance-based partial least square (PLS). Compared with CBSEM, PLS lacks comparatively the reference books and full applications. The main purpose of this study is to develop a paradigm to demonstrate how to assess the reliability, convergent validity, discriminant validity, and path analysis in a proposed research model by using Smart PLS. We hope this study’s result can offer some correct steps when using PLS.
Forensic voice Comparison using likelihood ratios based on Polynomial curves fitted to the formant trajectories of Australian English

Earlier studies have indicated that information regarding speaker identity can be extracted from the dynamic spectral properties of diphthongs. It is widely accepted that likelihood ratios provide the logically and legally correct method for the evaluation of forensic evidence. Some studies have conducted likelihood-ratio analyses based on simple models of the dynamic formant properties of diphthongs (e.g., dual-target model), and others have used more sophisticated polynomial curve fitting models of the dynamic formant properties of diphthongs but have not conducted likelihood ratio analyses. The present study examines the strength of evidence which can be produced by a likelihood ratio analysis based on the coefficients of polynomial curves fitted to the formant trajectories of Australian English /aI/ tokens. A cubic polynomial model offers a substantial improvement over the dual-target model.
Systematic capacitance matching errors and corrective layout procedures

Precise capacitor ratios are employed in a variety of analog and mixed signal integrated circuits. The use of identical unit capacitors to form larger capacitances can easily produce 1% accuracy, but, in many cases, 0.1% accuracy can provide important performance advantages. Unfortunately, the ultimate matching precision of the ratio is limited by a number of systematic and random error sources. We have analyzed the source and significance of the systematic error sources on actual integrated circuit layouts and isolated five key contributors. Based on this analysis, we have developed a list of generic layout rules and a layout scheme that predict matching accuracies better than 0.1% for the individual systematic error sources using capacitor sizes in the range of 20-40 /spl mu/m. >
Computer networks in communication survey research

The paper explores the feasibility of using computer networks as communication survey research instruments. Also covered are the use of computers and computer networks in survey studies; a listing of the advantages and disadvantages of network surveys as compared with mail, phone, and fax surveys; a description of the development steps of network surveys; and a comparison of differences in network survey forms. Research issues are also discussed.
Abnormal Motion Detection for Intelligent Video Surveillance

A method of abnormal motion detection for intelligent video surveillance is presented, which includes object intrusion detection, object overlong stay detection and object overpopulation detection. Background subtraction algorithm is used to detect moving objects in video streams. Kalman filter is applied for object tracking. By the construction of relation matrix, the tracking process is divided into five statuses for prediction and estimation, which are object disappearing, object separating, new object appearing, object sheltering and object matching. The object parameters and predictive information in the next frame which is used to track moving objects is established by Kalman filter. Then, three types of abnormal motion detection are implemented. The relative position of alarm area or guard line with the rectangle boxes of the moving objects is used to detect whether the object is invading. The existing time of the moving objects in monitor area is counted to detect whether the object is staying too long. Moving objects in the monitor area are classified and counted to detect whether the objects are too much. Alarm will be triggered when abnormal motion detection as defined is detected in the monitor area.
High performance analog behavioral modeling of operational amplifiers

This paper presents a new method of operational amplifiers SPICE macromodeling, based on a frequency domain description of the input-output transfer functions. It accurately models the frequency variations of the open-loop gain, the common-mode rejection, and the input and output impedances, by a direct specification of their Laplace domain expressions with all theirs dominant poles and zeros. The temperature dependencies of the main opamp characteristics are also included. The proposed behavioral macromodel leads to a low analysis time in comparison with the other opamp methods of modeling, with a higher accuracy and a better convergence.
The Design of the Single-Phase Inverter Based on DSP (TMS320F2812)

This paper designs a single-phase inverter.Battery as a 12V DC input, and output for the 24V,50 HZ standard AC wave. The load is resistive.The power supply adopts the Boost booster and two full-bridge inverter transform. For the control circuit, the preceding Boost converter using tl494 chip control closed-loop feedback and for the inverter part, adopting the 6N137 to finish the optical coupling isolation.Then,through the DSP (TMS320F2812) to complete the output of SPWM modulation.And the modulated SPWM signal can drive chip IR211 conducting the full bridge inverter. Finally, through a low-pass filter output the standard sine AC inverter power.
Shaking video stabilization with content completion

A new stabilization algorithm to counterbalance the shaking motion in a video based on classical Kandade-Lucas- Tomasi (KLT) method is presented in this paper. Feature points are evaluated with law of large numbers and clustering algorithm to reduce the side effect of moving foreground. Analysis on the change of motion direction is also carried out to detect the existence of shaking. For video clips with detected shaking, an affine transformation is performed to warp the current frame to the reference one. In addition, the missing content of a frame during the stabilization is completed with optical flow analysis and mosaicking operation. Experiments on video clips demonstrate the effectiveness of the proposed algorithm.
Optimal Route Search in Mobile Ad-Hoc Network using Ant Colony Optimization

In Ad-Hoc networks the mobile nodes communicate with each other using multi-hop wireless links. The main drawback of such network is that there are no stationary infrastructures to route the packets. Hence, routing protocols have to adapt quickly and elegantly to frequent and unpredictable changes in network technology and they have to do so while conserving the memory, power and bandwidth resource. The Ant Colony Optimization technique implemented upon such networks have helped the nodes in finding the routes to different nodes in an optimized way same as ants find the optimum route to its food. The techniques provided so far have considered the search space utilized by a node as the space occupied by all the nodes that are present in the network which requires message passing among all the nodes that are present in the network consuming plenty of bandwidth and power only to find the routes to different nodes. If we divide the search space among the nodes forming clusters then the number of messages communicating will be reduced thereby reducing the bandwidth occupied and power consumed.
A Development of the Unified Object-Oriented Analysis and Design Methodology for Security-Critical Web Applications Based on Object-Relational Database - Forcusing on Oracle11g -

In the development process of application systems, the most important works are analysis and design. Most of the application systems are implemented on database system. So, database design is important. Also, IT System are confronted with more and more attacks by an increase interconnections between IT systems. Therefore security-related processes belong to a very important process. Security is a complex non-functional requirement that can interaction of many parts in the system. But Security is considered in the final stages of development. Therefore, Their increases the potential for the final product to contain vulnerabilities. Accordingly, Early in development related to security analysis and design process is very important. J2EE gives a solution based on RBAC((Role Based Access Control) for security and object-relational database also has RBAC for security. But there is not a object-oriented analysis and design methodology using RBAC of J2EE and object-relational database for security. In this paper, the unified object-oriented analysis and design methodology is developed for security-critical web application systems based on J2EE and object-relational database. We used UMLsec and RBAC of object-relational database and J2EE for this methodology.
Design and performance of high‐power 1.5 μm DFB lasers

A comprehensive design for high-power DFB lasers is discussed. An anti-reflection/high-reflection facet structure and optimized coupling between forward and backward propagation waves in continuous corrugation-type devices are shown in to be essential for this purpose. By applying the forementioned optimization to 1.5 μm DFB laser parameters, a maximum output power of 45 mW and a quantum efficiency of 37 percent are obtained at 20°C. The devices oscillate in a single-longitudinal-mode with a side-mode suppression ratio of more than 30 dB under 1 GHz sinusoidal modulation.
A multiple-sequence spread spectrum system for powerline communications

By using a multiple-sequence spread spectrum technique employing sequences generated by linear feedback shift registers, relatively high data rates over powerlines together with low error rates and robustness can be achieved. The method admits easy incorporation of a threshold decision scheme whereby erasures as well as errors are declared, enabling detection of poor channel conditions. By incorporating an informationless sequence of the same period in quadrature with the information-bearing sequence, carrier recovery, spreading sequence synchronization and block code synchronization can all be achieved jointly. Individual symbols can be detected using Hadamard Transforms, which can be efficiently implemented in either software or hardware. Also, the system is "downward compatible" with "conventional" direct sequence spread spectrum schemes in which a narrowband binary signal is mixed with an informationless linear spreading code.
Modern languages and Specific Learning Difficulties (SpLD): implications of teaching adult learners with dyslexia in distance learning

In modern language (ML) distance learning programmes, teachers and students use online tools to facilitate, reinforce and support independent learning. This makes it essential for teachers to develop pedagogical expertise in using online communication tools to perform their role. Teachers frequently raise questions of how best to support the needs of their diverse groups of adult language learners. This is particularly relevant in the case of modern language students with learning difficulties, including dyslexia, whose previous experiences of language learning can sometimes be negative and frustrating. This case study relates to a staff development project which took place between December 2012 and June 2013 at the Department of Languages in the Open University, UK, and involved 12 ML teachers across a range of languages and levels. In the Dyslexia and Modern Language Learning project, teachers worked and learnt together to: (1) develop understanding of key issues in relation to ML learning and dyslexia, (2) share good practice and experiences through reflection and collaboration, (3) find effective methods and strategies to support adult ML learners with dyslexia and (4) facilitate the joint design of learning resources for the online environment. The study presents the findings and the outcomes of the project, including the set of teaching and learning resources produced by the teachers as well as their recommendations on good practice. It also discusses the impact of the project on developing ML teachers’ attitudes and practices when supporting adult students with dyslexia.
Image retrieval and pattern recognition

In this work, we study the relationship between content- based image retrieval and pattern recognition, by modeling the image retrieval process in a probabilistic method. A model called random image database will be presented, together with a retrieval quality measure called probability of self similar, which enables us to establish the link between image retrieval and pattern recognition. The main result is that such a quality measure is uniformly upperbounded by its pattern recognition counterpart using nearest neighbor rule, when only one training sample is available for each class. Therefore a feature measure having better performance in the one training sample per class case should be favored over features doing well in large training sample situations.