Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtual human modelling and animation for real-time sign language visualisation

This thesis investigates the modelling and animation of virtual humans for real-time sign language visualisation. Sign languages are fully developed natural languages used by Deaf communities all over the world. These languages are communicated in a visual-gestural modality by the use of manual and non-manual gestures and are completely different from spoken languages. Manual gestures include the use of hand shapes, hand movements, hand locations and orientations of the palm in space. Non-manual gestures include the use of facial expressions, eye-gazes, head and upper body movements. Both manual and nonmanual gestures must be performed for sign languages to be correctly understood and interpreted. To effectively visualise sign languages, a virtual human system must have models of adequate quality and be able to perform both manual and non-manual gesture animations in real-time. Our goal was to develop a methodology and establish an open framework by using various standards and open technologies to model and animate virtual humans of adequate quality to effectively visualise sign languages. This open framework is to be used in a Machine Translation system that translates from a verbal language such as English to any sign language. Standards and technologies we employed include H-Anim, MakeHuman, Blender, Python and SignWriting. We found it necessary to adapt and extend H-Anim to effectively visualise sign languages. The adaptations and extensions we made to H-Anim include imposing joint rotational limits, developing flexible hands and the addition of facial bones based on the MPEG-4 Facial Definition Parameters facial feature points for facial animation. By using these standards and technologies, we found that we could circumvent a few difficult problems, such as: modelling high quality virtual humans; adapting and extending H-Anim; creating a sign language animation action vocabulary; blending between animations in an action vocabulary; sharing animation action data between our virtual humans; and effectively visualising South African Sign Language.
A nonparametric statistical approach to breath segmentation

A nonparametric statistic is used to identify change-points along the respiratory waveform that correspond to shifts between inspiration and expiration, thereby segmenting the airflow waveform into discrete breaths. The nonparametric statistic used to segment the respiratory waveform is robust in the presence of wild-points, which makes it well suited for processing the often artifactual respiratory airflow waveform. This technique can be used to identify extremely shallow trends as long as the digitizing resolution is adequate to distinguish the sample magnitudes within the N-tuple. As a result, a wide range of breath magnitudes can be identified. Computationally, this technique requires only addition, subtraction, and a look-up table, so it can be implemented efficiently with a microprocessor. <<ETX>>
The Multicomputer Toolbox approach to concurrent BLAS and LACS

The authors describe many of the issues involved in general-purpose concurrent basic linear algebra subprograms (concurrent BLAS or CBLAS) and discuss data-distribution independence, while further generalizing data distributions. They comment on the utility of linear algebra communication subprograms (LACS). They also describe an algorithm for dense matrix-matrix multiplication and also discuss matrix-vector multiplication issues. With regard to communication, they conclude that there is limited leverage in LACS per se as a stand-alone message-passing standard, and propose that needed capabilities instead be integrated in a general, application-level message passing standard, focusing attention on CBLAS and large-scale application needs. Most of the proposed LACS features are similar to existing or needed general-purpose primitives anyway. All of the ideas discussed have been implemented or are under current development within the Multicomputer Toolbox open software system. <<ETX>>
Using Text-Analysis Computer Software and Thematic Analysis on the Same Qualitative Data: A Case Example

The acceptance and application of qualitative methods has been steadily increasing, and recent advances in computer analytic software programs have produced a rapidly evolving landscape of new methods and analytic tools. However, discussions regarding the use of these new computer-based methods alongside traditional qualitative methods remain sparse. The aim of this article is to present an example of using quantitative text analysis software, the Linguistic Inquiry and Word Count program, alongside a traditional qualitative method, thematic analysis. Data included 46 transcribed life-narratives shared by individuals with schizophrenia. We present findings from both analyses and offer an example of a method that combines these 2 approaches. Results and examples provided are discussed in light of the potential to strengthen analyses by using these methods collaboratively.
QUANTITATIVE COMPARISON OF METRICS FOR HUMAN POSE ESTIMATION

Human Pose Estimation is an important problem in computer vision that has received considerable attention in recent years. The multitude of applications related to Visual Surveillance, Human Computer Interaction and Activity Recognition often require the ability to estimate human pose. The ability to quantify the orientation of humans observed in images is a rather challenging problem attributed to variation in illumination, occlusions, and variations due to articulation of the human body. Many approaches to address this problem have been investigated, most of which rely on the use of 3D models and estimate the pose based on a model-fitting process. Such approaches are limited due to the assumptions of static and easily removable background, in addition to limited occlusion and variations in the articulations that can be incorporated in the 3D training dataset. Alternatively, approaches based on local image and shape features have also been proposed. In this thesis we consider pose estimation based on image features and provide a comparative evaluation to assess the utility of three common feature descriptors and three common classifiers. Image feature-based pose estimation involves a multi-step process including Feature Extraction, Feature Selection, and Classification. We investigate Histogram-based, GIST-based and SIFT-based feature extraction and representation algorithms. In the Feature Selection stage we reduce the dimensionality of the features using Information Gain and Principal Component Analysis. For classification we first discretize the pose estimation into 4 coarse orientations denoted by right-, left-, frontand back-facing. Classification is studied as both a hierarchical (two stage) solution and a direct estimation. In the hierarchical solution, we group frontand back-facing
Towards practical control design using neural computation

An effort is made to develop neural-network-based control design techniques which address the issue of performance/control trade-off. Additionally, the control design needs to address the important issue of achieving adequate performance in the presence of actuator nonlinearities such as position and rate limits. These issues are discussed using the example of aircraft flight control. Given a set of pilot input commands, a feedforward net is trained to control the vehicle within the constraints imposed by the actuators. This is achieved by minimizing an objective function which is a weighted sum of the tracking errors, control input rates, and control input deflections. A trade-off between tracking performance and control smoothness is obtained by varying, adaptively, the weights of the objective function. The neurocontroller performance is evaluated in the presence of actuator dynamics using a simulation of the vehicle. Appropriate selection of the different weighs in the objective function results in good tracking of the pilot commands and smooth neurocontrol. <<ETX>>
Quick Mapping Evaluator – application for ontology mapping evaluation: a case study on nuclear reactor domain

A comparative study of different string similarity metrics for ontology mapping using Quick Mapping Evaluator (QME) has been carried out. A Java Swing based GUI application, QME, has been developed. This QME is equipped with different algorithms like String Equality, Longest Common Subsequence and Levenshtein Distance for evaluation of the ontology matching at different thresholds in terms of precision, recall, Fmeasure metrics. As a case study the QME results for ontology matching between electrical power supply and distributed power system logics of the nuclear reactor are considered for validating the performance of the system. The evaluator is used as an add-on to the semantic web based knowledge management system for nuclear reactor domain under development.
A Combined Genetic Algorithms-local Search Engine (GAs–LCE) in Constrained Nonlinear Programming

Evolutionary optimization provides robust and efficient techniques for solving complex real-world problems. The aim of this paper is to present an enhanced evolutionary algorithm for solving constraint nonlinear programming problems NLPPs, which based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Our proposed approach is made of two phases, firstly, phase I is a classical genetic algorithm, which based on the ideas of repair strategy and coevolution. Secondly in phase II, Based on the k-means cluster algorithm, the search space is shrunk after phase I to the generated rectangular-atom with highly rate and concentrating the optimal solution region, so local search techniques will implemented in order to get more accurate optimal solution. Finally, the results of various experimental studies using a suite of benchmark functions have demonstrated the superiority of the proposed algorithm to finding the global optimal solution for constraint nonlinear programming problems. Original Research Article El-Qorashy et al.; BJAST, 8(3): 324-333, 2015; Article no.BJAST. 2015.210 325
Random Test Case Generation and Delta Debugging for Bit­Vector Logic with Arrays

Random test case generation paired with Delta Debugging provides the programmer with an efficient way of finding and fixing code defects during software development. In this work existing and new Delta Debugging algorithms are applied to BTOR files. BTOR is the input format of Boolector, an SMT solver for bit-vector logic with arrays. To improve the quality of Boolector we developed a random DAG (directed acyclic graph) generator for the BTOR format. When the generator finds a failure inducing input, this input can be minimized with little effort using one of our implemented Delta Debugging algorithms. The defect in the source code can then be located by using the small input file in a debugging session. The input file can be appended to the set of regression tests. This text describes a new algorithm for generating random DAGs. The algorithm has several input parameters. The most important one (maximum node count) affects the size of the generated files. In an experiment we varied this parameter to find out which setting must be used in order to find the highest portion of failure inducing inputs while spending as little running time as possible in the Boolector executable. In another experiment we show how tweaking the algorithm's parameters influences the running time of Boolector and the satisfiability of the resulting formulas. We show how existing Delta Debugging algorithms must be modified in order to be applied to BTOR files. After experimenting with the algorithms from the literature we discovered that an improvement is necessary that considers BTOR's specific DAG structure. We propose two new algorithms which handle cases better when failure inducing parts of the DAG are located in great depths and where the failure inducing part is very small compared to the entire size of the input file.
Analysis and two proposed design methodologies for optimizing power efficiency of a class D amplifier output stage

In this paper, we analyze the power dissipation mechanisms and derive the overall power efficiency of a Class D output stage realized using the finger and waffle layouts. We propose two design methodologies to determine the aspect ratios of the transistors in the output stage for optimum power efficiency: (i) optimization to a single modulation index point, and (ii) optimization to a range of modulation indices. For the design of an output stage with optimum power efficiency (and small IC area), we recommend the waffle layout realization optimized to a range of modulation indices. The theoretical analysis and derivations are verified on the basis of computer simulations and measurements on fabricated prototype ICs.
Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2012

Because of their unpredictable appearance and shape, segmenting brain tumors from multi-modal imaging data is one of the most challenging tasks in medical image analysis. Although many different segmentation strategies have been proposed in the literature, it is hard to compare existing methods because the validation datasets that are used differ widely in terms of input data (structural MR contrasts; perfusion or diffusion data; .), the type of lesion (primary or secondary tumors; solid or infiltratively growing), and the state of the disease (pre- or post-treatment). In order to gauge the current state-of-the-art in automated brain tumor segmentation and compare between different methods, we are organizing a Multimodal Brain Tumor Segmentation (BRATS) challenge that is held in conjunction with the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2012) on October 1st, 2012 in Nice, France.
A dynamic communication model for loosely coupled hybrid tracking systems

This paper proposes a TCP/IP based communication model for a dynamic self-configuring linkage of loosely coupled hybrid object tracking systems. The model combines existing concepts - as were implemented for Bluetooth or Jini - and expands them by additional mechanisms required for the calibration of real-time tracking systems. Using the proposed communication model it will be possible not only to integrate tracking systems dynamically into existing. sensor networks, but also to synchronize and calibrate: the sensors in time and space. After calibration the sensor network may serve as basis for further analysis or fusion tasks. To make it possible to support a wide range of tracking systems an XML schema is introduced, defining. the description of a sensor's features and performance.
A SAS® Macro for Automating the 'Change-In-Estimate' Strategy for Assessing Confounding

Although the “change-in-estimate” (CIE) strategy is conceptually more accurate than the “significance-test-of-the covariate” (STC) strategy for assessing confounding in the causal modeling of observational epidemiological data, the use of the CIE strategy is hampered by the cumbersome need for analysts to run an enormous amount of models. Indeed, assessing n covariates for potential confounding using the CIE strategy requires ((n)*(n+1)/2)+1) models. With 10 potential confounders, this translates to as many as 56 models. Automating the CIE strategy in SAS® will allow for a better assessment of confounding using this method. This paper introduces %backconf, a SAS® macro that automatically implements the CIE strategy using a backward elimination of covariates resulting in the least change of the estimate of the exposure variable. %Backconf incorporates the GENMOD procedure and easily accommodates different values allowed for by the class, where, link, dist, offset and weight statements. It can thus be used for Linear, Binomial, Logistic, or Poisson regression modeling amongst others. Furthermore, unlike existing software for implementing this approach, %backconf accommodates groups of variables to be considered as one entity (for example a variable and its higher quadratic or cubic terms) and covariates (such as matching variables) to be continually adjusted for in the model. Results of each step of the elimination of variables are summarized in a user-friendly and easily interpretable table at the end of the output. After reading this paper, SAS® users should be able to readily apply this macro to facilitate their analysis.
De-Identification in Learning Analytics

Learning Analytics has reserved its position as an important field in the educational sector. However, the large-scale collection, processing and analyzing of data have steered the wheel beyond the border lines and faced an abundance of ethical breaches and constraints. Revealing learners’ personal information and attitudes, as well as their activities, are major aspects that lead to personally identify individuals. Yet, de-identification can keep the process of Learning Analytics in progress while reducing the risk of inadvertent disclosure of learners’ identities. In this paper, the authors talk about de-identification methods in the context of learning environment and propose a first prototype conceptual approach that describes the combination of anonymization strategies and Learning Analytics techniques.
Towards a framework for co-creating Open Scholarship

A recent edition of ALT-J made a call for papers that looked at ‘theoretical approaches in digitally mediated environments’. A key part of this call was to use the Boyer Model of Scholarship as a frame of reference. The authors felt that there were limitations to this model which could be addressed in light of the recent moves to develop Open Scholarship. Our concern with Boyer is that he suggests a separation between researchers, who ‘build new knowledge through traditional research’ and teachers who ‘study teaching models and practices to achieve optimal learning’. Boyer identifies four ‘Types’ of Scholarship, those of Discovery, Integration, Application and Teaching (DIAT), but places the responsibility for ‘creative work in established field’, with the traditional researcher role (Discovery). Furthermore this model implies a linear flow concerning how new knowledge becomes a part of teaching, implying that the teaching is mostly instructional, with a limited view of how new and emerging pedagogies might be utilised. The Learner-Generated Contexts Research Group has been concerned to develop a co-creation approach to learning and find this separation curious. We argue that using the Pedagogy, Andragogy, Heutagogy (PAH) Continuum enables more flexible approaches, through a mix of PAH, allowing for a wide range of technology uses, which also changes the relationship to research. We look at how we might both apply a co-creation approach to Boyer’s model, inspired by the Open Scholar movement, and also make DIAT more iterative and less discrete. Consequently we have both extended Boyer’s DIAT system to include Co-creating as an additional type and changed some ‘measures of performance’ to enable an iterative process of scholarship to emerge which also involves learners. We also examine how network effects ‘enable generative network effects to occur’ on scholarship and how applying Epistemic Cognition to evolving subject frameworks might enable the co-creation of research agendas. The co-creation model of Open Scholarship is presented in a table designed to simulate debate on this subject. Keywords: open scholar; scholarship; research; co-creation; contexts; teaching; PAH Continuum; epistemic cognition; open education resources; OER; networked learning
Open Service Architecture in Agent-based P2P Environment

Put ting t he co ncept of Agent into P2 P service architect ure brings t he bet ter influence on agilit y and adapta2 bilit y for t he architect ure. Based o n t he dee p research of relative knowledge ,open service architect ure in Agent2based P2 P enviro nment ,named OSA2ABP ,was p ropo sed in t his paper . The architect ure was made up of five2layer model s and multi2agent interactive model . Compared wit h t he p resent model s ,t he architect ure has t he technical advantages of open2 ing ,Agent compatibilit y ,reso urce unified description and etc. Keywords P2 P ,Mo bile2Agent ,Web service ,Migration mechanism
On the visual span during object search in real-world scenes

The current study investigated from how large a region around their current point of gaze viewers can take in information when searching for objects in real-world scenes. Visual span size was estimated using the gaze-contingent moving window paradigm. Experiment 1 featured window radii measuring 1, 3, 4, 4.7, 5.4, and 6.1°. Experiment 2 featured six window radii measuring between 5 and 10°. Each scene occupied a 24.8 × 18.6° field of view. Inside the moving window, the scene was presented in high resolution. Outside the window, the scene image was low-pass filtered to impede the parsing of the scene into constituent objects. Visual span was defined as the window size at which object search times became indistinguishable from search times in the no-window control condition; this occurred with windows measuring 8° and larger. Notably, as long as central vision was fully available (window radii ≥ 5°), the distance traversed by the eyes through the scene to the search target was comparable to baseline performance. However, to move their eyes to the target, viewers made shorter saccades, requiring more fixations to cover the same image space, and thus more time. Moreover, a gaze-data based decomposition of search time revealed disruptions in specific subprocesses of search. In addition, nonlinear mixed models analyses demonstrated reliable individual differences in visual span size and parameters of the search time function.
Online interactive courseware: using movies to promote cultural understanding in a CALL environment

Student interest in films as a medium for ESL education is high. Interest, however, is not enough to foster understanding in a traditional classroom environment. A more hands-on interactive approach to studying a second language via film is needed. By using online interactive exercises to study the language and culture in film, students are able to gain a better understanding of the language used in the film. This paper outlines a course that was developed using online interactive exercises and film to study language and culture. The course incorporates several modern technologies to allow students to take an active role in their learning and to increase their skills in areas that the students perceive to be of value in the future, namely listening, reading, and presentation skills. Automated feedback functions let the students, as well as the instructors, constantly monitor their progress. These technologies allow a more efficient use of classroom time and permit the students to go into the content of the film – especially the cultural aspects – much more deeply. Through this course, students are able to boost their confidence and their motivation to continue the study of language and culture via films on their own
Transmission characteristics of MPEG2 encoded super high definition images

We have investigated super high definition (SHD) images supporting resolutions beyond 2048/spl times/2048 pixels/frame with 24-bit color separation at 60 frames/s for many professional applications of multimedia communications. However, 6 Gbps is needed to transmit moving SHD image sequences without any compression. This paper expands the MPEG2 standard from main profile at high level (MP@HL) to main profile at super high level (MP@SHL) to transmit SHD images via B-ISDN networks. The transmission of MPEG2 compressed SHD images over ATM networks is simulated. The strong burstiness of compressed SHD images is clarified and the transmission characteristics of these images over 155 Mbps and 600 Mbps ATM lines are determined.