Miracle-dz/UniFAR-FTUs huggingface dataset:
Pronunciation Fundamentals: Evidence-based perspectives for L2 teaching and research

1. Foreword 2. Acknowledgements 3. Chapter 1. Key concepts 4. Chapter 2. Historical overview of pronunciation 5. Chapter 3. A pedagogical perspective on L2 phonetic acquisition 6. Chapter 4. Pronunciation errors and error gravity 7. Chapter 5. Pronunciation instruction research 8. Chapter 6. Assessment of L2 pronunciation 9. Chapter 7. Technology in L2 pronunciation instruction 10. Chapter 8. Social aspects of accent 11. Chapter 9. The ethics of second language accent reduction 12. Chapter 10. Future directions 13. Glossary 14. References 15. Subject Index 16. Author Index
PERFORMANCE EVALUATION OF CLASSIFICATION METHODS FOR HEART DISEASE DATASET

Classification techniques are greatly deployed in several application domains for the purpose of classification, estimation and prediction. This paper evaluates the performance of three basic classifiers (i.e., k-NN, Naive Bayesian and Decision Tree) for the highly sparse dataset (i.e., medical data), which has been acquired from online machine learning repositories. The goal of the study is to evaluate performance of three basic classifiers, since each classifier works at different learning mechanism and to predict possible treatment outcomes based on well-known patterns of the treatments. The experimental results reveal that k-NN classifier produces better prediction results as compared to other two classifiers for the considered heart disease dataset. Decision Tree classifier predicts poorly for the sparse dataset, specially, when dataset comprises of varying attribute values.
Esclerosis múltiple, calidad de vida y atención sociosanitaria

La esclerosis multiple es una enfermedad neurodegenerativa. Se caracteriza por presentar una gran variabilidad de sintomas y por evolucionar en forma de crisis o brotes. Historicamente se han observado divergencias en los datos sobre su prevalencia. Segun los datos manejados en este estudio, puede afirmarse que la prevalencia se da, al menos, en 78 casos por cada 100.000 habitantes para Navarra, y que alcanza los 144 casos en el conjunto del Estado espanol. Esas cifras revelan que los datos utilizados tradicionalmente estaban notablemente por debajo de las cifras reales. En la actualidad no existe ninguna respuesta curativa para la esclerosis multiple, pero si opciones terapeuticas paliativas que alivian su cronicidad. En ese sentido, y como en todas las enfermedades cronicas, la mejora de la calidad de vida es hoy en dia una cuestion de maxima importancia. La investigacion nos muestra mejoras significativas principalmente en aspectos medico-sanitarios, pero tambien revela debilidades en otras areas relacionadas con la autonomia y la movilidad de las personas afectadas, con su insercion en el ambito laboral, con sus relaciones sociales, con la necesidad de mejorar el apoyo a su entorno familiar o con la imagen social. En la esclerosis multiple emergen de manera simultanea necesidades sociales y sanitarias. En ese sentido, todo avance en el desarrollo de la atencion sociosanitaria sera positivo para las personas afectadas y para su entorno.
Comparison of spatio-temporal tracking methods for coronaries in DSA

Pattern recognition methods are applied to track a single coronary in its movement. The efficiency of several deformable models is tested in order to accurately locate the same vessel branch all over the digital subtraction angiography (DSA) imaging sequence by the use of a single projection view. Hereby, functional information, such as flow measurements, very helpful to coronary lesion diagnosis, could be provided. <<ETX>>
Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications

Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big concern. As the number of new Android applications tends to be rapidly increased in the near future, there is a need for automatic malware detection quickly and efficiently. In this paper, we define a simple static analysis approach to first extract the features of the android application based on intents and categories the application into a known major category and later on mapping it with the permissions requested by the application and also comparing it with the most obvious intents of category. As a result, getting to know which apps are using features which they are not supposed to use or they do not need.
The Phonology of German

In this book Richard Wiese provides the most complete and up-to-date description presently available of the phonology of German. Starting with a presentation of phonemes and their features, the author then describes in detail syllables, higher prosodic units, phonological conditions of word-formation, patterns of redundancy for features, phonological rules, and rules of stress for words and phrases. He lays particular emphasis on the interaction of morphology and phonology. He focuses on the present-day standard language, but includes occasional discussion of other variants and registers. The study is informed by recent models of phonological theory, and for phonologists and morphologists it provides both a rich source of material and critical discussion of current problems and solutions. It also serves as an introduction to the sound-system of German for the non-specialist reader. This book is intended for linguists, especially phonologists and morphologists; scholars and students of German.
Aggregate production planning in an imprecise environment through the goal programming and the satisfaction functions

This study proposes a general goal programming (GP) model to solve the aggregate production planning (APP) problem in an imprecise environment with multiple objectives. The goals and technological parameters are imprecise and expressed through intervals. The concept of satisfaction functions is utilised to integrate explicitly the decision maker‘s (DM) preferences. In order to verify our proposed model, a numerical example from literature is described. An experimental comparison demonstrates that our solution is better than those obtained by existing models.
Data visualization: the end of the rainbow

A rainbow colormap is often supplied as a default in visualization software. In this kind of colormap, red is mapped to the highest data value, blue to the lowest, and the other data values are interpolated along the full extent of the spectrum. But there is more to color than meets the eye. Color is a perceptual as well as physical phenomenon. What is commonly called color-hue-is only one of three parameters. Another is the brightness of the signal-intensity. The third is the admixture of white -saturation. Change any one parameter enough, and the color looks different. (The hue-intensity-saturation model of color is one of a several explored through the years, and captures some of the basic characteristics of basic color perception.) To make matters worse, the parameters' relationship to what is perceived is nonlinear. At the same intensity, for example, yellow appears brighter than blue. Some of the perceptual principles involved have been implemented in software developed at IBM Corp.'s Thomas J. Watson Research Center, Yorktown Heights, NY. The module runs with IBM's visualization package Data Explorer and is called Pravda (for perceptual rule based architecture for visualizing data accurately).
Computer Aided Performance Engineering: Current State of the Art. Addendum to Final Technical Report,

Abstract : This is an addendum to the Final Technical Report submitted as a result of Phase I SBIR work awarded to Infopike, Inc. This addendum reflects the work done by us in assessing the state of the art in the field of Computer Aided Performance Engineering. Performance evaluation of computer and software systems has become a rapidly growing field with a growing number of tools being developed for analyzing various performance aspects of such systems. The literature on performance evaluation methodologies has also mushroomed with various proposals from researchers all over the world. This addendum presents the results of a survey conducted on automated performance analysis tools for computer systems. The survey includes measurement-based tools, analytical tools, simulation tools and visualization tools, and describes their properties and capabilities. The tools have been categorized based on their analysis capabilities and include system-oriented, process-oriented and module-oriented categories. The tools surveyed in this paper incorporate various techniques including simulation, modeling (Petri net, queuing, semi-markov etc.), measurement, visualization and emulation. We also present a new methodology for tool classification that aids system designers.
Comparative Analysis of Advanced Encryption Standard, Blowfish and Rivest Cipher 4 Algorithms

Cryptography is one of the main categories of computer security that converts information from its normal form into an unreadable form. The two main characteristics that identify and differentiate one encryption algorithm from another are its ability to secure the protected data against attacks and its speed and efficiency in doing so.Cryptography is required to transmit confidential information over the network. It is also demanding in wide range of applications which includes mobile and networking applications. Cryptographic algorithms play a vital role in providing the data security against malicious attacks. But on the other hand, they consume significant amount of computing resources like CPU time, memory, encryption time etc. Normally, symmetric key algorithms are preferred over asymmetric key algorithms as they are very fast in nature. Symmetric algorithms are classified as block cipher and stream ciphers algorithms. In this research project, I comparedthe AES and Blowfish algorithms with different modes of operation (ECB, CBC, and CFB) and RC4 algorithm (stream cipher) in terms encryption time, decryption time, memory utilization and throughput at different settings likevariable key size and variable data packet size.A stimulation program is developed using PHP and JavaScript scripting languages. The program encrypts and decrypts different file sizes ranging from 1MB to 50MB. Firstly the user input 32 characters of key and 16 characters of Initialization Vector that would be used by the algorithm to encrypt and decrypt the message. After the key and Initialization vector are input, the user then use the browse button to select a file which has a size ranging from 1MB to 50 MB on the hard-drive. A prompt is displayed if the size of the file exceeds the specified range. The submit button is used by the user to initiate the process. A notification is displayed on the screen while the process is being executed. During the encryption and decryption process, the software automatically creates a file which copies the contents of the files being encrypted and decrypted into a folder on the user’s hard-drive. The stimulator analyzes and produces graphical representation of the results to the user.
Intuitive Bedienung laserbasierter Montageassistenz

Kurzfassung Unternehmen erwarten durch den Einsatz intuitiver Bedienkonzepte ökonomische, technische und nutzerorientierte Vorteile. Das Zentrum für Mechatronik und Automatisierungstechnik (ZeMA) und die LAP GmbH Laser Applikationen haben eine Studie zur Auswahl neuer Bedienkonzepte durchgeführt. In der Studie wurden die Effektivität, Effizienz und Nutzerfreundlichkeit der Bedienung laserbasierter Montageassistenzsysteme analysiert. Eine Smartwatch, ein Armband mit Gestensteuerung und eine Sprachsteuerung wurden mit einer Infrarot (IR)-Fernbedienung verglichen.
Composición de servicios: una aplicación de la web semántica y las técnicas de planificación automática

This article proposes applying semantic web and artificial intelligence planning techniques to a web services composition model dealing with problems of ambiguity in web service description and handling incomplete web information. The model uses an OWL-S services and implements a planning technique which handles open world semantics in its reasoning process to resolve these problems. This resulted in a web services composition system incorporating a module for interpreting OWL-S services and converting them into a planning problem in PDDL (a planning module handling incomplete information) and an execution service module concurrently interacting with the planner for executing each composition plan service.
Children with specific language impairment and their contribution to the study of language development*

ABSTRACT Children with specific language impairment (SLI) are distinguishable from typically developing children primarily in the pace and course of their language development. For this reason, they are appropriate candidates for inclusion in any theory of language acquisition. In this paper, the areas of overlap between children with SLI and those developing in typical fashion are discussed, along with how the joint study of these two populations can enhance our understanding of the language development process. In particular, evidence from children with SLI can provide important information concerning the role of language typology in language development, the optimal ages for acquiring particular linguistic details, the robustness of the bilingual advantage for children, the role of input in children's acquisition of grammatical details, the unintended influence of processing demands during language assessment, the contributions of treatment designs to the study of typically developing children, and the study of individual differences in language development.
A Survey Paper on Social Sign-On Protocol OAuth 2.0

This paper presents the amalgamation of different social sites and the concept of social sign-on. Latest Trends of using Facebook Platform, Google Friend Connect, Twitter etc have elevated the concept of social sign-on. These social-networks connect services increase access to and enrich user data in the Social Web, although they also present several security and privacy challenges. It enables a third-party application to obtain limited access to an HTTP service, either on behalf of a resource owner by orchestrating an approval interaction between the resource owner and the HTTP service, or by allowing the third-party application to obtain access on its own behalf. In this paper, we have presented the basic concept of the social sign-on protocol OAuth 2.0 and few challenges faced by this protocol.
COLLISION DETECTION FOR CLOTH SIMULATION USING BOUNDING SPHERE HIERARCHY

For the past 2-decades, the challenges of collision detection on cloth simulation have attracted numerous researchers. Simple mass spring model is used to model the cloth where the movement of the particles within the cloth was controlled by applying the Newton’s second law. After the modeling stage, implementation of the collision detection algorithm took place on cloth has been done. The collision detection technique used is bounding sphere hierarchy. Then, quad tree is being used to partitioning the bounding sphere and the collision search was based on the top-down approach. A prototype of the collision detection system is developed on cloth simulation and several experiments were conducted. Time taken for this system to be executed is around 235.258 milliseconds. Then the frame rate is at the average of 22 frames per second which is close to the real time system. Times taken for the collision detection system travels from root to nodes were 23 seconds. As a conclusion, the computational cost for bounding sphere hierarchy is much higher because the bounding sphere required more vertices for generation process, however the execution time for bounding sphere hierarchy is faster than the AABB hierarchy.
A Novel Coarse-to-fine Level Set Framework for Ultrasound Image Segmentation

Ultrasound image segmentation is a fundamental but undoubtedly challenging problem in many medical applications due to various unpleasant artifacts, e.g., noise, low contrast and intensity inhomogeneity. This paper presents a coarse-to-fine framework for ultrasound image segmentation based on a preprocessing step via speckle reducing anisotropic diffusion (SRAD) and a modified version of Chan-Vese model by proposing novel evolution functional involving the Sobolev gradient. SRAD is a diffusion method tailored for ultrasound image denoising, and is adopted here to construct a despeckled image which allows us to obtain a coarse segmentation of the input image by carrying out our proposed CV model. This coarse segmentation will be further used by our level set model as a constraint to guide the fine segmentation. We compare the proposed model with some famous region-based level set methods. Experimental results in both synthetic and clinical ultrasound images validate the high accuracy and robustness of our approach, indicating its potential for practical applications in ultrasound imaging.
A New Hybrid Approach for Modeling Accurate Fuzzy Rule Based Classification Systems

we propose in this article a new hybrid method for modeling accurate fuzzy rule based classication systems. The new method is a combination of manifold based data mapping method, a heuristic fuzzy rule based construction method and an evolutionary based rule weighting approach. Manifold based data mapping method considers the intricate geometric relationships that may exist among the data and computes a new representation of data that optimally preserves local neighborhood information in a certain sense. Although this new representation does not secure the interpret ability of obtained fuzzy models, the main intention of this research is to improve the classication accuracy signicantly. Experiments on some well-known datasets are performed to show the performance of the new proposed approach. Some nonparametric statistical tests are used to analysis the results obtained in experiments. Experimental results conrm the eectiveness of our proposed method in improvement of the classication accuracy.
An algorithm for parallel stereo matching based on dynamic programming

This paper proposes an algorithm for parallel stereo matching based on dynamic programming and presents a massively parallel implementation of this algorithm. Our implementation can use many processors per scanline, compared to a naive approach of one processor per scanline. This is important because typical images contain 256 to 1024 scanlines, while massively parallel machines can have many more processors. We also introduce a method of handing inter-scanline inconsistencies that is very well suited for parallel implementation. The method only increases the total amount of processing needed to solve the stereo matching problem by a small fraction. A parallel implementation of both the dynamic programming algorithm and the inter-scanline inconsistency correction algorithm are fully discussed.
Sistema de reconocimiento de emociones faciales

Actualmente existe la necesidad de ser capaces de clasificar las expresiones faciales de los humanos de manera automatica para realizar algun tipo de analisis. El proyecto esta dirigido al estudio e implementacion de un sistema de reconocimiento de emociones faciales, utilizando redes neuronales (Deep Learning). A lo largo de este trabajo se hace uso de seis datasets diferentes. El resultado demuestra que el modelo creado a partir de la union de los seis datasets obtiene mejores resultados que cualquiera de ellos por solitario.
Biologically motivated neural computing in early vision processing

We introduce a network of networks (NoN) model to solve image processing problems in early vision. The method is motivated by the fact that natural image formation is a local process, and thus processing can be accomplished by a globally coordinated, local parallel processing structure, readily implemented by the hierarchical cluster architecture of the NoN model. The modeling is very powerful in that it achieves high quality adaptive processing, and virtually eliminates the computational difference between inhomogeneous and homogeneous conditions. Computer simulations show that this method is able to provide fast, quality image processing in early vision.
Effects of substrate on phase-noise of bipolar voltage-controlled oscillators

So far, there have been many studies addressing the effects of the substrate on silicon-based integrated RF passive components, but none of them has addressed to what extent the substrate influences RF front-end circuits and phenomena, such as noise-figure and phase-noise. In particular, there are many different models of spiral inductors on silicon, and even more substrate models of such inductors, all claiming to be representative of their onchip counterparts. When subjected to verification in a circuit environment, for example in LC oscillators, those models often predict a dramatically different circuit performance in terms of phase-noise, voltage-swing, loop-gain and tuning-range, for a given power consumption. Therefore, this aspect of model verification is presented in this paper, showing that the design trajectory of LC-oscillators depends to an excessively large extent on the inductor models used in the analysis. Also, it is shown that the phase-noise of a quasi-tapped oscillator is, contrary to common belief, not a monotonic function of substrate resistivity.
Extraction of Brain Tumour in MRI Images using Marker Controlled Watershed Transform Technique in MATLAB

In recent years, substantial research has been carried out in the field of image processing to evaluate different structures and information from images. Image processing techniques have played a pivotal role in a wide range of medical image applications. They have been widely used to design different computational algorithms for extracting clinical information from medical images in different modalities including MRI, CT and Ultrasound. This paper aims to propose the use of image processing techniques in the medical ﬁeld. The objective of this paper is to develop a MATLAB based algorithm that can be used to extract a brain tumor from a MRI Image. In this research, we have performed some noise removal functions, segmentation techniques and morphological operations for detection and extraction which are the basic concepts of image processing. We have developed a Watershed Transform technique based on internal and external markers. The detection and extraction of tumor from MRI image of the brain is done by using MATLAB software.
Sensor-fusion of intensity- and laser range-images

The exploration of unknown environment is an important task for the new generation of mobile service robots. These robots are supposed to operate in dynamic and changing environments together with human beings and other static or moving objects. Sensors that are capable of providing the quality of information that is required for the described scenario are optical sensors like digital cameras and laser scanners. In this paper sensor integration and fusion for such sensors is described. Complementary sensor information is transformed into a common representation in order to achieve a cooperating sensor system. Sensor fusion is performed by matching the local perception of a laser scanner and a camera system with a global model that is being built up incrementally. The Mahalanobis distance is used as matching criterion and a Kalman filter is used to fuse matching features. A common representation including the uncertainty and the confidence is used for all scene features. The system's performance is demonstrated for the task of exploring an unknown environment and incrementally building up a geometrical model of it.