Miracle-dz/UniFAR-FTUs huggingface dataset:
Study and Implementation of Morphology for Image Segmentation

The field of computer vision is concerned with extracting features and information from images in order to make analysis of images easier so that more and more information can be extracted. The task of image segmentation is a first step in many computer vision methods and serves to simplify the problem by grouping the pixels having similar attributes in the image. It is hard to clearly define image segmentation because there are many levels of detail in an image and therefore many possible ways of meaningfully grouping pixels i.e., various methods of image segmentation exist utilizing different image characteristics, e.g. shape, texture, motion, contrast, gray level etc. This thesis, presents a way to approach image segmentation of ultrasound images as well segmentation followed by counting of objects in images by using mathematical morphology, explain an efficient implementation for this approach, and show segmentation results using mathematical morphology.
Algorithm for joint decoding of turbo codes and M-ary orthogonal modulation

In this paper, we consider the concatenation of turbo codes and M-ary orthogonal modulation. A modified decoding algorithm that utilizes the correlated nature of an orthogonal symbol drawn from a Hadamard matrix and the soft-input/soft-output module of turbo codes is introduced. This improved decoding algorithm can significantly lower the error shoulder and reduce the SNR required for a given error probability.
Constructing Decision Trees for Mining High-speed Data Streams

Very fast decision tree is one of the most successful and prominent algorithms specifically designed for stream data classification. In this paper, we develop a new decision tree induction model CFDT (Clustering feature decision tree model), which is an extension to VFDT (Very fast decision tree). CFDT applies a micro-clustering algorithm that scans the data only once to provide the statistical summaries of the data for incremental decision tree induction. Moreover, micro-clusters also serve as classifiers in tree leaves to improve classification accuracy and reinforce any-time property. Our experiments on synthetic and real-world datasets show that CFDT is highly scalable for data streams while also generating high classification accuracy with high speed.
DYNAMIC POWER SUPPLY DESIGN FOR VARYING ENVELOPE SIGNALS USING ENVELOPE TRACKING

DYNAMIC POWER SUPPLY DESIGN FOR VARYING ENVELOPE SIGNALS USING ENVELOPE TRACKING METHOD Muhlis Kenan Özel M.S. in Electrical and Electronics Engineering Supervisor: Prof. Dr. Abdullah Atalar July 2012 In modern communication systems, demand for higher data-rate is consistently growing. Higher data-rate within a limited bandwidth tends to require more amplitude modulation (AM) to increase number of symbols per second. Amplitude modulated carriers should be amplified using linear power amplifiers (PAs). Although, linear PAs have good performance in terms of linearity, they are efficient only when they transmit at maximum power. However, modern communication signals have high peak-to-average-power ratio (PAPR), therefore probability of a PA transmitting at maximum power is low. As a conclusion, efficiencies are degraded to alarmingly low values and the problem translates to heat and shorter battery life issues. In this thesis, we investigate how dynamic power supplies (DPS) perform for non-constant envelope RF signals. We have designed a DPS and used it to test efficiency enhancement of two PAs compared to the same PAs operating with constant supply. Our aim was to obtain efficiency increase compared to constant supply case without introducing extra non-linearity. We have obtained satisfying results for both amplifiers.
Dynamic programming speech recognition using a context-free grammar

This paper deels with the use of context-free grammars in automatic speech recognition. A dynamic programming algorithm for recognizing and parsing spoken word strings of a context-free grammar is presented. The algorithm can be viewed as a probabilistic extension of the CYK algorithm along with the incorporation of the nonlineer time alignment. Details of the implementation and experimental tests are described.
Analysis of Users’ Behavior on Book Loan Log Based On Association Rule Mining

— This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, Apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.
Large vocabulary speech recognition using a hidden Markov model for acoustic/phonetic classification

Experiments with a speech recognition system are reported. The system comprises an acoustic/phonetic decoder, a lexical access mechanism and a syntax analyzer. The acoustic, phonetic and lexical processing are based on a continuously variable duration hidden Markov model (CVDHMM). The syntactic component is based on the Cocke-Kasami-Young (CKY) parser and a content-free covering grammar of English. Lexical items are represented in terms of the 43 phonetic units. In recognition tests conducted on a separate data set, a 70% correct recognition rate on phonetic units in fluent speech was observed. In two additional tests on isolated words, a 40% word recognition was observed with the complete 52000 word lexicon. When the vocabulary size was reduced to 1040 words, the recognition rate improved to 80%. After syntax analysis the word recognition rate rose to 90%. <<ETX>>
An Application of Bitwise-Based Indexing to Web Service Composition and Verification

Nowadays, advent of web service is considered as a technology bringing a revolution operations of online B2B (Business to Business) and B2C (Business to Customer) applications. However, the user requirement for web services is diverse and complex. In most cases, a simple web service cannot meet the user requirement. Therefore, the composition of web services (or Web Service Composition - WSC) is set out as an indispensable. When the number of web services in repository increase, the computational cost of composition problem also increases significantly. The performance of composition process depends on the way we organize web services in the repository. Indexing is a technique of data mining field which can help us organize the web services and retrieve them optimally. In this paper, we proposed a bitwise-based indexing mechanism for fast location of suitable web services. This approach is implemented and proved its effectiveness over the real datasets with thousands of web services. As a result, significant improvement of performance has been made, especially as compared to other existing works in the same field.
Probability and Statistics in the Core Curriculum

Mathematics is distinguished from most other sciences by a lack of consensus on the content of an introductory overview for potential majors and other serious students. Chemists offer Chemistry 101–102, typically an introduction to the major branches of chemistry. We traditionally offer a year of calculus, followed in the second year by more calculus and perhaps some differential equations and linear algebra. This is hardly a balanced introduction to the nature and variety of mathematics. Attempts at reform have been common, and so has their failure. Table 1 shows one current reform proposal, the contents of a version of “Mathematics 101–102” developed with NSF funding (COMAP, 1997). There is no calculus, which is left for the second year. There is also no statistics, though probability does appear. The absence of statistics in “Mathematics 101–102” should attract comment. After all, CUPM recommended in 1981 that “other mathematical sciences courses, such as computer science and applied probability and statistics, should be an integral part of the first two years of study. ” (See Steen 1989, page 5.) This suggestion has generally brought agreement in principle (though little action). I want to offer a partial disagreement in principle. I will argue that, whatever the merits of “Mathematics 101–102,” its authors have done the right thing about probability and statistics. They have included the first and omitted the second. To my taste, they would have done well to exercise the same rigor with respect to computer science, in exchange for some continuous mathematics in the first college year. The point is this: a mathematics core ought to display to students the nature and variety of mathematics, including its applicability, but is not the place to develop the principles of related fields. Probability has an important place within mathematics. Statistics does not, and an attempt to include it will be disruptive.
A Novel Improvement to Google Scholar Ranking Algorithms Through Broad Topic Search

Google Scholar uses ranking algorithms to find the most relevant academic research possible. However, its algorithms use an exact keyword match and citation count to sort its results. This paper presents a novel improvement to Google Scholar algorithms by aggregating multiple synonymous searches into one set of results, offsetting the necessity to guess all potential search phrases for a research topic. This design science research method uses a broad topic analysis that examines search queries, finds synonymous phrases, and combines all keyword searches into one set of results based on current Google Scholar citation count algorithms. To support and evaluate this research-in-progress, several users will compare multiple niche search queries against old and new algorithms. The expectation of this design is to introduce modern algorithm techniques to academic search engines, resulting in greater quality, discoverability, and core topic diversity of published research.
MOSFET modeling for analog circuit CAD: Problems and prospects

The requirements for good MOSFET modeling as they apply to usage in analog and mixed analog-digital design are discussed. A set of benchmark tests that can be easily performed is given, and it is argued that most CAD (computer-aided design) models today fail such tests even for simple, long-channel devices at room temperature. A number of other problems are discussed, and in certain cases specific cures are suggested. The issue of parameter extraction is addressed. Finally, the context of model development and usage is considered, and it is argued that some of the factors responsible for the problems encountered in the modeling effort are of a nontechnical nature.
Perceptually transparent audio compression based on a variable bit rate AAC coder

The paper presents an implementation of a perceptually transparent variable bit rate (VBR) audio coder that complies with the MPEG-4 advanced audio coding (AAC) standard. The coder is based on the MPEG-4 reference software source code of CBR coder. With small modifications in the reference source code a coder guaranteeing perceptual transparency is achieved at compression ratios considerably better than that of the reference CBR coder. Comparison tests indicate that files generated by the perceptually transparent VBR coder applied to a standard set of test items are considerably smaller (in average 24%) than the smallest CBR files of the same quality.
COMPARATIVE ANALYSIS OF SPEECH RECOGNITION SYSTEMS WITH OPEN CODE

В статье проведен сравнительный анализ наиболее распространенных систем автоматического распознавания речи с открытым исходным кодом. При сравнении использовалось множество критериев, включая структуры систем, языки программирования при реализации, наличие подробной документации, поддерживаемые языки распознавания, ограничения накладываемые лицензией. Также были проведены эксперименты на нескольких речевых корпусах для определения скорости и точности распознавания. В результате для каждой из рассмотренных систем были выработаны рекомендации по применению с дополнительным указанием сферы деятельности.
Introduction to Information Technology Law

Now in its sixth edition, Introduction to Information Technology Law (formerly "Introduction to Computer Law"), provides a comprehensive and accessible introduction to the law as it relates to computers. Adopting a practical approach that places the law in the context of computer use, this book is highly suitable for undergraduate law students, non-specialist students and computer professionals.
On-Line Dynamic Voltage Scaling for EDZL Scheduling on Symmetric Multiprocessor Real-Time Systems

EDZL (Earliest Deadline Zero Laxity) scheduling is known to be at least as EDF (Earliest Deadline First) in task scheduling on symmetric multiprocessor real-time systems; however, there are few works on energy conversation on the EDZL. This paper proposes an on-line Dynamic Voltage Scaling (DVS) algorithm of the global EDZL to reduce energy consumption of real-time tasks. The proposed algorithm dynamically adjusts processor speed at each scheduling point with re-assigning deadlines of active jobs that reduces power consumption of processors while making all real-time tasks schedulable by EDZL. Extensive simulations show that the proposed algorithm reduces power consumption more than the previous algorithm for EDZL.
Multi-Scale Banking to 45º

In his text Visualizing Data, William Cleveland demonstrates how the aspect ratio of a line chart can affect an analyst’s perception of trends in the data. Cleveland proposes an optimization technique for computing the aspect ratio such that the average absolute orientation of line segments in the chart is equal to 45 degrees. This technique, called banking to 45°, is designed to maximize the discriminability of the orientations of the line segments in the chart. In this paper, we revisit this classic result and describe two new extensions. First, we propose alternate optimization criteria designed to further improve the visual perception of line segment orientations. Second, we develop multi-scale banking, a technique that combines spectral analysis with banking to 45°. Our technique automatically identifies trends at various frequency scales and then generates a banked chart for each of these scales. We demonstrate the utility of our techniques in a range of visualization tools and analysis examples.
Active distributed management for IP networks

We argue that a management platform for the future Internet has to be inherently distributed and programmable. This motivates us to introduce a new management architecture, named active distributed management, which exploits the active network and mobile agent paradigms and provides the properties of distributed control and programmability inside the network. We realize the ADM architecture as a management middleware composed of several layers. In order to facilitate the development of efficient and correct programs, these layers include patterns for distributed algorithms that are typical for management applications and a set of building blocks for constructing management programs. First results of an ADM prototype system are presented.
Automated generation of hybrid automata for multi-rigid-body mechanical systems and its application to the falsification of safety properties

ABSTRACT What if we designed a tool to automatically generate a dynamical transition system for the formal specification of mechanical systems subject to multiple impacts, contacts and discontinuous friction? Such a tool would represent an advance in the description and simulation of these complex systems. This is precisely what this paper offers: Dyverse Rigid Body Toolbox (DyverseRBT). This tool requires a sufficiently expressive computational model that can accurately describe the behaviour of the system as it evolves over time. For this purpose, we propose an alternative abstraction of multi-rigid-body (MRB) mechanical systems with multiple contacts as an extended version of the classical hybrid automaton, which we call MRB hybrid automaton. One of the chief characteristics of the MRB hybrid automaton is the inclusion of computation nodes to encode algorithms to calculate the contact forces. The computation nodes consist of a set of non-dynamical discrete locations, discrete transitions and guards between these locations, and resets on transitions. They can account for the energy transfer not explicitly considered within the rigid-body formalism. The proposed modelling framework is well suited for the automated verification of dynamical properties of realistic mechanical systems. We show this by the falsification of safety properties over the transition system generated by DyverseRBT.
La ressource Nomage. Confronter les attentes théoriques aux observations du comportement linguistique des nominalisations en corpus

La ressource presentee dans cet article combine un corpus de noms deverbaux annotes semantiquement et syntaxiquement, fonde sur le French Treebank, et un lexique electronique fournissant des informations d'ordre morphologique, syntaxique et semantique sur les noms presents dans le corpus ainsi que sur les verbes dont ils sont derives. ABSTRACT. The resource presented in this paper combines a semantically and syntactically anno-tated corpus of deverbal nouns based on the French Treebank, and an electronic lexicon, pro-viding descriptions of morphological, syntactic and semantic properties of the deverbal nouns found in our corpus and of their verbal sources. MOTS-CLES : corpus annote, lexique fonde sur corpus, nominalisation, aspect lexical, structure argumentale.
MOBİL ÖĞRENMENİN ÖĞRENCİ BAŞARISINA ETKİSİ: BİR META ANALİZ ÇALIŞMASI

Bu calismada 2009-2014 yillari arasinda uluslararasi alanda daha once mobil ogrenme ile ilgili yapilmis deneysel arastirmalarin bir araya toplanip, genel etki buyuklugunun belirlenmesi amaclanmistir. Bu amacla arastirmada, sistematik sentezleme yontemlerinden biri olan “MetaAnaliz Yontemi” kullanilmistir. Konu ile ilgili EBSCOhost veri tabaninda aratilan 3.512 makaleye ulasilmis, calismanin kapsami geregi belirlenen dâhil edilme olcutleri dâhilinde 10 calisma analiz edilmistir. Arastirmada etki buyuklugu indeksi olarak Cohen’nin d etki buyuklugu kullanilmistir. Yapilan homojenlik testi sonucunda, sabit etki modelinden rastgele etki modeline cevrilmistir. Rastgele etki modeline gore yapilan analiz sonucunda, mobil ogrenmenin, akademik basariya etkisi d=0.849 etki buyuklugu pozitif yonde ve yuksek duzeyde bir etkiye sahip oldugu ortaya cikmistir. Yapilan meta-analizde elde edilen kritik p degeri, mobil ogrenme calismalarinin birlestirilebilecegini ve egitimde, mobil ogrenmenin daha fazla kullanilmasi gerektigi sonucunu vermektedir
DESMET: a methodology for evaluating software engineering methods and tools

DESMET was a DTI-backed project with the goal of developing and validating a methodology for evaluating software engineering methods and tools. The project identified nine methods of evaluation and a set of criteria to help evaluators select an appropriate method. Detailed guidelines were developed for three important evaluation methods: formal experiments, quantitative case studies and feature analysis evaluations. This article describes the way the DESMET project used the DESMET methodology both to evaluate the methodology itself and to provide direct assistance to the commercial organisations using it.
A Comparative Study between the Support Vectors Machines and the K-Nearest Neighbors in the Handwritten Latin Numerals Recognition

In this paper we present a comparison between two methods of learning-classification, the first is the K-Nearest Neighbors (KNN) and the second is the Support Vectors Machines (SVM), these both methods are supervised and used for the recognition of handwritten Latin numerals that are extracted from the MNIST standard database. The recognition process organized as follows: in the pre-processing of numeral images, we exploited the thresholding, the centering and the normalization techniques, in the features extraction we have used the morphology mathematical, the zoning and the zig-zag methods. The classification methods include the K-Nearest Neighbors and the Support Vectors Machines. Our experiments results proved the highest test accuracies 93.13% and 86.50% respectively with SVM and KNN classifiers. The simulation results that we obtained demonstrate the SVM is more performing than the KNN in this recognition.
Safe Programming at the C Level of Abstraction

Memory safety and type safety are invaluable features for building robust software. However, most safe programming languages are at a high level of memory management. This control is one reason C remains the de facto standard for writing systems software or extending legacy systems already written in C. The Cyclone language aims to bring safety to C-style programming without sacrificing the programmer control necessary for low-level software. A combination of advanced compile-time techniques, run-time checks, and modern language features helps achieve this goal. This dissertation focuses on the advanced compile-time techniques. A type system with quantified types and effects prevents incorrect type casts, dangling-pointer dereferences, and data races. An intraprocedural flow analysis prevents dereferencing NULL pointers and uninitialized memory, and extensions to it can prevent proofs demonstrate that these compile-time techniques are sound: The safety violations they address become impossible. A less formal evaluation establishes two other design goals of equal importance. First, the language remains expressive. Although it rejects some safe programs, it permits many C idioms regarding generic code, manual memory management, lock-based synchronization, NULL-pointer checking, and data initialization. Second, the language represents a unified approach. A small collection of techniques addresses a range of problems, indicating that the problems are more alike than they originally seem.
Intra-connecting an exemplary literary corpus with semantic web technologies for exploratory literary studies

Many (modernist) works of literature can be understood by their associativeness, be it constructed or “free”. This network-like character of (modernist) literature has often been addressed by terms like “free association”, connotation”, “context” or “intertext”. This paper proposes an experimental and exemplary approach to intraconnect a literary corpus of the Austrian writer Ilse Aichinger with semantic web-technologies to enable interactive explorations of word-associations.
A fast neural net training algorithm and its application to voiced-unvoiced-silence classification of speech

The authors describe a fast training algorithm for feedforward neural nets, and apply it to a two-layer neural network to classify segments of speech as voiced, unvoiced, or silence. The speech classification method is based on features computed for each speech segment and used as input to the network. The network weights are trained using a fast training algorithm which uses a quasi-Newton error minimization method with a positive-definite approximation of the Hessian matrix. When used for voiced-unvoiced-silence classification of speech frames, the performance of the network compares favorably with that of current approaches. Experimental results are presented for speaker-dependent speech classification, including evaluation of the effects of the type of input data used during training. The results indicate satisfactory performance with errors in the range 3-5%, based on manual classification of the speech frames. <<ETX>>