Miracle-dz/UniFAR-FTUs huggingface dataset:
Hidden Markov models applied to very low bit rate speech coding

A new type of very low bit rate speech coder based on a global Discrete Hidden Markov Model (DHMM) of continuous speech for a single speaker is presented here. Several important issues of the training, coding, and decoding procedures are discussed for a 64-state, 1024-observation model. Such a framework is useful in reducing the redundancy in a 10-bit classical Vector Quantizer (VQ), and could lead to a DHMM coder with a bit rate comparable to that of a Segment Vocoder (SV) or a Matrix Quantizer (MQ). This is achieved not only by modelling the long term non-stationarity and the inter-frame time dependencies of the speech, but also by efficiently representing a different kind of information such as vocal tract structure and linguistic patterns.
Review Techniques of Data Privacy in Cloud Using Back Propagation Neural Network

Back Propagation is the scheme for neural network learning. This learning accuracy gained by collaborative learning. In existing system support this kind of learning on limited dataset and between two parties. It cannot protect intermediate result. In our proposed system multiple parties perform collaborative learning on arbitrarily partitioned data using cloud computing. In which for privacy preservation each party send plain text to the cloud and cloud encrypt that text. In this way minimizing the computation and communication cost. To support the various operations over cloud we are using the different algorithm. In this way cloud show our learning scheme is secure. Keywords—Privacy Preserving, Neural network, Cloud computing, Back Propagation.
Una plataforma de evaluación automática con una metodología efectiva para la enseñanza/aprendizaje en programación de computadores An automatic evaluation platform with an effective methodology for teaching/learning computer programming

Learning to program is a difficult process for novice students and challenging for teaching methods. In this paper we present an automatic evaluation platform and a methodology to support the teaching/learning process in computer programming introductory courses for engineering students at the Universidad de Concepcion. This platform uses static/dynamic techniques and applies comprehension /analysis evaluation enabling personalized feedback to students. This work includes the criteria used to create didactic problems sequences and effective ways to apply them through automatic evaluation. The results obtained during six years of application show that automatic evaluation along with the proposed methodology improves student’s motivation, performance and self-efficacy. The methodology used to study the effectiveness of the platform includes qualitative and quantitative analysis. The qualitative aspects are extracted by observing student behavior during the learning process, whereas the quantitative analysis is based on student data registered by the platform. In order to gather quantitative information, we applied different experiments based on control and experimental student groups.
INTRUSION DETECTION SYSTEM: TIME PROBABILITY METHOD AND HYPERBOLIC HOPFIELD NEURAL NETWORK

Nowadays, high level security maintenance between the two companies is the significant issue when they are communicating between them. However, the goal of achieving complete secure communication between those companies communicating over the internet with various networks is still lacked by the following factors such as misuses and intrusions. Thus, the Intrusion Detection Systems are very important components to detect these types of attacks. There are various approaches being utilized to these intrusion detections, but any of the systems so far is not completely flawless. The proposed framework utilized novel methods such as time probability based pattern detection method and Hyperbolic Hopfield Neural Network for detect the intrusion from the real time network datasets. The experimental results shows our proposed
A MODEL-BASED COMPUTER SYSTEM FOR TEACHING LEGAL-CASE SOLVING

This research aims at providing a solution for problems experienced by law students when solving legal cases. We propose a computer coach for training legal-case solving, the ROSA system. The basis for ROSA is an explicit, teachable and learnable model of legalcase solving, executable by machines and by humans. In this paper the construction of the model for teaching and learning legal-case solving is described and the tracer, a tool to support the information management during the case-solving process, is introduced. 1 Legal-case solving Legal cases are frequently used in legal education for teaching law students how to apply law to a specific situation. For this purpose legal cases (either hypothetical or based on real cases) are used as examples and as problem situations to be solved by a student when learning legal problem solving. Cases are also used in preliminary examinations as problems that need to be solved by the student. A legal case contains a description of a situation and a legal question. In the situation description, the specific facts and events are supplied. The case needs to be solved on the basis of the (sometimes hidden) legal question(s). The situation description may vary from a short case to cases of one page or more. The question(s) in between or at the end restrict both the problem situation and the possible range of solutions. The question may indicate a direction to the relation and may put the student on a reasoning track. The case is constructed from a legal dogmatic point of view; cases are formulated with the dogmatic means of solving in mind. The cases used in major subjects as civil law, criminal law, constitutional law and administrative law are closed regarding the content, that is, the problem is presented in a specific area of law and the solution has to be found within that area. Moreover, the student has to look for a solution that is acceptable within the legal system (to look, for instance, at the consequences for society is not the issue). There is a correct solution; sometimes there are two or more solutions possible. An
Asynchronous Techniques for System-on-Chip Design Digital circuit designs that are not sensitive to delay promise to allow operation without clocks for future systems-on-a-chip.

SoC design will require asynchronous techniques as the large parameter variations across the chip will make it impossible to control delays in clock networks and other global signals efficiently. Initially, SoCs will be globally asynchronous and locally synchronous (GALS). But the complexity of the numerous asynchronous/synchronous interfaces required in a GALS will eventually lead to entirely asynchronous solutions. This paper introduces the main design principles, methods, and building blocks for asynchronous VLSI systems, with an em- phasis on communication and synchronization. Asynchronous circuits with the only delay assumption of isochronic forks are called quasi-delay-insensitive (QDI). QDI is used in the paper as the basis for asynchronous logic. The paper discusses asyn- chronous handshake protocols for communication and the notion of validity/neutrality tests, and completion tree. Basic building blocks for sequencing, storage, function evaluation, and buses are described, and two alternative methods for the implementation of an arbitrary computation are explained. Issues of arbitration, and synchronization play an important role in complex distributed systems and especially in GALS. The two main asynchronous/synchronous interfaces needed in GALSVone based on synchronizer, the other on stoppable clockVare described and analyzed.
Reporting Failures in Functional Logic

Computing with failures is a typical programming technique in functional logic programs. However, there are also situations where a program should not fail (e.g., in a deterministic top-level computation) but the evaluation fails accidentally, e.g., due to missing pattern combinations in an operation defined by pattern matching. In this case, the program developer is interested in the context of the failed program point in order to analyze the reason of the failure. Therefore, this paper discusses techniques for reporting failures and proposes a new one that has been integrated in a Prolog-based compiler for the declarative multi-paradigm language Curry. Our new technique supports separate compilation of modules, i.e., the compilation of modules has not taken into account whether failures should be reported or not. The failure reporting is only considered in some linking code for modules. In contrast to previous approaches, the execution of programs in the failure reporting mode causes only a small overhead so that it can be also used in larger applications.
RECEPTORS AND SYLLABLE TRAJECTORIES

The present study aims at discovering the emergence of syllabic receptors appealing solely to phonotactic information in a given language. Our work focuses on French phonotactics. The research exploits a Self-Organizing Map (SOM) to create a knowledge representation of receptors which become specifically tuned to syllabic behaviors through an unsupervised learning protocol. Our simulations highlight not only syllable (and syllabification) modeling in quantitative terms (seen as the emergent by-product of frequency and phonotactic regularities), but other non-trivial aspects of the implicit phonotactic knowledge that speakers exhibit in a given language.
Mise en oeuvre de notations standardisées, formelles et semi-formelles dans un processus de développement de systèmes embarqués temps-réel répartis.

Dans une demarche classique d'ingenierie dirigee par les modeles (IDM), l'ingenieur modelise son systeme a l'aide d'une notation semi-formelle, le valide puis l'implante. L'etape de validation, basee sur ces modeles, est particulierement cruciale pour les systemes temps-reel repartis et embarques (TR2E), afin de s'assurer de leur respect d'invariants de securite, ou de leur bon fonctionnement logique ou temporel. Cependant, une demarche IDM n'est pas suffisante car elle n'indique pas comment utiliser les modeles pour faire des analyses. Quels modeles (ou vues) utiliser ? Pour analyser quel type de proprietes ? Ainsi, il est necessaire d'adopter une demarche d'Ingenierie dirigee par les Verifications et les Validations (IDV2) : les modeles crees sont ceux qui sont utiles pour s'assurer que le systeme est correctement construit (verification), et qu'il satisfait un ensemble de proprietes specifiees en amont dans le processus de developpement (validation). Cette these propose un processus de developpement, de validation et de verification base sur des notations formelles, et dedie aux applications temps-reel reparties embarquees. Nous nous appuyons sur une notation pivot standard pour appliquer cette demarche IDV2 : le langage AADL (Architecture Analysis and Design Language) permet a l'ingenieur de specifier son application TR2E depuis son architecture materielle jusqu'a son deploiement logiciel. Il repose sur l'existence d'un executif ayant certaines proprietes et proposant differents services. Ce processus prend en compte les aspects comportementaux de l'application ainsi que les aspects architecturaux de l'executif. Il repose sur des notations standardisees, permettant de faire face aux problemes d'interoperabilites des outils mis en oeuvre. Pour l'applicatif, des proprietes comme l'absence d'interblocage, l'utilisation et le dimensionnement de ressources ou encore l'ordonnancement du systeme sont validees. Pour l'executif, le fait que l'architecture de celui-ci et les services proposes sont en adequation avec les proprietes evoquees lors de sa configuration est verifie. Notre demarche permet d'obtenir des retours aussi bien a propos de l'applicatif que de l'executif, et permet de corriger ou modifier les modeles dans un processus de developpement iteratif. Au cours de notre demarche, nous exploitons et transformons les specifications AADL vers differentes notations standardisees : les reseaux de Petri pour la validation de l'applicatif, la notation Z pour la verification de l'executif utilise, PolyORB.
ICT and Multimedia in Primary School

The paper outlines the result of a threeyear research project concerning the use of multimedia and ICT in primary schools in Austria. The aim of the study was to evaluate the efficiency of learning with multimedia applications (offline products e.g. CD-ROM, user software e.g. word processing and presentation and Internet) and to develop didactic models for learning with new media as well as a model for an ICT curriculum for primary schools. The use of multimedia learning environments in the classroom requires special knowledge. Teachers need technical support as well as didactic models to introduce users to software and learn about new aspects of learning theories in combination with learning with new technologies.
International Workshop on Foundations and Techniques for Open Source Software Certification (OpenCert 2009)

Abstract . Problems with portability of applications across various Linux distributions is one of the major sore spots of independent software vendors (ISVs) wishing to support the Linux platform in their products. The source of the problem is that different distributions have different sets of system libraries that vary in the interfaces (APIs) provided, with respect to both composition and behavior. And the critical questions arise such as “which distributions my application would run on” or “what can I specifically do to make my application run on a greater number of distributions”. This article presents an approach and the Linux Application Checker tool that help to answer such questions by automatically analyzing the target application and confronting collected data with the internal knowledge base containing information about the various real world distributions. Additionally, Linux Application Checker is an official tool approved by the Linux Foundation for certifying applications for compliance with the Linux Standard Base (LSB) standard, the leading effort for the “single Linux specification”.
Current State of Ontology Matching. A Survey of Ontology and Schema Matching

Ontology matching is an important task when data from multiple data sources is integrated. Problems of ontology matching have been studied widely in the research literature and many different solutions and approaches have been proposed also in commercial software tools. In this survey, well-known approaches of ontology matching, and its subtype schema matching, are reviewed and compared. The aim of this report is to summarize the knowledge about the state-of-the-art solutions from the research literature, discuss how the methods work on different application domains, and analyze pros and cons of different open source and academic tools in the commercial world.
Guest Editors’ Introduction: On the Contributions of Applied Science/Engineering Research to Information Systems

JAY F. NUNAMAKER, JR. is Regents and Soldwedel Professor of MIS, Computer Science, and Communication, and director of the Center for the Management of Information and the National Center for Border Security at the University of Arizona. He received his Ph.D. in operations research and systems engineering from Case Institute of Technology, an M.S. and B.S. in engineering from the University of Pittsburgh, and a B.S. from Carnegie Mellon University. He received his professional engineer’s license in 1965. He was inducted into the Design Science Hall of Fame in May 2008. He received the LEO Award for Lifetime Achievement from the Association for Information Systems (AIS) and was elected a Fellow of the AIS. He was featured in the July 1997 issue of Forbes magazine on technology as one of the eight key innovators in information technology. He is widely published, with an h-index of 60. He specializes is in system analysis and design, collaboration technology, and deception detection. The commercial product, GroupSystems’ ThinkTank, based on his research, is often referred to as the gold standard for structured collaboration systems. He founded the MIS Department at the University of Arizona in 1974 and served as department head for eighteen years.
Evolution of Scientific Collaboration Communities in the AACE

This paper investigates the evolving co-authorship networks generated by the scientific production of EdMedia, SITE and E-Learn, three world conferences promoted by the Association for the Advancement of Computing in Education (AACE). The studied data corresponds to measurements made over the scientific papers submitted to these conferences from 1999 to 2011. The conducted analysis is based on cumulative co-authorship networks and presents several statistics about the most relevant temporal evolving characteristics phenomena exhibited by these three scientific collaboration communities. The dynamics and activity of these networks, as well as their morphology and connectivity, are observed to provide meaningful interpretations of the measurements found in the context of a collaboration network of researchers.
A multiple join index for data warehouses

The demands of today's software applications are more and more each day. They need to collect, manage and transform more and more data with a complex structure. These data are nowadays organized in data warehouses. To accelerate data mining searches that combine multiple restrictive queries indexing techniques are usually used. The paper proposes a new multiple join index structure, which is useful for multiple join operations between tables. The algorithm to build this index structure is presented and, also, some types of queries that can be accelerated with the index help.
Double Sparsity Dictionary for Seismic Noise Attenuation

ABSTRACTA key step in sparsifying signals is the choice of a sparsity-promoting dictionary. There are two basic approaches to design such a dictionary: the analytic approach and the learning-based approach. Although the analytic approach enjoys the advantage of high efficiency, it lacks adaptivity to various data patterns. On the other hand, the learning-based approach can adaptively sparsify different data sets but has a heavier computational complexity and involves no prior-constraint pattern information for particular data. We have developed a double-sparsity dictionary (DSD) for seismic data to combine the benefits of both approaches. We have evaluated two models to learn the DSD: the synthesis model and the analysis model. The synthesis model learns DSD in the data domain, and the analysis model learns DSD in the model domain. We tested the analysis model and proposed to use the seislet transform and data-driven tight frame (DDTF) as the base transform and adaptive dictionary, respectively, in the DS.
A New Public-Key Cryptosystem

A New Public-Key Cryptosystem Chris Hettinger Department of Mathematics, BYU Master of Science Public key cryptosystems offer important advantages over symmetric methods, but the most important such systems rely on the difficulty of integer factorization (or the related discrete logarithm problem). Advances in quantum computing threaten to render such systems useless. In addition, public-key systems tend to be slower than symmetric systems because of their use of number-theoretic algorithms. I propose a new public key system which may be secure against both classical and quantum attacks, while remaining simple and very fast. The system’s action is best described in terms of linear algebra, while its security is more naturally explained in the context of graph theory.
Lagrangian formulation of underwater vehicles' dynamics

Key properties of the equations of motion for underwater vehicles are derived both theoretically and experimentally. The equations of motion for underwater vehicles are derived in a Lagrangian framework. The Lagrangian approach has several distinctive advantages compared to the Newtonian approach. This is especially true in the context of underwater vehicles. The derivation of the hydrodynamic added inertia and the vehicle's rigid body equations of motion can be done in a common framework. The added inertia is given a clear and physical interpretation when the vehicle-ambient water system is considered from an energy point of view instead of a force-moment approach. <<ETX>>
Feature Selection and Integration in Automatic Classification of Japanese Texts

We explore the problem of automatic text clas- sification using Japanese documents. Unlike other languages that use roman letters, Japanese language poses a problem of not availing word boundary information. As such bag-of-words approach in constructing features may not be sufficient to en- hance machine learning techniques. We propose a method for feature selection and construction to improve automatic clas- sification performance of Japanese texts. Our approach in- volve extracting syntactic word categories and Chinese charac- ters (Kanji) separately. Then we combine the extracted infor- mation to build an informative feature set. We carried out var- ious experiments using four learning algorithms to evaluate its effectiveness. The proposed method generally outperformed its counterparts method for Japanese document representation. Keyword - Japanese text classification, Feature selection, Fea- ture integration, Feature transformation.
OPTIMIZATION OF LZ77 DATA COMPRESSION ALGORITHM

Data compression refers to reducing the amount of space needed to store data or reducing the amount of time needed to transmit data. Many data compression techniques allow encoding the compressed form of data with different compression ratio. In particular, in the case of LZ77 technique, it reduces the data concurrency of an input file. In the output of this technique it conveys more information that is actually not needed in practical. Removing the extra information from the encoded file that makes this algorithm more optimal. Our task is to identify how much extra information it conveys and how can we minimize it so that there is no trouble at the time of decoding. Basically the encoded output of LZ77 is the sequence of triplets (a structure of encoded output) that is in binary and having fix size. For making the triplets of fix size, sometimes we are creating unnecessary information. We present the method of variable triplet size as a way to improve LZ77 compression and demonstrate it through many experiments. In our optimization algorithm we are getting more compression ratio compare to the conventional LZ77 data compression algorithm.