Miracle-dz/UniFAR-FTUs huggingface dataset:
The Nonlinear Time Alignment Model for Speech Recognition System

We present the new nonlinear time alignment model, which is much faster than widely accepted DTW algorithms. This work has been started with the aim of finding suitable time alignment algorithm and features, for Marathi (Language spoken in the state of Maharashtra, India) word Speech Recognition System. Proposed algorithm shows comparable or better recognition efficiency than widely accepted algorithms and is robust to end point variations. In this work, vocabularies are: (1) 46 isolated monosyllabic confusing Marathi alphabets and (2) 46 non-confusing names of the persons. The features used are LPC, LFCC and MFCC. For the confusing word vocabulary, the proposed algorithm proved to be best showing maximum recognition efficiency of 89.13% and second best is Itakura's DTW algorithm with maximum recognition efficiency of 86.96%. LFCC with Itakura's DTW algorithm shows poor performance with maximum recognition efficiency of 13.40%. But LFCC with proposed algorithm shows comparable results for non-confusing vocabulary.
High confidence personal identification by rapid video analysis of iris texture

The concept of using the iris of the eye as a kind of optical fingerprint for personal identification is discussed. By isolating and encoding the visible texture of the iris from a video image into a multiscale sequence of quadrature 2D Gabor coefficients, a 256-byte iris code has been developed that uniquely identifies any individual, with astronomic confidence levels. Following image analysis, the critical problem of pattern recognition is transformed essentially into a statistical test of independence on the real and imaginary parts of the complex 2D Gabor coefficients. Statistical decision theory permits rigorous execution of identification decisions from comparisons of iris codes, at the rate of 4000 per second, including computation of the confidence associated with each identification decision. Such a recognition system has been developed using a conventional zoom videocamera. In tests to date, the system has never failed to identify any enrolled individual correctly. <<ETX>>
MAC Protocol Implementation & Design for Wireless Distributed Computing

: The idea of wireless distributed computing is rapidly gaining recognition owing to its promising potential in military, public safety and commercial applications. This concept basically entails distributing a computationally intensive task that one radio device is assigned, among its neighboring peer radio devices. The added processing power of multiple radios can be harnessed to significantly reduce the time consumed in obtaining the results of the original complex task. Since the idea of wireless distributed computing depends on a radio device forming a network with its peers, it is imperative and necessary to have a medium access control (MAC) protocol for such networks which is capable of scheduling channel access by multiple radios in the network, and ensuring reliable data transfer, incorporating rate adaptation as well as handling link failures. The thesis presented here elaborates the design and implementation of such a MAC protocol for WDC employed in a practical network of radio devices configurable through software. It also bring to light the design and implementation constrains and challenges faced in this endeavor and puts forward viable solutions.
Theory and Applications of Satisfiability Testing: 6th International Conference, Sat 2003, Santa Margherita Ligure, Italy, May 5-8 2003: Selected Revised Papers (Lecture Notes in Computer Science, 2919)

Satisfiability and Computing van der Waerden Numbers. - An Algorithm for SAT Above the Threshold. - Watched Data Structures for QBF Solvers. - How Good Can a Resolution Based SAT-solver Be? - A Local Search SAT Solver Using an Effective Switching Strategy and an Efficient Unit Propagation. - Density Condensation of Boolean Formulas. - SAT Based Predicate Abstraction for Hardware Verification. - On Boolean Models for Quantified Boolean Horn Formulas. - Local Search on SAT-encoded Colouring Problems. - A Study of Pure Random Walk on Random Satisfiability Problems with "Physical" Methods. - Hidden Threshold Phenomena for Fixed-Density SAT-formulae. - Improving a Probabilistic 3-SAT Algorithm by Dynamic Search and Independent Clause Pairs. - Width-Based Algorithms for SAT and CIRCUIT-SAT.- Linear Time Algorithms for Some Not-All-Equal Satisfiability Problems. - On Fixed-Parameter Tractable Parameterizations of SAT.- On the Probabilistic Approach to the Random Satisfiability Problem. - Comparing Different Prenexing Strategies for Quantified Boolean Formulas. - Solving Error Correction for Large Data Sets by Means of a SAT Solver. - Using Problem Structure for Efficient Clause Learning. - Abstraction-Driven SAT-based Analysis of Security Protocols. - A Case for Efficient Solution Enumeration. - Cache Performance of SAT Solvers: a Case Study for Efficient Implementation of Algorithms. - Local Consistencies in SAT.- Guiding SAT Diagnosis with Tree Decompositions. - On Computing k-CNF Formula Properties. - Effective Preprocessing with Hyper-Resolution and Equality Reduction. - Read-Once Unit Resolution. - The Interaction Between Inference and Branching Heuristics. - Hypergraph Reductions and Satisfiability Problems. - SBSAT: a State-Based, BDD-Based Satisfiability Solver. - Computing Vertex Eccentricity in Exponentially Large Graphs: QBF Formulation and Solution. - The Combinatorics of Conflicts between Clauses. - Conflict-Based Selection of Branching Rules. - The Essentials of the SAT 2003 Competition. - Challenges in the QBF Arena: the SAT'03 Evaluation of QBF Solvers. - kcnfs: An Efficient Solver for Random k-SAT Formulae. - An Extensible SAT-solver. - Survey and Belief Propagation on Random K-SAT.
New Landscape of Data Management Technologies

The revolutionary progress of data collecting techniques, dramatic decrease of the price of storage devices, as well as the desirability of people to extract information from the data have given birth to the so-called big data and data management technologies usher in the age of big data. RDBMS (relational database management system) undergoes a development of 40 years since the 1970s and now encounters some difficulties such as limited system scalability and limited data variety support. In recent years, noSQL technologies has risen suddenly as a new force. The technologies can manage, process, and analyze various types of data, achieve rather high performance with the help of parallel computing, can handle even bigger volume of data with the nice property of highly scalability. The paper follows the path of database technology progress and unfolds the new landscape of data management technologies from the angle of ∗ 基金项目: 国家自然科学基金(61070054, 60873017, 61170013); “核高基”国家科技重大专项(2010ZX01042-001-002, 2010ZX 01042-002-002-03); EMC 中国研究院“EMC 全球 CTO 办公室”资金 收稿时间: 2012-06-12; 定稿时间: 2012-10-16; jos 在线出版时间: 2012-11-23 CNKI 网络优先出版: 2012-11-23 12:08, http://www.cnki. net/kcms/detail/11.2560. TP.20121123. 1208.003. html 176 Journal of Software 软件学报 Vol.24, No.2, February 2013 applications (operational as well as analytic applications). The paper also identifies some chanllenging and important issues that deserve further investigation, with the authors’ recent research work introduced at the end.
Designing a Passive Folding String Device with an Electromagnet

We propose a passively foldable string device. This string device is composed of multiple modules which have an electromagnet on each face. The string is folded according to the pattern of the magnetic poles of the electromagnets, like proteins that fold according to the order of amino acids. It is unfolded if all the magnets have the same polarity. This string can be folded even if the string is long and heavy using an external force, for example a vibration or convection. This kind of device can be used not only as an experimental tool for studying a selffolding process but also as a three-dimensional physical display. In this paper, we propose a design of the folding string device and show some results of experiment for verification of this idea.
Data mining using neural fuzzy for student relationship management

: - Customer Relationship Management (CRM) initiatives have attracted much attention in recent years. The technology behind CRM is data mining, which require human interaction with the technology so as to achieve a successful CRM strategy. In this paper, we look at the implementation of CRM in the environment of an educational institution, known as Student Relationship Management (SRM). This paper examines the difference between SRM and CRM, and proposes a model for performing part of the SRM role. Intelligent techniques mainly Artificial Neural Network (ANN) and Fuzzy theory are used as intelligent tools to interact with the human analyst in formulating a SRM strategy.
Reconstruction of individual trees based on LiDAR and in situ data

This paper presents a method to reconstruct individual trees from Terrestrial Laser Scanning (TLS) data obtained in leafoff conditions of an experiment plot. It firstly used the point clouds to build the branch structures of trees with a global optimization method. Computer generated needles and shoots were added to the previously constructed branches according to the leaf area (LA) of each individual tree, in consideration of clumping effect of small-scale structures. The LA was determined by the proportion of crown volume in this plot with LAI measured. In this way, several larix trees with different shapes and heights were reconstructed, which is basis of 3D forest scene reconstruction.
Scalable video with raptor for wireless multicast networks

In this paper, we investigate scalability performance using H.264 codec for wireless multicast networks. A set of experiments are implemented to measure the error resilience of advanced Video codec (AVC) subsequences and Scalable Video Codec (SVC). The impact of Raptor, a powerful Forward Error Correction (FEC) code, is also investigated for scalability and a scheme for scalable codec with Raptor is proposed.
IMPROVING PRIVACY IN SHARING OF PERSONAL HEALTH DATA STORAGE ON CLOUD

PHRs grant patients access to a wide range of health information sources, best medical practices and health knowledge. In patient centric secure sharing, patients will create, manage and control their personal health data from one place using the web. In cloud computing, it is attractive for the health record service providers to shift their patients data applications and storage into the cloud, in order to like the flexible resources and diminish the operational cost, but by storing health records in the cloud, the patients be unable to find physical control to their personal health data, which makes it required for each patient to encrypt the data prior to uploading to the cloud servers. Under encryption, it is difficult to achieve fine-grained access control to personal health data in a scalable and well-organized way. Existing cryptographic enforced access control schemes are mostly designed for the single-owner scenarios. In this, suggest a patient-centric frame work and a suite of mechanism for data access control to PHRs stored in semi-trusted servers. To allow fine-grained and scalable access control for PHRs, control attribute based encryption (ABE) techniques to encrypt every patients data. Different from earlier works in protected data outsourcing, center on the multiple data owner scenario, and separate the user in the system into multiple security domains that really decreases the key managing complexity for owners and users. In this way, a high degree of patient privacy is assured concurrently by developing multi-authority ABE.
Agentes inteligentes y web semántica: hacia la verbalización de un subconjunto de UML en una herramienta gráfica web

RESUMEN El proyecto de investigación Agentes Inteligentes y Web Semántica, financiado por la Universidad Nacional del Comahue, tiene como objetivo general la generación de conocimiento especializado en el área de agentes inteligentes y en lo referente a la representación y el uso del conocimiento en sistemas computacionales basados en la Web, es decir, lo que se ha llamado la Web Semántica. El objetivo general del trabajo de investigación es la extensión de una herramienta de modelado ontológico, denominada crowd, mediante la verbalización de un subconjunto del lenguaje de modelado conceptual UML. Esta integración permitirá generar especificaciones en Lenguaje Natural a partir de un diagrama de clases. Esta línea de investigación se desarrolla en forma colaborativa entre docentesinvestigadores de la Universidad Nacional del Comahue y de la Universidad Nacional del Sur, en el marco de proyectos de investigación financiados por las universidades antes mencionadas.
Towards the automation of program debugging

Program debugging is one of the most important activities in software development. However, given the growing size and complexity of software today, manual debugging is quickly becoming prohibitively time-consuming and expensive. One way to reduce this cost is to automatically lead programmers to the locations of faults, i.e., localize the faults, using run-time information from failed and successful program executions. With this in mind, we propose a fault localization technique named DStar (D*), which has its origins rooted in binary similarity coefficient-based analysis, such that D* can guide programmers to faults without requiring any prior knowledge of program structure or semantics. Via rigorous case studies we show that D* is more effective at fault localization than a host of other contemporary fault localization techniques. Additionally, we present an equivalence relation by virtue of which two or more fault localization techniques may be provably shown to be equivalent, i.e., equally as effective at locating faults. This is an important relation as it can help do away with need for time-consuming and arduous case studies to compare the effectiveness of fault localization techniques, which was previously the norm. It can also be applied to make existing fault localization techniques more efficient without sacrificing effectiveness. However, while fault localization techniques such as D* are quite effective at locating faults, they still suffer from one fundamental limitation in that they offer no guidance as to how the faults may subsequently be fixed, and this is solely left up to the programmer. We therefore, also propose a strategy that combines the processes of fault localization and mutation, to automatically produce potential fixes for faulty programs, while doing so in an efficient manner. Case studies reveal that the strategy holds great promise in the context of automatic fault-fixing. The ultimate goal of this research is to help automate the program debugging process, thereby making it much more efficient and considerably less expensive.
The Surgical and Management Decision-Making Process of BRCA1 and BRCA2 Mutation Carriers

ii Dedication . iv Acknowledgments. v Vita . vi List of Tables . ix List of Figures . x Chapter 1: Background . 1 Hereditary Breast and Ovarian Cancer. 1 HBOC Management . 4 Effects of Management Options on Health and Quality of Life . 8 Management Decision-making Process . 11 Factors Involved in Risk Management Decision-making . 14 Involvement of Others in Decision-making . 18 Chapter 2: Methods . 24 Study Participants . 24 Procedures . 24 viii Data Analysis . 25 Chapter 3: Results . 28 Participant Demographics . 28 Main Study Themes . 29 Decision-making factors. 29 Ease of decision-making. 34 Individuals involved in the decision-making process. 37 Physicians. 39 Genetic counselors. 42 Family and other BRCA1 and BRCA2 carriers. 43 Chapter 4: Discussion . 47 Study Limitations . 56 Practice Implications . 57 Research Recommendations . 57 References . 59 Appendix A: Interview Guide . 70
Automatization of lexicographic work

A new approach to lexicographic work, in which the lexicographer is seen more as a validator of the choices made by computer, was recently envisaged by Rundell and Kilgarriff (2011). In this paper, we describe an experiment using such an approach during the creation of Slovene Lexical Database (Gantar, Krek, 2011). The corpus data, i.e. grammatical relations, collocations, examples, and grammatical labels, were automatically extracted from 1,18-billion-word Gigafida corpus of Slovene. The evaluation of the extracted data consisted of making a comparison between the time spent writing a manual entry and a (semi)-automatic entry, and identifying potential improvements in the extraction algorithm and in the presentation of data. An important finding was that the automatic approach was far more effective than the manual approach, without any significant loss of information. Based on our experience, we would propose a slightly revised version of the approach envisaged by Rundell and Kilgarriff in which the validation of data is left to lower-level linguists or crowd-sourcing, whereas high-level tasks such as meaning description remain the domain of lexicographers. Such an approach indeed reduces the scope of lexicographer’s work, however it also results in the ability of bringing the content to the users more quickly.
A Design of the Extraction System for an Internet Business Region Variation based on OLAP

With the popularization of an internet, the quantity of web information and the online business have been increased. In the online business, it is important to predict to variation of the Internet business region variation. User can need more efficiently target marketing than general marketing. For this purpose, this paper proposes a design of OLAP using Discovery-driven exploration of domain data cube. This design suggests to analyze the Internet business region variation based on domain, and prediction of the change of Internet business region as well. In addition, the appropriation of the result from OLAP design applied by discovery-driven exploration is presented by the comparison between the statistical analysis of domain registration and the statistical analysis of the Internet Business. The performance of the proposed algorithm is analyzed by a series of experiments to identify its various characteristic.
Simplied Methodology for Obtaining the Dynamic Model of Robot Manipulators

The main goal of this manuscript is to present a simplification of the Euler-Lagrange methodology, which allows us to simplify the obtaining of dynamic model of a robot using the intrinsic properties of dynamic model, which allows to reduce the computation time when the model is programmed. Using the L 2 norm, the proposed methodology is compared with the Euler-Lagrange methodology for obtaining a performance index to determine the proposed simplification efficiency. The main contribution of this manuscript is to present a methodology to obtain the completely symmetric dynamic model.
Current concepts in fracture reduction

Summary Fracture management includes preoperative planning, implant selection, fracture reduction, implant application, and postoperative patient management. Fracture reduction can be one of the most challenging parts of the process. Time honoured principles, of gradual progressive traction and counter-traction, to anatomically restore the bone contour are still effective methods of fracture reduction (2). However, new concepts have emerged that incorporate: balanced anaesthesia techniques, image guided minimally invasive implant placement, bone alignment (rather than anatomical reconstruction) for comminuted fractures, and additional methods of achieving mechanical leverage (1, 3, 4, 16). The purpose of this paper is to discuss the decision making process for selecting fracture reduction techniques; and to describe those techniques for achieving and maintaining reduction for specific fractures.
Verification and Test Methods for Access Control Policies/Models

Access control systems are among the most critical of computer security components. Faulty policies, misconfigurations, or flaws in software implementations can result in serious vulnerabilities. To formally and precisely capture the security properties that access control should adhere to, access control models are usually written, bridging the gap in abstraction between policies and mechanisms. Identifying discrepancies between policy specifications and their intended function is crucial because correct implementation and enforcement of policies by applications is based on the premise that the policy specifications are correct. As a result, policy specifications represented by models must undergo rigorous verification and validation through systematic verification and testing to ensure that the policy specifications truly encapsulate the desires of the policy authors. Verifying the conformance of access control policies and models is a non-trivial and critical task, and one important aspect of such verification is to formally check the inconsistency and incompleteness of the model and safety requirements of the policy, because an access control model and its implementation do not necessarily explicitly express the policy, which can also be implicitly embedded by mixing with direct access constraints or other access control models.
A Comparative Study between MFCC and DWT Feature Extraction Technique

Past research in mathematics, acoustics, and speech technology have provided many methods for converting data that can be considered as information if interpreted correctly. In order to find some statistically relevant information from data, it is important to have mechanisms for reducing the information of each segment in the audio signal into features. These features should describe each segment in such a characteristic way that other similar segments can be grouped together by comparing their features. Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. This paper deals with comparative analysis of MFCC and DWT feature extraction technique.
Grounded Theory, Sensitizing Concepts, and Computer-Assisted Theory Building, di Roberto Cipriani

The classical approach in sociology concerns the use of hypotheses and hypothesis testing processes to determine what, if any, effects can be attributed to particular factors in the field being studied. But other scholars suggest another procedure which eliminates the presence of previous hypotheses and privileges an interpretive – as opposed to a hypothetic-deductive – approach to data analysis. However, in the latter approach crucial questions appear for the researcher: how does one approach the data and data analyses to ensure the credibility of findings? Blumer’s suggestion about «sensitizing concepts» seems to be appropriate in order to reach not only a reliable interpretation of data but also the possibility of «building theory». This process could be supported by computer-assisted research, namely using NVivo as dedicated software for qualitative analysis. However, not all kind of operations can be performed by the computer, no matter how appealing the market offering may be. Every single passage has to be monitored, and nothing can be taken for granted.
Deployment of Secure Collaborative Softwares as a Service in a Private Cloud to a Software Factory

—This paper presents a proposal of deploying secure communication services in the cloud for software factory university UNB (University of Brasília - Brazil). The deployment of these services will be conducted in a private cloud, allocated in the CESPE (Centro de Seleção e de Promoção de Eventos) servers. The main service that will be available is the EXPRESSO, which is a system maintained by SERPRO (Serviço Federal de Processamento de Dados). These services increase the productivity of the factory members and increase their collaboration in projects developed internally.