Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconnaissance automatique de gestes manuels en langue des signes

Nous abordons dans ce papier la reconnaissance automa-tique de gestes manuels statiques pour des applications en langue des signes. Dans un travail precedent, nous avons propose une methode de reconnaissance de formes (classification et recherche) basee sur le recalage et les geode-siques de formes. Cette methode est concue pour etre ro-buste aux points aberrants et aux variabilites interindivi-duelles. Cette robustesse peut parfois mener a des confusions lorsque nous travaillons avec des classes de formes a faible dissemblance et donc a faible separabilite. La diffe-rence entre ces classes de formes serait consideree comme donnee aberrante. Dans cet article, nous revisons notre methode de reconnaissance de formes pour bien s'adap-ter aux classes a faible dissemblance. Nous nous placons en particulier dans le contexte de la reconnaissance de gestes manuels. Les resultats experimentaux sur la base de reference GESTURES montrent tout l'interet de notre approche. Mots Clefs Langue de signes, reconnaissance de formes, recalage, ro-bustesse. Abstract This paper deals with the static hand gesture recognition for sign language applications. In a previous work, we proposed a method of pattern recognition (classification and research) based on robust registration and shapes geode-sics. This robustness may lead sometimes to errors when dealing with databases with low variability among shape classes so low separability. The difference between these classes could be interpreted as aberrant data. In this paper , we revise and adjust our method to be adapted for classes with low dissimilarity. We consider particularly the problem of gesture recognition. Experimental results on the GESTURES test base show the advantage of our approach.
Apriori Based Algorithms And Their Comparisons

— Mining frequent itemsets from the large transactional database is a very critical and important task. The first algorithm for mining all frequent itemsets and strong association rules was the AIS algorithm by [2]. Shortly after that, the algorithm was improved and renamed Apriori. Apriori algorithm is the most classical and important algorithm for mining frequent itemsets. This paper aims to presents a basic Concepts of some of the algorithms (Direct Hashing and Pruning (DHP), Partitioning, Sampling, Dynamic Itemset Counting (DIC), Improved Apriori algorithm) based upon the Apriori like algorithm for mining the frequent item sets along with their capabilities and comparisons.
Scheduling in packet switches with relaxed constraint

In this thesis, I present a series of new scheduling algorithms for an ATM-like crossbar input-queued switching fabric of an IP router. These new scheduling algorithms are developed based on three popular existing scheduling algorithms: Parallel Iterative Matching, Round Robin Matching, and Iterative Round Robin Matching with SLIP. The basic idea of our research is to divide all outputs of the IP router into a few groups. All outputs in the same output group are multiplexed into a high-speed link. Cells (traffic) can be directed to a group of outputs instead of an individual output. The performance of our new scheduling algorithms are measured with simulation. The simulation results indicate that our new scheduling algorithms can achieve an excellent throughput while consuming much less computing time than existing scheduling algorithms.
UH-60A airloads data acquisition and processing system

National Aeronautics and Space Administration, Ames Research Center, recently completed the joint NASA/Army UH-60A Airloads Program. The objective of this program was to make in-flight the measurements of rotor blade airloads, blade vortex interaction, and blade acoustics. An advanced digital instrumentation system, capable of synchronous acquisition of several hundred high frequency pressure channels was designed and developed to gather the required airloads data. The instrumentation system was designed to operate on the rotor hub of a Blackhawk helicopter acquiring data, in night, from pressure transducers, strain gauges, and accelerometers embedded in the rotor blade, built under contract by Sikorsky Aircraft. A parallel effort was initiated to develop a ground telemetry system with the capability to handle the 7.5 megabits per second PCM-encoded telemetry data, generated by the instrumentation system, in real-time. The purpose of this paper is to describe the design and performance of the rotary data acquisition system which was used to digitally acquire high speed rotor blade pressure data. These data were found to achieve the flight test research objectives of the UH-60A Airloads Program. <<ETX>>
Policies for distributed systems and networks : international workshop, POLICY 2001, Bristol, UK, January 29-31, 2001 : proceedings

Policy Specification and Analysis. - Author Obliged to Submit Paper before 4 July: Policies in an Enterprise Specification. - The Ponder Policy Specification Language. - IPSec/VPN Security Policy: Correctness, Conflict Detection, and Resolution. - Monitors for History-Based Policies. - RBAC and Security Policy. - A Type/Domain Security Policy for Internet Transmission, Sharing, and Archiving of Medical and Biological Data. - Tower: A Language for Role Based Access Control. - Translating Role-Based Access Control Policy within Context. - Model-Based Tool-Assistance for Packet-Filter Design. - Network Policy Realization. - Policy Based SLA Management in Enterprise Networks. - Integrating Goal Specification in Policy-Based Management. - Taxonomy and Description of Policy Combination Methods. - Issues in Managing Soft QoS Requirements in Distributed Systems Using a Policy-Based Framework. - Perspectives on Policy Architectures. - A Policy Based Management Architecture for Large Scale Active Communication Systems. - Policy-Driven Management of Agent Systems. - On Policy-Based Extensible Hierarchical Network Management in QoS-Enabled IP Networks. - Towards Extensible Policy Enforcement Points.
An authenticated key agreement scheme for sensor networks

In wireless sensor networks, the messages between pairs of communicating nodes are open to eavesdropping, tampering, and forgeries. These messages can easily be protected using cryptographic means but the nodes need to share a common secret pairwise key. This thesis proposes a new scheme, the Blom-Yang key agreement (BYka) scheme, that enables pairs of sensor nodes in large networks to compute their pairwise keys quickly and efficiently. Prior to deployment, the Trusted Authority (TA), assigns each node their public IDs, and using its master keys, computes and stores in the nodes their private key-sets. When a pair of nodes need to obtain their pairwise keys, they exchange their public key identifier IDs which are just 16-bit integers. Using the counterpart’s ID with its own set of private keys, the nodes are able to compute a large common pairwise key, but only if they have obtained their keying material from the same TA. Hence, the scheme is also mutually authenticating. The computations use simple arithmetic operations which are fast and efficient, easily undertaken by sensor devices which have limited computational, memory, and energy resources. For example, it is able to compute keys of 128 bits in 279 milliseconds in the MICAz mote, requiring 1170 bytes of memory to store the private keying material. Similar key agreement schemes, already widely used in computer networks, use public key cryptographic algorithms which require computationally expensive mathematical operations, taking much longer time, and requiring much more resources. The security of the BYka scheme is based on the difficulty of obtaining information
Zastosowanie algorytmów przeszukiwania grafów do analizy obrazów medycznych

There are many methods for image segmentation [1, 2]: threshold, area, edge and hybrid methods. Area methods indicate groups of similar pixels form local regions [3, 4]. Edge methods detect boundaries between homogeneous segments [5, 6, 7]. In this paper we present the results of tests of unconventional implementation of graph search methods for the analysis of images generated from magnetic resonance imaging [8]. We explored the effectiveness of different approaches for dividing areas within a similar gray scale, using adapted graph search algorithms (DFS, BFS) after appropriate modification (Fig. 1). For this purpose, the Weka package (a tool for pre-processing, classification, regression, clustering and data visualization) was used [9]. A training set was generated after analyzing all the series of images from the database. First, we evaluated models created using certain algorithms and compared their efficacy (Tab. 1). This was followed by a selection of attributes (Tab. 2) and a re-evaluation of the models (Tab. 3). Comparison of the results of both evaluations showed that after selection of the relevant product attributes, you can achieve up to 100% detection of patients with hydrocephalus and over 90% proper recognition of healthy persons. This encourages further research and observation, such as whether persons wrongly classified as sick actually developed the disease in time. We designed a web application for the study, written in Windows Azure, as well as a GUI for automatic processing of a series of images (Fig. 2).
Méthodes pour l'archéologie linguistique : datation par combinaison d'indices temporels

Résumé. Dans cet article, nous présentons notre participation au défi fouille de texte (DEFT) 2011 à la tâche de datation d’un document. Notre approche est fondée sur une combinaison de plusieurs sous-systèmes, certains supervisés, d’autres non supervisés, et utilise plusieurs ressources externes comme Wikipédia, les Google Books n-grams ainsi que des connaissances sur les réformes orthographiques du français. Notre meilleur système obtient un score de 0,378 sur les portions de 300 mots et de 0,452 sur les portions de 500 mots, ce qui représente 37% de décennies correctes et 10% d’années correctes au premier rang sur les portions de 300 mots, et 42% de décennies correctes et 14% d’années correctes au premier rang sur les portions de 500 mots.
Performance impact of programmer-inserted Data Prefetches for irregular access patterns with a case study of FMM VList algorithm

Data Prefetching is a well-known technique to speed up applications wherein hardware prefetchers or compilers speculatively prefetch data into caches closer to the processor to ensure it’s readily available when the processor demands it. Since incorrect speculation leads to prefetching useless data which, in turn, results in wasting memory bandwidth and polluting caches, prefetch mechanisms are usually conservative and prefetch on spotting fairly regular access patterns only. This gives the programmer with a knowledge of application, an opportunity to insert fine-grain software prefetches in the code to clinically prefetch the data that is certain to be demanded but whose access pattern is not too obvious for hardware prefetchers or compiler to detect. In this study, the author demonstrates the performance improvement obtained by such programmer-inserted prefetches with the case study of an FMM (Fast Multipole Method) VList application kernel run with several different configurations. The VList computation requires computing the Hadamard product of matrices. However, the way each node of the octree is stored in the memory, leads to indirect accessing of elements where memory accesses themselves are not sequential but the pointers pointing to those
A resource estimation method based on timed Petri net for discrete production systems

This work presents a method for modelling and resource estimation of production systems. A production system transforms raw material into products. Such products may be composed of parts in a given determined order. Therefore, there is a flow of raw material or parts inside the system. The production planning of products depends on economics factors and also of the amount of available capital for investments. These factors are basically related to market demands, customer preferences, availability of raw material and supplies. Based on the planning, the number and the type of resources used on the shop floor have to be defined. However, one important problem that should be taken into account is the number of resources needed to carry out the planning considering the minimal makespan time. Solving this problem means to reduce the production costs. Due to this fact, the main goal of this work is to introduce a Petri net based approach to solve the mentioned problem for Discrete Production Systems (DPS). Besides, a Petri net based approach for modeling is also presented.
The Impact of Ubiquitous Computing in the Internet Age: How Middle School Teachers Integrated Wirel

This study investigated teacher experiences that emerged as a result of the introduction of wireless technology that placed personal laptops in the hands of every student in their classrooms. Five themes emerged as major factors during the transition to the effective use of ubiquitous technology in the classroom and its positive effects on teachers, including administrative expectations, knowledge acquisition, methods of teaching, teacher/student relationships, and teacher/teacher relationships.
Successive Test Case Generation (STCG) Algorithm for Metamorphic Testing to Generate Follow-up Test Cases

Generating the more efficient dynamic test cases became a challenging task, which improvises the test result accuracy while testing a software application. Metamorphic Testing (MT) has emerged as successful and proven methodology to alleviate the design of complex test oracles in software testing since last decade. Generating the follow-up test cases is the featured advantage of Metamorphic Testing to reveal the hidden bug information from underlying software applications. But earlier research scholars of Metamorphic Testing were used the traditional follow-up test case generation strategies, which are suffering from inadequate or no training data set which leads to inefficient test case generation. Because of this limitation, MT is unable to reach the expected performance in testing of a software application. In this paper, we introduced a Successive Test Case Generation (STCG) Algorithm in the area of Metamorphic Testing to generate the efficient follow-up test cases to identify the hidden bug’s information. STCG algorithm is designed as to implement a supervised training data set, to direct the follow-up test case generation strategy to generate the next level cases. STCG algorithm is different from the traditional algorithm in the way of mapping the relations based on rank values. Experimental results are showing that our approach is having high scalability than other approaches.
The design and implementation of the self compiler, an optimizing compiler for object-oriented programming languages

Object-oriented programming languages promise improved programmer productivity through abstract data types, inheritance, and message passing. Unfortunately, traditional implementations of object-oriented language features are much slower than traditional implementations of their non-object-oriented counterparts. This dissertation describes a collection of implementation techniques that can improve the run-time performance of object-oriented languages. The new techniques identify those messages whose receiver can only be of a single representation and eliminate the overhead of message passing by replacing the message with a normal direct procedure call; these direct procedure calls are then amenable to traditional inline-expansion. Type analysis extracts representation-level type information about the receivers of messages. Customization transforms a single source method into several compiled versions, each version specific to a particular inheriting receiver type; customization allows all messages to self to be inlined away (or at least replaced with direct procedure calls). To avoid generating too much compiled code, the compiler is invoked at run-time, generating customized versions only for those method/receiver type pairs used by a particular program. Splitting transforms a single path through a source method into multiple separate fragments of compiled code, each fragment specific to a particular combination of run-time types. Messages to expressions of these discriminated types can then be optimized away in the split versions. These techniques have been implemented as part of the compiler for the SELF language, a purely object-oriented language designed as a refinement of Smalltalk-80. If only pre-existing implementation technology were used for SELF, programs in SELF would run one to two orders of magnitude slower than their counterparts written in a traditional non-object-oriented language. However, by applying the techniques described in this dissertation, the performance of the SELF system is five times better than the fastest Smalltalk-80 system, better than that of an optimizing Scheme implementation, and close to half that of an optimizing C implementation. These techniques could be applied to other object-oriented languages to boost their performance or enable a more object-oriented programming style.
Modified stack search algorithm for VQ-based tree encoding

A modified stack algorithm for VQ-based tree encoding on image compression applications is presented. The encoding process in vector quantization (VQ) is computationally intensive due to its massive search computation operations. There are, generally, two approaches developed to overcome this problem. One is a fast full search approach and the other is a tree search approach (or tree-structured VQ). A modified stack algorithm which is based on a perfectly regular data structure, "stack", for binary tree search is proposed. Some appropriate metric functions for stack tree search in the VQ-based codebook tree are also suggested. The experimental results that show the improvement over the binary search are reported.
Parametric representation of musical sounds

The rationale of this research work was to find appropriate sound parameters on the basis of which it is possible to discern musical instrument sounds. A review of parameters used in musical acoustics was carried out focusing on the frequency-domain. Some of parameters were extracted from sound representations. Then, the quality of calculated parameters was tested statistically. Additionally, some discretization methods were applied in order to create so-called feature vectors that are to be used for feeding inputs of decision algorithms. Experimental results and conclusions are showed in the paper.
A 'propagative' approach to sensitivity analysis

It is shown that the computational cost of traditional approaches to sensitivity analysis is logically unnecessary and can be largely avoided by propagating and combining sensitivities during a computation, rather than recomputing them. This propagative approach to sensitivity analysis is described and the algorithm implemented to explore its potential is presented. Initial results indicate that this approach has tremendous potential, reducing a combinatorial process to a linear one. In addition, it is noted that the approach has implications beyond sensitivity analysis: it suggests a novel computational paradigm in which functions replace themselves by approximations when they are first called and these approximations are used for the remainder of a computation, e.g. to improve performance. Sensitivity analysis is simply one instance of this approach, using linear approximations based on partial derivatives; however, the approach and the computational environment implemented allow arbitrary approximations to be used. <<ETX>>
Progress in Speech Recognition for Romanian Language

In this chapter we will present the progress made in automatic speech recognition for Romanian language based on the ASRS_RL (Automatic Speech Recognition System for Romanian Language) research platform. Speech recognition is a research domain with a long history, but despite this fact, still open for new investigations and answers to the not yet finally solved questions. This situation can be explained by the difficulty of the task, underlying on the fact that speech is a human product, with a high degree of correlation in content, but with a great variability in the formal manifestation as an acoustic signal. Great difficulties cause also the imperfection of the audio chain and the noises in the environment. The best-known strategies for speech recognition are the statistical and the connectionist ones, but fuzzy sets can also play an important role. Based on HMM’s the statistical strategies have many advantages, among them being recalled: rich mathematical framework, powerful learning and decoding methods, good sequences handling capabilities, flexible topology for statistical phonology and syntax. The disadvantages lie in the poor discrimination between the models and in the unrealistic assumptions that must be made to construct the HMM’s theory, namely the independence of the successive feature frames (input vectors) and the first order Markov process. Based on artificial neural networks (ANNs), the connectionist strategies for speech recognition have the advantages of the massive parallelism, good adaptation, efficient algorithms for solving classification problems and intrinsic discriminative properties. However, the neural nets have difficulties in handling the temporal dependencies inherent in speech data. The learning capabilities of the statistical and the neural models are very important, classifier built on such bases having the possibility to recognize new, unknown patterns with the experience obtained by training. The introduction of fuzzy sets allows on one hand the so-called fuzzy decisions, on other hand the “fuzzyfication” of input data, often more suitable for recognition of pattern produced by human beings, by speaking, for example. In a fuzzy decision, the recognizer realizes the classification based on the degree of membership to a given class for the pattern to be classified, a pattern belonging in a certain measure to each of the possible classes. This O pe n A cc es s D at ab as e w w w . ite ch on lin e. co m
A Transliteration Algorithm for Adapting a Japanese Voice Controlled Browser to English

We propose a novel algorithm to transliterate English to Japanese and its application to a voice controlled browser, which enable ordinary Japanese people to browse English Web site by voice. Speech recognition software designed for native English speakers do not work for most Japanese because Japanese can’t pronounce English as native English speakers do. Therefore, we combined Japanese speech recognition software with English-to-Japanese transliteration software. The accuracy of our transliteration algorithm is 80 % recall for the top candidate, and 92 % recall for the top three candidates. The browser using this transliteration algorithm makes it possible for Japanese to navigate English Web pages almost as accurate as Japanese pages by voice commands.
The Aṣṭādhyāyī of Pāṇini

This book represents the first attempt in the history of the world to describe and analyse the components of a language on scientific lines. It has been acclaimed as the first and foremost specimen of decriptive grammar but has also been the chief source of inspiration for the linguist engaged in describing languages of different regions. To understand Sanskrit language, and especially that part of it which embodies the highest aspirations of ancient Aryan people, the Brahmanas, Samhitas, Upanishads, it is absolutely necessary to have a complete knowledge of the Grammar elaborated by Panini. yThe present work is an english translation of Ashtadhyayi in two volumes.