Miracle-dz/UniFAR-FTUs huggingface dataset:
The use of word elicitation to identify distinctive gestural systems on Amami Island

Les As. decrivent une methode de production de mots a partir d'une image et montrent dans quelle mesure elle peut etre utilisee pour identifier differents systemes linguistiques du langage par signes dans une aire geographique, en l'occurrence, l'ile d'Amami au sud du Japon. L'analyse de la coherence lexicale et de l'agencement dans la denomination de 25 mots revele des schemas distincts qui sont correles avec les schemas d'interaction sociale entre les 21 personnes soumises a cette experience. En se basant sur les schemas d'interaction sociale et familiale de ces personnes, les As. identifient les types de systemes gestuels qu'ils attendent de chaque groupe, en les classant en gestes non linguistiques, en signes utilises a la maison de maniere isolee et en signes utilises a la maison d'une maniere plus developpee. Cette methode s'avere etre un outil tres efficace pour identifier la variation dans une communaute utilisant le langage par signes
Foggy Images Classification Based On Features Extraction and SVM

An algorithm of foggy image classification is presented in this paper. First, the RGB images are converted to HSI images and next we analysis the distribution of the histograms of H, S, I plane separately, from which we extract the variance of each plane under different foggy conditions as the HSI model features. Second, the dichromatic atmospheric scattering model is introduced and based on this model we develop an algorithm for computing the angular deviation of different foggy images compared to clear day image as another feature. Finally, we use this feature set to train a multi-class SVM classifier to classify four different levels of foggy images. Experiment results show that the algorithm is more than 90% accurate. Keywords-HSI model; histogram; dichromatic atmospheric scattering model; SVM
What-if analysis and the illusion of control

The research presented hypothesizes that what-if analysis creates an 'illusion of control' which causes people to overestimate its effectiveness. The study reported found that what-if analysis improved performance for about half of the subjects and degraded performance for the rest in a simulated production scheduling task. However, all subjects but one reported believing what-if to be beneficial to their decision performance. Erroneous beliefs persisted in the face of outcome feedback showing inferior performance when what-if analysis was used. In light of other research linking user acceptance to users' performance perceptions, these results indicate the potential for sustained but dysfunctional use of what-if analysis due to overconfidence. <<ETX>>
The Phonetics of Russian

Preface Abbreviations Part I. Phonetic Theory and Transcription: 1. Introduction 2. The organs of speech 3. Breath and voice 4. Vowels and consonants 5. How to learn vowels 6. The classification of vowels 7. How to describe consonants 8. The principles of transcription, phonemes 9. Digraphs Part II. the Phonetics of Russian: 10. Types of Russian pronunciation 11. General notes on the Russian vowels and consonants 12. The Russian vowels in detail 13. The Russian semi-vowel j 14. The Russian diphthongs 15. Labialization and velarization 16. Palatalized consonants and their phonetic representation 17. The Russian plosive consonants 18. The Russian fricative consonants 19. The Russian affricative consonants 20. The Russian nasal consonants 21. The Russian lateral consonants 22. The Russian rolled consonants 23. Similitude and assimilation 24. Accent, stress and length 25. Intonation 26. Passages for practice Appendices Indices.
Advanced age is a risk factor for post-operative complications and mortality after a pancreaticoduodenectomy: a meta-analysis and systematic review.

BACKGROUND The aim of this meta-analysis was to analyse the outcomes of major pancreatic surgery among the elderly (≥75 and ≥80 years of age). METHODS A systematic literature search was conducted using Embase, MEDLINE, Cochrane and PubMed databases on all studies published between January 1990 and April 2012 reporting peri-operative outcomes after a pancreaticoduodenectomy (PD) among the elderly. Primary end-points measured were peri-operative mortality and the incidence of post-operative complications. Secondary outcomes considered included the incidence of post-operative pancreatic fistula formation (POPF), delayed gastric emptying (DGE), wound infection, pneumonia, post-operative bleeding and length of hospital stay. RESULTS Eleven trials were included comprising 5186 patients; 7 studies comparing endpoints in patients aged ≥75 years vs. younger populations and 4 studies comparing endpoints in patients aged ≥80 years vs. younger populations. In both groups, there was a statistically significant increase in the incidence of mortality and post-operative pneumonia in the elderly population. The incidence of post-operative complications was also found to be statistically significant among patients ≥80 years of age vs. their younger cohorts. CONCLUSIONS There is an increased incidence of post-operative mortality and pneumonia after a PD among all elderly patients ≥75 years of age, as well as an increased incidence of post-operative complications among patients ≥80 years of age. Additional randomized control trials studying post-PD operative outcomes in elderly vs. younger patients with standardization of comorbidities is therefore necessary to confirm the conclusions presented here.
Robotics at IBM

A June 1982 article in Inc. magazine reviews the current state of robotics. The modern industrial robot is a development of American inventors and engineers; the first applications were in Ford and General Motors plants in 1961. Despite its original lead in research and applications, however, the United States currently has only 4,100 robots in use. Meanwhile, Japan has 14,246 at work. There are about 150 Japanese robot manufacturers with sales last year of $246 million. During the same period, 30 U.S. manufacturers have had sales of $155.5 million.
The Application of Semantic Similarity in Text Classification

Text classification is a challenging problem which aims to automatically assign unlabeled documents to predefined one or more classes according to its contents. The major problem of text classification is the high dimensionality of the feature space. This paper proposes an approach based on the semantic similarity between the title vectors and the category vectors using the tf*rf weighting method. Experiments show that text classifier based on semantic similarity helps dimension sensitive learning algorithms such as KNN to eliminate the “curse of dimensionality” and as a result makes an important improvement in all categories.
A modified Iterative Amplitude clipping and filtering technique for PAPR reduction in OFDM systems

Orthogonal frequency multiplexing (OFDM) is a promising technique for high data-bit-rate in wireless communication systems. However, one of the major drawback of OFDM is high peak-to-average power ratio (PAPR). In this paper, we propose modified Iterative Amplitude clipping and filtering (IACF) technique to reduce the PAPR in OFDM signal. This paper evaluates PAPR reduction effect with a graded band-limiting filter in the iterative clipping and filtering method. The computer simulation result shows that the proposed method achieves target PAPR using fewer iteration numbers as in conventional method and improves the PAPR and BER performance as compared to conventional Amplitude clipping and filtering (AFC) method.
High Performance Velocity Estimation for Controllers with Short Processing Time by FPGA

In motion control, the number of controllers based on field programmable gate arrays (FPGAs) has increased in recent years owing to the inherent short sampling time. At present, the most commonly implemented velocity estimation methods are the M and T methods. The proposed velocity estimation method reduces the calculation time by eliminating the division operation and prevents reduction in resolution owing to a short sampling time. In addition, the proposed method shows a high performance across a wide range of velocities. Program implementation in FPGAs has a low computational cost and a high calculation speed. The conventional methods present some difficulties in programming using FPGAs owing to the divider implementation. The validity of the proposed method was tested using a velocity controller based on a disturbance observer.
Optimal scheduling with deadline constraints in tree networks

The problem of scheduling time-critical messages over a tree network is considered. Messages arrive at any of the nodes and have to reach the root node before their deadlines expire, else they are considered lost. The network is assumed to be operating in discrete time and the messages need one time unit for transmission from one node to the next along its path. The arrival and deadline processes are arbitrary. The policy which transmits messages with smallest extinction (arrival+deadline) time at every link is shown to minimize the number of lost messages over all time intervals and for every sample path.
A self-terminating low-voltage swing CMOS output driver

A CMOS output pad driver circuit is described that automatically series-terminates a driven line in the line's characteristic impedance. The circuit has advantages in speed, power, and size over conventional designs. The key idea is the use of emitter-coupled logic (ECL) compatible low-voltage swings for signaling, combined with the use of the driver transistor as both a switch and as a termination resistor. An on-chip measurement circuit dynamically adjusts the impedance of the driver to match the impedance of an external reference impedance standard, allowing the circuit to compensate for both chip and board level fabrication variations. >
Evaluation of Feasibility of Ankle Pressure and Foot Oxymetry Values for the Detection of Critical Limb Ischemia in Diabetic Patients

A total of 261 diabetic patients were admitted because of rest pain and/or foot ulcer in 1 limb. Ankle pressure (AP) and transcutaneous oxygen tension (TcPO2) were measured, and digital subtraction arteriography was performed. Transcutaneous oxygen tension was <30 mm Hg in 213 patients and ≥30<50 mm Hg in 48 patients. Ankle pressure could not be measured in 109 patients. In 50 patients, AP was <70 mm Hg and in 102 patients, it was ≥70 mm Hg. Arteriography showed evidence of stenoses >50% of vessel lumen diameter in all patients. Major amputation was performed in 16 patients; AP was <70 mm Hg in 4 patients and ≥70 mm Hg in 6. It was not practicable in the remaining 6 patients. Transcutaneous oxygen tension was <30 mm Hg in 15 patients and ≥30 mm Hg in 1 patient. For diagnosis of critical limb ischemia (CLI) in diabetic patients presenting with rest pain or foot ulcer, measurement of TcPO 2 is essential not only when AP is not measurable but also when this value is ≥70 mm Hg.
Word category prediction based on neural network

This paper proposes a new method of the word category prediction for the speech recognition system. In order to improve the speech recognition results, not only the acoustical information but also certain linguistic information is needed. World category prediction is a very effective method to implement an accurate word recognition system. Traditional statistical approaches require considerable training data to estimate the probabilities of word sequences, and many parameters to memorize probabilities. And it is difficult to predict unseen data which does not include the training data. To solve this problem, NETgram, which is the neural network for word category prediction, is proposed. The performance of the NETgram is comparable to that of the statistical model although the NETgram requires fewer parameters than the statistical model. Also the NETgram performs effectively for unknown data, i.e., the NETgram interpolates sparse training data. Results of analyzing the NETgram show that the NETgram learns .
Characteristics of a buck converter with new control scheme using a triangle waveform modulated by output voltage

In this paper, the authors propose a new control scheme in which the output voltage is fed back into a triangle waveform of a control circuit to improve the transient response of a switching converter. The circuit structure of the proposed system is very simple and will therefore reduce the size and weight of the apparatus and have reduced production costs. Also, because an error amplifier is not used, the circuit is not affected by switching noise or the like and the circuit is easy to design. In this paper, the proposed system is applied to a synchronous rectifying buck converter; the basic properties are analyzed and the system is verified experimentally. As a result, it was confirmed that the proposed scheme has superior regulation properties and transient response characteristics. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 90(7): 52–59, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.20256
Strand Spaces: Proving Security Protocols Correct

A strand is a sequence of events; it represents either an execution by a legitimate party in a security protocol or else a sequence of actions by a penetrator. A strand space is a collection of strands, equipped with a graph structure generated by causal interaction. In this framework, protocol correctness claims may be expressed in terms of the connections between strands of different kinds. Preparing for a first example, the Needham-Schroeder-Lowe protocol, we prove a lemma that gives a bound on the abilities of the penetrator in any protocol. Our analysis of the example gives a detailed view of the conditions under which it achieves authentication and protects the secrecy of the values exchanged. We also use our proof methods to explain why the original Needham-Schroeder protocol fails. Before turning to a second example, we introduce ideals as a method to prove additional bounds on the abilities of the penetrator. We can then prove a number of correctness properties of the Otway-Rees protocol, and we clarify its limitations. We believe that our approach is distinguished from other work by the simplicity of the model, the precision of the results it produces, and the ease of developing intelligible and reliable proofs even without automated support.
NOISE ANALYSIS AND MODELLING WITH NEURAL NETWORKS AND GENETIC ALGORITHMS

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver's chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features. The available {rotation, noise level} data series were compactly described by means of a reduced set of characteristic features obtained by computing the Discrete Wavelet Transform (DWT) and keeping only the most significant coefficients, which act as the true target series to be modeled. A neural network of RBF type was used to model the relationship between the constructive parameters vectors and the DWT coefficients. The training procedure is based on the Genetic Algorithms (GA) approach. An accurate input-output model was obtained, enabling the interpretation of the found dependencies. This was accomplished through sensitivity analysis, which measures the effect of including or eliminating each constructive parameter on the perceived noise level.
Integrating an educational 3D game in Moodle

Different approaches have demonstrated that learning improves when implemented in a constructivist and social way. In addition, electronic games and simulations are perceived to have high educational value because of their motivational and emotional factors. This potential value can be developed by defining appropriate scenarios in which players are presented learning objectives with playable goals using different strategies. The authors introduce a prototype intended to include such scenarios in learning flows, partially integrating the learning management system Moodle and BioWare's game Neverwinter Nights. First, the authors analyze the reasons and background that support their proposal. They then provide a description of the motivational and cognitive factors that influence human interaction with video games (especially 3D games) and learning. The implemented prototype is then introduced, taking into account scenarios, roles, environments, and how collaboration is implemented. Finally, the authors present their conclusions.
Evaluating Behavioral Change in Multigroup Collaboration for Content Publishing Over the Web

In this article, an evaluation of the behavioral change of groups collaborating towards the production of multilingual digital content is provided by using the data publication duration times as a proxy. In parallel, the assessment of feedback as a stimulant of social behavior in developing such systems is given. The evaluation is based on a system developed by a consortium of experts in the context of a European project towards the provision of an eServices platform on Organic Agriculture (OA). Group behavior of the partners involved is studied and analyzed using regression models for the extraction of trends and patterns while the results of their collaboration are discussed and valuable conclusions regarding the improvement of collaborative work over the Internet are presented.
Adaptive Histogram Equalization And Its Applications

This paper describes an efficient array-processor implementation of an adaptive histogram equalization algorithm for digital image enhancement. The algorithm is based on a sliding window approach, and computes local histograms and grey level mappings for generating uniform (equalized) histograms for each pixel location. Equivalently, this method can be interpreted as generating local maximum entropy representations of the original image data. For sample digital imagery, it is shown that on the average, a 62% increase in local entropy can be obtained. In addition, the effects of adjusting key parameters (such as local brightness, gain, etc.) upon processed imagery are discussed. The technique has been applied to the analysis of high quality digital imagery and found to be particularly effective for accentuating subtle texture and detail in the data.
A Statistical Model for Real-Time Video Moving Target Detection Based on Bayesian Statistics

Video moving target detection is an important foundation issues in computer vision, based on the analysis of the advantages and disadvantages of each existing moving target detection model, using Bayesian statistical theory as a framework, proposes a statistical model that can detect moving objects in video in real-time. The model combines time, space and color and other relevant information of pixel, divides and extracts Video segmentation’s foreground. By selecting the appropriate reference background can improve the precision and accuracy of the detection.
Exploring Insights through Visualization of Association Rules from Text Mining Statistics

Visualization is an important technique for analysis of knowledge derived from text mining. While different approaches exist for visualization, this paper presents a novel way of visualizing the strength of association between multiple terms that summarizes association in the form of a matrix. This approach is expected to improve the way decision makers analyze insights from text mining.
Simultaneous retrievals of soil moisture and vegetation biomass from multi-configuration passive microwave measurements

A modeling approach is implemented to retrieve simultaneously soil and vegetation parameters from low-frequency microwave observations. The microwave observations were performed over a wheat field at L- and C-band. The model algorithm is based on a simple radiative transfer approach. The optical thickness /spl tau/ is assumed to be proportional to the vegetation water content VWC. Two model parameters are used: r/sub /spl tau// and C/sub pol/. The parameter r/sub /spl tau// is the ratio of the optical thickness at L- and C-band. The parameter C/sub pol/ is used to parameterize /spl tau/ as a function of view angle and polarization. Using the inversion algorithm based on microwave and thermal infrared measurements, both soil moisture and VWC are retrieved during the vegetation cycle and during a four-hour irrigation phase. The study shows the inversion algorithm can provide accurate estimates of both soil moisture and vegetation biomass. The analysis also clearly demonstrates the high potential of the low-frequency passive microwave observations to monitor soil and vegetation characteristics.
HMM-based operational gesture recognition method

This paper introduces a gesture recognition method based on HMM (Hidden Markov Model). Because of HMM's special advantage in coping with temporal sequence, we used it on matching input gesture sequence with the typical gesture sequence, it not only get a good correctness and fault tolerance, but also can determine the begin and end of gestures from a series of input images. And using the skin distribution as gesture features got a robust result.
Feature extraction for early auditory-visual integration

Sonar operators combine auditory and visual information to make decisions relating to target detection and identification. Many past attempts to automate the role of sonar operators have only considered the visual information and have been unsuccessful. An assessment has been made of the auditory component of the sonar operator role. This information has been used to select three algorithms with the potential for detecting features that discriminate between target types. Results are presented of the application of these algorithms to relevant time series data. Subsequently the usage of these features is discussed in terms of the concept of early auditory-visual integration. (5 pages)
Capabilities‐based educational equivalency units: Beginning a professional dialogue

Abstract This article proposes a basic model for the transformation of academic equivalency in distance education, shifting from a unit of measurement that relies on time in the classroom (the Carnegie unit) to one that focuses on learner achievement. The Capabilities‐Based Educational Equivalency (CBEE) model puts forward a framework of academic equivalency that is founded on valid and useful instructional design objectives. While allowing time to be variable (rather than constant) and holding academic achievement relatively constant, the CBEE model permits the comparison of student achievement in face‐to‐face and distance education, as well as between programs delivering instruction via a wide variety of media.
Dynamic testing of control systems

The paper reviews the manual, computer-controlled, and computer-based dynamic testing of control systems, and the reasons for the popularity of such tests. It is shown that correlation techniques are necessary in either time or frequency domains in order to reduce uncertainty due to measurement noise. Engineering guidelines for choosing those test measurements, such as spot frequencies and cross-correlation function time delays, which contain the most useful information for system checkout are included, so that the test time necessary to achieve user confidence in the particular product may be considerably reduced. Hardware examples are used throughout to illustrate the approach.