Miracle-dz/UniFAR-FTUs huggingface dataset:
The eNTERFACE&#146;05 Audio-Visual Emotion Database

This paper presents an audio-visual emotion database that can be used as a reference database for testing and evaluating video, audio or joint audio-visual emotion recognition algorithms. Additional uses may include the evaluation of algorithms performing other multimodal signal processing tasks, such as multimodal person identification or audio-visual speech recognition. This paper presents the difficulties involved in the construction of such a multimodal emotion database and the different protocols that have been used to cope with these difficulties. It describes the experimental setup used for the experiments and includes a section related to the segmentation and selection of the video samples, in such a way that the database contains only video sequences carrying the desired affective information. This database is made publicly available for scientific research purposes.
A novel alignment model inspired on IBM Model 1

We present an extension to IBM Model 1 for training word-to-word lexicon probabilities. This model takes into account a given fixed segmentation of the source and target sentences in the estimation of the statistical dictionary. Our experimentation on the Europarl corpus shows that a statistical consistent improvement in the translation quality can be achieved by including our proposed model as a new information source in a log-linear combination of models.
A Simple Uniform Semantics for Concatenation-based Grammar

htmlabstractWe define a more formal version of literal movement grammar (LMG) as outlined in [Gro95c], in such a way that it provides a simple framework that incorporates a large family of grammar formalisms (Head Grammar [Pol84], LCFRS, [Wei88]), PMCFG, [KNSK92] and String Attributed Grammars [Eng86]). The semantics is (both in rewriting and least fixed point definitions) simple and elegant, and sheds some new light on shared properties of the mentioned formalisms. We then define a restricted version called simple LMG and show that it generates languages that are not mildly context sensitive, yet preserves the polynomial time recognition property of LCFRS.
The development of a taste education program for preschoolers and evaluation of a program by parents and childcare personnel

The change in people's dietary life has led to an increase in an intake of processed foods and food chemicals, raising awareness about taste education for preschoolers whose dietary habits start to grow. This study aims to evaluate the effectiveness and satisfaction of parents and childcare personnel after developing a taste education program and demonstrating it in class. A part of the curriculum developed by Piusais and Pierre was referred for the program. After educating 524 preschoolers in child care facilities in Seoul, a satisfaction survey was conducted on the program. The data in this study were analyzed using SPSS 14.0. Statistical analysis was conducted based on the frequency after collecting the data. Mean ± SD used to determine satisfaction with taste education, with preferences marked on a five-point scale and the alpha was set at 0.05. The program includes five teachers' guides with subjects of sweetness, saltiness, sourness, bitterness and harmony of flavor, and ten kinds of teaching tools. For the change in parents' recognition of the need for taste education based on five-point scale, the average of 4.06 ± 0.62 before the program has significantly increased to 4.32 ± 0.52 (P < 0.01). Regarding the change in the preferences for sweetness, saltiness, sourness, and bitterness, the average has increased to 3.83 ± 0.61, 3.62 ± 0.66, 3.64 ± 0.66, and 3.56 ± 0.75 respectively. In an evaluation of instructors in child care facilities, the average scores for education method, education effect, education contents and nutritionists, and teaching tools were at 4.15 ± 0.63, 3.91 ± 0.50, 4.18 ± 0.50, and 3.80 ± 0.56 respectively. In addition, the need for a continuous taste education scored 4.42 ± 0.67. This program has created a positive change in preschoolers' dietary life, therefore the continuation and propagation of the taste education program should be considered.
INTERRELATIONSHIP OF STRESS, BODY IMAGE, NEGATIVE MOOD STATE AND SUSCEPTIBILITY TO ABNORMAL EATING BEHAVIOUR AMONG GAME SPECIFIC FEMALE ATHLETES: AN EXPLORATORY APPROACH

Purpose: To achieve and maintain a perfect body shape athlete often follows restrictive dieting which ultimately leads them to eating disorders. The purpose of the study was to identify whether there is an interrelationship of abnormal eating behaviours, perceived stress, negative mood state and self-perception of body image among athletic population and another was to observe the consequences of negative psychological well-being and game specificity on food choices and frequency. A secondary purpose of this study was to identify the “at risk-eating disorder” participants who were involved in different sports category. Methods: One thirty eight healthy young female participants matched for BMI were selected by purposive sampling. Subjects were divided into 4 categories i.e. aesthetic games group, endurance groups, strength group and healthy controls. Structured questionnaires were used for data collection during their non-competitive session. ANOVA followed by Scheffe’s test was applied to compare different parameters among the groups. Regression model examined the associations among disordered eating behaviours, stress, body shape concern, emotional eating, total mood disturbance and food choice. Findings: Result revealed disordered eating behaviour was significantly prominent in control and aesthetic game group than other two groups. Control group obtained the highest score in stress and emotional eating while aesthetic game group secured the highest score in body shape concern. Mood disturbance was more prevalent in strength group. Body mass index, body shape concern, emotional eating and total mood disturbance were identified as strongest predictor of EAT-26 scores. The result revealed that controls and aesthetic game group exhibit more abnormal eating behaviours than others. Value: This result will help to indicate abnormal eating behaviour and its relation with psychological well-being among female athletic population. Interventions programmes should be designed to cope up with competitive pressure to avoid abnormal eating behaviour. Article visualizations:
Phenotypic and genotypic methods for typing Campylobacter jejuni and Campylobacter coli in poultry 1

Human campylobacteriosis, an infection caused by the bacterium Campylobacter, is a major issue in the United States food system, especially for poultry products. According to the Center for Disease Control, campylobacterosis is estimated to affect over 2.4 million people annually. Campylobacter jejuni and Campylobacter coli are 2 species responsible for the majority of campylobacterosis infections. Phenotypic and genotypic typing methods are often used to discriminate between bacteria at the species and subspecies level and are often used to identify pathogenic organisms, such as C. jejuni and C. coli. This review describes the design as well as advantages and disadvantages for 3 current phenotypic techniques (biotyping, serotyping, and multilocus enzyme electrophoresis) and 6 genotypic techniques (multilocus sequence typing, PCR, pulse-field gel electrophoresis, ribotyping, flagellin typing, and amplified fragment length polymorphisms) for typing pathogenic Campylobacter spp.
RECSA: Resource for Evaluating Cross-lingual Semantic Annotation

In recent years large repositories of structured knowledge (DBpedia, Freebase, YAGO) have become a valuable resource for language technologies, especially for the automatic aggregation of knowledge from textual data. One essential component of language technologies, which leverage such knowledge bases, is the linking of words or phrases in specific text documents with elements from the knowledge base (KB). We call this semantic annotation. In the same time, initiatives like Wikidata try to make those knowledge bases less language dependent in order to allow cross-lingual or language independent knowledge access. This poses a new challenge to semantic annotation tools which typically are language dependent and link documents in one language to a structured knowledge base grounded in the same language. Ultimately, the goal is to construct cross-lingual semantic annotation tools that can link words or phrases in one language to a structured knowledge database in any other language or to a language independent representation. To support this line of research we developed what we believe could serve as a gold standard Resource for Evaluating Cross-lingual Semantic Annotation (RECSA). We compiled a hand-annotated parallel corpus of 300 news articles in three languages with cross-lingual semantic groundings to the English Wikipedia and DBPedia. We hope that this new language resource, which is freely available, will help to establish a standard test set and methodology to comparatively evaluate cross-lingual semantic annotation technologies.
M ULAN : A Java Library for Multi-Label Learning

M ULAN is a Java library for learning from multi-label data. It offers a variety of classiﬁcation, ranking, thresholding and dimensionality reduction algorithms, as well as algorithms for learning from hierarchically structured labels. In addition, it contains an evaluation framework that calculates a rich variety of performance measures
Mathematical Optimization of Simulated Laser Welds on Aluminum Alloys

We present a coupled simulation–optimization procedure fo the improvement of the laser welding process. This is achieved by introducin g a functional to measure the quality of a weld and later performing a mathemat ical optimization of it. The welding process to be included in the functional is simulated using an adaptive finite element method for the thermal and mechanica l subproblems. The functional is optimized using a constrained mathematical o ptimization method and the optimized parameters giving some desired propertie s of the welds are found. In this paper, the results obtained for two di fferent optimization goals are presented, namely a general test problem in which all good prope rties of the welds are assumed to have the same importance, and another in which a g er importance is given to the residual stress and the full penetratio n of the weld.
Evaluation of Matching Accuracy of Template Matching Using a Steganography Algorithm

The steganography that we suggested uses the data that ties strongly to the characteristics of the original image as watermark information without changing the original image. Although similarity with zero-watermarking is pointed out, the major difference is that our method does not need pre-processing for a feature extraction at decoding. Since the decoding can do at high speed, besides using as the original steganography, it is possible to apply it to similar image retrieving, similar image order sorting or template matching. For example, when applying it to medical images, a doctor is possible to pick some similar images from a medical image database and refers the treatments through the images with concealing the information of the patient. This time, we have investigated the identification accuracy of our method with respect to the template matching of similar image searching.
Evaluation of the Agronomic Characters of Sweet Potato Varieties Grown at Varying Levels of Organic and Inorganic Fertilizer

Sweet potato (Solanum tuberosum), a staple tuber crop in parts of the Sudan and Guinea savanna zone of Nigeria is known for its resistance to drought, vigorous early growth and low input requirements. Increase in population which has resulted to land shortages has led to reduction in traditional methods of maintaining soil fertility. Technologies based on combinations of organic and inorganic sources of fertilizer would produce higher and more sustainable yields than either organic or inorganic fertilizer alone or farmers' indigenous management practices. Field trials to evaluate the agronomic characters of two sweet potato varieties were conducted during the wet seasons of 2004 and 2005 at the Institute for Agricultural Research (IAR) farm Samaru Zaria. The treatments consisted of three rates each of organic and inorganic fertilizer and two varieties of sweet potato. Organic and inorganic fertilizer application did not have significant effects on vine length, number of leaves, number of branches and total dry matter. Dan Zaria however produced significantly more number of branches than Dan Bakalori, which is attributed to differences in genetic composition of the sweet potato varieties. Application of organic fertilizer increased the yield of sweet potato in both years. Yield obtained from the variety Dan Bakalori was significantly heavier than that obtained from Dan Zaria. Application of 4t/ha organic fertilizer resulted in the highest yield of sweet potato which was not significant. The result however suggests that further increase in organic fertilizer might lead to increases in yield. This requires further long term studies.
Convergence Verification of Asynchronous Iterations

This paper describes a novel approach to convergence verification of asynchronous iterations in addition to reachability analysis of them. Asynchronous iterations are computation schemes capable of capturing all possible behaviors of distributed systems employing connectionless communication protocols such as UDP/IP. The robustness of these systems against uncertainty in packet delivery can be assured by proving their convergence. We construct some theorems on the basis of fixpoint computations to derive a method for convergence verification, and implement it in trial programs using binary decision diagrams. Theoretical analysis reveals its effectiveness in reducing memory usage, and experimental results support its extreme advantage in execution times. They suggest the possibility of practical use of this method.
System for automated diagnosis in cellular networks based on performance indicators

This paper presents a system for automated diagnosis of problems in a cellular network, which comprises a method and a model. The reasoning method, based on a naive Bayesian classifier, can be applied to the identification of the fault cause in GSM/GPRS, 3G or multi-systems networks. A diagnosis model for GSM/GPRS radio access networks is also described, whose elements are available in the network management systems (NMSs) of most networks. It is shown that the statistical relations among the elements, that is the quantitative part of the model, under certain assumptions, can be completely specified by means of the parameters of beta density functions. In order to support the theoretical concepts, a model has been built based on data from a real network and the automated diagnosis system has been used to classify problems in a cellular network, showing that the solution is easily implemented and that the diagnosis accuracy is very high, therefore leading to a reduction in the operational costs of running the network. Copyright © 2005 AEIT.
CAN THE USE OF A COMPUTER SIMULATION GAME ENHANCE MECHANICAL REASONING ABILITY: AN EXPLORATORY STUDY

This exploratory study sought to discover if transition y ear students interacting with the computer simulation game “The Incredible Machine” co uld enhance their mechanical reasoning abilities. Related research suggests m any educational benefits of computer simulation games. Students worked as groups of 3 or 4 in a collaborative environment. The study followed the structure of a pre-test /po -test control group design. Mechanical reasoning ability was measured using the Differential Aptitude Test for Guidance. An analysis of pre-test and post-te st results revealed no significant improvement between the experimental group and the contro l group. However interesting gender differences were discovered. Signifi cant differences in favour of male participants were discovered in the t-test analys is of both pre-test raw scores and post-test raw scores. No significant difference in the amount of improvement made by males and females in the experimental group was revea led. Observation, together with student feedback provided some evidence of differing patt ern of mouse usage, reactions to the game, interactional styles, and strat egies used by the groups. Recommendations for further research studies are made.
Classification of Polarimetric SAR Images Using Evolutionary RBF Networks

This paper proposes an evolutionary RBF network classifier for polar metric synthetic aperture radar ( SAR) images. The proposed feature extraction process utilizes the full covariance matrix, the gray level co-occurrence matrix (GLCM) based texture features, and the backscattering power (Span) combined with the H/&alpha;/A decomposition, which are projected onto a lower dimensional feature space using principal component analysis. An experimental study is performed using the fully polar metric San Francisco Bay data set acquired by the NASA/Jet Propulsion Laboratory Airborne SAR (AIRSAR) at L-band to evaluate the performance of the proposed classifier. Classification results (in terms of confusion matrix, overall accuracy and classification map) compared to the Wish art and a recent NN-based classifiers demonstrate the effectiveness of the proposed algorithm.
A fuzzy engine model for efficient stock market prediction

The prediction of stock market is considered a non-trivial problem in the financial arena. In the last few years many sophisticated models were developed to predict the stocks in order to achieve a maximum profit. Fuzzy models are one of the powerful methods that are used in this field. This paper proposes a fuzzy engine model that acts as an expert indicator that can generate buy and sell signals. The fuzzy engine model combines the most popular technical indicators with their firing strengths to provide a new fuzzy indicator that achieves good results compared to the other traditional indicators. Experiments were conducted to evaluate the performance of the model and the results prove that the fuzzy engine model gives more reliable buy and sell positions in different time horizons compared to other technical indicators.
Analyzing the dangers posed by Chrome extensions

A common characteristic of modern web browsers is that their functionality can be extended via third-party add-ons. In this paper we focus on Chrome extensions, to which the Chrome browser exports a rich API: extensions can potentially make network requests, access the local file system, get low-level information about running processes, etc. To guard against misuse, Chrome uses a permission system to curtail an extension's privileges. We demonstrate a series of attacks by which extensions can steal data, track user behavior, and collude to elevate their privileges. Although some attacks have previously been reported, we show that subtler versions can easily be devised that are less likely to be prevented by proposed defenses and can evade notice by the user. We quantify the potential danger of attacks by examining how many currently available extensions have sufficient privileges to carry them out. As many web sites do not employ defenses against such attacks, we examine how many popular web sites are vulnerable to each kind of attack. Our results show that a surprisingly large fraction of web sites is vulnerable to many attacks, and a large fraction of currently available extensions is potentially able to carry them out.
MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory

Easy-to-use macromolecular viewers, such as UCSF Chimera, are a standard tool in structural biology. They allow rendering and performing geometric operations on large complexes, such as viruses and ribosomes. Dynamical simulation codes enable modeling of conformational changes, but may require considerable time and many CPUs. There is an unmet demand from structural and molecular biologists for software in the middle ground, which would allow visualization combined with quick and interactive modeling of conformational changes, even of large complexes. This motivates MMB-GUI. MMB uses an internal-coordinate, multiscale approach, yielding as much as a 2000-fold speedup over conventional simulation methods. We use Chimera as an interactive graphical interface to control MMB. We show how this can be used for morphing of macromolecules that can be heterogeneous in biopolymer type, sequence, and chain count, accurately recapitulating structural intermediates. We use MMB-GUI to create a possible trajectory of EF-G mediated gate-passing translocation in the ribosome, with all-atom structures. This shows that the GUI makes modeling of large macromolecules accessible to a wide audience. The morph highlights similarities in tRNA conformational changes as tRNA translocates from A to P and from P to E sites and suggests that tRNA flexibility is critical for translocation completion.
International Conference on Information Systems ( ICIS ) 2010 COMPLEMENTARITY OF THE IMPACT OF ALTERNATIVE SERVICE CHANNELS ON BANK PERFORMANCE

Faced with intense competition, banks have deployed information technology (IT) to serve customers more efficiently and effectively in diverse ways. The challenge bank managers face is in utilizing alternative service channels to win customers and retain competitive advantages. This study investigates the impact of banks’ use of channel mix strategy. We show strong complementarities between traditional branch channel and IT-based self-service channels on performance. The value provided by a channel depends both on its own level of investment and investments in other channels. It can be misleading to examine channels independently or simply view each channel as a substitute for other channels. Even though different channels do substitute each other to some extent, migration of transactions from traditional channels to the IT-based channels may change customers’ overall demand such that it increases demand for all channels by transforming traditional channels to perform more value-added services or serve more profitable customers.