Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining High Quality Clusters of SAGE Data

Analysis of Gene Expression (SAGE) is a method that allows the quantitative and simultaneous analysis of the whole gene function of a cell. One of the advantages of this method is that the experimenter does not have to select a priori the mRNA sequences that will be counted in a sample. This makes SAGE a powerful tool for analyzing gene expression and studying various diseases, such as cancer. An important concern in cancer studies is the discovery of the differences between healthy and cancerous samples and the accurate separation of these two groups of samples. However, the high dimensionality of the data, the multiple cell sources (i.e. bulk and cell line) and the multiple cancer subtypes make very difficult the effective clustering of SAGE libraries. Furthermore, the various sources of noise pose an extra challenge to data miners. For all these reasons we propose an approach that involves the discretization of the data, the selection of the most prominent gene tags and the use of a clustering algorithm in order to obtain more compact and reliable clusters that can assist cancer profiling. We experimented with two families of clustering algorithms, partitional and hierarchical, and we utilized various cluster validity criteria in order to evaluate the resulted clustering structures. The experimental results have shown that our approach provides more interesting clustering structures.
FANATISME DAN AGRESIVITAS SUPORTER KLUB SEPAK BOLA

Penelitian ini bertujuan untuk mengetahui sejauh mana hubungan antara fanatisme dengan agresivitas pada supporter sepak bola. Penelitian ini dilakukan dengan metode kuantitatif. Subjek dalam penelitian ini adalah 97 orang yang terdiri dari suporter klub sepak bola Persija Jakarta (The Jakmania) dan suporter klub sepak bola Persib Bandung (Viking). Hasil perhitungan korelasi diketahui bahwa signifikansi antara variabel fanatisme dan agresivitas adalah sebesar 0,038 dan R=0,181. Hasil analisis diketahui bahwa terdapat hubungan yang signifikan antara fanatisme dengan agresivitas pada suporter sepak bola. Koefisien R menunjukkan bahwa hubungan antara fanatisme dan agresivitas berada pada taraf hubungan yang sangat lemah. Kata K unci: Fanatisme, Agresivitas, Suporter Sepak Bola
A New Method to Evaluate Good Design for Brand Recognition in the Digital World

: Visual aesthetics has become a crucial element in strengthening brand experience. In the digital era, however, designers need to approach aesthetics from a holistic standpoint where both traditional and more modern factors are taken into consideration. In this paper we present digital BrandUX, a new method to improve brand consistency through the evaluation of aesthetic features. It builds on the Design Format Analysis (DFA) of Warell (2001) with the addition of a structured step-by-step approach. To test the method we analysed two web sites using both DFA and digital BrandUX. The results showed that digital BrandUX is a promising advance in aesthetic evaluation, assisting designers in identifying a greater number of visual aesthetic features. Moreover, the method ensured that the designers explored and identified all types of factors, with the exception of language. Future lines include the development of a handbook to improve ease of use of the method.
Visual Exploration and Comparative Analytics of Multidimensional Data Sets

Recently, rapidly growing amounts of data with numerous attributes and variables arise in various areas of science, engineering, business, and others. Analysis of the multi-faceted information contained in multidimensional data sets has already led to breakthroughs in many fields and emergence of new information-based industries. For instance, insights from business data can enable marketing experts to make better decisions, such as optimizing operations, preventing threats and fraud, capitalizing on new sources of revenue, and deepening customer engagement. Data with high dimensionality and complexity has far exceeded our human ability for comprehension without powerful tools. While many advanced computational models and algorithms have been developed for discovering useful information in multidimensional data sets, these fully-automated approaches may not work well when users only have vague hypotheses or even no hypothesis before analyzing the data. Visualization enhances human’s understanding by organizing information in graphical display, offering the possibility of visual exploration of data for knowledge discovery and sense-making. Visual exploration strengthens human perceptual capabilities with visual interfaces to guide data navigation, actively engaging users into the exploration process to make knowledge discovery much more efficient. However, due to the increasing heterogeneity and complexity of multidimensional data, the multidimensional data space exceeds human comprehension. Novel representations are needed to display and organize data
ENTORNOS PERSONALES DE APRENDIZAJE: ESTADO DE LA SITUACIÓN EN LA FACULTAD DE CIENCIAS DE LA EDUCACIÓN DE LA UNIVERSIDAD DE MÁLAGA. PERSONAL LEARNING ENVIRONMENTS: STATE OF SITUATION IN THE SCHOOL OF EDUCATION AT THE UNIVERSITY OF MALAGA.

Este articulo esta basado en un estudio realizado con el objetivo de conocer el papel que los entornos personales de aprendizaje (PLE) juegan en la formacion del alumnado de la Facultad de Ciencias de la Educacion de la Universidad de Malaga. Se ha estudiado cuales son las aplicaciones y herramientas que mas emplea el alumnado en su aprendizaje no formal. Se puede concluir que, en general, el alumnado no utiliza efectivamente los medios de los que disponen y los que lo hacen no asocian el empleo de los PLE con usos academicos. Palabras clave: entornos personales de aprendizaje, universidad, aprendizaje no formal, TIC.
Enhancing feature selection with contextual relatedness filtering using Wikipedia

ENHANCING FEATURE SELECTION WITH CONTEXTUAL RELATEDNESS FILTERING USING WIKIPEDIA Melih Baydar M.S. in Computer Engineering Advisor: Fazlı Can August 2017 Feature selection is an important component of information retrieval and natural language processing applications. It is used to extract distinguishing terms for a group of documents; such terms, for example, can be used for clustering, multi-document summarization and classification. The selected features are not always the best representatives of the documents due to some noisy terms. Addressing this issue, our contribution is twofold. First, we present a novel approach of filtering out the noisy, unrelated terms from the feature lists with the usage of contextual relatedness information of terms to their topics in order to enhance the feature set quality. Second, we propose a new method to assess the contextual relatedness of terms to the topic of their documents. Our approach automatically decides the contextual relatedness of a term to the topic of a set of documents using co-occurrences with the distinguishing terms of the document set inside an external knowledge source, Wikipedia for our work. Deletion of unrelated terms from the feature lists gives a better, more related set of features. We evaluate our approach for cluster labeling problem where feature sets for clusters can be used as label candidates. We work on commonly used 20NG and ODP datasets for the cluster labeling problem, finding that it successfully detects relevancy information of terms to topics, and filtering out irrelevant label candidates results in significantly improved cluster labeling quality.
Modelling infection risk due to environmental contamination in hospital single and multi-bed ward accommodation

This research considers whether hospital single rooms are better than multi-bed accommodation at reducing the risk of healthcare-acquired infections. The focus is to provide a mathematical model which quantifies the contamination levels of healthcare workers’ (HCW) hands from surfaces within rooms. This is achieved through a multidisciplinary approach involving computational fluid dynamics (CFD) and biological experimental techniques coupled with clinical observation and Markov Chain Monte-Carlo modelling. Spatial deposition of aerosolised bacteria was measured in a test room under different layouts: An empty room, a single-bed and a two-bed room. Comparison with CFD demonstrates realistic predictions of spatial deposition, and a Reynolds Stress turbulence model yields superior results compared to other models. An observational study of patient care at aWelsh hospital showed that hand hygiene choice and frequency varied strongly. HCWs performing short episodes of care had a predilection for alcohol rub. In other care types the usage of alcohol rub or soap and water was 50/50. HCW surface contact patterns in rooms were modelled by a Markov chain and fed into a mathematical model to calculate the pathogen colonisation level on hands after patient care. A parametric study highlights the differences between care type and colonisation. Results indicate that hand hygiene carried out by nurses may need to be rethought. The model was applied using CFD predicted spatial contamination levels, in both multibed and single rooms. When ventilation rates were equal, hand colonisation differences were small. Results demonstrate that this depends on care type, the number of surface contacts and in particular on the distribution of surface pathogens. Contamination on the HCWs’ hands decreases monotonically after care in single rooms; however increases during contact with subsequent patients in multi-bed rooms. Enforcing hand hygiene due to the knowledge of an infectious patient makes single rooms significantly less risk prone.
Some generalizations of the class of analytic functions with respect to k-symmetric points

In this article, we introduce a new class $M_{s}^{k}[\alpha,\beta,\lambda]$ which generalizes the various classes of analytic functions with respect to k-symmetric points. Naturally, the class $M_{s}^{k}[\alpha,\beta,\lambda]$ combines the classes $S_{s}^{k}(\alpha,\beta)$ and $C_{s}^{k}(\alpha,\beta)$. We also study the coefficient estimates and obtain some inequalities related to the coefficients of functions in these classes. We develop the integral representation, inclusions and convolution conditions for the functions in the class $M_{s}^{k}[\alpha,\beta,\lambda]$ .
Exploring The New York Slow Fashion Value Chain: Local Animals, Fibers, And Knitwear

This study explores the prospective development of a Fibershed in the strong fiber community of New York. It draws inspiration from the Northern California Fibershed project. “Fibershed” is a reference to fiber farms, mills, and artisan studios that support regional clothing cultures and economies. The first part of this study explored the diversity of NY fiber farms, with a focus on current marketing strategies implemented by 67 fiber farmers. The second part of the study implemented fiber farmer’s marketing strategies into a consumer survey for locally produced wool, alpaca, and cashmere knitwear. Nine marketing conditions were developed that presented basic information, emphasized local production, and the individuality of the fiber animals. Findings from 250 NY women suggested that the marketing strategies do not influence product evaluation. However, other variables including product personality, user image congruence, and consumer ethnocentricity positively influenced product evaluation. Findings from the consumer survey highlight the difficulty marketing fiber products online, especially among a consumer market that prefers to touch fiber products before purchasing.
Performance of VSG-CDMA and MC-CDMA in multirate systems

The performance of two multirate schemes in DS/CDMA systems, variable spreading gain (VSG-CDMA) and multicode (MC-CDMA) are compared. We first present the signal model for a multirate DS/CDMA system. Then, the performance in terms of asymptotic multiuser efficiency (AME), near-far resistance (NFR), and BER are evaluated. Some typical detectors are considered in multirate systems. These include the optimal maximum-likelihood detector, the sub-optimal linear detector, the interference canceller and the conventional MF detector. We show that in multirate systems, MC-CDMA has a very similar performance to VSG-CDMA employing low-rate detection (LRD). But it performs much better than VSG-CDMA employing high-rate detection (HRD). Furthermore, we show some important distinctions between multirate systems and single-rate systems.
Interacting Bosons at Finite Angular Momentum Via Complex Langevin

Quantum field theories with a complex action suffer from a sign problem in stochastic nonperturbative treatments, making many systems of great interest – such as polarized or mass-imbalanced fermions and QCD at finite baryon density – extremely challenging to treat numerically. Another such system is that of bosons at finite angular momentum; experimentalists have successfully achieved vortex formation in ultracold bosonic atoms, and have measured quantities of interest such as density profiles and the moment of inertia. However, the treatment of superfluids requires the use of complex bosons, making the usual numerical methods unusable. In this work, we apply complex Langevin, a method that has gained much attention in lattice QCD, to the calculation of basic properties of interacting bosons at finite angular momentum. We show preliminary results for the angular momentum and moment of inertia and benchmark calculations in the noninteracting limit.
The Association of Prenatal and Infant Phthalate Exposure and Childhood Asthma Symptoms

INTRODUCTION: Childhood asthma is one of the leading chronic diseases among children. Environmental exposures may may increase the risk of asthma by altering organ system maturation trajectories during critical times of development. The purpose of this study was to examine the association between childhood asthma and respiratory symptoms and exposure to phthalates before and after birth. METHODS: The Study for Future Families (SFF) cohort is a multi-state pregnancy cohort first recruited in 1999. Urine samples were collected from the pregnant woman and then her infant. This study initiated another follow-up phase where SFF children, now aged 5 to 11, were assessed for respiratory symptoms using a screening tool created specifically for this study based on previously validated tools. The screener was administered on two occasions (N=164 and N=113). Multivariable logistic regression was used to examine these associations while adjusting for child sex, child age, and prenatal maternal stress. RESULTS: The study prevalence of doctor-diagnosed asthma (12% to 15%) was nearly equivalent to national estimates (13.3%). For exposure during the prenatal period, boys and girls showed increased risk for asthma with increasing concentrations of phthalate metabolites. Boys showed greater magnitudes of risk compared to girls. For example, the sum of di(2-ethylhexyl) phthalate metabolites
PENGARUH TINGKAT PENDIDIKAN ORANG TUA TERHADAP PRESTASI BELAJAR SISWA DI SDN INPRES 1 BIROBULI

Cara membimbing anak belajar di rumah akan berpengaruh terhadap prestasi belajar anak, sehingga anak di sekolah akan mempunyai prestasi belajar yang berbeda sesuai dengan bimbingan yang diperoleh anak dari orang tuanya berpendidikan tinggi ternyata kurang berhasil dalam mendidik anaknya. Keberhasilan dalam mendidik anak adalah anak yang di sekolah pintar dan memperoleh prestasi yang baik. Dari uraian di atas sehingga penulis termotivasi memelih judul “Pengaruh Tingkat Pendidikan Orang Tua Terhadap Prestasi Belajar Siswa di SDN Inpres 1 Birobuli”. Permasalahan pokok dalam penelitian ini yaitu: Apakah ada pengaruh tingkat pendidika orang tua terhadap prestasi belajar siswa di SDN Inpres 1 Birobuli? Tujuan penelitian ini untuk mengetahui pengaruh tingkat pendidikan orang tua siswa terhadap prestasi belajar siswa. Tehnik pengumpulan data yang digunakan ialah tehnik dokumentasi dengan tehnik observasi. Tehnik analisis data yaitu tehnik analisis deskriptif dan analisis inferensial. Subjek penelitian adalah 24 orang siswa SDN Inpres 1Birobuli. Berdasarkan hasil penelitian tingkat pendidikan orang tua siswa berpengaruh terhadap prestasi belajar siswa. Berdasarkan data yang ditemukan dalam penelitian ini, bahwa tingkat pendidikan orang tua berpengaruh terhadap prestasi anak. Sebagai Orang tua memberikan bimbingan dan membantu anaknya belajar dirumah untuk mengerjakan tugas dari sekolah agar anaknya mendapat prestasi yang baik di sekolah. Sesuai hasil yang telah dilakukan di lapangan ternyata hipotesis dapat diterima, terdapat pengaruh yang signifikan antara tingkat pendidikan orang tua siswa terhadap prestasi belajar siswa, nilai r hitung ≥ r tabel (0,627 ≥ 0,404). Jadi H a diterima sedangkan H 0 ditolak. Kata Kunci: Pendidikan Orang Tua, Prestasi Belajar Siswa.
QuikSCAT geophysical model function for hurricane wind and rain

The SeaWinds scatterometer on the QuikSCAT spacecraft has been operating since August 1999 to provide global mapping of ocean winds. The ocean surface winds from the QuikSCAT scatterometer have been shown to be accurate, except for precipitating and extreme high wind conditions. It is known that the QuikSCAT scatterometer winds typically underestimate the strength of tropical cyclones and overestimate the wind speed for low to moderate wind speeds (3-10 m/s) under rainy conditions. We examined collocated QuikSCAT radar data and SSM/I rain rate to assess the effects of rain. It is shown that the QuikSCAT /spl sigma/0s increase with increasing rain rate for low and moderate wind speeds (<15 m/s) and has an opposite trend for hurricane force winds (>32 m/s). It is also shown that the QuikSCAT /spl sigma/0 modulation by the wind direction is reduced by the rain. The results are consistent with the existing QuikSCAT wind speed biases and characteristics of wind direction solutions at the presence of rain. Our results suggest that the rain rate can be introduced as an additional modeling parameter for the Ku-band scatterometer model function to reduce the wind retrieval bias resulting from the rain for adverse weather conditions.
Evaluation de la qualité microbiologique de quelques aliments de rue dans la ville de Ouagadougou au Burkina Faso

A Ouagadougou, les aliments de rues sont vendus essentiellement par les femmes (75 %) de differents âges, pres de 50 % des vendeurs sont illettres et n'ont pas tous recu de formation en bonnes pratiques de fabrication et d'hygiene. Notre etude a montre qu'il existe des risques de contamination au cours des operations de vente des aliments de rue. L'environnement de vente des aliments chez les vendeurs sedentaires est souvent insalubre, a cause de la presence d'insectes (de grillons, de mouches et de moustiques dans les jarres d'eau), de la proximite de toilettes publiques, de caniveaux d'eaux residuaires, de flaques d'eau a odeur desagreable envahissante. L'etude de la qualite microbiologique des aliments de grande consommation collectes aupres des differentes categories de vendeurs a montre la presence d'une flore aerobie mesophile abondante, composee de differents germes comme les staphylocoques, les coliformes, les salmonelles, les shigelles et les streptocoques. La presence des salmonelles et shigelles rend certains aliments impropres a la consommation.
A Novel Deep Fuzzy Classifier by Stacking Adversarial Interpretable TSK Fuzzy Sub-Classifiers With Smooth Gradient Information

Different from our previous stacked-structure-based deep fuzzy classifier, in this paper, we explore the distinctive role of adversarial outputs of training samples in enhancing the classification performance of a stacked-structure-based deep fuzzy classifier. In order to achieve such goals, an adversarial Takagi–Sugeno–Kang (TSK) fuzzy classifier, which is denoted as TSKa, is proposed. With the TSKa, interpretable IF parts of first-order fuzzy rules can be generated by the random selection of fixed linguistic terms along each feature. According to our theoretical analysis, adversarial outputs of training samples enhance TSKa's generalization capability, thereby, resulting in the potential feasibility of leveraging their smooth gradient information with respect to the inputs in the training input space to construct a stacked-structure-based deep fuzzy classifier. In this paper, a novel deep fuzzy classifier is devised by stacking a series of TSKa sub-classifiers and training them by a deep learning strategy. An advantage of the proposed deep fuzzy classifier is its easy yet fast training. The training of each layer consists of two basic steps: computation of the smooth gradient information of adversarial outputs with respect to the inputs, and fast training of each corresponding TSKa by the least learning machine method. Comprehensive experiments on both benchmark datasets and an industrial case demonstrate the promising performance and advantages of the proposed deep fuzzy classifier.
Students' Motivations for Class Attendance

Objective. The objective of this study was to describe and categorize students' motivations for attending class or choosing not to attend class. Methods. Trained student facilitators conducted 5 focus groups. Nine first-year and 24 second-year pharmacy students participated in the focus groups, which were tape recorded and transcribed. A content analysis was conducted using the transcripts. Two coders coded the transcripts and percent agreement was used to assess inter-coder reliability. Frequencies were reported. Results. Eighteen variables emerged from the data. The percent agreement for each variable ranged from 0.83 to 1.00. The variables cited most frequently as motivators for class attendance by both the first- and second-year pharmacy students were “class handouts not inclusive, faculty presented new information in class,” and “faculty apply information to solving real problems. ” The variables cited most frequently by both first- and second-year pharmacy students as a motivator for not attending cl.
Verifying a concept of adaptive communication with LEO satellites using SDR-based simulations

Abstract The paper is related to an adaptive satellite communication system for data transmission from small, low cost, low Earth orbit satellites. Tests run in a set-up consisting of a number of software-defined radio (SDR) modules operating as a satellite, a ground station, and a satellite channel simulator, have shown that by changing modulation scheme and code rate one can obtain increase of amount of data which can be downloaded from a satellite during a single pass over a ground station approximately by a factor of 2. To determine data rates obtainable in an SDR system using a common personal computer as a digital signal processing device, execution times of particular processing steps involved in the reception process were measured.
Geometric and Solid Modeling: An Introduction

It is the view of the author that the streams of geometric and solid modeling are converging, and that as the importance of this convergence is anticipated and recognized, the need for the development of techniques to bridge the gap between the two becomes critical. This book is devoted to filling that need. "Geometric and Solid Modeling" deals with the concepts and tools needed to design and implement solid-modeling systems and their infrastructure and substrata, making this information remarkably accessible--to the novice as well as to the experienced designer. The essential algorithms and the underlying theory needed to design these systems are given primary emphasis. Techniques for the study and implementation of geometric algorithms are taken from computer science, numerical analysis, and symbolic computation, among other areas. Special attention is given to geometric investigations of implicit and parametric surfaces, with the focal point being the possible integration of geometric and solid modeling.