Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Mining Research in Education

As an interdisciplinary discipline, data mining (DM) is popular in education area especially when examining students' learning performances. It focuses on analyzing educational related data to develop models for improving learners' learning experiences and enhancing institutional effectiveness. Therefore, DM does help education institutions provide high-quality education for its learners. Applying data mining in education also known as educational data mining (EDM), which enables to better understand how students learn and identify how improve educational outcomes. Present paper is designed to justify the capabilities of data mining approaches in the filed of education. The latest trends on EDM research are introduced in this review. Several specific algorithms, methods, applications and gaps in the current literature and future insights are discussed here.
Strategies and Tactics in Operational Semantics

We refer to strategies setting the objective of a computation step rather than to evaluation strategies (as eager or lazy evaluations). We use these strategies to define semantics of a system starting from its elementary operational entities, and then combining them. The tactics of a strategy are given by rewriting steps. While a strategy is at a higher level and defines ”what is the goal” of a computation, the tactics are at a lower level and tell ”how it is possible to reach the goal”. We use rewriting systems as a general model of computing. In this framework we give an operational semantics of the strategic transitions in terms of tactical rewritings. The approach is inspired by a new model of computation given by membrane systems. We define the strategy semantics for membrane systems involving the maximal parallel rewriting and priorities. We show that strategies are not powerful enough to define alone the semantics of membrane systems involving promoters. This is possible when we encode the state of the membrane in a richer structure.
Test-Retest Reliability and Validity of Three Different Agility Tests for Various Team Sports in Young Male Athletes

The purpose of this study is to examine the reproducibility of three different agility tests in basketball, soccer and water polo team sports. To determine the reliability 44 young male athletes (Basketball age 16.5 ±0.6, height 177.9 ±7.7 weight 70.0 ±7.1; Soccer age 16.3 ±0.5, height 169.2 ±5.0, weight 71.2 ±7.9; Water Polo age 17.1 ±0.7, height 181.3 ±6.7, weight 76.7 ±7.2) performed 3 different agility tests (Zig-Zag, Illinois and AS) on two occasions 1 wk. apart for test-retest. Sprint time scores were analyzed for each test. To determine the reliability Paired Sample T-test and Pearson Correlation Statistics were computed. Scores of teams were compared with ANOVA statistics to determine the difference. Test results showed that there was no significant difference between the two occasions for all agility test on subjects and teams (p > 0.01). There was higher correlation between test-retest values of subjects (r = 0.90–0.97). Three different agility tests were found valid in determining agility with significant moderate level correlation. (r = 0.36–0.44; p < 0.01). Differences among sport branches were found significant for agility scores (p < 0.05). All three agility tests are reliable and valid for team sport athletes. Soccer players had better scores than other branches in soccer specific test (AS). This study showed that sport specific agility tests are more useful than general agility tests.
Towards Data Isolation & Collaboration in Storage Cloud

Cloud Storage has been turned into a common platform shared among varied organizations, even market competitors, thus has raised many security concerns. Most of the current researches focus on data encryption and decryption, in this paper, however, we take an alternative perspective-access control, to design and implement a secure solution for cloud storage, aiming to solve both the data isolation problem, which ensures that data in storage cloud owned by one company wouldn't be crossly accessed by other ones, and data collaboration problem, which makes data sharing between different organizations through storage cloud possible while still under the restriction of company data isolation. Besides, we have presented a pretty flexible security policy which could be easily customized to fit the variant security requirements in different cooperation. Finally, a prototype has been implemented based on HDFS by this policy, and the time cost is given and evaluated.
Reflecting on the ethics of researching communication in superdiverse contexts

Reflecting on the ethics of researching communication in superdiverse contexts Fiona Copland INTRODUCTION Ethics as both epistemology and practice has been growing in importance in the social sciences at the same time as institutions have been tightening their requirements in terms of ethical approval processes. Many of our understandings about ethical research derive directly from medical models (Copland and Creese 2015) and these have been helpful in supporting social science researchers in developing ethical approaches to their work. Notwithstanding, many institutional ethics approval processes, are not a good ‘fit’ for the kind of work social sciences researchers do, and ethics committees can struggle to understand and then approve research designs that are embryonic or field work that is situated in sites where ethical issues cannot always be predicted. In addition, the focus on the ethics approval form as product may lull researchers into believing that ethics are not part of the research process, and therefore they do not pay attention when ‘ethically important moments’ (Guillemin and Gillam 2004) occur in the field.
A Spatial-Temporal QoS Prediction Approach for Time-aware Web Service Recommendation

Due to the popularity of service-oriented architectures for various distributed systems, an increasing number of Web services have been deployed all over the world. Recently, Web service recommendation became a hot research topic, one that aims to accurately predict the quality of functional satisfactory services for each end user. Generally, the performance of Web service changes over time due to variations of service status and network conditions. Instead of employing the conventional temporal models, we propose a novel spatial-temporal QoS prediction approach for time-aware Web service recommendation, where a sparse representation is employed to model QoS variations. Specifically, we make a zero-mean Laplace prior distribution assumption on the residuals of the QoS prediction, which corresponds to a Lasso regression problem. To effectively select the nearest neighbor for the sparse representation of temporal QoS values, the geo-location of web service is employed to reduce searching range while improving prediction accuracy. The extensive experimental results demonstrate that the proposed approach outperforms state-of-art methods with more than 10% improvement on the accuracy of temporal QoS prediction for time-aware Web service recommendation.
Hierarchical Part-Template Matching for Human Detection and Segmentation

Local part-based human detectors are capable of handling partial occlusions efficiently and modeling shape articulations flexibly, while global shape template-based human detectors are capable of detecting and segmenting human shapes simultaneously. We describe a Bayesian approach to human detection and segmentation combining local part-based and global template-based schemes. The approach relies on the key ideas of matching a part-template tree to images hierarchically to generate a reliable set of detection hypotheses and optimizing it under a Bayesian MAP framework through global likelihood re-evaluation and fine occlusion analysis. In addition to detection, our approach is able to obtain human shapes and poses simultaneously. We applied the approach to human detection and segmentation in crowded scenes with and without background subtraction. Experimental results show that our approach achieves good performance on images and video sequences with severe occlusion.
Does Greater Inequality Lead to More Household Borrowing? New Evidence from Household Data

One suggested hypothesis for the dramatic rise in household borrowing that preceded the financial crisis is that low-income households increased their demand for credit to finance higher consumption expenditures in order to "keep up" with higherincome households. Using household level data on debt accumulation during 2001-2012, we show that low-income households in high-inequality regions accumulated less debt relative to income than their counterparts in lower-inequality regions, which negates the hypothesis. We argue instead that these patterns are consistent with supply-side interpretations of debt accumulation patterns during the 2000s. We present a model in which banks use applicants' incomes, combined with local income inequality, to infer the underlying type of the applicant, so that banks ultimately channel more credit toward lower-income applicants in low-inequality regions than high-inequality regions. We confirm the predictions of the model using data on individual mortgage applications in high- and low-inequality regions over this time period.
mRNA pseudoknot structures can act as ribosomal roadblocks

Several viruses utilize programmed ribosomal frameshifting mediated by mRNA pseudoknots in combination with a slippery sequence to produce a well defined stochiometric ratio of the upstream encoded to the downstream-encoded protein. A correlation between the mechanical strength of mRNA pseudoknots and frameshifting efficiency has previously been found; however, the physical mechanism behind frameshifting still remains to be fully understood. In this study, we utilized synthetic sequences predicted to form mRNA pseudoknot-like structures. Surprisingly, the structures predicted to be strongest lead only to limited frameshifting. Two-dimensional gel electrophoresis of pulse labelled proteins revealed that a significant fraction of the ribosomes were frameshifted but unable to pass the pseudoknot-like structures. Hence, pseudoknots can act as ribosomal roadblocks, prohibiting a significant fraction of the frameshifted ribosomes from reaching the downstream stop codon. The stronger the pseudoknot the larger the frameshifting efficiency and the larger its roadblocking effect. The maximal amount of full-length frameshifted product is produced from a structure where those two effects are balanced. Taking ribosomal roadblocking into account is a prerequisite for formulating correct frameshifting hypotheses.
A multi-modal and multi-algorithmic biometric system combining iris and face

In this paper, we have developed an algorithm which combines features from human iris and face for person verification. Iris recognition is one of the most accurate biometric modalities having verification results close to 98%. On the other hand, face is one of the most widely used biometric features because of its ease of capture. We have adapted score level fusion strategy for our system. However, in addition to this, we are using two different features for face: Gabor filters based and Local Binary Patterns (LBP) based. The iris features are extracted using Daugman's Gabor filters based approach. Using this information, we have developed a multi-modal (combining iris and face), multi-algorithmic (using two different algorithms for feature extraction from face) biometric system. With this system, we achieved more than 85% improvement in the verification performance in terms of Equal Error Rate as compared to the uni-biometrics based system.
On-the-fly generation of k-path tests for C functions

We propose a novel method, called PathCrawler, for the automatic generation of structural tests satisfying the all-paths criterion or its k-path variant. The source code is instrumented so as to recover the symbolic execution path each time that the program under test is executed. This code is first executed using inputs arbitrarily selected from the input domain. The resulting symbolic path is transformed into a path predicate by projection of the conditions onto the input variables. The next test is obtained by using constraint logic programming to find new input values outside the domain of the path which is already covered. The instrumented code is then executed on this test and so on, until all feasible paths have been covered. Our method combines static and dynamic analysis in a way that avoids the disadvantages of both. It is currently being implemented for the C language.
Brain-machine-muscle interfaces for restoring locomotion after spinal cord injuries

iv PUBLICATION ARISING FROM THE THESIS . vi ACKNOLEDGEMENTS . vii CONTENTS . viii CHAPTER 1: INTRODUCTION . 1 Spinal cord injury . 1 Current treatments for SCI paraplegics . 4 Functional electrical stimulation . 5 Brain-machine interfacing . 14 Physiological basis of locomotion . 18 Rationale of the current study . 20 Conceptual and experimental model . 21 Research questions . 22 Research hypothesis . 22 Study design and objectives . 22 Outline of the thesis . 23 CHAPTER 2: EXTRACTING NEURAL INFORMATION ON LOCOMOTION FROM CORTICAL RECORDINGS . 24 Background . 24 Methods . 27
New Features Extraction and Application in Fingerprint Segmentation

We present a useful and effective fingerprint image segmentation. We extract two new features with which our algorithm can distinguish the blurred area from foreground, and, therefore, can reduce the number of false minutiae. We use supervised RBF neural network to classify patterns and select typical patterns to train the classifier. Experimental results show a significant improvement in fingerprint segmentation performance.
Stereo Measurement of Objects in Liquid and Estimation of Refractive Index of Liquid by Using Images of Water Surface

In this paper, we propose a new stereo measurement method of objects in liquid whose refractive index is unknown. In recent years, demands for underwater tasks, such as digging of ocean bottom resources, exploration of aquatic environments, rescues, and salvages, have increased. Therefore, underwater robots or underwater sensing systems that work instead of human become important, and technologies for observing underwater situations correctly and robustly from cameras of these systems are needed (Yuh, 2001). However, it is very difficult to observe underwater environments with cameras (Hulburt, 1945; Stewart, 1991; Caimi, 1996), because of the following three big problems. 1. View-disturbing noise (Fig. 1(a)) 2. Light attenuation effect (Fig. 1(b)) 3. Light refraction effect (Fig. 1(c)) The first problem is about suspended matters, such as bubble noises, small fishes, small creatures, and so on. They may disturb camera's field of view (Fig. 1(a)).
Development of “A Scale for Participation of Families to Inclusive Education Environments of Gifted and Talented Children”

The aim of this research is to develop a scale in order to determine the participation level of families to inclusive preschool and primary school education environments, in which talented and gifted children receive education together with typically developing children. In this context, study group of the research was comprised of 1007 families, who had children studying in various preschool education institutions and primary schools, which provide inclusive education in Ankara province. Data obtained from 456 persons included to the study group were subjected to Exploratory factor analysis, and data obtained from 551 persons were subjected to Confirmatory factor analysis. We determined that the scale was comprised of 11 items and one-dimensional scale. The scale was named as “A Scale for Participation Of Families to the Inclusive Education Environment” in the direction of expert opinions and body of literature. The scale explains 42,58% of total variance. Cronbach’s alpha internal consistency coefficient was calculated in order to determine reliability of the scale, and we obtained the value of 0.89. As we examined the goodness of fit indexes that were obtained as a result of confirmatory factor analysis, we determined that the included items were good fit to the single-factor structure. Also, item-test correlations of the items were calculated, and we reached to the result that all of the values were above . 30. Consequently, we determined that the scale comprised of 11 items and single-factor structure is reliable.
TTAinterfaceTrendAnalysis: A R GUI for Routine T emporal T rend Analysis and Diagnostics

Trend detection in hydrologic and water quality time series has received considerable attention in the recent past for pure research purposes on methodological development and/or assessment of ecological status [1,2]. Trend assessment is of particular interest because environmental changes have been sometimes unusual in the past few decades with consequences on the environment in general, including impacts on living resources and fishing management. Time-series are of importance to studies on the biological influence of anthropogenic effects and climatic changes, both in themselves and in providing a baseline and/or reference conditions for future investigations. These works could be particularly helpful to scientists and policymakers within the framework of European directives (Water Framework Directive (WFD 2000/60/EC), Marine Strategy Framework Directive (MSFD 2008/56/EC)) and regional sea convention (OSPAR convention [3]). In this context and due to the heterogeneity, the variety of data sources and the variety of statistical analysis methodologies, there is a clear need for unifying methods of temporal trend assessment, for the purpose of a given directive or convention devoted to assess trends towards or from a good environment status. Consequently, the authors proposed the TTAinterfaceTrendAnalysis package with the aim to develop a standard procedure (routine) to assess temporal trend on database and which can be entirely done through a Graphical User Interface (GUI). Package containing temporal trend tests already exist in R language such as wq or pastecs, however they need command lines and are only ideal for advanced users who can deal with it. The TTAinterfaceTrend Analysis package uses the power of such tools but simplify their use (from database creation to results interpretation) through a GUI for standard, non-statistician user.
Activation in inhibitory brain regions during food choice correlates with temptation strength and self-regulatory success in weight-concerned women

Food choices constitute a classic self-control dilemma involving the trade-off between immediate eating enjoyment and the long term goal of being slim and healthy, especially for weight-concerned women. For them, decision-making concerning high (HE) and low energy (LE) snacks differs when it comes to the need for self-control. In line, our first study aim was to investigate which brain regions are activated during food choices during HE compared to LE energy snacks in weight-concerned women. Since it is particularly difficult to resist HE snacks when they are very tasty, our second aim was to investigate in which brain regions choice-related activation varies with the food's tastiness. Our third aim was to assess in which brain regions choice-related activation varies with individual differences in self-regulatory success. To this end, 20 weight-concerned women indicated for 100 HE or LE snacks whether they wanted to eat them or not, while their brains were scanned using fMRI. HE snacks were refused more often than equally-liked LE snacks. HE snack choice elicited stronger activation in reward-related brain regions [medial to middle orbitofrontal cortex (OFC), caudate]. Highly tasty HE snacks were more difficult to resist and, accordingly, activation in inhibitory areas (inferior frontal gyrus, lateral OFC) was negatively associated with tastiness. More successful self-controllers showed increased activation in the supplementary motor area during HE food choices. In sum, the results suggest that HE snacks constitute a higher reward for weight-concerned women compared to (equally-liked) LE snacks, and that activation during food choice in brain regions involved in response inhibition varied with tastiness and individual differences in self-regulatory success. These findings advance our understanding of the neural correlates of food choice and point to new avenues for investigating explanations for self-regulatory failure.
Clinicians’ Tendencies to Under-Rate Parkinsonian Tremors in the Less Affected Hand

The standard assessment method for tremor severity in Parkinson’s disease is visual observation by neurologists using clinical rating scales. This is, therefore, a subjective rating that is dependent on clinical expertise. The objective of this study was to report clinicians’ tendencies to under-rate Parkinsonian tremors in the less affected hand. This was observed through objective tremor measurement with accelerometers. Tremor amplitudes were measured objectively using tri-axis-accelerometers for both hands simultaneously in 53 patients with Parkinson’s disease during resting and postural tremors. The videotaped tremor was rated by neurologists using clinical rating scales. The tremor measured by accelerometer was compared with clinical ratings. Neurologists tended to under-rate the less affected hand in resting tremor when the contralateral hand had severe tremor in Session I. The participating neurologists corrected this tendency in Session II after being informed of it. The under-rating tendency was then repeated by other uninformed neurologists in Session III. Kappa statistics showed high inter-rater agreements and high agreements between estimated scores derived from the accelerometer signals and the mean Clinical Tremor Rating Scale evaluated in every session. Therefore, clinicians need to be aware of this under-rating tendency in visual inspection of the less affected hand in order to make accurate tremor severity assessments.
Static Analysis of Students' Java Programs

A recent industry survey (Townhidnejad and Hilburn, 2002) has reported that more than fifty percent of a software project's budget is spent on activities related to improving software quality. Industry leaders claim that this is caused by the inadequate attention paid to software quality in the development phase. This paper introduces a static analysis framework which can be used to give beginning students practice in writing better quality Java programs and to assist teaching staff in the marking process. The framework uses both software engineering metrics and relative comparison to judge the quality of student's programs and provide feedback about how solutions might be improved.