Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring the effect of inventing practice exercises on learning in an introductory programming course

A key determinant of success for novice programmers is the extent to which they practice writing code. In a typical introductory programming course, students are given numerous projects, assignments and lab exercises to work through to develop their confidence and skill. In general, designing and preparing suitable problems for these tasks requires a great deal of time and draws heavily on the experience of the instructor. However, for certain small scale problems, students may be quite capable of inventing their own exercises. In fact, research across various disciplines indicates this can be a useful learning activity in itself. We explored this idea in an introductory computing course (n > 180) by conducting a randomized, controlled experiment in which a group of students invented programming exercises prior to an exam. Although the created exercises were used by all students in the course for practice, the group that invented them performed significantly better on the exam. Further to this, students perceived the process of inventing exercises as contributing to their learning in the course. We discuss the conditions under which similar approaches may also be successful, and we investigate the quality and difficulty of the student-invented exercises.
Speaker verification using various prosodic kernels

In this article text independent speaker verification problem is considered. The approach in which SVM and prosodic features are employed has been chosen. Prosodic features are modelled by Legendre polynomials. In order to map a sequence of prosodic vectors to fixed dimensional vector three kernels were used: VQ kernel, GMM supervector kernel and Fisher kernel. These three kernels were compared and its combination was evaluated.
Reading bar graphs: Effects of extraneous depth cues and graphical context.

Manipulating the way a graph is drawn influences viewers' ability to extract information from it. In a series of experiments with simple bar graphs, the authors varied the rendering characteristics and relative heights of the bars and asked participants to estimate the quantities portrayed. The addition of 3-dimensional (3D) perspective depth cues lowered accuracy. This accuracy disadvantage diminished when a short delay was introduced before judgments were reported. The height of the judged bar relative to nearby graphical elements also affected accuracy; this effect was about 1 order of magnitude larger and remained intact when the delay was introduced. Nearby elements also affected viewers' bias (under- or overestimatio n). These effects do not seem to be due to misestimation of object depth. The results suggest that warnings about accuracy decrements due to 3D shading may be overstated, whereas distortions due to neighboring elements should be of more concern.
Design of Future Television

To enable the future users to create their own product concepts is a relatively new idea in the design of consumer products. In this paper, ten TV viewers created new concepts of interactive television programs and applications for digital television. During the user study, the study participants were asked to gather data on themselves in their home environment. The study focused on TV viewers’ leisure time and their thoughts of the television in the future. The study resulted in a set of user profiles and innovations of future interactive applications the study participants designed for themselves. The study aims at creating a user centered design method with the study participants as equal research partners with the designers.
The Definition, Dimensionality and Content of Newcomer’s Organizational Socialization: A Perspective from Identity Theory

The research on newcomer’s organizational socialization (OS) has been criticized for lacking a fundamental theoretical basis, thereby imitating the method of how to measure OS effect. Role Identity Theory and Social Identity Theory can provide OS research a substantial theoretical basis. Based on the theoretical discussion on the boundaries of OS concept, the identity nature of OS was explored as a newcomers' role identity and social identity development process. The identity theory also revealed two dimensions of OS effect. The content of each dimension was further discussed. Future efforts are expected to develop new OS scale and conceptual model on the basis of identity theory. The identity theory also implies the advancement of research methodology in the future OS study.
Towards a new Approach for Arabic root extraction: Exploit relations between the word letters and their placement in the word for Arabic root extraction

In this paper we present a new root-extraction approach for Arabic words. The approach tries to assign for Arabic word a unique root without having a database of word roots, a list of words patterns or even a list of all the prefixes and the suffixes of the Arabic words. Unlike most of Arabic rule-based stemmers, it tries to predict the letters positions that may form the word root one by one using some rules based on the relations among the Arabic word letters and their placement in the word. This paper will focus on two parts of the approach. The first one deals with the rules that distinguish between the Arabic definite article “ ال -AL” and the permanent component “ ال -AL” that may found in any Arabic word. The second part of the approach adopts the segmentation of the word into three parts and classifies Arabic letters in to groups according to their positions in each segment. The proposed approach is a system composed of several modules that corporate together to extract the word root. The approach has been tested and evaluated using the Holy Quran words. The results of the evaluation show a promising root extraction algorithm.
Plagiarism detection across programming languages

Plagiarism is a widespread problem in assessment tasks; in computing courses, students often plagiarise source code. For all but the smallest classes, manual detection of such plagiarism is impractical, and, while automated tools are available, none has been applied to detect inter-lingual plagiarism, where source code is copied from one language to another. In this work, we propose a novel approach, XPlag, to detect plagiarism involving multiple languages using intermediate program code produced by a compiler suite. We describe experiments to evaluate XPlag, and show that we can detect inter-lingual plagiarism with reasonably good precision.
Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP) and optimized support vector regression (SVR). Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA), particle swarm optimization algorithm (PSO), and cuckoo optimization algorithm (COA). Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1) analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2) the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3) the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.
How quickly should communication robots respond?

This paper reports a study about system response time (SRT) in communication robots that utilize human-like social features, such as anthropomorphic appearance and conversation in natural language. Our research purpose established a design guideline for SRT in communication robots. The first experiment observed user preferences toward different SRTs in interaction with a robot. In other existing user interfaces, faster response is usually preferred. In contrast, our experimental result indicated that user preference for SRT in a communication robot is highest at one second, and user preference ratings level off at two seconds. However, a robot cannot always respond in such a short time as one or two seconds. Thus, the important question is “What should a robot do if it cannot respond quickly enough? ” The second experiment tested the effectiveness of a conversational filler: behavior to notify listeners that the robot is going to respond. In Japanese “etto” is used to buy time to think and resembles “well. ” and “uh. ” In English. We used the same strategy in a communication robot to shadow system response time. Our results indicated that using a conversational filler by the robot moderated the user's impression toward a long SRT.
A Cluster-Based Approach for Semantic Similarity in the Biomedical Domain

We propose a new cluster-based semantic similarity/distance measure for the biomedical domain within the framework of UMLS. The proposed measure is based mainly on the cross-modified path length feature between the concept nodes, and two new features: (1) the common specificity of two concept nodes, and (2) the local granularity of the clusters. We also applied, for comparison purpose, five existing general English ontology-based similarity measures into the biomedical domain within UMLS. The proposed measure was evaluated relative to human experts' ratings, and compared with the existing techniques using two ontologies (MeSH and SNOMED-CT) in UMLS. The experimental results confirmed the efficiency of the proposed method, and showed that our similarity measure gives the best overall results of correlation with human ratings. We show, further, that using MeSH ontology produces better semantic correlations with human experts' scores than SNOMED-CT in all of the tested measures
Relations between playing activities and fine motor development

ABSTRACT Children’s fine motor skills (FMS) are being increasingly recognized as an important aspect of preschool development; yet, we know very little about the experiences that foster their development. We utilized a parent-administered children’s fine and gross motor activities questionnaire (MAQ) to investigate links with FMS. We recruited a sample of 225 preschool children (aged 5;9) and assessed FMS and vocabulary. Additionally, parents completed the MAQ and a questionnaire on home literacy environment (HLE) to test two competing accounts. According to a differential account, fine motor activities lead to greater FMS, whereas according to an epiphenomenal account, a generally more educative home environment fosters FMS alongside other skills. Findings were highly differential: FMS linked to the fine-MAQ but not to the gross-MAQ or the HLE, whereas vocabulary linked to the HLE, but not the fine- or gross-MAQ. The data underscore fine motor activities as a distinct factor in the preschool period.
Robust Association Tests for the Replication of Genome-Wide Association Studies

In genome-wide association study (GWAS), robust genetic association tests such as maximum of three CATTs (MAX3), each corresponding to recessive, additive, and dominant genetic models, the minimum p value of Pearson's Chi-square test with 2 degrees of freedom, and CATT based on additive genetic model (MIN2), genetic model selection (GMS), and genetic model exclusion (GME) methods have been shown to provide better power performance under wide range of underlying genetic models. In this paper, we demonstrate how these robust tests can be applied to the replication study of GWAS and how the overall statistical significance can be evaluated using the combined test formed by p values of the discovery and replication studies.
THE CEREBRAL PALSIES: A PHYSIOLOGICAL APPROACH

The cerebral palsies (CP) are a heterogeneous group of non-progressive motor disorders of the developing brain. By convention, brain injuries occurring at any stage antenatally and postnatally to the age of 2 years are included in the definition of CP. Primary disorders of the spinal cord such as neural tube defects, neuropathies, and myopathies are excluded. Cerebral palsy should be viewed as part of a “continuum of reproductive casualty”,1 comprising miscarriages, stillbirths, and severe and minor brain injuries. Consequently, the incidence and causes of CP are a matter of great interest since they provide a benchmark of reproductive health. The incidence of CP in developed countries is stable at about 2–2.5/1000 live births. The risk of CP for premature babies is 5–80/1000 live births, though the majority of cases of CP are term born babies (fig 1). Figure 1 Cerebral palsy rates and numbers (excluding cases due to postneonatal causes) by gestational age and year of birth in Western Australia, 1981 to 1992. Prematurity is defined as birth below 37 weeks gestation. Note that although the rate of CP is higher for the preterm baby per thousand live births (lines), term births account for the majority of cases of CP (histograms). Modified from Stanley et al ,31 by permission of MacKeith Press. There are many ways of classifying CP, but the simplest is according to number and distribution of affected limbs: monoplegia, hemiplegia, diplegia, triplegia, and quadriplegia. As a rule, hemiplegia is associated with late third trimester injuries. By contrast, the risk of bilateral brain injury increases with prematurity. The various means of classifying the cerebral palsies are summarised in table 1. The modified Swedish classification shown in table 2 is most used because of its simplicity. The relation between gestational age and CP phenotype is well established (table 3). …
FIT-2, an extraction program based on the SPICE-PAC simulation software

FIT-2, an interactive program for extraction of transistor parameters for SPICE-like circuit simulators, is discussed. It is based on a circuit simulator rather than on an explicit set of model equations. Several optimization methods are built into the program to provide robust as well as sufficient fitting of device characteristics. The flexibility of the approach is obtained by specification of extraction details in the data sets rather than the extraction procedure. Extraction results for heterojunction bipolar transistors are used as an illustration of FIT-2's capabilities. Several directions for further research are identified. <<ETX>>
COMBINING COMPARATIVE AND SIMULTANEOUS ANALYSIS APPROACHES BASED ON FUZZY INTEGRATION FOR CHANGE DETECTION

: The purpose of this paper is to investigate the applicability of change detector combination for improving the performance of change detection in remotely sensed data. Thereby, outputs of two fuzzy change detectors based respectively on comparative analysis and simultaneous analysis approaches are combined to yield a single decision. Both change detectors utilize the squared Mahalanobis distance from the prototypes of classes to formulate the fuzzy membership model, while the combination is carried out by using the Sugeno fuzzy integral. This method combines the objective evidences in the form of fuzzy class membership values with subjective importance measures of each change detector. Bitemporal SPOT images covering a region of Algeria are used for evaluating the performance of the proposed scheme. Based on our experiments the effectiveness of the combination rule has been proved. Furthermore, the results obtained for several classes of change showed that it outperforms the individual change detectors by increasing the detection of nonspurious changes while reducing the number of false alarms.
Algorithmic Characterization of Rationalizability in Extensive Form Games

We construct a dynamic epistemic model for extensive form games, which generates a hierarchy of beliefs for each player over her opponents` strategies and beliefs, and tells us how those beliefs will be revised as the game proceeds. We use the model to analyze the implications of the assumption that the players possess common (true) belief in rationality, thus extending the concept of rationalizability to extensive form games.
Aligned Single Walled Carbon Nanotubes for Strain Sensor

Single walled carbon nanotube shows excellent chemical and physical properties and it has been extensively explored for novel applications. It has been shown that single walled carbon nanotube can be used to improve sensitivity of sensors such as bio sensors, gas sensors and mechanicals sensor by its unique properties. As a mechanical sensor, a mechanical force deforms the single walled carbon nanotubes and changes its electrical properties such as resistivity. The deformation results in changing of electrical structure such as band gap of single walled carbon nanotubes. In this study, we fabricate a strain sensor using single walled carbon nanotubes with an efficient structure. The structure contains aligned and multiple numbers of single walled carbon nanotubes to raise sensitivity of the strain sensor. The structure fabricated in this study is much reliable and efficient compared to the sensor with individual single walled carbon nanotube.
A multivariable ANFIS model for sEMG based remote control system

The sEMG (Surface Electromyogram) is a kind of physiological signal corresponding to the muscle action. The analysis of sEMG signal can obtain the charateristics of the motion information. In this paper, a remote control system based on sEMG was developed. The system consists of host and client computer. A sEMG signal recording device was designed. The recorded data was transit by Zigbee wireless communication technique to a host computer. The obtained data was analysed based on a developed multivariable ANFIS model in order to recognize the corresponding hand movement. The recognition result was shown on a client computer by a local area network. The developed control system mimics the remote clinical diagnosis circumstance, which was realizable for real application.
Digital IIR Filter Design Using Adaptive Simulated Annealing

Adaptive infinite-impulse-response (IIR) filtering provides a powerful approach for solving a variety of practical problems. Because the error surface of IIR filters is generally multi-modal, global optimisation techniques are required in order to avoid local minima. We apply a global optimisation method, called the adaptive simulated annealing (ASA), to digital IIR filter design. An important advantage of the ASA is the simplicity in software programming. Simulation study involving system identification application shows that the proposed approach is accurate and has a fast convergence rate, and the results obtained demonstrate that the ASA offers a viable tool to digital IIR filter design.
On the Effectiveness of the Scheduling Algorithm of the Dynamically Trace Scheduled VLIW

In a machine that follows the dynamically trace scheduled VLIW (DTSVLIW) architecture, VLIW instructions are built dynamically through a scheduling algorithm that can be implemented in hardware. These VLIW instructions are cached so that the machine can spend most of its time executing VLIW instructions without sacrificing any binary compatibility. This paper evaluates the effectiveness of the DTSVLIW instruction scheduling algorithm by comparing it with the first come first served (FCFS) algorithm, used for microinstruction compaction, and the Greedy algorithm, used by the Dynamic Instruction Formatting architecture. In order to perform these comparisons, we have performed experiments using the SPECint95 benchmark suite.
Influence of a Prolonged Tennis Match Play on Serve Biomechanics

The aim of this study was to quantify kinematic, kinetic and performance changes that occur in the serve throughout a prolonged tennis match play. Serves of eight male advanced tennis players were recorded with a motion capture system before, at mid-match, and after a 3-hour tennis match. Before and after each match, electromyographic data of 8 upper limb muscles obtained during isometric maximal voluntary contraction were compared to determine the presence of muscular fatigue. Vertical ground reaction forces, rating of perceived exertion, ball speed, and ball impact height were measured. Kinematic and upper limb kinetic variables were computed. The results show decrease in mean power frequency values for several upper limb muscles that is an indicator of local muscular fatigue. Decreases in serve ball speed, ball impact height, maximal angular velocities and an increase in rating of perceived exertion were also observed between the beginning and the end of the match. With fatigue, the majority of the upper limb joint kinetics decreases at the end of the match. No change in timing of maximal angular velocities was observed between the beginning and the end of the match. A prolonged tennis match play may induce fatigue in upper limb muscles, which decrease performance and cause changes in serve maximal angular velocities and joint kinetics. The consistency in timing of maximal angular velocities suggests that advanced tennis players are able to maintain the temporal pattern of their serve technique, in spite of the muscular fatigue development.
Equivalent operator preconditioning for linear elliptic problems

The numerical solution of linear elliptic partial differential equations most often involves a finite element or finite difference discretization. To preserve sparsity, the arising system is normally solved using an iterative solution method, commonly a preconditioned conjugate gradient method. Preconditioning is a crucial part of such a solution process. It is desirable that the total computational cost will be optimal, i.e. proportional to the degrees of freedom of the approximation used, which also includes mesh independent convergence of the iteration. This paper surveys the equivalent operator approach, which has proven to provide an efficient general framework to construct such preconditioners. Hereby one first approximates the given differential operator by some simpler differential operator, and then one chooses as preconditioner the discretization of this operator for the same mesh. In this survey we give a uniform presentation of this approach, including theoretical foundation and several practically important applications.
Informative Gene Discovery for Cancer Classification from Microarray Expression Data

Gene expression data analysis from microarray is a new advance of cancer diagnosis. However, the gene expression data often have high dimensionality and small sample size. These properties cause severe difficulties in classification. Gene selection is thus a crucial pre-processing step to filter out uninformative genes prior to the classification step. Our approach to perform gene selection is an information theoretic approach combining with sequential forward floating search. Experimental results show that our method is capable of efficiently finding a compact set of informative genes which can effectively discriminate different classes
An Efficient Group Key Exchange Protocol from Pairings

Recently, several ID-based authenticated group key agreement (AGKA) crytosystems based on bilinear pairings have been proposed. It is an increasingly active research area because of the simplicity of the public key management and the efficiency. However most of the group key agreement protocols have the security and performance weakness. In this paper, we propose an authenticated group key agreement protocol with perfect forward secrecy that requires only one round without verifying signatures. We show that our scheme satisfies all known security requirements, and therefore it is more secure and efficient than other protocols.