Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Corpus-Based and Structural Methods on Approximation of Semantic Relatedness in Ontologies

In this paper, the authors compare the performance of corpus-based and structural approaches to determine semantic relatedness in ontologies. A large light-weight ontology and a news corpus are used as materials. The results show that structural measures proposed by Wu and Palmer, and Leacock and Chodorow have superior performance when cut-off values are used. The corpus-based method Latent Semantic Analysis is found more accurate on specific rank levels. In further investigation, the approximation of structural measures and Latent Semantic Analysis show a low level of overlap and the methods are found to approximate different types of relations. The results suggest that a combination of corpus-based methods and structural methods should be used and appropriate cut-off values should be selected according to the intended use case.
Achieving the Functionality of Filter Conditions in a Partial Order Planner

One of the most common modifications made to the standard STRIPS action representation is the inclusion of filter conditions. A key function of such filter conditions is to distinguish between operators that represent different context-dependent effects for the same action. We consider how filter conditions may be used to provide this functionality in a complete and correct partial order planner. We conclude that they are not effective, and that in general the use of filter conditions is incompatible with the basic assumptions that lie behind partial order planning. We present an alternative mechanism, using the secondary preconditions of Pednault (1988, 1991) to represent context-dependent effects. The use of secondary preconditions is effective, and preserves completeness and correctness.
VMASC Statistics and Social Network Analysis Project Report

Social network data are typically characterized by a set of binary link variables yi,j measured on pairs a set of objects or nodes. The presence of a link from i to j is expressed as yi,j = 1, and the absence of such a link by yi,j = 0. The situation in which it is not known whether or not there is a link from i to j is denoted as yi,j = NA, indicating the information about the relationship from i to j is “not available. ” Some network data is undirected, in which yi,j = yj,i by design. Examples of undirected data include co-membership data, sexual networks and needle-sharing networks. Data in which it possible that yi,j 6= yj,i is called directed data, and include types of communication and other social interaction data. Social network data is a particular instance of so-called relational data, which describes generic pairwise information about relationships among a set of objects. The basic notation for relational data is the same as in social network data, except that the measurement yi,j is no longer required to be binary. Relational data include such things as export and import data among countries as well as length or frequency of communications among a set of actors. Data on the relationships among n actors or nodes can be expressed as an n×n matrix Y with an undefined diagonal, typically called a sociomatrix. Frequently accompanying such relational data are vectors of predictor variables xi,j , which may be specific to nodes or pairs. For example, among a set of schoolchildren, xi,j could contain demographic information about the pair i, j such as age, sex, SES and co-residence in the same neighborhood. Information on p predictor variables measured on each pair can be expressed with an n× n× p-dimensional array X. A common approach to the analysis of such data is to fit a statistical model relating Y to X. A statistical model can provide many forms of inference, such as a description of the association ∗Departments of Statistics, Biostatistics and the Center for Statistics and the Social Sciences, University of
Zero-Efficient Buffer Design for Reliable Network-on-Chip in Tiled Chip-Multi-Processor

Network-on-chip (NoC) is a promising solution for efficient interconnection between processor cores in chip-multi-processor (CMP). This paper is focusing on the energy-efficient design of buffers, a group of the most important components in NoC. From our investigation, an overwhelming majority of "zero" is contained in the packets transmitting in NoC for CMP. A zero-efficient buffer design is proposed as well as the error control scheme. Compared with conventional design, up to 43% energy consumption can be saved. We use a 90 nm CMOS process in our simulation.
Biomedical and clinical markers, illness perceptions, coping, benefit finding, adjustment, and treatment outcomes in hepatitis C: a self-regulatory, biopsychosocial model.

Objectives. Study 1.1 investigated whether illness perceptions, adaptive and maladaptive coping strategies, and benefit finding predicted physical and psychosocial adjustment in individuals diagnosed with hepatitis C virus (HCV) within an expanded self-regulatory model of illness (SRM). Study 1.1 also determined whether coping strategies and benefit finding mediated the relationship between illness perceptions and physical and psychosocial adjustment outcomes. Study 1.2 assessed whether coping strategies independently accounted for variance in adjustment and the role of illness perceptions in predicting adjustment after controlling for coping strategies. Study 2.1 investigated whether illness perceptions and adaptive and maladaptive coping strategies predicted Hepatitis C (HCV) treatment outcomes after controlling for clinical, behavioural and demographic markers relevant to HCV. Study 2.2 assessed whether benefit finding predicted HCV treatment response after controlling for treatment control, substance use and mental health. Study 2.3 investigated whether physical (physical health) and psychosocial adjustment (depression, life satisfaction, and positive affect) predicted HCV treatment response after controlling for substance use and mental health comorbidity. Method. For Studies 1.1 and 1.2, a total of 126 participants with HCV completed an online questionnaire assessing illness perceptions, coping, benefit finding, and depression, physical functioning, life satisfaction and positive affect as the adjustment outcomes. For Studies 2.1, 2.2 and 2.3, thirty two participants with HCV completed two online questionnaires at Time 1 (pre-HCV treatment) and Time 2 (three months post commencement of HCV treatment). At time 1 clinical,
The role of thermal evaporation in galaxy formation

In colour–magnitude diagrams, most galaxies fall in either the ‘blue cloud’ or the ‘red sequence’, with the red sequence extending to significantly brighter magnitudes than the blue cloud. The bright-end of the red sequence comprises elliptical galaxies with boxy isophotes and luminosity profiles with shallow central cores, while fainter elliptical galaxies have discy isophotes and power-law inner surface-brightness profiles. An analysis of published data reveals that the centres of galaxies with power-law central surface-brightness profiles have younger stellar populations than the centres of cored galaxies. We argue that thermal evaporation of cold gas by virial-temperature gas plays an important role in determining these phenomena. In less massive galaxies, thermal evaporation is not very efficient, so significant amounts of cold gas can reach the galaxy centre and fill a central core with newly formed stars, consistent with the young stellar ages of the cusps of ellipticals with power-law surface-brightness profiles. In more massive galaxies, cold gas is evaporated within a dynamical time, so during an accretion event star formation is inhibited, and a core in the stellar density profile produced by dissipationless dynamics cannot be refilled. In this picture, the different observed properties of active galactic nuclei in higher-mass and lower-mass ellipticals are also explained because in the former the central supermassive black holes invariably accrete hot gas, while in the latter they typically accrete cold gas. An important consequence of our results is that at the present time there cannot be blue, star-forming galaxies in the most massive galactic haloes, consistent with the observed truncation of the blue cloud at ∼L*.
Design of mixed H 2 = H 1 control systems using algorithms inspired by the immune system

We utilize optimization algorithms inspired by the immune system for treating the mixed H2=H1 control problem. Both precisely known systems and uncertain systems with polytopic uncertainties are investigated. For the latter, a novel methodology is proposed to compute the worst case norms within the polytope of matrices. This methodology consists in defining the worst case norm computation as an implicit optimization problem with a special structure. We exploit this structure of the problem for its solution. The paper presents both mono and multiobjective optimization algorithms developed from the clonal selection principle. The former is the real-coded clonal selection algorithm (RCSA) and the latter is the multiobjective clonal selection algorithm (MOCSA). The complete design process involves the combination of synthesis and analysis. The RCSA is used for analysis, through the worst case norm computation for a given provided controller. The MOCSA is used for synthesis, working on a population of candidate controllers, until providing an estimate of the Pareto set for the mixed H2=H1 control problem. The numerical examples illustrate the power and the validity of the proposed approach for robust control design. Moreover, our approach for worst case norm evaluation is compared with other approaches available in literature. 2007 Elsevier Inc. All rights reserved.
Wire Segmenting For Improved Buffer Insertion

Buffer insertion seeks to place buffers on the wires of a signal netto minimize delay. Van Ginneken [Buffer Placement in Distributed RC-tree Networks for Minimal Elmore Delay] proposed an optimal dynamicprogramming solution (with extensions proposed by [7] [8][9] [12]) such that at most one buffer can be placed on a singlewire. This constraint can hurt solution quality, but it may be circumventedby dividing each wire into multiple smaller segments.This work studies the problem of finding the correct number of segmentsfor each wire in the routing tree. Too few segments yieldssub-par solutions, but too many segments can lead to excessive runtimes and memory loads. We derive new theoretical results forcomputing the appropriate number of buffers (and hence wire segments)which motivate our new wire segmenting algorithm. Weshow that using wire segmenting as a precursor to buffer insertionproduces solutions within a few percent of optimal, while usingonly seconds of CPU time.
The Relationship between L1/L2 Literacy and L3 Acquisition/Odnos između J1/J2 pismenosti i ovladavanja trećim jezikom

Abstract The present study examined the role of L1 and L2 literacy in the acquisition of English (L3) relative clauses. It was based on a correlational research design and included 100 female high school students from two educational districts of Tabriz (an Azeri-speaking city in Iran). The Oxford Solutions Placement Test, a questionnaire, and two syntactic structure tests were administered to the participants. The statistical analyses revealed: (1) no significant correlation between the bilinguals' level of literacy skills in their L1 and their acquisition of English (L3) relative clauses; (2) a significant correlation between the bilinguals' level of literacy skills in their L2 and their acquisition of English (L3) relative clauses. Key words: bilingualism; first and second language; literacy skills; third language acquisition. --- Sažetak U ovom je istraživanju analizirana uloga pismenosti na prvom (J1) i drugom (J2) jeziku u ovladavanju trecim (J3) jezikom kod dvojezicnih ispitanica koje su usvajale relativne recenice na engleskom jeziku. Pritom se koristio korelacijski nacrt istraživanja u kojem je sudjelovalo 100 ucenica srednje skole, odabranih iz dvaju obrazovnih podrucja u Tabrizu (grad u Iranu u kojem se govori azerski jezik). Od instrumenata su se koristili: test engleskog jezika (eng. The Oxford Solutions Placement Test), upitnik i dva testa za provjeru znanja o sintaktickim strukturama. Statisticke su analize otkrile da: (1) ne postoji znacajna korelacija između razine pismenosti na prvom jeziku kod dvojezicnih ucenica i njihova usvajanja relativnih recenica na engleskom kao trecem jeziku; (2) postoji znacajna korelacija između razine pismenosti na drugom jeziku kod dvojezicnih ucenica i njihova usvajanja relativnih recenica na engleskom kao trecem jeziku. Kljucne rijeci: dvojezicnost; prvi i drugi jezik; vjestine citanja i pisanja; ovladavanje trecim jezikom.
C. ELEGANS MEETS DATA SONIFICATION: CAN WE HEAR ITS ELEGANT MOVEMENT?

We introduce our video-data sonification of Caenorhabditis elegans (C. elegans) , a small nematode worm that has been extensively used as a model organism in molecular biology. C. elegans exhibits various kinds of movements, which may be altered by genetic manipulations. In pursuit of potential applications of data sonification in molecular biology, we converted video data of this worm into sounds, aiming to distinguish the movements by hearing. The video data of C. elegans wild type and transgenic types were sonified using a simple motion-detection algorithm and granular synthesis. The movement of the worm in the video was transformed into the sound cluster of very-short sine-tone wavelets. In the evaluation test, the group of ten participants (from both molecular biology and audio engineering) were able to distinguish sonifications of the different worm types with an almost 100% correct response rate. In the post-experiment interview, the participants reported more detailed and accurate comprehension on the timing of the worm’s motion in sonification than in video.
A design method for modular energy-aware software

Nowadays reducing the overall energy consumption of software is important. A well-known solution is extending the functionality of software with energy optimizers, which monitor the energy consumption of software and adapt it accordingly. To make such extensions manageable and to cope with the complexity of the software, modular design of energy-aware software is necessary. Therefore, this paper proposes a dedicated design method for energy-aware software.
Daily affective experiences predict objective sleep outcomes among adolescents

Adolescence is a sensitive period for changes in both sleep and affect. Although past research has assessed the association between affect and sleep among adolescents, few studies have examined both trait (typical) and day‐to‐day changes in affect, and fewer still have specifically examined negative social evaluative emotions (e.g. embarrassment) in relation to sleep. Both between‐ and within‐person variations in daily affect were examined in relation to four objectively‐measured sleep outcomes (sleep hours; sleep latency; sleep efficiency; and length of wake bouts) among adolescents. Participants (N = 77 high‐school students; 42.9% female; M = 14.37 years) wore an actiwatch and completed daily‐diaries for 3 days. The results of hierarchical linear models (controlling for age, gender, race, ethnicity, parental employment status, income, puberty and caffeine) indicated that negative social evaluative emotions and high‐arousal affective experiences generally predicted poor sleep outcomes, whereas low‐arousal affective experiences were associated with good sleep outcomes. Specifically, at the person level, adolescents reporting higher negative social evaluative emotions had shorter average sleep hours, and those experiencing higher anxiety–nervousness had longer wake bouts. In addition, individuals experiencing more dysphoria (sad, depressed, lonely) had longer average sleep hours and shorter wake bouts, while those experiencing more calmness had shorter sleep latencies. At the within‐person level, individuals had longer sleep latencies following days that they had experienced high‐arousal positive affect (e.g. excitement), and had longer wake bouts following days they had experienced more negative social evaluative emotions. The results highlight the detrimental effects of negative social evaluative emotions and high‐arousal affective states for adolescent sleep.
The varying relationship between New Zealand students ’ attitude to reading and reading literacy achievement

Results from the 2006 Progress in International Reading Literacy Study (PIRLS) show that for New Zealand’s Grade 4 students, those with a more positive attitude to reading tended to have higher reading literacy achievement (Chamberlain, 2007; Mullis, Martin, Kennedy, & Foy, 2007). However, in their analysis of PIRLS data English-speaking countries, Gnaldi, Schagen, Twist, and Morrison (2005), suggest that for Grade 4 students with low reading literacy achievement, the measure of attitude to reading requires careful interpretation due to those students’ difficulty understanding the items comprising this measure. This suggests the possibility of variation, with reading literacy achievement, in the relationship between attitude to reading and reading literacy achievement. The current study uses correlation curves (Bjerve & Doksum, 1993) to investigate this variation in New Zealand’s PIRLS 2006 data. It finds that, overall, the correlation between attitude to reading and reading literacy achievement varied substantially with reading literacy achievement. However, for students with reading literacy achievement between 0.5 and 1 standard deviations below the mean, and for those with reading literacy achievement just under 0.5 standard deviations above the mean, this correlation was lower than expected. This possibly indicates behavioral phenomena, test effects or a combination of both, and certainly indicates the need for further theoretical consideration and analytical work.
A Data Collector with GPRS Sever for the Research of Bioelectricity in Standing Trees

It has been observed that there is sustained bioelectricity in standing trees, which is a potential energy for wireless sensor networks. Manual measurement has been the main approach to obtain data to analyze the mechanism, which is inconvenient and possibly leads to measurement errors. In order to obtain accurate and real-time data, and to avoid human errors, an automatic data collector was designed. The collector has low power consumption and provides a reliable approach to obtain data for the research of bioelectricity in standing trees. It has the ability to automatically measure relevant parameters, including electrical potential differences between a tree and surrounding soil, air temperature, air relative humidity, soil temperature, soil moisture and light intensity, and to send data to a remote server through the GPRS network. The GPRS server has been designed and developed with Microsoft Visual Basic 6.0. It has the ability to receive data which are sent from the automatic data collector and to save the data in an Excel file, providing a convenience for the research of bioelectricity in standing trees. Copyright © 2014 IFSA Publishing, S. L.
Analysis of Android Inter-App Security Vulnerabilities Using COVERT

The state-of-the-art in securing mobile software systems are substantially intended to detect and mitigate vulnerabilities in a single app, but fail to identify vulnerabilities that arise due to the interaction of multiple apps, such as collusion attacks and privilege escalation chaining, shown to be quite common in the apps on the market. This paper demonstrates COVERT, a novel approach and accompanying tool-suite that relies on a hybrid static analysis and lightweight formal analysis technique to enable compositional security assessment of complex software. Through static analysis of Android application packages, it extracts relevant security specifications in an analyzable formal specification language, and checks them as a whole for inter-app vulnerabilities. To our knowledge, COVERT is the first formally-precise analysis tool for automated compositional analysis of Android apps. Our study of hundreds of Android apps revealed dozens of inter-app vulnerabilities, many of which were previously unknown.
Academics’ perceptions of the benefits and challenges of self and peer assessment in higher education

Abstract Despite compelling evidence of its potential effectiveness, uptake of self and peer assessment in higher education has been slower than expected. As with other assessment practices, self and peer assessment is ultimately enabled, or inhibited, by the actions of individual academics. This paper explores what academics see as the benefits and challenges of implementing self and peer assessment, through the analysis of interviews with 13 Australian academics. Thematic analysis of our qualitative data identified seven themes of benefits and five challenges. Our academics showed strong belief in the power of self and peer assessment as formative assessment, contrary to past literature which has focussed on the accuracy of students’ marking. This paper therefore brings insights as to not only what academics value about self and peer assessment but also identifies potential inhibitors in practice. Recommendations are made about improving the design and implementation of self and peer assessment in higher education.
Towards Wide Learning: Experiments in Healthcare

In this paper, a Wide Learning architecture is proposed that attempts to automate the feature engineering portion of the machine learning (ML) pipeline. Feature engineering is widely considered as the most time consuming and expert knowledge demanding portion of any ML task. The proposed feature recommendation approach is tested on 3 healthcare datasets: a) PhysioNet Challenge 2016 dataset of phonocardiogram (PCG) signals, b) MIMIC II blood pressure classification dataset of photoplethysmogram (PPG) signals and c) an emotion classification dataset of PPG signals. While the proposed method beats the state of the art techniques for 2nd and 3rd dataset, it reaches 94.38% of the accuracy level of the winner of PhysioNet Challenge 2016. In all cases, the effort to reach a satisfactory performance was drastically less (a few days) than manual feature engineering.
EEG Subband Analysis using Approximate Entropy for the Detection of Epilepsy

Epilepsy is a neurological disorder which affects the nervous system. Epileptic seizures are due to sudden hyperactivity in certain parts of the brain. Electroencephalogram (EEG) is the commonly used modality for the detection of epilepsy. Automatic seizure detection helps in diagnosis and monitoring of epilepsy especially during long term recordings of EEG. This paper presents non linear analysis of EEG for the detection of epilepsy using approximate entropy (ApEn). The proposed method involves ApEn measured from EEG subbands applied as features to an artificial neural network (ANN) classifier. The ApEn measured from delta, theta, alpha, beta and gamma subbands of normal EEG, ictal and inter ictal EEGs are used as features. In the present work detection of epilepsy is considered as a two class problem. In the first case the classification is done between normal and ictal EEGs and in the second case, classification is done between normal and inter ictal EEGs. For both cases artificial neural networks with back propagation training are used as classifiers. The classification accuracy of 100% is obtained for normal and ictal groups and that of 98.9% is obtained for normal and inters ictal EEGs.