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关键词： Java   Genetic algorithms   Learning systems   Biological cells   Programming profession   Education   Adaptive computer learning   computer science   educational software   genetic algorithms   individual differences   object-oriented programming   remedial learning  

摘要： Contribution: An online genetic algorithm-based remedial learning system is presented in order to strengthen students' understanding of object-oriented programming (OOP) concepts by tailoring personalized learning materials according to each student's strengths and weaknesses. Background: Prior studies on computer programming education have analyzed methods of learning OOP, and shown that teaching this topic is a challenge. A simple and personalized learning system for generating remedial learning materials would therefore be valuable, but had yet to be designed. Intended Outcomes: Students' grasp of OOP concepts is expected to improve through study of the tailored remedial learning materials generated by the system. Application Design: Students who had previously studied OOP were recruited to test the learning system in a two-semester pre-experiment using a one-group pre-test-post-test design. The students first took a pre-test that determined their individual strengths and weaknesses in these concepts. They then read three sets of quiz-based remedial learning materials; each set was generated by the system according to the individual student's answers in the pre-test and previous quizzes. Findings: 1) Overall, the changes between learners' pre-and post-test scores were significant; 2) Score changes for different learners (junior, senior, low-achievement, and high-achievement learners) and for different learning styles (intensive and non-intensive) were also significant; and 3) Score changes for low-achievement learners were greater than those for high-achievement learners.

关键词： Runtime verification   Formal methods   Computer science   Formal verification   COMPONENT-BASED SYSTEMS   TEMPORAL-LOGIC   PARAMETER SYNTHESIS   INFORMATION-FLOW   HYBRID SYSTEMS   MODEL CHECKING   TIME   FRAMEWORK   SPECIFICATIONS   ROBUSTNESS  

摘要： Runtime verification is an area of formal methods that studies the dynamic analysis of execution traces against formal specifications. Typically, the two main activities in runtime verification efforts are the process of creating monitors from specifications, and the algorithms for the evaluation of traces against the generated monitors. Other activities involve the instrumentation of the system to generate the trace and the communication between the system under analysis and the monitor. Most of the applications in runtime verification have been focused on the dynamic analysis of software, even though there are many more potential applications to other computational devices and target systems. In this paper we present a collection of challenges for runtime verification extracted from concrete application domains, focusing on the difficulties that must be overcome to tackle these specific challenges. The computational models that characterize these domains require to devise new techniques beyond the current state of the art in runtime verification.

关键词： Clustering algorithms   Linear programming   Kernel   Iterative methods   Computer science   Anomaly detection   Task analysis   Overlapping clustering   K-Means   outlier   semidefinite programming   graph clustering   community detection   ALGORITHM   CONVERGENCE   CUTS  

摘要： Traditional clustering algorithms, such as K-Means, output a clustering that is disjoint and exhaustive, i.e., every single data point is assigned to exactly one cluster. However, in many real-world datasets, clusters can overlap and there are often outliers that do not belong to any cluster. While this is a well-recognized problem, most existing algorithms address either overlap or outlier detection and do not tackle the problem in a unified way. In this paper, we propose an intuitive objective function, which we call the NEO-K-Means (Non-Exhaustive, Overlapping K-Means) objective, that captures the issues of overlap and non-exhaustiveness in a unified manner. Our objective function can be viewed as a reformulation of the traditional K-Means objective, with easy-to-understand parameters that capture the degrees of overlap and non-exhaustiveness. By considering an extension to weighted kernel K-Means, we show that we can also apply our NEO-K-Means idea to overlapping community detection, which is an important task in network analysis. To optimize the NEO-K-Means objective, we develop not only fast iterative algorithms but also more sophisticated algorithms using low-rank semidefinite programming techniques. Our experimental results show that the new objective and algorithms are effective in finding ground-truth clusterings that have varied overlap and non-exhaustiveness; for the case of graphs, we show that our method outperforms state-of-the-art overlapping community detection algorithms.

关键词： Feature extraction   Spatiotemporal phenomena   Neural networks   Streaming media   Solid modeling   Learning systems   Computer science   3-D convolution   global representations   person reidentification (re-ID)   vector of local aggregated descriptors (VLAD)  

摘要： We present the global deep video representation learning to video-based person reidentification (re-ID) that aggregates local 3-D features across the entire video extent. Existing methods typically extract frame-wise deep features from 2-D convolutional networks (ConvNets) which are pooled temporally to produce the video-level representations. However, 2-D ConvNets lose temporal priors immediately after the convolutions, and a separate temporal pooling is limited in capturing human motion in short sequences. In this paper, we present global video representation learning, to be complementary to 3-D ConvNets as a novel layer to capture the appearance and motion dynamics in full-length videos. Nevertheless, encoding each video frame in its entirety and computing aggregate global representations across all frames is tremendously challenging due to the occlusions and misalignments. To resolve this, our proposed network is further augmented with the 3-D part alignment to learn local features through the soft-attention module. These attended features are statistically aggregated to yield identity-discriminative representations. Our global 3-D features are demonstrated to achieve the state-of-the-art results on three benchmark data sets: MARS, Imagery Library for Intelligent Detection Systems-Video Re-identification, and PRID2011.

关键词： International cooperation  

摘要： THEORETICAL COMPUTER SCIENCE has been a vibrant part of computing research in India for the past 30 years. India has always had a strong mathematical tradition. One could also argue that in the 1980s and 1990s, theory offered a unique opportunity to keep up with international research in computing despite limited access to state-of-the-art hardware. The Annual International Conference Foundations of Software Technology and Theoretical Computer Science (FSTTCS) was launched in 1981. FSTTCS2 allowed Indian researchers a natural opportunity to interact with leading academics worldwide. Another early impetus was funding for international collaboration through agencies such as the Indo-French Centre for Promotion of Advanced Research (CEFIPRA). © 2019 ACM.

关键词： Computer science   Intentional teaching   Communities of practice   Primary education  

摘要： Computer Science (CS) education is being increasingly included in primary school curricula across New Zealand. As a group, Pasifika students are less likely to engage with CS at tertiary level and in the workforce, so understanding more about their engagement with school level CS seems important. A multiple case-study design was used to explore the nature of engagement with CS for six Year 7 and 8 Pasifika students. Data were collected via a drawing task, semi-structured interviews and observations of CS teaching sessions then analysed using inductive thematic analysis. Four themes emerged as important to participant engagement with CS: participation, reification, imagination and alignment. Additionally, several potential barriers and enablers were identified across three broad themes: access, perceptions and affect. Results highlight Pasifika students' need for adequate access to CS education and intentional teaching around its purpose and relevance to their current and future identities.

关键词： Software engineering   WCAG 2   0   Testing tools   Usability testing   Web design   Computer science   FEDERAL-GOVERNMENT  

摘要： The current development of the Internet and its growing use make it necessary to satisfy the needs of users with disabilities. The primary objective of this study is to examine healthcare-related websites in nine European countries in order to evaluate the status of their accessibility. Such a detailed statistical comparison has not yet been made in Europe, especially as the present study offers a dual measurement system combining both the application of automated testing software and statistical analysis of user feedback. The study compares 48 websites from Eastern Europe with 51 sites from Western and Northern Europe. The research phase was performed in three steps: firstly by using AChecker, secondly by Nibbler and subsequently followed by user feedback questionnaires evaluated by a group of experts. The overall goal of this study is to determine the most common accessibility problems and to draw site owners' attention to shortcomings so that they can improve the quality of service of their healthcare-related sites in the future. The investigated European websites are grouped into Eastern and Western-Northern countries. We compared our results from different perspectives and ascertained that no significant differences can be established between the two groups predicated on their respective economic situations. Equally, no correlations were observed while comparing the sizes of web pages in Kbytes, the number of barriers and their Nibbler accessibility scores. Furthermore, there appears to be no correlation between the results of the software tests and the percentage of the elderly population in the respective country.

关键词： depression   hair cortisol   HPA axis   life stress   HAIR CORTISOL-LEVELS   SALIVARY CORTISOL   MAJOR DEPRESSION   DIURNAL CORTISOL   1ST ONSET   COGNITIVE VULNERABILITIES   INTERPERSONAL STRESS   HEALTHY-INDIVIDUALS   MORNING CORTISOL   PREDICTORS  

摘要： Background Stress is consistently implicated in depression. Using a vulnerability-stress framework, the hypothalamic-pituitary-adrenal (HPA) axis may be one factor affecting the stress-depression association. However, the interactive influence of recent life stress and HPA axis functioning on depressive symptoms remains unclear. It is particularly important to understand the synergistic association during adolescence, as this is a developmental period associated with a high risk for depression. Methods A community sample of 58 adolescents (67% female, 59% Caucasian; mean age, 15.07 years) participated. Adolescents completed a well-validated measure of depressive symptoms and a structured life events interview to assess recent life stress. Hair cortisol concentration was obtained to measure cumulative exposure to HPA axis functioning. Results Recent life stress and cumulative HPA axis exposure measured through hair cortisol were directly associated with higher depressive symptoms. Further, cumulative HPA axis exposure moderated the relationship between recent life stress and depressive symptoms. The recent life stress-depression association occurred for adolescents who experienced average and high, but not low, levels of cumulative HPA axis exposure. Conclusions The current study builds on prior work and finds both a direct and interactive association of recent life stress and cumulative HPA axis functioning with depressive symptoms during adolescence. Identifying youth who experience high levels of HPA axis exposure is important to prevent the onset of depression.

关键词： Astronomy and astrophysics   Computer science   Mathematics and computing   Neuroscience   Ocean sciences  

摘要： Andrew Robinson reviews five of the week’s best science picks.

关键词： Education   Computer science   Data analysis   Connectivism   Personal learning environments   Learning communities   Adaptive learning objects  

摘要： Eco-connectivist communities are groups of individuals with similar characteristics, which emerge in a connectivist learning process within a knowledge ecology. ARMAGAeco-c is a reflexive and autonomic middleware for the management and optimization of eco-connectivist knowledge ecologies using description, prediction and prescription models. Adaptive Learning Objects are autonomic components that seek to personalize Learning Objects according to certain contextual information, such as learning styles of the learner's, technological restrictions, among other aspects. MALO is a system that allows the management of Adaptive Learning Objects. One of the main challenges of the connectivist learning process is the adaptation of the educational context to the student needs. One of them is the learning objects. For this reason, this work has two objectives, specifying a data analytics task to determine the learning style of a student in an eco-connectivist community and, adapting instances of Adaptive Learning Objects using the learning styles of the students in the communities. We use graph theory to identify the referential member of each eco-connectivist community, and a learning paradigm detection algorithm to identify the set of activities, strategies, and tools that Adaptive Learning Objects instances should have, according to the learning style of the referential member. To test our approach, a case study is presented, which demonstrates the validity of our approach.