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关键词： Education   Bibliometrics   Collaboration   Licenses   International collaboration   Computer science   Buildings   Computer science education   computing education research   computing education   scientometrics   science mapping   review  

摘要： Computerisation and digitalisation are shaping the world in fundamental and unpredictable ways, which highlights the importance of computing education research (CER). As part of understanding the roots of CER, it is crucial to investigate the evolution of CER as a research discipline. In this paper we present a case study of a Finnish CER conference called Koli Calling, which was launched in 2001, and which has become a central publication venue of CER. We use data from 2001 to 2020, and investigate the evolution of Koli Calling's scholarly communities and zoom in on it's publication habits and internalisation process. We explore the narrative of the development and scholarly agenda behind changes in the conference submission categories from the perspective of some of the conference chairs over the years. We then take a qualitative perspective, analysing the conference publications based on a comprehensive bibliometric analysis. The outcomes include classification of important research clusters of authors in the community of conference contributors. Interestingly, we find traces of important events in the historical development of CER. In particular, we find clusters emerging from specific research capacity building initiatives and we can trace how these connect research spanning the world CER community from Finland to Sweden and then further to the USA, Australia and New Zealand. This paper makes a strategic contribution to the evolution of CER as a research discipline, from the perspective of one central event and publication venue, providing a broad perspective on the role of the conference in connecting research clusters and establishing an international research community. This work contributes insights to researchers in one specific CER community and how they shape the future of computing education

关键词： Public health   Artificial intelligence   Computer science   Medicine   Oncology   Pharmaceutical sciences   Pharmacology   Physics   Therapy  

摘要： Adverse drug events represent a key challenge in public health, especially with respect to drug safety profiling and drug surveillance. Drug-drug interactions represent one of the most popular types of adverse drug events. Most computational approaches to this problem have used different types of drug-related information utilizing different types of machine learning algorithms to predict potential interactions between drugs. In this work, our focus is on the use of genetic information about the drugs, in particular, the protein sequence and protein structure of drug protein targets to predict potential interactions between drugs. We collected information on drug-drug interactions (DDIs) from the DrugBank database and divided them into multiple datasets based on the type of information, such as, chemical structure, protein targets, side effects, pathways, protein-protein interactions, protein structure, information about indications. We proposed a similarity-based Neural Network framework called protein sequence-structure similarity network (S3N), and used this to predict the novel DDI’s. The drug-drug similarities are computed using different categories of drug information based on multiple similarity metrics. We compare the results with those from the state-of-the art methods on this problem. Our results show that proposed method is quite competitive, at times outperforming the state-of-the-art. Our performance evaluations on different datasets showed the predictive performance as follows: Precision 91%-98%, Recall 90%-96%, F1 Score 86%-95%, AUC 88%-99% Accuracy 86%-95%. To further investigate the reliability of the proposed method, we utilize 158 drugs related to cardiovascular disease to evaluate the performance of our model and find out the new interactions among the drugs. Our model showed 90% accuracy of detecting the existing drug interactions and identified 60 new DDI’s for the cardiovascular drugs. Our evaluation demonstrates the effectiveness of S3N in pre

关键词： 科教融合   计算机专业   培养模式  

摘要： 目前我国高等教育进入了快速发展新阶段，创新人才培养受到各高校的重视。如何提高本科生创新人才创新能力，科学研究如何与教学相融合，成为目前高校重点关注的话题。为提高大学生的科研能力和创新创业能力，针对高校计算机专业人才的培养模式进行分析，通过分析科教融合发展与现状，探索基于科教融合的计算机创新人才培养模式，将课程思政融入科学实践联合培养，引入开放基金项目为驱动的培养路径，提出阶梯式科教融合培养模式。通过在计算机专业探索与实践，取得了显著的教学成果，培养的学生获得了各类大学生创新比赛奖项，获批各级大学生创新训练计划项目，科研能力得到进一步提升。基于科教融合开展的计算机创新人才培养，满足新时代办学治校的新要求，为高校创建一流大学提供了新思路。

关键词： 初中英语   单元教学   整体性评价  

摘要： 课堂教学评价应将教学活动与评价活动有机结合，教学评价应发生在教学活动中，是英语课程教学的重要活动。然而，目前初中英语教师在课堂上采用的教学评价仍然停留在内容单一，教师为主，没有具体、可操作、可检测的教学活动上。文章在单元整体视域下，以人教版八上Unit 6 “I'm going to study computer science” 为例，通过“教学内容分析、教学目标设计、教学评价活动设计”等环节，探索单元整体教学评价活动设计的新思路，使英语课堂教与学的效率得到提高。

关键词： Bisac category: computers   software development \u0026 engineering   computer graphics   computers   computer simulation   computers   computer science  

ISBN: (数字)9781636393216 ISBN: (纸本)9781636393209;9781636393223

摘要： This book gives a broad overview of research on sound simulation driven by a variety of applications. Vibrating objects produce sound, which then propagates through a medium such as air or water before finally being heard by a listener. As a crucial sensory channel, sound plays a vital role in many applications. There is a well-established research community in acoustics that has studied the problems related to sound simulation for six decades. Some of the earliest work was motivated by the design of concert halls, theaters, or lecture rooms with good acoustic characteristics. These problems also have been investigated in other applications, including noise control and sound design for urban planning, building construction, and automotive applications. Moreover, plausible or realistic sound effects can improve the sense of presence in a virtual environment or a game. In these applications, sound can provide important clues such as source directionality and spatial *** book first surveys various sound synthesis methods, including harmonic synthesis, texture synthesis, spectral analysis, and physics-based synthesis. Next, it provides an overview of sound propagation techniques, including wave-based methods, geometric-based methods, and hybrid methods. The book also summarizes various techniques for sound rendering. Finally, it surveys some recent trends, including the use of machine learning methods to accelerate sound simulation and the use of sound simulation techniques for other applications such as speech recognition, source localization, and computer-aided design.

关键词： Graphics processing units   Hardware   Scalability   Bandwidth   Fans   Computer science   Libraries   Reproducible computation   student cluster competition  

摘要： Hidayetolu et al. (2019) proposed a novel memory-centric computation system, MemXCT. As a challenge at SC20, we reproduce the computational efficiency of MemXCT on our Azure cloud cluster. Our experiments evaluate the overall performance and the strong scalability with real datasets and verify part of the conclusions in the original article.

摘要： ~~

关键词： Computer science  

ISBN: (数字)9783110788105;9783110788198 ISBN: (纸本)9783110787993

摘要： This book provides an up-to-date account of current research in quantum information theory, at the intersection of theoretical computer science, quantum physics, and mathematics. The book confronts many unprecedented theoretical challenges generated by infi nite dimensionality and memory effects in quantum communication. The book will also equip readers with all the required mathematical tools to understand these essential questions.

关键词： Software engineering   Computer science   Software fault localization   Software debugging   Causal inference   Machine learning  

摘要： Statistical fault localization (SFL) techniques use execution profiles and success/failure information from software executions, in conjunction with statistical inference, to automatically score program elements based on how likely they are to be faulty. SFL techniques typically employ one type of profile data: coverage data, predicate outcomes, or variable values. In the relatively short history of automated SFL, most proposed techniques are based on statistical relationships between the elements of coverage profiles/spectra and the occurrences of program failures. Valuable information carried by variables has usually been ignored, and far fewer techniques are based on the analysis of variable values. In addition, the vast majority of subject programs used to evaluate techniques have been small programs containing artificial faults (faults created by mutations in code), rather than large programs containing real faults (faults logged by developers), which inhibit the credibility of these techniques. Most SFL techniques measure correlation, rather than causation, between profile values and success/failure, and so, they are subject to confounding bias that distorts the scores they produce. In recent years, techniques using the sound causal inference methodology (Causal Statistical Fault Localization) to adjust for the confounding bias properly have been successfully applied to a wide range of programs and profile data. While these first attempts at causal statistical fault localization have yielded promising results, they have lacked cohesion between the different types of profile data, flexible machine learning models, or large subject programs containing real faults in their empirical evaluation. In my work, I present new insights into the properties and limitations inherent in the SFL literature and their effect on the performance of SFL. Furthermore, I present novel algorithms that use causal inference techniques and flexible machine learning models to integrate

关键词： African Americans   Chicago   Economic mobility  

摘要： The City of Chicago is one of the most racially segregated cities in America. This thesis looks at the series of decisions made to create a culture that allowed the policy of hate to be ensconced in the lives of Black Chicagoans for the better part of a century. This culture, deemed in this paper as “Security Culture,” was designed to stagnate Black life and relegate it to the outskirts of not only the city but of upper society. In the midst of the 21st century, the rise of “Cancel Culture”—or attempts to hold controversial statements and action to account—took hold. This study aims to interrogate what effect the trauma of living in Security Culture has caused Black Chicagoans if any and what identity shifts Black people have made to rationalize their upward mobility if earned. To test this theory, a new grading scale was developed, the Compounding Racial Trauma Index Score, that looked at six neighborhoods across the Chicagoland area. Each neighborhood was scored based on metrics of health and wealth. Lastly a series of semi- structured interviews were conducted with people who were born before and after the highway was developed to determine how Security Culture altered their lives and or decisions in Chicago. The results showed that neighborhoods in Chicago are as segregated as ever and neighborhoods with wealthier Black families do not necessarily create environments that foster Black wealth for other Black residents. This as wealthy White families create environments that allow other Whites to create generational wealth. These results suggest and reinforce the theory that Black people form new middle-class identities while also navigating a Security Culture that despite attempts at nullification is still as prolific as ever.