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关键词： Mobile applications   Data collection   Monitoring   Data analysis   Computer science   Tutorials   Stakeholders   Smartphone device   mobile app   app usage   behavior analysis   data mining  

摘要： As smartphones have become indispensable personal devices, the number of smartphone users has increased dramatically over the last decade. These personal devices, which are supported by a variety of smartphone apps, allow people to access Internet services in a convenient and ubiquitous manner. App developers and service providers can collect fine-grained app usage traces, revealing connections between users, apps, and smartphones. We present a comprehensive review of the most recent research on smartphone app usage analysis in this survey. Our survey summarizes advanced technologies and key patterns in smartphone app usage behaviors, all of which have significant implications for all relevant stakeholders, including academia and industry. We begin by describing four data collection methods: surveys, monitoring apps, network operators, and app stores, as well as nine publicly available app usage datasets. We then systematically summarize the related studies of app usage analysis in three domains: app domain, user domain, and smartphone domain. We make a detailed taxonomy of the problem studied, the datasets used, the methods used, and the significant results obtained in each domain. Finally, we discuss future directions in this exciting field by highlighting research challenges.

关键词： Unified modeling language   Software design   Object oriented modeling   Software   Syntactics   Object recognition   Codes   Computer science   computer science education   object oriented modeling   software design   software engineering   systems engineering education  

摘要： Software modeling is a creative activity in which software components and their relationships are identified based on customer requirements. Based on the literature, object-oriented software modeling is based on four fundamental pillars which are abstraction, encapsulation, decomposition, and inheritance. However, despite the existence of guidelines and recommendations for implementing the object-oriented approach, novice software designers do not make good design decisions, leading to inefficient designs that cannot be modifiable, understandable, or user-friendly distribute at the development level. The literature reveals that the most common difficulties faced by software designers is a lack of understanding and confusion of concepts related to the object-oriented approach, as well as difficulties in creating Unified Modeling Language diagrams, especially class diagrams. The work presented in this article uses a qualitative and quantitative approach to determine, in a group of university students, what are the most recurrent difficulties and their persistence during the time. The qualitative case study is the method that allowed to generate the documents: diagnostic and evaluation tests. Additionally, a thematic analysis was used to identify, analyze and report patterns within the data. In order to know the occurrences of the problems in the case study, as part of our quantitative approach, a comparative study was applied to compare the results obtained between the diagnostic and evaluation tests and thus establish the similarities and differences among the cases observed, through the hierarchical clustering technique. The findings of this study show us 16 difficulties identified after the qualitative analysis, while the quantitative analysis shows us the number of occurrences and their persistence over time. The difficulties reported in both analyzes focus on these three difficulties: a) Definition of attributes that could be a class, b) Classes with inadequate o

关键词： Automated construction   Machine Learning   Construction   Safety   Near-Miss Reporting   Neural Networks   n-grams  

摘要： Limited academic attention has been paid to the applicability of Machine Learning (ML) approaches for analyzing worker-reported near-miss safety reports, as opposed to injury reports, at construction sites. Although resource-efficient analysis through ML of large volumes of such data at construction sites can help guide practitioners in decision-making to prevent injuries. The current study addresses this research gap by evaluating the relevance of ML approaches through quantitative and qualitative methods for scaling efficient near-miss reporting programs at construction sites. The study uses an extensive experimentation strategy consisting of input data processing, n-gram modeling, and sensitivity analysis. It first tests the proposition that, despite the data -quality challenges, the high performance of different ML algorithms can be achieved in automatically classifying the textual near-miss observations. The study relies on worker-reported near-miss data collected from a real construction site in Kuwait. The classification performance of various ML approaches is evaluated using F1 scores for three academically novel but commonly used category labels at the sites -"Unsafe Act (UA)," "Unsafe Condition (UC)," and "Good Observation (GO)." In addition, the practitioner's input was utilized to assess the practical applicability of ML classifiers for construction sites. The conventional Logistic Regression (LR) classifiers have a comparatively high F1 score of 0.79. However, ML classifiers faced challenges in distinguishing between UA and UC. Further, the analysis reveals that optimal ML classifiers may lose on being acceptable to human decision-makers. Overall, despite the promising performance of ML tools for the near-miss data, the sites with low maturity of reporting systems may find themselves unable to leverage ML to scale their reporting systems. A simplified experimentation strategy like the current study could help practitioners identify the data-specific opt

关键词： Ontologies   Computer science   Metadata   Measurement   Industries   Licenses   Collaboration   Scholarly data   knowledge graph   conference analytics   bibliographic data   scholarly ontologies   science of science  

摘要： Scientific conferences are essential for developing active research communities, promoting the cross-pollination of ideas and technologies, bridging between academia and industry, and disseminating new findings. Analyzing and monitoring scientific conferences is thus crucial for all users who need to take informed decisions in this space. However, scholarly search engines and bibliometric applications only provide a limited set of analytics for assessing research conferences, preventing us from performing a comprehensive analysis of these events. In this paper, we introduce the AIDA Dashboard, a novel web application, developed in collaboration with Springer Nature, for analyzing and comparing scientific conferences. This tool introduces three major new features: 1) it enables users to easily compare conferences within specific fields (e.g., Digital Libraries) and time-frames (e.g., the last five years);2) it characterises conferences according to a 14K research topics from the Computer Science Ontology (CSO);and 3) it provides several functionalities for assessing the involvement of commercial organizations, including the ability to characterize industrial contributions according to 66 industrial sectors (e.g., automotive, financial, energy, electronics) from the Industrial Sectors Ontology (INDUSO). We evaluated the AIDA Dashboard by performing both a quantitative evaluation and a user study, obtaining excellent results in terms of quality of the analytics and usability.

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： 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.

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