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关键词： Costs   Lattices   Manganese   Computer science   Read only memory   Computational modeling   Computational efficiency   Group signatures   time-bound keys   lattice-based cryptography   anonymity  

摘要： Group signatures are active cryptographic topics where group members are granted right to sign messages anonymously on behalf of their group. However, in practical applications, such rights are not permanent in most cases and are usually limited to some time periods. This means that the signing right of each group member needs to be associated with time periods such that it can be automatically changed with the latter. Among the known approaches, verifier local revocation (VLR) seems to be the feasible one to implement the above functionality, but it will cause an inefficient verification process when the group size is large. In this paper, we describe a group signature scheme with time-bound keys, based on the hardness of lattice assumption, which implements the limitation of the signing right to any time period by constructing a lattice-based redactable signature scheme. Our scheme still adds VLR mechanism for some members who need to revoke prematurely, but the time-bound keys function ensures such members are only a small fraction that do not incur excessive cost for revocation check. We give implementation for our scheme under 93-bit and 207-bit security respectively to demonstrate the practicability-all costs are independent of the group size and achieve a relatively efficient level.

关键词： Prediction algorithms   Collaborative filtering   Costs   Clustering algorithms   Motion pictures   Computer science   Semantics   user reviews   aspects   Word2vec   K-means clustering   Euclidean distance  

摘要： Collaborative filtering (CF) is one of the most widely utilised approaches in recommendation techniques. It suggests items to users based on the ratings of other users who share their preferences. Thus, one of the aims of CF is to find reliable neighbours. Typically, CF produces a sparse user-item rating matrix, when relying only on the ratings to identify the precise neighbours, resulting in poor performance. User reviews can be essential in overcoming those situations because of the diverse elements available in reviews. The most popular element is aspects, which can provide a fine-grained analysis of users' behaviours, thus improving personalised recommendations. However, increasing the number of aspects also results in sparsity, therefore may deteriorate the recommendation performance. As a result, clustering of aspects may lessen this sparsity, but it is yet unclear how much this would affect the performance of CF systems. This study proposes a CF approach based on aspect clustering that addresses the above issue in terms of rating prediction. The approach aims to reduce the sparseness in the multi-criteria rating matrix by grouping aspects into clusters based on their semantic similarity, which will be less expensive and require less memory to discover the neighbourhood set. Our approach extracts aspects and represents them using Google's pre-trained Word2vec model. Then, aspects are organised into clusters using the K-means clustering algorithm. Multi-dimensional Euclidean distance is used as a similarity measure for finding the appropriate neighbours and predicted ratings of unseen items are then made using the k NN algorithm. This study also identifies the number of aspects that significantly impacts CF performance. Experiments are carried out using a real large-scale dataset: the Amazon movie dataset. Evaluation is also performed by comparing CF performance of the proposed approach with three different baseline approaches. Results show that the proposed ap

关键词： 物的社会生命   行动者网络理论   语境化   奥林匹克运动   体育文化　　the social life of things   actor-network theory   context   Olympic Movement   sports culture  

摘要： 本文以奥运金牌的物质性和社会符号意义为视角，试图在“社会的社会学”和“联结的社会学”两种对立范式之间寻找交互融合的解释机制，以探讨金牌嵌入社会文化之中的行动逻辑，考察金牌与其他行动者交互所建构的社会事实。金牌在从被激活到发挥能动作用，再到语境再造的社会生命历程中，转化为一种社会生产力，促进了奥运冠军等行动者的社会阶序跃迁，激励了竞技体育从业者行为，在群体中创造了区隔与联结；金牌在礼俗社会中的嵌入，揭示了现代性背景下人情关系互动的变异趋势和价值属性，以及社会交换互动和权力运行的微观生态。随着金牌进入展陈状态，它不但促进了社会记忆的再语境化，延续了“物之活力”，而且表意了新文化空间的生成，形塑了一种社会网络体系和文化传承机制。

关键词： Audience response system   Confidence   Engagement   Technology advances  

摘要： Technology advances have changed the way faculty teach and students learn. The classroom has evolved from students listening to their faculty lecture to convey their knowledge to students utilizing interactive electronic resources that can take students worldwide in milliseconds. Tools in the classroom have also allowed faculty to quiz students with immediate feedback so that the faculty can adjust their lessons on the spot and cover concepts that students are struggling with understanding. For example, Audience Response Systems (ARS) are a form of quizzing tool that allows the faculty to engage more with students and cover material that students struggle with immediately. This research evaluated the student and alums confidence and knowledge gained between a traditional lecture class and a class that used an ARS as a lecture replacement in a computer science program at a community college. Results indicate that using an ARS affects computer science students, increasing their engagement and confidence. Four themes that appeared from the research included Knowledge, Engagement, Balance, and Support. Students felt that adding an ARS to their classes helped increase the knowledge gained in the course. They also thought that using an ARS increased their engagement in their classes and with the faculty and fellow students. Participants also believed that there was support for them with an increased ability to ask questions of their faculty and other students. Finally, participants believed that using an ARS was one part of a balanced course when paired with other modalities such as lectures and hands-on activities. The research revealed that using an ARS in classes increased students' confidence and knowledge, but it was only one part of the process. The conclusion of the research suggests that using an ARS should be incorporated with other modalities to enrich the students’ experience and boost engagement, thus increasing knowledge.

ISBN: (纸本)9787111718161

关键词： Measurement   Training   Visualization   Task analysis   Computer science   Decoding   Electronic mail   Diverse video captioning   conditional variational autoencoders   progressive training  

摘要： Describing a video using natural language is an inherently one-to-many translation task. To generate diverse captions, existing VAE-based generative models typically learn factorized latent codes via one-stage training merely from stand-alone video-caption pairs. However, such a paradigm neglects set-level relationships among captions from the same video, not fully capturing the underlying multimodality of the generative process. To overcome this shortcoming, we leverage neighbouring descriptions for the same video that are articulated with noticeable topics and language variations (i.e., paraphrases). To this end, we propose a novel progressive training method by decomposing the learning of latent variables into two stages that are topic-oriented and paraphrase-oriented, respectively. Specifically, the model learns from divergent topic sentences obtained by semantic-based clustering in the first stage. It is then trained again through paraphrases with a cluster-aware adaptive regularization, allowing more intra-cluster variations. Furthermore, we introduce an overall metric DAUM, a Diversity-Accuracy Unified Metric to consider both the precision of the generated caption set and its coverage on the reference set, which has proved to have a higher correlation with human judgment than previous precision-only metrics. Extensive experiments on three large-scale video datasets show that the proposed training strategy can achieve superior performance in terms of accuracy, diversity, and DAUM over several baselines.

关键词： Computer Science  

ISBN: (数字)9788770229883 ISBN: (纸本)9788770229890

摘要： This book provides practical advice for everyone on how to effectively secure yourself, your devices, and your privacy in an era where all of those things seem doomed. From acquiring software, to the ongoing flaws in email, to the risks of file sharing, and issues surrounding social media and social reputation, Practical Insecurity is the tool you need to maximize your self-protection in the digital world. Everyone has had a brush with cybersecurity—in some way. Our computer has gotten a virus, somebody you know has lost all their company’s data because of ransomware, someone has stolen our identity, a store we do business with has their computer system compromised—including our account—so we are offered free identity protection, and so on. It seems like everyday there is another bit of bad news and it often impacts us. But, the question largely goes unanswered: what can I do as an individual or as the owner of a small business to protect myself against having my security compromised? Practical Insecurity provides the answers.

关键词： Documentation   Web services   Mobile applications   Software engineering   Data processing   Software development management   Computer science   Client applications   web services   web APIs   client application problems  

摘要： Web Services (WSs) are gaining worldwide popularity due to reliable and fast intercommunication services for the development of web and mobile applications. WSs are provided to client application developers through web Application Programming Interfaces (APIs), such as YouTube API, Twitter API, Facebook API, etc. Due to the popularity of WSs, the developers frequently discuss various WSs-based application' issues on online forums, such as Stack Overflow (SO). This study aims to highlight the problems faced by client developers in the development process of WSs-based applications using the dataset of SO. The comprehension of developers' conversations on SO can give insight into the frequency, difficulty, and popularity of different WSs-related problems of developers. We downloaded 12,746 posts from SO relevant to WSs-related issues for this article. We used the topic modeling technique (LDA) to extract various topics from the SO dataset. The topics are labeled and organized into categories and sub-categories according to relationships among them. The difficulty and popularity of each topic have been analyzed. Our investigation yield several findings. First, developers focus on six topics related to WSs on SO: Client APIs development, Data Processing, Web services Authorization, Framework Support, Web APIs, and Mobile Applications. Secondly, the advantages and disadvantages of web applications topic (Fused_Popularity=0.39), from the Clients APIs development category have the highest prevalence, followed by Database (DB) and Data Processing in Applications topic (Fused_Popularity=0.38) from the Data Processing category. Third, most WSs-related topics in all categories are evolving promptly on SO, i.e., new questions are added daily about WSs development, deployment, and authorization. Fourth, the questions of type howare primarily asked in Framework support, Client APIs development, and Web APIs categories. Although, many questions in other categories are of the kind W

关键词： Curriculum studies   Gender bias   Video games   Women   Sexism  

摘要： This doctoral dissertation documents the experiences of women (student and faculty) in computer science programs. The research emerges from the literature on the gender gap in computing and video gaming. Thus, the author seeks to find the meaning that participants have granted to their experiences as undergraduate students and faculty, in a climate that has marginalized them. It is believed that through the study and insight of the participants' anecdotal data, the researcher will find pertinent ways to understand how the current curricular practices and scholarship have perpetuated misogyny, gender-bias, and the silencing of women in computing and video gaming. The experiences documented for this research consist of five women participants (two students and three faculty). The data collected through phenomenological interviews, where women discussed their experiences as students and educators, with video games, and their thoughts on how to improve the pathway for other women. Through the interviews, the researcher identified four themes: bias in computing, sexism in video games, pertinence of gender in computer science, and improving the pathway. The themes and meaning of the participants illustrate the challenges these women have encountered in their field. Paralleled to the challenges they identify opportunities for growth as future computer scientists (students), and as educators. Their agency in a socio-political climate of misogyny and marginalization, has served as a called to become part of history and a movement that seeks to set the path for women.

关键词： Team sports   Prediction   Algorithm   Computer science   Big data  

摘要： Due to the chaotic nature of soccer, the predictive statistical models have become in a current challenge to decision-making based on scientific evidence. The aim of the present study was to systematically identify original studies that applied machine learning (ML) to soccer data, highlighting current possibilities in ML and future applications. A systematic review of PubMed, SPORTDiscus, and FECYT (Web of Sciences, CCC, DIIDW, KJD, MEDLINE, RSCI, and SCIELO) was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 145 studies initially identified, 32 were fully reviewed, and their outcome measures were extracted and analyzed. In summary, all articles were clustered into three groups: injury (n = 7);performance (n = 21), which was classified in match/league outcomes forecasting, physical/physiological forecasting, and technical/tactical forecasting;and the last group was about talent forecasting (n = 5). The development of technology, and subsequently the large amount of data available, has become ML in an important strategy to help team staff members in decision-making predicting dose-response relationship reducing the chaotic nature of this team sport. However, since ML models depend upon the amount of dataset, further studies should analyze the amount of data input needed make to a relevant predictive attempt which makes accurate predicting available.