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2020 International conference on Intelligent computing, Automation and Systems, ICICAS 2020

作者： Shang, Xuechun Zhou, Kang Chen, Xuan Liu, Jiangrong Yang, Yanzi Li, Guangbin Wuhan Polytechnic University School of Mathematics and Computer Science Wuhan China Polytechnic University School of Mathematics and Computer Science Wuhan China Qianjiang Jujin Rice Industry Co. Ltd. Enterprise-School Joint Innovation Center Qianjiang China

ISBN: (纸本)9781728191461

In order to enable companies to directly infer the quality standard of the requisite frozen dumpling ingredients based on the quality of the frozen dumplings, this paper proposes a data-driven model-based analysis method. The method firstly studies the core indicators and main components of glutinous rice flour through data analysis, and secondly uses the core indicators and main components of glutinous rice flour to predict the quality indicators of instant frozen dumplings. Then the upper and lower bounds of the range of variation of the core indicators of glutinous rice flour are used as decision variables, and the quality requirements of frozen soup dumplings and glutinous rice flour itself are used as constraints to find the region of the range of variation of the indicators that are dedicated to glutinous rice flour as widely as possible. Finally, we adjusted the model, and the optimal range of glutinous rice flour indexes included almost all raw materials with high sensory score in the sample data, and solved the problem of setting quality standards for special glutinous rice flour. © 2020 IEEE.

关键词： Multiobjective optimization

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Detect cooperative Hyping Among VIP Users and Spammers in Sina Weibo 13th

Detect Cooperative Hyping Among VIP Users and Spammers in Si...

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13th CCF conference on computer supported cooperative work and social computing (ChineseCSCW)

作者： Guo, Ziyu Liu, Shijun Wang, Yafang Wang, Liqiang Pan, Li Wu, Lei Shandong Univ Jinan Peoples R China

ISBN: (纸本)9789811330445;9789811330438

Sina Weibo services provide platforms for massive information dissemination and sharing between hundreds of millions of users. The hot topics in this platform attract substantial interest and have enormous potential for business and society. As a result, it has attracted spam teams with malicious intent. In this paper, we study how to detect such opinion spam teams and how do they guide public opinion. Our model is unsupervised and adopts a Bayesian framework to distinguish between spammers and non-spammers. Experiments conducted on a dataset of a Sina Weibo hot topic with a 0.81 F1-measure demonstrate the proposed method's effectiveness. Through further analysis, we found the phenomenon and some methods of the cooperative hyping among VIP users and spammers (in Sect. 3.2). VIP users are small in number but have a great influence due to they have a large number of followers, so VIP users are responsible for hyping topics so that it attract more attention, then a lot of spammers guide public opinion through a lot of manual postings.

关键词： Hot topics Spammer detection Guide public opinion Bayesian modeling cooperative hyping

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A survey of emotion analysis in text based on deep learning 8

A survey of emotion analysis in text based on deep learning

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8th IEEE International conference on Smart City and Informatization, iSCI 2020

作者： Cao, Lihong Peng, Sancheng Yin, Pengfei Zhou, Yongmei Yang, Aimin Li, Xinguang Laboratory of Lang. Eng. and Comp. Guangdong University of Foreign Studies Guangzhou China School of Computer Central South University Changsha China School of Info. Sci. and Tech. Guangdong University of Foreign Studies Guangzhou China College of Computer Guangdong University of Technology Guangzhou China

ISBN: (纸本)9781665403948

With the rapid development of mobile Internet, and the popularization of e-commerce and social networks, people have changed from the simple users of network information to the main publishers of network information. Thus, a large number of various network data have been generated, and a large part of these data contains negative emotions. Mining these data can make us better understand the views and positions of netizens, and help to grasp the key information of network public opinion. In this paper, we provide an introduction for the background knowledge of emotion analysis, including different definitions and classification methods of emotion. Then, we summarize the related models of deep learning, as well as the main emotion analysis methods in text based on deep learning, and make a detailed introduction and comparison on these methods. Finally, we enumerate the challenges of emotion analysis in text, and the future research trend for emotion analysis. © 2020 IEEE.

关键词： Deep learning

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Empirical Research on Cluster Analysis of Spectral Information of Hyperspectral Remote Sensing Data 13

Empirical Research on Cluster Analysis of Spectral Informati...

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2020 IEEE Congress on Cybermatics: 13th IEEE International conferences on Internet of Things, iThings 2020, 16th IEEE International conference on Green computing and Communications, GreenCom 2020, 13th IEEE International conference on Cyber, Physical and social computing, CPSCom 2020 and 6th IEEE International conference on Smart Data, SmartData 2020

作者： Dong, Yueyu Dai, Fei Xu, Xiaolong Qin, Mingming Qiang, Zhenping School of Big Data and Intellegent Engineering Southwest Forestry University Kunming China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9781728176475

The most notable features of hyperspectral remote sensing data are high spectral resolution and high dimensionality. Analyzing the spectral information of the data with clustering requires proper spectral measurements. And clustering results validating methods satisfy high-dimensional data are required. In this paper, three clustering algorithms of K-means, K-means++, and Chameleon were used in the empirical research, based on the famous data set of IndianPine. In the experiments, four spectral measures of SBD, SID, SSD and SPM were used as spectral similarity measures, and S-Dbw was chosen as clustering validating method. As S-Dbw is a relative validating index, the algorithms with different parameter combinations had been experimented many times, verified the effectiveness of the solution composed with selected clustering methods, spectral measures, and clustering validating method. Experimental results showed that hyperspectral information enhanced the ability to distinguish ground objects;Chameleon's performance was best, and S-Dbw could effectively analyze hyperspectral data;the performance of the spectral measurements showed a certain correlation with the clustering method. © 2020 IEEE.

关键词： Cluster analysis

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Collecting data for service design in public offices: A case study 9

Collecting data for service design in public offices: A case...

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9th Latin American conference on Human computer Interaction (CLIHC)

作者： Magallanes, Yazmin Alfredo Sanchez, J. NEUX Lab User Res Area Puebla Mexico Lab Nacl Informat Avanzada Xalapa Veracruz Mexico

ISBN: (纸本)9781450376792

Service design has to do with making services meet the user's needs. Service design can be used to improve an existing service or to create a new one. We conducted a study aimed to further the concept of service design through an investigation of the situation of teachers and workers at one of the State Secretariats of Education in Mexico regarding the management of administrative procedures. The complexity of a procedure depends on many factors, such as time to obtain a resolution, trips to the management offices, varied requirements, physical documentation, and process clarity. Commonly, governments are asked to provide these procedures more efficiently. In order to make progress towards our goal, we applied 6500 surveys to teachers of elementary education levels of the Secretariat. We detected difficulties related to the lack of communication bridges, the lack of tools to facilitate the process of starting a procedure, the high costs for the management of procedures, and the performance of the Secretariat in this field.

关键词： Service design computing in government computer supported cooperative work

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An optimization method for resource allocation in fog computing 13

An optimization method for resource allocation in fog comput...

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作者： Yin, Chao Li, Tongfang Qu, Xiaoping Yuan, Sihao School of Information Science and Technology Jiujiang University Jiujiang332005 China

ISBN: (纸本)9781728176475

With the rapid development of the network, a huge amount of data will be generated. Existing technologies usually use cloud computing to process data. However, when all the data of users need to be transferred to the cloud for processing, it will cause long transmission delay due to the distance between users and cloud computing data center. Fog computing connects network edge devices downward and cloud data center upward, which greatly shortens the transmission distance of user data. Fog computing is an effective way to solve the problems of high delay, bandwidth bottleneck and security. In this paper, we have developed an optimization method, which establish an optimization problem with minimum average task delay as optimization objective and various system resources. By variable substitution, the nonconvex optimization problem is equivalent to a new optimization problem whose objective is nonconvex and all constraints are convex. In order to solve the global optimal solution of the nonconvex optimization problem, a new lower bound is designed by relaxing the objective to a lower bound quadratic function. We have evaluated our system by simulation test. The results verify the effectiveness of the optimization method. © 2020 IEEE.

关键词： Resource allocation

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Pomelo, a collaborative education technology interaction robot 19

Pomelo, a collaborative education technology interaction rob...

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proceedings of the 14th acm/IEEE International conference on Human-Robot Interaction

作者： Liora Nasi Yoel Nasi Can Aydin Rana Taki Batuhan Byaraktar Ece Tabag Sedat Yalcin C.S. IdeaLab Hisar School Istanbul Turkey C.S. Idea Lab Hisar School Istanbul Turkey

ISBN: (纸本)9781538685556

We have designed "Pomelo", an interactive robot that teaches children basic algorithmic skills and enhances classroom collaboration through games. Pomelo looks like a friendly dog with a screen displaying its eyes and cooperates with the students through vision and speech. Pomelo becomes a part of the class instead of merely being a second teacher by interacting with children in the same way children interact with each other, like "Robovie" [1]. Ultimately, Pomelo will encourage kids to use technology as an interactive learning tool instead of a form of addictive entertainment while creating a more cooperative and social classroom environment.

关键词： speech recognition and synthesis education computer-supported cooperative work computer assisted instruction visual programming collaborative learning

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Spatial Task Allocation Based on User Trajectory Prediction 13th

Spatial Task Allocation Based on User Trajectory Prediction

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13th CCF conference on computer supported cooperative work and social computing (ChineseCSCW)

作者： Jiang, Yun He, Wei Cui, Lizhen Yang, Qian Peng, Zhaohui Shandong Univ Sch Software Jinan Peoples R China Shandong Univ Sch Comp Sci & Technol Jinan Peoples R China

ISBN: (纸本)9789811330445;9789811330438

With the rapid development of wireless communication technology and mobile intelligent terminals, location based service has been widely used for its unique features such as mobility, practicality and portability, including mobile crowdsourcing. In mobile computing environment, mobile crowdsourcing task allocation has become a focused research issue. In mobile crowdsourcing, application scenarios are in dynamic state, and workers are also willing to accept tasks. In response to these challenges, this paper proposes a mobile crowdsourcing task allocation strategy based on user trajectory prediction. First, the location points in user historical trajectory data are clustered into regions using k-means algorithm. Then the user's trajectory is analyzed and excavated to get the user's mobile pattern. On this basis, we extract mobile rules and calculate the confidence. According to the mobile rules, we predict the region that the user will reach, and finally assign the tasks in the region to him. The prediction based task allocation method proposed in this paper avoids the additional cost that platform need to pay to users, recommends user the task that more suitable for him, and improves the success rate of task allocation. Finally, based on the analysis and simulation experiments of real datasets, the proposed method can effectively predict the location region of users, and at the same time, it can achieve better results than other methods in the situation of task allocation and completion.

关键词： Mobile computing environment Mobile crowdsourcing Trajectory prediction Task allocation

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Applications of social identity theory to research and design in social computing

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proceedings of the acm on Human-computer Interaction 2018年第CSCW期2卷 1-34页

作者： Seering, Joseph Ng, Felicia Yao, Zheng Kaufman, Geoff Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States

Research in computer-supported cooperative work has historically focused on behaviors of individuals at scale, using frames of interpersonal interaction such as Goffman’s theories of self-presentation. These frames prioritize research detailing the characteristics, personal identities, and behaviors of large numbers of interacting individuals, while the social identity concepts that lead to intra- and inter-group dynamics have received far less attention. We argue that the emergent properties of self-categorization and social identity, which are particularly fluid and complex in online spaces, provide a complementary perspective with which to re-examine traditional topics in social computing. We discuss the applicability of the social Identity Perspective to both established and new research domains in CSCW, proposing alternative perspectives on self-presentation, social support, collaboration, misbehavior, and leadership. We propose a set of methodological considerations derived from this body of theories and accompanying empirical work. We close by considering how broad concepts and lessons from social identity provide a valuable lens for inspiring future work in CSCW. © 2018 Association for computing Machinery.

关键词： Computation theory

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Identity and Belonging for Graduate Apprenticeships in computing The experience of first cohort degree apprentices in Scotland 19

Identity and Belonging for Graduate Apprenticeships in Compu...

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acm conference on Innovation and Technology in computer Science Education (ITiCSE)

作者： Taylor-Smith, Ella Smith, Sally Smith, Colin F. Edinburgh Napier Univ Sch Comp Edinburgh Midlothian Scotland

ISBN: (纸本)9781450363013

In September 2017, our university's first graduate apprentices began degrees in Software Development, Cybersecurity, and Information Technology Management for Business. This study explores how apprentices experience their association with the university and identities as students, but also employees. In Scotland, Graduate Apprenticeships (GAs) are undergraduate degrees in which the students are in full-time employment, while completing degree modules over four years, as for a traditional full-time degree. The curriculum follows a skills framework designed by employers so that graduates have the professional and technical attributes required by the industry. The degrees parallel Degree Apprenticeships in England, though there are national differences in implementation. Themes of identity and belonging are central to current investigations of the experience of STEM students, especially computing students, as fewer students choose STEM courses, and many transfer out of their subjects or do not complete their degrees. The research hypothesis is that the apprentices' employment will provide a strong IT professional identity supports their progress at university. Semi-structured interviews with apprentices in the first computing cohorts explored their situated perspectives. Responses were identified which concerned the apprentices' identity as students or employees, including themes around belonging. Thematic analysis of these responses revealed that apprentices defined themselves in opposition to traditional student identities and did draw strength from their identity as employees. They experienced belonging specifically within their GA cohort the first of its kind in the university. A better understanding of identity and belonging can be used by universities to address the challenges of retention.

关键词： Graduate apprenticeship degree apprenticeship work-based learning identity belonging

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