{"title":"Malicious Android Application Detection Based on Composite Features","authors":"Jingxu Xiao, Kaiyong Xu, Jialiang Duan","doi":"10.1145/3331453.3361664","DOIUrl":"https://doi.org/10.1145/3331453.3361664","url":null,"abstract":"With the use of mobile phones, malicious applications are constantly developing, affecting the normal use of mobile phones by users. For the malicious application of Android platform, a detection model based on combined features is proposed. The model extracts the dynamic and static features and select the importance of them. Selecting Combination Features from important features. Taking the combined features as new features, and combing the single features to detect Android malicious applications. Experiments are carried out using different classification algorithm. which verifies the proposed Android malicious application detection model is feasible and superior, and the detection accuracy is up to 97.12%.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115483494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luhong Diao, Yang Liu, Dong Nan, Yong Qiao, Juan Peng
{"title":"Units and Layers' Effects on Deep Boltzman Machines","authors":"Luhong Diao, Yang Liu, Dong Nan, Yong Qiao, Juan Peng","doi":"10.1145/3331453.3361289","DOIUrl":"https://doi.org/10.1145/3331453.3361289","url":null,"abstract":"This paper analyzes the units' and layers' effects on deep Boltzman machines. It divides the DBM into two parts and reveals how the two parts affect the DBM's approximation capability. It indicates that the representation power of deep Boltzman machine is not always improved with more units and layers. When a deep Boltzman machine is best already, more units and layers will nearly always lead to worse performance.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"97 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126029402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ScholarSeq","authors":"Yu Liu, Zhenzhao Sun, Yizhou Yan, Jing Li","doi":"10.1145/3331453.3362039","DOIUrl":"https://doi.org/10.1145/3331453.3362039","url":null,"abstract":"H-sequence, as the time evolution of h-index, is a promising approach to evaluating a scholar's performance throughout his entire career. However, the lack of benchmark dataset that could be used to compare and evaluate various new and existing h-sequence methods has limited the development of h-sequence or other time series indicators. In order to solve this problem, we have crawled about 7,276,970 papers in computer science field. After that, we find the most cited papers t that could identify out 200 top scientists and 50 ordinary scientists. Finally, we construct a benchmark dataset called ScholarSeq which contains information of 150 particular scholars who are major in computer science field. The dataset includes 37,900 papers published by these authors and 3,263,813 citing papers. ScholarSeq provides citation counts in each individual year for each paper, which can be applied to various academic career impact assessments based on time sequence such as h-sequence. Furthermore, it is of great significance that we package the dataset in paper-time matrices so that informetricians can easily get access to and study various innovative sequences of impact measures. In order to illustrate how to use ScholarSeq, we apply the dataset to analyze 4 state-of-the-arts h-sequence methods. Moreover, we have shared source codes, entire dataset and many other files on our website at http://scholarseq.beyondcloud.cn/.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122415243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discovering Research Teams from Scientific Papers and Patents","authors":"H. Han, Xiaorui Zhai, Jingpeng Han, Yaxin Ran","doi":"10.1145/3331453.3362040","DOIUrl":"https://doi.org/10.1145/3331453.3362040","url":null,"abstract":"Most existing team discovery methods are based on collaboration networks using papers or patents data. They usually have low efficiency because they have to create the whole network containing all researchers. In addition, these methods can't immediately output research topics for each discovered team. A novel team discovery method is presented to solve these problems. The method extracts institutional names from papers and patents to build the institution base, and extracts authors and inventors to build the researcher base after name disambiguation. Then, the method exploits Author Topic model to mine distributions of topics and researchers in papers and patents and builds research topic base. The component analysis technique is used to discover teams under each research topic by analyzing its collaboration network. Experiments show the proposed method can identify teams without establishing a whole network by integrating papers and patent data. Meanwhile, the method can provide research topics for found teams.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122805222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Long Term Healthcare System for Elders by Using Internet of Things with Big Data","authors":"Ching-Lung Lin, H. Lin, Shu-Chi Lin, Yung-Te Liu","doi":"10.1145/3331453.3362042","DOIUrl":"https://doi.org/10.1145/3331453.3362042","url":null,"abstract":"This paper proposes an elder care system that develops a multi-solution for Taiwan's current Long-Term Care 2.0. The system is designed by using the Internet of Things, Big data, cloud database, application of various sensors, and the integration of the experiences of the Long-Term Care Centers. We find a way to create the maximum effectiveness with the least resources, so that elders in long-term care centers can keep their ability of daily living activities (ADLs) and instrumental activities of daily living (IADLs), and it alleviates internal pressures and costs inside country under the continuing aging society.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121695643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Scientometric Review of Research Evolution in Digital Forensics","authors":"Guihuang Jiang, Chenguang Li","doi":"10.1145/3331453.3362055","DOIUrl":"https://doi.org/10.1145/3331453.3362055","url":null,"abstract":"In this paper, we reviewed the scientific literature of digital forensics between 1990 to 2019. The visualized charts of keyword cloud, surging keywords and co-citation networks were generated by CiteSpace V. Based on the analysis, it was found that: (1) the research contents of digital forensics are focused on eight aspects. They are basic theory and methods, physical equipment and forensic methods, image forgery identification, file recovery and data extraction, smart phones and social network forensics, case-based forensics and crime forensics, automatic identification technology and tools, cloud computing and cloud forensics. (2) The research evolutional paths were followed by storage media, image forensics technologies, data recovery technologies, encryption and decryption technologies, human and social characteristics. (3) The breakthrough of image forgery identification technology accelerated the development of digital forensics; smart phone and social network forensics and automated forensics technologies bring important paradigm shift; in the future, automatic forensics and cloud forensics will be hot research directions.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130137051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Improved Algorithm for Solving Scheduling Problems by Combining Generative Adversarial Network with Evolutionary Algorithms","authors":"Menghui Chen, Ruiran Yu, Shengjian Xu, Yifei Luo, Zhihua Yu","doi":"10.1145/3331453.3361639","DOIUrl":"https://doi.org/10.1145/3331453.3361639","url":null,"abstract":"With1 the continuous application of evolutionary algorithms in various combinatorial optimization problems, the traditional evolutionary algorithms are prone to premature convergence and fall into local optimization solutions as the complexity of the problems increases. To solve this problem, this paper proposes a hybrid algorithm combining the Generative adversarial nets (GAN) and Genetic Algorithm (GA). The algorithm is based on Genetic Algorithm and introducted the GAN sample as another sample to the generated model. The algorithm expected more abundant sample information through GAN mining, got the advantage of sample training GAN through the GA. It makes GAN learn from the edge of sample information, which can generate more advantages of samples. The generated sample is injected into the evolution of the next generation, increasing the diversity of samples and increasing the opportunity to find the optimal solution. In this paper, the hybrid algorithm is used to solve the Permutation Flow Shop Problem to verify the algorithm's solution ability. Experimental results show that the hybrid algorithm can avoid premature local optimal solution compared with the traditional evolutionary algorithm.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134084589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Opinion Dynamics on Evolving Complex Networks with Explosive Suppression","authors":"Wenting Wang, Xingxing Zhou, Fuzhong Chen","doi":"10.1145/3331453.3362062","DOIUrl":"https://doi.org/10.1145/3331453.3362062","url":null,"abstract":"The interactions of opinions on the complex networks are significantly impacted by the structure of the networks. Previous studies of this kind mainly investigated the opinion dynamics on the fixed networks as a kind of synchronization. In this study, we focus on how the opinions evolving on the growing networks. We provide isolated nodes with different initial opinions at the beginning. The Achlioptas process is introduced to link the nodes eventually. The opinions of two nodes influence each other linearly if there is a link between the two nodes. We establish both random graph and scale-free networks in this paper. The finite-size scaling is discussed. We discover explosive transition of the speed for the opinions to achieve a consensus on some networks. Meanwhile, the stability of the networks to suppress the random damage is highly enhanced by the Achlioptas process to link all the nodes as a network. The encouraging results are obtained on different structures of networks.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133927045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Designing a Congestion Pricing System with the Help of the Intelligent Transportation Based on the Internets of Things","authors":"Peng Wang, Bingkun Lu, Ruiwen Liu, Cong-Shun Wang","doi":"10.1145/3331453.3360967","DOIUrl":"https://doi.org/10.1145/3331453.3360967","url":null,"abstract":"With the traffic congestion in Beijing further expanding, the traffic situation is suffering the same problem nationwide. Despite introducing multiple measures to reduce congestion, including limiting car purchases and raising parking fees, the problem has not eased. The introduction of the Intelligent Transportation systems can help to contain the expansion of traffic congestion. Intelligent Transportation systems provide traffic management authorities with the most up-to-date information about the traffic situation. This paper first clarifies the traffic congestion severity of the study area in Beijing, and then analyzes the congestion pricing models in China, Singapore, London and Stockholm respectively, and points out that China's congestion pricing is still in the demonstration stage. Then, from the perspective of technical analysis and charging patterns, this paper compares the operation methods of the four major types of toll collection systems used in the above regions. Based on the large area and population of Beijing and the numerous vehicles, the combination of The ETC-based Multi-Lane Free Flow System and Vehicle License Plate Recognition (VLPR)should be used. Then, this paper gives the general framework of the congestion pricing system, and clarifies its charging collection method, charging area, charging period and charging objective. Finally, considering the reliability, stability, anti-interference, compatibility and expansion capabilities of the system, this paper considers TS3203 / 10B system of the Swedish manufacturer Combitech AS to be the most suitable.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131219226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enabling Smart Collaboration with Smart University Services","authors":"Ouidad Akhrif, Y. Idrissi, N. Hmina","doi":"10.1145/3331453.3361311","DOIUrl":"https://doi.org/10.1145/3331453.3361311","url":null,"abstract":"Technological innovations have changed the educational model and the interactions between the learner and his academic environment to acquire and share knowledge, indeed, the emergence of Smart University (SU) concept enable smart learning process by encompassing a range of smart components, which involve the implementation of an adaptive educational model using informational smart technologies. The servitization of learning process is a very important issue that allows the university to be proactive, scalable and smart. Thanks to the specificity of the service-oriented concept; the smart university system based on service-oriented paradigm enables the university to satisfy students' needs and ensure effective and proactive learning methods, which boosted by intelligent layers, additional treatment and data-powered. The paper concludes with \"smart collaborative learning\", as a relevant concept that adopts smart interactions to promotes modern methods of collaboration between teams of smart learners.","PeriodicalId":162067,"journal":{"name":"Proceedings of the 3rd International Conference on Computer Science and Application Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115477376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}