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The cuckoo search and integer linear programming based approach to time-aware test case prioritization considering execution environment 14th

The cuckoo search and integer linear programming based appro...

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14th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2018

作者： Wong, Yu Zeng, Hongwei Miao, Huaikou Gao, Honghao Yang, Xiaoxian School of Computer Engineering and Science Shanghai University Shanghai200444 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai200444 China Computing Center Shanghai University Shanghai200444 China School of Computer and Information Engineering Shanghai Polytechnic University Shanghai China

ISBN: (纸本)9783030129804

Regression testing plays an important role in software development process. The more mature software system development is, the greater the proportion of regression testing during software life cycle takes. To this point, test case prioritization techniques are proposed to detect more faults as early as possible and improve the effectiveness of regression testing. However, it is often performed in a time constrained execution environment. This paper introduces a new method of time-aware test case prioritization. First of all, it takes advantage of the cuckoo search algorithm to reorder test suite. Then, integer linear programming model is employed to test selection in light of time budget. At last, a novel fitness function is designed focusing on code coverage that from method-call information perspective. Experimental results show that our method improves the effectiveness of fault detection compared with traditional fault detection techniques especially time is constrained. © 2019, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Fault detection

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Research on Green Energy Saving ECO Intelligent System engineering Cycle

Research on Green Energy Saving ECO Intelligent System Engin...

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作者： Jue-Jia Chen Shinn-Dar Wu Dong-Yan Chen Jie Li Ta-Wei Huang Software Engineering Department of Computer Science Neusoft Institute Guangdong School of Chemistry and Materials Engineering Huizhou University USA Saint Paul's College & DePaul University Royal Global Business Center Department of information management and Engineering Neusoft Institute Guangdong

With the improvement of living standards, the national coverage of heaters is also higher. From the original only the northern part of the installation of heating devices, to the south of the central area has also installed heaters, and even some people in the southern area installed heaters. With the increase in sales volume and fierce competition, companies need to reform and innovate products to meet the higher requirements of customers for energy-saving effects, comfort and safety. The design of the heater involves theories of structure, integrated circuit, program algorithm, aerodynamics, heat transfer and so on. Due to the technical level and cost constraints of enterprises, few companies can produce safe, energy-saving, moisturizing and comfortable heaters suitable for the public. In this study, the green energy-saving circulating heater of ECO intelligent system adopts the incremental ECO processing algorithm, with the single-chip STC89 C52 as the main control chip system, combined with the peripheral STC89 C52 temperature data acquisition, HIH-3010 humidity data collector, A/D Conversion module, keyboard settings, LCD1602 liquid crystal display and other circuit modules. This design realizes the temperature value that the heater provides the user with the optimum indoor temperature value and sets the heating according to the user's needs. When the set temperature value is reached or the temperature is high, the controller will control the heating element to reduce power or automatically power off to achieve safe power saving effect.

关键词： .Green energy saving ECO intelligent system engineering

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The study of searchable encryption mechanism

The study of searchable encryption mechanism

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International Conference on Intelligent Computing, Communication and Devices, ICCD 2017

作者： Cui, Ranran Zhang, Yongsheng Li, Nengneng School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250358 China

ISBN: (纸本)9789811089435

With the development of information technology, more and more data information uploaded to the cloud server, cloud computing encryption storage technology for data security has become particularly important. This paper mainly studies and analyzes the searchable encryption technology in cloud computing. Firstly, the research status of domestic and foreign research is analyzed. Secondly, the classification of searchable encryption technology is introduced from different aspects, and the classification model of searchable encryption technology A detailed elaboration. Finally, some problems encountered in searchable confidentiality technology and the prospect of this technology are introduced. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Cryptography

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Research on education resource recommendation algorithm based on implicit feedback and pairwise 10

Research on education resource recommendation algorithm base...

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10th International Conference on information Technology in Medicine and Education, ITME 2019

作者： Huang, Xiaoxiang Zhang, Yongsheng Zheng, Zhihua Zhang, Jie Duan, Jiaxi School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan250358 China

ISBN: (纸本)9781728139173

In view of the problem of how to improve the accuracy of education resources recommendation in Internet era, a recommendation algorithm based on implicit feedback and pairwise education resources are proposed. Firstly, the feature extraction of learner-education resource is carried out, and the implicit features of learner-education resource are extracted by implicit semantic model, and the prediction results of factor decomposition are used as input to sorting learning algorithm. Converting sorting problems to classification problems uses the theory of ordering learning. Based on the experiment comparison with the traditional recommendation algorithm, it is compared with the comparison algorithm, which has better effect on the recommendation of educational resources. The algorithm increases by nearly 30% on metrics MAP, NDGG. © 2019 IEEE.

关键词： Learning algorithms

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Research and implementation of teaching system for higher vocational specialty courses based on hybrid teaching mode 10

Research and implementation of teaching system for higher vo...

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10th International Conference on information Technology in Medicine and Education, ITME 2019

作者： Zhang, Penglong Zhang, Yongsheng Fan, Shaojun Huang, Xiaoxiang Zhang, Jie School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan250358 China

ISBN: (纸本)9781728139173

In recent years, with the diversified development of education and training in China and the continuous 'Internet +', enterprises and society have put forward higher requirements for the ability of skilled talents. However, in the vocational specialty colleges that transport a large number of skilled talents, it is increasingly difficult to meet the needs of students' learning and development. At the same time, it is difficult for students to select appropriate content for independent learning in the vast information on the Internet. Hybrid teaching is a teaching mode that combines the advantages of both traditional teaching and networked teaching. The specialty courses teaching system is based on hybrid teaching mode. It uses Java Web technology as the basis for adopting B/S development mode, MySQL database and eclipse, Navicat as Development tools. The research and implementation of the hybrid teaching system is conducive to the school to help bridging the communication between the students and the enterprise, so that students can learn more directly and provide high-skilled talents with basic professional knowledge and skilled skills. On the other hand, through practice, it also helps to promote the development of hybrid teaching reform, thus solving the complexity and particularity of the informationization process in higher vocational colleges. © 2019 IEEE.

关键词： Teaching

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A hybrid filtering-based network document recommendation system in cloud storage

A hybrid filtering-based network document recommendation sys...

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International Journal of Computational science and engineering

作者： Wu, Yuezhong Liu, Qin Li, Changyun Wang, Guojun School of Information Science and Engineering Central South University Changsha410083 China School of Computer Science Hunan University of Technology Zhuzhou412007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory School of Computer Science Hunan University of Technology Zhuzhou412007 China School of Computer Science and Educational Software Guangzhou University Guangzhou510006 China

Since the key requirement of users is to efficiently obtain personalised services from mass network document resources, a hybrid filtering-based network document recommendation system is designed with the method of incorporating the content-based recommendation and collaborative filtering recommendation based on the powerful and extensible storage and computing power in cloud storage. The proposed system realises the main service module on Hadoop and Mahout platforms, and processes the documents containing the information of user interests by applying AHP-based attribute weighted fusion method. Based on the network interaction, the proposed system not only has advantages on the extensible storage space and high recommendation precision but also has an essential role in realising network resources sharing and personalised recommendation. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Storage as a service (STaaS) Collaborative filtering information retrieval systems Recommender systems Cloud storages Collaborative filtering recommendations Content based recommendation Document recommendation Network interaction Personalised recommendations Recommendation precision User interest model

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Smart Security Framework for Educational Institutions Using Internet of Things(IoT)

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computers, Materials & Continua 2019年第7期61卷 81-101页

作者： Afzal Badshah Anwar Ghani Muhammad Ahsan Qureshi Shahaboddin Shamshirband Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Faculty of Computing and Information Technology University of JeddahKhulais21959Kingdom of Saudi Arabia Department for Management of Science and Technology Development Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam

Educational institutions are soft targets for the terrorist with massive and defenseless *** the recent past,numbers of such attacks have been executed around the *** research,in order to provide a secure environment to the educational institutions is a challenging *** effort is motivated by recent assaults,made at Army Public School Peshawar,following another attack at Charsada University,Khyber Pukhtun Khwa,Pakistan and also the Santa Fe High School Texas,USA *** study uses the basic technologies of edge computing,cloud computing and IoT to design a smart emergency alarm system *** is engaged in developing this world smarter,can contribute significantly to design the Smart Security Framework(SSF)for educational *** the emergency situation,all the command and control centres must be informed within seconds to halt or minimize the *** this article,the SSF is *** framework works on three *** first layer is the sensors and smart devices *** these sensors and smart devices are connected to the Emergency Control Room(ECR),which is the second layer of the proposed *** second layer uses edge computing technologies to process massive data and information *** third layer uses cloud computing techniques to transmit and process data and information to different command and control *** proposed system was tested on Cisco Packet Tracer *** result shows that this approach can play an efficient role in security alert,not only in the educational institutions but also in other organizations too.

关键词： Internet of things smart security framework massacres terrorism smart emergency alert

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RSI-Net: Two-Stream Deep Neural Network for Remote Sensing Images-based Semantic Segmentation

arXiv

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arXiv 2021年

作者： He, Shuang Lu, Xia Gu, Jason Tang, Haitong Yu, Qin Liu, Kaiyue Ding, Haozhou Chang, Chunqi Wang, Nizhuan Jiangsu Key Laboratory of Marine Bioresources and Environment Jiangsu Key Laboratory of Marine Biotechnology Co-Innovation Center of Jiangsu Marine Bio-Industry Technology Jiangsu Ocean University Lianyungang222005 China School of Geomatics and Marine Information Jiangsu Ocean University Lianyungang222005 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada School of Computer Engineering Jiangsu Ocean University Lianyungang222005 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing211800 China School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen518060 China Peng Cheng Laboratory Shenzhen518055 China School of Biomedical Engineering ShanghaiTech University Shanghai201210 China

For semantic segmentation of remote sensing images (RSI), trade-off between representation power and location accuracy is quite important. How to get the trade-off effectively is an open question, where current approaches of utilizing very deep models result in complex models with large memory consumption. In contrast to previous work that utilizes dilated convolutions or deep models, we propose a novel two-stream deep neural network for semantic segmentation of RSI (RSI-Net) to obtain improved performance through modeling and propagating spatial contextual structure effectively and a decoding scheme with image-level and graph-level combination. The first component explicitly models correlations between adjacent land covers and conduct flexible convolution on arbitrarily irregular image regions by using graph convolutional network, while densely connected atrous convolution network (DenseAtrousCNet) with multi-scale atrous convolution can expand the receptive fields and obtain image global information. Extensive experiments are implemented on the Vaihingen, Potsdam and Gaofen RSI datasets, where the comparison results demonstrate the superior performance of RSI-Net in terms of overall accuracy (91.83%, 93.31% and 93.67% on three datasets, respectively), F1 score (90.3%, 91.49% and 89.35% on three datasets, respectively) and kappa coefficient (89.46%, 90.46% and 90.37% on three datasets, respectively) when compared with six state-of-the-art RSI semantic segmentation methods. © 2021, CC BY-NC-ND.

关键词： Semantic Segmentation

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PGD-UNet: A Position-Guided Deformable Network for Simultaneous Segmentation of Organs and Tumors

PGD-UNet: A Position-Guided Deformable Network for Simultane...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ziqiang Li Hong Pan Yaping Zhu A. K. Qin School of Automation Southeast University Nanjing China Department of Computer Science and Software Engineering Swinburne University of Technology John St Hawthorn VIC Australia School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Precise segmentation of organs and tumors plays a crucial role in clinical applications. It is a challenging task due to the irregular shapes and various sizes of organs and tumors as well as the significant class imbalance between the anatomy of interest (AOI) and the background region. In addition, in most situation tumors and normal organs often overlap in medical images, but current approaches fail to delineate both tumors and organs accurately. To tackle such challenges, we propose a position-guided deformable UNet, namely PGD-UNet, which exploits the spatial deformation capabilities of deformable convolution to deal with the geometric transformation of both organs and tumors. Position information is explicitly encoded into the network to enhance the capabilities of deformation. Meanwhile, we introduce a new pooling module to preserve position information lost in conventional max-pooling operation. Besides, due to unclear boundaries between different structures as well as the subjectivity of annotations, labels are not necessarily accurate for medical image segmentation tasks. It may cause the overfitting of the trained network due to label noise. To address this issue, we formulate a novel loss function to suppress the influence of potential label noise on the training process. Our method was evaluated on two challenging segmentation tasks and achieved very promising segmentation accuracy in both tasks.

关键词： Convolution Tumors Image segmentation Feature extraction Task analysis Medical diagnostic imaging

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A survey on VV&A of large-scale simulations

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International Journal of Crowd science 2019年第1期3卷 63-86页

作者： Wang, Yanan Li, Jianqiang Hongbo, Sun Li, Yuan Akhtar, Faheem Imran, Azhar Beijing University of Technology Beijing China Yantai University Yantai China Faculty of Information Technology Beijing University of Technology Beijing China and Department of Computer Science Sukkur IBA University Sukkur Pakistan School of Software Engineering Beijing University of Technology Beijing China

Purpose: Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations. Design/methodology/approach: After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations). Findings: The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations). Originality/value: This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations). © 2019, Yanan Wang, Jianqiang Li, Sun Hongbo, Yuan Li, Faheem Akhtar and Azhar Imran.

关键词： software engineering

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