检索结果-内蒙古大学图书馆

14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2018

作者： Cheng, Dandan Wang, Xingwei Zhang, Shuang Huang, Min College of Computer Science and Engineering Shenyang China College of Software Shenyang China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781538680971

information-Centric Networking (ICN), as a promising networking paradigm, is facing some challenges with its routing, such as content retrieval, efficiency, etc. In this paper, a Cat Swarm Optimization (CSO)based Quality of Service (QoS)Routing mechanism (CSOQR)is proposed to solve the routing problems in ICN. Firstly, a network model is built to imitate biological behaviors including link model and intelligent node model. Secondly, a user's Quality of Experience (QoE)is mapped to the corresponding QoS level, thus the user's QoS satisfaction is calculated. Then, the forwarding probability of an interface is calculated according to user's QoS satisfaction, and two forwarding interfaces are selected respectively based on Tracing Mode Face Choosing (TMFC)and Seeking Mode Face Choosing (SMFC). In this way, multiple content sources can be found through multiple paths to improve routing success rate, and we devise a migration strategy to balance node load. Finally, the proposed mechanism is simulated on both CERNET and CERNET2. Simulation results show that the proposed CSOQR has good performance in terms of routing success rate, routing hop count and node load. © 2018 IEEE.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

AMOGA: A Static-Dynamic Model Generation Strategy for Mobile Apps Testing

arXiv

引用

arXiv 2019年

作者： Salihu, Ibrahim-Anka Ibrahim, Rosziati Ahmed, Bestoun S. Zamli, Kamal Z. Usman, Asmau Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor86400 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor86400 Malaysia Department of Mathematics and Computer Science Karlstad University Karlstad Sweden Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang GambangPahang26300 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor86400 Malaysia

In the past few years, mobile devices have been increasingly replacing traditional computers as their capabilities such as CPU computation, memory, RAM size, and many more, are being enhanced almost to the level of conventional computers. These capabilities are being exploited by mobile apps developers to produce apps that offer more functionalities and optimized performance. To ensure acceptable quality and to meet their specifications (e.g., design), mobile apps need to be tested thoroughly. As the testing process is often tedious, test automation can be the key to alleviating such laborious activities. In the context of the Android-based mobile apps, researchers and practitioners have proposed many approaches to automate the testing process mainly on the creation of the test suite. Although useful, most existing approaches rely on reverse engineering a model of the application under test for test case creation. Often, such approaches exhibit a lack of comprehensiveness as the application model does not capture the dynamic behavior of the applications extensively due to the incompleteness of reverse engineering approaches. To address this issue, this paper proposes AMOGA, a strategy that uses a hybrid, static-dynamic approach for generating user interface model from mobile apps for model-based testing. AMOGA implements a novel crawling technique that uses the event list of UI element associated with each event to dynamically exercise the events ordering at the run-time to explore the applications’ behavior. An experimental evaluation was performed to assess the effectiveness of our strategy by measuring the code coverage and the fault detection capability through the use of mutation testing concept. Results of the experimental assessment showed that AMOGA represents an alternative approach for model-based testing of mobile apps by generating comprehensive models to improve the coverage of the applications. The strategy proved its effectiveness by achieving high co

关键词： Model checking

来源：评论

学校读者我要写书评

暂无评论

Poster: Are our students engaged in their studies?: Professional engagement vs. study engagement 40

Poster: Are our students engaged in their studies?: Professi...

引用

40th ACM/IEEE International Conference on software engineering, ICSE 2018

作者： Sturm, Arnon Lethbridge, Timothy C. Software and Information Systems Engineering Ben Gurion University of the Negev Israel Electrical Engineering and Computer Science University of Ottawa Canada

ISBN: (纸本)9781450356633

Engagement has been shown to contribute to students' success. We used an NSSE-like survey and interviews to examine engagement of students registered in software engineering and information system engineering at Ben Gurion University of the Negev (BGU). The survey showed BGU students had generally lower engagement in comparison to US students except for in collaborative learning. BGU students lean towards perceiving their studies as a means for professional success rather than for traditional academic success. We attribute the differences between the students and their US counterparts to differences in culture and the age of digital media that allows for multiple ways of learning beyond the university. © 2018 Authors.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

ResGANet: Residual group attention network for medical image classification and segmentation

引用

Medical image analysis 2022年 76卷 102313页

作者： Junlong Cheng Shengwei Tian Long Yu Chengrui Gao Xiaojing Kang Xiang Ma Weidong Wu Shijia Liu Hongchun Lu College of Information Science and Engineering Xinjiang University Urumqi 830000 China College of Computer Science Sichuan University Chengdu 610065 China. College of Software Engineering Xin Jiang University Urumqi 830000 China Key Laboratory of Software Engineering Technology Xinjiang University China. Electronic address: tianshengwei@***. College of Information Science and Engineering Xinjiang University Urumqi 830000 China. Xinjiang Key Laboratory of Dermatology Research People's Hospital of Xinjiang Uygur Autonomous Region China. The First Affiliated Hospital of Xinjiang Medical University Urumqi 830000 China. School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu 610031 Sichuan China.

In recent years, deep learning technology has shown superior performance in different fields of medical image analysis. Some deep learning architectures have been proposed and used for computational pathology classification, segmentation, and detection tasks. Due to their simple, modular structure, most downstream applications still use ResNet and its variants as the backbone network. This paper proposes a modular group attention block that can capture feature dependencies in medical images in two independent dimensions: channel and space. By stacking these group attention blocks in ResNet-style, we obtain a new ResNet variant called ResGANet. The stacked ResGANet architecture has 1.51-3.47 times fewer parameters than the original ResNet and can be directly used for downstream medical image segmentation tasks. Many experiments show that the proposed ResGANet is superior to state-of-the-art backbone models in medical image classification tasks. Applying it to different segmentation networks can improve the baseline model in medical image segmentation tasks without changing the network architecture. We hope that this work provides a promising method for enhancing the feature representation of convolutional neural networks (CNNs) in the future.

关键词： Deep learning Image classification Image segmentation Medical image analysis Residual group attention network

来源：评论

学校读者我要写书评

暂无评论

Performance assessment of mono and poly crystalline silicon photovoltaic arrays under Pannonian climate conditions

Performance assessment of mono and poly crystalline silicon ...

引用

Eurocon

作者： Matej Žnidarec Damir Šljivac Dario Došen Boris Dumniŋ Department of Power Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Software Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Power Electronic and Telecommunication Engineering Faculty of Technical Sciences Novi Sad Novi Sad Serbia

This paper conducted performance assessment of two photovoltaic arrays made of different silicon photovoltaic technologies installed at the test site of the Laboratory for Renewable Energy Sources at the Faculty of Electrical engineering, computer science and information Technology Osijek in Croatia. Each of the two photovoltaic arrays consists of 20 series-connected photovoltaic modules with total installed power of 5 kWp, which are then connected to the grid-tie inverter. Studied PV technologies are monocrystalline and polycrystalline silicon. Performance of the photovoltaic arrays is evaluated using 12 months of continuous measurements of the electrical output with assessment of the influence of European humid continental climate measured meteorological data on the performance, electricity production and efficiency of the investigated photovoltaic arrays. Monthly energy yield, performance ratio and capacity factor of each PV array is also calculated. Furthermore, empirical analysis of meteorological and electrical parameters is conducted and mathematical models of efficiency in relation to module temperature are determined.

关键词： Temperature measurement Meteorology Mathematical model Radiation effects Temperature dependence Silicon Photovoltaic systems

来源：评论

学校读者我要写书评

暂无评论

A Canvas Based Multi-Program Assessment System for ABET CAC and EAC Accreditations

A Canvas Based Multi-Program Assessment System for ABET CAC ...

引用

Frontiers in Education (FIE) Conference

作者： Wen-Li Wang Mei-Huei Tang Computer Science and Software Engineering Penn State Erie The Behrend College Erie PA USA Computer Information Science Gannon University Erie PA USA

ISBN: (数字)9781728117461

ISBN: (纸本)9781728117478

This is an Innovative Practice Full Paper. This paper introduces a multi-program assessment system for a department offering multiple majors to seek accreditation from ABET CAC and EAC. The Canvas LMS is our mandated tool for faculty to set up course rubrics, assign grades, and communicate with students. However, it falls short on solving several of our data issues, including data retrieval, data separation, data sharing, data integration, and data security. The Canvas LMS provides no data download for individual rubric criteria of an instrument, hindering analysis to a more granular level. There is also no information to identify a student's major, making data separation for different academic programs difficult. Faculty are reluctant to share student data on Canvas for integration, worrying about a violation to FERPA. Moreover, data sharing and data integration can increase the risk of data security. Our assessment system is built atop of Canvas and is a service oriented web application for faculty to assess student performance and generate instrument reports. The reports reveal only computed statistics for data sharing, integration and security purposes. The provided web services can interact with another system to distinguish student majors and consolidate instruments whose rubric criteria cover the same performance indicators (PIs). The system is a safe and sound methodology to conquer our data problems and can facilitate both formative and summative analyses for the program outcomes evaluation.

关键词： Instruments Accreditation Web services Data integration Data security Data collection Systems architecture

来源：评论

学校读者我要写书评

暂无评论

Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges

arXiv

引用

arXiv 2023年

作者： Jha, Debesh Sharma, Vanshali Banik, Debapriya Bhattacharya, Debayan Roy, Kaushiki Hicks, Steven A. Tomar, Nikhil Kumar Thambawita, Vajira Krenzer, Adrian Ji, Ge-Peng Poudel, Sahadev Batchkala, George Alam, Saruar Ahmed, Awadelrahman M.A. Trinh, Quoc-Huy Khan, Zeshan Nguyen, Tien-Phat Shrestha, Shruti Nathan, Sabari Gwak, Jeonghwan Jha, Ritika K. Zhang, Zheyuan Schlaefer, Alexander Bhattacharjee, Debotosh Bhuyan, M.K. Das, Pradip K. Fan, Deng-Ping Parasa, Sravanthi Ali, Sharib Riegler, Michael A. Halvorsen, Pål de Lange, Thomas Bagci, Ulas Machine & Hybrid Intelligence Lab Department of Radiology Northwestern University Chicago United States SimulaMet Oslo Norway Oslo Metropolitan University Oslo Norway Jadavpur University Kolkata India Indian Institute of Technology Guwahati India Institute of Medical Technology and Intelligent Systems Technische Universität Hamburg Germany University of Oslo Norway Julius-Maximilian University of Würzburg Germany Faculty of Information Technology University of Science VNU-HCM Viet Nam Department of IT Convergence Engineering Gachon University Seongnam13120 Korea Republic of School of Computing University of Leeds LeedsLS2 9JT United Kingdom College of Engineering Australian National University Canberra Australia Department of Engineering Science University of Oxford Oxford United Kingdom National University of Computer and Emerging Sciences Karachi Campus Pakistan Swedish Medical Center Seattle United States Kathmandu Nepal Couger Inc Tokyo Japan Department of Software Korea National University of Transportation Chungju Korea Republic of University of Bergen Bergen Norway Department of Medicine and Emergencies Mölndal Sahlgrenska University Hospital Region Västra Götaland Sweden Department of Molecular and Clinical Medicin Sahlgrenska Academy University of Gothenburg Sweden ETH Zurich Zurich Switzerland

Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is a need for an automated system that can flag missed polyps during the examination and improve patient care. Deep learning has emerged as a promising solution to this challenge as it can assist endoscopists in detecting and classifying overlooked polyps and abnormalities in real time, improving the accuracy of diagnosis and enhancing treatment. In addition to the algorithm's accuracy, transparency and interpretability are crucial to explaining the whys and hows of the algorithm's prediction. Further, conclusions based on incorrect decisions may be fatal, especially in medicine. Despite these pitfalls, most algorithms are developed in private data, closed source, or proprietary software, and methods lack reproducibility. Therefore, to promote the development of efficient and transparent methods, we have organized the "Medico automatic polyp segmentation (Medico 2020)" and "MedAI: Transparency in Medical Image Segmentation (MedAI 2021)" competitions. The Medico 2020 challenge received submissions from 17 teams, while the MedAI 2021 challenge also gathered submissions from another 17 distinct teams in the following year. We present a comprehensive summary and analyze each contribution, highlight the strength of the best-performing methods, and discuss the possibility of clinical translations of such methods into the clinic. Our analysis revealed that the participants improved dice coefficient metrics from 0.8607 in 2020 to 0.8993 in 2021 despite adding diverse and challenging frames (containing irregular, smaller, sessile, or flat polyps), which are frequently missed during a

关键词： computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

Classification decision based on a hybrid method of weighted knn and hyper-sphere SVM

引用

International Journal of Performability engineering 2018年第5期14卷 985-994页

作者： Chen, Peng Shi, Guoyou Liu, Shuang Zhang, Yuanqiang Špelič, Denis Navigation College Dalian Maritime University Dalian116026 China Department of Software Engineering Dalian Neusoft University of Information Dalian116030 China School of Computer Science and Engineering Dalian Minzu University Dalian116605 China Faculty of Electrical Engineering and Computer Science University of Maribor MariborSI-2000 Slovenia

Hyper-sphere Support Vector Machine (SVM) is very effective for solving multi-class classification problems. Considering data distribution is very important for convergence of solving support vectors, a weight factor is imported into the original hyper-sphere SVM. After computing data for each training class, this weight factor is decided by its center-distance ratio. In the training process, data with bigger weight is put into the data processing thread first and is then followed by smaller ones. To save computation cost, a parallel genetic algorithm based SMO multi-threading is adopted. For a test sample, its class decision is based on its position with each classification of hyper-sphere. If all class-specific hyper-spheres are independent of each other, a new test sample can be classified correctly. But, if some hyper-spheres have common spaces, that is, one hyper-sphere intersects with one or more hyper-spheres, it is hard to decide the class of the test sample. Based on detailed analysis of three decision rules for the intersection data classification, one decision rule that combines the kNN method is put forward in this paper. For other simple inclusion cases, the simple decision rule is defined. Through two real experimental results of navigation tracking and ship meeting situations classification, our new proposed algorithm has a higher classification accuracy and boasts a lower computation cost than other algorithms. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Impact Damage Identification for Composite Material Based on Transmissibility Function and OS-ELM Algorithm

引用

Journal of Quantum Computing 2019年第1期1卷 1-8页

作者： Yajie Sun Yanqing Yuan Qi Wang Sai Ji Lihua Wang Shaoen Wu Jie Chen Qin Zhang Jiangsu engineering Centre of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information and Control Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Science Ball State UniversityMuncieUSA

A method is proposed based on the transmissibility function and the OnlineSequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to theimpact damage of composite materials. First of all, the transmissibility functions of theundamaged signals and the damage signals at different points are calculated. Secondly,the difference between them is taken as the damage index. Finally, principal componentanalysis (PCA) is used to reduce the noise feature. And then, input to the online sequencelimit learning neural network classification to identify damage and confirm the damagelocation. Taking the amplitude of the transmissibility function instead of the accelerationresponse as the signal analysis for structural damage identification cannot be influencedby the excitation amplitude. The OS-ELM algorithm is based on the ELM (ExtremeLearning Machine) algorithm, in-creased training speed also increases the recognitionaccuracy. Experiment in the epoxy board shows that the method can effectively identifythe structural damage accurately.

关键词： Impact damage transmissibility function OS-ELM

来源：评论

学校读者我要写书评

暂无评论

A location-aware GIServices quality prediction model via collaborative filtering

引用

International Journal of Digital Earth 2018年第9期11卷 897-912页

作者： Qingxi Peng Lan You Na Dong State Key Lab of Software Engineering Wuhan UniversityWuhanPeople’s Republic of China Faculty of Computer Science and Information Engineering Hubei UniversityWuhanPeople’s Republic of China Institute of Space and Earth Information Science The Chinese University of Hong KongHong KongPeople’s Republic of China

The quality of GIServices(QoGIS)is an important consideration for services sharing and ***,QoGIS is a complex concept and difficult to be evaluated *** of the current studies have focused on static and non-scalable evaluation methods but have ignored location sensitivity subsequently resulting in the inaccurate QoGIS *** intensive geodata and computation,GIServices are more sensitive to the location factor than general *** paper proposes a location-aware GIServices quality prediction model via collaborative filtering(LAGCF).The model uses a mixed CF method based on time zone feature from the perspectives of both user and *** zone is taken as the location factor and mapped into the prediction process.A time zone-adjusted Pearson correlation coefficient algorithm was designed to measure the similarity between the GIServices and the target,helping to identify highly similar *** adopting a coefficient of confidence in the final generation phase,the value of the QoGIS most similar to the target services will play a dominant role in the comprehensive *** series of experiments on large-scale QoGIS data were implemented to verify the effectivity of *** results showed that LAGCF can improve the accuracy of QoGIS prediction significantly.

关键词： Location-aware QoGIS quality prediction GIServices collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：