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Studies in Big Data 2021年 73卷 v-vii页

作者： Chakraborty, Chinmay Banerjee, Amit Kolekar, Maheshkumar H. Garg, Lalit Chakraborty, Basabi Department of Electronics and Communication Engineering Birla Institute of Technology Ranchi Mesra India Department of Electrical Engineering Indian Institute of Technology Patna Patna India Faculty of Software and Information Science Iwate Prefectural University Takizawa Japan Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta Msida Malta

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The use of public-private partnership in the machine-building industry

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AIP Conference Proceedings 2022年第1期2467卷

作者： Oksana Bondarskaya Tatyana Bondarskaya Sergey Pichugin Anna Drozdova Elena Avksentieva Sergey Yekimov 1Tambov State Technical University Tambov Russian 2S. P. Korolev Rocket and Space Corporation Energia Moscow Russia 3Faculty of Business Informatics and Integrated Systems Management Department of Industrial Economics and Management National Research Nuclear University MEPhI Moscow Russia 4Faculty of Software Engineering and Computer Systems ITMO University St. Peterburg Russia 5Publishing House “Education and Science” Prague The Czech Republic

The process of reengineering business processes, in our opinion, is an iterative procedure in the process of enterprise management. Each subsequent business process in the business process chain is a logical continuation of the previous one. The reengineering procedure is characterized by the presence of some feedback about the impact of each individual business process on the overall set of business processes. During the implementation of reengineering, traditional business approaches may undergo revision. Often, many business rules need to be improved and are outdated. The use of public-private partnerships, in our opinion, can be considered as elements of reengineering, since partnerships with the state can open up new business development prospects for an enterprise, and many business processes used at this enterprise can be rethought and updated. The production of high-quality and high-performance agricultural machinery can be of great importance for solving the problem of ensuring food security of the state. The use of various forms of public-private partnership allows us to speed up the solution of this problem. The implementation of economic modernization requires the full use of the economic potential of the state. This can be achieved only if public-private partnerships are effectively implemented, since they allow combining the resources of the state and private business to achieve common goals.

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Optimization of Neural Network Parameters Based on a Genetic Algorithm for Prediction of Time Series

Optimization of Neural Network Parameters Based on a Genetic...

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International Multi-Conference on Industrial engineering and Modern Technologies (FarEastCon)

作者： V.S. Tormozov A.L. Zolkin K.A. Vasilenko Senior lecturer of the Software engineering for computers and computer-based systems sub-faculty Pacific National University Khabarovsk Tikhookeanskaya St. 136 Ph.D. in Engineering Science Povolzhskiy State University of Telecommunications and Informatics Samara Highest category lecturer Service and design college of the Vladivostok State University of Economics and Service Service and design college of the Vladivostok State University of Economics and Service Vladivostok

ISBN: (数字)9781728169514

ISBN: (纸本)9781728169521

The article proposes a method that allows to solve the complex combinatorial problem of structural optimization of an artificial neural network with a large dimension of the space of optimization parameters using the stochastic mutation function with a constant coefficient of variation. A study on assessment of applicability of this approach to solve the problem is given. This method is proposed to be used for the forecasting of time series values.

关键词： Genetic algorithms Sociology Neurons Biological cells Artificial neural networks Time series analysis Optimization

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Effect of number of versions on receiving high citations

TechRxiv

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TechRxiv 2020年

作者： Ale Ebrahim, Nader Salehi, Hadi Mohammadjafari, Marjan Embi, Mohamed Amin Bakhtiyari, Kaveh Danaee, Mahmoud Shakiba, Masoud Shahbazi-Moghadam, Masoomeh Zavvari, Azam Department of Industrial Engineering Faculty of Engineering Kerman Branch Islamic Azad University Kerman Iran Faculty of Literature and Humanities Najafabad Branch Islamic Azad University Isfahan Najafabad Iran Bangi 43600 Malaysia Department of Computer & Cognitive Science Facultyof Engineering University of Duisburg-Essen Duisburg Germany Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia University of Malaya Malaysia Faculty of Agriculture Roudehen Branch Islamic Azad University Roudehen Iran Center for Software Technology and Management Faculty of Information Science and Technology Universiti Kebangsaan Malaysia UKM Bangi Selangor 43600 Malaysia Perdana School of Science Technology and Innovation Policy Universiti Teknologi Malaysia Malaysia

Nowadays, the h-index is an index that attempts to measure both the productivity and impact of the published work of a scientist or scholar. The index is based upon the set of the scientist's most cited papers and the number of citations that they have received in other publications. Besides, the most commonly used measure of journal quality is Impact Factor. This is a number which attempts to measure the impact of a journal in terms of the average number of citations to recent articles published in the journal. So, receiving more citation is very important for authors and journals to get high h-index and impact factor. In this paper, we tried to analyses the effect of the number of available version from the web on receive more citations. We analyzed 10162 papers which are published in Scopus database in year 2010. Then we developed a software to collect the number of citations and versions of each paper from Google Scholar automatically. The results show that … © 2020, CC BY.

关键词： Indexing (of information)

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IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive Computing (Plenary Panel Report-II)

IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive...

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IEEE International Conference on Cognitive Informatics

作者： Witold Kinsner Haibin Zhu George Baciu Guiming Luo Fernando Rubio Jie Sui Runhe Huang Hironori Hiraishi Jun Peng Liang Chen FI2CICC Dept of ECE Univ. of Manitoba Winnipeg Canada FI2CICC Nipissing University ON Canada FI2CICC Dept. of Computing Hong Kong Polytechnic University Hong Kong FI2CICC Software Institute Tsinghua University Beijing China FI2CICC Dept. of Computer Systems &#x0026 Computation Complutense Univ. of Madrid Spain FI2CICC Aberdeen University Aberdeen UK FI2CICC Faculty of Computer and Information Sciences Hosei University Japan Faculty of Engineering Ashikaga University Tochigi Japan FI2CICC School of AI Chongqing Univ. of Science and Technology Chongqing China Dept. of Computer Science Univ. of Northern British Columbia BC Canada

ISBN: (纸本)9781665421201

Cognitive Computing (CC) is a contemporary field of fundamental intelligence theories and general AI technologies triggered by the transdisciplinary development in intelligence, computer, brain, knowledge, cognitive, robotic, and cybernetic sciences for engineering implementations. This paper presents a summary of the plenary panel (Part II) on the theoretical foundations of CI/CC and recent breakthroughs in AI engineering reported in the 20th IEEE International ICCI*CC Conference (ICCI*CC'21). The latest advances in CI and CC towards general AI are presented by twenty-two distinguished panelists. Strategic AI engineering applications in CI, CC, and cognitive systems are elaborated for abstract intelligence, cognitive robots, autonomous systems, intelligent vehicles, and safety-and-mission-critical systems.

关键词： Knowledge engineering Intelligent vehicles Autonomous systems Conferences Cognitive informatics Cognitive robotics Cognitive systems

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Prioritized process test: An alternative to current process testing strategies

arXiv

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arXiv 2019年

作者： Bures, Miroslav Ahmed, Bestoun S. Zamli, Kamal Z. Department of Computer Science Faculty of Electrical Engineering Czech Technical University Karlovo nam. 13 Praha 2 121 35 Czech Republic Department of Mathematics and Computer Science Karlstad University Sweden IBM Center of Excellence Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang Malaysia

Testing processes and workows in information and Internet of Things systems is a major part of the typical software testing effort. Consistent and efficient path-based test cases are desired to support these tests. Because certain parts of software system workows have a higher business priority than others, this fact has to be involved in the generation of test cases. In this paper, we propose a Prioritized Process Test (PPT), which is a model-based test case generation algorithm that represents an alternative to currently established algorithms that use directed graphs and test requirements to model the system under test. The PPT accepts a directed multigraph as a model to express priorities, and edge weights are used instead of test requirements. To determine the test-coverage level of test cases, a test-depth-level concept is *** compared the presented PPT with five alternatives (i.e., the Process Cycle Test, a naive reduction of test set created by the Process Cycle Test, Brute Force algorithm, Set-covering Based Solution and Matching-based Prefix Graph Solution) for edge coverage and edge-pair coverage. To assess the optimality of the path-based test cases produced by these strategies, we used fourteen metrics based on the properties of these test cases and 59 models that were created for three real-world systems. For all edge coverage, the PPT produced more optimal test cases than the alternatives in terms of the majority of the metrics. For edge-pair coverage, the PPT strategy yielded similar results to those of the alternatives. Thus, the PPT strategy is an applicable alternative, as it reects both the required test coverage level and the business priority in parallel. Copyright © 2019, The Authors. All rights reserved.

关键词： software testing

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software module clustering based on the fuzzy adaptive teaching learning based optimization algorithm

arXiv

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arXiv 2019年

作者： Zamli, Kamal Z. Din, Fakhrud Ramli, Nazirah Ahmed, Bestoun S. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Gambang Kuantan Pahang26300 Malaysia Department of Computer Science and IT Faculty of Information Technology University of Malakand KPK Pakistan Department of Mathematics and Statistics Faculty of Information Technology and Quantitative Science Universiti Teknologi MARA Pahang Malaysia Faculty of Electrical Engineering Department of Computer Science Czech Technical University Czech Republic

Although showing competitive performances in many real world optimization problems, Teaching Learning based Optimization Algorithm (TLBO) has been criticized for having poor control on exploration and exploitation. Addressing these issues, a new variant of TLBO called Adaptive Fuzzy Teaching Learning based Optimization (ATLBO) has been developed in the literature. This paper describes the adoption of Fuzzy Adaptive Fuzzy Teaching Learning based Optimization (ATLBO) for software module clustering problem. Comparative studies with the original Teaching Learning based Optimization (TLBO) and other Fuzzy TLBO variant demonstrate that ATLBO gives superior performance owing to its adaptive selection of search operators based on the need of the current search. Copyright © 2019, The Authors. All rights reserved.

关键词： Optimization

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Development of M-learning Application based on Knowledge Management Processes

Development of M-learning Application based on Knowledge Man...

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2018年第七届软件与计算机应用国际会议

作者： Mostafa Al-Emran Vitaliy Mezhuyev Adzhar Kamaludin Maryam ALSinani Faculty of Computer Systems and Software Engineering Universiti Malaysia

The wide spectrum use of mobile devices has brought numerous opportunities to develop and design Mobile Learning(M-learning) applications that will assist learners in their studies. From the Mlearning perspective, in order to improve the learners' capabilities through the use of mobile devices, Knowledge Management(KM) processes(Knowledge Acquisition, Knowledge Sharing, Knowledge Application, and Knowledge Protection) should be incorporated in M-learning applications. The literature shows that several research studies were carried out with the aim of developing M-learning applications. Due to the lack of literature on examining the impact of KM processes on M-learning acceptance theoretically and practically, the main objective of this study is to develop a M-learning application that enables KM processes(Acquisition, Sharing, Application, and Protection). Moreover, the paper describes the M-learning application framework that was developed based on KM processes. In addition, the paper deliberates the implementation of the application in two different universities in two different regions, namely: Universiti Malaysia Pahang(UMP) in Malaysia, and Al Buraimi University College(BUC) in Oman. Other implications and discussions are also presented in the paper.

关键词： M-learning knowledge management processes mobile application

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

arXiv

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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

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A NovelMethod to Improve the Retrieved Multilingual Documents Score

A NovelMethod to Improve the Retrieved Multilingual Document...

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International Conference on computer, Control, Electrical, and Electronics engineering (ICCCEEE)

作者： Abas Aboras Aiman Solyman Albaraa Abobieda Hajer Yousif School of Software Engineering South China University of Technology Guangzhou China Faculty of Computer Studies International University of Africa Khartoum Sudan Department of Computer Systems and Networks Sudan University of Science and Technology SUST Khartoum Sudan

ISBN: (数字)9781728110066

ISBN: (纸本)9781728110073

With an ever-increasing number of resources on the Web, different language resources such as newspapers, magazines, and articles have become available. This demands for an improved technique in the information retrieval to extirpate the communication barrier among languages. Search engines are the cornerstones for informational contents and the link between the two parties of publishing and retrieval of content. Moreover, the search for information is no longer narrowed to users of the native language of the original source. Most of the non-English users such as Arabic speakers are unable to express the terms in their own language. Also, the terminologies written in the native language of the source are acquired from the English language. This challenge drives users to use mixed terms (multilingual terms) to get better results, especially in the scientific domain. This paper attempts to address the problem of documents retrieval using multilingual queries. When users use mixed queries, the results of the multilingual documents will dominate the top of the retrieved documents rather than other relevant documents, and the scores of the mixed documents obtain extra weight values that are not really part of their actual weighting value. This paper proposes a novel method to improve the results of the retrieved documents by adjusting the score of multilingual documents. For experiments, we used a mixed test collection containing mixedlanguage documents (Arabic and English). The results showed that the proposed method led to an enhanced performance in documents retrieval from multilingual queries which made them relevant, effective and accurate thus proving that our approach is more reliable than other traditional approaches.

关键词： Search engines Terminology Mathematical model Search problems Vocabulary Indexes

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