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5th International Conference on engineering, Applied Sciences and technology, ICEAST 2019

作者： Laomuad, Sattra Chansuttirangkool, Manutsiri Lekdee, Kriangsak Soysouvanh, Saysamone Vongchumyen, Charoen Mitatha, Somsak Faculty of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok10540 Thailand Technology of Information System Management Devision Faculty of Engineering Mahidol University Nakornpathom Thailand Office of Information Technology Administration for Educational Development Bangkok10400 Thailand

ISBN: (纸本)9781728100678

This paper proposes the design of recursive Anycast DNS service system using as a replacement for the original unicast DNS service system that the UniNet Network is active and having problems supporting the volume of client traffic that has a large number of educational institutions. In order to increase the efficiency of providing services to clients of educational institutions. The designing from setting up the server host in various node and the designing the server connected to a suitable network for routing protocol has been proposed, including designing an emergency backup system that regards to compatibility with current network systems and the use of the original unicast DNS system to be useful. As a result of testing the designed system, it was found that the Query time of the new system was 2 times less than that of the original system for query IPv4, and 5 times less than that of the original system for query IPv6. Anycast DNS system that was installed can support the amount of DNS Query more 15 times than the original unicast DNS system. © 2019 IEEE.

关键词： Border Gateway Protocol

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Production Time Optimization using Campbell Dudek Smith (CDS) Algorithm for Production Scheduling 4

Production Time Optimization using Campbell Dudek Smith (CDS...

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4th International Conference on Energy, Environment, Epidemiology and information system, ICENIS 2019

作者： Mashuri, Chamdan Mujianto, Ahmad Heru Sucipto, Hadi Arsam, Rinaldo Yudianto Permadi, Ginanjar Setyo Information System Department Information Technology Faculty Hasyim Asy'ari University Jombang Indonesia Informatics Engineering Department Information Technology Faculty Hasyim Asy'ari University Jombang Indonesia Informatics Management Department Information Technology Faculty Hasyim Asy'ari University Jombang Indonesia

The production time optimization study used the Campbell Dudek smith (CDS) algorithm in the production process scheduling aimed at makespan optimization for engine operation to produce 12-size pan products, 14-size griddle, 16-size griddle, 18-size griddle, and 20-size griddle. The method applied by the Campbell Dudek and Smith (CDS) algorithm, CDS is a method used in flowshop-type scheduling developed from Johnson's rule that is able to minimize makespan 2 machines arranged in series. The CDS method is very suitable for production characters who apply the machine sequence to the production process. CDS produces several iterations that have makespan values, from the few iterations the most minimum makespan value is obtained to determine the order of products to be produced. This research produces an application that can schedule products to be produced by the machine automatically. From the results of testing with a total production of 12 pieces on each product with repetitions of 6 times, the minimum makespan value is 210.12 minutes with a work order of 20, grid 18, griddle 16, griddle 14, and griddle 12. Accuracy of results Application testing showed 99.99% for the first time and 99.96% for the second time when compared to manual calculations. © The Authors, published by EDP Sciences, 2019.

关键词： Scheduling

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Knowledge management infrastructure capabilities towards innovative work behavior: Employee's resilience and role of functional flexibility

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Heliyon 2024年第20期10卷 e38742页

作者： Nassani, Abdelmohsen A. Al-Aiban, Khalid M. Rosak-Szyrocka, Joanna Yousaf, Zahid Isac, Nicoleta Badshah, Waqar Department of Management College of Business Administration King Saud University P.O. Box 71115 Riyadh 11587 Saudi Arabia Department of Public Administration College of Business Administration King Saud University P.O. Box 71115 Riyadh 11587 Saudi Arabia Department of Production Engineering and Safety Faculty of Management Czestochowa University of Technology Czestochowa 42-200 Poland Higher Education Department Government College of Management Sciences Mansehra 22300 Pakistan Business Administration Istanbul Sabahattin Zaim University Halkalı Cad. No: 281 Halkalı Küçükçekmece Istanbul 34303 Turkey Department of Management and Business Administration Pitesti University Center National University of Science and Technology POLITEHNICA Bucharest Romania Management Information System Istanbul University Süleymaniye KaptanıDerya İbrahim PaşaYkş. No:5 Fatih İstanbul 34126 Turkey

This study aims to identify the specific mechanisms through which knowledge management infrastructure capabilities (KMIC) can affect IWB and provide insights into how organizations can support innovation through the development of resilient employees. Therefore, current research investigates the association between Knowledge-management Infrastructure Capability (KMIC), Employee Resilience, Function-al-Flexibility (FF), and Innovative Work-Behavior (IWB) in the workplace. The data was collected through a survey of 374 employees working in tourism firms. For data collection, random sampling method and SEM technique was used. The outcomes demonstrate that KMIC has significant link with IWB;findings also present that employee's resilience mediates and functional flexibility moderates in the association between KMIC and IWB, which in turn have a positive and significant impact on IWB. By investing in knowledge management practices, developing employee resilience, and enhancing functional flexibility, organizations can improve their competitiveness, promote growth and innovation, and enhance their employees' well-being and job satisfaction. This study just explored how KMIC affected innovative work behavior directly and indirectly. In future additional factors such as leadership style and organizational culture could be explored. Additionally, the study found that functional flexibility moderates the relationship between employee resilience and IWB. This study finding offer imperative implications for organizations that aims to improve their employees' resilience, functional flexibility, and IWB through knowledge management practices. Through inferring these dynamics, this research provides valued insights for upcoming studies on the executive origination and offer useful instructions for industries pursuing to raise employee determined invention with strong KMIC, nurturing resilience and stimulating functional flexibility. © 2024 The Author(s)

关键词： Employee's resilience Functional flexibility Innovative work behavior KMIC

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Arabic handwritten character recognition based on convolution neural networks and support vector machine

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arXiv 2020年

作者： Shams El Den, Mahmoud Yassien Elsonbaty, Amira A. ElSawy, Wael Z. Department of Machine Learning and Information Retrieval Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh33511 Egypt Department of Electronic and Communication Higher Institute of Engineering and Technology New Damietta Egypt Department of Business Information System Faculty of Management Technology and Information System PortSaid University 42511 Egypt

Recognition of Arabic characters is essential for natural language processing and computer vision fields. The need to recognize and classify the handwritten Arabic letters and characters are essentially required. In this paper, we present an algorithm for recognizing Arabic letters and characters based on using deep convolution neural networks (DCNN) and support vector machine (SVM). This paper addresses the problem of recognizing the Arabic handwritten characters by determining the similarity between the input templates and the pre-stored templates using both fully connected DCNN and dropout SVM. Furthermore, this paper determines the correct classification rate (CRR) depends on the accuracy of the corrected classified templates, of the recognized handwritten Arabic characters. Moreover, we determine the error classification rate (ECR). The experimental results of this work indicate the ability of the proposed algorithm to recognize, identify, and verify the input handwritten Arabic characters. Furthermore, the proposed system determines similar Arabic characters using a clustering algorithm based on the K-means clustering approach to handle the problem of multi-stroke in Arabic characters. The comparative evaluation is stated and the system accuracy reached 95.07% CRR with 4.93% ECR compared with the state of the art. Copyright © 2020, The Authors. All rights reserved.

关键词： Support vector machines

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Modeling the number of confirmed cases of COVID-19 in East Java using negative binomial regression based on least square spline estimator

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AIP Conference Proceedings 2024年第1期3083卷

作者： Arip Ramadan Nur Chamidah I. Nyoman Budiantara Student of Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Department of Information System School of Industrial and System Engineering Telkom University Surabaya 60231 Indonesia. Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Department of Statistics Faculty of Sciences and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia.

The East Java Province has experienced a significant surge in number of confirmed cases of COVID-19. This study endeavors to investigate the potential correlation between weather conditions and the incidence of number of confirmed cases of COVID-19 in East Java. To achieve this, a nonparametric regression model, specifically, the Negative Binomial Regression (NBR) model based on the least squares spline estimator, was utilized. The outcomes of the study indicate that the Mean Absolute Percentage Error (MAPE) of nonparametic regression model is 0.30. Meanwhile, the MAPE for the parametric regression model is 0.34. The results show that a nonparametric regression model approach is better than parametric regression model approach. The study establishes that the truncated spline estimator based NBR model represents the best fit, with an MLCV value of -256.71. The findings of the study suggest that a temperature less than 21.75°C is associated with a decrease of 13.28 number of confirmed cases of COVID-19 per each 1°C increase, while a temperature between 21.75°C and 25.78°C is linked to an increase of 6.85 number of confirmed cases of COVID-19 per each 1°C increase. In contrast, a temperature greater than 25.78°C is associated with a decrease of 139.42 number of confirmed cases of COVID-19 per each 1°C increase. Similarly, a wind speed less than 5.57 m/s is related to a decrease of 12.99 number of confirmed cases of COVID-19 per each 1 m/s increase, whereas a wind speed between 5.57 m/s and 8.99 m/s is associated with a decrease of 10.29 number of confirmed cases of COVID-19 per each 1 m/s increase. Furthermore, a wind speed greater than 8.99 m/s is linked to a decrease of 19.16 number of confirmed cases of COVID-19 per each 1 m/s increase. The study provides evidence that higher temperatures and wind speeds result in a slower rise in the incidence of the number of confirmed cases of COVID-19. Consequently, it is recommended that the local government remains vigilant du

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Correction: Explainable lung cancer classification with ensemble transfer learning of VGG16, Resnet50 and InceptionV3 using grad-cam

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BMC medical imaging 2024年第1期24卷 195页

作者： Yogesh Kumaran S J Jospin Jeya Mahesh T R Surbhi Bhatia Khan Saeed Alzahrani Mohammed Alojail Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru 562112 India. Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India. Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru 562112 India. trmahesh.1978@***. School of science engineering and environment University of Salford Manchester UK. Management Information System Department College of Business Administration King Saud University Riyadh Saudi Arabia.

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Analysing the impact of COVID-19 outbreak and economic policy uncertainty on stock markets in major affected economies

Analysing the impact of COVID-19 outbreak and economic polic...

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6th Smart Cities Symposium (SCS 2022)

作者： A. Matuka S. S. Asafo G. O. Eweke P. Mishra S. Ray M. Abotaleb T. Makarovskikh A.A. Alhussan A.A. Abdelhamid E.M. El-Kenawy P. Dutta S. Chowdhury University of Macerata Department of Economics and Law Macerata Italy Department of Banking & Finance Niger Delta University Amassoma Nigeria College of Agriculture J.N.K.V.V. Powarkheda India Centurion University of Technology and Management Paralakhemundi India Department of System Programming South Ural State University Chelyabinsk Russia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia Department of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technolog School of Engineering and Technology Amity University Kolkata Kolkata India MCA Department Sri Venkateshwara College of Engineering and Technology Chittoor India

The covid-19 pandemic and Economic Policy Uncertainty resulting from the shutdown of production, withdrawal of investments, enforcement of lockdowns and quarantines globally, have been directly affecting stock markets worldwide. This study is thus an attempt to analyse the impact of the COVID-19 pandemic on stock market behaviour in major affected economies. Moreover, the time frame was extended by using current data which investigate the impact of the virus during the boom and the blast phase in the country's most hit by the pandemic crisis such as China, Italy, UK and US. The frequency of the data is daily, and it dates from 3 January 2020 up to 10 February 2021. The considered time framework will give a deep insight into how stock markets behave in the case of an exogenous shock. The Dickey-Fuller Augmented Unit Root Test indicates that all the variables are stationary at first difference, which is one of the main conditions to have robust result, and the ARCH-LM test for the heteroskedasticity of the residuals, which show that all the probability values are significant, rejecting the null hypothesis of no ARCH effect. Based on the results of GARCH (1,1), we conclude that the change in stock markets volatility is positive and significant in China, Italy, UK and USA. This suggests that the impacts of COVID-19 outbreak and economic policy uncertainty on Stock Markets are a significant and Homogeneous across the studied countries, and the shock on FTSE Italia All Share has the longest time to vanish which makes it the riskiest to invest during this period, while the shock on SP500 USA has the shortest time to disappear meaning that it is safest Stock Market in this study. These findings have significant implications for policymakers, institutional and individual investors and Financial Markets analysts.

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Handwriting prediction using the support vector machine method in web-based applications

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AIP Conference Proceedings 2022年第1期2659卷

作者： Syaifudin Dian Pratiwi Trubus Rahardiansyah Anasthesia Karunia Charles Hafiz Wijaya Khoirun Nisa 1Information System Study Program Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia 2Informatic Engineering Study Program Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia 3Department of Law Universitas Trisakti Jakarta Indonesia

Current technological advances have progressively encouraged individuals to use web-based applications. To determine the owner of a handwriting, one of the manual methods is generally done by people. And it can be done by a web application to find out the person’s handwriting. The Support Vector Machine (SVM) Method is a strategy of artificial intelligence used to recognize handwriting. This study intends to create a handwriting recognition framework using the Support Vector Machine (SVM) Method on a web-based application, with extraction features that are important as the basis for describing and characterizing handwritten images. The results obtained from predictions using the Support Vector Machine are by using 16 data and there are 80 tests carried out in total. The results obtained indicate that there are 25 incorrect prediction tests and 55 correct prediction tests so that the level of accuracy obtained is 68.75%.

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Oxidative Stress and Natural Antioxidants: Back and Forth in the Neurological Mechanisms of Alzheimer’s Disease

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Journal of Alzheimer's Disease 2023年第3期96卷 877-912页

作者： Mani, Shalini Dubey, Rajni Lai, I-Chun Babu, M. Arockia Tyagi, Sakshi Swargiary, Geeta Mody, Deepansh Singh, Manisha Agarwal, Shriya Iqbal, Danish Kumar, Sanjay Hamed, Munerah Sachdeva, Punya Almutary, Abdulmajeed G. Albadrani, Hind Muteb Ojha, Shreesh Singh, Sandeep Kumar Jha, Niraj Kumar Centre for Emerging Diseases Department of Biotechnology Jaypee Institute of Information Technology UP Noida India Division of Cardiology Department of Internal Medicine Taipei Medical University Hospital Taipei Taiwan School of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Division of Radiation Oncology Department of Oncology Taipei Veterans General Hospital Taipei Taiwan The Ph.D. Program for Translational Medicine College of Medical Science and Technology Taipei Medical University Academia Sinica Taipei Taiwan Institute of Pharmaceutical Research GLA University Mathura India Department of Molecular Sciences Macquarie University Sydney Australia Department of Health Information Management College of Applied Medical Sciences Buraydah Private Colleges Buraydah Saudi Arabia Department of Life Sciences School of Basic Sciences and Research (SBSR) Sharda University Uttar Pradesh Greater Noida India Department of Pathology Faculty of Medicine Umm Al-Qura University Makkah Saudi Arabia GloNeuro Vishwakarma Road Noida India Department of Biomedical Sciences College of Health Sciences Abu Dhabi University Abu Dhabi United Arab Emirates Department of Clinical Laboratory Sciences College of Applied Medical Sciences Imam Abdulrahman Bin Faisal University Eastern Province Dammam Saudi Arabia Department of Pharmacology and Therapeutics College of Medicine and Health Sciences United Arab Emirates University Abu Dhabi United Arab Emirates Indian Scientific Education and Technology Foundation Lucknow India Department of Biotechnology School of Engineering & Technology (SET) Sharda University Uttar Pradesh Greater Noida India School of Bioengineering and Biosciences Lovely Professional University Punjab Phagwara India Department of Biotechnology School of Applied & Life Sciences (SALS) Uttaranchal University Uttarakhand Dehradun India Department of Biotechnology Engineering and Food Technology Chandigarh University Mohali India

Alzheimer’s disease (AD) is characterized by the progressive degeneration of neuronal cells. With the increase in aged population, there is a prevalence of irreversible neurodegenerative changes, causing a significant mental, social, and economic burden globally. The factors contributing to AD are multidimensional, highly complex, and not completely understood. However, it is widely known that aging, neuroinflammation, and excessive production of reactive oxygen species (ROS), along with other free radicals, substantially contribute to oxidative stress and cell death, which are inextricably linked. While oxidative stress is undeniably important in AD, limiting free radicals and ROS levels is an intriguing and potential strategy for deferring the process of neurodegeneration and alleviating associated symptoms. Therapeutic compounds from natural sources have recently become increasingly accepted and have been effectively studied for AD treatment. These phytocompounds are widely available and a multitude of holistic therapeutic efficiencies for treating AD owing to their antioxidant, anti-inflammatory, and biological activities. Some of these compounds also function by stimulating cholinergic neurotransmission, facilitating the suppression of beta-site amyloid precursor protein-cleaving enzyme 1, α-synuclein, and monoamine oxidase proteins, and deterring the occurrence of AD. Additionally, various phenolic, flavonoid, and terpenoid phytocompounds have been extensively described as potential palliative agents for AD progression. Preclinical studies have shown their involvement in modulating the cellular redox balance and minimizing ROS formation, displaying them as antioxidant agents with neuroprotective abilities. This review emphasizes the mechanistic role of natural products in the treatment of AD and discusses the various pathological hypotheses proposed for AD. © 2023 – IOS Press. All rights reserved.

关键词： Alzheimer’s disease antioxidants neuroprotection oxidative stress therapeutics vitamins

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Operation management for strategic planning in hospitals

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AIP Conference Proceedings 2023年第1期2603卷

作者： Navaneetha Krishnan Rajagopal Muhammed Yousoof Suresh Esakki Senthil Kumar Subramaniam Tamilselvan Manickam S. Sivamani Faculty of Business Studies Department University of Technology & Applied Sciences Salalah Sultanate of Oman Faculty of Management Information System Dhofar University Salalah Sultanate of Oman Department of Business Studies SNS College of Technology Coimbatore 641 035 Tamilnadu India Faculty of Business Studies Department University of Technology & Applied Sciences Ibri Sultanate of Oman Department of Engineering University of Technology and Applied Sciences Salalah Oman

There have been a few, if any, studies on the convergence of operational management and strategic planning in healthcare, despite the fact that there are a large number of studies on these two topics. Healthcare leaders are under pressure to enhance service quality and save costs, which are two major concerns in the context of planning. This makes us wonder to just what extent operations are taken into account during the company’s strategy, and what effect this may have. We establish a trend in health board research and publications that address the operational capabilities of excellence, adaptability, availability, and controlling costs by reviewing the existing literature. These studies can be used as a starting point for study into hospital strategic planning, which is a topic that has received little attention in the academic literature. We also show how hospitals are dealing with operational capacities, and we finish with consequences for hospital managers and recommendations for further studies for academics.

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