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Implementation of Certainty Factor Method for Diagnoses of Photocopy Machine Damage

Journal of Physics: Conference Series 2019年第1期1255卷 012059-012059页

作者： Pakpahan, Aditiya Jijon Raphita Sagala Yesputra, Rolly Saputra, Herman Lubis, Adyanata Husain Sihotang, Hengki Tamando Teknik Informatika STMIK Pelita Nusantara Medan Sumatera Utara Indonesia Sistem Komputer STMIK Royal Kisaran Sumatera Utara-Indonesia STKIP Rokania Pasir Pengaraian Riau Teknik Informatika STMIK Bumigora Mataram Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Sumatera Utara Indonesia

Photocopying machines are machines that make paper copies of documents and other visual images quickly and cheaply. PT. TRITANU has a copy machine product, such as the Fotocpy Sharp machine Type B201D. The rapid development of photocopying technology at this time can be seen that adult photocopying machines are now not only operating copier but can scan, print, and even fax. The rapid development of photocopying technology does not necessarily provide complete convenience to users. This can be seen from the high cost of consultation in the event of damage to the photocopy machine, requiring time to check the damaged machine, and not to mention other procedures in the repair that exist at PT. TRANANU. So from to provide solutions to these problems, the researchers made an Expert System for Handling Print Results Problems on Sharp Photocopying Machines Type B201D Using the Certainty Factor Method. System testing shows that the system is able to diagnose damage to the B201D copy machine based on the symptoms in the printout, even though these symptoms contain uncertainty. The results of the diagnosis are accompanied by Certainty Factor values that indicate the level of truth, accuracy of possible damage to the B201D copy machine.

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Knowledge and Awareness of Generative Artificial Intelligence Use in Medicine Among International Stakeholders: A Cross-Sectional Study

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Journal of evidence-based medicine 2025年第2期18卷 e70034页

作者： Xufei Luo Bingyi Wang Yule Li Shuang Liu Haodong Li Yaxuan Ren Wah Yang Kyle Lam Stephen R Ali Gemma Sharp Fabio Ynoe Moraes Ye Wang Di Zhu Zhenhua Yang Daher Mohammad Robert Fruscio Maged N Kamel Boulos Zhicheng Lin Kazuki Ide Xuping Song Lu Zhang Yih Chung Tham Hui Liu Long Ge Yaolong Chen Zhaoxiang Bian Evidence-Based Medicine Center School of Basic Medical Sciences Lanzhou University Lanzhou China. Research Unit of Evidence-Based Evaluation and Guidelines Chinese Academy of Medical Sciences (2021RU017) School of Basic Medical Sciences Lanzhou University Lanzhou China. World Health Organization Collaboration Center for Guideline Implementation and Knowledge Translation Lanzhou China. Institute of Health Data Science Lanzhou University Lanzhou China. Key Laboratory of Evidence Based Medicine of Gansu Province Lanzhou University Lanzhou China. Editorial Office of Medical Journal of Peking Union Medical College Hospital Peking Union Medical College Hospital Chinese Academy of Medical Sciences & Peking Union Medical College Beijing China. Chinese Journal of Hematology National Clinical Research Center for Blood Diseases Haihe Laboratory of Cell Ecosystem Institute of Hematology & Blood Diseases Hospital Chinese Academy of Medical Sciences & Peking Union Medical College Tianjin China. Tianjin Institutes of Health Science Tianjin China. School of Public Health Lanzhou University Lanzhou China. School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu China. Department of Metabolic and Bariatric Surgery The First Affiliated Hospital of Jinan University Guangzhou China. Department of Surgery and Cancer Imperial College London London UK. Reconstructive Surgery and Regenerative Medicine Research Centre Institute of Life Sciences Swansea University Medical School Swansea UK. School of Psychology University of Queensland Brisbane Australia. Department of Oncology Queen's University Kingston Canada. School of Chinese Medicine Vincent V.C. Woo Chinese Medicine Clinical Research Institute Hong Kong Baptist University Hong Kong China. Orthopedic Department Hôtel Dieu de France Beirut Lebanon. UO Gynecology Fondazione IRCCS San Gerardo dei Tintori Monza Italy. Department of Medicine and Surgery University of Milan-Bicocca Milan Italy.

OBJECTIVE:To assess the knowledge, attitudes, and practices (KAP) of medical stakeholders regarding the use of generative artificial intelligence (GAI) tools. METHODS:A cross-sectional survey was conducted among stakeholders in medicine. Participants included researchers, clinicians, and medical journal editors with varying degrees of familiarity with GAI tools. The survey questionnaire comprised 40 questions covering four main dimensions: basic information, knowledge, attitudes, and practices related to GAI tools. Descriptive analysis, Pearson's correlation, and multivariable regression were used to analyze the data. RESULTS:The overall awareness rate of GAI tools was 93.3%. Participants demonstrated moderate knowledge (mean score 17.71 ± 5.56), positive attitudes (mean score 73.32 ± 15.83), and reasonable practices (mean score 40.70 ± 12.86). Factors influencing knowledge included education level, geographic region, and attitudes (p < 0.05). Attitudes were influenced by work experience and knowledge (p < 0.05), while practices were driven by both knowledge and attitudes (p < 0.001). Participants from outside China scored higher in all dimensions compared to those from China (p < 0.001). Additionally, 74.0% of participants emphasized the importance of reporting GAI usage in research, and 73.9% advocated for naming the specific tool used. CONCLUSION:The findings highlight a growing awareness and generally positive attitude toward GAI tools among medical stakeholders, alongside the recognition of their ethical implications and the necessity for standardized reporting practices. Targeted training and the development of clear reporting guidelines are recommended to enhance the effective use of GAI tools in medical research and practice.

关键词： ChatGPT cross‐sectional survey generative artificial intelligence knowledge and awareness

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Swarm intelligence: Past, present and future

arXiv

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arXiv 2018年

作者： Yang, Xin-She Deb, Suash Zhao, Yu-Xin Fong, Simon He, Xingshi School of Science and Technology Middlesex University LondonNW4 4BT United Kingdom IT & Educational Consultant Ranchi India Decision Sciences and Modelling Program Victoria University MelbourneVIC Australia College of Automation Harbin Engineering University Harbin China Department of Computer and Information Sciences University of Macau Macau China College of Science Xi'an Polytechnic University No. 19 Jinhua South Road Xi'an China

Many optimization problems in science and engineering are challenging to solve, and the current trend is to use swarm intelligence (SI) and SI-based algorithms to tackle such challenging problems. Some significant developments have been made in recent years, though there are still many open problems in this area. This paper provides a short but timely analysis about SI-based algorithms and their links with self-organization. Different characteristics and properties are analyzed here from both mathematical and qualitative perspectives. Future research directions are outlined and open questions are also highlighted.68T99, 90C30, 90C59 Copyright © 2018, The Authors. All rights reserved.

关键词： Swarm intelligence

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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Comparative analysis of RC4+ algorithm, RC4 NGG algorithm and RC4 GGHN algorithm on image file security

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IOP Conference Series: Materials science and Engineering 2018年第1期420卷

作者： F Akbar H Mawengkang S Efendi Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia. Department of Mathematics University Sumatera Utara Medan Indonesia. Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia.

File security is very important in maintaining the confidentiality of the information contained in the file. For that we need a way for information to be kept secrecy, that is with the science of cryptography. Cryptography is one method that disguises data to form encrypted data. In the symmetric RC4+ (Ron Code or Rivest's Cipher) algorithm, it provides secure message security and is an efficient stream cipher. RC4 NGG stream cipher algorithm 3-5 times faster than RC4 algorithm and but still have weakness in KSA randomization. The RC4 GGHN stream cipher algorithm is based on the RC4 algorithm and is relatively more efficient but still has weaknesses. Based on literature review from several research sources, it was stated that RC4+, RC4 NGG, RC4 GGHN are algorithms that are faster and more efficient than RC4 algorithm. Therefore, it is necessary to compare the encryption process with the aim of comparing and knowing which algorithm is better from running time and algorithm complexity. In this research we will perform two tests on each algorithm, image encryption using different key length and same image size and image encryption using the same key length and different image size. The results obtained in this research is RC4 NGG algorithm is the fastest algorithm between the three algorithms that is 13.3% faster than RC4+ and 10.2% faster than RC4 GGHN where the key lengths used in encryption do not affect the processing time and image size used in encryption very affects the processing time.

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Service Quality Improvement by Using the Quality Function Deployment (QFD) Method at the Government General Hospital

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Journal of Physics: Conference Series 2019年第1期1363卷

作者： Abdurrozzaq Hasibuan Luthfi Parinduri Oris Krianto Sulaiman Abdul Rahman Suleman Adek Khadijatul Z Harahap Masnilam Hasibuan Frits Gerit John Rupilele Janner Simarmata Nuning Kurniasih GS Achmad Daengs Abdussakir Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Faculty of Computer Science Universitas Victory Sorong Sorong Indonesia Faculty of Economic Universitas Graha Nusantara Padangsidimpuan Indonesia Universitas Negeri Medan Medan Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Faculty of Economic Universitas 45 Surabaya Surabaya Indonesia Faculty of Science and Technology Universitas Islam Negeri Maulana Malik Ibrahim Malang Indonesia

In the face of increasingly competitive competition in the hospital industry, RSU managers are required to be able to develop strategies, policies or new breakthroughs related to improving the quality of their services, through improving the characteristics of hospital services, which focus on patient needs, so that the risk of errors or discrepancies between service characteristics that are enhanced by what the patient wants can be avoided or minimized. From the results of research conducted there are 21 variables of patient needs from a health service at the Government General Hospital (RSU). Whereas the patient's research on the service quality of the Government Hospital is 1 variable that has fulfilled the needs of patients, namely that they are satisfied with the quality of hospital services. Variable is the state and completeness of modern medical facilities. Whereas for other variables there are gaps so that they cannot meet patient expectations until the highest quality limit is very satisfied, it is necessary to have a direction of improvement. To obtain the suitability, the technique used to improve the characteristics of the service is the application of the QFD method. The QFD method in this study is in the form of a quality service matrix at the Government General Hospital. From the HOQ matrix, the service quality of the Government Hospital is obtained from the input of the Government Hospital/management that there are priority variables needed to improve their quality, which is generally the patient's needs related to the recovery of patients, including the knowledge and abilities of doctors, medicines the treatment given in the healing of patients, the service of examination, treatment and care that is fast and precise, guarantee of security and trust in the services provided and the completeness of the readiness and cleanliness of the equipment used. So there are 33 service quality characteristics prioritized for further improvement, with the main pr

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Power of pausing: Advancing understanding of thermalization in experimental quantum annealers

arXiv

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arXiv 2018年

作者： Marshall, Jeffrey Venturelli, Davide Hen, Itay Rieffel, Eleanor G. USRA Research Institute for Advanced Computer Science Mountain ViewCA94035 United States USRA NAMS Quantum Academy R&D Student Program NASA Ames Research Center Mountain ViewCA94035 United States Department of Physics and Astronomy Center for Quantum Information Science & Technology University of Southern California Los AngelesCA90089 United States QuAIL NASA Ames Research Center Moffett FieldCA94035 United States Information Sciences Institute University of Southern California Marina del ReyCA90292 United States

We investigate alternative annealing schedules on the current generation of quantum annealing hardware (the D-Wave 2000Q), which includes the use of forward and reverse annealing with an intermediate pause. This work provides new insights into the inner workings of these devices (and quantum devices in general), particular into how thermal effects govern the system dynamics. We show that a pause mid-way through the anneal can cause a dramatic change in the output distribution, and we provide evidence suggesting thermalization is indeed occurring during such a pause. We demonstrate that upon pausing the system in a narrow region shortly after the minimum gap, the probability of successfully finding the ground state of the problem Hamiltonian can be increased over an order of magnitude. We relate this effect to relaxation (i.e. thermalization) after diabatic and thermal excitations that occur in the region near to the minimum gap. For a set of large-scale problems of up to 500 qubits, we demonstrate that the distribution returned from the annealer very closely matches a (classical) Boltzmann distribution of the problem Hamiltonian, albeit one with a temperature at least 1.5 times higher than the (effective) temperature of the annealer. Moreover, we show that larger problems are more likely to thermalize to a classical Boltzmann distribution. Copyright © 2018, The Authors. All rights reserved.

关键词： Boltzmann equation

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An Improvement Data Hiding Scheme Based on Formula Fully Exploiting Modification Directions and Pixel Value Differencing Method 11

An Improvement Data Hiding Scheme Based on Formula Fully Exp...

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11th Asia Joint Conference on information Security, AsiaJCIS 2016

作者： Kuo, Wen-Chung Li, Jyun-Jia Wang, Chun-Cheng Wuu, Lih-Chyau Huang, Yu-Chih Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Taiwan Department of Information Management Tainan University of Technology Taiwan

ISBN: (纸本)9781509022854

Recently, a modified data hiding scheme based on pixel value differencing and improving exploiting modification directions is proposed by Shen and Huang. There are two major contributions in this scheme. One is to enhance the embedding rate and good embedding capacity and the other is an optimization problem used to solve the overflow/ underflow problem. In fact, they propose the similar brute force method to solve overflow/underflow problem in their proposed scheme. To overcome the overflow/underflow problem exactly, we will propose the close form to solve this problem in this paper. Then, an improvement data hiding scheme based on FFEMD (Formula Fully Exploiting Modification Directions) and pixel value differencing method is proposed. According to our analysis, it is not only to keep the advantages of Shen-Huang scheme but also to use the close form to solve the overflow/ underflow problem. © 2016 IEEE.

关键词： Pixels

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Perceptron Partition Model to Minimize Input Matrix

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IOP Conference Series: Materials science and Engineering 2019年第1期536卷

作者： Zulfian Azmi Mahyuddin K.M. Nasution Muhammad. Zarlis Herman Mawengkang Syahril Efendi Postgraduate Doctoral of Computer Science Universitas Sumatera Utara Padang Bulan USU Medan 20155 Indonesia. Information Technology Department Universitas Sumatera Utara Padang Bulan USU Medan 20155 Indonesia. Program Pasca Sarjana Doktoral Ilmu Komputer Universitas Sumatera Utara Indonesia. Department of Mathematics Universitas Sumatera Utara Padang BulanUSU Medan20155 Indonesia.

Implementation of Neuron Network model using Perceptron has not given optimal result in real time learning. The large number of inputs expressed in matrix form makes the process slower in pattern recognition. So, it takes characteristic to represent all the input matrices by using the partition method. By partitioning each input and with the best weight and using the activation function will produce an output value. And learning is valid in recognizing patterns only 1 iteration only. Further validation is done on the water mill control module with dissolved oxygen input, water pH, salinity and water temperature. With Perceptron Partition learning algorithm more real-time than perceptron model. Testing on the waterwheel input whether rotating or stopping by Matrix Laboratory software simulation.

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Publisher Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

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Nature genetics 2023年第1期55卷 166页

作者： Huipeng Li Elise T Courtois Debarka Sengupta Yuliana Tan Kok Hao Chen Jolene Jie Lin Goh Say Li Kong Clarinda Chua Lim Kiat Hon Wah Siew Tan Mark Wong Paul Jongjoon Choi Lawrence J K Wee Axel M Hillmer Iain Beehuat Tan Paul Robson Shyam Prabhakar Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India. Synthetic Biology Genome Institute of Singapore Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. Department of Pathology Singapore General Hospital Singapore Singapore. Department of Colorectal Surgery Singapore General Hospital Singapore Singapore. Data Analytics Department Institute for Infocomm Research Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. paul.robson@***. The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA. paul.robson@***. Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA. paul.robson@***. Department of Biological Sciences National University of Singapore Singapore Singapore. paul.robson@***. Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. prabhakars@gis.a-star.edu.sg.

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