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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Thanamatee, Tawan Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol Ketcham, Mahasak King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Applied Computer Science Program King Mongkut s University of Technology Thonburi Bangkok Thailand Department of Digital Media Technology Thailand King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand

ISBN: (纸本)9798350336573

The purpose of this research was to develop a power consumer service support system, a case study of the Provincial Electricity Authority, Chumphon Province. By applying the ITIL version 3 operating framework to be applied in conjunction with the geographic information system, the efficiency of the application of the geographic information system was assessed, the quality of the system was assessed by experts and the satisfaction of general users was assessed. This system was developed to increase the efficiency and accuracy of electricity consumer services. receive follow-up notifications request for service and service complaints Able to display statistical reports in geographic information formats resulting in standardized customer service management. Evaluation results of the efficiency of the system in finding and displaying the coordinates of service locations have an average overall efficiency of F-Measure of 92 percent and the quality assessment of experts at a good level with an average of 4.17 deviations. The standard was 0.51 and the satisfaction assessment results of general users were at a good level with an average of 4.35 and a standard deviation of 0.42 from both groups of assessors. It can be concluded that the developed system can be applied to real work efficiently and effectively © 2023 IEEE.

关键词： Geographic information systems

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A MAC Protocol for Target-Tracking in Wireless Sensor Network

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Chinese Journal of Electronics 2023年第2期22卷 359-362页

作者： Mingxi Li Yan Xiong Yi Chen Hu Si School of Computer Science and Technology University of Science and Technology of China Hefei China New Star Research Institute of Applied Technology Hefei China School of Electronic Science and Technology University of Science and Technology of China Hefei China

Efficient target localization in Wireless sensor network (WSN) relies significantly on the Medium access control (MAC) it implements. TDMA MAC protocol is customarily used in these applications. But it only has good performance in motionless target detection, and can't cope with target-tracking detection. In this paper, a Target-tracking MAC (TT-MAC) protocol is proposed for target-tracking detection in target localization WSN. In this protocol, an energy-based clustering technique is used to achieve target-tracking detection, a sleeping mechanism is proposed for energy conservation, and a tight scheduling mechanism is proposed to reduce the latency. The protocol is compared with the cluster-based MAC protocol on Mica2 platform, and shows its superiority in energy and latency.

关键词： Location awareness Wireless communication Wireless sensor networks Time division multiple access Protocols Energy conservation Object detection

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Characterization of Vertical Wind Speed Profiles Based on Ward's Agglomerative Clustering Algorithm

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Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1437-1449页

作者： M.C.Bueso A.Molina-García A.P.Ramallo-González A.Fernández-Guillamón Department of Applied Mathematics and Statistics Universidad Politécnica de Cartagena30202 CartagenaSpain Department of Automatics Electrical Engineering and Electronic TechnologyUniversidad Politécnica de Cartagena30202 CartagenaSpain Department of Information and Communications Engineering Computer Science FacultyUniversity of Murcia30100 MurciaSpain Universidad de Castilla La-Mancha Campus Universitario02071 AlbaceteSpain

Wind turbine blades have been constantly increasing since wind energy becomes a popular renewable energy source to generate electricity. Therefore, the wind sector requires a more efficient and representative characterization of vertical wind speed profiles to assess the potential for a wind power plant site. This paper proposes an alternative characterization of vertical wind speed profiles based on Ward's agglomerative clustering algorithm, including both wind speed module and direction data. This approach gives a more accurate incoming wind speed variation around the rotor swept area, and subsequently, provides a more realistic and complete wind speed vector characterization for vertical profiles. Real wind database collected for 2018 in the Forschungsplattformen in Nordund Ostsee(FINO) research platform is used to assess the methodology. A preliminary pre-processing stage is proposed to select the appropriated number of heights and remove missing or incomplete data. Finally, two locations and four heights are selected, and 561588 wind data are characterized. Results and discussion are also included in this paper. The methodology can be applied to other wind database and locations to characterize vertical wind speed profiles and identify the most likely wind data vector patterns.

关键词： Clustering algorithm wind speed data management power generation

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Smart Bin for Covid19 2

Smart Bin for Covid19

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Department of Digital Media Technology Thailand

ISBN: (纸本)9798350336573

The purpose of this research was to develop a device that would facilitate visually impaired people in the use of lidded bins. And reduce the risk of spreading COVID-19 and other pathogens that may be contaminated with the trash area to all users Able to develop prototype devices to be used in practice and have the opportunity to extend it for practical use in the community area Or a point where there is a risk of the spread of garbage dumping information per day of that area for use in further data analysis. © 2023 IEEE.

关键词： Internet of things

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Cumulants from fluctuating width of rapidity distribution

arXiv

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arXiv 2023年

作者： Barej, Michal Bzdak, Adam AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków30-059 Poland

In relativistic heavy-ion collisions, the longitudinal fluctuations of the fireball density caused, e.g., by baryon stopping fluctuations result in event-by-event modifications of the shape of the proton rapidity density distribution. The multiparticle rapidity correlation functions due to the varying distribution width of the proton rapidity density in central Au+Au collisions at low energies are derived. The cumulant ratios are calculated and discussed in the context of the recent STAR Collaboration results. We find that the cumulant ratios for small width fluctuations seem to be universal. © 2023, CC BY.

关键词： Heavy ions

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A news image captioning approach based on multimodal pointer-generator network

A news image captioning approach based on multimodal pointer...

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作者： Chen, Jingqiang Zhuge, Hai School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Network Engineering Guangzhou University Guangzhou China Department of Computer Science School of Engineering and Applied Science Aston University Birmingham United Kingdom Key Laboratory of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing China

News image captioning aims to generate captions or descriptions for news images automatically, serving as draft captions for creating news image captions manually. News image captions are different from generic captions as news image captions contain more detailed information such as entity names and events. Therefore, both images on news and the accompanying text are the source of generating caption of news image. Pointer-generator network is a neural method defined for text summarization. This article proposes the Multimodal pointer-generation network by incorporating visual information into the original network for news image captioning. The multimodal attention mechanism is proposed by splitting attention into visual attention paid to the image and textual attention paid to the text. The multimodal pointer mechanism is proposed by using both textual attention and visual attention to compute pointer distributions, where visual attention is first transformed into textual attention via the word-image relationships. The multimodal coverage mechanism is defined to reduce repetitions of attentions or repetitions of pointer distributions. Experiments on the DailyMail test dataset and the out-of-domain BBC test dataset show that the proposed model outperforms the original pointer-generator network, the generic image captioning method, the extractive news image captioning method, and the LDA-based method according BLEU, METEOR, and ROUGL-L evaluations. Experiments also show that the proposed multimodal coverage mechanisms can improve the model, and that transforming visual attention to pointer distributions can improve the model. © 2020 John Wiley & Sons, Ltd.

关键词： Statistical tests

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Genetic Algorithm Based Adaptive FSO Communication Link

Genetic Algorithm Based Adaptive FSO Communication Link

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Business Analytics for technology and Security (ICBATS), International Conference on

作者： Abedallah Abualkishik Muhammad Saleem Umer Farooq Muhammad Asif Muhammad Hassan Javaid Ahmad Malik College of Computer and Information Technology American University in the Emirates Dubai United Arab Emirates School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science LGU Lahore Pakistan

Free Space Optical (FSO) communication systems are used to transmit high data rates over short distances through the atmosphere. However, the performance of FSO communication links can be severely impacted by atmospheric conditions, such as fog, rain, and atmospheric turbulence. These conditions cause temporary and spatial changes in light intensity, which can lead to signal degradation and disruption. To ensure reliable FSO communication, it is important to take into account the meteorological conditions of the location where the FSO communication link will be deployed. This will help in determining the expected level of link availability and identifying potential problems that could arise due to atmospheric conditions. For example, if a location is prone to fog or heavy rain, it may not be suitable for FSO communication link. One key factor in the design and operation of FSO communication links is the Geometrical Losses (GL), which refer to the loss of power due to the divergence of the laser beam as it propagates through the atmosphere. This can be minimized by increasing the diameter of the receiver aperture, which allows more of the laser beam to be collected and directed towards the *** this paper, the researchers used a Genetic Algorithm (GA) to minimize GLs in the FSO communication link. The GA is an optimization technique that mimics the process of natural selection to find the best solution to a problem. In this case, the GA was used to find the optimal diameter of the receiver aperture that would minimize GLs. The researchers used the optimum tool in MATLAB 2017 to implement the GA and found that after a certain number of iterations, the GLs remained constant. This was considered to be the optimal diameter of the receiver aperture.

关键词： Rain Atmosphere Apertures Propagation losses Mathematical models Laser beams Security

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Closest Celestial Body Search Using KD Trees

Closest Celestial Body Search Using KD Trees

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International Conference on computer Communication and Informatics (ICCCI)

作者： P Priya Ponnusamy C P Shabariram V R Umayal A Susmeta Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Neelambur Coimbatore India

A Binary Search Tree is expanded into a KD Tree to handle the multi-dimensional key searches. A discriminator makes the KD tree different from the BST. This discriminator will take branching decisions at every level based on the key search. It can handle multi-dimensional coordinate object searching. K-d trees enable O(klogn) lookup times for the k nearest points to some point x. This is extremely useful, especially in cases where an O(n) lookup time is intractable already. In this work, a kd tree has been created based on how a celestial body is positioned in relation to the sun. It aims at finding the minimum in a particular dimension, searching for a celestial body and its nearest neighbor.

关键词： Binary search trees Search problems Sun Informatics

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Smart Alarm Clock for Effective Sleep Health 2

Smart Alarm Clock for Effective Sleep Health

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Kwansomkid, Kantapat Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand Department of Digital Media Technology Thailand

ISBN: (纸本)9798350336573

The purpose of this research is to study and develop an alarm clock to help wake up at the set time. Without having to snooze the alarm and not be so sleepy that you have to go back to sleep again. to help reduce the risk of sleep-related disease By using various sensors, the Internet Of Thing (IoT) technology is used for health benefits. And from the evaluation of the accuracy of the system by experts. has a total value of 86% © 2023 IEEE.

关键词： Internet of things

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Utilization of Machine Learning in Breast Cancer Detection

Utilization of Machine Learning in Breast Cancer Detection

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Information technology (ACIT)

作者： Mutaz Momani Nidal Yousef Qotadeh Aljawazneh A.T Issa Suhaila Abuowaida Raed Alazaidah Mohammed Talat Khouj Radwan Batyha Esraa Abu Elsoud Department of Computer Science Faculty of Information Technology Zarqa University Zarqa Jordan Department of Computer Science Faculty of Information Technology Al-Albayt University Mafraq Jordan Department of Data Science and AI Faculty of Information Technology Zarqa University Zarqa Jordan Department of Electrical Engineering University of Business and Technology Jeddah Saudi Arabia Department of Computer Science Faculty of IT Applied Science Private University Amman Jordan

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Breast cancer is the most prevalent cancer among women and can be deadly, necessitating early detection to enhance patient outcomes and treatment effectiveness. Recently, Machine Learning (ML) techniques have shown potential in medical diagnostics, especially in breast cancer screening. ML algorithms examine extensive medical databases, including patient records, to identify subtle patterns and anomalies indicative of cancer. These algorithms excel at recognizing intricate patterns that may be missed by human analysis. Thereby, increasing the precision of breast cancer diagnoses. By evaluating and analyzing medical data, ML algorithms can detect minute anomalies, facilitating early identification of potential cancer cases. A significant advantage of ML-based breast cancer detection is its capacity for continuous learning and adaptation. In this study, we utilized 34 classifiers and five feature selection methods on three datasets. The first dataset comprises 286 instances with 10 integer-type features. The second dataset includes 699 instances with 10 integer-type features, and the third dataset consists of 286 instances with 13 integer-type features. For Dataset 1, Filtered Classifier and J-48 yielded the best results, while the Bayesnet classifier performed best on Dataset 2. In Dataset 3, SimpleLogistic and LMT achieved the best outcomes. Regarding feature selection, the study showed that the GainRatioAttributeEval, InfoGainAttributeEval, and CorrelationAttributeEval techniques are the best among the feature selection methods tested in the study.

关键词： Machine learning algorithms Databases Machine learning Feature extraction Breast cancer Pattern recognition Classification algorithms Medical diagnosis Information technology Medical diagnostic imaging

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