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Student Conference on Research and Development (SCOReD)

作者： Joshu Leonardy Nawal Zuhdaniel Aflah Mohd Rashidi Bin Salim Mohd Haniff Bin Ibrahim Hadi Bin Manap Wildan Panji Tresna Faculty of Electrical Engineering Universiti Teknologi Malaysia JohorBahru Malaysia Military Physics Study Program The Republic of Indonesia Defense University Bogor Indonesia Faculty of Electrical & Electronic Engineering Technology University Malaysia Pahang Al Sultan Abdullah Pekan Malaysia Research Center for Photonics National Research and Inovation Agency Indonesia South Tangerang Indonesia

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

This research explores the use of a modified infrared (IR) camera equipped with a high-pass filter to distinguish between natural objects (vegetation) and artificial objects (synthetic military uniforms) in an environment where vegetation makes objects difficult to detect. In military operations, especially guerrilla warfare in tropical forests, detecting enemies camouflaged in vegetation makes it difficult to distinguish targeted objects. Visible light cameras usually struggle to distinguish between synthetic and natural colors. This methodology involves the use of Python programming and various libraries, such as Computer Vision (CV), to process images captured by modified cameras. A graphical user interface (GUI) was developed to analyze color values, focusing on the red, green, and blue spectra. The results show that the modified IR camera can more effectively separate synthetic and natural object color peaks compared to a standard visible light camera, offering potential applications in military reconnaissance and sniper operations. This research demonstrates how image processing can improve object detection in complex environments.

关键词： Image color analysis Vegetation mapping Object detection Reconnaissance programming Cameras Standards Research and development Graphical user interfaces Python

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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Linear Fresnel collector (LFC) for enhancing solar water desalination process 8

Linear Fresnel collector (LFC) for enhancing solar water des...

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8th International engineering Conference on Renewable Energy and Sustainability, ieCRES 2023

作者： El-Khozondar, Hala J. Elnaggar, Mohamed Elnaggar, Mohamed Ellouh, Ahmed Omar Alghaffari, Mahmoud Walid Nassar, Hamza Bassam Alnahhal, Mohammed Islamic University of Gaza Electrical Engineering and Smart Systems Department Palestine Palestine Technical College - Deir El-Balah Engineering Program Department Palestine Wadi Alshatti University Mechanical & Renewable Energy Eng. Dept Brack Libya Al-Azhar University Renewable Energy Engineering Department Gaza Palestine Islamic University of Gaza Mechanical Engineering Department Palestine Israa University-Palestine Faculty of Engineering and Information Technology Palestine

ISBN: (纸本)9798350300758

The limited availability of clean water resources in Gaza Strip is due to the increasing salinity of groundwater, which is due to unbalanced consumption. Furthermore, the increase in the poverty level among the people and the lack of fossil fuel resources, and the high intensity of solar radiation in the strip have grabbed the attention of the authors to think about a suitable alternative to produce potable water via solar energy. This study aims to investigate the linear Fresnel collector (LFC) coupled with a solar still-single effect active system. The solar still was designed to match the LFC output to avoid any heat losses that may decrease the system's effectiveness. A CFD simulation was carried out using Ansys Fluent software to predict temperature and pressure distributions to find out the efficiency of the LFC collector. The results showed that the use of LFC leads to an increase in the efficiency of the solar still, and the daily production of distilled water reaches 1.5 Litre /m2 © 2023 IEEE.

关键词： Potable water

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Real Time Monitoring System of Drinking Water Quality Using Internet of Things 24

Real Time Monitoring System of Drinking Water Quality Using ...

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24th International Electronics Symposium, IES 2022

作者： Abidin, Zainul Maulana, Eka Nurrohman, Muhammad Yogi Wardana, Fitri Candra Warsito Universitas Brawijaya Faculty of Computer Science Department of Computer Engineering Malang Indonesia Universitas Brawijaya Faculty of Engineering Department of Electrical Engineering Malang Indonesia Universitas Brawijaya Master Program in Environmental Resources and Development Management Postgraduate School Malang Indonesia Universitas Brawijaya Faculty of Mathematics and Natural Sciences Department of Chemistry Malang Indonesia

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

In order to reduce Polyethylene Terephthalate (PET) bottle plastic waste, Universitas Brawijaya (UB) provided reverse osmosis drinking water in some buildings. Water monitoring is needed to keep the water quality. Therefore, a water monitoring system based on Total Dissolved Solids (TDS), pH, and water flow was proposed. Since the UB buildings have good internet connection (WiFi), Internet of Things (IoT) was employed to the system to support real time monitoring. So, data of TDS, pH, and water flow can be periodically sent to cloud and displayed to a specific website. The system worked very well and the data can be summarized and used by operator as indicators of performance of the reverse osmosis machine. When water quality and performance decrease, operator must check filters membrane or water pump for further maintenance to support long life use. Although the sensors have been calibrated properly, some measurement errors occur. The measurement error percentages of TDS and pH are 0.62% and 0.94%, respectively. © 2022 IEEE.

关键词： Internet of things

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The Design of VBee Diary Writing Application 9

The Design of VBee Diary Writing Application

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9th International Conference on Education and Technology, ICET 2023

作者： Sidupa, Christiana Nugroho, Hermawan Perdani, Yella Dezas Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Informatics Engineering Study Program Salatiga Indonesia Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Bandung Indonesia

ISBN: (纸本)9798350358292

The development of critical thinking, creativity, and communication abilities is facilitated by the acquisition of writing skills, which are significant for students. Nevertheless, a considerable number of students presently encounter difficulties in locating the impetus and enthusiasm required for engagement in writing endeavors. The focus of the present paper is application design. The VBee application is a web-based application that facilitates the expression of user creativity and fosters a deeper appreciation for the art of writing. The application boasts a highly intuitive interface that effortlessly enables users to document their thoughts and experiences. It offers a plethora of features that not only facilitate writing but also foster self-expression, including customizable emoticons and the option to provide feedback. By designing the application, it could help support vocational school students in improving the quality of skill-focused education, particularly their English creative writing skill in enjoyment. Besides, the teachers are assisted to guide their students with technologically advanced and entertaining learning tools. © 2023 IEEE.

关键词： Students

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Java Bali Grid Mean Time To Failure Prediction using Machine Learning

Java Bali Grid Mean Time To Failure Prediction using Machine...

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Technology, engineering, and Computing Applications (ICTECA), International Conference on

作者： Priyo Adi Sesotyo M.M. Lanny W. Pandjaitan Lukas Professional Engineer Study Program Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Electrical Engineering Dept. Universitas Semarang Semarang Indonesia Electrical Engineering Master Program Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

The role of Mean Time To Failure (MTTF) is critical to maintain cost-efficient in smart grids, as the predictive maintenance means for ensuring their reliability. Java Bali grid is the most important power network in Indonesia, because it holds 75% energy sales and the foundation of the Indonesian government, business and industrial sectors. One method for prediction in the machine learning is the Linear Regression, as part of the Supervised Learning technique. The regression model extracts the grid overload variable from MV distribution system, where connected load (MVA) divided by the number of MV customers. The model constructs the Linear Regression function, where the slope and intercept values found from the correlation between predicted response and actual response. After confronting the function f(x) and the coefficient of determination (R2), the test results for the MTTF prediction values for Java-Bali’s region shows the higher accuracy when the R2 shows highest value.

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An Optimal Framework for SDN Based on Deep Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Smart Home Security System Using Face Recognition Based on IoT- CNN 2

Smart Home Security System Using Face Recognition Based on I...

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2nd International Conference on Information Technology Research and Innovation, ICITRI 2023

作者： Febriantono, M. Aldiki Zuhair, Alvin Khaeruddin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia University of Islam Blitar Electrical Engineering Department Blitar Indonesia University of Muhammadiyah Malang Diploma III Electronic Technology Vocational Study Program Malang Indonesia

ISBN: (纸本)9798350324945

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning Computer Vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning Computer Vision holds tremendous benefits for homeowners. © 2023 IEEE.

关键词： Face recognition

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study of Radiation Pattern Response on Phase-Controlled Ku-Band 8×4 Array Antenna

Study of Radiation Pattern Response on Phase-Controlled Ku-B...

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International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)

作者： Yohanes Galih Adhiyoga Tri Nur Arifin Ganjar Febriyani Pratiwi Erfiana Wahyuningsih Bagus Edy Sukoco Yaya Sulaeman Teguh Praludi Folin Oktafiani Yuyu Wahyu Research Center for Telecommunication National Research and Innovation Agency Bandung Indonesia Electrical Engineering Study Program Universitas Dian Nusantara Jakarta Barat Indonesia

ISBN: (数字)9798350389920

ISBN: (纸本)9798350389937

This paper presents the design, simulation, and parametric study of a phase-controlled Ku-Band $8 \times 4$ array antenna for satellite communication. The single element is a rectangular patch antenna fed directly by a $50-0 \mathrm{hm}$ coaxial feed optimized for operation at 12.5 GHz. In the array configuration, 32 elements are arranged linearly along the x and y axes to achieve a gain of 24 dBi. The proposed study focused on the effect of phase control along the x-axis and y-axis to steer the radiation pattern in azimuth and elevation, respectively. Simulations reveal that increasing the phase difference applied to the elements results in a more significant shift of the main beam direction but also increases the sidelobe level (SLL) and decreases the antenna gain. The study further demonstrates that the main beam direction does not increase linearly beyond a specific phase difference, and grating lobes become apparent when the phase difference exceeds 90 degrees. The number of array elements can be increased to achieve a broader range of main beam steering, and higher bit phase shifters can provide finer phase resolution. The findings of this study offer valuable insights for optimizing phase-controlled beam steering in array antennas, balancing performance trade-offs, and enhancing the flexibility and effectiveness of the beam steering mechanism.

关键词： Phased arrays Satellite antennas Beam steering Azimuth Antenna theory Spaceborne radar Radar antennas Ku-band Microwave antenna arrays Antenna radiation patterns

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Economic and Sensitivity Analyses for an Optimal Hybrid Power Generation for Stand-Alone Power Systems: Case of Klongrua, Phato, Chumphon, Thailand

Economic and Sensitivity Analyses for an Optimal Hybrid Powe...

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2022 International electrical engineering Congress, iEECON 2022

作者： Jeenthanom, Pathumwadee Saelao, Jeerawan Muangjai, Worrajak Thongporn, Jutturit Panlawan, Nattawat Somsak, Teerasak Rajamangala University of Technology Lanna Electrical Engineering Program Faculty of Engineering Chiang Mai Thailand Maejo University Division of Mathematics Faculty of Science Chiangmai Thailand Rajamangala University of Technology Lanna Collage of Integrated of Science and Technology Chiang Mai Thailand

ISBN: (纸本)9781665402064

This paper analyzes a hybrid power system for an independent power system for Baan Khlongrua community, which is a village far from the transmission line system so that the community has electricity available all the time. The designed system consists of solar cells, batteries, inverters and small power turbines. Therefore, this research assesses the economic value and analyzes the system's sensitivity. It is assumed that the electricity demand will increase by 4.25% per year. The analysis data found that in the first year, the cost of energy (COE) was 0.137 /kWh, the second year was 0.132 /kWh, and the third year was 0.127 /kWh. Year 1 has a high COE due to system design being approximately 10% larger than current demand, and in years 4, 5, 6, COE will increase. As a result of the designed system, it will not produce enough electricity to meet the electrical load of the village. Therefore, a diesel generator compensates during the power shortage, causing the CO2 value in the year 4,5,6 to 3,780 kg/yr 2,898 kg/yr 3,265 kg/yr increased. This CO2 value, therefore, affects the COE increase, and COE decreases from 0.137 to 0.127 /kWh. the payback period of the system can be quickly achieved. © 2022 IEEE.

关键词： Sensitivity analysis

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