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Biomedical Instrumentation and Technology Conference (IBITeC), International

作者： Arief Purnama Muharram Farhan Hilmi Taufikulhakim Ayu Purwarianti Faculty of Medicine Universitas Indonesia Jakarta Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Master Program of Informatics Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

COVID-19 is an acute respiratory disease that has become a pandemic worldwide. Many studies have been conducted to enhance our understanding of COVID-19. However, the abundance of information obtained from these studies has resulted in information overload. In this study, we purposed a simple COVID-19 Knowledge Graph in Bahasa Indonesia as a way to reconstruct knowledge to combat this information overload. We used Bahasa Indonesia in our study to explore its potential for constructing a Knowledge Graph (KG). The construction of our KG involved manual curation of medical literatures and annotation of entities and relationships by the domain experts. The KG was implemented using Neo4J version 5. We successfully demonstrated our COVID-19 KG, which consists of 240 nodes and 276 relationships with 15 and 14 node and relationship labels, respectively. Accessing the information within the KG is made effortless through the use of Cypher queries in Neo4J. Further research is still needed to develop the KG into a larger and better one. However, our COVID-19 KG can serve as a basis for further development.

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Supervised Learning Models for Early Detection of Albuminuria Risk in Type-2 Diabetes Mellitus Patients 10

Supervised Learning Models for Early Detection of Albuminuri...

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10th International Conference on Advanced Informatics: Concept, Theory and Application, ICAICTA 2023

作者： Muharram, Arief Purnama Tahapary, Dicky Levenus Lestari, Yeni Dwi Sarayar, Randy Dirjayanto, Valerie Josephine School of Electrical Engineering and Informatics Master Program of Informatics Institut Teknologi Bandung Bandung Indonesia Indonesia Medical Education and Research Institute Universitas Indonesia Metabolic Disorder Cardiovascular and Aging Research Center Faculty of Medicine Jakarta Indonesia Universitas Indonesia Faculty of Medicine Cipto Mangunkusumo General Hospital Ophthalmology Department Jakarta Indonesia Universitas Indonesia Faculty of Medicine Jakarta Indonesia

ISBN: (纸本)9798350329919

Diabetes, especially T2DM, continues to be a significant health problem. One of the major concerns associated with diabetes is the development of its complications. Diabetic nephropathy, one of the chronic complication of diabetes, adversely affects the kidneys, leading to kidney damage. Diagnosing diabetic nephropathy involves considering various criteria, one of which is the presence of a pathologically significant quantity of albumin in urine, known as albuminuria. Thus, early prediction of albuminuria in diabetic patients holds the potential for timely preventive measures. This study aimed to develop a supervised learning model to predict the risk of developing albuminuria in T2DM patients. The selected supervised learning algorithms included Naive Bayes, Support Vector Machine (SVM), decision tree, random forest, AdaBoost, XGBoost, and Multi-Layer Perceptron (MLP). Our private dataset, comprising 184 entries of diabetes complications risk factors, was used to train the algorithms. It consisted of 10 attributes as features and 1 attribute as the target (albuminuria). Upon conducting the experiments, the MLP demonstrated superior performance compared to the other algorithms. It achieved accuracy and f1-score values as high as 0.74 and 0.75, respectively, making it suitable for screening purposes in predicting albuminuria in T2DM. Nonetheless, further studies are warranted to enhance the model's performance. © 2023 IEEE.

关键词： Forecasting

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Effect of Laying and Bonding Parameters of High-Voltage Underground Cables on Thermal and electrical Performances by Multiphysics Fem Analysis

SSRN

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SSRN 2023年

作者： Demirol, Yunus Berat Kalenderli, Özcan Istanbul Technical University Graduate School of Electrical Engineering Program ITU Ayazaga Maslak Istanbul34469 Turkey Istanbul Technical University Faculty of Electrical and Electronics Engineering ITU Ayazaga Maslak Istanbul34469 Turkey

In high-voltage underground cable systems, current carrying capacity and power losses vary according to the screen bonding type, the phase sequence, the distance between the cables, and the number of parallel systems. In this study, electrical and thermal analyses of a system consisting of two parallel cables were carried out according to different design parameters, and the performances were evaluated. Trefoil and flat layouts were used in the analyzed systems. In addition, the structure of the single-side and solidly bonded systems was also examined. While carrying out the investigations, the variation of the distance between the cables according to three different parameters was also discussed. In total, 56 different scenarios were created, and the systems' performances were examined. Screen currents, screen voltages, cable temperatures, and power losses were considered while conducting the investigations. In this context, coupled electrical and thermal calculations were performed in the Ansys Electronics Suite finite element software. Additionally, the study utilized the CymCap program to verify the finite element model created, with analytical analyses conducted in accordance with IEC 60287 standards. The significance of these calculations cannot be overstated, as the analysis results demonstrate the direct impact of various design parameters on the system's overall performance. © 2023, The Authors. All rights reserved.

关键词： Finite element method

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Arduino and LabVIEW Based Ping-Pong Ball Position Control using PID Controller

Arduino and LabVIEW Based Ping-Pong Ball Position Control us...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Agus Ramelan Febri Abdul Rohman Meiyanto Eko Sulistyo Feri Adriyanto Nike Sartika Diky Zakaria Dept. of Electrical Engineering Faculty of Engineering Universitas Sebelas Maret Surakarta Indonesia Dept. of Electrical Engineering UIN Sunan Gunung Djati Bandung Bandung Indonesia Mechatronics and Artificial Intelligence Study Program Universitas Pendidikan Indonesia Bandung Indonesia

Industrial development requires accurate and reliable control technology. One of the popular control systems is PID control. This paper discusses the implementation of the PID method for ping-pong ball position control by utilizing the theory of the Coanda effect. The control system was designed using Arduino as the controller and LabVIEW as the control interface. Tests were carried out by combining set point values to determine whether the position control system worked properly or not. The test results show that the PID method combined with LabVIEW can work well with the results of the PID control test at successive heights of 15 cm, 20 cm, 25 cm, 30 cm, and 35 cm obtained rise time (tr) 3.49 seconds, 4.58 seconds, 9.08 sec, 9.92 sec, and 8.84 sec. The average tolerance is 1.5 cm for the upper limit and 1 cm for the lower limit.

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Towards cross-modal causal structure and representation learning 2

Towards cross-modal causal structure and representation lear...

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2nd Machine Learning for Health Symposium, ML4H 2022

作者： Mao, Haiyi Liu, Hongfu Xiaotian Dou, Jason Benos, Panayiotis V. Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh United States Michtom School of Computer Science Brandeis University United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Epidemiology University of Florida United States

Does the SARS-CoV-2 virus cause patients' chest X-Rays ground-glass opacities? Does an IDH-mutation cause differences in patients' MRI images? Conventional causal discovery algorithms, although well developed to uncover the cause-effect relationships on structured data, cannot elucidate causal relations between unstructured images and structured scalar variables due to the complexity of the former. In this paper, we consider causal discovery between images and structured (scalar) variables. Specifically, we derive low dimensional image representations to analyze with structured variables. We propose a two-module amortized variational algorithm named Cross-Modal Variational Causal representation and structure Learning (CMCL). CMCL jointly learns identifiable representations given a set of independent structured variables and causal relations via formulating latent representations and structured variables into a direct acyclic graph. Moreover, we further enforce counterfactual invariance/variance onto representations. We demonstrate that CMCL outperforms other related methods on synthetic datasets and validate causal relations on semi-synthetic datasets by visualization. © 2022 P.N. Argaw, E. Healey & I.S. Kohane.

关键词： Coronavirus

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IoT and Peer-to-peer Signal Notification Methods Reduce the Time Needed to Detect Wildfire Heat Points

IoT and Peer-to-peer Signal Notification Methods Reduce the ...

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International Conference on Green Technology and Sustainable Development (GTSD)

作者： Nattawat Panlawan Teerasak Somsak Jutturit Thongpron Worrajak Muangjai Montri Ngaodet Visut Assanavijit Phiched Thanin Suriyon Sungkham Kosol Oranpiroj Noppom Patcharaprakiti Peeraya Somsak Kan Nakaiam Faculty of Engineering RMUTL Program in Electrical Engineering Chiang Mai Thailand College of Integrated Science and Technology RMUTL Chiang Mai Thailand Research and Development Institute RMUTL Chiang Mai Thailand Faculty of Business Administration and Liberal Arts RMUTL Chiang Mai Thailand

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

The issue of dust and smoke resulting from forest fires in northern Thailand. This is caused by people burning the forest to get forest products. Individuals can start forest fires by intentionally burning the forest to extract forest resources. Deforestation negatively affects the well-being of vulnerable patients and has repercussions on public health. The decrease in tourist numbers impacts the economy. Individuals setting fire to the forest to gather forest resources impact government and public sector connections. The education sector has implemented many strategies to educate and mitigate forest fires. There is a fire suppression system. Remove garbage, leaves, and branches that are flammable. However, forest fires remain a concern. Collaboration among three entities in the community can aid in preventing unauthorized forest fires through communal procedures. From multiple ministries, the local organization department, and the central government Collaborating to safeguard Forest fire suppression and afforestation This study is a component of the forest fire surveillance division. If the forest fire's location is not clearly indicated, participating in combined operations will lead to issues because of the overlap in operational responsibilities. Previously, thermal imaging satellites were utilized for coordinate determination. If the satellite completes two orbits each day and identifies a hot location, it initiates a forest fire. Firefighters cannot reach the area to put out forest fires; thus, they need to enter from a nearby, accessible location. Joining the forest fire prevention volunteer organization is challenging and will require approximately 24 to 25 hours. This study aims to conserve energy by utilizing an loT system that transmits peer-to-peer signals. Individuals are prepared to dismantle this system. The villagers can develop it themselves due to its modest cost of $10. During a forest fire (temperature exceeding 50 degrees Celsius), specific ope

关键词： Meters Heating systems Temperature distribution Wildfires Satellites Government Forestry

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Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using Random Forest, KNN, Decision Tree and Naïve Bayes 7

Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using ...

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7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Pohan, Husni Iskandar Suparta, Wayan Heryadi, Yaya Wibowo, Antoni Lukas Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Dengue Hemorrhagic Fever is an acute viral infectious disease caused by the dengue virus. Transmitted through the bite of Aedes Mosquitoes and divided into 4 severity. Severity 1 and 2 are characterized by a decrease in platelet levels below normal and there is a change in hemoconcentration, while Severity 3 and 4 are included in Dengue Shock Syndrome (DSS). The purpose of the study was to classify the severity of dengue, based on age, gender, platelets, body temperature, bleeding, and also doctor's recommendation. The advancement of information technology is the reason for the development of medical science, especially with artificial intelligence. Abundant medical data becomes a source that can be processed in improving the quality of medical information. The method chosen is Random Forest, kNN, Decision Tree and Naïve Bayes. The dataset used is the medical records of all DHF patients for 30 months in the period Jan 2019 to June 2021, at the Nadhifa Al Ghiffari Clinic in Bojongsoang District, Bandung Regency. © 2022 IEEE.

关键词： Decision trees

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Smart Dome 4.0: Low-Cost, Independent, Automated Energy System for Agricultural Purposes enabled by Machine Learning 2

Smart Dome 4.0: Low-Cost, Independent, Automated Energy Syst...

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2021 2nd International Symposium on Automation, Information and Computing, ISAIC 2021

作者： Budiman, Arief S Gunawan, Fergyanto Djuana, Endang Pardamean, Bens Romeli, Sugiarto Putri, Dianing Nn Aji, Daisman Pb Rahardjo, Kuat Stevanus Ilham Wibowo, M. Daffa, Nadiev Owen, Raymond Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia PT. Impack Pratama Industri Tbk Jakarta Indonesia Mechanical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

Many economically essential crops in Indonesia (such as coffee, tea, chocolate, or copra) require storage or drying under certain environmental conditions, especially temperature and humidity. The solar dryer dome, typically used for agricultural purposes in Indonesia, produces a sufficient amount of heat to increase the evaporation rate inside the dome and reduce the moisture content of the commodity. A hybrid solar dryer accompanied by a photovoltaic panel, fan, and ventilation system is generally suitable. The system can provide an optimum environment with minimum control. However, as the outdoor temperature and humidity change dramatically, such as at night time, more control is required. Based on Industry 4.0 technologies, we have developed a new kind of hybrid solar dryer that provides an optimum environment 24/7. The system, called Smart Dome 4.0, is an intelligent, low-cost, self-sufficient drying and storage system to support Indonesia Agriculture 4.0. The system has a local power generation unit to self-sustain the required energy and operate without connecting to the electricity grid. The system utilizes a machine-learning algorithm to predict the environmental condition and optimally uses self-generated electric power. The developed Smart Dome 4.0 technology is critical to producing a sustainable solar dome under drastic environmental dynamics. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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Particle swarm optimization with local search for height-map surface reconstruction from point clouds in reverse engineering

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Neural Computing and Applications 2024年 1-20页

作者： Gálvez, Akemi Fister, Iztok Deb, Suash Fister, Iztok Iglesias, Andrés Dept. of Applied Mathematics and Computational Sciences E.T.S.I. Caminos Canales y Puertos University of Cantabria Avda. de los Castros s/n Santander39005 Spain Faculty of Pharmaceutical Sciences Toho University 2-2-1 Miyama Funabashi274-8510 Japan Faculty of Electrical Engineering and Computer Science University of Maribor Koroska cesta 34 Maribor2000 Slovenia IT & Educational Consultant Ranchi India Distinguished Professorial Associate Decision Sciences and Modeling Program Victoria University Melbourne Australia

Surface reconstruction is a classical process in industrial engineering and manufacturing, particularly in reverse engineering, where the goal is to obtain a digital model from a physical object. For that purpose, the real object is typically scanned or digitized and the resulting point cloud is then fitted to mathematical surfaces through numerical optimization. The choice of the approximating functions is crucial for the accuracy of the process. Real-world objects such as manufactured workpieces often require complex nonlinear approximating functions, which are not well suited for standard numerical methods. In a previous paper presented at the ISMSI 2023 conference, we addressed this issue by using manually selected approximation functions via optimization through the cuckoo search algorithm with Lévy flights. Building upon that work, this paper presents an enhanced and extended method for surface reconstruction by using height-map surfaces obtained through a combination of exponential, polynomial and logarithmic functions. A feasible approach for this goal is to consider continuous bivariate distribution functions, which ensures consistent models along with good mathematical properties for the output shapes, such as smoothness and integrability. However, this approach leads to a difficult multivariate, constrained, multimodal continuous nonlinear optimization problem. To tackle this issue, we apply particle swarm optimization, a popular swarm intelligence technique for continuous optimization. The method is hybridized with a local search procedure for further improvement of the solutions and applied to a benchmark of 15 illustrative examples of point clouds fitted to different surface models. The performance of the method is analyzed through several computational experiments. The numerical and graphical results show that the method is able to recover the shape of the point clouds accurately and automatically. Furthermore, our approach outperforms other alternati

关键词： Particle swarm optimization (PSO)

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Automatic Transfer Function Improvement based on Genetic Algorithm 7

Automatic Transfer Function Improvement based on Genetic Alg...

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7th International Conference on engineering, Applied Sciences and Technology, ICEAST 2021

作者： Paenoi, Nattapong Sitjongsataporn, Suchada Mahanakorn Inst. of Innov. Faculty of Engineering and Technology Mahanakorn University of Technology Electrical Engineering Program Bangkok Thailand Mahanakorn Inst. of Innov. Faculty of Engineering and Technology Mahanakorn University of Technology Dept. of Electronic Engineering Bangkok Thailand

ISBN: (纸本)9781665441223

This paper presents the automatic transfer function improvement based on the genetic algorithm for searching the optimal transfer function. A traditional genetic algorithm is modified to perform the searching process. The proposed chromosome design is presented in the form of 15-bit supported the resistance and inductance. Transfer function is used to design and control the systems. The optimal fitness function is used for the objective function of system to optimize the transfer function. Experiment results show that the second order of automatic transfer function performed by the genetic algorithm can achieve more accuracy than the traditional first order transfer function process. By the process improvement using the genetic algorithm, the time is used for searching transfer function with the chromosome design under the optimal fitness function by the genetic algorithm is approximately 13.35 seconds. © 2021 IEEE.

关键词： Genetic algorithms

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