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Monitoring Stress Level Through EDA by Using Convex Optimization 1

1st International Conference on Electronics, Biomedical engineering, and Health Informatics, ICEBEHI 2020

作者： Fajriaty, Nuzula Dwi Rahma, Osmalina Nur Putri, Yang Sa’ada Kamila Ariyansah Putra, Alfian Pramudita Rahmatillah, Akif Ain, Khusnul Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Biomedical Signals and Systems Research Group Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia

ISBN: (数字)9789813369269

ISBN: (纸本)9789813369252

This study designed an effective system for monitoring stress levels based on Electrodermal Activity (EDA) sensors by knowing the signal patterns and characteristics using convex optimization decomposition. The EDA sensor considered accurate and sensitive for identifying stress by analyzing the skin conductivity (SC) due to the changes in sympathetic nerve activity. However, the SC signal consists of phasic and tonic components, which needed to decompose to analyze stress levels. The SC signals also followed by the white Gaussian noise, which represents the error value. Hence, deconvolution is a crucial stage for the further process because the quality of the measurement depends on this result. This study aims to deconvolve the SC signal using the convex optimization method (cvxEDA). This model is physiology inspired by EDA based on Bayesian statistics, convex mathematical optimization, and sparsity. This research conducted with 18 subjects through three sessions of measurement. The given stimuli arise in each session to increase the level of stress. The results showed that this method could separate and identify SC. The Phasic component shows an increase in the stimulus of each session, as seen from the number of peaks. In contrast, there were no significant differences in the tonic component. This study shows that the phasic component is closely related to changes in sudomotor nerve activity (SMNA) and response to a stressor, which could be useful to classify stress levels in the future study. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convex optimization

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A scenario analysis for community-based sanitation planning in Labuan Bajo, a tourism hub in Indonesia

Socio-Ecological Practice Research

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Socio-Ecological Practice Research 2025年 1-20页

作者： Sofiyah, Evi Siti Sianipar, Imelda Masni Juniaty Rahman, Ari Caesarina, Naila Putri Suhardono, Sapta Lee, Chun-Hung Suryawan, I Wayan Koko Department of Environmental Engineering Faculty of Infrastructure Planning Universitas Pertamina Jakarta Indonesia Department of International Relations Faculty of Social Science and Political Science Universitas Kristen Indonesia Jakarta Indonesia Environmental Sciences Study Program Faculty of Mathematics and Natural Sciences Universitas Sebelas Maret Surakarta Indonesia Department of Natural Resources and Environmental Studies College of Environmental Studies and Oceanography National Dong Hwa University Hualien Taiwan ROC

Rapid urbanization and tourism growth are straining sanitation systems, water resources, and public health in many developing regions. Labuan Bajo, Indonesia, a super-priority tourism destination, faces water shortages and inadequate sanitation infrastructure, increasing environmental and health risks. This study examines community-based sanitation adaptation strategies using an adaptive capacity framework and a choice experiment (CE) method to assess community willingness to participate in sanitation improvements. Three scenarios were tested: (1) community skill improvement, promoting composting septic tank waste and community involvement in sanitation planning; (2) health education platform, integrating septic tank sludge removal services with public health education; and (3) adaptive climate community-based sanitation, a comprehensive approach combining waste management, education, and community engagement to enhance sanitation resilience. Results show that education, government support, and community participation drive successful sanitation adaptation. Among the three scenarios, education-focused and comprehensive approaches had the highest Marginal Willingness to Participate (MWTP) values, reflecting strong community interest in health-focused sanitation solutions. Government policies and financial support were crucial for long-term success. This research provides practical insights for policymakers, urban planners, and development agencies working on climate-resilient sanitation solutions in tourism-driven and water-scarce regions. Future studies should explore how these strategies can be adapted in different settings.

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Ontology-Driven IoT System for Monitoring Hypertension 25

Ontology-Driven IoT System for Monitoring Hypertension

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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： de Souza, Pedro Lopes de Souza, Wanderley Lopes Pires, Luís Ferreira Moreira, João Luiz Rebelo da Silva Rodrigues, Ronitti Juner Ciferri, Ricardo Rodrigues Semantics Cybersecurity & Services Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente P.O. Box 217 Enschede Netherlands Ubiquitous Computing Group Graduate Program in Computer Science Computing Department Federal University of São Carlos P.O. Box 676 São Carlos Brazil

ISBN: (纸本)9789897586484

Hypertension is a noncommunicable disease (NCD) that causes global concern, high costs and a high number of deaths. Internet of Things, Ubiquitous Computing, and Cloud Computing enable the development of systems for remote and real-time monitoring of patients affected with NCDs like hypertension. This paper reports on a system for monitoring hypertension patients that was built by employing these techniques. This system allows the vital signs of a patient (blood pressure, heart rate, body temperature) to be captured via sensors built in a wearable device similar to a wristwatch. These signals are transmitted to the patient's mobile device for processing, and the generated clinical data are sent to the cloud to be properly presented and analysed by the health professionals responsible for the patient. To deal with semantic interoperability issues that arise when multiple different devices and system components must interoperate, a semantic model was conceived for this system in terms of ontologies for diseases and devices. This paper also presents the semantic module that we developed and implemented in the cloud to perform reasoning based on this model, demonstrating the potential benefits of incorporating semantic technologies in our system. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Ontology

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Analysis of user satisfaction to the traditional shipping service at Oliong Port of Bagansiapiapi

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AIP Conference Proceedings 2024年第1期2927卷

作者： Hetty Fadriani Y. S. Herawati Andrew Ghea Mahardika Ika Sartika Budi Nuryono Civil Engineering Study Program Sekolah Tinggi Teknologi Mandala Bandung Indonesia Electrical Engineering Study Program Universitas Kristen Maranatha Bandung Indonesia

Traditional shipping is an important part of national sea transportation potency, that playing main roles to serve inland areas, remote and outer islands in Indonesia. Oliong Port of Bagansiapiapi is the one that provides short-distance traditional shipping services for island-people in Rokan Hilir Regency. The purpose of this study was to assess the user satisfaction to traditional shipping services at the Port Oliong of Bagansiapiapi, in order to arrange future improvement policies. The method of Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) applied to assess the level of satisfaction and importance of each indicators of the traditional shipping service. There are six service indicators involved, i.e. connectivity, intermodality, travel time, travel cost, safety and security. Results from CSI analysis show that the value of user satisfaction about 79% (in the range of Moderate Level of Satisfaction category with CSI Value from 50% to 80%). IPA analysis recommend that the indicators of Travel Costs and Safety which in quadrant-I as the top priority to improve, while safety indicator which in quadrant-IV only need to be maintain its performance.

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Evaluating a New Configuration for Medium-Voltage Drive Systems in a Mining Plant

Evaluating a New Configuration for Medium-Voltage Drive Syst...

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Industrial Applications Society Annual Conference on Petroleum and Chemical Industry

作者： André M. Alzamora Caio Eduardo Silva Marco T. A. Êvo Hélder De Paula Graduate Program in Electrical Engineering Federal University of Uberlândia (UFU) Uberlândia MG Brazil Electrical Engineering Department (DEPEL) Federal University of São João del-Rei (UFSJ) São João del-Rei MG Brazil Faculty of Electrical Engineering (FEELT) Federal University of Uberlândia (UFU) Uberlândia MG Brazil

Large AC motors are ubiquitous in the mining industry, and these often require medium-voltage (MV) converters. Generally, long cables provide the connection between the variable speed drive (VSD) and the motor, which increases problems involving high frequency currents and overvoltages. These undesired phenomena are attenuated by large, heavy and expensive inverter output filters. As an alternative solution to such problems, the authors have proposed, in previous works, the separation of the frequency converter into its rectifier and inverter units, where the rectifier remains in its original location and the inverter is placed beside the motor, thus establishing a DC transmission link through the long cable. Such a configuration naturally (i) mitigates the high-frequency phenomena, (ii) reduces the voltage drop along the cable, and (Hi) can result in substantial copper savings. Until the present moment, the evaluations performed on the proposed topology was aimed at low voltage mining applications, which have shown excellent results. However, since MV drive systems are common in the mining industry, the proposed drive topology should also be analyzed considering this application. In this way, this paper evaluates the copper and energy savings obtained through this alternative drive topology by means of a case study involving three MV motor drive systems situated in a mining plant.

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Improving Candle Direction Classification in Forex Market Using Support Vector Machine with Hyperparameters Tuning 7

Improving Candle Direction Classification in Forex Market Us...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Oetama, Raymond Sunardi Heryadi, Yaya Lukas Suparta, Wayan Computer Science Bina Nusantara University Jakarta Indonesia Binus Graduate Program Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Institut Teknologi Nasional Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned. © 2022 IEEE.

关键词： Support vector machines

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Implementation of Malaria Detection Using MobileNetV2 Pretrained Model for Improved Deep Learning Based Diagnostics

Implementation of Malaria Detection Using MobileNetV2 Pretra...

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International Conference on Computing, engineering, and Design (ICCED)

作者： Rahmat Hidayat Achmad Solichin Adhitia Erfina Sudin Saepudin Muhamad Muslih Mohd Zainuri Saringat Master of Computer Science Budi Luhur University Jakarta Indonesia Information Systems Study Program Nusa Putra University Sukabumi Indonesia Department of Software Engineering Faculty of Computer Science and Information Technology Tun Hussein Onn Malaysia University

ISBN: (数字)9798331529376

ISBN: (纸本)9798331529383

The Plasmodium parasite, which causes malaria, is an acute fever illness that infects people when a female Anopheles mosquito bites them. It is predicted that malaria would claim 619,000 lives in 2021, with 96% of those deaths occurring in the African continent. We can achieve this by using a microscope to examine thick and thin blood smears. The proficiency of a microscope examiner is crucial for doing microscopic examinations. Consider how time-consuming, ineffective, and costly it would be to examine thousands of malaria cases. Consequently, Creating an automated method for detecting malaria parasites is the aim of this study. We employ a MobileNetV2 pretrained model with CNN technology. Because it has been trained on dozens or even millions of data points, this pretrained model is incredibly light but dependable. There are two main benefits of automatic malaria parasite detection: firstly, it can offer a more accurate diagnosis, particularly in locations with limited resources; secondly, it lowers diagnostic expenses. The optimizer utilizes Adam Weight, the criteria uses NLLLoss, and the model is trained using 32 for batch_size. In the fourteenth epoch, we obtained the maximum accuracy score of 96.26% based on the training data. The outcomes of the predictions demonstrate how excellent this score is. EfficienceNet, DenseNet, AlexNet, and other pretrained models are among the alternatives that scientists are advised to try training with.

关键词： Training Adaptation models Accuracy Costs Malaria Microscopy Data visualization Training data Cost function Data models

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Analysis of Six-spoked Asterisk Slot CPW Antenna for Wireless Communication Systems

Analysis of Six-spoked Asterisk Slot CPW Antenna for Wireles...

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International Conference on Wireless and Telematics (ICWT)

作者： Hafizha Silmi Nur Rahkmi Nurul Fahmi Arief Hakim Enjang Akhmad Juanda Azwar Mudzakkir Ridwan Mariya Al Qibtiya Heri Gunawan Dept. of Electrical Eng. Education Universitas Pendidikan Indonesia Bandung Indonesia Dept. of Electrical Engineering UIN Sunan Gunung Djati Bandung Indonesia Indonesian Tadris Study Program UIN Sunan Gunung Djati Bandung Indonesia

Coplanar waveguide (CPW) antennas are widely used in wireless communication systems because they can be easily integrated with microwave circuits. This article describes a method for improving the performance of CPW antennas by incorporating a slot into the patch design. The antenna was fabricated on an FR4 substrate with dimensions of 43 mm x 40 mm and a thickness of 1.6 mm. The patch section of the antenna was modified by incorporating a slot. The size and shape of the slot were adjusted to achieve optimal performance. The most effective modified design was then fabricated and its properties were measured. The fabricated antenna exhibited an operational frequency range of 2.24 GHz to 7.30 GHz. It also had an omnidirectional radiation pattern and a maximum gain of 5.825 dB.

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Salt Hash Password Using MD5 Combination for Dictionary Attack Protection

Salt Hash Password Using MD5 Combination for Dictionary Atta...

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International Conference of Computer and Informatics engineering (IC2IE)

作者： Agung Nugroho Teddy Mantoro Cyber Defense Engineering Study Program Sains and Defense Technology Faculty The Republic of Indonesia Defense University Bogor Indonesia Departement of Computer Science Media-Tech Lab Sampoerna University Jakarta Indonesia

Using MD5 hashing of passwords in web logins is highly vulnerable to dictionary attacks. One online application for cracking hashed passwords using a dictionary attack that is free and easy to use is ***. Even so, the use of hashing passwords using MD5 which has a low level of security is still commonly found to secure web login passwords. This research presents an increase in security through a combination of salt hash passwords when using MD5. The methodology of this study uses a quantitative experimental method to apply hash salt passwords using the MD5 combination. The password cracking test was carried out using the *** online hash cracking application on weak passwords such as “admin” with the addition of a password hash salt using the MD5 combination. The results showed that Salt Password using the MD5 combination could not be cracked by *** using a dictionary attack.

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High Level Learning Approach for High Level Collision Avoidance Using Sensors 1

High Level Learning Approach for High Level Collision Avoida...

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1st IEEE International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022

作者： Naibaho, Lamhot Razauddin Vertivendan, L. Karunakaran, V. Oberoi, Ashish Vishwath, N.C. Ajay Christian University of Indonesia English Language Education Study Program Faculty of Letters and Languages Indonesia Gulf Colleges Saudia Arabia Department of Computer and Information Sciences Saudi Arabia Galgotias University Department of CSE Uttar Pradesh Greater Noida India Faculty of Engineering and Technology Department of CSE Bangalore India RIMT University Department of CSE Godindgarh Mandi India Parul Institute of Engineering and Technology Parul University Aeronautical Department India

ISBN: (纸本)9781665456876

Motion planning for many unmanned aircraft is challenging because they have a larger configuration space than self-driving automobile development (Automated guided vehicles). Additionally, there are more significant uncertainties and disruptions in UAV environments, which makes inter automatic navigation more difficult. In this letter, I proposed a 2 recurrent neural networks (RL) oriented multi-UAV collision avoidance technique by modeling the unpredictability or noise in the environment. Our objective is to create a strategy that can construct a path without clashing with anything using local noisy data. But unlike supervised algorithms, RL lacks a steady training data set with floor labels, thus its collision avoidance strategies often show significant fluctuation and are difficult to reproduce. To solve these issues, we created a two-stage training method for RL-based collision avoidance. We first optimize the policy, and then we utilize a supervised learning methodology with a loss function that encourages the agents to adopt the well-known reciprocity obstacle detection mechanism. In the second step, we use transmission to fine-tune the policy. The complete computer simulation findings demonstrate that this approach can handle noisy local views with erratic sound levels and can design moment & accident paths under inadequate sensing. We review the impact of our policies in a variety of ways. © 2022 IEEE.

关键词： Recurrent neural networks

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