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2nd International Conference on Innovative and Creative Information Technology, ICITech 2021

作者： Siagian, Pandapotan Fernando, Erick Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781728197463

Good air quality is very important in human health. However, air pollution has been polluted everywhere, whether in the house, in cities. This is caused by a growing industry that produces air pollution. Room air pollution and various cities will contribute to air pollution, which will cause problems for human health. This work measures the carbon monoxide level using the MQ-7 sensor and measures the air's carbon dioxide level with the CCS811 sensor and MH-Z19 sensor. All three sensors are connected to the NodeMCU ESPS266, and we call it a NodeMCU module. Tests are carried out in three rooms in the house, and then three NodeMCU modules are used so that the three modules will send data alternately. Raspberry Pi3 (RPi3) functions as a server that collects data and acquires information data from sensors. Data from the CCS811 (TCOV) sensor, MH-Z19 (co2), will be processed first with fuzzy logic rules to make decisions about CO2, which are right, moderate, nasty conditions. The process is carried out on the Raspberry Pi 3 server with MQTT using publication, customer, fuzzy logic, and broker services. The value of the sensor's measurement results can be accessed via a smartphone and provides good air control values. © 2021 IEEE.

关键词： Air quality

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Biomedical Image Quality Improvement with Spatial Domains 2

Biomedical Image Quality Improvement with Spatial Domains

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2nd International Conference on Innovative and Creative Information Technology, ICITech 2021

作者： Fernando, Erick Siagian, Pandapotan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia

ISBN: (纸本)9781728197463

Digital image processing aims to improve the quality of an original image so that it can display an image that is relatively better than the original image, so as to obtain the detailed information needed for an analysis need. Quality degradation Biomedical images in computerization usually experience changes in brightness, blur, and contrast stretching. Because of the deterioration in the image quality, doctors and patients cannot obtain the information needed for analysis, therefore the need for biomedical image processing techniques with spatial domain methods to improve the quality and details of information in the image so that it helps doctors in diagnosing. Data analysis is biomedical images like X-ray images, CT-Scan (Computer Tomographic Scan) images, and USG (Ultrasound Graphic) images. A focused study on improving image quality can be done with digital spatial domain image processing techniques. Digital domain image processing is digital image processing based on the manipulation of pixel values in the image directly, in the form of point processing and mask processing. Process testing for each image for Blur level is CT-scan images with a value of 0.98436, ultrasound images with a value of 0.9875, X-ray images with a value of 0.9836. This value is blur level value get near to 1 which means the image becomes clearer. The analysis results prove that the spatial domain method can clarify the object image in this study. The biomedical image quality processing model is proven to be able to improve the quality of the image that is declining due to the digitization process and assist the user in analyzing the biomedical image. © 2021 IEEE.

关键词： Image quality

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Long Short Term Memory Networks for Stroke Activity Recognition base on Smartphone 5

Long Short Term Memory Networks for Stroke Activity Recognit...

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5th IEEE International Conference on Information Technology, Information systems and Electrical engineering, ICITISEE 2021

作者： Siagian, Pandapotan Fernando, Erick Del Institute Of Technology Faculty Of Informatics And Electrical Engineering Computer Engineering Study Program North Sumatera 22381 Indonesia Bina Nusantara University School Of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781665401968

Aims this study to analyze rehabilitation exercises using sensor data embedded in smartphones is widely used to recognize human activities regularly to gain a better understanding of human behavior. However, it is rarely used to measure accelerators of patient movement in hospital wards. This paper proposes an optimized neural network-based feature extraction approach based on the Long Short Term Memory technique to recognize human activity using data from a tri-axial accelerometer. The activity to be measured is the Range of Motion for patient rehabilitation, and rehabilitation exercises are one of the most important steps for recovery. The results of the softmax regression trained on the dataset set have 1, 076, 105 records and 12 class attributes (class distribution). The experimental results on the SAR dataset show that our Long Short Term Memory-based approach is practical and successful, with an accuracy of 89.74%. © 2021 IEEE.

关键词： Smartphones

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Optimization strategies for Micro-grid energy management and scheduling systems by Sine cosine Algorithm 3

Optimization strategies for Micro-grid energy management and...

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3rd International Conference on Electrical, Computer and Communication engineering, ECCE 2023

作者： Islam, Mohammad Ariful Zardar, Md. Abu Shafiullah, Md Nadia, Awatif Institute of Energy Technology Chittagong University of Engineering and Technology Chattogram Bangladesh Bangladesh University of Business and Technology Department of Eee Dhaka Bangladesh Interdisciplinary Research Center for Renewable Energy & Power Systems King Fahad University of Petroleum and Minerals Saudi Arabia Military Institute of Science & Technology Electrical and Electronics and Communication Engineer Dhaka Bangladesh

ISBN: (纸本)9798350345360

Energy is an essential factor for power generation, where a community microgrid seeks to integrate renewable energy sources such as solar, wind, tidal, hydropower, and bioenergy into a distribution network along with an energy storage system. This is not only for the security of national growth, but also to minimize electricity costs and availability. The source of renewable energy has no predicted schedule for synchronization of power generation, supporting battery as energy storage for emergency supply or backup. In this paper, predictive scheduling of battery energy considering the cost of degradation due to charging and discharging cycles is proposed. According to the economy, day ahead planning has required a technique for solving the cost efficiency. In this paper, planned has developed by sine-cosine algorithm, which belongs to mathematical trigonometric base populations sector meta-heuristic technique. The sine-cosine algorithm works on the principle of trigonometric mathematical solution to search a target location within an area evaluation. © 2023 IEEE.

关键词： Heuristic algorithms

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A Comprehensive Survey of Time Series Forecasting: Architectural Diversity and Open Challenges

arXiv

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arXiv 2024年

作者： Kim, Jongseon Kim, Hyungjoon Kim, HyunGi Lee, Dongjun Yoon, Sungroh Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of R&D Department LG Chem R&D Department Samsung SDI

Time series forecasting is a critical task that provides key information for decision-making across various fields, such as economic planning, supply chain management, and medical diagnosis. After the use of traditional statistical methodologies and machine learning in the past, various fundamental deep learning architectures such as MLPs, CNNs, RNNs, and GNNs have been developed and applied to solve time series forecasting problems. However, the structural limitations caused by the inductive biases of each deep learning architecture constrained their performance. Transformer models, which excel at handling long-term dependencies, have become significant architectural components for time series forecasting. However, recent research has shown that alternatives such as simple linear layers can outperform Transformers. These findings have opened up new possibilities for using diverse architectures. In this context of exploration into various models, the architectural modeling of time series forecasting has now entered a renaissance. This survey not only provides a historical context for time series forecasting but also offers comprehensive and timely analysis of the movement toward architectural diversification. By comparing and re-examining various deep learning models, we uncover new perspectives and presents the latest trends in time series forecasting, including the emergence of hybrid models, diffusion models, Mamba models, and foundation models. By focusing on the inherent characteristics of time series data, we also address open challenges that have gained attention in time series forecasting, such as channel dependency, distribution shift, causality, and feature extraction. This survey explores vital elements that can enhance forecasting performance through diverse approaches. These contributions lead to lowering the entry barriers for newcomers to the field of time series forecasting, while also offering seasoned researchers broad perspectives, new opportuniti

关键词： Supply chain management

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Factors Affecting Interior Acceleration Sound Preference for Electric Vehicles: A Path Analysis

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2022年第1期66卷 1902 - 1907页

作者： May Jorella Lazaro Sungho Kim Adriance Wilfred Anggang Minsik Choi Myung Hwan Yun 1Interdisciplinary Program in Cognitive Science Seoul National University Seoul Korea Department of Industrial Engineering Seoul National University Seoul Korea

Vehicle sound design is gaining attention in the automotive industry, especially for Electric Vehicles (EV). For EVs, acceleration sound is critical for both user experience (UX) and safety. Despite the abundance of UX-related studies investigating the external presentation of acceleration sound for EVs, internal presentation of acceleration sound seems to be overlooked. Thus, further understanding on what influences the user preferences for internal EV sound is essential for better EV sound design. This study aims to explore and develop a simple theoretical path model to help understand the relationship between pragmatic quality, hedonic quality, novelty, and user preferences for EV internal acceleration sounds. Thirty-two participants evaluated twenty-seven EV acceleration sound samples using a 12-item semantic differential scale with bipolar adjective pairs that describe the measured variables in a controlled experimental setting. The relationship between the modeled variables was analyzed using bias-corrected factor score path analysis (BCFSPA). Results showed that the modified model yielded good model fit indices and partially confirmed the initial hypotheses. It was found that pragmatic and hedonic quality had a positive relationship with user preference, whereas, novelty had a negative relationship with hedonic quality and user preference for EV sounds. This study contributes to the understanding of factors that affects user preference for EV sound and provides initial accounts to different approaches and methods for model testing.

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Optimal control of a three-stages supply chain model with shortages 19

Optimal control of a three-stages supply chain model with sh...

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19th IEEE International Multi-Conference on systems, Signals and Devices, SSD 2022

作者： Saif, Abdul-Wahid A. Khaldi, Mustapha K. Ferik, Sami El Baubaid, Ahmad El-Alwani, Jumah Control and Instrumentaion Engineering King Fahd University of Petroleum & Minaralsls Dhahran31261 Saudi Arabia Industrial and Systems Engineering King Fahd University of Petroleum & Minaralsls Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics Saudi Arabia Al Faiha'a University Department of Xxx Jubail Saudi Arabia

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

This paper considers an optimal control of a three-stage supply chain model that consists of a manufacturer, a vendor and a retailer. The model is developed under a continuous-time review policy where the deterioration rate is fixed, shortages are allowed and the demand is assumed to be a linear function of price. Optimal control theory for non-smooth dynamic systems is applied in order to maximize the supply chain profit by optimizing both of the production rate and the dynamic price. To illustrate the result of the proposed model, a numerical example is presented. © 2022 IEEE.

关键词： Deterioration

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Risk Assessment and Mitigation for Business Sustainability in Coal Industry

Risk Assessment and Mitigation for Business Sustainability i...

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Technology & engineering Management Conference - Asia Pacific (TEMSCON-ASPAC), IEEE

作者： F R. Fidry I. Vanany J D T. Purnomo Interdisciplinary School of Management and Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Industrial and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Statistics Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798331515881

ISBN: (纸本)9798331515898

The large impact on global warming of steam power plants may trigger a variety of risk events that could disrupt the business sustainability of coal industries. Research literature still lacks investigations that assess risk events and determine mitigation programs to tackle critical risk events. The purpose of this study was to determine risk events, assess risk events, and determine mitigation programs. The research activities of this study consisted of reviewing related literature, interviewing three managers in three companies, and slightly modifying the House of Risk model. The results show that the most important risk events are: low coal reserves, frequent changes in governmental policies, and others. The outcomes of this research may help coal industry practitioners in Indonesia to understand risk events that could affect the business sustainability of their companies in the future. Also, the Indonesian government can use the results of this research to provide policies that support business sustainability.

关键词： Coal industry Uncertainty Prevention and mitigation Supply chains Companies Coal Coal mining Sustainable development Business Systematic literature review

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DOSE: Drum One-Shot Extraction from Music Mixture

DOSE: Drum One-Shot Extraction from Music Mixture

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Suntae Hwang Seonghyeon Kang Kyungsu Kim Semin Ahn Kyogu Lee Department of Intelligence and Information Music and Audio Research Group (MARG) Seoul National University Department of Mechanical Engineering Seoul National University Interdisciplinary Program in Artificial Intelligence Seoul National University Artificial Intelligence Institute Seoul National University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Drum one-shot samples are crucial for music production, particularly in sound design and electronic music. This paper introduces Drum One-Shot Extraction, a task in which the goal is to extract drum one-shots that are present in the music mixture. To facilitate this, we propose the Random Mixture One-shot Dataset (RMOD), comprising large-scale, randomly arranged music mixtures paired with corresponding drum one-shot samples. Our proposed model, Drum One-Shot Extractor (DOSE), leverages neural audio codec language models for end-to-end extraction, bypassing traditional source separation steps. Additionally, we introduce a novel onset loss, designed to encourage accurate prediction of the initial transient of drum one-shots, which is essential for capturing timbral characteristics. We compare this approach against a source separation-based extraction method as a baseline. The results, evaluated using Fréchet Audio Distance (FAD) and Multi-Scale Spectral loss (MSS), demonstrate that DOSE, enhanced with onset loss, outperforms the baseline, providing more accurate and higher-quality drum one-shots from music mixtures. The code, model checkpoint, and audio examples are available at https://***/HSUNEH/DOSE

关键词： Training Measurement Accuracy Source separation Instruments Production Data models Electronic music Transient analysis Speech processing

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A Study of the Ecological Dynamics of Batumi, on the Black Sea Coast, Analyzing Environmental Factors and Their Impact

A Study of the Ecological Dynamics of Batumi, on the Black S...

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International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Lily Petriashvili Irine Khomeriki Mzia Kiknadze Tamar Lominadze Nona Otkhozoria Dept. of Program Engineering Georgian Technical University Tbilisi Georgia Dept. of Interdisciplinary Informatics Georgian Technical University Tbilisi Georgia Dept. of Computer Engineering Georgian Technical University Tbilisi Georgia Dept. of Information Systems Georgian Technical University Tbilisi Georgia Dept. of Microprocessor and Measurement Systems Georgian Technical University Tbilisi Georgia

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

This paper studies the complex ecological dynamics of Batumi on the Black Sea coast, through adetailed analysis of environmental factors and their impact. We use Business Intelligence (BI) methods to explore the complex interactions between natural and human impacts on the local ecosystems. By using data-focused approaches, including statistical analysis and predictive modeling, we aim to distinguish patterns and trends in ecological dynamics. This study aspires to make clear the complex relationships between environmental factors such as climate change, pollution levels, habitat degradation, and biodiversity loss, and their impacts on the coastal ecosystem of Batumi. Through this study, we aim to provide valuable information on sustainable management practices and conservation measures to protect the ecological integrity of this important coastal region.

关键词： Sea coast Pollution Statistical analysis Ecosystems Habitats Sea measurements Predictive models

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