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Main Melody Configuration and Chord Algorithm for Relaxing Music Generation

Intelligent Automation & Soft Computing 2023年第1期35卷 661-673页

作者： Chih-Fang Huang Ai-Hsien Fan Jin-Huang Huang Hsing-Cheng Huang Department of Health and Marketing Kainan UniversityTaoyuanTaiwanChina Master Program at School of Healthcare Management Kainan UniversityTaoyuanTaiwanChina Ph.D.Program of Mechanical and Aeronautical Engineering Feng Chia UniversityTaichungTaiwanChina

This study applies the diatonic chord in music theory,utilization rate,and the close relationship between the main chord system,the dominant chord system,and the subordinate chord *** the perspective of music theory,the computer can automatically and quickly analyze the music,and establish a set of algorithms for configuring the chord accompaniment for the main melody,called the symmetrical circle offifths algorithm,SCFA(Symmetrical Circle of Fifths Algorithm).SCFA can immediately confirm the key,perform harmony analysis,configure chord accompaniment for the main melody,and effectively and correctly complete any given melody or *** can also quickly analyze and correctly configure the chord accompaniment for any MIDI(Musical Instrument Digital Interface)music,enriching the musicality of the *** can also allow scorers or computer music creators to quickly deconstruct the harmony configuration of the *** the measurement of bio-feedback sensor HRV(Heart Rate Variability),it can achieve a relaxing music healing effect.

关键词： Symmetrical circle of fths algorithm SCFA bio-feedback sensor HRV heart rate variability relaxing music healing effect

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A Soft System Approach for Smart Agriculture: The Use of Digital Marketing in Organic Farm Business 11

A Soft System Approach for Smart Agriculture: The Use of Dig...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Sanny, Lim Heriyati, Pantri Pratiwi, Chairani Putri Lo, Diana Aguzman, Glory Prasetyaningtyas, Sekar Wulan Binus Business School Master-Program Bina Nusantara University Management Department Jakarta Indonesia Bina Nusantara University Department of Management Research in Management Jakarta Indonesia Bina Nusantara University Binus Entrepreneurship Center Management Department Jakarta Indonesia Bina Nusantara University Food Technology Department Faculty of Engineering Jakarta Indonesia Binus Business School Master-Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350389654

One of the main problems in the organic farm industry is the marketing channel to find its customers. This problem might lead to a loss of possibility of gaining economic value from them. Implementation of digital marketing technologies could prevent economic value loss since digitalization utilizes tools to create strategies to reach its customers. However, the digital marketing application in organic farm has obstacles and a lack of discussion in the literature, particularly in the case of Indonesia. This research develops a conceptual model of the application for digital marketing in an organic farming through the soft systems methodology approach. The results shed light on the ongoing literature by identifying the overall system and relevant components. The lack of engagement between producers and consumers, which reduces consumers' desire to buy organic foods, is one of the other difficulties that this study also brings to light. It is advised that producers improve contact with their stakeholders and customers to better understand their requirements and desires to implement digitalization in this business. © 2024 IEEE.

关键词： Digital Marketing Internet Technologies Organic Farming Smart Farming Soft System Methodology

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The Banking Industry is Undergoing a Digital Transformation as Part of Industrial 4.0 10

The Banking Industry is Undergoing a Digital Transformation ...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Sardjono, Wahyu Pranata, Dewi Sagita Ramdhana, Aditya Agung Dwi BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Mathematical & Engineering Sciences King's College London Cyber Security Studi Program Faculty of Natural Department of Informatics West Minster Strands WC2R 2LS United Kingdom University of Airlangga Master of Management Faculty of Economics and Business Surabaya60286 Indonesia

ISBN: (纸本)9798350363104

In the current day, digital transformation is imperative;both customer demand and market competitiveness are mostly driving that trend. The fourth industrial revolution has also affected the financial sector. One difficulty that has to be addressed is the desire from customers for quick and useful services. Traditional procedures need to be replaced with digital ones. Furthermore, banking organizations will have a competitive edge in the current market if they are successful in this digital transformation process. Successful transformation, however, does not happen by accident;in fact, the likelihood of completing this change is seen to be very low, necessitating rigorous planning for a company that is ready for the future. There are several components to the preparation in question, both internal and external. In this situation, the company's ability to combine and rearrange its resources quickly is essential for adapting to the ever-changing business environment. © 2024 IEEE.

关键词： Commerce

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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Distributed Flexible Job Shop Scheduling through Deploying Fog and Edge Computing in Smart Factories Using Dual Deep Q Networks

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Mobile Networks and Applications 2024年第3期29卷 886-904页

作者： Lin, Chun-Cheng Peng, Yi-Chun Chen, Zhen-Yin Annie Fan, Yu-Hong Chin, Hui-Hsin Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program of Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan Department of Information Technology Overseas Chinese University Taichung407 Taiwan

Flexible job shop scheduling (FJSP) has garnered enormous attention within the realm of smart manufacturing, where, beyond job sequencing, the selection of machines holds considerable importance. As smart factories progress with the Internet of things (IoT) and cyber-physical systems (CPS), scheduling methodologies are advancing towards intelligent decentralization. However, with the expansion of factories, conventional cloud computing struggles to manage the substantial influx of data. To tackle this issue, this work incorporates a fog computing and edge computing framework into the distributed FJSP workstations. In this framework, the workstations each of which consists of multiple machines are categorized based on the different nature of the accommodated machines, and operate independently to reduce unnecessary information transmission, in which each machine is equipped with edge computing capacity. The fusion of fog computing and edge computing allows for the offloading of computational tasks from cloud computing, effectively reducing latency. While previous solutions for FJSP have predominantly relied on linear programming or metaheuristic algorithms, this work proposed a novel distributed approach based on a dual deep Q networks (dual DQN) architecture, integrating deep learning (DL) with reinforcement learning (RL). Within the cloud center, the initial neural network determines the machine selection rules for fog computing, while the secondary neural network decides the job dispatching rules for edge computing devices. Edge computing devices execute the schedule and provide feedback to the cloud, which refines the results through an iterative training process, so that to minimize the makespan. The experimental findings indicate that employing dual DQNs outperforms the methods of utilizing only one single machine selection rule. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Reinforcement learning

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Relationship between drought and soil erosion based on the normalized differential water index(NDWI)and revised universal soil loss equation(RUSLE)model

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Regional Sustainability 2024年第4期5卷 133-144页

作者： Muhammad RENDANA Wan Mohd Razi IDRIS Febrinasti ALIA Supli Effendi RAHIM Muhammad YAMIN Muhammad IZZUDIN Department of Chemical Engineering Faculty of EngineeringUniversitas SriwijayaIndralaya30662Indonesia Master Program of Environmental Management Graduate SchoolUniversitas SriwijayaPalembang30139Indonesia Department of Earth Sciences and Environment Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaBangi43600Malaysia Department of Civil Engineering Faculty of EngineeringUniversitas SriwijayaIndralaya30662Indonesia Master Program of Agricultural Sciences Graduate Study ProgramUniversitas Muhammadiyah PalembangPalembang30263Indonesia Department of Agribusiness Faculty of AgricultureUniversitas SriwijayaIndralaya30662Indonesia Department of Sociology Faculty of Social and Political SciencesUniversitas SriwijayaIndralaya30662Indonesia

The Langat River Basin in Malaysia is vulnerable to soil erosion risks because of its exposure to intensive land use activities and its topography,which primarily consists of steep slopes and mountainous ***,climate change frequently exposes this basin to drought,which negatively affects soil and water ***,recent studies have rarely shown how soil reacts to drought,such as soil ***,the purpose of this study is to evaluate the relationship between drought and soil erosion in the Langat River *** analyzed drought indices using Landsat 8 satellite images in November 2021,and created the normalized differential water index(NDWI)via Landsat 8 data to produce a drought *** used the revised universal soil loss equation(RUSLE)model to predict soil *** verified an association between the NDWI and soil erosion data using a correlation *** results revealed that the southern and northern regions of the study area experienced drought *** predicted an average annual soil erosion of approximately 58.11 t/(hm^(2)·a).Analysis of the association between the NDWI and soil erosion revealed a strong positive correlation,with a Pearson correlation coefficient of *** assumed that the slope length and steepness factor was the primary contributor to soil erosion in the study *** a result,these findings can help authorities plan effective measures to reduce the impacts of drought and soil erosion in the future.

关键词： Drought Soil erosion Normalized differential water index(NDWI) Revised universal soil loss equation(RUSLE) Langat River Basin

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Current advances in bioethanol synthesis from lignocellulosic biomass: sustainable methods, technological developments, and challenges

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Journal of Umm Al-Qura University for Applied Sciences 2025年 1-18页

作者： Novia, Novia Melwita, Elda Jannah, Asyeni Miftahul Selpiana, Selpiana Yandriani, Yandriani Afrah, Bazlina Dawami Rendana, Muhammad Department of Chemical Engineering Faculty of Engineering Universitas Sriwijaya Jl. Raya Palembang-Prabumulih KM 32 Inderalaya Sumatera Selatan Ogan Ilir 30662 Indonesia Master Program of Environmental Management Graduate School Universitas Sriwijaya Jl. Padang Selasa 524 Bukit Besar Sumatera Selatan Palembang 30139 Indonesia Doctoral Program Faculty of Engineering Universitas Sriwijaya South Sumatra Palembang 30139 Indonesia

Bioethanol production from lignocellulosic biomass has become an economical and environmentally friendly substitute to current petroleum-based fuels. This is due to its ability to decrease carbon dioxide emissions and make use of plentiful natural resources. Current advances in this area concentrate on improving the effectiveness and expandability of the conversion procedures by using inventive pretreatment approaches, enhanced enzyme compositions, and refined fermentation technologies. Consolidated bioprocessing (CBP) and utilizing genetically modified microbes have expedited the decomposition of intricate biomass complexes and enhanced overall productivity. Furthermore, process intensification developments, such as the adoption of hybrid reactors and continuous production systems, have considerably decreased production expenses and energy usage. Nevertheless, there are still obstacles to overcome, including the raw materials inconsistency, the demand for efficient recovery and purifying techniques, and the financial viability of extensive processes. This study examines the latest developments in bioethanol production from lignocellulosic biomass. It focuses on ecological approaches, technical advancements, and the main obstacles that need to be overcome to exploit its promise as a biofuel fully. This review primarily focused on outcomes documented in the last five years from 2019 to 2024. The first segment of this work focuses on the second-generation bioethanol production process, which includes: the properties and composition of lignocellulosic biomass, pretreatment, enzymatic saccharification, and fermentation. The subsequent portion of this paper examines a techno-economic analysis, the obstacles and the prospective technology outlook. It finishes by discussing findings from research fields that haven't been investigated yet, besides the obstacles faced in bioethanol manufacturing methods. © The Author(s) 2025.

关键词： Bioethanol Enzymatic hydrolysis Fermentation Lignocellulosic biomass Pretreatment

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Creating Mathematical Models to Help Formulate Company Strategies for Knowledge management System Implementation 9

Creating Mathematical Models to Help Formulate Company Strat...

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9th International Conference on Information management and Technology, ICIMTech 2024

作者： Sardjono, Wahyu Perdana, Widhilaga Gia Pranata, Dewi Sagita BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jakarta13220 Indonesia King's College London Cyber Security Studi Program Faculty of Natural Mathematical & Engineering Sciences Department of Informatics Strands West MinsterWC2R 2LS United Kingdom

ISBN: (纸本)9798350390025

This research aims to build a mathematical model to formulate the problems of implementing knowledge management systems in companies that often face obstacles in achieving the desired objectives and goals. With increasing competition in the business sector, organizations or organizations realize the importance of utilizing the knowledge assets that reside in each individual and organization. If this knowledge can be managed optimally, it can become a competitive advantage for the company due to the emergence of innovative ideas by the concepts of knowledge management theory. By implementing optimal knowledge management (KM), companies can design innovative solutions to improve business operations and increase overall revenue. The factor analysis method will be used to find the determining factors for the success of the implementation of knowledge management systems (KMS) and the regression analysis method will also be used to form a mathematical model of several new factors which are formed as independent variables with the current level of community understanding of KMS as the dependent variable. The research results provide insight into strategies to improve success factors to successfully facilitate KMS implementation. This study contributes to existing knowledge management by providing insight into dynamics that go beyond the technical aspects of KMS, ultimately developing strategies for more effective and efficient utilization of knowledge and organizational growth and supporting competitive advantage for companies. © 2024 IEEE.

关键词： Knowledge organization system (KOS)

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Evaluating AI-Induced Anxiety and Technical Blindness in Healthcare Professionals 3

Evaluating AI-Induced Anxiety and Technical Blindness in Hea...

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3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Christian, Michael Pardede, Ratlan Gularso, Kurnadi Wibowo, Suryo Muzammil, Oktafalia Marisa Sunarno University of Bunda Mulia Dept. of Management Jakarta Indonesia University of Bunda Mulia Master of Management Jakarta Indonesia Krida Wacana Christian University Dept. of Medical Profession Study Program Jakarta Indonesia Bina Nusantara University Dept. of Business Management School Dept. of Business Undergraduate Program Bekasi Indonesia University of Tama Jagakarsa Dept. of Mechanical Engineering Jakarta Indonesia

ISBN: (纸本)9798350367492

The widespread implementation of artificial intelligence (AI) in various industries, including healthcare, provides significant benefits but raises concerns. Notably, apprehensions about AI generating issues, experiencing malfunctions, and hindering work extend to fears of replacing medical professional positions. This research aims to quantitatively assess the impact of anxiety forms, specifically social, technical blindness and AI configuration, on job replacement anxiety among medical doctors. A pre-test approach was employed to gather data from 38 doctors in Jakarta who regularly interact with AI in their daily work. The study used PLS-SEM structural modelling with SmartPLS 3.0 as the analysis tool. Findings indicate that both social and technical blindness and AI configuration significantly influence job replacement anxiety. Additionally, the study reveals that elements within the AI configuration interact with social-technical blindness, and the AI setup effectively mitigates its impact on job replacement anxiety. These anxieties notably affect medical professionals' fears of being replaced in their current roles. Previous research shows that anxiety about AI among healthcare personnel is persistent. However, this worry can be reduced or eliminated through continuous awareness, education, and understanding of AI's purpose and limitations. This study aims to provide medical practitioners with a comprehensive understanding of AI constraints and the aspects requiring direct doctor involvement. © 2024 IEEE.

关键词： Artificial intelligence

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Identification of Extreme Precipitation Changes Due to Climate Change in Indonesia 3rd

Identification of Extreme Precipitation Changes Due to Clima...

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3rd International Conference on Radioscience, Equatorial Atmospheric Science and Environment, INCREASE 2023

作者： Aminah, Siti Riawan, Edi Syahputra, Muhammad Ridho Kuntoro, Arno Adi Master Program in Water Resource Management Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung Indonesia Atmospheric Sciences Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung Indonesia Water Resources Engineering Research Group Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9789819707393

This study uses Global Precipitation Measurement (GPM) and Coupled Model Intercomparison Project Phase 6 (CMIP6) precipitation data to identify extreme precipitation intensity and frequency changes in Indonesia. Extreme precipitation calculations were performed using the Gumbel distribution and return period fitted to annual maxima data. Extreme precipitation and frequency of extreme events were compared between the historical period and the near-future period (2026–2055) and the far-future period (2070–2099) to identify changes. The results showed that there were changes in extreme precipitation in Indonesia both in intensity and frequency of occurrence. Extreme precipitation with a 5-year return period in Indonesia generally has a change value in the range of − 5 to + 25% with most areas likely to increase. The increased value reaches + 20% in the near-future period and + 40% in the far-future period. For the frequency of extreme precipitation above the 5-year return period in Indonesia, the change value is generally in the range of − 40 to + 120% with most areas likely to increase. The increased value reaches + 160% in the near-future period and + 200% in the far-future period. In the higher emission scenario (SSP5-8.5), the areas with higher values of increase will expand both in the change in intensity and frequency of occurrence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Climate change

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