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arXiv 2024年

作者： Muluneh, Mequanent Argaw Peng, Yan-Tsung Degife, Worku Abebe Tadesse, Nigussie Abate Demeku, Aknachew Mebreku Su, Li Institute of Information Science Academia Sinica Taipei Taiwan Department of Information System University of Gondar Gondar Ethiopia Department of Computer Science National Chengchi University Taipei Taiwan Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Taiwan Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Material Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan

Computational music research plays a critical role in advancing music production, distribution, and understanding across various musical styles in the world. Despite the immense cultural and religious significance, the Ethiopian Orthodox Tewahedo Church (EOTC) chants are relatively underrepresented in computational music research. This paper contributes to this field by introducing a new dataset specifically tailored for the analysis of EOTC chants, also known as Yaredawi Zema. This work provides a comprehensive overview of a 10-hour dataset, 369 instances, creation, and curation process, including rigorous quality assurance measures. Our dataset has a detailed word-level temporal boundary and reading tone annotation along with the corresponding chanting mode label of audios. Moreover, we have also identified the chanting options associated with multiple chanting notations in the manuscript by annotating them accordingly. Our goal in making this dataset available to the public1 is to encourage more research and study of EOTC chants, including lyrics transcription, lyric-to-audio alignment, and music generation tasks. Such research work will advance knowledge and efforts to preserve this distinctive liturgical music, a priceless cultural artifact for the Ethiopian people. © 2024, CC BY.

关键词： Music

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Water scarcity and drought in WANA countries

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Procedia Engineering 2012年 33卷 14-29页

作者： Jauad El Kharraz Alaa El-Sadek Noreddine Ghaffour Eric Mino Euro-Mediterranean Information System on know-how in the Water sector (EMWIS) BP 23 Sophia Antipolis 06901 France Water Resources Management Program College of Graduate Studies Arabian Gulf University Kingdom of Bahrain Water Desalination and Reuse Center King Abdullah University of Science and Technology (KAUST) KSA

Water Security was a central theme of WANA Forum 2010, where regional experts warned that the wars of the 21st century will be fought over water. Climate change will only exacerbate problems in a region already stressed by lack of water, food and political and social unrest. Across the Arc of Crisis, from Somalia, Sudan and Egypt in Africa to Yemen, Iraq, Pakistan, and Afghanistan in West Asia, water scarcity in the region has already lead to drought and famine, loss of livelihood, the spread of water-borne diseases, forced migrations and open conflict. Water scarcity is closely linked to food and health security, making better water management a key stepping stone for poverty reduction and economic growth. If nothing changes, most of the WANA countries will encounter, in less than a generation, serious problems in managing inland freshwater, the availability of which, in sufficient quantity and quality, may become, as it is already the case in several of these countries, a main challenge for economic and social development. Wastage and pollution will then be such that « water stress » will affect, in a way or another, most of the populations of WANA countries and the poorest first of all. The effects of global warming will increase current trends. On the other hand, water scarcity in the WANA region is an issue of growing concern. With heavy demand from agriculture, growing populations and virtually no remaining untapped water sources, the need to establish water-management strategies in the region is of vital importance. WANA countries can be divided into three major agro-ecologies, each facing slightly different challenges. Rain-fed areas are dependent on a low and extremely variable rainfall, resulting in minimal yields, a problem exacerbated by frequent drought. Rainfall occurs in the form of intense and unpredictable storms, and as a result, the crusting soils are unable to absorb the moisture, which rapidly becomes lost through evaporation or runoff. Irrigate

关键词： water scarcity drought WANA region water demand water supply climate change

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Parameter Optimization of Support Vector Regression Using Harris Hawks Optimization

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Procedia Computer Science 2021年 179卷 17-24页

作者： I Nyoman Setiawan Robert Kurniawan Budi Yuniarto Rezzy Eko Caraka Bens Pardamean Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Department of Information Management College of Informatics Chaoyang University of Technology Taiwan (ROC) Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia 11530 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia. 11530.

Support Vector Regression (SVR) is often used in forecasting. Adjustment of parameters in the SVR affects the results of forecasting. This study aims to analyze the SVR method that is optimized using Harris Hawks Optimization (HHO), hereinafter referred to as HHO-SVR. The HHO-SVR was evaluated using five benchmark datasets to determine the performance of this method. The HHO process is also compared based on the type of kernel and other metaheuristic algorithms. The results showed that the HHO-SVR has almost the same performance as other methods but is less efficient in terms of time. In addition, the type of kernel also affects the process and results.

关键词： SVR harris hawks optimization parameter optimization kernel forecasting

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A scoring model to detect abusive billing patterns in health insurance claims

A scoring model to detect abusive billing patterns in health...

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第二届(2013)老年人口与健康产业国际会议

作者： Hyunjung Shin Hayoung Park Junwoo Lee Won Chul Jhee Department of Industrial and Information Systems Engineering Ajou UniversitySan 5 Woncheon-dongYeo Technology Management Economicsand Policy Graduate ProgramSeoul National University599 Gwanak-ro Department of Industrial and Information Engineering Hongik University72-1 Sangsu-dongMapo-gu Seou

We propose a scoring model that detects outpatient clinics with abusive utilization patterns based on profiling information extracted from electronic insurance *** model consists of (1) scoring to quantify the degree of abusiveness and (2) segmentation to categorize the problematic providers with similar utilization *** performed the modeling for 3705 Korean internal medicine *** applied data from practitioner claims submitted to the National Health Insurance Corporation for outpatient care during the 3rd quarter of 2007 and used 4th quarter data to validate the *** considered the Health Insurance Review and Assessment Services decisions on interventions to be accurate for model *** compared the conditional probability distributions of the composite degree of anomaly (CDA) score formulated for intervention and non-intervention *** assess the validity of the model,we examined confusion matrices by intervention history and group as defined by the CDA *** CDA aggregated 38 indicators of abusiveness for individual clinics,which were grouped based on the CDAs,and we used the decision tree to further segment them into homogeneous clusters based on their utilization *** validation indicated that the proposed model was largely consistent with the manual detection techniques currently used to identify potential *** proposed model,which can be used to automate abuse detection,is flexible and easy to *** may present an opportunity to fight escalating healthcare costs in the era of increasing availability of electronic healthcare information.

关键词： Health insurance claims Medical abuse detection Fraud detection Degrees of anomaly Data mining

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Preliminary Plan for Data Collection on Stakeholder information Interdependence in Area-Business Continuity management: A Case Study of Flood management in Thai Industrial Zones

Preliminary Plan for Data Collection on Stakeholder Informat...

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International Symposium on Communications and information Technologies (ISCIT)

作者： Penpitcha Arayachookiat Kumpol Saengtabtim Akira Kodaka Natt Leelawat Jing Tang Kenji Watanabe Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness.

关键词： Disasters Disaster management Data collection information and communication technology Stakeholders Floods Risk management Iterative methods Interviews Resilience

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An effect of tsunami to hotel occupancy: A case of Phuket, Thailand 11

An effect of tsunami to hotel occupancy: A case of Phuket, T...

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11th Aceh International Workshop and Expo on Sustainable Tsunami Disaster Recovery, AIWEST-DR 2018

作者： Tang, J. Leelawat, N. Suppasri, A. Imamura, F. School of Management Technoogy Sirindhorn International Institute of Technology Thammasat University 131 Moo 5 Tiwanont Road Bangkadi Pathum Thani12000 Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Pathumwan Bangkok10330 Thailand Disaster and Risk Management Information Systems Research Group Chulalongkorn University Phayathai Road Pathumwan Bangkok10330 Thailand Risk and Disaster Management Program Graduate School Chulalongkorn University Phayathai Road Pathumwan Bangkok10330 Thailand International Research Institute of Disaster Science Tohoku University 468-1 Aramaki-Aza Aoba Aoba-ku Sendai980-0845 Japan

As a popular city for global tourists, more than one third of the Phuket GPP depends on the hotel and restaurant sector. The 2004 Indian Ocean Tsunami caused a serious physical damage to hotels and a high cancellation of bookings in the post disaster period, which, in turn, led to most THB 3 billion drop of the hotel and restaurant sector income in 2005 in Phuket. In addition, many tourism facilities in Phuket suffered bankruptcy or a slump, because they started their business again immediately after the reconstruction phase, while tourists did not really come back. This paper is an initiative study of our research project to evaluate the effects of the 2004 Indian Ocean Tsunami on Hotel Occupancy, with a focus on the speed for the physical reconstruction and tourism market recovery. We collected the physical reconstruction period and the hotel occupancy recovery data of six hotels that located in the Patong Beach of Phuket from 2003 to 2017. Through calculation, the average of damage rate (i.e., unavailability of the rooms in this study) is 55.89%, with an average speed for the physical reconstruction to rebuild the rooms about 6.07% of the overall rooms per month. The quotient of these two values indicates that the reconstruction period is around 9.2 months. However, the average period for reconstruction and tourism recovery is about 20 months. There is an about 11 months' delay between that hotel and resorts have finished the reconstruction and the tourists start to visit Phuket as usual. Therefore, the local government, local tourist authority, and hotel entrepreneurs can consider these findings in order to prepare the recovery plan for tourism industry in the future tsunami. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Recovery

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Convolution gradient method based on fitness-driven design considering global information

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ICIC Express Letters 2014年第3期8卷 651-659页

作者： Domoto, Eri Okuhara, Koji Koide, Noriaki Ueno, Nobuyuki Department of Media Business Hiroshima University of Economics 5-37-1 Gion Asaminami-Ku Hiroshima 731-0192 Japan Department of Information and Physical Sciences Graduate School of Information Science and Technology Osaka University 1-5 Yamadaoka Suita Osaka 565-0871 Japan Graduate School of Comprehensive Scientific Research Program in Management and Information Systems Prefectural University of Hiroshima 1-1-71 Ujina-Higashi Minami-ku Hiroshima City Hiroshima 734-8558 Japan

In many industries, a usual business model has a problem to realize mass customization, because it is difficult to satisfy the diversified customer needs. Total supply chain optimization is formulated as a stochastic programming problem, and then it is difficult to obtain a better solution for it. In this paper, we have proposed a new hybrid dynamical system of convolution gradient dynamics and swarm intelligence for finding a better optimal solution. Dynamics of convolution gradient has been derived in neural network framework. Swarm intelligence is the optimization technique based on the action of groups, such as birds, fish, and a colony of ants. From a theoretical point of view, we show how to combine them. The proposed hybrid algorithm can realize the interpolation search which is the mechanism of the dynamics of local search and global search. In numerical examples, we show that the proposed model can behave better dynamics for test functions and application of total supply chain optimization. © 2014 ICIC International.

关键词： Convolution

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Energy consumption of high-rise double skin façade buildings, a machine learning analysis

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Journal of Building Engineering 2024年 89卷

作者： Rezaie, Maedeh Kariminia, Shahab Band, Shahab S. Ameri, Rasoul Farokhi, Maryam Pai, Hao-Ting Gocer, Ozgur Rismanchi, Behzad Shooshtarian, Salman Department of Architecture Advancement in Architecture and Urban Planning Research Center Najafabad Branch Islamic Azad University Najafabad Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Department of Information Management National Yunlin University of Science and Technology Taiwan Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan School of Architecture Design and Planning The University of Sydney SydneyNSW Australia Renewable Energy and Energy Efficiency Group Department of Infrastructure Engineering Faculty of Engineering and Information Technology The University of Melbourne Australia School of Property Construction and Project Management RMIT University Melbourne Australia

Most energy exchanges take place through the building skin. The skin characteristics play a decisive role in the extent of these exchanges, but they are somewhat more varied in the double skin façade (DSF). Among these characteristics, cavity segmentation has a noticeable effect on the implementation of the DSF in different directions during the hot and cold seasons. The aim of this study was to investigate the role of DSF segmentation in energy consumption and natural ventilation of high-rise buildings in hot and dry climates. This study used DesignBuilder software to study sixty-four segmentation component scenarios in an eight-story residential building in Isfahan, Iran. Moreover, a proposed hybrid model utilizing the hybridization of the Hunger Game Search and Gradient Boosting (HGS-GB) algorithm was employed to estimate energy consumption in various scenarios involving lighting, heating, cooling, and total scenarios. The available outcomes revealed that the HGS-GB model had a better performance in comparison with other individual models, such as Gradient Boosting (GB), Random Forest (RF), and K-nearest neighbors (KNN). The R2 values for lighting, heating, cooling, and total energy estimation were 0.9993, 0.9958, 0.9991, and 0.9922, respectively. The findings of this study suggest the significance of DSF segmentation in energy consumption and natural ventilation in high-rise buildings in hot and dry climates. © 2024 Elsevier Ltd

关键词： Forestry

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Classifying Attitudes of Thai Business Organizations Toward the Perceived Benefit of Customer Predictive Analytics

Classifying Attitudes of Thai Business Organizations Toward ...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Santisook Limpeeticharoenchot Nagul Cooharojananone Thira Chavarnakul Kanokwan Atchariyachanvanich Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand Department of Commerce Chulalongkorn University Bangkok Thailand Faculty of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (纸本)9781538626344;9781538626337

In this paper, we applied K-means++, Agglomerative and Decision Tree techniques to classify characteristics of Thai business organizations toward the perceived benefit of predictive analytics. We believe that different characteristics of business organizations require different solution approaches to overcome challenges and gain business value. In the exploratory survey, we collected 84 respondents, who are data analysts, business analysts, business owners, management, and IT managers. The respondents' size of organization varies from small firms to large firms. The result from three techniques of classification shows that Thai business organizations perceiving the benefit of predictive analytics could be divided into two groups. We further confirmed that with the analysis of variance technique to identify the difference of means in each parameter. We also found that the most important descriptive profile is led by customer-related factors such as a change in the percentage of customers, the number of direct customers, and number of sales and marketing staff. These are followed by technology factors, which are the number of external and internal data sources and number of analytics and technologies currently used for data analytics.

关键词： Organizations Data analysis Clustering algorithms Big Data Organizational aspects Decision trees

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Assessing the Performance of Machine Learning Algorithms for Water Level Prediction in the Chao Phraya River and its Tributaries: A Focus on Low and High Water Levels

SSRN

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SSRN 2024年

作者： Priyasiri, Wilmat D.S.M. Rittima, Areeya Kraisangka, Jidapa Sawangphol, Wudhichart Phankamolsil, Yutthana Talaluxmana, Yutthana Graduate Program in Environmental and Water Resources Engineering Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Thailand Faculty of Information and Communication Technology Mahidol University Thailand Environmental Engineering and Disaster Management Program Mahidol University Kanchanaburi Campus Thailand Department of Water Resources Engineering Faculty of Engineering Kasetsart University Thailand

High precision of hydrological prediction is crucial for real–time operation of flood and drought risk mitigation and strategic planning. This study assessed the predictive performances of three Machine Learning (ML) algorithms;XGBoost, Random Forest (RF), and Multi–Layer Neural Networks (MLNNs) for water level prediction with a focus on low and high water levels. The one–day and one–week water level prediction models for six key gauged stations along the Chao Phraya River and its major tributaries were accordingly developed. Selecting the combination of input features was carried out and structured in the prediction model at all gauged stations based on the physical river–reservoir system using past water level, rainfall, controlled reservoir outflow, and upstream discharges with different travel times. The statistical evaluation indicated that both XGBoost and RF, the tree–based ML models, with rainfall input robustly outperformed than MLNNs, as it strongly achieved higher R2 from 0.957 to 0.999 for model training and from 0.743 to 0.995 for model testing and lower MAE, MSE, and RMSE values for all prediction scenarios. Among these three ML algorithms applied for daily prediction, RF demonstrated the superior performance for low water level prediction exhibiting the smallest percentage error of overestimating lying between +0.0088% and +0.9380%. XGBoost, RF, and MLNNs, demonstrated acceptable performance level for high water level prediction as it shows small percentage error of both overestimating and underestimating lying between –2.2696% and +1.1587%. Additionally, it can capture the entire testing dataset with high precision than weekly model. © 2024, The Authors. All rights reserved.

关键词： Rain

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