• Geomechanics and Engineering
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• v.25 no.1
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• pp.1-16
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• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• Animal Bioscience
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• v.37 no.7
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• pp.1213-1224
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• 2024

Objective: Enterotypes (ETs) are the clustering of gut microbial community structures, which could serve as indicators of growth performance and carcass traits. However, ETs have been sparsely investigated in waterfowl. The objective of this study was to identify the ileal ETs and explore the correlation of the ETs with growth performance and carcass traits in Muscovy ducks. Methods: A total of 200 Muscovy ducks were randomly selected from a population of 5,000 ducks at 70-day old, weighed and slaughtered. The growth performance and carcass traits, including body weight, dressed weight and evidenced weight, dressed percentage, percentage of apparent yield, breast muscle weight, leg muscle weight, percentage of leg muscle and percentage of breast muscle, were determined. The contents of ileum were collected for the isolation of DNA and 16S rRNA gene sequencing. The ETs were identified based on the 16S rRNA gene sequencing data and the correlation of the ETs with growth performance and carcass traits was performed by Spearman correlation analysis. Results: Three ETs (ET1, ET2, and ET3) were observed in the ileal microbiota of Muscovy ducks with significant differences in number of features and α-diversity among these ETs (p<0.05). Streptococcus, Candida Arthritis, and Bacteroidetes were the presentative genus in ET1 to ET3, respectively. Correlation analysis revealed that Lactococcus and Bradyrhizobium were significantly correlated with percentage of eviscerated yield and leg muscle weight (p<0.05) while ETs were found to have a close association with percentage of eviscerated yield, leg muscle weight, and percentage of leg muscle in Muscovy ducks. However, the growth performance of ducks with different ETs did not show significant difference (p>0.05). Lactococcus were found to be significantly correlated with leg muscle weight, dressed weight, and percentage of eviscerated yield. Conclusion: Our findings revealed a substantial variation in carcass traits associated with ETs in Muscovy ducks. It is implied that ETs might have the potential to serve as a valuable biomarker for assessing duck carcass traits. It would provide novel insights into the interaction of gut microbiota with growth performance and carcass traits of ducks.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.10a
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• pp.101-114
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• 2008

An efficient mine management system demand constant attention of mine managers on the key performance indicators like production targets, equipment status, condition of haul roads, safety etc.. There is a wealth of information generated during day to day working of the mine. The success of a mining enterprise is a function of reliability of accumulated information and decision making on the basis of such information. In the present paper a computerized mine operations management system developed for a large opencast mine making use of the potential benefits of geographical information systems, real time kinematic global positioning systems and a communication network to improve the overall efficiency of the mine is presented.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.121-128
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• 2013

Because of governmental regulations, large-scale discount stores are trying to find a new way that can expand a market size. Homeplus virtual store has received attention from the other companies, because virtual store can access 24 hours and be unfettered by governmental regulations. The purpose of the study is to review performance and strategies of Homeplus virtual store as well as the cause of the failure of imitators. To do this, we can find key indicators of success of virtual store.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.466-482
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• 2015

IT is the key enabler of digital economy. Appropriate usage of IT can provide a strategic competitive advantage to a firm in a dynamic competitive environment. However, there has been a continuing debate on whether IT can actually enhance the productivity of firms. This concept is called IT productivity paradox. In this study, we analyzed the causality among appropriate indicators to demonstrate the real impact of IT on productivity. The 12,100 sample data from 2011 were used for analysis. As expected, the results indicated that mobile device usage, website adoption, e-commerce, open source, cloud computing, and green computing positively influence IT productivity. This unprecedented large-scale analysis can provide clarification regarding the ambiguous causal mechanism between IT usage and productivity.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.33-45
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• 2013

The trend toward ubiquitous computing does not represent simply a change in the way people access and use information. In the end it will have a profound effect on the way people work with each other. In this paper, we have defined functionalities of an information system that helps operate a kind of smart office environment, and implemented the system using RFID technology. The system provides three major functions-time and attendance management, personalized message notification, and flexible seat allocation for a smart working center. We have also suggested the key performance indicators and performed a KPI analysis to measure an efficiency of implemented system.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.21-26
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• 2007

Kaplan & Norton introduce the BSC in early 1990s. after introducing the Balanced scorecard, The Balanced scorecard has been evolved in various function. In the various functional Balanced scorecard, this paper focuses on the logistics BSC, and the decision the weights of Key Performance Indicators. In this paper, a combination of Balanced scorecard and AHP-LTV based approach proposed multi-criteria provides a more accurate representation of the problem for measuring company.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.71-78
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• 2022

Wearable devices have the potential to revolutionize future medical diagnostics and personal healthcare. The integration of biosensors into scalable form factors allow continuous and noninvasive monitoring of key biomarkers and various physiological indicators. However, conventional wearable devices have critical limitations owing to their rigid and obtrusive interfaces. Recent developments in functional biocompatible materials, micro/nanofabrication methods, multimodal sensor mechanisms, and device integration technologies have provided the foundation for novel skin-interfaced bioelectronics for advanced and user-friendly wearable devices. Nonetheless, it is a great challenge to satisfy a wide range of design parameters in fabricating an authentic skin-interfaced device while maintaining its edge over conventional devices. This review highlights recent advances in skin-compatible materials, biosensor performance, and energy-harvesting methods that shed light on the future of wearable devices for digital health and personalized medicine.

• ETRI Journal
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• v.42 no.5
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• pp.669-685
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• 2020

5G AgiLe and fLexible integration of SaTellite And cellulaR (5G-ALLSTAR) is a Korea-Europe (KR-EU) collaborative project for developing multi-connectivity (MC) technologies that integrate cellular and satellite networks to provide seamless, reliable, and ubiquitous broadband communication services and improve service continuity for 5G and beyond. The main scope of this project entails the prototype development of a millimeter-wave 5G New Radio (NR)-based cellular system, an investigation of the feasibility of an NR-based satellite system and its integration with cellular systems, and a study of spectrum sharing and interference management techniques for MC. This article reviews recent research activities and presents preliminary results and a plan for the proof of concept (PoC) of three representative use cases (UCs) and one joint KR-EU UC. The feasibility of each UC and superiority of the developed technologies will be validated with key performance indicators using corresponding PoC platforms. The final achievements of the project are expected to eventually contribute to the technical evolution of 5G, which will pave the road for next-generation communications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.65-73
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• 2018

The dynamic capabilities of sensing market signals, creating new opportunities and reconfiguring resources and capabilities to new opportunities in a rapidly changing economic environment determines the competitiveness of the enterprise to create added value and survival. This study conceptualized a two-stage performance measurement framework based on the casual model of resource (input)-process-performance (output). We have developed a 'Process capability index' that reflect the dynamic capabilities factors as a key intermediary product linking resource inputs and performance outputs in enterprise performance measurement. The process capability index consists of four elements : manpower (level of human resource), operation productivity, structure and risk management. The DEA (Data Envelopment Analysis) model was applied to the developed performance indicators to analyze the branch office performance of a telecom company. Process capability efficiency (stage 1) uses resource inputs to reach a certain level of process capabilities. In performance result efficiency (stage 2), the process capabilities are used to generate sales revenues and subscribers. The two-stage DEA model derives intermediate output values that optimize the individual stages simultaneously. Some branch offices in the telecom company have focused on process capability efficiency or some other branch offices focused on performance result efficiency. Positioning map using two-stage efficiency decomposition and benchmarking can help identify the sources of inefficiencies and visualize strategic directions for performance optimization. Applications of two-stage DEA in conjunction with the case study that are meaningfully used in performance measurement areas have been scarce. In particular, this paper has the contribution to present a new performance measurement model considering the organization theory, the dynamic capabilities.