• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4B
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• pp.184-191
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• 2008

NanoQplus, which is an embedded operating system for wireless sensor networks (WSNs) and developed by Electronics and Telecommunications Research Institute (ETRI), provides programmer-friendly preemptive multi-threading programming technique, but it has poor network protocol stack, as compared to TinyOS, one of the famous operating systems for WSNs. In this paper, we apply dynamic MANET on-demand routing (DYMO) protocol, which is being standardized in Internet Engineering Task Force (IETF), to NanoQplus. Since DYMO has been proposed for mobile ad-hoc networks (MANETs) and MANETs have less resource restrictions than WSNs, the basic DYMO protocol cannot be applied to WSNs without modifications. Moreover, coherence with MAC protocol should be considered in order to eliminate redundant data between MAC and network layers. Thus, we propose a modified version of the basic DYMO protocol for NanoQplus. The experimental results from a real sensor network test-bed show that the DYMO implementation using NanoQplus works efficiently in WSNs.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1041-1049
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• 2010

In Korean professional baseball, attendance is the largest source of revenue for development of professional baseball and the highest concern of professional baseball teams. So, if there is demand forecasting model, it will be helpful for pennant chasers to work out the strategies for drawing attendance. For this reason, this research intends to suggest the model which estimates Korean professional baseball's attendance and uses all usable variables which have an effect on attendance in limited circumstances. We supposed that dependent variable is attendance as well as several independent variables and error term are homoscedastic variance. And then, we compared the models which assume conditional heteroscedastic variance like GARCH and EGARCH with GARCH-t models which use the assumption that error term's distribution follows student-t distribution. In result of that, we could confirm that the models which were made by using GARCH(1,1)-t made estimates the most accurately among the several models considered.

• International Commerce and Information Review
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• v.16 no.2
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• pp.185-198
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• 2014

The purpose of this paper is to examine a causal relationship and interaction among payment of education expenses, economic growth, imports and exports. The results of 'the Granger causality test' suggest that payment of education expenses are affected by imports and exports; and the other factors are not related. In addition, payment of education expenses and the relationship among variables confirmed by IRF show that payment of education expenses has a minus(-) effect on exports at the beginning and then it turns into plus(+) as a certain time passes. On the other hand, it has a minus(-) effect on imports at the beginning, and this gradually changes to zero(0). Lastly, it turns out that it has a plus(+) effect on GDP. It is therefore estimated that the demand for high-quality manpower is expected to grow and new investments for education to rise with increases in imports and exports with initial acceleration. The findings show that government education investment in foreign languages and research manpower must take precedence in order to meet the demand for high-quality manpower.

• Journal of Environmental Impact Assessment
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• v.8 no.2
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• pp.95-107
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• 1999

The organic contents of reservoir sediment can offer a good indicator to events in history of lake life. Reservoir sediment have many information of the past and future fingerprint about development direction of life cycle in biological animals. So, in this study we made an effort to know the distribution of organic contents in Daecheong reservoir sediment. Items for this investigations are such as follows: Loss on ignition, COD, Organic carbon, TN, TP, heavy metal contents, Loss on ignitions were determined in 6.44~15.91% and COD were determined in 1.606~6.859%, organic carbon in 1,077~3.743%. Contents of TP and TN were in the range of 0.083~0.757%, and 0.645~0.926%, respectively.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.71-77
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• 2015

Upcoming ground-breaking applications for always-on tiny interconnected devices steadily demand two-fold features of processor cores: aggressively low power consumption and enhanced performance. We propose implementation of a novel superscalar low-power processor core with a low supply voltage. The core implements intra-core low-power microarchitecture with minimal performance degradation in instruction fetch, branch prediction, scheduling, and execution units. The inter-core lockstep not only detects malfunctions during low-voltage operation but also carries out software-based recovery. The chip incorporates a pair of cores, high-speed memory, and peripheral interfaces to be implemented with a 65nm node. The processor core consumes only 24mW at 350MHz and 0.68V, resulting in power efficiency of $80{\mu}W/MHz$. The operating frequency of the core reaches 850MHz at 1.2V.

• Korean Journal of Acupuncture
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• v.41 no.3
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• pp.59-67
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• 2024

Objectives : By reviewing NIH's SPARC program and NCCIH's TARA project, we would like to suggest the direction of research on acupoint utilization in Korea. Methods : The goals, operation methods, result linkage strategies, collaborative activities, and research contents of the SPARC program and TARA program were reviewed and summarized. Results : SPARC connects the identification of medical device mechanisms, clinical efficacy, regulatory approval, and industrialization through nerve stimulation, and the research results are provided to researchers and companies as an open access database. The TARA program creates an open access database of anatomy, physiology, and pathology information on acupuncture points and links it with SPARC to increase understanding and utilization of acupuncture points in the development of medical devices and conducts international cooperation with Korea, China, Japan, etc. Korea's acupuncture point utilization research lacks medical device industrialization connectivity and international cooperation planning. Conclusions : Korea's research on the use of acupuncture points should be planned and managed so that it can be linked to medical device industrialization. In addition, it is necessary to anticipate the demand for bioelectronic medical devices and conduct joint research through open access database linkage and international cooperation.

• Spatial Information Research
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• v.23 no.2
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• pp.49-57
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• 2015

Recently, Through the linkage and opening, the fusion of the spatial information, it is necessary for productive ecosystem to provide a variety of information and to increase the civil use. Depending on the economic growth, demand for quality of life and well-being has been on the increase. Spatial information service contents for the public convenience has emerged to solve the problem such as health, safety, welfare and discomfort of daily life This study aims to implement search services for a tailored residence space through the three-dimensional data modeling on cadastral information. To achieve this goal, we established the requirements for deriving a registered object by investigating recent trend with respect to existing cadastral data model and defined property and relationship. Focusing on Songpa-gu, Jamsil station in Seoul, we implemented search services for a tailored residence space for three-dimensional right analysis in conjunction with residential and commercial complex building. As a result, we derived a way to supply 3D cadastre information through open platforms (VWorld) and to represent efficiently, which is able to improve the quality of spatial information service contents for the public convenience as well as to widen utilization of information.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.21-32
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• 2003

This paper discusses the design of location optimization visualization and feasibility of 3 dimensional visualization techniques. In generic GIS visualization of location analysis, 2 dimensional visualization techniques have been used to map location elements and model solution, such as displaying demand and supply points, drawing connecting lines(e. g. spider line) of optimal locations to their demands, and representing density of location variations. Nevertheless, current GIS and location analysis literatures have little attentions in 3D visualization applications for location optimization problems. Previous research has been neglected 3D visualization of solution performances and its evaluation of solution quality. Consequently, this paper demonstrates potential benefits of 3D visualization techniques and its appropriate GIS applications for location optimization analysis. The visualization effectiveness of 3D approaches is examined in terms of spatial accessibility, and solution performance of optimal location models is evaluated. Finally, this paper proposes extensive 3D visualization perspectives for location analysis and GIS research as a further research agenda.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.125-130
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• 2017

In the business environment of the modern society, it is not possible for the company, which is a producer of accounting information, to provide accounting information to the users of accounting information because it can not satisfy the information demand of the accounting information users due to the problem of information asymmetry. Therefore, the purpose of this study is to find out what information should be provided for satisfying the information needs of users of accounting information. This study investigates the qualitative characteristics of accounting information based on K-IFRS in the provision of accounting information and conducts empirical studies based on the users of accounting information of listed companies and unlisted companies. And how to improve the satisfaction. As a result of empirical research, it was confirmed that the accounting information satisfying the qualitative characteristics is useful for meeting the information needs of users of accounting information.