• Journal of Korea Trade
• /
• v.24 no.3
• /
• pp.20-36
• /
• 2020

Purpose - As the global product network expands through both internationalization and diversification of the multimodal transportation system, corporate strategies have shifted to emphasize the importance of a high value-added international logistics system. To guide policies and strategies to attract relevant industries, this study aims to analyze the location competitiveness of regional logistics distribution center to serve Northeast Asia. Design/methodology - Multi-criteria techniques are considered to offer a promising framework for evaluating decision-making factors. This paper employed an analytic hierarchy process to analyze the hierarchal structure of determinants for selecting the location of a regional logistics distribution center. Adopting both qualitative and quantitative evaluations, this study suggest political implications for a regional logistics distribution center development, such as the direction of political support, service differentiation and infrastructure development. Findings - This study developed a location competitiveness evaluation model, based on the case study of the major port-cities in Northeast Asia. Evaluation model incorporates five factors underpinning 17 components extracted using factor analysis. The results revealed that the logistics factor is the most significant factor for evaluating the competitiveness of a regional logistics distribution center. The remaining factors were market, costs, and services environment. Comparing qualitative and quantitative evaluations, results provide useful insights for a regional logistics distribution center development in Northeast Asia. Originality/value - This study revealed differences between qualitative and quantitative evaluations. The finding implies that prior works on evaluation models of competitiveness has not successfully measured the gap between quantitative data and expert' evaluations. To overcome this limitation, this paper considered both actual data such as actual distance, cost, the number of companies located, and expert opinions.

• BMB Reports
• /
• v.43 no.10
• /
• pp.643-648
• /
• 2010

Sir William Osler (1849-1919) recognized that "variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions we know as disease". Accordingly, the traditional methods of medicine are not always best for all patients. Over the last decade, the study of genomes and their derivatives (RNA, protein and metabolite) has rapidly advanced to the point that genomic research now serves as the basis for many medical decisions and public health initiatives. Genomic tools such as sequence variation, transcription and, more recently, personal genome sequencing enable the precise prediction and treatment of disease. At present, DNA-based risk assessment for common complex diseases, application of molecular signatures for cancer diagnosis and prognosis, genome-guided therapy, and dose selection of therapeutic drugs are the important issues in personalized medicine. In order to make personalized medicine effective, these genomic techniques must be standardized and integrated into health systems and clinical workflow. In addition, full application of personalized or genomic medicine requires dramatic changes in regulatory and reimbursement policies as well as legislative protection related to privacy. This review aims to provide a general overview of these topics in the field of personalized medicine.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.8
• /
• pp.3689-3696
• /
• 2011

In decision support system, knowledge workers require aggregation operations of the large data and are more interested in the trend analysis rather than in the punctual analysis. Therefore, it is necessary to provide fast approximate answers rather than exact answers, and to research approximate query answering techniques. In this paper, we propose a new approximation query answering method which is based on Fuzzy C-means clustering (FCM) method and Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed method using FCM-ANFIS can compute aggregate queries without accessing massive multidimensional data cube by producing the KR model of multidimensional data cube. In our experiments, we show that our method using the KR model outperforms the NMF method.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.166-169
• /
• 2006

Our country's coast is vulnerable area to natural disaster which the repetitive damages occur every year including a loss of lives, the damage of facilities and erosion mostly except for the east coast because of a typhoon, tidal waves, sea water overflowing by topographic structure of low-lying gentle slope and shallow sea. However, as for prevention of natural disaster occurring every year, the situation is that it's centered on the restorationcentered measures and the general disaster prevention research to minimize damages at the time of disaster occurrence is insufficient. This study intendedlop t to devehe techniques possible for real time sampling of damage prediction areas on Web in order to support decision making for damage prevention and establishment of disaster prevention policy. For this, the thematic map was produced related to disaster based on high-resolution satellite picture, and the environmental DB similar to real world was constructed through topographic construction of three-dimension integrating the parts of land and the sea. In addition, the system was developed possible for the expression of damageable regions by real time grasp of dangerous regions at the time of disaster occurrence through over flowing simulation of three-dimension, and it's intended to prepare a basis to minimize damages to disaster situations through it.

• Asia pacific journal of information systems
• /
• v.3 no.2
• /
• pp.93-116
• /
• 1993

This study surveys 212 accounting information systems (AIS) of 85 manufacturing firms by using the research model based on the management process of AIS to figure out the current status and problems of the computing environment and AIS of Korean firms. The analysis of the current status leads to the suggestions to promote the utilization and efficiency of AIS. The level of experiences and education of information system (IS) personnel turns out to be still low. More education is needed to upgrade the IS personnel. AIS users lack in the computer knowledge. The users need more computer education. The analysis on the computerization and information characteristics of the AIS subsystems shows that the computerization is well established in the financial accounting area. On the other hand, the computerization for managerial accounting areas is in its early stage. The managerial accounting systems need be developed to support the managerial decision making effectively. The majority of firms develop the AIS by their own IS teams. When firms use the consulting services in developing AIS, they prefer accounting firms. The majority of firms fail to evaluate the AIS because the evaluation tools are not available. Most firms do not perform the auditing for AIS. It is needed to develop the tool and techniques for evalauation and auditing AIS.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.55 no.3
• /
• pp.85-89
• /
• 2013

In the current domestic, many industrial accidents have happened. And these are analyzed according to several factors. But it is difficult that they evaluate their business safety. Thus, we conducted a study on business specific safety assessment techniques in order that business know their safety level and perform appropriative safety activities. Study methods are survey and AHP (Analytic Hierarchy Process). Each specific weighting factors to calculate the survey was conducted for safety and consulting experts (20 persons). Weight factor was used to AHP decision support as one of the ways through a number of alternatives to the ratings for the Minesota Multiphasic. Factors are each type of industry, specific industrial scale, disaster type and strength, worker age and tenure period, and region. First, survey was conducted with 20 professionals to estimate the weighting factors. Weights between factors using the AHP analysis tool based on the mean values were calculated. Second, last 3 years between the industrial accidents statistics were used to calculate the weights for each of the rating factors in the Occupational Safety and Health Agency. Grade weights between each factor which was based on the rating of each factor was calculated as the average of three years. Finally, the weights between each factor and the grade weights for each factor using the safety level of the enterprise were calculated so that you can evaluate the weighting.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.12
• /
• pp.1215-1219
• /
• 2006

Scheduling plays an important role in the process management in terms of providing profit-maximizing operation sequence of multiple orders and estimating completion times of them. In order to takes its full potential, varying conditions should be properly reflected in computing the schedule. The adjustment of scheduling decisions has to be made frequently in response to the occurrence of variations. It is often challenging because their model has to be adjusted and their solutions have to be computed within short time period. This paper employs Model Predictive Control(MPC) principles for updating the process condition in the scheduling model. The solutions of the resulting problems considering variations are computed using parametric programming techniques. The key advantage of the proposed framework is that repetition of solving similar programming problems with decreasing dimensionis avoided and all potential schedules are obtained before the execution of the actual processes. Therefore, the proposed framework contributes to constructing a robust decision-support tool in the face of varying environment. An example is solved to illustrate the potential of the proposed framework with remarks on potential wide applications.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.25 no.1
• /
• pp.69-75
• /
• 2007

The information in physical planning field shows the socio-economic potentials of land resources while cadastral data does the physical and legal realities of the land. The two domains commonly deal with land information but have different views. Cadastre has to evolved to the multi-purpose ones which provide value-added information and support a wide spectrum of decision makers by mixing their own information with other spatial/non-spatial databases. In this context, the demands of data exchange between the two domains is growing up but this cannot be done without resolving the heterogeneity between the two information applications. Both of either discipline sees the reality within its own scope, which means each has a unique way to abstract real world phenomena to the database. The heterogeneity problem emerges when an GIS is autonomously and independently established. It causes considerable communication difficulties since heterogeneity of representations forms unique data semantics for each database. The semantic heterogeneity obviously creates an obstacle to data exchange but, at the same time, it can be a key to solve the problems too. Therefore, the study focuses on facilitating data sharing between the fields of cadastre and physical planning by resolving the semantic heterogeneity. The core job is developing a conversion mechanism of cadastral data into the information for the physical planning by DB coupling techniques.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.8B
• /
• pp.691-698
• /
• 2003

Throughput response characteristics depending on the network bandwidth allocation need to be modeled to devise adaptive control mechanism to support QoS of the network. Thus, two models are proposed in this study. The first one is a dynamic system model and the other one is a stochastic model. The dynamic system model is developed to represent dynamic characteristics of the network and the stochastic model is developed to represent distribution of measured throughput data. An optimization technique is used for decision of proposed model's factor. The result confirms that the characteristics of proposed models are similar with actual network's characteristics.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.31-40
• /
• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.