• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.101-108
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• 2015

This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.533-538
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• 2013

The damage caused by Recent frequently occurring locality torrential rains is increasing rapidly. In case of densely populated metropolitan area, casualties and property damage is a serious due to landslides and debris flows and floods. Therefore, the importance of predictions about the torrential is increasing. Precipitation characteristic of the bad weather in Korea is divided into typhoons and torrential rains. This seems to vary depending on the duration and area. Rainfall is difficult to predict because regional precipitation is large volatility and nonlinear. In this paper, Very short-term precipitation forecasting pattern model is implemented using KLAPS data used by Korea Meteorological Administration. we designed very short term precipitation forecasting pattern model using GA-based RBFNNs. the structural and parametric values such as the number of Inputs, polynomial type,number of fcm cluster, and fuzzification coefficient are optimized by GA optimization algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.105-112
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• 2017

PCI Express is a bus technology that connects the processor and the peripheral I/O devices that widely used as an industry standard because it has the characteristics of high-speed, low power. In addition, PCI Express is system interconnect technology such as Ethernet and Infiniband used in high-performance computing and computer cluster. PGAS(partitioned global address space) programming model is often used to implement the one-sided RDMA(remote direct memory access) from multi-host systems, such as computer clusters. In this paper, we design and implement a OpenSHMEM API based on PCI Express maintaining the existing features of OpenSHMEM to implement RDMA based on PCI Express. We perform experiment with implemented OpenSHMEM API through a matrix multiplication example from system which PCs connected with NTB(non-transparent bridge) technology of PCI Express. The PCI Express interconnection network is currently very expensive and is not yet widely available to the general public. Nevertheless, we actually implemented and evaluated a PCI Express based interconnection network on the RDK evaluation board. In addition, we have implemented the OpenSHMEM software stack, which is of great interest recently.

• Journal of Technologic Dentistry
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• v.18 no.1
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• pp.73-94
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• 1996

This study was aimed for evaluating the validity of relative-productivity index on the basis of working hour(RPHW index) designed by author as new productivity index and drawing up a plan of bettering productivity to cope with financial difficulty of dental laboratories. Fortyeight dental laboratories extracted by cluster-sampling method form all the dental laboratories in Seoul were subjected for this study. And in each of them, the term of establishment which was divied into three group as short-term, mid-term and long-term group, the scale of dental laboratory which as divided into two group by number of dental technician as small-scale group and large-scale group, the salary system which was composed of salary criteria, pay according to ablility criteria and collectiveagree, the salary level, simple labor productivity index(SLP index), relative-productivity index on the basis of worker number(ROWN) and relative-productivity index on the basis of working hour(RPWH index) were surveyed through the self-administractive questionaires. The results as follows : Most of dental laboratories(93.6%) were managed by non-professional managers. The establishment rate per year of dental laboratory was the increase. The mean number of employees of dental laboratories was $7.00{\pm}3.90$ person. The ratio of smallscale group(under the 5 employees) was 42.6% and as the term of establishment was shorter, the ratio of small-scale group was higher. The mean establishment area of dental laboratories was $24.49{\pm}10.97$ unit and the mean establishment area per head of dental laboratories was $4.05{\pm}3.90$ unit. The estabilshment area and area per head were not significantly associted with the term of establishment, but as the term of establishment was shorter, the estabkishment area per head was slightly wider. The establishment area per head in small-scale group was significantly wider than large-scale group(over the 6 emplayees) The salary criteria(54.4%), pay according to ability(79.2)m ability criteria(77.1%) and collectiveagree(79.2%) as salary systems were used in the most of all dnetal laboratoies. The all salary systems were not significantly associated with the term of establishment and the scale of dental laboratories. The monthly mean salary level of dental laboratoies was $125.64{\pm}31.06$ milion won. The monthly salary level was not significantly associated with the term of establishment and the scale of dental laboratores. But the monthly salary level in the short-term group and the small-scale group were slightly lower than others. The SLP index, the RPWN index and the RPWH index of dental laboratories were $132.16{\pm}48.41$, $382.41{\pm}128.76$ and $76.06{\pm}25.11$, respectively. The SLP, the RPWN and the RPWH of dental laboratories were not significantly associated with the term SLP, the RPWN and the RPWH of dental laboratories were significantly associated with the area of dental laboratory and the salary level. Except for only the association salary criteria among salary system with RPWH of dental laboratories, all other salary system were not associated with the SLP, the RPWN and the RPWH of dental laboratories.

• Management & Information Systems Review
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• v.39 no.3
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• pp.53-82
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• 2020

Daejeon Metropolitan City has the best innovation capability infrastructure (ICT) required for the 4th industry. Nevertheless, there are scattered factors that hinder the industrial ecosystem. In this study, the factor of job creation was approached from the viewpoint of organizational ecology in consideration of regional characteristics during the 4th Industrial Revolution.That is, the case of job creation through overseas ICT-based clusters (or cities) was examined. Then, the factors of organizational ecology, 'niche', 'variation', 'selection', and 'retention' were derived. Through this process, we explored the environment surrounding Daejeon Metropolitan City and benchmarked lessons from existing overseas cluster cases. As a result, we discover the 'niche' of ICT-based job creation and suggest strategies for the 'variation' process to survive in the ecosystem and how to be 'retention' in the ecosystem. n conclusion, the strategy of the organizational ecological approach to establish itself as a metropolitan city as the strength of Daejeon city and the 'innovation hub' that is evident, such as '4th Industrial Revolution City', 'Innovation City Designation', and 'Secure Excellent Capability of SW' Insist on need. Through this study, we hope that there will be a theoretical contribution to the prior research lacking from original research such as the scarcity of ICT-based job creation research in response to the era of the fourth industrial revolution, recognition of the importance of the region in job creation, and presentation of an organizational ecological approach of sustainable clusters.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.716-720
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• 2006

Fuzzy sets are good for abstracting and unifying information using natural language like terms. However, fuzzy sets embody vagueness and users may have different attitude to the vagueness, each user may choose difference one as the best among several fuzzy values. In this paper, we develop a method teaming a user's, preference on fuzzy values and select one which fits to his preference. Users' preferences are modeled with artificial neural networks. We gather learning data from users by asking to choose the best from two fuzzy values in several representative cases of comparing two fuzzy sets. In order to establish tile representative comparing cases, we enumerate more than 600 cases and cluster them into several groups. Neural networks ate trained with the users' answer and the given two fuzzy values in each case. Experiments show that the proposed method produces outputs closet to users' preference than other methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.49-60
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• 2020

The number of traffic control equipment installed to prevent traffic accidents increases every year due to continuous installation by the National Police Agency and local governments. However, it is installed based on qualitative judgment rather than engineering analysis results. The purpose of this study was to present additional installations in the future by presenting the installation criteria considering the severity of accidents for each road type and calculating the appropriate number of installations. ARI indicators that can indicate the severity of traffic accidents were developed, and road types were classified through analysis of variance and cluster analysis, and accident information by road type was analyzed to derive ARI of clusters with high traffic accident severity. The ARI values required to determine the installation of equipment for each road type were presented, and 5,244 additional installation points were analyzed.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.11
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• pp.381-394
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• 2022

Recently, due to the personalization and customization of data, Internet-based services have increased requirements for real-time processing, such as real-time AI inference and data analysis, which must be handled immediately according to the user's situation or requirement. Real-time tasks have a set deadline from the start of each task to the return of the results, and the guarantee of the deadline is directly linked to the quality of the services. However, traditional container systems are limited in operating real-time tasks because they do not provide the ability to allocate and manage deadlines for tasks executed in containers. In addition, tasks such as AI inference and data analysis basically utilize graphical processing units (GPU), which typically have performance impacts on each other because performance isolation is not provided between containers. And the resource usage of the node alone cannot determine the deadline guarantee rate of each container or whether to deploy a new real-time container. In this paper, we propose a monitoring technique for tracking and managing the execution status of deadlines and real-time GPU tasks in containers to support real-time processing of GPU tasks running on containers, and a node list management technique for container placement on appropriate nodes to ensure deadlines. Furthermore, we demonstrate from experiments that the proposed technique has a very small impact on the system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.105-116
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• 2023

The fatality rate of secondary accidents is seven times that of general traffic accidents. If limited to highways, one in four deaths are said to occur from secondary accidents. Unexpected situations which do not give drivers time to prepare are the cause of secondary accidents. This risk results in more fatalities on highways with high driving speeds. Existing studies have conducted research on traffic accidents and on secondary traffic accidents that occur after a primary traffic accident, without considering unexpected situations that may occur on the road. Therefore, to reduce damage and casualties caused by secondary accidents, there is a need to create a safe road environment by removing the possibility of causing accidents. This study analyzes whether the day of occurrence, time of occurrence, and radius of the curve of an unexpected situation are related to the occurrence of an unexpected situation. This study was based on data of accidents that occurred in 2022 on the Cheonan-Nonsan Expressway and the Seoul-Yangyang Expressway. The radius of the curve was calculated by dividing the section of the highway into straight, clothoid, and curved sections through cluster analysis. Results of the analysis indicate that the day and time of occurrence and the curve radius are associated with unexpected situations.

• Information Systems Review
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• v.21 no.3
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• pp.111-129
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• 2019

Recently, artificial intelligence (AI)-enabled products and services such as smartphones, smart speakers, chatbots are being released due to advances in AI technology. Thus researchers making effort to reveal that consumers' intention to adopt AI-enabled products. Yet, little is known about the intended adoption of AI-enabled products. Because most of studies has been not consideredthe perceived utility value of consumers for each attribute by classified based on the characteristics of AI-enabled products. Therefore, the purpose of this study is to investigate the difference in importance between attributes that affect the intention to adopt of AI-enabled products. For this, first, identified and classified the attributes of AI-enabled products based on IS Success Model of DeLone and McLean. Second, measured the utility value of each attribute on the adoption of AI-enabled products through conjoint analysis. And we employed construal level theory to see whether there are differences in the relative importance of AI-enabled products attributes depending on the temporal distance. Third, we segmented the market based on the utility value of each respondent through cluster analysis and tried to understand the characteristics and needs of consumers in each segment market. We expect to provide theoretical implications for conceptually structured attributes and factors of AI-enabled products and practical implications for how development efforts of AI-enabled products are needed to reach consumers need for each segment.