• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.175-196
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• 2004

This study focuses on improving the performance of freeway incident detection by introducing some new measures to reduce false alarms in developing a new incident detection model. The model consists of the 5 major components through which a series of decision makings in determining the given traffic flow condition are made. The decision making process was designed such that the causes of traffic congestions can be accurately classified into several types including incidents and bottlenecks according to their unique characteristics. The model performance was tested and found to be compatible with that of the existing well-recognized models in terms of the detection rate and detection time. It should noted that the model produced much less false alarms than most of the existing models. The study results prove that the initial objective of the study was satisfied as it was an experimental trial to improve the false alarm rate for the incident detection model to be more pactically usable for traffic management purposes.

• Journal of Korea Port Economic Association
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• v.25 no.3
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• pp.385-406
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• 2009

The volume of trade between Korea and China has been growing significantly year by year since the diplomatic relations have been established in 1992. The economic and logistics cooperation between the two countries is crucial not only for the development of their economic relations but for promotion of value-added logistics. However there are still huge and serious impediments to logistics network and management between the two countries including bottlenecks in transport and customs procedures. The purpose of this study is to investigate how to promote value added logistics activities between Korea and Shandong Province of China. It is suggested the ways to increase VAL activities such as enhanced division of international labour within industries, provision of comprehensive logistics service and establishment of strategy for supply chain management between the two countries.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.85-92
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• 2015

As computer game maps get more elaborate, path-finding by using $A^*$ algorithm in grid-based game maps becomes bottlenecks of the overall game performance. It is because the search space becomes large as the number of nodes increases with detailed representation in cells. In this paper we propose an efficient pathfinding method in which the computer game maps in a regular grid is converted into the polygon-based representation of the list of vertices and then the visibility information about vertices of polygons can be utilized. The conversion to the polygon-based map does not give any effect to the real-time query process because it is preprocessed offline. The number of visited nodes during search can be reduced dramatically by designing heuristics using visibility information of vertices that make the accuracy of the estimation enhanced. Through simulations, we show that the proposed methods reduce the search space and the search time effectively while maintaining the advantages of the grid-based method.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.244-253
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• 2021

This study examined how the fire evacuation induction service system using a smartphone navigation application in the event of a fire affects the fire evacuation time, and the following conclusions were drawn. 1. The evacuation time was reduced by 22 seconds when the navigation application was used in computer scenario simulation. Even in the demonstration simulation, the evacuation time was reduced by 40 seconds when the navigation application was used. This indicates that the navigation application is effective in shortening the evacuation time in case of fire. 2. As a result of the demonstration scenario simulation, the time until the end of evacuation was 39 seconds faster in the case of evacuation guidance than in the case where it was not conducted. 3. No bottlenecks occurred in the evacuation route during the demonstration scenario simulation. As a result, there was a difference in the time required to complete the evacuation between the computer scenario simulation and the demonstration scenario simulation.

• Journal of Construction Engineering and Project Management
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• v.9 no.2
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• pp.1-24
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• 2019

Poor project performance has been noted as the bane in the construction industry globally. This paper sought to investigate, by way of literature, the performance patterns of construction projects in Kenya since independence (1963-2018). This was informed by reports of undesirable project performance in the industry. This descriptive study used available studies previously done in this subject area. In sum, literature is replete with evidence on a myriad of challenges facing the execution of projects. The study established that generally, the project performance is poor and has assumed a chronic trajectory spanning over five decades. On average, the findings reveal that 35-60% of projects initiated in Kenya face cost overruns while time overrun is most severe with 35-73% projects overrunning their schedule. In addition, the findings problematize the issue of plurality of performance measurement regimes in the construction industry. Here, it was observed that no singular construct exists to objectively measure the various facets that constitute the 'health' of a project. This paper has contributed to the body of knowledge by examining the performance patterns in Kenya for over fifty years while at the same time identifying the bottlenecks inherent in projects execution. Importantly, the conceptual performance efficiency framework derived in the current study presents a paradigm shift in the monitoring and evaluation of projects. To this end, an in-depth analysis is recommended on the interaction of efficiency enablers in the buildup of performance efficiency index (PEI). Similarly, a further inquiry is recommended on the integration and impact of the proposed framework in the management of projects.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.70-85
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• 2021

Deep learning methodology, which has been actively studied in recent years, has improved the performance of artificial intelligence. Accordingly, systems utilizing deep learning have been proposed in various industries. In traffic systems, spatio-temporal graph modeling using GNN was found to be effective in predicting traffic speed. Still, it has a disadvantage that the model is trained inefficiently due to the memory bottleneck. Therefore, in this study, the road network is clustered through the graph clustering algorithm to reduce memory bottlenecks and simultaneously achieve superior performance. In order to verify the proposed method, the similarity of road speed distribution was measured using Jensen-Shannon divergence based on the analysis result of Incheon UTIC data. Then, the road network was clustered by spectrum clustering based on the measured similarity. As a result of the experiments, it was found that when the road network was divided into seven networks, the memory bottleneck was alleviated while recording the best performance compared to the baselines with MAE of 5.52km/h.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.51-61
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• 2008

This paper suggests a new way to implement high speed AES on Intel Core2 processors and AMD Athlon64 processors, which are used all over the world today. First, Core2 Processors of EM64T architecture's memory-access-instruction processing efficiency are lower than calculus-instruction processing efficiency. So, previous AES implementation techniques, which had a high rate of memory-access-instruction, could cause memory-bottleneck. To improve this problem we present the partial round key techniques that reduce the rate of memory-access-instruction. The result in Intel Core2Duo 3.0 Ghz Processors show 185 cycles/block and 2.0 Gbps's throughputs in ECB mode. This is 35 cycles/block faster than bernstein software, which is known for being the fastest way. On the other side, in AMD64 processors of AMD64 architecture, by removing bottlenecks that occur in decoding processing we could improve the speed, with the result that the Athlon64 processor reached 170 cycles/block. The result that we present is the same performance of Matsui's unpublished software.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.92-97
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• 2021

The importance of processes in cryogenic environments is increasing in a way to address problems such as critical dimension (CD) narrow and bottlenecks in micro-processing. Accordingly, in this paper, we proceed with the design and analysis of Electrostatic Chuck(ESC) and Coolant in cryogenic environments, and present optimal model conditions to provide the temperature distribution analysis of ESC in these environments and the appropriate optimal design. The wafer temperature uniformity was selected as the reference model that the operating conditions of the refrigerant of the liquid nitrogen in the doubled aluminum path were excellent. Design of simulation (DOS) was carried out based on the wheel settings within the selected reference model and the classification of three mass flow and diameter case, respectively. The comparison between factors with p-value less than 0.05 indicates that the optimal design point is when five turns of coolant have a flow rate of 0.3 kg/s and a diameter of 12 mm. ANOVA determines the interactions between the above factor, indicating that mass flow is the most significant among the parameters of interests. In variable selection procedure, Case 2 was also determined to be superior through the two-Sample T-Test of the mean and variance values by dividing five coolant wheels into two (Case 1 : 2+3, Case 2: 3+2). Finally, heat transfer analysis processes such as final difference method (FDM) and heat transfer were also performed to demonstrate the feasibility and adequacy of the analysis process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1835-1845
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• 2021

To accurately identify black ice and warn the drivers of information in advance so they can control speed and take preventive measures. In this paper, we propose a lightweight black ice detection network based on infrared road images. A black ice recognition network model based on CNN transfer learning has been developed. Additionally, to further improve the accuracy of black ice recognition, an enhanced lightweight network based on MobileNetV2 has been developed. To reduce the amount of calculation, linear bottlenecks and inverse residuals was used, and four bottleneck groups were used. At the same time, to improve the recognition rate of the model, each bottleneck group was connected to a 3×3 convolutional layer to enhance regional feature extraction and increase the number of feature maps. Finally, a black ice recognition experiment was performed on the constructed infrared road black ice dataset. The network model proposed in this paper had an accurate recognition rate of 99.07% for black ice.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.8-13
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• 2021

The purpose of this study is to propose a throughput costing as a performance measurement tool to measure cost indicators, which are one of the indicators for evaluating organizational performance in a smart factory manufacturing environment. An empirical study by questionnaire was conducted, and 60 experts were surveyed to verify the hypothesis. As a result of the study, it was concluded that the information provided based on throughput costing is helpful in cost measurement and in evaluating organizational performance efficiency and effectiveness, and it was confirmed that this method has usefulness to support the planning and control process. It is proposed that the use of throughput costing by constraint theory, which can maximize throughput and optimize inventory levels in the manufacturing process, can find solutions to bottlenecks affecting the efficiency and effectiveness of organizational performance.