• Journal of KIISE:Databases
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• v.33 no.2
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• pp.151-162
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• 2006

RDF Semantics, one of W3C Recommendations, provides the RDFS entailment rules, which are used for the RDFS inference. Sesame, which is well known RDF repository, supports the RDBMS-based RDFS inference using the forward-chaining strategy. Since inferencing in the forward-chaining strategy is performed in the data loading time, the data loading time in Sesame is slow down be inferencing. In this paper, we propose the order scheme for applying the RDFS entailment rules to improve inference performance. The proposed application order makes the inference process terminate without repetition of the process for most cases and guarantees the completeness of inference result. Also the application order helps to reduce redundant results during the inference by predicting the results which were made already by previously applied rules. In this paper, we show that our approaches can improve the inference performance with comparisons to the original Sesame using several real-life RDF datasets.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.143-160
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• 2001

Micro-simulation models have been recognized as an efficient assessment tool in developing traffic signal control technologies. In this paper a prototype of a microscopic simulation model which can be applied to evaluate the performance of traffic-adaptive signal control strategies was developed. In the simulation process, space-based arrays were appled to estimate parameters of car following and lane changing models. Two levels of link types, a micro-type and macro-type links, were also embodied in the simulation process. The proposed model was tested on a test network consists of 9 intersections. The performance of the proposed model was evaluated in link by link comparisons with the results of NETSIM. The results show that the proposed model could appropriately simulate traffic flows of the test network. The model also produces traffic adaptive signal timings, cycle lengths and green times for turning movements, based on the detector data. It implies that the optimization process of the model produces reasonable signal timings for the test network on the cycle basis.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.207-216
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• 2002

This paper present a design and implementation of a distributed audio, Video stream service framework based on CORBA for efficient processing and control of audio/video stream. We design software components which support processing, control and transmission of audio/video streams as distributed objects. For optimization of stream transmission performance, we separate the transmission path of control data and media data. Distributed objects are defined by IDL and implemented using JAVA. And device dependent facilities like media capturing, playing and communication channels are implemented using JMF (Java Media Framework) components. We show a connection establishment and control procedure of streams communication. And for evaluation, we implement a test system and experiment a system performance. Our experiments show that test system has somewhat longer connection latency time compared to TCP connection establishment, but has optimized media transmission time compared to CORBA IIOP. Also test system show acceptable service quality of media transmission.

• Journal of KIBIM
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• v.9 no.3
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• pp.19-29
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• 2019

Currently, BIPV (Building Integrated Photovoltaic) design technology lacks analysis function at the planning stage, and there is a lack of understanding and reliability of BIPV design method and system for building designers. To design and consider various building integrated solar design alternatives, the color of building integrated solar is often monotonous or does not match the design direction of the building. In this study, architectural designers can select various color modules in the planning and design process of the building and analyze the characteristics of color module solar cells and compare and analyze the actual solar radiation and predicted solar radiation in Republic ofKorea Seoul to reduce the confusion of design methods. By building a BIM design integrated system that can prove the quality of the building and analyze the shading analysis and power generation performance architecturally, it can improve the reliability of color module solar cell applicability that can express aesthetics in buildings and the predicted solar power generation capacity of each region. In the initial design stage, based on the empirical data of the BIPV system, it is possible to analyze the power generation performance for each installation angle and installation direction by analyzing the surrounding environment and the installation area, and accurately determine the appropriateness of the design accordingly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.1-19
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• 2021

The graph-based tag recommendation algorithm FolkRank can effectively utilize the relationships between three entities, namely users, items and tags, and achieve better tag recommendation performance. However, FolkRank does not consider the internal relationships of user-user, item-item and tag-tag. This leads to the failure of FolkRank to effectively map the tagging behavior which contains user neighbors and item neighbors to a tripartite graph. For item-item relationships, we can dig out items that are very similar to the target item, even though the target item may not have a strong connection to these similar items in the user-item-tag graph of FolkRank. Hence this paper proposes an improved FolkRank algorithm named FolkRank++, which fully considers the user-user and item-item internal relationships in tag recommendation by adding the correlation information between users or items. Based on the traditional FolkRank algorithm, an initial weight is also given to target user and target item's neighbors to supply the user-user and item-item relationships. The above work is mainly completed from two aspects: (1) Finding items similar to target item according to the attribute information, and obtaining similar users of the target user according to the history behavior of the user tagging items. (2) Calculating the weighted degree of items and users to evaluate their importance, then assigning initial weights to similar items and users. Experimental results show that this method has better recommendation performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1632-1638
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• 2020

In this paper, we investigate a multi-beam satellite communication system where multiple terminals transmit information signals to the gateway via a satellite. The satellite is equipped with phased array antennas to form multiple spot beams of which bandwidths are not identically allocated. We formulate an optimization problem to maximize fairness of beam bandwidth allocation. In order to solve the problem, we propose two heuristic algorithms; iterative beam bandwidth allocation (IBBA) and request ratio-based beam bandwidth allocation (RRBBA) algorithms. The IBBA algorithm iteratively equalizes the ratio of allocated bandwidth of each beam to their resource request while the RRBBA algorithm allocates beam bandwidth calculated from the ratio. Simulation results show that the IBBA algorithm has close fairness performance to the optimum while the RRBBA algorithm has less performance than the IBBA algorithm at the price of reduced computational complexity.

• Korean Journal of Construction Engineering and Management
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• v.23 no.6
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• pp.21-29
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• 2022

Productivity estimation of construction operations is crucial to successful project delivery. Especially in the preconstruction phase, the adequacy and effectiveness of plans directly affect the actual performance of operations. Currently, productivity estimation is conducted by referring to existing references such as the Construction Standard Production Rate. However, it is difficult to promptly apply changing conditions of operations when using such references. Moreover, it is difficult to deduce the optimal combination of construction machinery for the given condition. This paper presents a simple simulation model that can be used to generate productivity data that considers site conditions and construction equipment combination. The suggested method is expected to be used as a decision making assisting tool for practitioners who rely on estimations using the Construction Standard Production Rate when establishing construction plans using heavy machinery such as backhoes, loaders and dumptrucks.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.156-163
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• 2015

This paper presents a new framework for design and economic evaluation of wind energy-based electricity supply system. We propose a network optimization (mixed-integer linear programming) model to design the underlying energy supply system. In this model we include practical constraints such as land limitations of onshore wind farms and different costs of offshore wind farms to minimize the total annual cost. Based upon the model, we also analyze the sensitivity of the total annual cost on the change of key parameters such as available land for offshore wind farms, required area of a wind turbine and the unit price of wind turbines. We illustrate the applicability of the suggested model by applying to the problem of design of a wind turbines-based electricity supply problem in Jeju. As a result of this study, we identified the major cost-drivers and the regional cost distribution of the proposed system. We also comparatively analyzed the economic performance of on/off shore wind farms in wind energy-based electricity supply system of Jeju.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.37-45
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• 2015

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures: the extraction of information from signals and the estimation of emitter location. Various algorithms based on CAF(complex ambiguity function), which is known as a basic method, has been presented in the area of extractions. When we extract TDOA and FDOA information using a conventional method based on the CAF algorithm from communication signals, considerably long integration time is required for the accurate position estimation of an unknown emitter far from sensors more than 300 km. Such long integration time yields huge amount of transmission data from sensors to a central processing unit, resulting in heavy computiational complexity. Therefore, we theoretically analyze the integration time for TDOA/FDOA information using CRLB and propose a two-stage global optimization algorithm which can minimize the transmission time and a computational complexity. The proposed method is compared with the conventional CAF-based algorithms in terms of a computational complexity and the CRLB to verify the estimation performance.