• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.173-187
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• 2018

This paper proposes a computer vision and deep learning-based technique for surveillance camera system for vehicle counting as one part of parking lot management system. We applied the You Only Look Once version 2 (YOLOv2) detector and come up with a deep convolutional neural network (CNN) based on YOLOv2 with a different architecture and two models. The effectiveness of the proposed architecture is illustrated using a publicly available Udacity's self-driving-car datasets. After training and testing, our proposed architecture with new models is able to obtain 64.30% mean average precision which is a better performance compare to the original architecture (YOLOv2) that achieved only 47.89% mean average precision on the detection of car, truck, and pedestrian.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.909-920
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• 2003

Nowadays, IT for CRM has been growing and developed rapidly. Typical techniques are statistical analysis tools, on-line multidimensional analytical processing (OLAP) tools, and data mining algorithms (such neural networks, decision trees, and association rules). Among customer data, web log data is very important and to use these data efficiently, applying OLAP technology to analyze multi-dimensionally. To make OLAP cube, we have to precalculate multidimensional summary results in order to get fast response. But as the number of dimensions and sparse cells increases, data explosion occurs seriously and the performance of OLAP decreases. In this paper, we presented why the web log data sparsity occurs and then what kinds of sparsity patterns generate in the two and t.he three dimensions for OLAP. Based on this research, we set up the multidimensional data models and query models for benchmark with each sparsity patterns. Finally, we evaluated the performance of three OLAP systems (MS SQL 2000 Analysis Service, Oracle Express and C-MOLAP).

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.284-291
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• 2021

As the current security monitoring system is operated as a passive system only for response after an attacker's attack, it is common to respond to intrusion incidents after an attack occurs. In particular, when new assets are added and actual services are performed, there is a limit to vulnerability testing and pre-defense from the point of view of an actual hacker. In this paper, a new security monitoring model has been proposed that uses multiple hacking-related search engines to add proactive vulnerability response functions of protected assets. In other words, using multiple search engines with general purpose or special purpose, special vulnerabilities of the assets to be protected are checked in advance, and the vulnerabilities of the assets that have appeared as a result of the check are removed in advance. In addition, the function of pre-checking the objective attack vulnerabilities of the protected assets recognized from the point of view of the actual hacker, and the function of discovering and removing a wide range of system-related vulnerabilities located in the IP band in advance were additionally presented.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.1-8
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• 2022

In this paper, we propose a fire detection system based on CCTV images using an object tracking technology with YOLOv4 model capable of real-time object detection and a DeepSORT algorithm. The fire detection model was learned from 10800 pieces of learning data and verified through 1,000 separate test sets. Subsequently, the fire detection rate in a single image and fire detection maintenance performance in the image were increased by tracking the detected fire area through the DeepSORT algorithm. It is verified that a fire detection rate for one frame in video data or single image could be detected in real time within 0.1 second. In this paper, our AI fire detection system is more stable and faster than the existing fire accident detection system.

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.471-478
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• 2003

Traditionally,, analysis, simulation and measurement have all been used to evaluate the performance of network protocols and functional entities that support mobile wireless service. Simulation methods are useful for testing the complex systems which have the very complicate interactions between components. To develop a mobile call simulator which is used to examine, validate, and predict the performance of mobile wireless call procedures must have the teletraffic model, which is to describe the mobile communication environments. Mobile teletraffic model is consists of 2 sub-models, traffic source and network traffic model. In this paper, we analyzed the network traffic data which are gathered from selected Base Stations (BSs) to define the mobile teletraffic model. We defined 4 types of cell location-Residential, Commercial, Industrial, and Afforest zone. We selected some Base Stations (BSs) which are represented cell location types in Seoul city, and gathered real data from them And then, we present the call rate per hour, cail distribution pattern per day, busy hours, loose hours, the maximum number of call, and the minimum number of calls based on defined cell location types. Those parameters are very important to test the mobile communication system´s performance and reliability and are very useful for defining the mobile network traffic model or for working the existed mobile simulation programs as input parameters.

• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.61-69
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• 2019

In this paper, we propose a multisensory(i.e., visual-auditory-tactile) based AR system for the education of cultural heritage. The proposed system provides a multisensory interaction by designing a user to experience with a 3D printed artifact which is mapped by a virtual 3D content of digital heritage. Compared with the existing systems of cultural heritage education based on augmented reality(AR) technology, this system focused on not only providing learning experience via a sense of visual and auditory, but also a sense of tactile. Furthermore, since this systems mainly provided the direct interactions using a 3D printed model, it gives a higher degree of realism than existing system that use touch or click motions on a 2D display of mobile phones and tablets. According to a result of user testing, we concluded that the proposed system delivered the excellent presence and learning flow to users. Particularly, from the usability evaluation, a 3D printed target artifact which is similar in shape to original heritage artifact, achieved the highest scores among the various tested targets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.39-47
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• 2020

The fire protection system for high-rise buildings is currently confined to the preparation of sprinklers, emergency stairs, and exit and monitoring systems. On the other hand, an integrated system, including the model with scenario-based actions, is required for effective fire protection. An integrated fire protection system is needed to operate and manage the total cycle of the fire protection. In this study, an integrated fire protection system, which included sensing and consequent processes related to fire emergencies, was designed and implemented. The designed scheme can gather and analyze the data of the production, operation, and consumption patterns as it integrates fire protection systems for fire fighters and evacuating people. The integrated fire protection technology and system, which has target performance with satisfied 1/2 sec transaction response time and 1.2 transactions per second, is expected to contribute to market creation in converged technology-based fire protection fields.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.9
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• pp.419-428
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• 2017

In an embedded system, modules exchange data by interacting among themselves. Exchanging erroneous resource data among modules may lead to execution errors. The interacting resources produce dependencies between the two modules where any change of the resources by one module affects the functionality of another module. Several investigations of the embedded systems show that interaction faults between the modules are one of the major cause of critical software failure. Therefore, interaction testing is an essential phase for reducing the interaction faults and minimizing the risk. The direct and indirect interactions between the modules generate interaction faults. The direct interaction is the explicit call relation between the modules, and the indirect interaction is the remaining relation that is made underneath the interface that possesses data dependence relationship with resources. In this paper, we investigate the errors that are based on the indirect interaction between modules and introduce a new test criterion for identifying the errors that are undetectable by existing approaches at the integration level. We propose a novel approach for generating the interaction model using the indirect interaction pattern and design test criteria that are based on different interaction errors to generate test cases. Finally, we use the fault injection technique to evaluate the feasibility and effectiveness of our approach.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.67-80
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• 2000

Distributed cooperative information system is the one that has various knowledge sources as well as problem solving capabilities to get information in a distributed and heterogeneous data environment. In a distributed cooperative information system. a control mechanism to facilitate the available information is very important. and usually the role of the control mechanism determines the behavior of the total system In this research. we proposed a model of the distributed cooperative information system which is based on the multi-agent paradigm. We also implemented a test system to show l its feasibility. The proposed system makes the knowledge sources into agents and a special agent called 'facilitator' controls the cooperation between the knowledge agents The facilitator uses the knowledge granularity level to determine the sequence of the activation of the agents. In other words. the knowledge source with simple but fast processing mechanism activates first while more sophisticated but slow knowledge sources are activated late. In an environment in which we have several knowledge sources for the same topic. the proposed system will simulate the focusing mechanism of human cognitive process.