• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.29-48
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• 2019

Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.727-732
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• 2015

These days, many researchers are working on Future Internet and a new networking paradigm called Software Defined Networking draws a great attention. In this paper, we redefine Software Defined Networking as Service Defined Networking which means that packets are categorized according to types of services. By using Service Defined Networking, we are not only dealing with the way to utilize the network resources efficiently but we also propose an algorithm to minimize the waiting time for packets to be delivered. This proposed algorithm can solve the delay problem, one of the most significant problems caused by network congestion. Also, since we are adopting Service Defined Networking, network resource utilization can be improved compared to the existing network.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.149-157
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• 2018

In this paper, we propose an attack detection technology using SDN Controller to study security threats in IoT environment. The research methodology has been developed by applying IoT security threat management technology to the IoT layer and analyzing the research trend of applied security technology. The study results show that the effectiveness of the detection method using the sampling method is studied by adding OpenFlow based SDN Controller to the network switch equipment of the existing IoT network. This method can detect the monitoring and attack of the whole network by interworking with IDS and IPS without affecting the performance of existing IoT devices. By applying such improved security threat countermeasure technology, we expect to be able to relieve anxiety of IoT security threat and increase service reliability.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.165-171
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• 2019

The study of the computer architecture has shown that major improvements in price-to-energy performance stems from domain-specific hardware development. This paper analyzes the tensor processing unit (TPU) ASIC which can accelerate the reasoning of the artificial neural network (NN). The core device of the TPU is a MAC matrix multiplier capable of high-speed operation and software-managed on-chip memory. The execution model of the TPU can meet the reaction time requirements of the artificial neural network better than the existing CPU and the GPU execution models, with the small area and the low power consumption even though it has many MAC and large memory. Utilizing the TPU for the tensor flow benchmark framework, it can achieve higher performance and better power efficiency than the CPU or CPU. In this paper, we analyze TPU, simulate the Python modeled OpenTPU, and synthesize the matrix multiplication unit, which is the key hardware.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.7
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• pp.778-787
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• 1999

이제까지 대부분의 다중 에이전트 시스템에서는 에이전트 사회에 속한 모든 응용 에이전트를 작업 요청에 관계없이 처음부터 구동시킨다고 가정하였다. 이러한 에이전트 정적 구동 방법은 에이전트 관리를 단순하게 해주는 이점을 제공하지만 워크플로우 관리나 전자상거래와 같이 매우 많은 수의 에이전트로 구성되는 응용 분야에서는 시스템 과부하와 자원의 낭비 등 많은 문제점을 초래한다. 동적 에이전트 관리는 이에 대한 해결책으로 아주 많은 수의 에이전트를 포함하는 다중 에이전트 시스템에서 현재 수행중인 작업에 관련된 에이전트만을 선별하여 구동시키고, 작업이 끝난 에이전트는 종료시킴으로써 자원의 낭비를 막고 에이전트간의 상호작용 시에 요구되는 에이전트 통신의 복잡도 부담을 감소시키는 효과를 낸다. 본 논문에서는 자바로 에이전트 관리 시스템을 구현하고, 이 관리 시스템을 통해 각기 다른 언어로 개발된 응용 에이전트가 분산된 환경에서 상호 협력을 통해 작업을 수행할 수 있는 기법을 제안한다. 사용자나 다른 에이전트의 요청으로 에이전트를 동적으로 수행시키기 위해 다른 언어로의 확장을 가능하게 하는 Java Native Interface(JNI)를 사용한 기술 및 이러한 이질적인 에이전트간의 원활한 통신을 위해서 KQML 언어 인터페이스를 통한 통신 기능을 제안한다. 이질적 에이전트의 동적 관리를 가능하게 함으로써 다중 에이전트 시스템의 자원 이용 효율성과 확장성을 높이고 다양한 환경 변화에 대한 적응성과 개선된 협동능력을 제공한다.Abstract It has been assumed that all application agents in a multi-agent system are pre-invoked and remain active regardless of whether they are actually used. Although this kind of static agent invocation simplifies the management of agents, it causes several problems such as the system overload and a waste of resources, especially in the areas of the workflow management and the electronic commerce that consist of tens and even hundreds of application agents. A solution for these problems is the scheme of dynamic agent management that selectively invokes only agents that are actually requested and terminates them when they are no longer needed. This method prevents a waste of system resources and alleviates the complexity of agent communications.This paper proposes an agent management system implemented in Java that supports interactions between application agents that are developed using different languages. Dynamic agent invocation is accomplished by Java Native Interface(JNI) that links two heterogeneous methods, and by KQML language interface that facilitates the communications between heterogeneous agents. This scheme of dynamic agent management provides efficient resource usage, easy extensibility, dynamic adaptibility to changes in the environment, and improved cooperation.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.