• IEIE Transactions on Smart Processing and Computing
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• 제6권3호
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3865-3883
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• 2016

Infrastructure as a Service (IaaS) encapsulates computer hardware into a large amount of virtual and manageable instances mainly in the form of virtual machine (VM), and provides rental service for users. Currently, VM anomaly incidents occasionally occur, which leads to performance issues and even downtime. This paper aims at detecting anomalous VMs based on performance metrics data of VMs. Due to the dynamic nature and increasing scale of IaaS, detecting anomalous VMs from voluminous correlated and non-Gaussian monitored performance data is a challenging task. This paper designs an anomaly detection framework to solve this challenge. First, it collects 53 performance metrics to reflect the running state of each VM. The collected performance metrics are testified not to follow the Gaussian distribution. Then, it employs independent components analysis (ICA) instead of principal component analysis (PCA) to extract independent components from collected non-Gaussian performance metric data. For anomaly detection, it employs multi-class Bayesian classification to determine the current state of each VM. To evaluate the performance of the designed detection framework, four types of anomalies are separately or jointly injected into randomly selected VMs in a campus-wide testbed. The experimental results show that ICA-based detection mechanism outperforms PCA-based and LDA-based detection mechanisms in terms of sensitivity and specificity.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1664-1670
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• 1991

For kinematically redundant manipulators, conventional dynamic control methods of local torque optimization showed the instability which resulted in physically unachievable torque requirements. In order to guarantee stability of the null space vector method which resolves redundancy at the acceleration level, Maciejewski[1] analyzed the kinetic behavior of homogeneous solution component and proposed the condition to identify regions of stability and instability for this method. 'In this paper, a modified null space vector method is first presented based on the Maciejewski's condition which is a function of a manipulator's configuration. Secondly, a new control method which is based on the concept of aspects is proposed. It was shown by computer simulations that the modified null space vector method and the proposed method have a common property that a preferred aspect is preserved during the execution of a task. It was also illustrated that both methods demonstrate a drastic reduction of torque loadings at the joints in the tracking motion of a long trajectory when compared with the null space vector method, and thus guarantee the stability of joint torque.

• 한국게임학회 논문지
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• 제5권1호
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• pp.33-40
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• 2005

게임개발 프로젝트의 설계는 프로세스 구성과 게임 소프트웨어의 프로그램 산출물과 태스크의 관리는 개발자간에 연계하여 구성해야 한다. 기존 개임개발 프로젝트 설계는 프로젝트 활동의 정의 및 변경을 지원하고, 형상관리 도구는 버전제어, 작업공간 관리, 빌드 관리 등을 지원한다. 본 논문의 설계도구는 UML을 사용하여 게임 컴포넌트 기반 개발 프로세스 모델을 설계하고, 프로세스의 진행 상태 기록, 변경 요청에 따른 처리, 태스크별 작업 진행 보고서 작성, 산출물 등록과 변경, 버전 기록, 산출물 또는 서식 검색 등의 기능을 연구하였다. 또한 시스템 설계를 사용함으로써 게임 공학 활동에 참여하는 개발자들이 분산 개발 환경에서 게임 소프트웨어 개발에 필요한 정보와 산출물 관리를 생산성 있게 할 수 있다. 이 시스템 구성에 따라 정보를 공유하면서 설계의 체계화 및 표준화를 수행 할 수 있다.

• 한국도서관정보학회지
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• 제48권3호
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• pp.281-302
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• 2017

본 연구는 두 집단간에 복잡한 정보검색임무를 수행하는 동안 이용자의 정신상태의 차이점을 살펴보고자 하였다. 실험과 질문지를 통해서 데이터를 수집하고 분석하였고, 그 결과 정신적요구를 받은 참여자들이 안받은 참여자들보다 검색 중 생각을 더 많이 한 것으로 보이고, 부정적인 감정표현을 더 자주 한 것으로 보이고, 노력을 덜 한 것으로 보이며, 검색수행능력이 훼방을 받은 것으로 드러났다. NASA-TLX의 검사결과는 정신적요구, 수행능력, 좌절감에서 주요한 차이를 보이는 것으로 나타났다. 이러한 연구결과는 인터페이스 디자인이나 정보검색 시스템등의 개발에 도움을 줄 것으로 기대한다.

• 한국군사과학기술학회지
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• 제15권3호
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• pp.322-333
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, Radar Resource Management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed a rule-based scheduling algorithm and Simulated Annealing(SA) based scheduling algorithm, which are alternatively selected and applied to beam scheduler according radar load status in real-time. The performance of the proposed algorithm was evaluated on the multi-function radar scenario. As a result, we showed that our proposed algorithm can process a lot of beams at the right time with real time capability, compared with applying only rule-based scheduling algorithm. Additionally, we showed that the proposed algorithm can save scheduling time remarkably, compared with applying only SA-based scheduling algorithm.

• 기술사
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• 제32권1호
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• pp.122-141
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• 1999

Groupware is a new emerging research field, involving increasing numbers of institutions in the USA, Europe, and Asia such as Korea and Japan, etc., as an interdisciplinary research and development area with a strong computer science component. It grew from fairly unsystematic attempts by various developers to generate software that would increase the competence of people working together. This in turn was partly a response to: failures of and problems inherited from Office Automation and Management Information System ; some sociological intuitions about ways people might work together; and a search for uses of new interfacing, networking, and multi-media technologies. In this paper, groupware that has been configured to meet the needs of groups at work is defined as computer-based systems which support working groups of people engaged in common task in a shared environment. The basic concepts, origin, and historic research of the groupware are described. Specially, groupware relies on the approaches and contributions of many disciplines in computer science as well as sociology that is concerning human, social, and cultural activities. So, nine key disciplines of them upon which successful groupware depends are described briefly. Some state-of-the-art implementations and developments are reviewed through classifying and analyzing the current available groupware applications in the field or market.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.590-593
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• 2004

Extraction of ocean surface current velocity offers important physical oceanographic parameters especially on understanding ocean environment. Although Remote Sensing techniques were highly developed, the investigation of ocean surface current using Synthetic Aperture Radar (SAR) is not an easy task. This paper presents the results of ocean surface current observation using Doppler Centroid of ERS-1 SAR data obtained off the coast of Korea peninsula. We employed the concept, in which Doppler frequency shift and the ocean surface current are closely related, to evaluate ocean surface current. Moving targets cause Doppler frequency shift of the back scattered radar waves of SAR, thus the line-of-sight velocity component of the scatters can be evaluated. The Doppler frequency shift can be measured by estimating the difference between Doppler Centroid of raw SAR data and reference Doppler Centroid. Theoretically, the Doppler Centroid is zero; however, squinted antenna which is affected by several physical factors causes Doppler Centroid to be nonzero. The reference Doppler Centroid can be obtained from measurements of sensor trajectory, attitude and Earth model. The estimated Doppler Centroid was compensated by considering the accurate attitude estimation of ERS-1 SAR. We could verify the correspondence between the estimated ocean surface current and observed in-situ data in the error bound.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.126-129
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• 2006

The marine environment is under considerable threat from intentional or accidental oil spills, ballast water discharged, dredging and infilling for coastal development, and uncontrolled sewage and industrial wastewater discharges. Monitoring spills and illegal oil discharges is an important component in ensuring compliance with marine protection legislation and general protection of the coastal environments. For the monitoring task an image processing system is needed that can efficiently perform the detection and the tracking of oil spills and in this direction a significant amount of research work has taken place mainly with the use of radar (SAR) remote sensing data. In this paper the level set image segmentation technique was tested for the detection of oil spills. Level set allow the evolving curve to change topology (break and merge) and therefore boundaries of particularly intricate shapes can be extracted. Experimental results demonstrated that the level set segmentation can be used for the efficient detection and monitoring of oil spills, since the method coped with abrupt shape’s deformations and splits.

• 한국전문물리치료학회지
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• 제5권2호
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• pp.39-46
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• 1998

Thumb adduction is an abnormal pattern typically noted in children with spastic cerebral palsy. This abnormal pattern can limit hand function, specifically in the type and quality of prehension pattern used and in the coordination of release. This ABAB single-subject research was designed to examine the effects of short thumb opponens splint on hand function in cerebral palsy. The subject was a 4 years and 8 months old boy with right upper extremity spasticity. The child was fitted with a short thumb opponens splint, which was worn for 8 hours per day during the daytime. Two different measures were used: (a) prehension component scores; (b) Bruininks-Oseretsky test of motor proficiency. Data was collected three times a week for 10 weeks. Visual analysis of data indicate that after the application of a short thumb opponens splint, improvements were noted in the prehension pattern and fine motor functional task. The results of this study suggest that short thumb opponens splint may prove efficaciousness in the treatment of the child with cerebral palsy.