• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.58-61
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• 2002

In this paper, we present a new generalized k-Tree-based (CU/PE) allocation model to perform dynamic resource (CU/PE) allocation/deallocation decision for the reconfigurable MSIMD/MIMD multi-dimensional (k-D) mesh-connected architectures. Those reconfigurable multi-SIMD/MIMD systems allow dynamic modes of executing tasks, which are SIMD and MIMD. The MIMD task requires only the free sub-system; however the SIMD task needs not only the free sub-system but also the corresponding free CU. In our new k-Tree-based (CU/PE) allocation model, we introduce two best-fit heuristics for the CU allocation decision: 1) the CU depth first search (CU-DFS) in O(kN$_{f}$ ) time and 2) the CU adjacent search (CU-AS) in O(k2$^{k}$ ) time. By the simulation study, the system performance of these two CU allocation strategies was also investigated. Our simulation results showed that the CU-AS and CU-DFS strategies performed the same system performance when applied for the reconfigurable MSIMD/MIMD 2-D and 3-D mesh-connected architectures.

• Journal of Advanced Research in Ocean Engineering
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• 제3권3호
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Journal of Information Processing Systems
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• 제5권4호
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• pp.175-186
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• 2009

Power consumed by modern computer systems, particularly servers in data centers has almost reached an unacceptable level. However, their energy consumption is often not justifiable when their utilization is considered; that is, they tend to consume more energy than needed for their computing related jobs. Task scheduling in distributed computing systems (DCSs) can play a crucial role in increasing utilization; this will lead to the reduction in energy consumption. In this paper, we address the problem of scheduling precedence-constrained parallel applications in DCSs, and present two energy- conscious scheduling algorithms. Our scheduling algorithms adopt dynamic voltage and frequency scaling (DVFS) to minimize energy consumption. DVFS, as an efficient power management technology, has been increasingly integrated into many recent commodity processors. DVFS enables these processors to operate with different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. Our algorithms effectively balance these two performance goals using a novel objective function and its variant, which take into account both goals; this claim is verified by the results obtained from our extensive comparative evaluation study.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권5호
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• pp.370-377
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• 2010

지능 로봇은 복잡하고 동적인 환경 내에서 상황의 변화에 적절히 적응하여 사용자에게 다양한 서비스를 제공하는 지능 시스템이다. 따라서 로봇은 행위를 수행하는 동안 지속적으로 상황의 변화를 감지하여 변화에 적절히 반응해야 하며 주어진 상황에 대해 최선의 행위를 결정하여 수행할 수 있어야 한다. 또한 때때로 임의의 행동을 결정하여 보다 지능적인 행위를 수행할 수 있어야 한다. 본 논문에서는 이러한 지능 로봇의 복잡한 행위를 효과적으로 정의하고 구현하기 위해 Structured Circuit Semantics(SCS)에 기초를 둔 프로그래밍 언어(Structured Programming for Reactive Intelligent Tasks, SPRIT)와 SPRIT으로 작성된 프로그램을 다양한 로봇 환경에서 실행하고 검증하기 위한 작업 실행기(Task Executor)를 제시한다.

• 한국통신학회논문지
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• 제31권4A호
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• pp.393-401
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• 2006

배터리로 동작하는 휴대용 임베디드 시스템에서 에너지 소모는 중요한 설계 파라미터이며, 동적 전력 관리는 잘 알려진 저전력 설계 기법중의 하나이다. 본 논문에서는 실시간 시스템에서 에너지를 고려한 태스크 스케줄링 알고리듬을 제안한다. 제안한 스케줄링 알고리듬은 시스템에 여유 시간이 존재할 경우 장치 중첩도가 높은 태스크가 우선적으로 수행되도록 스케줄링 하여 장치의 전력 상태 전환 횟수를 줄여준다. 전력 상태 전환 횟수가 줄어들 경우 상태 전환에 따른 전력 소모가 감소하고, 동적 전력 관리의 기회를 더욱 얻을 수 있다. 실험 결과 EDF 알고리듬으로 동작 하는 시스템에서 동적 전력 관리를 한 경우와 비교하였을 때 에너지 소모가 약 23% 감소하였다.

• 한국정밀공학회지
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• 제24권7호
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• pp.133-138
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• 2007

It is important to understand the characteristics of amputee gait to develop more advanced prostheses. The aim of this study was quantitatively to analyze the stair climbing task for the above-knee amputee with a prosthesis and to predict muscle forces and joint moments at musculoskeletal joints by dynamic analysis. The three-dimensional musculoskeletal model of lower extremities was constructed by gait analysis and transformation software for one above-knee amputee and ten healthy people. The measured ground reaction forces and kinematical data of each joint by gait analysis were used as input data during inverse dynamic analysis. Lastly, dynamic analysis of above-knee amputee during stair climbing were performed using musculoskeletal models. The results showed that summed muscle farces of hip extensor of amputated leg were greater than those of sound leg but the opposite results were revealed at hip abductor and knee flexor of amputated leg. We could also find that the higher moments at hip and knee joint of sound leg were needed to overcome the flexion moment caused by body weight and amputated leg. In conclusion, dynamic analysis using musculoskeletal models may be a useful mean to predict muscle forces and joint moments for specific motion tasks related to rehacilitation therapy..

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권2호
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• pp.91-99
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• 2013

An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

• 대한수학교육학회지:학교수학
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• 제11권2호
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• pp.281-299
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• 2009

본 논문에서는 동적조작 환경 속에서 이루어지는 물리적 실험을 도구로 선택하여 발명되고 있는 과정으로서의 수학을 학생들이 접할 수 있도록 1) 정의 도입 방식을 변화시켜 의미 있는 수학적 정의를 만들어내는 2) 시각화를 통한 연속성 사고 능력을 강화하는 3) 발견과 탐구를 통하여 수학을 만들어내는 4) 문제를 제기하고 일반화하는 능력을 강화하는 사례들을 제시하고 분석함으로써 수학교과과정에 어떻게 동적조작 환경을 융합시킬 수 있는가를 보였다. 이러한 교수-학습 환경 하에서 발생할 수 있는 문제점을 분석하고, 이러한 문제점을 해결하기 위한 교사의 역할에 대해 논하였다.

• 한국멀티미디어학회논문지
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• 제7권7호
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• pp.886-895
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• 2004

본 논문에서는 멀티미디어 태스크와 경성 실시간 태스크가 공존하는 시스템에서 두 태스크들을 효율적으로 통합하고 스케쥴링하기 위한 CPU 대역폭의 동적 할당 기법이 제시된다. 연성 실시간적인 멀티미디어 태스크는 평균 실행 시간을 기반으로 처리되는 반면 경성 실시간 태스크는 최악의 경우에 대한 실행 시간을 기반으로 실행이 보장된다. 서버를 기반으로 하는 본 논문의 할당 기법은 CPU 대역폭을 두 태스크들에 대하여 분할한 후 특히 MPEG 비디오 스트림을 위한 멀티미디어 태스크들에 대하여는 할당된 대역폭을 다시 동적으로 조정한다. 제시된 기법의 목적은 시스템에 존재하는 경성 실시간 태스크들의 시간적 제약성을 모두 보장하면서 멀티미디어 태스크들의 종료시한이후 실행이 지연되는 시간을 최소화하는 것이다. 본 논문에서는 시뮬레이션 실험을 통하여 제시된 기법에서 멀티미디어 태스크들의 지연 시간이 다른 기법에 비하여 작아지는 결과를 보여주고 있다.