• World Technopolis Review
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• 제7권2호
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• pp.125-134
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• 2018

The purpose of this article is to introduce and describe the case of Fukuoka Next-generation Social System Creation Hub based on the conceptual framework of regional innovation platform strategy. In short, it is a "government-issued" regional innovation platform strategy to improve innovativeness with limited creative capital through "borrowing" not money but network, wisdom, know-how, and ideas from each other between some stakeholder groups in a region. The Fukuoka Industry, Science & Technology Foundation, which is the coordinating institution of the whole program, plays the role of a platformer to unify various projects into the program crossing borders between stakeholder groups for building regional innovation platforms that lends intensive support to feedback loops between the program facilitator and its partners in the program. Thanks to being a government-issued one, it could be tied together with some wide ranging issues of policy on social innovations, such as the "low carbon society" or the "health and longevity society." But at the same time, it is a concern that many regional research institutions that have innovative potential and diverse ideas become governed by the platform without their noticing it and dealt with in the same way based on "selected" and "designated" strategic goals. Therefore, it seems that a regional innovation platform strategy is a kind of "double-edged sword" in public policy in the era of "panopticism of bureaucratic society" in Japan.

• 한국컴퓨터정보학회논문지
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• 제16권9호
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• pp.115-122
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• 2011

무선 센서 네트워크는 제한된 에너지를 갖는 배터리에 의해 가동되며 한번 배치되면 사용자가 접근할 수 없고 배터리 교환이 불가능하다. 따라서 네트워크의 수명을 늘리기 위하여 네트워크 디자인 시에 에너지 효율성이 매우 중요하게 고려되어야 한다. BCDCP 기법에서는 모든 센서가 CH(클러스터 헤드)로 데이터를 보내고 CH는 BS(베이스 스테이션)로 취합된 데이터를 송신하는 효율적 클러스터링 프로토콜이지만 규모가 큰 네트워크에서는 적합하지 않으며 노드들의 물리적 위치를 고려하지 않기 때문에 효율성이 떨어진다. UCR 기법의 경우 BS에와 노드들의 거리만을 고려하기 때문에 BS에 가까운 노드가 빨리 죽는 문제가 있다. 본 논문에서는 균형된 에너지 소비를 통하여 네트워크 수명을 늘리기 위한 삼각모양 클러스터 라우팅 프로토콜(TSCRP- Triangular Shape Cluster Routing Protcol)을 제안한다. 본 기법은 비교적 간단하게 운영되기 때문에 헤드 선출에 필요한 오버헤드가 적고 센서들의 에너지 보유량뿐만이 아니라 센서들과 BS간의 거리를 유기적으로 결합하여 리더 노드를 선정하기 때문에 다른 기법에 비해 효율적이다. 실험에 의하면 TSCRP가 LEACH, BCDCP, UCR보다 우수한 것으로 나타났다.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2341-2350
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• 2012

Face detection is the first step of vision-based driver fatigue detection method. Traditional face detection methods have problems of high false-detection rates and long detection times. A space-time restrained Adaboost method is presented in this paper that resolves these problems. Firstly, the possible position of a driver's face in a video frame is measured relative to the previous frame. Secondly, a space-time restriction strategy is designed to restrain the detection window and scale of the Adaboost method to reduce time consumption and false-detection of face detection. Finally, a face knowledge restriction strategy is designed to confirm that the faces detected by this Adaboost method. Experiments compare the methods and confirm that a driver's face can be detected rapidly and precisely.

• 대한전기학회논문지:전력기술부문A
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• 제55권12호
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• pp.514-521
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• 2006

The existing ULTC operation control strategy based on the measured data deteriorates the voltage compensation capability making the efficient corresponding to the load variation difficult by following the fixed load center point voltage. Accordingly, this paper proposes a new on-line fuzzy ULTC controller based on the designed multiple load center points which can improve the voltage compensation capability of ULTC and minimize voltage deviation by moving in real-time the load center point according to the load variation to an adequate position among the multiple load center points designed using the clustering technique. The Max-Min distance technique is adopted as the clustering technique for the decision of multiple load points from measured MTr load current and PTr voltage, and the minimum distance classifier is adopted for the decision of fuzzy output membership function. To verify the effectiveness of the proposed strategy, Visual C++ MFC-based simulation environments is developed. Finally, the superiority the proposed strategy is proved by comparing the fuzzy ULTC operation control results based on multiple load center points with the existing ULTC operation control results based on fixed load center point using the data for three day.

• Journal of Mechanical Science and Technology
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• 제19권4호
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• pp.993-1000
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• 2005

A vehicle cruise control strategy designed based on human drivers driving characteristics has been investigated. Human drivers driving patterns have been investigated using vehicle driving test data obtained from 125 participants. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would feel comfortable to the human driver. Vehicle following charac­teristics of the cruise controlled vehicle have been investigated using real-world vehicle driving test data and a validated simulation package.

• 한국자동차공학회논문집
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• 제10권6호
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• pp.227-233
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• 2002

A vehicle longitudinal control strategy with guaranteed string stability for vehicle stop-and-go(SG) cruise control is presented in this paper. The SG cruise control systems should be designed such that string stability can be guaranteed in addition to that every vehicle in a string of SG cruise control vehicles must track any bounded acceleration and velocity profile of its preceding vehicle with a bounded spacing and velocity error. An optimal vehicle following control law based on the information of the 1311owing distance (clearance) and its velocity relative to the vehicle ahead (relative velocity) has been used and string stability analysis has been done based on the control law and constant time gap spacing policy, A validated multi-vehicle simulation package has been shown that the string stability analysis using the approximate model of the vehicle servo-loop which includes vehicle powertrain and brake control system dynamics is valid in the design of the SG cruise control law with guaranteed string stability.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1998년도 추계학술대회 및 정기총회
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• pp.17-20
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• 1998

The purpose of this paper is to develop a port simulation program for Inchon Port. The arrival and departure data from Inchon Port are analyzed, several probability density functions for the interval time and service time are estimated, and the berthing rules are constructed based on experts experiences. The port simulation program is written in visual basic considering the interarrival p.d.f., service rate p.d.f., berthing rules, and dual-dock system, and is used to analyze the effects of the changes in ship arrival rate and service rate upon the demurrage. It is expected that we can use the simulation results in order to prepare proper service level and to evaluate the appropriate investment strategy to be planned.

• 한국정보기술학회 영문논문지
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• 제9권1호
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• pp.77-87
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• 2019

The Butterfly model, which aims to solve contradiction problems, defines the type of contradiction for given problems and finds the problem-solving objectives and their strategies. Unlike the ARIZ algorithm in TRIZ, the Butterfly model is based on logical proposition, which helps to reduce trial and errors and quickly narrows the problem space for solutions. However, it is hard for problem solvers to define the right propositional relations in the previous Butterfly algorithm. In this research, we propose a contradiction solving algorithm which determines the right problem-solving strategy just with yes or no simple questions. Also, we implement the Butterfly Chatbot based on the proposed algorithm that provides visual and auditory information at the same time and help people solve the contradiction problems. The Butterfly Chatbot can solve contradictions effectively in a short period of time by eliminating arbitrary alternative choices and reducing the problem space.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.604-615
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• 2019

Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.