• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.

• International Journal of Control, Automation, and Systems
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• 제5권5호
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• pp.570-576
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• 2007

This paper presents a hexagon-based Q-leaning algorithm to find a hidden targer object with multiple robots. An experimental environment was designed with five small mobile robots, obstacles, and a target object. Robots went in search of a target object while navigating in a hallway where obstacles were strategically placed. This experiment employed two control algorithms: an area-based action making (ABAM) process to determine the next action of the robots and hexagon-based Q-learning to enhance the area-based action making process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1044-1047
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• 2005

In this paper, we present the strategy of object search for distributed autonomous robotic systems (DARS). The DARS are the systems that consist of multiple autonomous robotic agents to whom required functions are distributed. For instance, the agents should recognize their surrounding at where they are located and generate some rules to act upon by themselves. In this paper, we introduce the strategy for multiple DARS robots to search a hidden object at the unknown area. First, we present an area-based action making process to determine the direction change of the robots during their maneuvers. Second, we also present Q learning adaptation to enhance the area-based action making process. Third, we introduce the coordinate system to represent a robot's current location. In the end of this paper, we show experimental results using hexagon-based Q learning to find the hidden object.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.264-269
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• 2006

This paper presents the strategy for searching a hidden object in an unknown area for using by multiple distributed autonomous robotic systems (DARS). To search the target in Markovian space, DARS should recognize th ε ir surrounding at where they are located and generate some rules to act upon by themselves. First of all, DARS obtain 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to research for a target object while navigating in a un known hallway where some obstacles were placed. In the end of this paper, we present the results of three algorithms - a random search, an area-based action making process to determine the next action of the robot and hexagon-based Q-learning to enhance the area-based action making process.

• 한국지능시스템학회논문지
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• 제18권3호
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• pp.291-296
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• 2008

본 논문에서는 군집로봇시스템에서 목표물 추적을 위하여 SVM을 이용한 12각형 기반의 Q-learning 알고리즘을 제안한다. 제안한 알고리즘의 유효성을 보이기 위해 본 논문에서는 여러 대의 로봇과 장애물 그리고 하나의 목표물로 정하고, 각각의 로봇이 숨겨진 목표물을 찾아내는 실험을 가정하여 무작위, DBAM과 AMAB의 융합 모델, 마지막으로는 본 논문에서 제안한 SVM과 12각형 기반의 Q-learning 알고리즘을 이용하여 실험을 수행하고, 이 3가지 방법을 비교하여 본 논문의 유효성을 검증하였다.

• 대한임베디드공학회논문지
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• 제3권2호
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• pp.119-125
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• 2008

This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.

• Journal of Information Technology Applications and Management
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• 제30권6호
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• pp.1-15
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• 2023

With the advent of the Fourth Industrial Revolution, propelled by digital technology, we are transitioning into an era of hyperconnectivity, where everything and objects are becoming interconnected. A smart supply chain refers to a supply chain system where various sensors and RFID tags are attached to objects such as machinery and products used in the manufacturing and transportation of goods. These sensors and tags collect and analyze process data related to the products, providing meaningful information for operational use and decision-making in the supply chain. Before the spread of COVID-19, the fundamental principles of supply chain management were centered around 'cost minimization' and 'high efficiency.' A smart supply chain overcomes the linear delayed action-reaction processes of traditional supply chains by adopting real-time data for better decision-making based on information, providing greater transparency, and enabling enhanced collaboration across the entire supply chain. Therefore, in this study, a hierarchical model for building a smart supply chain was constructed to systematically derive the importance of key factors that should be strategically considered in the construction of a smart supply chain, based on the major factors identified in previous research. We applied AHP (Analytical Hierarchy Process) techniques to identify urgent improvement areas in smart SCM initiatives. The analysis results showed that the external supply chain integration is the most urgent area to be improved in smart SCM initiatives.

• Journal of Obesity & Metabolic Syndrome
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• 제27권4호
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• pp.213-222
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• 2018

Bariatric surgery has evolved from a surgical measure for treating morbid obesity to an epochal remedy for treating metabolic syndrome as a whole, which is represented by type 2 diabetes mellitus. Numerous clinical trials have advocated bariatric or metabolic surgery over nonsurgical interventions because of markedly superior metabolic outcomes in morbidly obese patients who satisfy traditional criteria for bariatric surgery (body mass index [BMI] >$35kg/m^2$) and in less obese or simply overweight patients. Nevertheless, not all diabetes patients achieve the most desirable outcomes; i.e., diabetes remission after metabolic surgery. Thus, candidates for metabolic surgery should be carefully selected based on comprehensive preoperative assessments of the risk-benefit ratio. Predictors for diabetes remission after metabolic surgery may be classified into two groups based on mechanism of action. The first is indices for preserved pancreatic beta-cell function, including younger age, shorter duration of diabetes, and higher C-peptide level. The second is the potential for an insulin resistance reduction, including higher baseline BMI and visceral fat area. Several prediction models for diabetes remission have been suggested by merging these two to guide the joint decision-making process between clinicians and patients. Three such models, DiaRem, ABCD, and individualized metabolic surgery scores, provide an intuitive scoring system and have been validated in an independent external cohort and can be utilized in routine clinical practice. These prediction models need further validation in various ethnicities to ensure universal applicability.

• 한국산업융합학회 논문집
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• 제26권1호
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• pp.1-14
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• 2023

To secure national future competitiveness, the Korean government announced the 『National Ultra-High Performance Computing (HPC) Innovation Strategy (2021.5.28.)』 and set three innovation strategy goals throughout establishing an innovation ecosystem. This study presented a heterogenous data-based strategic support framework that allowed to understand both the current status of domestic & foreign R&D areas and domestic industrial economy areas in terms of strategic fields related to ultra-high performance computing, and the empirical research was conducted in the life science and public health area. The HPC innovation ecosystem platform based on the connection of heterogeneous data (domestic R&D project-technology-industry-overseas R&D project) presented in this study provided useful and essential information that allowed establishing a specific action plan for the national HPC innovation strategy and contributing to vitalizing the innovation ecosystem. Since the evidence-based policy assumes that a more reasonable consensus is reached through a non-biased decision- making process among stakeholders, the proposed platform may contribute to enhancing policy momentum by increasing legitimacy and trust of planning of the national HPC strategy.

• 인터넷정보학회논문지
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• 제22권6호
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• pp.99-113
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• 2021

최근 육·해·공·우주에 이어 제 5전장 영역으로 사이버공간이 인식되면서 본격적으로 사이버공간을 작전 및 임무 영역으로 보는 활동에 관심이 집중되었다. 또한, 21세기는 4세대 전쟁방식으로 사이버공간을 기반으로 하는 사이버작전이 전개되고 있다. 이러한 환경에서 작전 수행은 지휘관의 의사결정에 따라 성공 여부가 판가름 된다. 따라서 이러한 의사결정의 합리성과 객관성을 높이기 위해서 체계적으로 방책(COA, Course Of Action)을 수립하고 선정하는 과정이 필요하다. 본 연구에서는 사이버작전 수행에 필요한 작전요소들을 분류하는 방안을 통하여 방책을 수립하고, 방책의 정량적 평가가 가능하다는 방향성을 제시하고자 한다. 이를 위해 작전 수행의 방책이 되는 사이버 작전요소 조합(COES, Cyber Operational Elements Set)을 구성하고 표적개발 과정에서 식별한 사이버 작전요소를 육하원칙(5W1H Method)을 기준으로 분류하는 방안을 제시한다. 또한 스턱스넷(STUXNET) 공격 사례에서 활용된 사이버 작전요소들을 제시한 분류 방안을 적용하여 사이버 작전요소 조합(COES)을 구성해 공격 방책들을 수립한다. 마지막으로 수립한 방책의 우선순위를 부여하고 최적의 방책 선정을 위해 방책의 정량적 평가를 수행하였다.