• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2319-2337
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• 2019

In this paper, we study the distributed cooperative caching for Internet content providers in a small cell of heterogeneous network (HetNet). A general framework based on bankruptcy game model is put forth for finding the optimal caching policy. In this framework, the small cell and different content providers are modeled as bankrupt company and players, respectively. By introducing strategic decisions into the bankruptcy game, we propose a caching value assessment algorithm based on analytic hierarchy process in the framework of bankruptcy game theory to optimize the caching strategy and increase cache hit ratio. Our analysis shows that resource utilization can be improved through cooperative sharing while considering content providers' satisfaction. When the cache value is measured by multiple factors, not just popularity, the cache hit rate for user access is also increased. Simulation results show that our approach can improve the cache hit rate while ensuring the fairness of the distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.19-27
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• 2016

Maritime transport is now regarded as one of the main contributors to global climate change by virtue of its $CO_2$ emissions. Meanwhile, slow steaming, i.e., slower ship speed, has become a common practice in the maritime industry so as to lower $CO_2$ emissions and reduce bunker fuel consumption. The practice raised various operational decision issues in terms of shipping companies: how much ship speed is, how much to bunker the fuel, and at which port to bunker. In this context, this study addresses an operation problem in a shipping companies, which is the problem of determining the ship speed, bunkering ports, and bunkering amount at the ports over a given ship route to minimize the bunker fuel and ship time costs as well as the carbon tax which is a regulatory measure aiming at reducing $CO_2$ emissions. The ship time cost is included in the problem because slow steaming increases transit times, which implies increased in-transit inventory costs in terms of shippers. We formulate the problem as a nonlinear lot-sizing model and suggest a Lagrangian heuristic to solve the problem. The performance of the heuristic algorithm is evaluated using the data obtained from reliable sources. Although the problem is an operational problem, the heuristic algorithm is used to address various strategic issues facing shipping companies, including the effects of bunker prices, carbon taxes, and ship time costs on the ship speed, bunkering amount and number of bunkering ports. For this, we conduct sensitivity analyses of these factors and finally discuss study findings.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.121-135
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• 2007

Constraint directed scheduling techniques, representing problem constraints explicitly and constructing schedules by constrained heuristic search, have been successfully applied to real world scheduling problems that require satisfying a wide variety of constraints. However, there has been little basic research on the representation and optimization of the objective value of a schedule in the constraint directed scheduling literature. In particular, the cost objective is very crucial for enterprise decision making to analyze the effects of alternative business plans not only from operational shop floor scheduling but also through strategic resource planning. This paper aims to explicitly represent and optimize the total cost of a schedule including the tardiness and inventory costs while satisfying non-relaxable constraints such as resource capacity and temporal constraints. Within the cost based scheduling framework, a cost propagation algorithm is presented to update cost information throughout temporal constraints within the same job.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.111-116
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• 2019

New technologies such as the IoT, Big Data, and Artificial Intelligence, starting from the Web, mobile, and smart device, enable new business models that did not exist before, and various types of Internet companies based on these business models has been emerged. In this research, we examine the factors that influence the success and failure of Internet companies. To do this, we review the recent studies on business model and examine the variables affecting the success of Internet companies in terms of network effect, user interface, cooperation with actors, creating value for users. Using the five derived variables, we will select 14 Internet companies that succeeded and failed in seven commercial business model categories. We derive decision tree by applying inductive learning based on ID3 algorithm to the analysis result and derive rules that affect success and failure based on derived decision tree. With these rules, we want to present the strategic implications for actors to succeed in Internet companies.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.502-509
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• 2023

This study presents a satellite constellation method that achieves optimal revisit performance by utilizing genetic algorithm techniques. The Walker method is a global coverage concept, and there are limitations to target-centered constellation considering the strategic environment of the Korean Peninsula. To overcome these limitations, targets are set in major areas of interest in North Korea, orbit elements with optimal revisit performance for each target are searched, and based on this, the number of satellites optimized for each target is derived using a genetic algorithm. The results of this study demonstrate the performance of the optimized constellation by applying phasing rules to achieve the desired revisit performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.96-108
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• 2017

The current collision warning and avoidance system(CWAS) is one of the representative Advanced Driver Assistance Systems (ADAS) that significantly contributes to improve the safety performance of a vehicle and mitigate the severity of an accident. However, current CWAS mainly have focused on preventing a forward collision in an uninterrupted flow, and the prevention performance near intersections and other various types of accident scenarios are not extensively studied. In this paper, the safety performance of Vision-Sensor (VS) and Radar-Sensor(RS) - based collision warning systems are evaluated near an intersection area with the data from Naturalistic Driving Study(NDS) of Second Strategic Highway Research Program(SHRP2). Based on the VS and RS data, we newly derived sixteen vehicle-to-vehicle accident scenarios near an intersection. Then, we evaluated the detection performance of VS and RS within the derived scenarios. The results showed that VS and RS can prevent an accident in limited situations due to their restrained field-of-view. With an accident prevention rate of 0.7, VS and RS can prevent an accident in five and four scenarios, respectively. For an efficient accident prevention, a different system that can detect vehicles'movement with longer range than VS and RS is required as well as an algorithm that can predict the future movement of other vehicles. In order to further improve the safety performance of CWAS near intersection areas, a communication-based collision warning system such as integration algorithm of data from infrastructure and in-vehicle sensor shall be developed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.21-32
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• 2006

The license plate recognition (LPR) unit consists of the following core components: plate region segmentation, individual character extraction, and character recognition. Out of the above three components, accuracy in the performance of plate region segmentation determines the overall recognition rate of the LPR unit. This paper proposes an algorithm for segmenting the license plate region on the front or rear of a vehicle in a fast and accurate manner. In the case of the proposed algorithm images are captured on the spot where unmanned monitoring of illegal parking and stowage is performed with a variety of roadway environments taken into account. As a means of enhancing the segmentation performance of the on-the-spot-captured images of license plate regions, the proposed algorithm uses a mathematical model for license plate colors to convert color images into digital data. In addition, this algorithm uses Gaussian smoothing and double threshold to eliminate image noises, one-pass boundary tracing to do region labeling, and MBR to determine license plate region candidates and extract individual characters from the determined license plate region candidates, thereby segmenting the license plate region on the front or rear of a vehicle through a verification process. This study contributed to addressing the inability of conventional techniques to segment the license plate region on the front or rear of a vehicle where the frame of the license plate is damaged, through processing images in a real-time manner, thereby allowing for the practical application of the proposed algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.75-96
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• 2016

This paper investigates the usefulness of drones in an urban delivery system. We define the vehicle and drone routing problem with time window (VDRPTW) and present a model that can describe a dual mode delivery system consisting of drones and vehicles in the metropolitan area. Drones are relatively free from traffic congestion but have limited flight range and capacity. Vehicles are not free from traffic congestion, and the complexity of urban road network reduces the efficiency of vehicles. Using drones and vehicles together can reduce inefficiency of the urban delivery system because of their complementary cooperation. In this paper, we assume that drones operate in a point-to-point manner between the depot and customers, and that customers in the need of fast delivery are willing to pay additional charges. For the experiment datasets, we use instances of Solomon (1987), which are well known in the Vehicle Routing Problem society. Moreover, to mirror the urban logistics demand trend, customers who want fast delivery are added to the Solomon's instances. We propose a hybrid evolutionary algorithm for solving VDRPTW. The experiment results provide different useful insights according to the geographical distributions of customers. In the instances where customers are randomly located and in instances where some customers are randomly located while others form some clusters, the dual mode delivery system displays lower total cost and higher customer satisfaction. In instances with clustered customers, the dual mode delivery system exhibits narrow competition for the total cost with the delivery system that uses only vehicles. In this case, using drones and vehicles together can reduce the level of dissatisfaction of customers who take their cargo over the time-window. From the view point of strategic flexibility, the dual mode delivery system appears to be more interesting. In meeting the objective of maximizing customer satisfaction, the use of drones and vehicles incurs less cost and requires fewer resources.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.1-7
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• 2010

Network Centric Warfare(NCW) is becoming a prominent concept in the current trend of warfare. To support high quality communication between strategic/tactical units in the concept of NCW, Tactical Airborne Networks are likely to be constructed in the near future to take part in the NCW. In these Tactical Airborne Networks with dynamic topology variations due to very high mobility of participants nodes, more efficient and reliable neighbor discovery protocols are needed. This paper presents the adaptive HELLO message scheduling algorithm for Tactical Airborne Network using directional antennas. The purposed algorithm can reduce the overhead of periodic HELLO message transfer, while guaranteeing successful data transmission. We concluded a mathematical analysis and simulation studies using Qualnet 4.5 for evaluation the performance and efficiency of the proposed scheme.