• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.173-178
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• 2013

To discover objects of interest in unstructured peer-to-peer networks, the peers rely on flooding query messages which create incredible network traffic. This article evaluates the performance of an unstructured Gnutella-like protocol over mobile ad-hoc networks and proposes modifications to improve its performance. This paper offers an enhanced mechanism for an unstructured Gnutella-like network with improved peer features to better meet the mobility requirement of ad-hoc networks. The proposed system introduces a novel caching optimization technique and enhanced ultrapeer selection scheme to make communication more efficient between peers and ultrapeers. The paper also describes an enhanced query mechanism for efficient searching by applying multiple walker random walks with a jump and replication technique. According to the simulation results, the proposed system yields better performance than Gnutella, XL-Gnutella, and random walk in terms of the query success rate, query response time, network load, and overhead.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.457-458
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• 2007

We investigated a resistor network model for the horizontal AlInGaN LED. Adding the proposed current density dependent relative quantum efficiency, the power simulation can be also obtained. Comparing the simulation and the measurement results for the LED with the size of $350{\mu}m$, the model is reasonable to simulate the forward voltage and the light output power. Using this model we investigated the optimization of the position and the number of the finger electrodes in a given chip area. It shows that the center disposition of the p-finger electrode in p-area is optimal for the voltage and best for the power. And the minimum number of the n-finger electrodes is best for the power.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2142-2149
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• 2002

Contacting with ground in the post-card area size only, tire supports entire automobile weight. As well, it characterizes most of automobile running performance. Among the design parameters, the carcass contour becomes a key design factor. This paper deals with the time-effective optimal design of tire crown contour in order to improve the tire wear performance by employing a back-propagation neural network model.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.448-450
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• 2003

인터넷 프로토콜의 이동성 지원(Mobile IP)은 단말의 이동성(host mobility)뿐만 아니라 네트워크의 이동성(network mobility)까지도 지원하도록 확장되고 있다. 그러나 이동 네트워크(mobile network)의 내부에 이동 단말(mobile host) 또는 이동 네트워크가 존재하는 경우와 칼이 중첩된 이동 네트워크(nested mobile network)의 경우 데이터가 전송되는 경로가 삼각형 또는 그 이상으로 복잡해지는 Triangular Routing 또는 Pinball Routing 문제가 발생하게 된다. 본 논문에서는 대응 단말(Correspondent node) 또는 Home Agent에서 위치 정보가 갱신(Binding Update)되는 과정을 재귀적으로 수행하게 함으로써 중첩된 이동 네트워크에서 최적의 경로로 데이터를 전달할 수 있도록 하는 방법을 제시한다.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.443-450
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• 2021

The study is devoted to the formation of a economic principles cargo delivery management in global supply chains. Mathematical model of delivering special categories of goods by road is a key element of these principles. The article analyzes the existing studies on solving the problem of cargo delivery in various aspects. It was noted that the greatest attention is paid to legal regulation, last mile delivery, optimization of routes and delivery schemes, information support, technological innovations, cluster routing, etc. In the developed mathematical model a minimum of total costs of forming loading units and freight shipments was defined as the criterion of optimality of organizing delivery by motor transport. The authors propose the creation of logistics clusters allowing the integration of urban transport flows and global supply chains.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1289-1302
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• 2019

In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

• Journal of Navigation and Port Research
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• v.43 no.5
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• pp.273-280
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• 2019

This study developed an optimization model, defined as the IPS (Itinerary for Passenger Satisfaction), for a cruise ship to identify an itinerary that maximizes passenger satisfaction. A 0-1 integer programming model was developed to provide an optimal sequence of ports of call, assigning a destination to each day of the cruise. The concepts of the destination access network and the neighborhood of a destination were designed and manipulated to organize the complex network of destinations so that each next destination is selected within a practical overnight sail. The developed model can also be viewed as a reduced variant of the traveling salesperson problem with less constraints. A set of example tests shows that practical scenarios of the IPS with moderate cruise duration can be easily solved with light computation loads. Considering cruise ship passengers usually make their decisions not relying on only one destination but on an itinerary in its entirety, the purpose of this study was to identify itinerary alternatives to attract potential cruise passengers for attaining maximum occupancy level.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.67-72
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• 2021

Wireless sensor networks (WSNs) require an enormous number of sensor nodes (SNs) to maintain processing, sensing, and communication capabilities for monitoring targeted sensing regions. SNs are generally operated by batteries and have a significantly restricted energy consumption; therefore, it is necessary to discover optimization techniques to enhance network lifetime by saving energy. The principal focus is on reducing the energy consumption of packet sharing (transmission and receiving) and improving the network lifespan. To achieve this objective, this paper presents a novel improved energy-efficient cluster-based routing protocol (IECRP) that aims to accomplish this by decreasing the energy consumption in data forwarding and receiving using a clustering technique. Doing so, we successfully increase node energy and network lifetime. In order to confirm the improvement of our algorithm, a simulation is done using matlab, in which analysis and simulation results show that the performance of the proposed algorithm is better than that of two well-known recent benchmarks.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.1-8
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• 2022

Supporting real-time flows with delay and throughput constraints is an important challenge for future wireless networks. In this paper, we develop an optimal scheduling scheme to optimally choose the packets to transmit. The optimal transmission strategy is based on an observable Markov decision process. The novelty of the work focuses on a priority-based probabilistic packet scheduling strategy for efficient packet transmission. This helps in providing guaranteed services to real time traffic in Heterogeneous Wireless Networks. The proposed scheduling mechanism is able to optimize the desired performance. The proposed scheduler improves the overall end-to-end delay, decreases the packet loss ratio, and reduces blocking probability even in the case of congested network.

• ETRI Journal
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• v.44 no.2
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.