• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.175-184
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• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.434-442
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• 2012

Several gateway selection schemes have been proposed that select gateway nodes based on a single Quality of Service (QoS) path parameter, for instance path availability period, link capacity or end-to-end delay, etc. or on multiple non-QoS parameters, for instance the combination of gateway node speed, residual energy, and number of hops, for Mobile Ad hoc NETworks (MANETs). Each scheme just focuses on the ment of improve only a single network performance, i.e., network throughput, packet delivery ratio, end-to-end delay, or packet drop ratio. However, none of these schemes improves the overall network performance because they focus on a single QoS path parameter or on set of non-QoS parameters. To improve the overall network performance, it is necessary to select a gateway with stable path, a path with themaximum residual load capacity and the minimum latency. In this paper, we propose a gateway selection scheme that considers multiple QoS path parameters such as path availability period, available capacity and latency, to select a potential gateway node. We improve the path availability computation accuracy, we introduce a feedback system to updated path dynamics to the traffic source node and we propose an efficient method to propagate QoS parameters in our scheme. Computer simulations show that our gateway selection scheme improves throughput and packet delivery ratio with less per node energy consumption. It also improves the end-to-end delay compared to single QoS path parameter gateway selection schemes. In addition, we simulate the proposed scheme by considering weighting factors to gateway selection parameters and results show that the weighting factors improve the throughput and end-to-end delay compared to the conventional schemes.

• IE interfaces
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• v.17 no.4
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• pp.472-481
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• 2004

In this paper, we propose a linear programming model of supply planning process for the supply chain collaboration strategy of a company. The amount of its supplying quantity relies on outsourcing suppliers heavily. Conversely, the revenues of those suppliers are highly dependent on the supplying quota from the supply network planning of the company. In order to keep the supply stable through collaboration, the company builds such a policy to guarantee the fairness on revenue between the supplies. For this, the supply network plan should keep the capacity utilization ratio even for all the suppliers. But the production capacities are different and the distribution of molds is disproportional through suppliers, so the supply network plan is not easily established with simple arithmetic processes. Therefore, we developed the linear programming model with those target function and constraints minimizing the costs for holding inventory and penalty of delayed delivery, simultaneously guaranteeing the even capacity utilization through suppliers. The proposed model has been applied to real case and the evaluation for the planning result from the model would be followed in order to make sure that our model guarantee on extracting the supply network plan subordinated to the policy. Also we mention about further studies for improvement of the model.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.323-328
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• 2005

Bridge structures are properly designed in accordance with the design specifications with required safety margin. However, due to the heavy vehicle traffic and environmental attacks, bridge often requires repairs and the deteriorated one should be replaced or rehabilitated. In this paper, a prior ranking algorithm is proposed to assist a decision making process in bridge management at network level. Based on the literature survey for the existing studuies, two important factors which affect the decision making procedure for bridge management at network level are identified. These factors are implemented into the algorithm as a load carrying capacity function and traffic function, respectively.

• Journal of muscle and joint health
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• v.11 no.1
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• pp.74-87
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• 2004

Purpose: This study aims to analyze the outcome of exercise programs for Rheumatoid Arthritis patients and its tendency with network analysis. Method: 30 articles from Medline search of foreign nursing journals(1966-2002) and 5 from three Korean nursing journals(1970-2002) were surveyed. The contents analyses were focused on outcome measures and network analysis of exercise programs. Results: Exercise programs result in improving muscle strength(91.7%), aerobic capacity(72.9%), and 50 feet walk time(57.3%). Among several exercises, water exercise, and Tai-chi are in the middle of weight-bearing exercises. In the experimental design, non-randomized control trials were 40%, and the functional status of subjects were not classified in 40% of the articles surveyed. Conclusion: Considering the results, muscle strength, aerobic capacity, and 50 feet walk time were tested as valid outcome measures. Tai-chi exercise could be recommended as proper exercise for Rheumatoid arthritis patients because of its low intensity of weight-bearing exercise. In terms of research methods, the randomized trials and functional classifications of rheumatoid arthritis should be done more strictly.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.563-568
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• 2013

The purpose of this study is to find the analytic solution for determining the optimal capacity (lot-size) of a batch-storage network to meet the finished product demand under infrequent shutdowns. Batch processes are bound to experience random but infrequent operating time losses. Two common remedies for these failures are duplicating another process or increasing the process and storage capacity, both of which are very costly in modern manufacturing systems. An optimization model minimizing the total cost composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units is pursued with the framework of a batch-storage network of which flows are susceptible to infrequent shutdowns. The superstructure of the plant consists of a network of serially and/or parallel interlinked batch processes and storage units. The processes transform a set of feedstock materials into another set of products with constant conversion factors.A novel production and inventory analysis method, the PSW (Periodic Square Wave) model, is applied. The advantage of the PSW model stems from the fact it provides a set of simple analytic solutions in spite of a realistic description of the material flow between processes and storage units. The resulting simple analytic solution can greatly enhance a proper and quick investment decision at the early plant design stagewhen confronted with diverse economic situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.81-92
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• 1997

The purpose of this paper is to develop a method of paramatric analysis that can be applied to an optimal solution of a maximum flow problem. We first define the transformed network corresponding to a given network. In such a network, we conduct paramatric analysis by determining changes in the optimal solution precipitated by changes in the capacity as the arc capacity varies from 0 to infinite. By this method we can easily calculate not only the characteristic region where the given optimal solution remains unchanged, but also the characteristic region where the value of the maximal flow gradually increases or decreases. The proposed method is demonstrated by numerical example.

• ETRI Journal
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• v.42 no.1
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• pp.36-45
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• 2020

A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.7-10
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• 2005

Ad hoc MAC protocols using directional antennas can be used to improve the network capacity. Directional antennas have a Deafness problem and decrease throughput of the network caused by increasing backoff duration. Dual channel protocols have been proposed to mitigate the Deafness and hidden node problems. In this paper, we propose a dual channel MAC protocol using a directional antenna to mitigate the Deafness problem and increase the network capacity. The performance of the proposed Ad hoc MAC protocol is confirmed by computer simulations using Qualnet ver. 3.8 simulator.