• IE interfaces
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• v.17 no.spc
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• pp.141-151
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• 2004

As today's business environment has become more and more competitive, forward as well as backward flows of products among members belonging to a supply chain have been increased. The backward flows of products, which are common in most industries, result from increasing amount of products that are returned, recalled, or need to be repaired. Effective management for the backward flows of products has become an important issue for businesses because of opportunities for simultaneously enhancing profitability and customer satisfaction from returned products. Since third party logistics service providers (3PLs) are playing an important role in reverse logistics operations, they should perform two simultaneous logistics operations for a number of different clients who want to improve their logistics operations for both forward and reverse flows. In this case, distribution networks have been independently designed with respect to either forward or backward flows so far. This paper proposes a mixed integer programming model for the design of network integrating both forward and reverse logistics. Since the network design problem belongs to a class of NP-hard problems, we present an efficient heuristic algorithm based on genetic algorithm (GA), of which the performance is compared to the lower bound by Lagrangian relaxation. Finally, the validity of proposed algorithm is tested using numerical examples.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.688-695
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• 2014

In a small wireless environment, such as your home or office, a various network using WiMedia PHY can be mixed. Because these networks operate independently for each application, data conflict can occur between adjacent networks. To avoid data conflict, the resource in a different time zone can be utilized. However, if devices in a network increase, available resources in the network decrease, and then the lack of resources necessary to provide service can occur. To solve this problem, we propose collision avoidacne scheme for coexistence of various UWB systems. In this paper, we evaluate the performance of the proposed scheme through simulation.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2565-2571
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• 2020

Background: Understanding the behaviour of nuclear fuel claddings by conducting burst test on single cladding tube under simulated loss-of-coolant accident conditions and developing theoretical cum empirical predictive computer codes have been the focus of several investigations. The developed burst criterion (a) assumes symmetrical deformation of cladding tube in contrast to experimental observation (b) interpolates the properties of Zircaloy-4 cladding in mixed α+β phase (c) does not account for azimuthal temperature variations. In order to overcome all these drawbacks of burst criterion, it is reasoned that artificial intelligence technique may be a better option to predict the burst parameters. Methods: Artificial neural network models based on feedforward backpropagation algorithm with logsig transfer function are developed. Results: Neural network architecture of 2-4-4-3, that is model with two hidden layers having four nodes in each layer is found to be the most suitable. The mean, maximum, and minimum prediction errors for this optimised model are 0.82%, 19.62%, and 0.004%, respectively. Conclusion: The burst stress, burst temperature, and burst strain obtained from burst criterion have average deviation of 19%, 12%, and 53% respectively whereas the developed neural network model predicted these parameters with average deviation of 6%, 2%, and 8%, respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.375-388
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• 2004

As today's business environment has become more and more competitive, forward as well as backward flows of products among members belonging to a supply chain have been increased. The backward flows of products, which are common in most industries, result from increasing amount of products that are returned, recalled, or need to be repaired. Effective management for these backward flows of products has become an important issue for businesses because of opportunities for simultaneously enhancing profitability and customer satisfaction from returned products. Since third party logistics service providers (3PLs) are playing an important role in reverse logistics operations, the 3PLs should perform two simultaneous logistics operations for a number of different clients who want to improve their logistics operations for both forward and reverse flows. In this case, distribution networks have been independently designed with respect to either forward or backward flows so far. This paper proposes a mixed integer programming model for the design of network integrating both forward and reverse logistics. Since this network design problem belongs to a class of NP-hard problems, we present an efficient heuristic based on Lagrangean relaxation and apply it to numerical examples to test the validity of proposed heuristic.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.74-84
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• 2013

Modern companies have been facing devastating impacts from unexpected events such as demand uncertainties, natural disasters, and terrorist attacks due to the increasing global supply chain complexity. This paper proposes a multi stage logistic network model under disruption risk. To formulate the problem practically, we consider the effect of continuity rate, which is defined as a percentage of ability of the facility to provide backup allocation to customers in the abnormal situation and affect the investments and operational costs. Then we vary the fixed charge for opening facilities and the operational cost according to the continuity rate. The operational level of the company decreases below the normal condition when disruption occurs. The backup source after the disrup-tion is recovered not only as soon as possible, but also as much as possible. This is a concept of the business continuity plan to reduce the recovery time objective such a continuity rate will affect the investments and op-erational costs. Through numerical experiments, we have shown the proposed idea is capable of designing a resilient logistic network available for business continuity management/plan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.724-727
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• 2004

With the development of modem communication and networking technology, more and more computing and communication facilities, automation equipments, hone information appliances and different type of networking terminals come into home all over the world. The user can control information appliances in home environments. The home environment can communicate with the external network via phone line, wired LAN, wireless LAN, or mixed. However, home information appliances that are connected to the external network are under attack and need to be secured. So specifying suitable security requirements and policies for digital home environment is critical in hone networking environments. This paper analyzes the possible vulnerability to home network, and specifies the security requirements derived from the vulnerability analysis for digital home environment

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.791-800
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• 2022

CCN, which has emerged to overcome the limitations of existing network structures, enables efficient networking by changing the IP Address-based network method to the Content-based network method. At this time, the contents are stored on each node(router) rather than on the top server, and considering the limitation of storage capacity, it is very important to determine which contents to store and release through the cache policy, and there are several cache policies that have been studied so far. In this paper, two of the existing cache policies, producer popularity-based and distance-based, were mixed. In addition, the mixing ratio was set differently to experiment, and we proved which experiement was the most efficient one.

• Korea-Australia Rheology Journal
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• v.14 no.4
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• pp.189-201
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• 2002

The interaction between hydrophobically modified hydroxyethyl cellulose (hmHEC), containing approximately 1 wt% side-alkyl chains of $C_{16}$, and an anionic sodium dodecyl sulphate (SDS) surfactant was investigated. For a semi-dilute solution of 0.5 wt% hmHEC, the previously observed behaviour of a maximum in solution viscosity at intermediate SDS concentrations, followed by a drop at higher SDS concentrations, until above the cmc of surfactant when the solution resembles that of the unsubstituted polymer, was confirmed. Additionally, a two-phase region containing a hydrogel phase and a water-like supernatant was found at low SDS concentrations up to 0.2 wt%, a concentration which is akin to the critical association concentration, cac, of SDS in the presence of hmHEC. Above this concentration, SDS molecules bind strongly to form mixed micellar aggregates with the polymer alkyl side-chains, thus strengthening the network junctions, resulting in the observed increase in viscosity and elastic modulus of the solution. The shear behaviour of this polymer-surfactant complex during steady and step stress experiments was examined In great detail. Between SDS concentrations of 0.2 and 0.25 wt%, the shear viscosity of the hmHEC-polymer complex network undergoes shear-induced thickening, followed by a two-stage shear-induced fracture or break-up of the network. The thickening is thought to be due to structural rearrangement, causing the network of flexible polymers to expand, enabling some polymer hydrophobic groups to be converted from intra- to inter-chain associations. At higher applied stress, a partial local break-up of the network occurs, while at even higher stress, above the critical or network yield stress, a complete fracture of the network into small microgel-like units, Is believed to occur. This second network rupture is progressive with time of shear and no steady state in viscosity was observed even after 300 s. The structure which was reformed after the cessation of shear is found to be significantly different from the original state.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.144-152
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• 1996

In this paper, a pulse-mode digital multilayer neural network with a massively parallel yet compact and flexible network architecture is presented. Algebraicneural operations are replaced by stochastic processes using pseudo-random pulse sequences and simple logic gates are used as basic computing elements. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. A statistical model of the noise(error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Numerical character recognition problems are applied to the network to evaluate the network performance and to justify the validity of analytic results based on the developed statistical model. The network architectures are modeled in VHDL using the mixed descriptions of gate-level and register transfer level (RTL). Experiments show that the statistical model successfully predicts the accuracy of the operations performed in the network and that the character classification rate of the network is competitive to that of ordinary Back-Propagation networks.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.357-363
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• 2023

In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.