• Journal of Science and Technology Studies
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• v.14 no.1
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• pp.87-116
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• 2014

This article focuses on synthetic hormone consumption that illegal act of heterogeneous forms of pharmaceuticalization. Athletes are not unfamiliar with the use of synthetic hormones that contain anabolic steroids. Synthetic hormones are used to increase muscle mass and strength. This drug use practice cannot simply be viewed as illegal. Athletes accumulate knowledge on these hormones that conflicts with the knowledge proffered by physicians and they consume drugs responsibly. Physicians' knowledge of these hormones is limited to their use in the treatment of abnormalities. Athletes, however, are expanding the role of these hormones to include their potential for enhancement. Thereby, a new value is assigned to synthetic hormones, and an informal market is formed. Previous studies in the fields of biopolitics and biomedicalization have mainly focused on the formal connection between biomedical science and the institutional network. This article, therefore, analyzes the informal and the various aspects of biomedicalization.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.154-162
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• 2003

In this paper, Associative Memory with Cellular Neural Networks classifies and recognizes image patterns as an operator applied to image process. CNN processes nonlinear data in real-time like neural networks, and made by cell which communicates with each other directly through its neighbor cells as the Cellular Automata does. It is applied to the optimization problem, associative memory, pattern recognition, and computer vision. Image processing with CNN is appropriate to 2-D images, because each cell which corresponds to each pixel in the image is simultaneously processed in parallel. This paper shows the method for designing the structure of associative memory based on CNN and getting output image by choosing the most appropriate weight pattern among the whole learned weight pattern memories. Each template represents weight values between cells and updates them by learning. Hebbian rule is used for learning template weights and LMS algorithm is used for classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.77-88
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• 2010

Wireless Mesh Networks are consist of mobility mesh clients and mesh routers. WMNs can communicate with heterogeneous networks such as IEEE 802.11, IEEE 802.15, IEEE 802.16 and sensor networks. WMNs which is based on ad hoc network are on research and developing to enhance WLANs, WPANs, or WMANs. WMNs can offer environment to serve human, service to person area, campus, and metro. But WMNs has many problems to solve about enhancing performance and generalization. Among them, Existing protocol layers has many problems enhancing to optimize WMNs. This document issues problems about WMNs in protocol layer and suggest the solutions. Also, suggests the requirements and the methods of QoS supporting issue.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2B
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• pp.183-191
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• 2004

Single shortest path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal cost multiple shortest paths in OSPF and IS-IS does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, among all the equal cost multiple shortest paths in the network, a set of TE-aware shortest paths, which reduces the maximum link load significantly, can be found and used by IP routers without any change of existing routing protocols and serious configuration overhead. While calculating TE-aware shortest paths. the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next-hop toward the destination by looking up the destination prefix. In this paper, we present a problem formulation of finding a set of TE-aware shortest paths in ILP, and propose a simple heuristic for the problem. From the simulation results, it is shown that TE-aware shortest path routing performs better than default shortest path routing and ECMP in terms of the maximum link load with the marginal configuration overhead of changing the next-hops.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.3-10
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• 2014

In this paper, the performances of the presented D2D (device-to-device) systems under the environment of the cognitive convergent overlay networks are evaluated based upon the locations of the D2D users' terminals, the power consumptions of the terminals and the reductions of the interference levels. As the capabilities of the users' terminals improve, the optimization of the system is crucial to the efficient utilization of the radio resources of the individual networks considering their mobility and the features of their networks. Users' mobility model is given for the performance evaluation of the D2D system. In this paper, the performances of the D2D systems are evaluated in terms of the performance index of the FER (frame error rate) employing multiantenna techniques (MIMO:multiple input multiple output) for the various network environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.41-55
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• 1995

In this paper, an optimal idenfication method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together wlth optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzzy-neural networks(FNNs) are tuned automatically using improved modified complex method and modified learning algorithm. For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activateti sluge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.530-533
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• 2010

This paper presents numerical analysis and design optimization of various turbine blade cooling techniques with three-dimensional Reynolds-averaged Navier-Stokes(RANS) analysis. The fluid flow and heat transfer have been performed using ANSYS-CFX 11.0. A fan-shaped hole for film-cooling has been carried out to improve film-cooling effectiveness with the radial basis neural network method. The injection angle of hole, lateral expansion angle of hole and ratio of length-to-diameter of the hole are chosen as design variables and spatially averaged film-cooling effectiveness is considered as an objective function which is to be maximized. The impingement jet cooling has been performed to investigate heat transfer characteristic with geometry variables. Distance between jet nozzle exit and impingement plate, inclination of nozzle and aspect ratio of nozzle hole are considered as geometry variables. The area averaged Nusselt number is evaluated each geometry variables. A rotating rectangular channel with staggered array pin-fins has been investigated to increase heat transfer performance ad to decrease friction loss using KRG modeling. Two non-dimensional variables, the ratio of the eight diameter of the pin-fins and ratio of the spacing between the pin-fins to diameter of the pin-fins selected as design variables. A rotating rectangular channel with staggered dimples on opposite walls are formulated numerically to enhance heat transfer performance. The ratio of the dimple depth and dimple diameter are selected as geometry variables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4814-4834
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• 2018

This paper presents an architecture for wireless sensor networks (WSNs) with blind source separation (BSS) applied to retrieve the received mixing signals of the sink nodes first. The little-to-no need of prior knowledge about the source signals of the sink nodes in the BSS method is obviously advantageous for WSNs. The optimization problem of the BSS of multiple independent source signals with complex and noncircular distributions from observed sensor nodes is considered and addressed. This paper applies Castella's reference-based scheme to Novey's negentropy-based algorithms, and then proposes a novel fast fixed-point (FastICA) algorithm, defined as the reference-signal negentropy complex FastICA (RSNT-cFastICA) for complex-valued noncircular-distribution source signals. The proposed method for the sink nodes is substantially more efficient than Novey's quasi-Newton algorithm in terms of computational speed under large numbers of samples, can effectively improve the power consumption effeciency of the sink nodes, and is significantly beneficial for WSNs and wireless communication networks (WCNs). The effectiveness and performance of the proposed method are validated and compared with three related BSS algorithms through theoretical analysis and simulations.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.67-82
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• 2001

The ILOF project addresses the needs of logistics industrial organizations to reduce information processing time, improve added and residual value of information and reduce processing and transportation costs. It deals with the information supply chain information systems shared by vertical partner as important entity, whose performance and optimization very significantly affects the efficiency and performance of logistics industries. This paper deals with logistics information exchange systems based on supply chain management, focusing on sharing database and processes between partners such as shipper, logistics broker, transportation company, shipping company etc., for smoothing the information flow, enhancing consumer service and reducing communication fee and labour costs. The significance of contribution of this research is the provision of a model for logistics information exchange including entity relationship diagram, data flow diagram and functions which is able to facilitate the formulation of a customer driven supply chain information network, there by enhancing the competitive edge of companies in logistics industries on local and global basis.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.185-194
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• 2013

Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.