• Convergence Security Journal
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• v.12 no.3
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• pp.35-43
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• 2012

The explosive growth of Internet traffic cause by smart equipment such as smart phone has led to a dramatic increase in demand for data transmission capacity and network control architecture, which requires high transmission rates beyond the conventional transmission capability. Next generation networks are expected to be controlled by Generalized Multi-Protocol Label Switching(GMPLS) protocol suite and operating at multiple switching layers. In order to ensure the most efficient utilization of multilayer network resources, effective global provisioning that providing the network with the possibility of reacting in advance to traffic changes should be provided. In this paper, we proposes a new path selection scheme in multilayer optical networks based on the vertical PCE architecture and a different approach to efficiently exploit multiple PCE cooperation.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.69-81
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• 2013

Maintaining connectivity is essential in multi-hop wireless networks since the network topology cannot be pre-determined due to mobility and environmental effects. To maintain the connectivity, a critical point in the network topology should be identified where the critical point is the link or node that partitions the network when it fails. In this paper, we propose a new critical point identification algorithm and also present numerical results that compare the critical points of the network and H-hop sub-network illustrating how effectively sub-network information can detect the network-wide critical points. Then, we propose two localized topological control resilient schemes that can be applied to both global and local H-hop sub-network critical points to improve the network connectivity and the network resilience. Numerical studies to evaluate the proposed schemes under node and link failure network conditions show that our proposed resilient schemes increase the probability of the network being connected in variety of link and node failure conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2469-2490
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• 2019

A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.403-411
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• 2021

This study discusses the influence of economic factors on the clothing exports from China and 15 South and Southeast Asian countries to the United States. A basic gravity trade model with three predictors, including the GDP value produced by exporting and importing countries and their geographical distance was established to explain the bilateral trade patterns. The conventional approach of multiple regression and the novel approach of Artificial Neural Networks (ANNs) were developed based on the value of clothing exports from 2012 to 2018 and applied to the trade pattern prediction of 2019. The results showed that ANNs can achieve a more accurate prediction in bilateral trade patterns than the commonly-used econometric analysis of the basic gravity trade model. Future studies can examine the predictive power of ANNs on an extended gravity model of trade that includes explanatory variables in social and environmental areas, such as policy, initiative, agreement, and infrastructure for trade facilitation, which are crucial for policymaking and managerial consideration. More research should be conducted for the examination of the balance between developing countries' economic growth and their social and environmental sustainability and for the application of more advanced machine-learning algorithms of global trade flow examination.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.119-128
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• 2024

The moveable ad hoc networks are untrustworthy and susceptible to any intrusion because of their wireless interaction approach. Therefore the information from these networks can be stolen very easily just by introducing the attacker nodes in the system. The straight route extent is calculated with the help of hop count metric. For this purpose, routing protocols are planned. From a number of attacks, the wormhole attack is considered to be the hazardous one. This intrusion is commenced with the help of couple attacker nodes. These nodes make a channel by placing some sensor nodes between transmitter and receiver. The accessible system regards the wormhole intrusions in the absence of intermediary sensor nodes amid target. This mechanism is significant for the areas where the route distance amid transmitter and receiver is two hops merely. This mechanism is not suitable for those scenarios where multi hops are presented amid transmitter and receiver. In the projected study, a new technique is implemented for the recognition and separation of attacker sensor nodes from the network. The wormhole intrusions are triggered with the help of these attacker nodes in the network. The projected scheme is utilized in NS2 and it is depicted by the reproduction outcomes that the projected scheme shows better performance in comparison with existing approaches.

• Annual Conference of KIPS
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• 2006.05a
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• pp.299-302
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• 2006

본 논문에서는 다중필터와 복합형 신경망으로 구성된 얼굴 검출 시스템과 WFMM 신경망을 이용한 피부색 검출기법을 소개한다. 전처리 단계에 해당하는 다중필터는 대상 영역의 수를 감소 시켜 시스템의 속도를 개선한다. 다중필터에 속한 색상필터는 총 11 가지의 색상 공간에서 피부색의 특징 값을 추출하여 학습 데이터로 사용하며, 이 학습 데이터에 의해 생성된 하이퍼 박스를 통해 피부색을 분류한다. 또한 WFMM 신경망의 연관도 요소 특성을 이용하여 각 색상 공간의 상대적 중요도를 분석하여 피부색 검출에 유용한 색상 공간을 분석하고 추출 한다. 얼굴패턴 검출을 위한 복합형 신경망은 첫 단계에서 가보 변환을 사용하는 CNN 을 통해 특징 지도를 생성하고, WFMM 신경망으로 최종 얼굴패턴을 검증한다.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.86-94
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• 2009

We propose a network-based global mobility mechanism between the IP based Access Networks. In the core network, the control message and data transmission were separated for fast location registration. In the local area, by applying the PMIPv6 technology, the network-based mobility was possible. Moreover, when the existing handover scheme compared with the proposed handover scheme, we can see definitely that the handover latency time of the proposed handover scheme has better performance than that of the existing handover scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• Journal of Distribution Science
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• v.12 no.5
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• pp.33-40
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• 2014

Purpose - This paper aims to review cold chain management, especially in the pharmaceutical industry, to explore the cold chain process of delivering temperature-sensitive pharmaceutical products, and to identify areas for further development. Research design, data, and methodology - The paper, based on literature review and corporate analysis, reviews the development and status of the cold supply chain system, including its important role in the pharmaceutical industry. Results - Logistics in this field requires more stages than are typically needed. Due to the unique characteristics of the market, few companies can provide the services; currently, only few global companies with large networks and high technologies can afford to do so. Expanding pharmaceutical markets to meet global demand will require cold chain development, especially in "pharmerging" markets. Conclusions - Cold chain is a highly sensitive market in terms of products being carried within the chain that itself is a complex system. However, at the same time, it is a niche market with new opportunities. Hence, a sound cold chain infrastructure is needed to satisfy companies, governments, and customers for both commercial and public reasons.