• 대한전기학회논문지
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• 제40권7호
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• pp.718-724
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• 1991

In this paper, we proposed an algorithm to improve the memory efficiency by means of learning thresholds in spite of correlations among input patterns to be memorized. The proposed algorithm does not need preprocess correlations among input patterns but processes them with a threshold on a neural network. When memory contents are destroyed by correlation, nearly all patterns can be properly recovered with past learning. Through experiments we show how out algorithm can improve the memory efficiency.

• JSTS:Journal of Semiconductor Technology and Science
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• 제9권4호
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• pp.216-224
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• 2009

The endless scaling down of the semiconductor process made the impact of the power network noise on the performance of the state-of-the-art chip a serious design problem. This paper compares the performances of two popular circuit reduction approaches used to improve the efficiency of power network noise analysis: moment matching-based model order reduction (MOR) and node elimination-based MOR. As the benchmarks, we chose PRIMA and R2Power as the matching-based MOR and the node elimination-based MOR. Experimental results indicate that the accuracy, efficiency, and memory requirement of both methods very strongly depend on the structure of the given circuit, i.e., numbers of the nodes and sources, and the number of moments to preserve for PRIMA. PRIMA has higher accuracy in general, while the error of R2Power is also in the acceptable range. On the other hand, PRIMA has the higher efficiency than R2Power, only when the numbers of nodes and sources are small enough. Otherwise, R2Power clearly outperforms PRIMA in efficiency. In the memory requirement, the memory size of PRIMA increases very quickly as the numbers of nodes, sources, and preserved moments increase.

• 한국환경과학회지
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• 제21권5호
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• pp.545-553
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• 2012

Eco-efficiency considers both environmental impacts and economic values. It is a useful tool for communicating with stakeholders for business decision making. This study evaluated the eco-efficiency factor (EEF) for the energy network of a dyeing company that supplies surplus heat to a neighboring apartment during the night. This symbiosis network is one of the eco-industrial park (EIP) projects in Korea and aims to benefit local residents and the industrial complex by utilizing surplus heat. In this study, two categories were annualized. The first quantified environmental burden based on $CO_2$ emissions and quantified product value in terms of steam sales. The second used a variety of environmental factors, such as fossil fuel, water and waste, to quantify environmental burden and used steam sales to quantify value. The EEF of the symbiosis network was 1.6, using the global warming impact, and determined using the multiple variable, was 1.33. This study shows that the EEF depends on variable details of environmental burden but the values of this project were very high contrast to other business or EIP project.

• Industrial Engineering and Management Systems
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• 제14권4호
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• pp.347-371
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• 2015

A hybrid procedure based on multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) is proposed to evaluate the relative efficiency of customer services in bank branches. First, a three-stage process including sub-processes such as customer expectations, customer satisfaction, and customer loyalty, is defined to model the banking customer services. Then, fulfillment of customer expectations, customer loyalty level, and the customer satisfaction degree are measured and quantified through a multi-dimensional questionnaire based on customers' perceptions analysis and MUSA method, respectively. The customer services scores and the other criteria such as mean of employee evaluation score, operation costs, assets, deposits, loans, number of accounts are considered in network three-stage DEA model. The proposed NDEA model is formed based on multipliers perspective, output-oriented, and constant return to scale assumptions. The proposed NDEA model quantifies and assesses the total efficiency of main process and assigns the efficiency to customer expectations, customer satisfactions, and customer loyalties sub-processes in bank branches. The whole procedure is applied on 30 bank branches in IRAN. The proposed approach can be used in other organizations such as airports, airline agencies, urban transportation systems, railway organizations, chain stores, chain restaurants, public libraries, and entertainment centers.

• 산업경영시스템학회지
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• 제36권4호
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• pp.59-63
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• 2013

In biomass gasification, efficiency of energy quantification is a difficult part without finishing the process. In this article, a radial basis function neural network (RBFN) is proposed to predict biomass efficiency before gasification. RBFN will be compared with a principal component regression (PCR) and a multilayer perceptron neural network (MLPN). Due to the high dimensionality of data, principal component transform is first used in PCR and afterwards, ordinary regression is applied to selected principal components for modeling. Multilayer perceptron neural network (MLPN) is also used without any preprocessing. For this research, 3 wood samples and 3 other feedstock are used and they are near infrared (NIR) spectrum data with high-dimensionality. Ash and char are used as response variables. The comparison results of two responses will be shown.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.663-665
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• 2004

Ethernet-based passive optical network(EPON) technology is being considered as a promising solution for next-generation broadband access network. It must have the property of high efficiency, low cost, and support quality of service(QoS). A major feature for this new architecture is the use of a shared transmission media between all connected optical network unit(ONU). Hence, medium access control(MAC) arbitration mechanisms are essential for the successful implementation of EPON. In this paper we propose a simple dynamic bandwidth allocation(DBA) algorithm that improves the performance of network and supports IP-based multimedia applications with the bursty data traffic. In addition, we introduce analytic models of proposed algorithms and prove the system based on our algorithm to be asymptotically stable. Simulation results show the new DBA algorithm provides high bandwidth efficiency and low queueing delay of ONU in EPON.

• Journal of Mechanical Science and Technology
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• 제20권7호
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• pp.929-940
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• 2006

Early detection and diagnosis of incipient induction machine faults increases machinery availability, reduces consequential damage, and improves operational efficiency. However, fault detection using analytical methods is not always possible because it requires perfect knowledge of a process model. This paper proposes a neural network based expert system for diagnosing problems with induction motors using vibration analysis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals, and the neural network is trained and tested using the vibration spectra. The efficiency of the developed neural network expert system is evaluated. The results show that a neural network expert system can be developed based on vibration measurements acquired on-line from the machine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2573-2589
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• 2023

As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

• 한국융합학회논문지
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• 제9권11호
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• pp.37-43
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• 2018

Science DMZ는 종단간 전송효율성 극대화를 위해 전용네트워크, DTN, 최소한의 보안정책과 같은 복합적인 요소를 고려한 네트워크 구조이다. 그리고 Science DMZ의 고대역폭의 전용네트워크를 충분히 활용하기 위해서는 DTN 튜닝이 필수적인 요소이다. 아울러 네트워크 병목구간으로 인한 패킷손실을 최소화하기 위해 네트워크 시스템의 튜닝이 병행적으로 수행되어야 한다. 본 논문에서는 Science DMZ 네트워크 구조에서 전송효율성 극대화를 위한 데이터 전송 노드 및 네트워크 시스템 튜닝 방안에 대해 제안한다. 국가과학기술연구망을 이용한 성능측정결과 DTN 튜닝 후 네트워크 성능이 튜닝을 하지 않을 것과 비교해 180% 성능향상을 보였다. 아울러 shaping 정책을 적용한 네트워크 시스템 튜닝 후 성능측정결과 손실 없이 9.4Gb/s의 성능을 보였다.

• 품질경영학회지
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• 제44권4호
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• pp.785-798
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• 2016

Purpose: This paper developed the framework for extracting strategies of research and business development (R&BD) based on the data envelopment analysis(DEA). Methods: DEA has been widely utilized in evaluating R&D efficiency. Even though, technology transfer and commercialization has been regarded as the important factors for practical R&D efficiency evaluation, most research have evaluated R&D efficiency by just using the DEA outputs such as the number of patents and papers. The technology transfer, commercialization and relations among costs and generated technology and commercialization are needed to be considered for more practical R&D efficiency evaluation. Thus, this research addressed a method on how to incorporate the commercialization factors into the R&DB efficiency evaluation, and improve the efficiency strategically in terms of R&D and B&D. To achieve this, this research utilized a two-stage network DEA model for R&BD efficiency evaluation. Results: The proposed framework was applied to the 15 public research institutes and the 34 universities for validation. R&BD efficiency for the 15 public research institutes and the 34 universities was evaluated, and the differentiated improvement strategies for the inefficient DMUs to improve their efficient were proposed. Conclusion: The R&BD efficiency would be effectively analyzed based on two-stage network DEA. It would be utilized for the effective strategy planning for cultivating R&BD.