• IE interfaces
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• v.14 no.2
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• pp.111-119
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• 2001

A tandem AGV system is based on partitioning all the stations into non-overlapping single vehicle closed loops with additional stations provided as an interface between adjacent loops. For an efficient use of this configuration, it is required to solve the load routing problem(LRP), which is primarily based on the fact that a load may be handled by several vehicles and moved through several loops before it reaches its destination. In this paper, a heuristic based on genetic algorithm(GA) is first developed to solve LRP. The first model obtains the optimal route of each job and the optimal direction of each loop when the vehicle in each loop travels unidirectionally. The second GA model obtaines the optimal polling sequence of the empty vehicle in each loop, when the vehicle can move bidirectionally.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.449-452
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• 2023

The rapid development of the Internet has led to a significant increase in multimedia content in social networks. How to better analyze and improve video classification models has become an important task. Deep learning models have typical "black box" characteristics. The model requires explainable analysis. This article uses two classification models: ConvLSTM and VGG16+LSTM models. And combined with the explainable method of LRP, generate visualized explainable results. Finally, based on the experimental results, the accuracy of the classification model is: ConvLSTM: 75.94%, VGG16+LSTM: 92.50%. We conducted explainable analysis on the VGG16+LSTM model combined with the LRP method. We found VGG16+LSTM classification model tends to use the frames biased towards the latter half of the video and the last frame as the basis for classification.

• Biomolecules & Therapeutics
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• v.30 no.2
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• pp.212-212
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• 2022

• Molecules and Cells
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• v.37 no.11
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• pp.767-776
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• 2014

Alzheimer's disease (AD) is clinically characterized with progressive memory loss and cognitive decline. Synaptic dysfunction is an early pathological feature that occurs prior to neurodegeneration and memory dysfunction. Mounting evidence suggests that aggregation of amyloid-${\alpha}$ ($A{\alpha}$) and hyperphosphorylated tau leads to synaptic deficits and neurodegeneration, thereby to memory loss. Among the established genetic risk factors for AD, the ${\varepsilon}4$ allele of apolipoprotein E (APOE) is the strongest genetic risk factor. We and others previously demonstrated that apoE regulates $A{\alpha}$ aggregation and clearance in an isoform-dependent manner. While the effect of apoE on $A{\alpha}$ may explain how apoE isoforms differentially affect AD pathogenesis, there are also other underexplored pathogenic mechanisms. They include differential effects of apoE on cerebral energy metabolism, neuroinflammation, neurovascular function, neurogenesis, and synaptic plasticity. ApoE is a major carrier of cholesterols that are required for neuronal activity and injury repair in the brain. Although there are a few conflicting findings and the underlying mechanism is still unclear, several lines of studies demonstrated that apoE4 leads to synaptic deficits and impairment in long-term potentiation, memory and cognition. In this review, we summarize current understanding of apoE function in the brain, with a particular emphasis on its role in synaptic plasticity and the underlying cellular and molecular mechanisms, involving low-density lipoprotein receptor-related protein 1 (LRP1), syndecan, and LRP8/ApoER2.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.5
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• pp.347-354
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• 2016

This study evaluated the effects of Fructus Corni Officinalis water extract (FCE) on congnitive impairment and Aβ clearance induced by beta amyloid Aβ (1-42) injection in the hippocampus of rat. Aβ (1-42) was injected into the hippocampus using a Hamilton syringe and micropump (5 ㎍/5 ㎕, 1 ㎕/min, each hippocampus bilaterally). FCE was administered orally once a day (100, 250, 500 mg/kg) for 4 weeks after the Aβ (1-42) injection. The acquisition of learning and retention of memory were tested using the Morris water maze. Aβ accumulation and Aβ clearance in the hippocampus were observed using immunostaining. Aβ (1-42) level in plasma was confirmed using enzyme-linked immunosorbent assay (ELISA). FCE significantly shortened the escape latencies during acquisition training trials. FCE significantly increased the number of target heading to the platform site and significantly shortened the time for the 1^sttargetheadingduringtheretentiontesttrial.FCEsignificantlyattenuatedtheAβ accumulation in the hippocampus produced by Aβ (1-42) injection. FCE significantly increased LRP-1 expression around vessels in the hippocampus and Aβ (1-42) levels in plasma. The results suggest that FCE improved cognitive impairment by ameliorate Aβ clearance and Aβ accumulation in the hippocampus. FCE may be a beneficial herbal formulation in treating cognitive impairment including Alzheimer's disease.

• IE interfaces
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• v.22 no.2
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• pp.153-164
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• 2009

An effective management for reverse flows of products such as reuse, repair and disposal, has become an important issue for every aspect of business. In this paper, we study the Location-Routing Problem (LRP) in the multi-stage closed-loop supply chain network. The closed-loop supply chain in this study integrated both forward and reverse flows. In forward flow, a factory, Distribution Center (DC) and retailer are considered as usual. Additionally in reverse flow, we consider the Central Returns collection Center (CRC) and disposal facility. We propose a mixed integer programming model for the design of closed-loop supply chain integrating both forward and reverse flows. Since the LRP belongs to an NP-hard problem, we suggest a heuristic algorithm based on genetic algorithm. For some test problems, we found the optimal locations and routes by changing the numbers of retailers and facility candidates. Furthermore, we compare the efficiencies between open-loop and closed-loop supply chain networks. The results show that the closed-loop design is better than the open one in respect to the total routing distance and cost. This phenomenon enlarges the cut down effect on cost as an experimental space become larger.

• The Journal of Information Systems
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• v.30 no.4
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• pp.203-226
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• 2021

Purpose The purpose of this study is to enhance the accuracy score of personal credit scoring using the convolutional neural networks and secure the transparency of the deep learning model using eXplainalbe Artifical Inteligence(XAI) technique. Design/methodology/approach This study built a classification model by using the convolutional neural networks(CNN) and applied a methodology that is transformation of numerical data to imaged data to apply CNN on personal credit data. Then layer-wise relevance propagation(LRP) was applied to model we constructed to find what variables are more influenced to the output value. Findings According to the empirical analysis result, this study confirmed that accuracy score by model using CNN is highest among other models using logistic regression, neural networks, and support vector machines. In addition, With the LRP that is one of the technique of XAI, variables that have a great influence on calculating the output value for each observation could be found.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.336-343
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• 2013

The purpose of the present study was to determine the effect of 4 weeks course of motorized spinal decompression delivered via SpineMT(mobilization & traction) combined with therapeutic modalities on the treatment of patients with lumbar radiculopathy(LRP). A total of 15 patients with LRP (mean age, 36.63 years; age range 20-50years) participated in this study. 4 weeks course of spinal decompression delivered via SpineMT combined with therapeutic modalities was delivered to the patients for 6 days per week for the first two weeks, and four times per week for two additional weeks. The entire treatment consisted of 20 visits over 4 week period. Comparisons of changes in the muscle strengthening (MS), straight leg raise (SLR), and Oswestry disability index (ODI) at pre-intervention, after 10 treatment sessions, and at discharge (after 20 treatment sessions) were analyzed. There were significant improvements in the outcome measures of MS test, SLR test, and ODI score after 10 and 20 sessions of spinal decompression treatment combined with therapeutic modalities as compared with the pre-intervention(p<0.05). Spinal decompression treatment combined with therapeutic modalities appears to be a safe and efficacious, noninvasive treatment modality for patients with LRP.

• Journal of the Korean Chemical Society
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• v.63 no.6
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• pp.505-510
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• 2019

• Electronics and Telecommunications Trends
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• v.15 no.5 s.65
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• pp.60-72
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• 2000

데스크탑 시스템과 내장형 시스템의 하드웨어 특성과 요구사항은 서로 다르기 때문에 데스크탑 기반의 Unix 운영체제로 널리 쓰이고 있는 GNU/Linux를 내장형 시스템의 운영체제로 사용하기 위해서는 여러 가지 구성 요소들에 대한 최적화가 뒤따라야 한다. GNU/Linux의 최적화를 위해 고려해 볼 수 있는 다섯 가지 방법을 설명하고, 실례로서 ZDISK와 LRP에서 만든 결과를 분석해 보기로 한다.