• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.500-509
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• 1999

In this paper, we consider an optimal routing problem when point-to-point and point-to-multipoint connection traffics are offered in an ATM network. We propose a mathematical model for cost-minimizing configuration of a logical network for a given ATM-based BISDN. Our model is essentially identical to the previous one proposed by Kim(Kim, 1996) which finds a virtual-path configuration where the relevant gains obtainable from the ATM technology such as the statistical multiplexing gain and the switching/control cost-saving gain are optimally traded-off. Unlike the Kim's model, however, ours explicitly considers the VP's QoS(Quality of Service) for more efficient utilization of bandwidth. The problem is a large-scale, nonlinear, and mixed-integer problem. The proposed algorithm is based on the local linearization of equivalent-capacity functions and the relaxation of link capacity constraints. As a result, the problem can be decomposed into moderate-sized shortest path problems, Steiner arborescence problems, and LPs. This fact renders our algorithm a lot faster than the previous nonlinear programming algorithm while the solution quality is maintained, hence application to large-scale network problems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.305-314
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• 2017

Most of the existing researches on systemwide optimization of generator maintenance scheduling do not consider the equivalent operating hours(EOHs) mainly due to the difficulties of calculating the EOHs of the CCGTs in the large scale system. In order to estimate the EOHs not only the operating hours but also the number of start-up/shutdown during the planning period should be estimated, which requires the mathematical model to incorporate the economic dispatch model and unit commitment model. The model is inherently modelled as a large scale mixed-integer nonlinear programming problem and the computation time increases exponentially and intractable as the system size grows. To make the problem tractable, this paper proposes an EOH calculation based on demand grouping by K-means clustering algorithm. Network congestion is also considered in order to improve the accuracy of EOH calculation. This proposed method is applied to the actual Korean electricity market and compared to other existing methods.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.818-833
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• 2021

To address the problems of low precision rate, insufficient feature extraction, and poor contextual ability in existing text sentiment analysis methods, a mixed model account of a CNN-BiLSTM-TE (convolutional neural network, bidirectional long short-term memory, and topic extraction) model was proposed. First, Chinese text data was converted into vectors through the method of transfer learning by Word2Vec. Second, local features were extracted by the CNN model. Then, contextual information was extracted by the BiLSTM neural network and the emotional tendency was obtained using softmax. Finally, topics were extracted by the term frequency-inverse document frequency and K-means. Compared with the CNN, BiLSTM, and gate recurrent unit (GRU) models, the CNN-BiLSTM-TE model's F1-score was higher than other models by 0.0147, 0.006, and 0.0052, respectively. Then compared with CNN-LSTM, LSTM-CNN, and BiLSTM-CNN models, the F1-score was higher by 0.0071, 0.0038, and 0.0049, respectively. Experimental results showed that the CNN-BiLSTM-TE model can effectively improve various indicators in application. Lastly, performed scalability verification through a takeaway dataset, which has great value in practical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.652-676
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• 2023

The objective of this study is to provide a deeper understanding of the factors that lead to the development and adoption of AI-based chatbots. We analyze the structural relationship between the organizational (externalities), systematic (fit), and the consumer-related (psychological) factors and their role in the adoption of AI-based chatbots. Founded on the theories of task-technology fit and network externalities, we present a conceptual model overlooking common perception-based theories (e.g., Technology Acceptance Model). We collected 380 responses from Indian banking consumers to test the model using the PLS-SEM method. Interestingly, the findings present a positive impact of all factors on consumers' intention to adopt AI-based chatbots. However, the interplays between these factors provide a mixed perspective for literature. Apart from employing a combination of factors that have been used to study technology adoption, our study explores the importance of externalities and their relationship with fit factors, a unique outlook often overlooked by prior research. Moreover, we offer a clear understanding of latent variables such as trust, and the intricacies of their interplays in a novel context. Thereby, the study offers implications for literature and practice, followed by future research directions.

• Journal of the military operations research society of Korea
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• v.34 no.3
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• pp.1-12
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• 2008

Design of supply chain network (SCN) is required to optimize every factor in SCN and to provide a long-term and strategic decision-making. A mathematical model can not reflect the real world because design of SCN contains variables and stochastic factors according to status of its system. This paper presents the designing methodology of military SCN using the mathematical model and the simulation model. It constructs SCN to minimize its total costs using the Mixed Integer Programming (MIP) model. And we solve problems of a vehicle assignment and routing through adaptation of experiment parameters repeatedly in the simulation model based on the results from the MIP model. We implement each model with CPLEX and AutoMod, and experiment to reconstruct SCN when the Logistic Support Unit is restricted to support military units. The results from these experiments show that the proposed method can be used for a design of military SCN.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.5
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• pp.143-148
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• 2010

In this study, the mixed model of the surface rainfall-runoff analysis using grid data and Illudas model was applied to the urban watershed of Bulgang river. After the surface rainfall-runoff was estimated with GIS data, the runoff hydrograph was calculated using network analysis at Jeungsan bridge, which is the final output of watershed. Estimated runoff hydrograph in this study was compared to the observed runoff hydrograph which is converted from the water stage at Jeungsan bridge. The relative errors of total runoff volume and peak discharge showed the range values of 11.70%~16.30% and 1.10%~6.96%, and then the difference of peak times had the values of less than 1 hour for 4 storms. Therefore, the mixed model in this study could be considered to estimate the runoff hydrograph for the prevention of disasters in urban watershed.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.27-37
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• 2018

The purpose of this study is figure out secondary education undergraduates' communication patterns and perceptions of use in KAKAOTALK, one of the most frequently used Social Network Service(SNS). The mixed method research was conducted of survey about 86 students and in-depth interview 10 of them. The chief implication of research showed that it has been firstly functioning them to sustain public and private network and to be an universal tool of expression their opinion, idea, themselves, however, they still regard face-to-face communication important. Secondly, they think that KAKAOTALK is a part of their everyday lives and regarded a communication space to freely express themselves and to adjust and manage their image. Thirdly, they psychologically solved their loneliness and were encouraged, moreover, the contents of communication were different according to usd of public or private team chat room. It needs a follow-up study comparatively to analyze other generation's cognitive psychological values in SNS and to suggest digital culture literacy guideline.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.22-29
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• 2019

Due to the development of ICT technology, convergence reality contents are utilized as technology for providing services in various industrial fields by visualizing various information such as sensor information and shared information in a service platform showing only simple three-dimensional contents. Research is underway to reduce the weight of applications by transmitting the resources of the object to be enhanced to the network as the information and the contents to be provided increase. In order to provide resources through the network, servers for processing various information such as pattern information, content information, and sensor information must be constructed in a cloud environment. However, in order to authenticate data transmitted and received in real-time in a cloud environment, there is a problem in that the processing is delayed and a delay phenomenon occurs in the rendering process and QoS is lowered. In this paper, we propose a system to distribute cloud server which provides augmented contents of convergent reality service that provides various contents such as sensor information and three - dimensional model, and shorten the processing time of reliable data through distributed relay between servers Respectively.