• The Journal of Information Systems
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• v.29 no.1
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• pp.159-179
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• 2020

Purpose: We present a scientometric review of the literature on platform government to serve three primary purposes: First, to cluster researches on platform government based on the research issues; second, to identify the major papers, authors, and keywords in the domain; and third, to explore the promising research areas of platform government. Design/methodology/approach: We collected the platform government research from Web of Science, and analyzed 1,536 articles that was published during time span of 1998-2019. Next, co-citation networks are constructed and analyzed by using CiteSpace to visualize the domain clusters and dynamic research trends in the platform government domain. Findings: We identified 13 sub areas of the platform government research: global investigation, consumer product quality, digital agora, civic crowd funding, and open data use etc. We also visualize the top 20 references with the strongest citation bursts, co-authors network, co-occurring keyword network, and timeline of co-citation clusters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.543-552
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• 1994

This paper presents a decentralized quadratic regulation architecture with feedforward neural networks for the control problem of complex systems. In this method, the decentralized technique was used to treat several simple subsystems instead of a full complex system in order to reduce training time of neural networks, and the neural networks' nonlinear mapping ability is exploited to handle the nonlinear interaction variables between subsystems. The decentralized regulating architecture is composed of local neuro-controllers, local neuro-identifiers and an overall interaction neuro-identifier. With the interaction neuro-identifier that catches interaction characteristics, a local neuro-identifier is trained to simulate a subsystem dynamics. A local neuro-controller is trained to learn how to control the subsystem by using generalized Backprogation Through Time(BTT) algorithm. The proposed neural network based decentralized regulating scheme is applied in the power System Stabilization(PSS) control problem for an imterconnected power system, and compared with that by a conventional centralized LQ regulator for the power system.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.369-378
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• 2010

The creation of the hydraulic turbine flow factor map will undoubtedly benefit its design by decreasing both the design cycle time and product cost. In this paper, the geometry and flow variables, which effectively affect the flow factor, are proposed, analyzed and determined. These flow variables are further used to create the operating condition maps by using different model approaches categorized into Response Surface Method (RSM) and Artificial Neural Network (ANN). The accuracies of models created by different approaches are compared and the performances of model approaches are analyzed. The influences of chosen variables and the combination of Principle Component Analysis (PCA) and model approaches are also studied. The comparison results between predicted and actual flow factors suggest that two-hidden-layer Feed-forward Neural Network (FFNN), and one.hidden-layer FFNN with PCA has the best performance on forming this mapping, and are accurate sufficiently for hydraulic turbine design.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2289-2291
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• 2003

NLPCA(Nonlinear Principal Component Analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA can be implemented by a feedforward neural network called AANN (AutoAssociative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA and Maximum Likelihood Estimation scheme is presented. To verify its applicability, simulation study on the data supplied from Saemangeum measurement stations is executed.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.93-100
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• 1998

This study presents the new method which can transfer the expert's skill to deburring robot through neural network. The expert's skill is expressed as association mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured. Finally the characteristics of the burr and corresponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.98-101
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• 2019

At present, deep convolutional neural networks have made a very important contribution in single-image super-resolution. Through the learning of the neural networks, the features of input images are transformed and combined to establish a nonlinear mapping of low-resolution images to high-resolution images. Some previous methods are difficult to train and take up a lot of memory. In this paper, we proposed a simple and compact deep recursive residual network learning the features for single image super resolution. Global residual learning and local residual learning are used to reduce the problems of training deep neural networks. And the recursive structure controls the number of parameters to save memory. Experimental results show that the proposed method improved image qualities that occur in previous methods.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.55-63
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• 2021

The design functionality put forward by mapping the interactiveness of information. The presentation of such information with the user interface model indicates that the guidelines, concepts, and workflows form the deliverables and milestones for achieving a visualized design, therefore forming the right trend is significant to ensure compliance in terms of changing consideration and applying evaluation in the early stages. It is evidenced that prototype design is guided by improvement specifications, includes modes, and variables that increase improvements. The study presents five user interface testing methods. The testing methods are heuristic evaluation, perspective-based user interface testing, cognitive walkthrough, pluralistic walkthrough, and formal usability inspection. It appears that the five testing methods can be combined and matched to produce reasonable results. At last, the study presents different mobile application designs for student projects besides the evaluation of mobile application designs to consider the user needs and usability.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.756-766
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• 2023

To effectively track the illegal use of digital images and maintain the security of digital image communication on the Internet, this paper proposes a reversible multipurpose image watermarking algorithm based on a deep residual network (ResNet) and perceptual hashing (also called MWR). The algorithm first combines perceptual image hashing to generate a digital fingerprint that depends on the user's identity information and image characteristics. Then it embeds the removable visible watermark and digital fingerprint in two different regions of the orthogonal separation of the image. The embedding strength of the digital fingerprint is computed using ResNet. Because of the embedding of the removable visible watermark, the conflict between the copyright notice and the user's browsing is balanced. Moreover, image authentication and traitor tracking are realized through digital fingerprint insertion. The experiments show that the scheme has good visual transparency and watermark visibility. The use of chaotic mapping in the visible watermark insertion process enhances the security of the multipurpose watermark scheme, and unauthorized users without correct keys cannot effectively remove the visible watermark.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.192-196
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• 2024

The memory coherence problem occurs while mapping shared virtual memory in a loosely coupled multiprocessors setup. Memory is considered coherent if a read operation provides same data written in the last write operation. The problem is addressed in the literature using different algorithms. The big question is on the correctness of such a distributed algorithm. Formal verification is the principal term for a group of techniques that routinely use an analysis that is established on mathematical transformations to conclude the rightness of hardware or software behavior in divergence to dynamic verification techniques. This paper uses UPPAAL model checker to model the dynamic distributed algorithm for shared virtual memory given by K.Li and P.Hudak. We analyse the mechanism to keep the coherence of memory in every read and write operation by using a dynamic distributed algorithm. Our results show that the dynamic distributed algorithm for shared virtual memory partially fulfils its functional requirements.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.25-30
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• 2024

Various new technologies and aiding instruments are always being introduced for the betterment of the challenged. This project focuses on aiding the mute in expressing their views and ideas in a much efficient and effective manner thereby creating their own place in this world. The proposed system focuses on using various gestures traced into texts which could in turn be transformed into speech. The gesture identification and mapping is performed by the Kinect device, which is found to cost effective and reliable. A suitable text to speech convertor is used to translate the texts generated from Kinect into a speech. The proposed system though cannot be applied to man-to-man conversation owing to the hardware complexities, but could find itself very much of use under addressing environments such as auditoriums, classrooms, etc