• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4958-4970
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• 2019

As technology advances, the amount of fake news is increasing more and more by various reasons such as political issues and advertisement exaggeration. However, there have been very few research works on fake news detection, especially which uses grammatical transformation on deep neural network. In this paper, we shall present a new Fake News Detection Model, called FAGON(Fake news detection model using Grammatical transformation On deep Neural network) which determines efficiently if the proposition is true or not for the given article by learning grammatical transformation on neural network. Especially, our model focuses the Korean language. It consists of two modules: sentence generator and classification. The former generates multiple sentences which have the same meaning as the proposition, but with different grammar by training the grammatical transformation. The latter classifies the proposition as true or false by training with vectors generated from each sentence of the article and the multiple sentences obtained from the former model respectively. We shall show that our model is designed to detect fake news effectively by exploiting various grammatical transformation and proper classification structure.

• Information Systems Review
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• v.5 no.2
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• pp.23-36
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• 2003

This study proposed the approaches to business process redesign and business network redesign in e-business environment through the case analysis of e-Transformation performed in Kolon Gloteck, Inc. which has been managed and operated in a traditional mode. The proposed e-Transformation approaches of the traditional firm in this study were as following: 1) Network-focused business process redesign; 2) Introducing ERP(Enterprise Resource Planning) as e-Business backbone; 3) Establishing transparence of business functions through using shared database; 4) Understanding customer and constructing IT(Information Technology) infrastructure for customer satisfaction; 5) Performing data and process standardization; 6) Applying the best suitable IT(Information Technology) such as JSP(Java Server Pages) and VPN(Virtual Private Network). The findings of this case study are thought to be useful as a practical guideline in carrying, out e-Transformation of the typical traditional firm and to provide significant basis for constructing the theoretical framework of e-Transformation methodology.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.187-201
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• 2014

As the complexity of business environment increases rapidly the use advanced information technology start to affect not only the business processes of individual companies but also the fundamental nature of business and industrial ecosystem. The changes observed at the level of business and industrial ecosystem encompasses a broad range of transformation. This unit of analysis is not sufficiently dealt with by existing information system research. This research attempted to analyze the changes in business ecosystem caused by digital transformation using Social Network Analysis. We studied structural change of the Korea film industry ecosystem chronologically divided by critical events. The film industry is chosen because it is an industry very sensitive to the changes in technology and has gone through massive transformation during the last three decade by way of using modern information technology.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.84-91
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• 2004

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc tight. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.8-20
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• 2023

The current study aims to determine digital transformation (organizational, technical, and human resources) requirements at Saudi universities from Umm Al-Qura University faculty members' perspectives. The researcher used a quantitative approach based on the descriptive analytical design. To answer the questions of the study, the researcher used the questionnaire as a data collection tool. The questionnaire was sent electronically to faculty members working in colleges and institutes affiliated with Umm Al-Qura University in Makkah Al-Mukarramah, Saudi Arabia. The questionnaire consisted of the three dimensions of digital transformation: organizational; technical; and human resources requirements. The results showed that requirements related to human resources came first with an average of 2.25 then the organizational requirements with an average of 1.95, and in the last, technical requirements came with an average of 1.64. In addition, some suggestions were given by the participants (faculty members) related to the mechanism that could contribute to implementing digital transformation at Saudi universities. Likewise, at the end of the study, the researcher has given some suggestions related to the implementation of digital transformation requirements at Saudi universities.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.39-47
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• 2023

This study compares various transformation techniques for multifocus image fusion. Multi-focus image fusion is a procedure of merging multiple images captured at unalike focus distances to produce a single composite image with improved sharpness and clarity. In this research, the purpose is to compare different popular frequency domain approaches for multi-focus image fusion, such as Discrete Wavelet Transforms (DWT), Stationary Wavelet Transforms (SWT), DCT-based Laplacian Pyramid (DCT-LP), Discrete Cosine Harmonic Wavelet Transform (DC-HWT), and Dual-Tree Complex Wavelet Transform (DT-CWT). The objective is to increase the understanding of these transformation techniques and how they can be utilized in conjunction with one another. The analysis will evaluate the 10 most crucial parameters and highlight the unique features of each method. The results will help determine which transformation technique is the best for multi-focus image fusion applications. Based on the visual and statistical analysis, it is suggested that the DCT-LP is the most appropriate technique, but the results also provide valuable insights into choosing the right approach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.107-114
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• 2021

Recently artificial intelligence technology has been introduced in various fields and various machine learning models have been operated in various frameworks as academic interest has increased. However, these frameworks have different data formats, which lack interoperability, and to overcome this, the open neural network exchange format, ONNX, has been proposed. In this paper we describe how to transform multiple machine learning models to ONNX, and propose algorithms and inference systems that can determine machine learning techniques in an integrated ONNX format. Furthermore we compare the inference results of the models before and after the ONNX transformation, showing that there is no loss or performance degradation of the learning results between the ONNX transformation.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.142-145
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• 1997

This paper presents an modified orthogonal neural network(MONN) based on orthogonal functions and applies the network to nonlinear system control. The accuracy of orthogonal neural network is essentially dependent on the choice of basic orthogonal functions. Modified orthogonal neural network is modified model of orthogonal neural network with input transformation to adapt its basic orthogonal functions. The results show that the modified orthogonal neural network has the excellent performance of approximating and controlling nonlinear systems and the input transformation make the ability of modified orthogoneural neural network better than one of orthogonal neural network.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.7-14
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• 2022

The presented research is devoted to the problems of achieving the goals of sustainable development, which will contribute to the development of industrial parks and their transformation into eco-industrial parks. The importance of the functioning of industrial parks and their transformation into eco-industrial ones in the direction of achieving sustainable development goals is substantiated. The development of industrial parks and their transformation through the coordination of dynamic development processes and the establishment of a system of mutually beneficial relations, due to the peculiarities of their functioning aimed at achieving sustainable development goals ensure the achievement of sustainable spatial development. Transformation of industrial parks will contribute to: increasing tax revenues of local budgets, increasing employment in the regions, raising public awareness of the need for environmentally friendly, energy efficient production, increasing the balance and harmony of social, economic and environmental development, modernization of territorial communities and regional enterprises resources and increase entrepreneurial initiative, rational use of available resources, intensification of small and medium enterprises, including innovation. The authors' scientific achievements are the substantiation of the principles of functioning of industrial parks in order to achieve the goals of sustainable development, which are based on a systematic approach and provide for the transformation into eco-industrial parks.