• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1201-1210
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• 2019

Stock price is characterized as being mutable, non-linear and stochastic. These key characteristics are known to have a direct influence on the stock markets globally. Given that the stock price data often contain both linear and non-linear patterns, no single model can be adequate in modelling and predicting time series data. The autoregressive integrated moving average (ARIMA) model cannot deal with non-linear relationships, however, it provides an accurate and effective way to process autocorrelation and non-stationary data in time series forecasting. On the other hand, the neural network provides an effective prediction of non-linear sequences. As a result, in this study, we used a hybrid ARIMA and neural network model to forecast the monthly closing price of the Shanghai composite index and Shenzhen component index.

• Progress in Medical Physics
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• v.31 no.3
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• pp.35-53
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• 2020

The authors congratulate the cerebrations for the 30 years of the Korean Society of Medical Physics (http://www.ksmp.or.kr/). The paper is published to recognize the anniversary. Geon-Ho Jahng invited Professor Z. H. Cho to join to submit this manuscript because he has been one of the leaders in the field of magnetic resonance imaging (MRI) during the last 40 years. In this review, we describe the development and clinical histories of MRI internationally and domestically. We also discuss diffusion and perfusion MRI, molecular imaging using MRI and MR spectroscopy (MRS), and the hybrid systems, such as positron emission tomography-MRI (PET-MRI), MR-guided focused ultrasound surgery (MRgFUS), and MRI-guided linear accelerators (MRI-LINACs). In each part, we discuss the historical evolution of the developments, technical developments, and clinical applications.

• Bulletin of the Korean Chemical Society
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• v.14 no.2
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• pp.183-187
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• 1993

Aryl carbenic anion radicals have been generated from the corresponding alkoxy-aryl diazo compounds by unimolecular decomposition reaction in various electrolyte/solvent systems. The electrochemical reductions of alkoxy-aryl diazo compounds in the electrolyte/solvent system are shown to initially be a one-electron process which affords the corresponding anion radicals. The unimolecular loss of nitrogen is favored at the propagation step and accelerated by the oxygen and carbon atoms of alkoxy group adjacent to the diazo function. The structure of the carbene anion radical in the termination is considered to be a resonance hybrid.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.1
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• pp.29-46
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• 1999

Most of the previous researches for the electronic cash system guarantee unconditional untraceability for the purpose of individual privacy. Such untraceable electronic cash system that only focuses on untraceability, however, has side effect such as money laundering, criminal activities. We present a escrow cash model using anonymous channel that supports not only untaceability but also crime prevention, and prove the efficiency of our scheme relative to previous escrow cash systems.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.45-52
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• 2020

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.131-139
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• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.33-38
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• 2022

The main purpose of the study is to determine the key aspects of the mechanisms of state management of the exchange of information about cyberattacks, cyber incidents, and information security incidents. The methodology includes a set of theoretical methods. Modern government, on the one hand, must take into account the emergence of such a new weapon as cyber, which can break various information systems, can be used in hybrid wars, influence political events, pose a threat to the national security of any state. As a result of the study, key elements of the mechanisms of state management of the exchange of information about cyberattacks, cyber incidents, and information security incidents were identified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1006-1027
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• 2022

In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone's next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.52-59
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• 2021

In this paper, we propose a system that allows small business owners focusing on the restaurant business to easily understand the management situation, and to manage the operation and management centering on the cost of food materials and profits and losses. In general, the metadata structure is different depending on the POS system, so it is necessary to first develop a standardized metadata model for a food material cost management system for small business owners in various industries. For that reason, the system proposed in this paper was applied to the cost management app by referring to the development of a data model using the metadata standard. In addition, in order to implement a cost profit/loss management system for small business owners in the restaurant industry, it was designed to support standardized metadata models from various types of POS systems, and is a hybrid app that can support a smart environment. Interface) was configured.

• Proceedings of the Membrane Society of Korea Conference
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• 1995.06a
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• pp.27-38
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• 1995

Based on innovative membrane module concepts reverse osmosis and nanofiltration are going to become important instruments in environmental engineering. One example is the Disc-Tube-module and its application for the purification of landfill leachate. Currently over 45 different landfills are using this ROCHEM DT-module, in some cases combined with the high pressure reverse osmosis versions of this module, operating at up to 120 bar and 200 bar. This state of the art membrane technology and the DTF-module for nanofiltration, developed by ROCHEM on the basis of the DT-module and RO-systems for the purification of landfill leachate, make possible in hybrid processes permeate recovery rates of more than 97 % with concentration factors up to 40.