• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.210-218
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• 2023

The author presents a simple data-driven intraday technical indicator trading approach based on Genetic Programming (GP) for return forecasting in the Bitcoin market. We use five trend-following technical indicators as input to GP for developing trading rules. Using data on daily Bitcoin historical prices from January 2017 to February 2020, our principal results show that the combination of technical analysis indicators and Artificial Intelligence (AI) techniques, primarily GP, is a potential forecasting tool for Bitcoin prices, even outperforming the buy-and-hold strategy. Sensitivity analysis is employed to adjust the number and values of variables, activation functions, and fitness functions of the GP-based system to verify our approach's robustness.

• Journal of KIISE:Information Networking
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• v.41 no.4
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• pp.186-191
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• 2014

Previous work only focuses on a maximization of network coding opportunity since it can reduce the number of packets in network system. However, it can make congestion in a relay node as each source node may transmit each packet with the maximum transmission rate based on the channel qualities. Therefore, in this paper, we propose CmNC (Congestion minimized Network Coding over unreliable wireless links) performing opportunistic network coding to guarantee the network coding gain with the consideration of the congestion and channel qualities. The relay node selects the best network code set based on the objective function for reducing the packet loss and congestion via a dynamic programming. With Qualnet simulations, we show CmNC is better up to 20% than the previous work.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.39-49
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• 2004

When there is a lack of detailed kinetic information, dFBA(dynamic flux balance analysis) has correctly predicted cellular behavior under given environmental conditions with FBA and different ial equations. However, until now, dFBA has centered on substrate concentration, cell growth, and gene on/off, but a detailed hierarchical structure of a regulatory network has not been taken into account. For this reason, the dFBA has limited the represen tation of interactions between specific regulatory proteins and genes and the whole transcriptional regulation mechanism with environmental change. Moreover, to calculate optimal metabolic flux distribution which maximizes the growth flux and predict the b ehavior of cell system, linear programming package(LINDO) and spreadsheet package(EXCEL) have been used simultaneously. thses two software package have limited in the visual representation of simulation results and it can be difficult for a user to look at the effects of changing inputs to the models. Here, we descirbes the construction of hierarchical regulatory network with defined symbolsand the development of an integrated system that can predict the total control mechanism of regulatory elements (opero ns, genes, effectors, etc.), substrate concentration, growth rate, and optimal flux distribution with time. All programming procedures were accoplished in a visual programming environment (LabVIEW).

• Geomechanics and Engineering
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• v.1 no.1
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• pp.53-74
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• 2009

In recent years, several computer-aided pattern recognition and data mining techniques have been developed for modeling of soil behavior. The main idea behind a pattern recognition system is that it learns adaptively from experience and is able to provide predictions for new cases. Artificial neural networks are the most widely used pattern recognition methods that have been utilized to model soil behavior. Recently, the authors have pioneered the application of genetic programming (GP) and evolutionary polynomial regression (EPR) techniques for modeling of soils and a number of other geotechnical applications. The paper reviews applications of pattern recognition and data mining systems in geotechnical engineering with particular reference to constitutive modeling of soils. It covers applications of artificial neural network, genetic programming and evolutionary programming approaches for soil modeling. It is suggested that these systems could be developed as efficient tools for modeling of soils and analysis of geotechnical engineering problems, especially for cases where the behavior is too complex and conventional models are unable to effectively describe various aspects of the behavior. It is also recognized that these techniques are complementary to conventional soil models rather than a substitute to them.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.21-26
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• 2022

This study touched on the effect of the different electronic course designs on the programming skills of university students. The researcher used the experimental research design of a quasi-experimental of two experimental groups to achieve the objectives of the study. The first group underwent an electronic course designed in the holistic pattern, and the second group was taught a course in a sequential pattern. This experimental design was intended to measure the impact of these two learning modes on the learners' cognitive and performance achievement of programming skills. An achievement test and observational form were the data collection tools. Data were analyzed statistically using Pearson correlation, Mann Whitney Test, and Alpha Cronbach. The findings revealed statistically- significant differences between the mean scores of the students of the first and second experimental groups in favor of the former concerning the observational form and the latter in the cognitive test. Based on the findings, some recommendations are suggested. Due to their effectiveness in the educational process, expanding using the e-courses at universities is vital. The university teachers are highly recommended to design e-courses and provide technical and material support to the e-courses user to fulfill their design purpose.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.809-814
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• 2018

With the proliferation of cloud computing infrastructures, service providers are able to deploy services in on-demand manner. Recently, microservice architecture has been attracting attention in order to maximize the efficiency of resource expansion in cloud infrastructure. Instead of implementing all of the service functions in a single software, service providers can easily and autonomously implement the necessary services by interconnecting the necessary services through an efficiently designed application programming interface (API). Moreover service developer can freely choice programming languages and define software, and functional structures to meet their functional requirements. In this paper, we propose virtual infrastructure manager service based on microservice architecture and evaluates its performance in scalability perspective.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.10a
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• pp.163-166
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• 2003

Hull form designers have to design a ship with satisfying an economical, technical and environmental demand. When it is concerned by a technical and environmental demand, there will be a economical demand left to criticize optimization. In this case, there were used to be requirements which needs to meet only a best performance not concerning about input of Human resource. Life cycle's cost contains building cost and operation cost so that now we need to check Man Hour cost in building a ship. This research shows a correlation between hull form information, i.e. curvature, length, breadth and thickness of surface and Man Hour of the Shell plating manufacture with using Artificial Neural Network and Gentic Programming. This study will support to classify initial work, to have a high assumption possible through predicting a Man Hour and to provide a guide book to infer a building cost and a economical optimization hull form.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.09a
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• pp.23-27
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• 2001

Making the safety situation from the various work system is very important in the industrial fields. The proposed neural network technique is the real titre computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objests during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of obejects. All of them request much memory space and titre. Therefore the most reliable neural-network algorithm is drived for real time recognition of obejects, which is composed of a dynamic programming algorithm based on sequence matching techniques. And the real time reconstruction of nonlinear image information is processed through several simulations. I-D LIPN hardware has been composed, and the real time reconstruction is verified through the various experiments.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.151-156
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• 2012

The current study presents a zero-one integer programming approach to determine the minimum break point set for the coordination of directional relays. First, the network is reduced if there are any parallel lines or three-end nodes. Second, all the directed loops are enumerated to reduce the iteration. Finally, the problem is formulated as a set-covering problem, and the break point set is determined using the zero-one integer programming technique. Arbitrary starting relay locations and the arbitrary consideration of relay sequence to set and coordinate relays result in navigating the loops many times and futile attempts to achieve system-wide relay coordination. These algorithms are compared with the existing methods, and the results are presented. The problem is formulated as a setcovering problem solved by the zero-one integer programming approach using LINGO 12, an optimization modeling software.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.32-42
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• 2023

The paper describes the new approaches to the automated analysis of curricula according to the higher education standard. The analysis process is proposed to carry out in two ways: (a) the analysis of completeness and sufficiency of curricula according to the standard of higher education; (b) the comparison of curricula of the same qualification and specialty. The problem of improving the quality of university students' training launches the process of monitoring and analyzing educational curricula and their correspondence to the higher education standard. We developed the rules and methods to compare curricula. In addition, we implemented the automated system of curricula comparison. The paper reveals the use of these methods based on the analysis of the curriculum bachelor level of higher education "Informatics", specialty "Computer science", at the Faculty of Computer Science and Cybernetics of the Taras Shevchenko National University of Kyiv. The findings put towards the idea that the implementation of developed methods as well as the automated system of curricula analysis will improve the educational services by higher education institutions.