• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.187-192
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• 2019

Majority problem and synchronization problem on cellular automata(CA) are hard to solve, since they are global problems while CA operate on local information. This paper proposes a way to find state transition rules of these problems. The rules of CA are represented as CMR(conditionally matching rules) and evolutionary algorithms are applied to find rules. We find many solution rules to these problems, compared the results with the previous studies, and demonstrated the effectiveness of CMR on one-dimensional cellular automata.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.242-248
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• 2024

Contemporary societal and environmental transformations coincide with the emergence of novel mental health challenges. anxiety disorder, a chronic and highly debilitating illness, presents with diverse clinical manifestations. Epidemiological investigations indicate a global prevalence of 5%, with an additional 10% exhibiting subclinical symptoms. Notably, 9% of adolescents demonstrate clinical features. Untreated, anxiety disorder exerts profound detrimental effects on individuals, families, and the broader community. Therefore, it is very meaningful to predict anxiety disorder through machine learning algorithm analysis model. The main research content of this paper is the analysis of the prediction model of anxiety disorder by machine learning algorithms. The research purpose of machine learning algorithms is to use computers to simulate human learning activities. It is a method to locate existing knowledge, acquire new knowledge, continuously improve performance, and achieve self-improvement by learning computers. This article analyzes the relevant theories and characteristics of machine learning algorithms and integrates them into anxiety disorder prediction analysis. The final results of the study show that the AUC of the artificial neural network model is the largest, reaching 0.8255, indicating that it is better than the other two models in prediction accuracy. In terms of running time, the time of the three models is less than 1 second, which is within the acceptable range.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.51-58
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• 2005

Interpreting a natural line drawing as a solid object requires simplifying assumptions in order to make the problem more tractable. Unfortunately, some of the assumptions made in the past have overly simplified the problem. Restricting the valency of vertices, and in particular allowing only trihedral vertices, distorts the problem, since algorithms which are satisfactory for the simplified problem are not satisfactory in the general case. This paper presents a test set of drawings of objects with higher-valency vertices. The intention in creating this test set is that it may be used to determine how effective various algorithms are in dealing with general (i.e. unrestricted) valency vertices.

• Earthquakes and Structures
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• v.12 no.3
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• pp.309-319
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• 2017

A new method is suggested for the retrofitting of torsionally sensitive buildings. The main objective is to eliminate the torsional component from the first two natural modes of the structure by properly modifying its stiffness distribution via selective strengthening of its vertical elements. Due to the multi-parameter nature of this problem, state-of-art optimization schemes together with an ad-hoc software implementation were used for quantifying the required stiffness increase, determine the required retrofitting scheme and finally design and analyze the required composite sections for structural rehabilitation. The performance of the suggested method and its positive impact on the earthquake response of such structures is demonstrated through benchmark examples and applications on actual torsionally sensitive buildings.

• Genomics & Informatics
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• v.18 no.1
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• pp.10.1-10.9
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• 2020

Advancements in next generation sequencing (NGS) technologies have significantly increased the translational use of genomics data in the medical field as well as the demand for computational infrastructure capable processing that data. To enhance the current understanding of software and hardware used to compute large scale human genomic datasets (NGS), the performance and accuracy of optimized versions of GATK algorithms, including Parabricks and Sentieon, were compared to the results of the original application (GATK V4.1.0, Intel x86 CPUs). Parabricks was able to process a 50× whole-genome sequencing library in under 3 h and Sentieon finished in under 8 h, whereas GATK v4.1.0 needed nearly 24 h. These results were achieved while maintaining greater than 99% accuracy and precision compared to stock GATK. Sentieon's somatic pipeline achieved similar results greater than 99%. Additionally, the IBM POWER9 CPU performed well on bioinformatic workloads when tested with 10 different tools for alignment/mapping.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.337-339
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• 2004

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1399-1410
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• 2003

In this paper, we develop a joystick manual driving algorithm for an electric vehicle called Cycab. Cycab is developed as a public transportation vehicle, which can be driven either by a manual joystick or an automated driving mode. The vehicle uses six motors for driving four wheels, and front/rear steerings. Cycab utilizes one industrial PC with a real time Linux kernel and four Motorola MPC555 micro controllers, and a CAN network for the communication among the five processors. The developed algorithm consists of two automatic vehicle speed control algorithms for normal and emergency situations that override the driver's joystick command and an open loop torque distribution algorithm for the traction motors. In this study, the algorithm is developed using SynDEx, which is a system level CAD software dedicated to rapid prototyping and optimizing the implementation of real-time embedded applications on distributed architectures. The experimental results verify the usefulness of the two automatic vehicle control algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1387-1392
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• 2015

SCS(Social Curation Service) is a service system to help sale and consumption with intelligent information about consumer's favor which is got from the combination of social service and internet shopping mall. This paper develops and analyzes some algorithms for catching the customer's preference tendency in SCS system. The developed algorithms are implemented to verify it's efficiency.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1113-1120
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• 2004

This paper proposes a novel hybrid genetic algorithm for the feature selection. Local search operations are devised and embedded in hybrid GAs to fine-tune the search. The operations are parameterized in terms of the fine-tuning power, and their effectiveness and timing requirement are analyzed and compared. Experimentations performed with various standard datasets revealed that the proposed hybrid GA is superior to a simple GA and sequential search algorithms.

• Korean Management Science Review
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• v.17 no.2
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• pp.75-86
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• 2000

In evolutionary algorithm, there exist various models for the evolution of the population with respect to schemes and strategies for reproduction. In the application of the algorithm to a specific problem, one model suitable to the problem is to be properly chosen and a program expert or a software is needed to help implement and test a designed algorithm. In this study, abject oriented modeling and the class library for simple evolutionary algorithms(SEA) with one population is developed. The library proposed here can be used as a generalized tool for solving problems in a wide range of domains.