• The Journal of the Korea Contents Association
• /
• v.18 no.4
• /
• pp.653-663
• /
• 2018

This study is a descriptive survey to examine the dementia related attitudes and dementia preventive behaviors in middle aged and to determine the relationships between the both sides. In this study, between October 1st and 9th, 2017, data were collected from the middle aged people in their 40s~60s in Korea through online questionnaires. Finally, 220 questionnaires were analyzed by t-test One way ANOVA, Pearson's correlation coefficient, and etc. The results of the study are as follows. First, 52.7% of the subjects were interested in prevention of dementia, but only 5.9% of them had experience of receiving education related to dementia. Second, fear of dementia was higher than cancer, cerebrovascular disease, and cardiovascular disease, but confidence in coping with the disease, expectation of the possibility of maintaining the daily life, expectation of the help of the family and the surrounding people, expectation of the national medical and economic support were significantly lower. Third, as the dementia preventive behaviors were implemented, the confidence in overcoming the disease, the expectation of the possibility of maintaining the daily life, the expectation of the help of the family and the surrounding people, the expectation of the medical and economic support of the country increased and the burden of the treatment cost was lowered. As a result, it is thought that this personal and social effort will improve the quality of life of the people by reducing physical, psychological, social and economic problems caused by dementia.

• Journal of the Korea Society for Simulation
• /
• v.20 no.1
• /
• pp.69-77
• /
• 2011

Modeling and Simulation(M&S) technology gets an attention from various parts such as industry and military. Especially, military uses the technology to cope with a different situation from the one in the Cold War and maximize the effect of training against the cost in the new environment. In order for the training based on M&S technology to be effective, the situations of a battlefield and a combat must be more realistically simulated. For this, a technique development on Computer-Generated Forces(CGF) which represents a unit's simulation logic and a human's simulated behaviors is focused. The CGF simulating a human's behaviors can be used in representing an enemy force, experimenting behaviors in a future war, and developing a new combat idea. This paper describes a methodology to accomplish Computer-Generated Forces' autonomous intelligence. It explains the process of applying a task behavior list based on the METT+T element onto CGFs. On the other hand, in the domain knowledge of military field manual, fuzzy facts such as "fast" and "sufficient" whose real values should be decided by domain experts can be easily found. In order to efficiently implement military simulation logics involved with such subjectivity, using a fuzzy inference methodology can be effective. In this study, a fuzzy inference methodology is also applied.

• Journal of Korea Water Resources Association
• /
• v.56 no.5
• /
• pp.337-345
• /
• 2023

Monitoring river microplastics is a challenging task since it is a time-consuming and high-cost process. The use of a physical model to have a better understanding of river microplastics' behaviors can complement the challenging monitoring process. However, there have been very limited studies on modeling river microplastics. In this study, therefore, we evaluated the applicability of one commonly used river water quality model, i.e., the Water Quality Analysis Simulation Program (WASP), in simulating the microplastic concentration in the river environment. We simulated the microplastic concentration in the Anyangcheon stream using the WASP's biochemical oxygen demand (BOD) and suspended solid (SS) variables as possible surrogate variables for the microplastics. Simulation analyses indicate that the SS state variable performs better than the BOD state variable to mimic the observed concentrations of microplastics. This is because of the characteristics of each water quality parameter; the BOD variable, a biochemical indicator, is inappropriate for modeling the behaviors of microplastics, which have generally constant biochemical features. In contrast, the SS variable, which has similar physical behaviors, followed the observed patterns of the microplastic concentrations well. To build a more advanced and accurate model for simulating the microplastic concentration, comprehensive and long-term monitoring studies of the river microplastics under different environmental conditions are needed, and the unit of microplastic concentration should be carefully addressed before its modeling application.

• Journal of Intelligence and Information Systems
• /
• v.18 no.1
• /
• pp.125-141
• /
• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of information and communication convergence engineering
• /
• v.5 no.2
• /
• pp.104-108
• /
• 2007

Ad hoc networks are a type of mobile network that function without any fixed infrastructure. One of the weaknesses of ad hoc network is that a route used between a source and a destination is to break during communication. To solve this problem, one approach consists of selecting routes whose nodes have the most stable link cost. This paper proposes a method for improving the low power distributed MAC. This method is based on the context awareness of the each nodes energy in clustering. We propose to select a new scheme to optimize energy conserving between the clustering nodes in MANET. And this architecture scheme would use context-aware considering the energy related information such as energy, RF strength, relative distances between each node in mobile ad hoc networks. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• Journal of Mechanical Science and Technology
• /
• v.15 no.4
• /
• pp.448-458
• /
• 2001

The primary goal of virtual prototyping is to eliminate the need for fabricating physical prototypes, and to reduce cost and time for developing new products. A virtual prototyping seeks to create a virtual environment where the development of a new model can be flexible as well as rapid, and experiments can be carried out effectively concerning kinematics, dynamics, and control aspects of the model. This paper addresses the virtual environment used for virtual prototyping of a passenger vehicle. It has been developed using the dVISE environment that provides such useful features as actions, events, sounds, and light features. A vehicle model including features, and behaviors is constructed by employing an object-oriented paradigm and contains detailed information about a real-size vehicle. The human model is also implemented not only for visual and reach evaluations of the developed vehicle model, but also for behavioral visualization during a crash test. For the real time driving simulation, a neural network model is incorporated into the virtual environment. The cases of passing bumps with a vehicle are discussed in order to demonstrate the applicability of a set of developed models.

• International Journal of Reliability and Applications
• /
• v.2 no.3
• /
• pp.209-240
• /
• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.6
• /
• pp.632-640
• /
• 2019

Desalination plant ships have been recently regarded as one of the probable solutions for drought seasons in many countries. Because desalination plants should be mounted on the desalination ships and special purpose storages such as salty waste water tanks are necessary, onboard and compartment arrangements would be distinguished from those of other conventional commercial ships. This paper introduces some basic design procedure including resistance/propulsion and seakeeping performances. The ship lines were improved step by step after modification of the ship lines and verification of resistance/propulsion performances using computational fluid dynamics (CFD). After finalization of the ship lines, the seakeeping performance was also evaluated to check motion behaviors and drive wave-induced loads such as the wave shear force and bending moment. It was proved that the predicted long-term vertical wave shear force and bending moment were significantly less than the rule-based ones, thus it is expected that the deliverables of this study will reduce the construction cost of desalination plant ships.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.451-458
• /
• 2017

An Electric Vehicle (EV) is operated with the electric energy of a battery in place of conventional fossil fuels. Thus, a suitable charging infrastructure must be provided to expand the use of electric vehicles. Because the battery of an EV must be charged to operate the EV, expanding the number of EVs will have a significant influence on the power supply and demand. Therefore, to maintain the balance of power supply and demand, it is important to be able to predict the numbers of charging EVs and monitor the events that occur in the distribution system. In this paper, we predict the hourly charging rate of electric vehicles using transformation matrix, which can describe all behaviors such as resting, charging, and driving of the EVs. Simulation with transformation matrix in a specific region provides statistical results using the Monte-Carlo Method.

• Journal of Korean Academy of Nursing
• /
• v.30 no.4
• /
• pp.932-947
• /
• 2000

The purpose of this study was to suggest directions for developing a Health Promotion Program for the elderly in Korea for the future. For this, twenty previously developed & implemented health promotion programs were reviewed and analyzed in terms of target population of the program, components of the program, measurement variables for effects of program, the effects of the program. The results were as follows. 1. Most of the target populations were older adults living independently in the community. 2. Components of the program were health education, health assessment and counseling and exercise program. - Health education was done in most of programs. The topics of health education that were often included in the programs were life style changes, medical knowledge, independent living, the concept of health promotion and changes related to aging. - In health assessment and counseling, health professionals discovered their health problems through health assessment or health risk appraisal. Then they developed health recommendations on each health problem and encouraged the elderly to implement the recommendations. 3. Variables measuring the direct effects of the program were health behavior, knowledge, attitude, skill, use of medical/health reference book. Variables measuring the indirect effects, biometric outcome, health status, functional status, medical service utilization, medical cost and wellbeing. 4. The analysis showed that health education was effective for changing health behaviors, improving knowledge, skill and attitude in the elderly. Those results were suggested to be used as guidelines for developing a health promotion program for the elderly in Korea for the future.