• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.49-61
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• 2006

This study suggests long-life asphalt pavement method which can save maintenance cost by increasing the design and performance period of pavements. The high modulus asphalt binder developed and then various physical tests are performed. Laboratory performance tests and accelerated pavement test are conducted for the high modulus and conventional mixtures. The test results show that dynamic modulus values of high modulus mixtures are higher than those of the conventional mixtures, The high modulus mixtures yield better fatigue, rutting and moisture damage performance than conventional mixtures. Structural analysis is performed and a database is built up for long life asphalt pavement design. Pavement response model is developed through a multiple regression analysis program, SPSS using the database. A design software for the long life pavements is developed based on the pavement response model and laboratory and field performance tests results. In addition, optimum pavement sections and materials are suggested. The suggested AC thickness of long life asphalt pavement is 29cm. A Life cycle cost analysis(LCCA) is conducted to check the economical efficiency of the long life pavement section. The LCCA result shows that initial construction costs of long life and conventional pavements are almost equal, but long life pavement is more profitable in terms of the LCCA.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.28-35
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• 2007

Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.57 no.3
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• pp.236-245
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• 2021

In this study, a drifting test using a experimental vessel (2,966 tons) in the northern waters of Jeju was carried out for the first time in order to obtain the fundamental data for drift. During the test, it was shown that the average leeway speed and direction by GPS position were 0.362 m/s and 155.54° respectively and the leeway rate for wind speed was 8.80%. The analysis of linear regression modes about leeway speed and direction of the experimental vessel indicated that wind or current (i.e. explanatory variable) had a greater influence upon response variable (e.g. leeway speed or direction) with the speed of the wind and current rather than their directions. On the other hand, the result of multiple regression model analysis was able to predict that the direction was negative, and it was demonstrated that predicted values of leeway speed and direction using an experimental vessel is to be more influential by current than wind while the leeway speed through variance and covariance was positive. In terms of the leeway direction of the experimental vessel, the same result of the leeway speed appeared except for a possibility of the existence of multi-collinearity. Then, it can be interpreted that the explanatory variables were less descriptive in the predicted values of the leeway direction. As a result, the prediction of leeway speed and direction can be demonstrated as following equations. Ŷ₁= 0.4031-0.0032X₁+0.0631X₂-0.0010X₃+0.4110X₄ Ŷ₂= 0.4031-0.6662X₁+27.1955X₂-0.6787X₃-420.4833X₄ However, many drift tests using actual vessels and various drifting objects will provide reasonable estimations, so that they can help search and rescue fishing gears as well.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.411-424
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• 2011

The studies of congruence in organizational research have explored the concepts such as person-job fit person-organization fit, or person-environment fit. The relevant studies dealt with the fit level as an important influencing factor on the performance. In particular, researchers have agreed that employees can be motivated by the high level fit of person-organization. However, few research developing an alternative methodological approach has been done. For the purpose mentioned above the statistics like D, |D| or $D^2$ and the Q values such as Q(the correlation between two sets of interval measures) or $Q_r$(the correlation between two rankings) have been conventionally adopted in spite of numerous methodological problems. In general, these traditional indices such as difference scores, or Q values, are nondirectional and add an extra weight to differences of lager magnitude. Therefore, Edwards (1993) introduced the polynomial regression and the response surface analysis to overcome flaws with conventional approaches. However, the method-ological approaches did not reflect the profile characteristics of person-organizational value fit and wouldn't be a proper solution for the fit level of person-organization value maximizing performance. Hence, this paper investigates alternative methodological approaches, the multivariate polynomial regression and the multiple response surface analysis, to avoid the problems issued from conventional ways.

• Toxicological Research
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• v.20 no.2
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• pp.89-100
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• 2004

The comet assay (also called the single-cell gel electrophoresis assay) has been widely used for detecting DNA damage and repair in individual cells. Since the conventional methods of evaluating comet assay data using frequency statistics are unsatisfactory we developed a new quantitative measure of DNA damage/repair that is based on all information residing in the dose/time-response curves of a comet experiment. Blood samples were taken from 25 breast cancer patients before undergoing radiotherapy. The comet assay was performed under alkaline conditions using isolated lymphocytes. Tail DNA, tail length, tail moment and tail inertia of the comet were measured for each patient at four doses of $\gamma$-rays (0, 2, 4 and 8 Gy) and at four time points after irradiation (0, 10, 20 and 30 min) using 100 cells each. The resulting three-dimensional dose-time response surface was modeled by multiple regression, and the second derivative, termed 2D, on dose and time was determined. A software module was programmed in SAS/AF to compute 2D values. We applied the new method successfully to data obtained from cancer patients to be assessed for their radiation sensitivity. We computed the 2D values for the four damage measures, i.e., tail moment, tail length, tail DNA and tail inertia, and examined the pairwise correlation coefficients of 2D both on the log scale and the unlogged scale. 2D values based on tail moment and tail DNA showed a high correlation and, therefore, these two damage measures can be used interchangeably as far as DNA repair is concerned. 2D values based on tail inertia have a correlation profile different from the other 2D values which may reflect different facets of DNA damage/repair. Using the dose-time response surface, other statistical models, e.g., the proportional hazards model, become applicable for data analysis. The 2D approach can be applied to all DNA repair measures, Le., tail moment, tail length, tail DNA and tail inertia, and appears to be superior to conventional evaluation methods as it integrates all data of the dose/time-response curves of a comet assay.

• Journal of Preventive Medicine and Public Health
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• v.38 no.3
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• pp.298-306
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• 2005

Objectives : To develop measurement scales of Internet addiction, and propose a Korean Internet Addiction Index (K-IAI) and classification criteria for Internet addiction from the threshold scores developed. Methods : The identification of the concept of 'Internet addiction' was based on the literature review. To select the scales, an exploratory factor analysis was applied. A construct validation was tested by a confirmatory factor analysis (CFA) with a structured equation model (SEM). In testing the validity of the classification criteria, ANOVA and non-recursive models with SEM were applied. Results : Out of 1,080 questionnaires distributed, 1,037 were returned,; a response rate of 96%. The Cronbach-$\alpha$ of all items was over 0.75. Using an exploratory factor analysis in the condition of a 6 factor constrain as the study model proposed, 23 of the initial 28 items were identified. In testing the discriminant and convergent validity of the selected 23 scales using CFA with SEM, the Internet addiction model explained about 93% of all variances of the data collected, and all the latent variables significantly explained the designated scales. A K-IAI was proposed using the T-scores of the sum of all factor averages. In the classification of users, the basic concept was a twostandard deviation approach of the K-IAI as the criteria of MMPI. The addiction group had a score ${\geq}70$ in the K-IAI, the pre-addiction group between ${\geq}50$ and <70, and the average user group <50. The Internet use times of the classified groups were statistically different in the ANOVA and multiple comparisons. Conclusions : The K-IAI is a reliable and valid instrument for measuring Internet addiction. Moreover, the taxonomy of the groups was also verified using various methods.

• The Korean Journal of Emergency Medical Services
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• v.24 no.1
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• pp.7-24
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• 2020

Purpose: Emergency medical service (EMS) personnel are at high risk of spreading infection. In this study, we used the PRECEDE model to identify the knowledge, status, and barriers to infection control among Korean paramedics to provide basic infection control data. Methods: A total of 164 respondents were analyzed for the study. A questionnaire was administered and collected through an online self-response platform. Descriptive analysis, t-test, ANOVA, multiple regression, and logistic regression analyses were performed to determine infection control practices and associated factors using SAS 9.4. To identify the pathways and direct, indirect, total effects based on the PRECEDE model, we used AMOS 26.0. Results: Highly rated self-efficacy (OR 8.82, 95% CI: 3.23-24.09), awareness (OR 6.05, 95% CI: 2.06-17.72), and enabling factors (OR 3.23, 95% CI: 1.18-8.78) led to superior infection control. As a result of the structural model analysis, the highly rated enabling factors and awareness led to superior practice patterns. Conclusion: Practice is related to self-efficacy, awareness, and enabling factors; however, further research is needed to develop strategies for infection control. In particular, institutional arrangements are needed to improve the enabling factors. Improving infection control performance may lead to better infection control and enhanced protection of EMS personnel and patients against infection risks.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.123-134
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• 2009

The CRM(Customer Relationship Management) is a business strategy model which can reap higher profits and can provide a competitive edge to an enterprise in today's new business environments. Early next year (2009), the Capital Market Consolidation Act will be in effect in South Korea. This is required for a qualitative growth to provide QoS (Quality of Service) and ensure growth in finance, IT industry & service. Accordingly, the securities and insurance companies, banks and other financial institutions make efforts to improve their derivative financial product and also enhance their services. In this paper we design and implement a Channel Server model for a Scalable Service Channel Server to efficiently manage the high volumes of inbound customer interactions based on the requirements of a CRM center. The proposed Scalable Service Channel Server supports integration with other third party service and standardization of multiple inbound service channels. The proposed model can be efficiently used in an inbound CRM center of any banking, finance, securities and insurance establishments.