• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.55-60
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• 2023

The IoT environment is very vulnerable to security threats, and if an intrusion occurs, it can cause great damage. In order to strengthen the security of the IoT environment, a curriculum that considers the characteristics of the IoT environment is needed. In this paper, we propose a curriculum model for cyber incident response in the Internet of Things environment. The proposed curriculum model was designed as a model for security threats in the IoT environment, types of intrusion incidents, and incident response procedures. The proposed curriculum model is expected to contribute to improving security awareness in the IoT environment and fostering cyber incident response experts in the IoT field. The proposed curriculum model strengthens the security of the IoT environment and is expected to be safe through security incident response in the IoT.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.3
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• pp.92-100
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• 1996

In order to control the water quality in rivers or lakes, it is needed to evaluate accurate amount of pollutant loadings from watersheds. The daily pollutant loadings were simulated using the pollutant loading calculation model which was composed of mathematical equations superimposed on the TANK model. The calibration of runoff and pollutant loading parameters were carried out with observed data, using a trial-and-error method. In addition, the proposed model was applied to evaluate its applicability for the representative watershed, the Bokha river watershed, Icheon city, Korea. The parameters of SS and T-P showed large values in the first tank while T-N showed large in the second tank. As a result of simulating the daily pollutant loadings by the pollutant loading calculation model, all of SS, T-N and T-P loadings were increased or decreased according to the amount of runoff discharge. Especially, it was apparent that SS and T-P loadings were significantly influenced by the runoff variation when it was rain. These results could partly explain that SS and T-P would occur mainly from the surface runoff while T-N would occur from both surface and subsurface flow.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.215-225
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• 2024

With the rapid development of Internet of Things (IoT) and big data technology, a large amount of data will be generated during the operation of related industries. How to classify the generated data accurately has become the core of research on data mining and processing in IoT industry chain. This study constructs a classification model of IoT industry chain based on improved random forest algorithm and text analysis, aiming to achieve efficient and accurate classification of IoT industry chain big data by improving traditional algorithms. The accuracy, precision, recall, and AUC value size of the traditional Random Forest algorithm and the algorithm used in the paper are compared on different datasets. The experimental results show that the algorithm model used in this paper has better performance on different datasets, and the accuracy and recall performance on four datasets are better than the traditional algorithm, and the accuracy performance on two datasets, P-I Diabetes and Loan Default, is better than the random forest model, and its final data classification results are better. Through the construction of this model, we can accurately classify the massive data generated in the IoT industry chain, thus providing more research value for the data mining and processing technology of the IoT industry chain.

• Korean Security Journal
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• no.37
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• pp.137-163
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• 2013

This research will incorporate cases from U.S public schools to analyze the factors which influences the security within the school and efficient security patterns to suggest an adequate suggestion to elevate domestic school security system. This study is divided into two following models: a serious criminal offense model, which considers crimes occurred on campus as subordinate variables, and a school violence model, which considers as subordinate variables after limiting an act of delinquency and an a group action that can harm the safety of students, although they are not included in the categories of crimes. First, from analyzing the factors which influences security within school, the explanation power of serious crime offense safety model and school violence safety model is measured 12% and 11.3%. In serious crime offense safety model, the safety education for students, among the safety programs provided by schools(t=2.548, p=0.011), parent participation to school management(t=10.694, p=0.000), Security activities on campus(t=3.643, p=0.000), and CPTED activity(t=6.467, p=0.000) are statistically significant, as affecting factors on the safety from serious crimes. Similarly in school violence model, the safety education for students, among the safety programs provided by schools(t=3.228, p=0.001), parent participation to school management(t=12.034, p=0.000), security activities on campus(t=2.663, p=0.000), and CPTED activity(t=3.928, p=0.000) are statistically significant, as affecting factors on the safety from school violence. Second, according to the analytic results on figuring out the optimal pattern to heighten the security activities, the serious offence model's explanatory power was 4.4% and school violence safety model rated 3.9%. With the serious offense safety model, the activity factors which showed statistically significant in influencing safety from serious offenses were cooperation with local police force (t=2112, p=0.035), school policy management (t=3.309, p=0.001), security patrolling activity (t=2.548, p=0.011). In the school violence model, security activities initiated by the school which showed statistically significant from serious offenses were cooperation with local police force (t=2.364, p=0.018) and policy management (t=4.142, p=0.000). In accordance with the result of this study, education for students rather than education for teachers is more positive in terms of the safety on campus, and parent participation, like education, is consistently needed for the safety on campus. In case of CPTED activity, reinforcing plans should be prepared by intactly accepting examples in the USA. In case of security activity, plans that can increase visibility and reinforce cooperation with local police in a smooth way will provide a positive effect to the safety on campus.

• Journal of Korean Society for Quality Management
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• v.43 no.4
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• pp.471-488
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• 2015

Purpose: Double sampling $T^2$ chart is a useful tool for detecting a relatively small shift in process mean when the process is controlled by multiple variables. This paper finds the optimal design of the double sampling $T^2$ chart in both economical and statistical sense under Weibull failure model. Methods: The expected cost function is mathematically derived using recursive equation approach. The optimal designs are found using a genetic algorithm for numerical examples and compared to those of single sampling $T^2$ chart. Sensitivity analysis is performed to see the parameter effects. Results: The proposed design outperforms the optimal design of the single sampling $T^2$ chart in terms of the expected cost per unit time and Type-I error rate for all the numerical examples considered. Conclusion: Double sampling $T^2$ chart can be designed to satisfy both economic and statistical requirements under Weibull failure model and the resulting design is better than the single sampling counterpart.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.112-117
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• 2004

This paper suggests the design and analysis of the fuzzy sliding mode control for a nonlinear system using Takagi-Sugeno(T-S) fuzzy model. In this control scheme, identifying procedure that the input gain matrices in a T-S fuzzy model are manipulated into the same one is needed. The input disturbances generated in the identifying procedure are resolved by incorporating the disturbance treatment method of the conventional sliding mode control. The proposed control strategy can also treat the input disturbances that can not be linearized in the linearization procedure of T-S fuzzy modeling. Design example for the nonlinear system, an inverted pendulum on a cart, demonstrates the utility and validity of the proposed control scheme.

• Korean Journal of Food Science and Technology
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• v.36 no.2
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• pp.349-354
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• 2004

Predictive growth model of Vibrio parahaemolyticus in modified surimi-based imitation crab broth was investigated. Growth curves of V. parahaemolyticus were obtained by measuring cell concentration in culture broth under different conditions ($Initial\;cell\;level,\;1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}\;colony\;forming\;unit\;(CFU)/mL$; temperature, 15, 25 37, and $40^{\circ}C$; pH 6, 7, and 8) and applying them to Gompertz model. Microbial growth indicators, maximum specific growth rate (k), lag time (LT), and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of V. parahaemolyticus increased with increasing temperature, reaching maximum rate at $37^{\circ}C$. LT and GT were also the shortest at $37^{\circ}C$. pH and initial cell number did not influence k, LT, and GT values significantly (p>0.05). Polynomial model, $k=a{\cdot}\exp(-0.5{\cdot}((T-T_{max}/b)^{2}+((pH-pH_{max)/c^{2}))$, and square root model, ${\sqrt{k}\;0.06(T-9.55)[1-\exp(0.07(T-49.98))]$, were developed to express combination effects of temperature and pH under each initial cell number using Gauss-Newton Algorism of Sigma plot 7.0 (SPSS Inc.). Relative coefficients between experimental k and k Predicted by polynomial model were 0.966, 0.979, and 0.965, respectively, at initial cell numbers of $1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}CFU/mL$, while that between experimental k and k Predicted by square root model was 0.977. Results revealed growth of V. parahaemolyticus was mainly affected by temperature, and square root model showing effect of temperature was more credible than polynomial model for prediction of V. parahaemolyticus growth.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.221-230
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• 2016

With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Bulletin of the Korean Mathematical Society
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• v.33 no.3
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• pp.377-383
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• 1996

We consider in this paper the following nonlinear regression model $$ (1.1) y_t = f(x_t, \theta_o) + \in_t, t = 1, \ldots, n, $$ where $y_t$ is the tth response, $x_t$ is m-vector imput variable, $\theta_o$ is a p-vector of unknown parameter belong to a parameter space $\Theta, f:R^m \times \Theta \ to R^1$ is a nonlinear known function, and $\in_t$ are independent unobservable random errors with finite second moment.