• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.111-118
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• 2024

In general network-based intrusion detection system is designed to detect malicious behavior directed at a network or its resources. The key goal of this paper is to look at network data and identify whether it is normal traffic data or anomaly traffic data specifically for accounting information systems. In today's world, there are a variety of principles for detecting various forms of network-based intrusion. In this paper, we are using supervised machine learning techniques. Classification models are used to train and validate data. Using these algorithms we are training the system using a training dataset then we use this trained system to detect intrusion from the testing dataset. In our proposed method, we will detect whether the network data is normal or an anomaly. Using this method we can avoid unauthorized activity on the network and systems under that network. The Decision Tree and K-Nearest Neighbor are applied to the proposed model to classify abnormal to normal behaviors of network traffic data. In addition to that, Logistic Regression Classifier and Support Vector Classification algorithms are used in our model to support proposed concepts. Furthermore, a feature selection method is used to collect valuable information from the dataset to enhance the efficiency of the proposed approach. Random Forest machine learning algorithm is used, which assists the system to identify crucial aspects and focus on them rather than all the features them. The experimental findings revealed that the suggested method for network intrusion detection has a neglected false alarm rate, with the accuracy of the result expected to be between 95% and 100%. As a result of the high precision rate, this concept can be used to detect network data intrusion and prevent vulnerabilities on the network.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.349-356
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• 2017

In this study, we propose a method to investigate topographic characteristics by applying machine learning which is an artificial intelligence analysis method based on the spatial data constructed using UAV and the training data created through spatial analysis. This method provides an alternative to the subjective judgment and accuracy of spatial data, which is a problem of existing topographic characteristics survey for officially assessed land price. The analysis method of this study is expected to improve the problems of topographic characteristics survey method of existing field researchers and contribute to more accurate decision of officially assessed land price by providing more objective land survey method.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.160-166
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• 2002

In this paper, data acquisition and analysis of a measuring machine for marine engine's cams is discussed. A rotary encoder and linear scale of the machine to measure angular and linear displacement respectively are interfaced to the PC via encoder board with 2 channels. The design and measuring data are interpolated by cubic spline curves to compute the precision error which is defined by the maximum and minimum distances between two curves. The minimum zone fit of ISO is employed to evaluate the geometric deviation. The developed system takes only 5 minutes to measure and analyze while the CMM takes over 1 hours even with a skilled operator.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.438-443
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• 2005

Handy paint rollers with simple or no patterns are generally used to transcribe its design to a wall just after painting. However, the types of the patterns are limited to several conventional ones, so that interior planners' or decorators' demands are gradually tending to getting attractive roller designs. In order to obtain abundant kinds of the roller designs, a new advanced 3D machining method should be established for cylindrical models. In this paper, a post-processor that can generate suitable NC data is proposed for multi-axis NC machine tools with a rotary unit. The 3D machining system with the post-processor is also presented for an attractive interior decorating. The machining system allows us to easily transcribe the relief designs from on a flat model to on a cylindrical model. The effectiveness of the proposed 3D machining system using the post-processor is demonstrated through some machining experiments.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.877-878
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• 2008

We suggest a feature reduction method to classify mouse function data sets, which integrate several biological data sets represented as high dimensional vectors. To increase classification accuracy and decrease computational overhead, it is important to reduce the dimension of features. To do this, we employed Hybrid Huberized Support Vector Machine with kernels used for a kernel logistic regression method. When compared to support vector machine, this a pproach shows the better accuracy with useful features for each mouse function.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.3
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• pp.75-78
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• 2008

Tire molds are manufactured by aluminum casting, direct five-axis machining, and electric discharging machining. Master models made of chemical wood are necessary if aluminum casting is used. They are designed with a three-dimensional computer-aided design system and milled by a five-axis machine. In this paper, a method for generating and machining a tire surface model is proposed and demonstrated. The groove surfaces, which are the main feature of the tire model, are created using a parametric design concept. An automatically programmed tool-like descriptive language is presented to implement the parametric design. Various groove geometries can be created by changing variables. For convenience, groove surfaces and raw cutter location (CL) data are generated in two-dimensional drawing space. The CL data are mapped to the tread surface to obtain five-axis CL data to machine the master model. The proposed method was tested by actual milling using the five-axis control machine. The results demonstrate that the method is useful for manufacturing a tire mold.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1090-1095
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• 1992

This paper describes the systematic control method of process information transfer and machine cell control in FMS implementation. We have constructed an experimental FMS computer network and control system. The system hardware consists of host computer to manage process data and information transfer of machine cells, cell control computers to control machine cells(NC lathe, machining center). On the other hand, software is made up of oredr management module, NC program searching and generation module, NC part program error check module and cell control module. In this study, we could arrive at conclusion as following : The first, each task could be accomplihed by the efficient information transfer in hierachical computer network. The second, data base system of part programs and process control data is needed for the efficint information transfer and production management. Lastly, expansion of FMS control system could be achieved by the hierachical and decentralized computer control system.

• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.53-59
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• 2004

Support vector machine(SVM) approach to regression can be found in information science literature. SVM implements the regularization technique which has been introduced as a way of controlling the smoothness properties of regression function. In this paper, we propose a new estimation method based on quadratic loss SVM for a linear fuzzy regression model of Tanaka's, and furthermore propose a estimation method for nonlinear fuzzy regression. This approach is a very attractive approach to evaluate nonlinear fuzzy model with crisp input and output data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.2
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• pp.67-74
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• 2003

This paper presents the development of the Inspection machine for SMD mounted on cream solder of PCB. There are mounting errors of SMD such as misalignment, missing part, wrong orientation, wrong polarity and so on. The main hardware of the system consists of a machine vision part and a motion control part. Operating software has been developed in GUI environment to help user convenience. The Inspection Jobs consist of two procedures, that is, creation of the inspection reference data and automatic inspection. The Inspection reference data has a tree structure of linked list including PCB information, blocks, components, windows, and inspection methods. This paper presents versatile inspection methods which include a section length method, a projection method and histogram method. Therefore, user can choose the suitable procedure for various components. Finally, the automatic Inspection procedure using the reference data checks the mounting errors of components.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.4
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• pp.21-27
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• 2004

In this paper, data acquisition and analysis of a measuring machine for marine engine's cams are discussed. A rotary encoder and linear scale of the machine to measure angular and linear displacement, respectively, are interfaced to the PC via an encoder board with 2 channels. The design and measuring data are interpolated by cubic spline curves to compute the precision error which is defined by the maximum and minimum distances between two curves. The minimum zone fit of ISO is employed to evaluate the geometric deviation. The developed system takes only 5 minutes to measure and analyze the precision error while the CMM takes over I hours even with a skilled operator.