• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.405-430
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• 2021

Production planning is a key part of production management of manufacturing enterprises. Since computerization began, modern production planning has been developed starting with Material Requirement Planning (MRP), and today Enterprise Resource Planning (ERP), Advanced Planning and Scheduling (APS), Supply Chain Management (SCM) has been spreading and advanced. However, in the shipbuilding field, rather than applying these general-purpose production planning methodologies, in most cases, each shipyard has developed its own production planning system. This is because the applications of general-purpose production planning methods are limited due to the order-taking industry such as shipbuilding with highly complicated construction process consisting of millions of parts per ship. This study introduces the design and development of the production planning system reflecting the production environment of heavy shipyards in Korea. Since Korean shipyards such as Hyundai, Daewoo and Samsung build more than 10 ships per year (50-70 ships in the case of large shipyards), a planning system for the mixed production with complex construction processes is required. This study draws requirements using PI/BPR (process innovation and business process reengineering) methodology to develop a production planning system for shipyards that simultaneously build several ships. Then, CBD software development methodology was applied for the design and implementation of planning system with drawn requirements. It is expected that the systematic development procedure as well as the requirements and functional elements for the development of the shipyard production planning system introduced in this study will be able to present important guidelines in the related research field of shipbuilding management.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.23-30
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• 2000

In this paper, the web-based speaker verification system is designed. To decide the speaker recognition algorithm applied to the web-based speaker verification system, the recognition performance and special features of the text-dependent speaker recognition algorithms(DTW, DHMM, SCHMM) are compared through the computer simulation. Using the results of computer simulation, select DHMM as speaker recognition algorithm at web-based speaker verification system because DHMM has the proper recognition performance and initial training utterance number. And by the three-tier method using the ActiveX, DCOM techniques web-based speaker verification system is designed to be operated in the distributed processing environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3884-3910
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• 2016

Intrusion Detection System (IDS) in general considers a big amount of data that are highly redundant and irrelevant. This trait causes slow instruction, assessment procedures, high resource consumption and poor detection rate. Due to their expensive computational requirements during both training and detection, IDSs are mostly ineffective for real-time anomaly detection. This paper proposes a dimensionality reduction technique that is able to enhance the performance of IDSs up to constant time O(1) based on the Principle Component Analysis (PCA). Furthermore, the present study offers a feature selection approach for identifying major components in real time. The PCA algorithm transforms high-dimensional feature vectors into a low-dimensional feature space, which is used to determine the optimum volume of factors. The proposed approach was assessed using HTTP packet payload of ISCX 2012 IDS and DARPA 1999 dataset. The experimental outcome demonstrated that our proposed anomaly detection achieved promising results with 97% detection rate with 1.2% false positive rate for ISCX 2012 dataset and 100% detection rate with 0.06% false positive rate for DARPA 1999 dataset. Our proposed anomaly detection also achieved comparable performance in terms of computational complexity when compared to three state-of-the-art anomaly detection systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1104-1113
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• 2015

In this paper, we propose Two-Dimensional Robust Face Recognition System Realized with the Aid of Facial Symmetry with Illumination Variation. Preprocessing process is carried out to obtain mirror image which means new image rearranged by using difference between light and shade of right and left face based on a vertical axis of original face image. After image preprocessing, high dimensional image data is transformed to low-dimensional feature data through 2-directional and 2-dimensional Principal Component Analysis (2D)2PCA, which is one of dimensional reduction techniques. Polynomial-based Radial Basis Function Neural Network pattern classifier is used for face recognition. While FCM clustering is applied in the hidden layer, connection weights are defined as a linear polynomial function. In addition, the coefficients of linear function are learned through Weighted Least Square Estimation(WLSE). The Structural as well as parametric factors of the proposed classifier are optimized by using Particle Swarm Optimization(PSO). In the experiment, Yale B data is employed in order to confirm the advantage of the proposed methodology designed in the diverse illumination variation

• Journal of Power Electronics
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• v.18 no.3
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• pp.746-756
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• 2018

Harmonic resonance exists in grid-connected inverter systems. In order to determine the network components that contribute to harmonic resonance and the composition of the resonant circuit, sensitivity theory is applied to the resonance characteristic analysis. Based on the modal analysis, the theory of sensitivity is applied to derive a formula for determining the sensitivities of each network component parameter under a resonance circumstance that reflects the participation of the network component. The solving formula is derived for both parallel harmonic resonance and series harmonic resonance. This formula is adopted to a 4-node grid-connected test system. The analysis results reveal that for a certain frequency, the participation of parallel resonance and series resonance are not the same. Finally, experimental results demonstrate that the solving formula for sensitivity is feasible for grid-connected systems.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.215-220
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• 1990

A.C. impedance properties of $RuO_2$ based thick film resistors which having different resistivity value (DuPont 1721 : $100{\Omega}$/ sq., 1741 : $10K{\Omega}$/sq.) were investigated using by impedance analyzer. In case of lower resistivity 1721 system, the complex impedance was composed nearly R component for all speciman sintered at above $600^{\circ}C$, and the frequency dependancy on impedance was not affected very much up to 5MHz and again gradually increase with increasing the frequency. In case of higher resistivity 1741 resistor system, impedance properties were very depandant on sintering temperature. When sintering temperature was $600^{\circ}C$, the complex impedance plot shows a vertical line, which correspond to lone capacitance equivalant circuit, and the impedance linearly decreased with increasing frequency. In case of speciman sintered at $700-900^{\circ}C$, the complex impedance plot shows semi-circular are correspond to a lumped RC combination, and the impedance shows constant value to 5MHz, again decreased with increasing frequency. But the complex impedance behavior of speciman sintered at $1000^{\circ}C$ was shows the equivalent circuit correspont to parallel combined LCR component, and the impedance was not varied with frequency.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.248-256
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• 2021

Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.37-48
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• 2001

ITS includes an Advanced Traveler Information System(ATIS) that provides travelers with service and facility data for the purpose of assisting prior to embarking on a trip or after the traveler is underway. ATIS consists of three major subsystems, which are a Pre-trip Traffic Information subsystem(PTIS), an En-route Traffic Information Subsystem(ETIS), and a Dynamic Route Guide Subsystem(DGIS). ATIS needs to be designed and implemented in accordance with the National ITS Architecture, a reference framework that spans all of standards activities. Recently, as software technology is rapidly improved and stabilized, there are some needs to reuse pre-developed and powerful ITS technology. ITS standardization based on components and open interfaces becomes a way to solve these reusability of current ITS technology. This paper focuses on how could we design and implement ATIS based on the component with the aid of UML(Unified Modeling Language). The UML methodology is expected to provide a standardized model for newly developed ITS components.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.63-70
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• 2019

We extract the symptom of panic disorder from the context awareness environment. It extracts body context information through natural movement that exists in everyday life and uses a component of panic disorder. The ontology theory can be used to provide information on the degree of symptoms of panic disorder through inference process. For the components of panic disorder to the information processing based on ontology are defined as Classes. Panic disorder index is expressed through ontology modeling so that the condition of panic disorder can be known. The derivation of panic disorder component and panic disorder index will enable context awareness based information service for panic disorder. The context information is periodically synchronized with the context awareness on based device. Panic disorder can be used to improve the lifestyle of panic disorder.