• Journal of Digital Convergence
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• v.13 no.9
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• pp.489-495
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• 2015

Image availability evaluated by the degree of agreement and sensitive using the process improve visualization according to the Algorithm modification in Image Post-Processing. Reliability measured by the Breast Imaging Reporting and Data System. 172 patients visit same period divided by BI-RADS, category five stages, and contents of breast parenchyma into Calcification, Nodule and Mass. Evaluated the TE/PV image reliability, visualization sensitive, agreement of diagnosis. Convergence analysis was an in various fields. According to the result of this research, PV has higher sensitive and accuracy about lesions than TE visual and there is a difference insensitive by contents of breast parenchyma. Therefore, practical use of Algorithm Modification(Tissue Equalization: TE, Premium View: PV) is expected to improve more accurate, useful diagnosis, which has not been easy until now.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.5
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• pp.275-281
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• 2010

Car HVAC is one of main factors influencing a potential customer's first impression. It should be fault-free, which requires the most stable control performance. So, the control algorithm consists of a proportional feedback only, not with an integral action needed for elimination of steady-state errors. To reduce the errors and make the response faster, feedforward algorithm based on predicted thermal load is added. To evaluate the performance, car HVAC is dynamically modelled and its control logic is simulated. The results shows that the proportional feedback leads to about $4^{\circ}C$ of steady-state error. When the feedback is combined with the feedforward algorithm and with a set value update based on disturbances, it predicts less than $1^{\circ}C$ of control error and improved thermal comfort.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.73-82
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• 2000

This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.139-155
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• 2003

This paper presents the new methodology of analyzing and classifying patterns of customers in mobile telecommunication market to enhance the performance of predicting the credit information based on the decision tree and neural network. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship and makes special management on the customer who has huh potential of getting out of contract in advance. The real implementation of proposed method shows that the predicted accuracy is higher than existing methods such as decision tree(CART, C4.5), regression, neural network and combined model(CART and NN).

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1620-1632
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• 1998

This paper presents a fast parallel algorithm for volume rendering and its implementation using C language and MPI MasPar Programming Language) on the 4,096 processor MasPar MP-2 machine. This parallel algorithm is a parallelization hased on the Lacroute' s sequential shear - warp algorithm currently acknowledged to be the fastest sequential volume rendering algorithm. This algorithm reduces communication overheads by using the sheared space partition scheme and the load balancing technique using load estimates from the previous iteration, and the number of voxels to be processed by using the run-length encoded volume data structure.Actual performance is 3 to 4 frames/second on the human hrain scan dataset of $128\times128\times128$ voxels. Because of the scalability of this algorithm, performance of ]2-16 frames/sc.'cond is expected on the 16,384 processor MasPar MP-2 machine. It is expected that implementation on more current SIMD or MIMD architectures would provide 3O~60 frames/second on large volumes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.434-439
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• 2013

It is very difficult to monitor the blind spots that are not recognized by traditional surveillance camera (CCTV) systems, and the surveillance efficiencies are very low though many accidents/events can be solved by the systems. In this paper, the fuzzy logic based sound source localization system using sound strength in the underground parking lot is suggested and the performance of the system is analyzed in order to enhance the stabilization and the accuracy of the localization algorithm in the suggested system. It is confirmed that the localization stabilization of the localization algorithm (SLA_fuzzy) using the fuzzy logic in the suggested system is 4 times higher than that of the conventional localization algorithm (SLA). In addition to this, the localization accuracy of the SLA_fuzzy in the suggested system is 29% higher than that of the SLA.

• Journal of the Korean Institute of Telematics and Electronics
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• v.18 no.5
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• pp.1-9
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• 1981

Experimental results on a 4-bit charge-coupled A/D converter are described. Major operations in the successive approximation algorithm are implemented in a monolithic chip, CCADC, which was fabricated usir p-channel CCD technology, with its die size of 4,200 mil2 Typical operating frequency range has been found out to be from 500Hz to 200kHz. In that frequency range, no missing code has been found in the whole signal range of 2.4 volts for ramp signal slewing at 1 LSB/(sampling time). A discussion is made on several layout techniques to conserve the nominal binary ratio of (8:4:2:1) among the areas of four adjacent potential wells (M wells), whose charge storing capacities correspond to each bit magnitude - 3.6 pC, 1.8 pC, 0.9 pC, and 0.45 pC nominal in the order of MSB to the LSB. The effect of 'dump slot', which is responsible for the excessive nonlinearity (2$\frac{1}{2}$LSB) in the A/D converter, is explained. A novel input scheme called 'slot zero insertion' to circumvent the deleterious effects of the dump slot is described with the experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.427-436
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• 1999

This paper describes an ECG signal labeling algorithm based on fuzzy clustering, which is very useful to the automated ECG diagnosis. The existing labeling methods compares the crosscorrelations of each wave form using IF-THEN binary logic, which tends to recognize the same wave forms such as different things when the wave forms have a little morphological variation. To prevent this error, we have proposed as ECG signal labeling algorithm using fuzzy clustering. The center and the membership function of a cluster is calculated by a cluster validity function. The dominant cluster type is determined by RR interval, and the representative beat of each cluster is determined by MF (Membership Function). The problem of IF-THEN binary logic is solved by FCM (Fuzzy C-Means). The MF and the result of FCM can be effectively used in the automated fuzzy inference -ECG diagnosis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2380-2386
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• 2017

Fresh agricultural product in Korea are currently being exported overseas through expensive air transportation, supported by the governments's farm export subsidies. However all members of the World Trade Organization(WTO) must halt government subsidies by 2023. Accordingly, it is necessary to use marine transport capable of carrying freight at low cost. Reefer containers are used for marine transportation of fresh produce but it have a problem due to the temperature difference inside the reefer container which causes of fresh cargo and drop in freshness during sea transportation. In order to solve the problem, we developed a temperature control algorithm for reefer container that maintain a constant temperature and minimizes the deviation inside reefer container. The result showed that the maintained a constant temperature within a maximum of $0.5^{\circ}C$ based on the set-point of $4.0^{\circ}C$ inside reefer container.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.4
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• pp.224-231
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• 2012

In this paper, we introduce a fuzzy inference systems based on fuzzy c-means clustering algorithm for fuzzy modeling of nonlinear process. Typically, the generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, the fuzzy rules of fuzzy model are generated by partitioning the input space in the scatter form using FCM clustering algorithm. The premise parameters of the fuzzy rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process.