• Journal of Korea Game Society
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• v.7 no.4
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• pp.117-123
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• 2007

This paper presents the Stone Influence, the Influence Point, and the Influence Area on computer Go. The Stone Influence is defined using the distance between stone and empty point. The Influence Point is defined using threshold value on the Stone Influence. The Influence Area is defined using lump of the Influence Points and its Core. In experiments using the Jeongseok data, the author obtained the threshold of Influence Points. The proposed method was verified by experiments where it was success fully applied to the influence in game of Go.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.145-152
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• 2004

This paper compares seat vibrations of a small passenger car and a SUV. The results also include the comparison of the human body accelerations and the ride values, such as the component ride values, and SEAT values of 12 axis accelerations obtained at the human body and seat track. The ride comfort evaluation is usually carried out by experiments of real cars which are expensive and sometimes may contain errors by passenger's postures. Simulations by computer, on the other hand, enable to solve these problems when the accuracy is proven. This paper, thus, also shows the correlation of human body vibration between experiments and computer simulations. For the computer simulation, korean dummy models are developed from the Hybrid III models by scaling the body data of Hybrid III to those of Korean men and women. From the comparison between the test data and simulation data, a nice correlation in trends was shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1521-1537
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• 2021

Through information hiding technique, secret message can be hidden in pictures. Stego-image quality and hiding capacity are two important metrics for information hiding. To enhance these metrics, many schemes were proposed by scholars in recent years. Some of them are effective and successful, but there is still a room for further improvement. A high capacity information hiding scheme (PAMO, Pixel-value Adjustment with Modulus Operation Algorithm) is introduced in this paper. PAMO scheme uses pixel value adjustment with modulus operation to hide confidential data in cover-image. PAMO scheme and some referenced schemes are implemented in Python and experiments are carried out to evaluate their performance. In the experiments, PAMO scheme shows better performance than other methods do. When secret message length is less than 72000 bits, the highest hiding capacity of PAMO can reach 7 bits per pixel, at the same time the PSNR of stego-images is greater than 30 dB.

• New & Renewable Energy
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• v.17 no.1
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• pp.19-32
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• 2021

Photovoltaic (PV) panels are generally treated as the most dependable components of PV systems; therefore, investigations are necessary to understand and emphasize the degradation of PV cells. In almost all specific deprivation models, humidity and temperature are the two major factors that are responsible for PV module degradation. However, even if the degradation mode of a PV module is determined, it is challenging to research them in practice. Long-term response experiments should thus be conducted to investigate the influences of the incidence, rates of change, and different degradation methods of PV modules on energy production; such models can help avoid lengthy experiments to investigate the degradation of PV panels under actual working conditions. From the review, it was found that the degradation rate of PV modules in climates where the annual average ambient temperature remained low was -1.05% to -1.16% per year, and the degree of deterioration of PV modules in climates with high average annual ambient temperatures was -1.35% to -1.46% per year; however, PV manufacturers currently claim degradation rates of up to -0.5% per year.

• KOGO NEWS
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• v.3 no.4
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• pp.10-15
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• 2003

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.83-102
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• 1994

Some optimal designs and data analysis methods based on a Gaussian spatial linear model for computer simulation experiments are considered. For designs of computer experiments, Latin-hypercube designs and some optimal designs are combined. A two-stage computational (2-points exchange and Newton-type) algorithm for finding the optimal Latin-hypercube design is presented. The spatial prediction model which was discussed by Sacks, Welch, Mitchell and Wynn(1989) for computer experiments, is used for analysis of the simulated data. Moreover, a method of contructing sequential (optimal) Latin-hypercube designs is considered. An application of this approach to the quality improvement and optimization of the integrated circuit design via the main-effects plot and the sequential experimental strategy is presented.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.9-16
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• 2023

Speech can actively elicit feelings and attitudes by using words. It is important for researchers to identify the emotional content contained in speech signals as well as the sort of emotion that resulted from the speech that was made. In this study, we studied the emotion recognition system using a database in Arabic, especially in the Saudi dialect, the database is from a YouTube channel called Telfaz11, The four emotions that were examined were anger, happiness, sadness, and neutral. In our experiments, we extracted features from audio signals, such as Mel Frequency Cepstral Coefficient (MFCC) and Zero-Crossing Rate (ZCR), then we classified emotions using many classification algorithms such as machine learning algorithms (Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)) and deep learning algorithms such as (Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM)). Our Experiments showed that the MFCC feature extraction method and CNN model obtained the best accuracy result with 95%, proving the effectiveness of this classification system in recognizing Arabic spoken emotions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.1-12
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• 2016

In this paper, we propose an approach that efficiently builds regional hazardous weather prediction models based on past weather data. Doing so requires finding the proper weather attributes that strongly affect hazardous weather for each region, and that requires a large number of experiments to build and test models with different attribute combinations for each kind of hazardous weather in each region. Using our proposed method, we reduce the number of experiments needed to find the correct weather attributes. Compared to the traditional method, our method decreases the number of experiments by about 45%, and the average prediction accuracy for all hazardous weather conditions and regions is 79.61%, which can help forecasters predict hazardous weather. The Korea Meteorological Administration currently uses the prediction models given in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2192-2197
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• 2003

This paper suggests remote experiments using the internet for the control education. The remote experiment is composed of equipment server computers, networks accessible to internet, and real plants such as inverted pendulums, crane systems and microcontrollers. Additionally, it requires a server program that has I/O functions with plants and calculate the control, an interface program bridging between web and the server program, and the home page including the detail explanation for the usage. For effective educations, how to perform experiments and how to combine the experiment with lectures will be discussed. The simple experiments by entering a few control parameters and the complex experiments by designing overall controls, will be explained. Technologies related with the remote experiment and other possible remote experiment will be introduced. It is demonstrated that the remote experiment will be very useful, particular for control education where students have difficulties in performing the experiments for lack of experimental equipments.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.321-338
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• 2008

This paper presents a Modified Multiple Depth First Search algorithm for the exploration of the indoor environments occupied with obstacles in random distribution. The proposed algorithm was designed and implemented to employ one or a team of Khepera II mini robots for the exploration process. In case of multi-robots, the BlueCore2 External Bluetooth module was used to establish wireless networks with one master robot and one up to three slaves. Messages are sent and received via the module's Universal Asynchronous Receiver/Transmitter (UART) interface. Real exploration experiments were performed using locally developed teleworkbench with various autonomy features. In addition, computer simulation tool was also developed to simulate the exploration experiments with one master robot and one up to ten slaves. Computer simulations were in good agreement with the real experiments for the considered cases of one to one up to three networks. Results of the MMDFS for single robot exhibited 46% reduction in the needed number of steps for exploring environments with obstacles in comparison with other algorithms, namely the Ants algorithm and the original MDFS algorithm. This reduction reaches 71% whenever exploring open areas. Finally, results performed using multi-robots exhibited more reduction in the needed number of exploration steps.