• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.279-285
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• 2022

In this paper, as a liberal arts course for non-majors, we developed a basic practice case for convolutional neural networks, which is essential for designing a basic convolutional neural network course curriculum. The developed practice case focuses on understanding the working principle of the convolutional neural network and uses a spreadsheet to check the entire visualized process. The developed practice case consisted of generating supervised learning method image training data, implementing the input layer, convolution layer (convolutional layer), pooling layer, and output layer sequentially, and testing the performance of the convolutional neural network on new data. By extending the practice cases developed in this paper, the number of images to be recognized can be expanded, or basic practice cases can be made to create a convolutional neural network that increases the compression rate for high-quality images. Therefore, it can be said that the utility of this convolutional neural network basic practice case is high.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.805-813
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• 2012

In this paper, we have designed and developed a middleware for an effectively approaching database to the existed brain disease clinical research system. The brain disease clinical research system was consisted of two parts i.e., a register and an analyzer. Since the register collects the registration data the analyzer yields a statistical data which based on the diverse variables. The middleware has designed to database management and a large data query processing of clients. By separating the function of each feature as a module, the module which was weakened connectivity between functionalities has been implemented the re-use module. And image data module used a new compression method from image to text for an effective management and storage in database. We tested the middleware system using 700 actual clinical medical data. As a result, the total data transmission time was improved maximum 115 times faster than the existing one. Through the improved module structures, it is possible to provide a robust and reliable system operation and enhanced security functionality. In the future, these middleware importances should be increased to the large medical database constructions.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.179-189
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• 2000

Recently, due to the increasing interests in deep sea development, all possible efforts to the development of underwater unmanned working vehicles such as AUV(Autonomous Underwater Vehicle) or underwater robot are exerted. This paper proposes a new efficient acoustic-based underwater image data communication system, which ensures a certain level of maximum throughput regardless of the propagation delay of ultrasonic and allowsfast data transmission through the multiple ultrasonic communication channel. Proposed system consists of an acoustic transducer which operates at 136kHz center frequency and it's 10kHz bandwidth, pre-amplifier, $\pi/4 QPSK$(Quadrature Phase Shift Keying) modulation/demodu-lation method, image compressing method using JPEG technique and modified Stop & Wait protocol. The experimental result of the system make it possible to transfer the underwater image as a high throughput at the basin test. The results of test are also verified which allows to desirable transmission performance compared with the existing developed system and the possibility to put the practical use of survey and investigation in the water.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.664-672
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• 2004

Widespread popularity of wireless data communication devices, coupled with the availability of higher bandwidths, has led to an increased user demand for content-rich media such as images and videos. Since such content often tends to be private, sensitive, or paid for, there exists a requirement for securing such communication. However, solutions that rely only on traditional compute-intensive security mechanisms are unsuitable for resource-constrained wireless and embedded devices. In this paper, we propose a selective partial image encryption scheme for image data hiding , which enables highly efficient secure communication of image data to and from resource constrained wireless devices. The encryption scheme is invoked during the image compression process, with the encryption being performed between the quantizer and the entropy coder stages. Three data selection schemes are proposed： subband selection, data bit selection and random selection. We show that these schemes make secure communication of images feasible for constrained embed-ded devices. In addition we demonstrate how these schemes can be dynamically configured to trade-off the amount of ded devices. In addition we demonstrate how these schemes can be dynamically configured to trade-off the amount of data hiding achieved with the computation requirements imposed on the wireless devices. Experiments conducted on over 500 test images reveal that, by using our techniques, the fraction of data to be encrypted with our scheme varies between 0.0244％ and 0.39％ of the original image size. The peak signal to noise ratios (PSNR) of the encrypted image were observed to vary between about 9.5㏈ to 7.5㏈. In addition, visual test indicate that our schemes are capable of providing a high degree of data hiding with much lower computational costs.