• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3159-3174
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• 1997

This paper reports a research to develop a methodology and a tool for understanding of very large and complex real-time software. The methodology and the tool mostly developed by the author are called the Architecture-based Real-time Software Understanding (ARSU) and the Software Re/reverse-engineering Environment (SRE) respectively. Due to size and complexity, it is commonly very hard to understand the software during reengineering process. However the research facilitates scalable re/reverse-engineering of such real-time software based on the architecture of the software in three-dimensional perspectives: structural, functional, and behavioral views. Firstly, the structural view reveals the overall architecture, specification (outline), and the algorithm (detail) views of the software, based on hierarchically organized parent-chi1d relationship. The basic building block of the architecture is a software Unit (SWU), generated by user-defined criteria. The architecture facilitates navigation of the software in top-down or bottom-up way. It captures the specification and algorithm views at different levels of abstraction. It also shows the functional and the behavioral information at these levels. Secondly, the functional view includes graphs of data/control flow, input/output, definition/use, variable/reference, etc. Each feature of the view contains different kind of functionality of the software. Thirdly, the behavioral view includes state diagrams, interleaved event lists, etc. This view shows the dynamic properties or the software at runtime. Beside these views, there are a number of other documents: capabilities, interfaces, comments, code, etc. One of the most powerful characteristics of this approach is the capability of abstracting and exploding these dimensional information in the architecture through navigation. These capabilities establish the foundation for scalable and modular understanding of the software. This approach allows engineers to extract reusable components from the software during reengineering process.

• Korean Journal of Soil Science and Fertilizer
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• v.28 no.4
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• pp.350-355
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• 1995

This study was conducted to use oyster shells, which have caused environmental problems in the coastal of Korea, as an agricultural material after processing. Physico-chemical components and neutralizing amount on the Ihyun silt loam of crushed oyster shell and slaked lime were examined. In field experiment, the properties of the soil, growth and yield of lettuce, cabbage, spinach, onion, red pepper and soybean were examined by the treatments of the shell(3.68ton/ha) or the lime (2.76ton/ha) with a randomized block design. Particle size of crushed oyster shell consisted of 73.4% of 1~60mesh and 26.6% larger then 61 mesh and contents of CaO, OM, and $P_2O_5$, etc. were 55.5%, 1.3%, and 0.29%, respectively. The requirement of the shell to neutralize the soil was 130~135% of the lime, but after 24months, it was the same. The application of the shell increased the contents of available $P_2O_5$ and $SiO_2$ exchangeable Ca in used soil. The shell tratment increased the leaf height, leaf width, etc. of the examined plants, and the yields 6~154% according to examined plants, as compared with the nonliminged, indicating that the shell possesses a great potential as an agricultural material with the same effectiveness as the lime.

• Journal of Periodontal and Implant Science
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• v.36 no.2
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• pp.555-565
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• 2006

The purpose of the present study is to evaluate the biological stability of the zirconia/alumina composite abutment by histologic and radiographic examination in clinical cases. 17 partially edentulous patients (5 men and 12 women, mean age 47) were treated with 37 implants. The implants were placed following the standard two-stage protocol. After a healing period of 3 to 6 months, zirconia/alumina composite abutments were connected. All radiographs were taken using paralleling technique with individually fabricated impression bite block, following insertion of the prosthesis and at the 3-, 6-, 12 month re-examinations. After processing the obtained images, the osseous level was calculated using the digital image in the mesial and distal aspect in each implant. An ANOVA and t-test were used to test for difference between the baseline and 3-, 6-, 12 months re-examinations, and for difference between maxilla and mandible. Differences at P <0.05 were considered statistically significant. For histologic examination, sample was obtained from the palatal gingiva which implant functioned for 12 months. Sections were examined under a light microscope under various magnifications. Clinically, no abutment fracture or crack as well as periimplantitis was observed during the period of study. The mean bone level reduction(${\pm}standard$ deviation) was 0.34 rom(${\pm}\;0.26$) at 3-months, 0.4 2mm(${\pm}\;0.30$) at 6-months, 0.62 mm(${\pm}\;0.28$) at 12-months respectively. No statistically significant difference was found between baseline and 3-, 6-, 12-months re-examinations (p > 0.05). The mean bone level reduction in maxilla was 0.33(${\pm}0.25$) at 3-months, 0.36(${\pm}0.33$) at 6-months, 0.56(${\pm}0.26$) at 12-months. And the mean bone level reduction in mandible was 0.35(${\pm}0.27$) at 3-months, 0,49(${\pm}0.27$) at 6-months, 0.68(${\pm}0.30$) at 12-months. No statistical difference in bone level reduction between implants placed in the maxilla and mandible. Histologically, the height of the junctional epithelium was about 2.09 mm. And the width was about 0.51 mm. Scattered fibroblasts and inflammatory cells, and dense collagen network with few vascular structures characterized the portion of connective tissue. The inflammatory cell infiltration was observed just beneath the apical end of junctional epithelium and the area of direct in contact with zirconia/alumina abutment. These results suggest the zirconia/alumina composite abutment can be used in variable intraoral condition, in posterior segment as well as anterior segment without adverse effects.

• Development and Reproduction
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• v.10 no.3
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• pp.159-168
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• 2006

Rodents and many other mammals have two chemosensory systems that mediate responses to pheromones, the main and accessory olfactory system, MOS and AOS, respectively. The chemosensory neurons associated with the MOS are located in the main olfactory epithelium, while those associated with the AOS are located in the vomeronasal organ(VNO). Pheromonal odorants access the lumen of the VNO via canals in the roof of the mouth, and are largely thought to be nonvolatile. The main pheromone receptor proteins consist of two superfamilies, V1Rs and V2Rs, that are structurally distinct and unrelated to the olfactory receptors expressed in the main olfactory epithelium. These two type of receptors are seven transmembrane domain G-protein coupled proteins(V1R with $G_{{\alpha}i2}$, V2R with $G_{0\;{\alpha}}$). V2Rs are co-expressed with nonclassical MHC Ib genes(M10 and other 8 M1 family proteins). Other important molecular component of VNO neuron is a TrpC2, a cation channel protein of transient receptor potential(TRP) family and thought to have a crucial role in signal transduction. There are four types of pheromones in mammalian chemical communication - primers, signalers, modulators and releasers. Responses to these chemosignals can vary substantially within and between individuals. This variability can stem from the modulating effects of steroid hormones and/or non-steroid factors such as neurotransmitters on olfactory processing. Such modulation frequently augments or facilitates the effects that prevailing social and environmental conditions have on the reproductive axis. The best example is the pregnancy block effect(Bruce effect), caused by testosterone-dependent major urinary proteins(MUPs) in male mouse urine. Intriguingly, mouse GnRH neurons receive pheromone signals from both odor and pheromone relays in the brain and may also receive common odor signals. Though it is quite controversial, recent studies reveal a complex interplay between reproduction and other functions in which GnRH neurons appear to integrate information from multiple sources and modulate a variety of brain functions.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.