• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.126-131
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• 2015

As flash-based storage systems have been actively employed in large-scale servers and data centers, reliability has become an indispensable element. One promising technique for enhancing reliability is static wear-leveling, which distributes erase operations evenly among blocks so that the lifespan of storage systems can be prolonged. However, increasing the capacity makes the processing overhead of this technique non-trivial, mainly due to searching for blocks whose erase count would be minimum (or maximum) among all blocks. To reduce this overhead, we introduce a new randomized block selection method in static wear-leveling. Specifically, without exhaustive search, it chooses n blocks randomly and selects the maximal/minimal erased blocks among the chosen set. Our experimental results revealed that, when n is 2, the wear-leveling effects can be obtained, while for n beyond 4, the effect is close to that obtained from traditional static wear-leveling. For quantitative evaluation of the processing overhead, the scheme was actually implemented on an FPGA board, and overhead reduction of more than 3 times was observed. This implies that the proposed scheme performs as effectively as the traditional static wear-leveling while reducing overhead.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.48-54
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• 2014

For the element ${\alpha}{\in}GF(p^n)$, two kinds of bases are known. One is a conventional polynomial basis of the form $\{1,{\alpha},{\alpha}^2,{\cdots},{\alpha}^{n-1}\}$, and the other is a normal basis of the form $\{{\alpha},{\alpha}^p,{\alpha}^{p^2},{\cdots},{\alpha}^{p^{n-1}}\}$. In this paper we consider the method of generating normal bases which construct the finite field $GF(p^n)$, as an n-dimensional extension of the finite field GF(p). And we analyze the code sequence generating algorithm and derive the implementation functions of code sequence generator based on the normal bases. We find the normal polynomials of degrees, n=5 and n=7, which can generate normal bases respectively, design, and construct the code sequence generators based on these normal bases. Finally, we produce two code sequence groups(n=5, n=7) by using Simulink, and analyze the characteristics of the autocorrelation function, $R_{i,i}(\tau)$, and crosscorrelation function, $R_{i,j}(\tau)$, $i{\neq}j$ between two different code sequences. Based on these results, we confirm that the analysis of generating algorithms and the design and implementation of the code sequence generators based on normal bases are correct.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.13-25
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• 1998

It is necessary to develop methodologies for the application of artificial neural network into hydrologic rainfall-runoff process, although there is so much applicability by using the functions of associative memory based on recognition for the relationships between causes and effects and the excellent fitting capacity for the nonlinear phenomenon. In this study, some problems are presented in the application procedures of artificial neural networks and the simulation of runoff hydrograph experiences are reviewed with nonlinear functional approximator by artificial neural network for rainfall-runoff relationships in a watershed. which is regarded as hydrdologic black box model. The neural network models are constructed by organizing input and output patterns with the deserved rainfall and runoff data in Pyoungchang river basin under the assumption that the rainfall data is the input pattern and runoff hydrograph is the output patterns. Analyzed with the results. it is possible to simulate the runoff hydrograph with processing element of artificial neural network with any hydrologic concepts and the weight among processing elements are well-adapted as model parameters with the assumed model structure during learning process. Based upon these results. it is expected that neural network theory can be utilized as an efficient approach to simulate runoff hydrograph and identify the relationship between rainfall and runoff as hydrosystems which is necessary to develop and manage water resources.

• Applied Microscopy
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• v.36 no.3
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• pp.217-226
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• 2006

Image processing by ultra high voltage electron microscopy (UHVEM) and tomography has offered major contributions to research in the field of cellular ultrastructure. Furthermore, such advancements also have enabled the improved analysis of three-dimensional cellular structures in botany. In the present study. using UHVEM and tomography, we attempted to reconstruct the three-dimensional images of plastid inclusions that probably differentiate during photosynthesis. The foliar tissues were studied Primarily with the TEM and further examined with UHVEM. The spatial relationship between tubular elements and the thylakoidal membrane and/or starch grains within plastids mainly have been investigated in CAM-performing Sedum as well as in $C_4$ Salsola species. The inclusion bodies were found to occur only in early development in the former, while they were found only in mesophyll cells in the latter. The specimens were tilted every two degrees to obtain two-dimensional images with UHVEM and subsequently comparison has been made between the two types. Digital image processing was performed on the elements of the inclusion body using tilting, tomography, and IMOD program to generate and reconstruct three-dimensional images on the cellular level. In Sedum plastids, the inclusion bodies consisted of tubular elements exhibiting about 20 nm distance between elements. However, in Salsola, plastid inclusion bodies demonstrated quite different element structure, displaying pattern, and origin relative to those of the Sedum. The inclusion bodies had an integrative relationship with the starch grains in both species.

• Korean Journal of Materials Research
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• v.9 no.10
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• pp.962-969
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• 1999

Elastic and elasto-plastic stress analyses of AlN/Cu and AlN/W pints produced by active-metal brazing method using Ag-Cu-Ti insert-metal were performed with use of Finite-Element-Method(FEM). The results of stress analyses were compared with those from the pint strength tests and the observations of fracture behaviors. It was shown that a remarkably larger maximum principal stress is built in the AlN/Cu pint compared to the A1N/ W joint. Especially, the stress concentration with tensile component was confirmed at the free surface close to the bonded interface of AlN/Cu. The elasto-plastic analysis under consideration of stress relaxation effect of Ag-Cu-Ti insert possessing a so-called 'soft-metal effect' showed that the insert leads to a lowering of maximum principal stress in AlNiCu pint, even though an increase of the insert thickness above 100$\mu\textrm{m}$ could not bring its further decrease. The maximum pint strengths measured by shear test were 52 and 108 MPa for AlNiCu and AlN/W pints. respectively. Typical fractures of AlN/Cu pints occurred in a form of 'dome' which initiated from the free surface of AlN close to the bonded interface and proceeded towards the AlN inside forming a large angle. AlN/W pints were usually fractured at AlN side along the interface of AlN/insert-metal.

• Korean Journal of Materials Research
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• v.9 no.10
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• pp.970-977
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• 1999

Effect of Mo interlayer on the relaxation of residual stress in AlN/Cu pint bonded by active-metal brazing method was investigated. The stress analyses by finite-element-method, the measurement of pint strength and the observation of fracture surface were carried out and their results were compared with each other. From the results of stress analysis it is confirmed that a Mo interlayer led to a shift of maximum stress concentration site from AlN/insert-metal interface$\rightarro$ insert-metal/Mo$\rightarro$Mo interlayer. Additionally, with increase of the Mo interlayer thickness the stress concentration with tensile component was separately built both at the interface of Cu/Mo and AlN/Mo. whereby the residual stress in the free surface of AlN close to the bonded interface was drastically reduced. The AlN/Mo/Cu pints with Mo interlayer thickness of above 400$\mu\textrm{m}$ showed the strengths higher than 200 MPa. upto max. 275 MPa, while the AlN/Cu pint only max. 52 MPa.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.1-7
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• 2011

Recently, various researches have been proposed to accelerate GPU-based volume ray-casting. However, those researches may cause several problems such as bottleneck of data transmission between CPU and GPU, requirement of additional video memory for hierarchical structure and increase of processing time whenever opacity transfer function changes. In this paper, we propose an efficient GPU-based empty space skipping technique to solve these problems. We store maximum density in a brick of volume dataset on a vertex element. Then we delete vertices regarded as transparent one by opacity transfer function in geometry shader. Remaining vertices are used to generate bounding boxes of non-transparent area that helps the ray to traverse efficiently. Although these vertices are independent on viewing condition they need to be reproduced when opacity transfer function changes. Our technique provides fast generation of opaque vertices for interactive processing since the generation stage of the opaque vertices is running in GPU pipeline. The rendering results of our algorithm are identical to the that of general GPU ray-casting, but the performance can be up to more than 10 times faster.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.733-742
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to this reason, memory usage for data stream analysis should be confined finitely although new data elements are continuously generated in a data stream. To satisfy this requirement, data stream processing sacrifices the correctness of its analysis result by allowing some errors. The old distribution statistics are diminished by a predefined decay rate as time goes by, so that the effect of the obsolete information on the current result of clustering can be eliminated without maintaining any data element physically. This paper proposes a grid based clustering algorithm for a data stream. Given a set of initial grid cells, the dense range of a grid cell is recursively partitioned into a smaller cell based on the distribution statistics of data elements by a top down manner until the smallest cell, called a unit cell, is identified. Since only the distribution statistics of data elements are maintained by dynamically partitioned grid cells, the clusters of a data stream can be effectively found without maintaining the data elements physically. Furthermore, the memory usage of the proposed algorithm is adjusted adaptively to the size of confined memory space by flexibly resizing the size of a unit cell. As a result, the confined memory space can be fully utilized to generate the result of clustering as accurately as possible. The proposed algorithm is analyzed by a series of experiments to identify its various characteristics

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.16-23
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• 2019

Fine particulate matter known as PM 2.5 refers to the atmospheric particulate matter that has a diameter less than 2.5 micrometer identified as dangerous element for human health and its concentration can provide us a clear picture about air dust concentration. Humans stay indoor almost 90% of their life time and also there is no official indoor dust concentration data, so our study is focused on measuring the indoor air quality. Indoor dust data monitoring is very important in hospital environments beside that other places can also be considered for monitoring like classrooms, cements factories, computer server rooms, petrochemical storage etc. In this paper, visible light communication system is proposed by Manchester encoding technique for electromagnetic interference (EMI)-free indoor dust monitoring. Important indoor environment information like dust concentration is transferred by visible light channel in wide range. An average voltage-tracking technique is utilized for robust light detection to eliminate ambient light and low-frequency noise. The incoming light is recognized by a photo diode and are simultaneously processed by a receiver micro-controller. We can monitor indoor air quality in real-time and can take necessary action according to the result.