• 전자공학회논문지B
• /
• 제33B권10호
• /
• pp.90-97
• /
• 1996

This paper presents an efficient parallel implementation and its performance evaluations of a SOFM neural netowrk on the multicomputer. We investigate the parallel performance as the size of a neural network N, the number of the patterns L, and the number of the processors p increase. We propose an analytica performance evaluation model for eac of the parallel implementations and verified the validity of the model through experiments. Analytical result show that the number of processors for a maximum speedup of the network decomposition nd the training-set decomposition increases in proportion to .root.N and .root.L, respectively. The performances of the both decompositions depend on the number of training patterns L and the size of the neural network N and, if L.geq.0.423N, the performance of trhe training-set decomposition is proved to be better than that of the network decomposition.

• ETRI Journal
• /
• 제37권5호
• /
• pp.990-1000
• /
• 2015

This paper presents an overlapping pattern substitution (PS) method. The original overlapping PS method as a reversible data hiding scheme works well with only four pattern pairs among fifteen possible such pairs. This paper generalizes the original PS method so that it will work well with an optimal pair from among the fifteen possible pattern pairs. To implement such an overlapping PS method, changeable and embeddable patterns are first defined. A class map is virtually constructed to identify the changeable and embeddable pairs. The run-lengths between consecutive least probable patterns are recorded. Experiments show that an implementation of our overlapping PS method works well with any possible type of pairs. Comparison results show that the proposed method achieves more embedding capacity, a higher PSNR value, and less human visual distortion for a given embedding payload.

• 한국생산제조학회지
• /
• 제21권1호
• /
• pp.58-64
• /
• 2012

Instead of the surface pattern arranged repeatedly in two axial direction on a plane, we propose double patterns superposing two one-axial linear patterns as a reference target for surface encoding. A upper layer of the superposed pattern is the transparent glass with grooves cut in it at a fixed pitch. The position is sensed by detecting a shift of beam due to difference of a refractive index. And a lower layer is the aluminum with color-coated grooves. The amount of beam reflected on the layer varies according to its targeting position and is detected for encoding. For the above reference pattern, we can detect two-axial positions using only the single beam. Furthermore, the pattern size can be expanded with a size of the detector kept constant, meaning that the measured range can be expanded easily. In this paper, we review the existing optical encoding methods for grid pattern, and discuss the hardware implementation of the suggested surface encoding method.

• 산업기술연구
• /
• 제30권A호
• /
• pp.9-15
• /
• 2010

Recently, Smart Grid is a emerging topic in power and communication industry. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. In order to successful implementation of Smart Grid, energy management function will be the key factor that coordinates and optimally controls the various loads according to the operating condition and environments, and the load patterns in residential and commercial building will be required as fundamental element for load management. In this study, we collects many types of energy usage data of electric appliances, analyze their load curves, and make the general load patterns for electrical appliance.

• 산업기술연구
• /
• 제30권A호
• /
• pp.3-8
• /
• 2010

Recently, There have been many attempts to optimize energy usage in buildings and houses using Information Technology(IT) and the typical implementation can be found in Intelligent Building and Zero Energy Building. These kinds of buildings need to forecast the building loads, estimate the capacity requirement for power supply, and decide the capacity of the main transformer of the building. Currently, the capacity of the main transformer has been decided just using typical load estimation method not considering the load characteristics and patterns. In this paper, we propose a new load estimation method considering the load characteristics and patterns of the builiding. The proposed method was applied to actual mail center and verified the feasibility of application to actual design of buildings.

• 한국멀티미디어학회논문지
• /
• 제19권8호
• /
• pp.1544-1552
• /
• 2016

If the undo/redo function is not reflected in the initial design of an application, it makes it difficult to implement the undo/redo function additionally, in this paper, we examined some examples to design the sodoku game and analyzed problems of the design to implement the undo/redo functions. For an efficient design of the undo/redo functions without using swing.undo package, we propose a class design using the Command, Memento, and Observer pattern these are used as organic. The proposed method is more efficient for distributed work than other method. We implemented a sudoku game using proposed design. In the undo/redo function testing, we could see that it works well.

• 국제초고층학회논문집
• /
• 제7권4호
• /
• pp.409-415
• /
• 2018

Recently, many countries around the world began to show interest in safety against terrorism, fire, and natural disasters. This study aimed to propose a quantitative measurement system for emergency evacuation and safety for various kinds of terrorism and fire within high-rise multi-purpose facilities, which can measure the pedestrians' ordinary walking patterns in the concourse with the highest pedestrian volume out of all the spaces within multi-story buildings, predict pedestrians' evacuation walking lines when a sudden disaster breaks out, and analyze the gait coefficient, occupant density, and evacuation behavior time.

• 대한전자공학회논문지SD
• /
• 제38권11호
• /
• pp.810-820
• /
• 2001

전통적인 이진 가산기는 최상위 비트까지 올림수 전달이 발생하고 직렬가산을 수행한다. 그러나, 변형부호화자리수 체계를 이용한 광가산기는 이진 가산기에서 발생하는 연속적인 올림수 전달을 제한하도록 제안되었다. 본 논문에서는 9가지 부호화된 입력 패턴 중에서 동일한 가산 결과를 가지는 패턴을 동일군으로 하여 5개의 기준패턴으로 만들어 기호치환 규칙수를 줄였다. 또한 결합공간부호화된 입력 패턴과 마스크의 직렬연결로 기존의 기호치환 가산기의 인식 단계에서 필요한 어떤 공간적인 연산없이 인식하여 시스템의 크기를 줄였다.

• Computers and Concrete
• /
• 제1권3호
• /
• pp.303-324
• /
• 2004

The Component-Based Software Development (CBSD) has established itself as a sound paradigm in the software engineering discipline and has gained wide spread acceptance in the industry. The CBSD relies on the availability of standard software components for encapsulation of specific functionality. This paper presents the framework for the development of a software component for the design of general member cross-sections. The proposed component can be used in component-based structural engineering software or as a stand-alone program developed around the component. This paper describes the use-case scenarios for the component, its design patterns, object models, class hierarchy, the integrated and unified handling of cross-section behavior and implementation issue. It is expected that a component developed using the proposed patterns and model can be used in analysis, design and detailing packages to handle reinforced concrete, partially prestressed concrete, steel-concrete composite and steel sections. The component can provide the entire response parameters of the cross section including determination of geometric properties, elastic stresses, flexural capacity, moment-curvature, and ductility ratios. The component can also be used as the main computational engine for stand-alone section design software. The component can be further extended to handle the retrofitting and strengthening of cross-sections, shear and torsional response, determination of fire-damage parameters, etc.

• 전자공학회논문지B
• /
• 제31B권9호
• /
• pp.159-165
• /
• 1994

In this paper, we propose a multi-layer associative neural network structure suitable for hardware implementaion with the function of performance refinement and improved robutst capability. Unlike other methods which reduce network complexity by putting restrictions on synaptic weithts, we are imposing a requirement of hidden layer neurons for the function. The proposed network has synaptic weights obtainted by Hebbian rule between adjacent layer's memory patterns such as Kosko's BAM. This network can be extended to arbitary multi-layer network trainable with Genetic algorithm for getting hidden layer memory patterns starting with initial random binary patterns. Learning is done to minimize newly defined network error. The newly defined error is composed of the errors at input, hidden, and output layers. After learning, we have bidirectional recall process for performance improvement of the network with one-shot recall. Experimental results carried out on pattern recognition problems demonstrate its performace according to the parameter which represets relative significance of the hidden layer error over the sum of input and output layer errors, show that the proposed model has much better performance than that of Kosko's bidirectional associative memory (BAM), and show the performance increment due to the bidirectionality in recall process.