• Earthquakes and Structures
• /
• v.1 no.1
• /
• pp.109-127
• /
• 2010

This work aims at introducing structural sensitivity analysis capabilities into existing commercial finite element software codes for the purpose of mapping retrofit strategies for a broad group of structures including heritage-type buildings. More specifically, the first stage sensitivity analysis is implemented for the standard deterministic environment, followed by stochastic structural sensitivity analysis defined for the probabilistic environment in a subsequent, second phase. It is believed that this new generation of software that will be released by the industrial partner will address the needs of a rapidly developing specialty within the engineering design profession, namely commercial retrofit and rehabilitation activities. In congested urban areas, these activities are carried out in reference to a certain percentage of the contemporary building stock that can no longer be demolished to give room for new construction because of economical, historical or cultural reasons. Furthermore, such analysis tools are becoming essential in reference to a new generation of national codes that spell out in detail how retrofit strategies ought to be implemented. More specifically, our work focuses on identifying the minimum-cost intervention on a given structure undergoing retrofit. Finally, an additional factor that arises in earthquake-prone regions across the world is the random nature of seismic activity that further complicates the task of determining the dynamic overstress that is being induced in the building stock and the additional demands placed on the supporting structural system.

• Journal of Korea Water Resources Association
• /
• v.30 no.3
• /
• pp.225-233
• /
• 1997

The nonlinear effects on the statistical properties of wave groups in terms of the average nomber of waves in a group and the mean number of waves in a high run is studied in this paper utilizing the complex envelope and total phase function, random variable transformation technique and perturbation method. It tures out that the phase distribution is modified significantly by nonlinearities and it show systematic excess of values near the mean phase and the corresponding symmetrical deficiency on both sides away from the mean. for the case of threshold crossing rate, it turns out that threshold crossing rate reaches its maxima just below the mean water level rather than zero and considerable amount of probability mass is shifted toward the larger values of water surface elevation as nonlinearity is getting profound. Furthermore, the mean waves in a high run associated with nonlinear wave are shown to have larger values than the linear counterpart. Similar trend can also be found in the average number of waves in a group.

• The Plant Pathology Journal
• /
• v.31 no.1
• /
• pp.33-40
• /
• 2015

Pigeonpea Sterility Mosaic Disease (PSMD) is an important foliar disease caused by Pigeonpea sterility mosaic virus (PPSMV) which is transmitted by eriophyid mites (Aceria cajani Channabasavanna). In present study, a F2 mapping population comprising 325 individuals was developed by crossing PSMD susceptible genotype (Gullyal white) and PSMD resistant genotype (BSMR 736). We identified a set of 32 out of 300 short decamer random DNA markers that showed polymorphism between Gullyal white and BSMR 736 parents. Among them, eleven DNA markers showed polymorphism including coupling and repulsion phase type of polymorphism across the parents. Bulked Segregant Analysis (BSA), revealed that the DNA marker, IABTPPN7, produced a single coupling phase marker (IABTPPN $7_{414}$) and a repulsion phase marker (IABTPPN $7_{983}$) co-segregating with PSMD reaction. Screening of 325 F2 population using IABTPPN7 revealed that the repulsion phase marker, IABTPPN $7_{983}$, was co-segregating with the PSMD responsive SV1 at a distance of 23.9 cM for Bidar PPSMV isolate. On the other hand, the coupling phase marker IABTPPN $7_{414}$ did not show any linkage with PSMD resistance. Additionally, single marker analysis both IABTPPN $7_{983}$ (P<0.0001) and IABTPPN $7_{414}$ (P<0.0001) recorded a significant association with the PSMD resistance and explained a phenotypic variance of 31 and 36% respectively in $F_2$ population. The repulsion phase marker, IABTPPN7983, could be of use in Marker-Assisted Selection (MAS) in the PPSMV resistance breeding programmes of pigeonpea.

• Smart Structures and Systems
• /
• v.25 no.3
• /
• pp.369-384
• /
• 2020

A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l₁-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_3
• /
• pp.1109-1123
• /
• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.10
• /
• pp.1167-1175
• /
• 2016

This paper proposes an efficient page-level mapping algorithm that reduces the erase count in the FTL for flash memory systems. By maintaining the weight for each write request in the request buffer, the proposed algorithm estimates the degree of temporal locality for each incoming write request. To exploit temporal locality deliberately for determination of hot request, the degree of temporal locality should be much higher than the reference point determined experimentally. While previous LRU algorithm treats a new write request to have high temporal locality, the proposed algorithm allows write requests that are estimated to have high temporal locality to access hot blocks to store hot data intensively. The pages are more frequently updated in hot blocks than warm blocks. A hot block that has most of invalid pages is always selected as victim block at Garbage Collection, which results in delayed erase operation and in reduced erase count. Experimental results show that erase count is reduced by 9.3% for real I/O workloads, when compared to the previous LRU algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.4
• /
• pp.544-553
• /
• 2013

In this paper, we propose the pattern classifier of Radial Basis Function Neural Networks(RBFNNs) for diagnosis of 3-phase partial discharge. Conventional methods map the partial discharge/noise data on 3-PARD map, and decide whether the partial discharge occurs or not from 3-phase or neutral point. However, it is decided based on his own subjective knowledge of skilled experter. In order to solve these problems, the mapping of data as well as the classification of phases are considered by using the general 3-PARD map and PA method, and the identification of phases occurring partial discharge/noise discharge is done. In the sequel, the type of partial discharge occurring on arbitrary random phase is classified and identified by fuzzy clustering-based polynomial Radial Basis Function Neural Networks(RBFNN) classifier. And by identifying the learning rate, momentum coefficient, and fuzzification coefficient of FCM fuzzy clustering with the aid of PSO algorithm, the RBFNN classifier is optimized. The virtual simulated data and the experimental data acquired from practical field are used for performance estimation of 3-phase partial discharge pattern classifier.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.631-634
• /
• 2002

In this paper, we propose an improved optical security system using three phase-encoded images and the principle of interference. This optical system based on a Mach-Zehnder interferometer consists of one phase-encoded virtual image to be encrypted and two phase-encoded images, encrypting image and decrypting image, where every pixel in the three images has a phase value of '0' and '$\pi$'. The proposed encryption is performed by the multiplication of an encrypting image and a phase-encoded virtual image which dose not contain any information from the decrypted image. Therefore, even if the unauthorized users steal and analyze the encrypted image, they cannot reconstruct the required image. This virtual image protects the original image from counterfeiting and unauthorized access.. The decryption of the original image is simply performed by interfering between a reference wave and a direct pixel-to-pixel mapping image of the encrypted image with a decrypting image. Both computer simulations and optical experiments confirmed the effectiveness of the proposed optical technique for optical security applications.

• Korean Institute of Interior Design Journal
• /
• v.13 no.2
• /
• pp.64-71
• /
• 2004

This study attempts to clarify inter-relationship between design expression in the surface of contemporary multi-family housing and physical trends in this digital age. The study examines characteristics of housing design influenced from new digital technology in the forms of metaphor such as dematerialization, fluidity and mobility. Currently constructed multi-family housing in Europe after 1990 has been analyzed to find digital reflections in the surfaces. As a conclusion, findings are as follows; In this digital age, a house is considered as a base in the forms of boxes and containers to network to outer worlds. In a complex of multi-family housing, public spaces move to the inside and become parts of private domain. Therefore, a house directly faces a street/outer world without transitional areas and devices. The facades of housing become delicate skins to control private domain in the inside and the world in the outside. In this digital age, the surfaces of housing are designed by ways of wrapping and screening. Printing and mapping methods are used to surface design because they are manipulative and flexible methods in design like graphic design. Screening devices using louvers and shutters are powerful tools to make random and unpredictable images. If units of a louver and a shutter were pixels, a whole surface would be a digital screen. In such assumption, the facade of buildings reflects digital screen to interface while the louvers in operation reflect clicking to network. As a conclusion, design expression in surfaces in-between of multi-family housing is a metaphor of digital mechanism.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.3 no.2
• /
• pp.12-17
• /
• 2010

An automatic facial feature points(FFPs) detection system is proposed. A face is represented as a graph where the nodes are placed at facial feature points(FFPs) labeled by their Gabor features and the edges are describes their spatial relations. An innovative flexible feature matching is proposed to perform features correspondence between models and the input image. This matching model works likes random diffusion process in the image space by employing the locally competitive and globally corporative mechanism. The system works nicely on the face images under complicated background, pose variations and distorted by facial accessories. We demonstrate the benefits of our approach by its implementation on the system.