• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.1-10
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• 2004

A web robot is a software that has abilities of tracking and collecting web documents on the Internet(l), The performance scalability of recent web robots reached the limit CIS the number of web documents on the internet has increased sharply as the rapid growth of the Internet continues, Accordingly, it is strongly demanded to study on the performance scalability in searching and collecting documents on the web. 'Design of web robot based on Multi-Agent to speed up documents collection ' rather than 'Sequentially executing Web Robot based on the existing Fork-Join method' and the results of analysis on its performance scalability is presented in the thesis, For collection speedup, a Multi-Agent based web robot performs the independent process for inactive URL ('Dead-links' URL), which is caused by overloaded web documents, temporary network or web-server disturbance, after dividing them into each agent. The agents consist of four component; Loader, Extractor, Active URL Scanner and inactive URL Scanner. The thesis models a Multi-Agent based web robot based on 'Amdahl's Law' to speed up documents collection, introduces a numerical formula for collection speedup, and verifies its performance improvement by comparing data from the formula with data from experiments based on the formula. Moreover, 'Dynamic URL Partition algorithm' is introduced and realized to minimize the workload of the web server by maximizing a interval of the web server which can be a collection target.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.1
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• pp.165-173
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• 2023

Various linear system solvers with multi-physics analysis schemes are compared focusing on the near-field region considering thermal-hydraulic-chemical (THC) coupled multi-physics phenomena. APro, developed at KAERI for total system performance assessment (TSPA), performs a finite element analysis with COMSOL, for which the various combinations of linear system solvers and multi-physics analysis schemes should to be compared. The KBS-3 type disposal system proposed by Sweden is set as the target system and the near-field region, which accounts for most of the computational burden is considered. For comparison of numerical analysis methods, the computing time and memory requirement are the main concerns and thus the simulation time is set up to one year. With a single deposition hole problem, PARDISO and GMRES-SSOR are selected as representative direct and iterative solvers respectively. The performance of representative linear system solvers is then examined through a problem with an increasing number of deposition holes and the GMRES-SSOR solver with a segregated scheme shows the best performance with respect to the computing time and memory requirement. The results of the comparative analysis are expected to provide a good guideline to choose better numerical analysis methods for TSPA.

• Transactions of Materials Processing
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• v.32 no.4
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• pp.208-214
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• 2023

This paper discusses the deformation characteristics of a scaled-down automotive outer door panel with vacuum-assisted incremental sheet forming. The vacuum condition between the die and Al6052-H32 sheet with a thickness of 1.0 mm is reviewed with the goal of improving the geometrical accuracy of the target product. The material flow according to the forming tool path, including the multi-tool path and conventional contour tool path, is investigated considering the degradation of the pillow effect. To reduce friction between the tool and the sheet during incremental forming, automotive engine oil (5W-30) is used as a lubricant, and the strain field on the surface of the formed product is analyzed using ARGUS. By comparing the geometry and material flow characteristics of products under different test conditions, it is confirmed that the product surface quality can be significantly improved when the vacuum condition is employed in conjunction with a multi-tool path strategy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.109-114
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• 2024

The effect of inter-channel coupling in multi-channel monopulse receiver is expected to increase by miniaturization trend of receiver. Therefore, in this paper, calibration method is proposed to compensation for inter-channel coupling in receiver of monopulse radar. And it can prevent distortion of angle information of target. Hardware configuration that consists of switch, directional coupler, matched load, ADC(Analog to Digital Converter), signal source of calibration is proposed to calibration. Total nine scattering parameters are obtained by controlling the switch and signal source of calibration. After that, method for restoring the undistorted signal is proposed using the mathematical relationship between the monopulse signal output from the antenna and the monopulse signal passing through the multi-channel receiver in the presence of inter-channel coupling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1888-1906
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• 2024

Aiming at the problems that the edge of melanoma image is fuzzy, the contrast with the background is low, and the hair occlusion makes it difficult to segment accurately, this paper proposes a model MSCNet for melanoma segmentation based on U-net frame. Firstly, a multi-scale pyramid fusion module is designed to reconstruct the skip connection and transmit global information to the decoder. Secondly, the contextural information conduction module is innovatively added to the top of the encoder. The module provides different receptive fields for the segmented target by using the hole convolution with different expansion rates, so as to better fuse multi-scale contextural information. In addition, in order to suppress redundant information in the input image and pay more attention to melanoma feature information, global channel attention mechanism is introduced into the decoder. Finally, In order to solve the problem of lesion class imbalance, this paper uses a combined loss function. The algorithm of this paper is verified on ISIC 2017 and ISIC 2018 public datasets. The experimental results indicate that the proposed algorithm has better accuracy for melanoma segmentation compared with other CNN-based image segmentation algorithms.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.225-233
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• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1470-1475
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• 2009

Until now for the safety of structures and equipment monitoring technology to measure the amount of the physical, if that is the one, one-point or single-source target is one the most. Therefore, becoming more numerous and complex to measure the amount of physical measurement technology that is comprehensive and complex, multi-source concepts to the monitoring of a multi-sensing technology is required. Have the same characteristics of multi-source multi-use space such as a multi-structure of facilities/equipment is. The people's safety in a multi-use facility will be directly related to life and even a little carelessness can lead to large-scale disaster occurs because of several factors, risks and to manage detect in advance the development of an intelligent monitoring technology is essential. Therefore, this study shows that multiple structures/facilities to improve the quality of human life in research to maintain a safe and comfortable living space for multi-source intelligence to the development of monitoring technology to achieve that goal, and the ubiquitous sensor network system on the basis of the wireless transmission module, and multiple research facilities/equipment for the ultra-small sensors for health monitoring study was performed.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.65-74
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• 2016

Ship ad-hoc network (SANET) extends the coverage of the maritime communication among ships with the reduced cost. To fulfill the growing demands of real-time services, the SANET requires an efficient clock time synchronization algorithm which has not been carefully investigated under the ad-hoc maritime environment. This is mainly because the conventional algorithms only suggest to decrease the beacon collision probability that diminishes the clock drift among the units. However, the SANET is a very large-scale network in terms of geographic scope, e.g., with 100 km coverage. The key factor to affect the synchronization performance is the signal propagation delay, which has not being carefully considered in the existing algorithms. Therefore, it requires a robust multi-hop synchronization algorithm to support the communication among hundreds of the ships under the maritime environment. The proposed algorithm has to face and overcome several challenges, i.e., physical clock, e.g., coordinated universal time (UTC)/global positioning system (GPS) unavailable due to the atrocious weather, network link stability, and large propagation delay in the SANET. In this paper, we propose a logical clock synchronization algorithm with multi-hop function for the SANET, namely multi-hop clock synchronization for SANET (MCSS). It works in an ad-hoc manner in case of no UTC/GPS being available, and the multi-hop function makes sure the link stability of the network. For the proposed MCSS, the synchronization time reference nodes (STRNs) are efficiently selected by considering the propagation delay, and the beacon collision can be decreased by the combination of adaptive timing synchronization procedure (ATSP) with the proposed STRN selection procedure. Based on the simulation results, we finalize the multi-hop frame structure of the SANET by considering the clock synchronization, where the physical layer parameters are contrived to meet the requirements of target applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.980-997
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• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.