• Journal of the Korean Geotechnical Society
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• v.20 no.4
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• pp.89-102
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• 2004

The generated blasting pressure wave initiated under decoupled-charge condition is a function of peak blasting pressure, rise time, and wave-shape function. The peak blasting pressure and the rise time are also the function of explosive and rock properties. The probabilistic distributions of explosive and rock properties are derived from the results of their property tests. Since the probabilistic distributions of explosive and rock properties displayed a normal distribution, the peak blasting pressure and the rise time can also be regarded as a normal distribution. Parameter analysis and uncertainty analysis were performed to identify the most influential parameter that affects the peak blasting pressure and the rise time. Even though the explosive properties were found to be the most influential parameters on the peak blasting pressure and the rise time from the parameter analyses, the result of uncertainty analysis showed that rock properties constituted major uncertainties in estimating the peak blasting pressure and the rise time rather than explosive properties. Damage and overbreak of the remaining rock around the excavation line induced by blasting were evaluated by dynamic numerical analysis. A user-subroutine to estimate the rock damage was coded based on the continuum damage mechanics. This subroutine was linked to a commercial program called 'ABAQUS/Explicit'. The results of dynamic numerical analysis showed that the rock damages generated by the initiation of stopping hole were larger than those from the initiation of contour hole. Several methods to minimize those damages were proposed such as relocation of stopping hole, detailed subdivision of rock classification, and so on. It was found that fracture probability criteria and fractured zones could be distinctively identified by applying fuzzy-random probability.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.73-80
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• 2004

Recently, many maritime accidents have been increased and the collisions due to human error are given a great deal of proportions out if them We develop the Real-time Collision Risk Monitoring System (CRMS) for the navigational officers to cope with the emergency situation promptly and thus to reduce the probability if casualty. In this study, the risk of collision is evaluated by two kinds if method. The first method is based on Fuzzy algorithm, which evaluates the risk of collision between traffic ships. The second method is based on Environmental Stress (ES) Model, where the total risk if collision is evaluated by the environmental stress felt by human. The developed real-time CRMS has been installed to the ship handling simulator system and its capabilities have been tested through simulator experiments.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.408-414
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• 2013

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.23-28
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• 2021

The article discusses the features of adaptation of the parameters of the physical layer of data transmission in self-organizing networks based on unmanned aerial vehicles operating in the conditions of "smart cities". The concept of cities of this type is defined, the historical path of formation, the current state and prospects for further development in the aspect of transition to "smart cities" of the third generation are shown. Cities of this type are aimed at providing more comfortable and safe living conditions for citizens and autonomous automated work of all components of the urban economy. The perspective of the development of urban mobile automated technical means of infocommunications is shown, one of the leading directions of which is the creation and active use of wireless self-organizing networks based on unmanned aerial vehicles. The advantages of using small-sized unmanned aerial vehicles for organizing networks of this type are considered, as well as the range of tasks to be solved in the conditions of modern "smart cities". It is shown that for the transition to self-organizing networks in the conditions of "smart cities" of the third generation, it is necessary to ensure the adaptation of various levels of OSI network models to dynamically changing operating conditions, which is especially important for the physical layer. To maintain an acceptable level of the value of the bit error probability when transmitting command and telemetry data, it is proposed to adaptively change the coding rate depending on the signal-to-noise ratio at the receiver input (or on the number of channel decoder errors), and when transmitting payload data, it is also proposed to adaptively change the coding rate together with the choice of modulation methods that differ in energy and spectral efficiency. As options for the practical implementation of these solutions, it is proposed to use an approach based on the principles of neuro-fuzzy control, for which examples of determining the boundaries of theoretically achievable efficiency are given.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.126-135
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• 2011

In this study, the algorithm for priority area of forest fire surveillance was developed to enhance the effectiveness of fire detection. The high priority surveillance area for forest fire detection was defined as the area with not only low value of viewshed analysis of the lookouts and detection cameras but also high fire occurrence probability. To build the priority map, fuzzy function and map algebra were used. The analysis results of Bonghwa-gun, Gyeongbuk Province, showed that the surveillance priority of central and southern area is higher than north area. This algorithm could be used in the allocation of fire prevention resources and selection of suitable point for new fire detection system.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.73-80
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• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

• Journal of Korean Society of Forest Science
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• v.110 no.1
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• pp.53-63
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• 2021

Sophora koreensis Nakai is an indigenous plant in Koreawith a restricted natural range, part of which is in Gangwon province. The species is known to contain phytochemicals that have beneficial effects on human health, and it is economically important in bioindustry. Because of the limited number of plants in a small range of habitats, the mass-propagation method should be developed for use and conservation. In vitro tissue culture is a reliable method in terms of mass propagation from selected clones of the species. We investigated the optimal conditions of the medium in this process, especially focusing on the concentrations of plant growth regulators(PGRs) in the culture of stem-containing axillary buds. Three statistical methods, i.e., ANOVA, response surface method(RSM), and fuzzy clustering were used to analyze the plant growth, number of shoots induced, and shoot length with various combinations of PGRs. Results from the RSM differed from those of the other two methods; thus, the method was not suitable. ANOVA and fuzzy clustering showed similar results. However, more accurate results were obtained using fuzzy clustering because it provided a probability for each treatment. On the basis of the fuzzy clustering analysis, stem tissue produced the greatest number of shoots(11.03 per explant; 63.33%) on a medium supplemented with 5-��M 6-benzylaminopurine and 2.5-��M thidiazuron(TDZ). Proliferation of shoots(2.18 ± 0.21 cm, 63.33%) was attained on a medium supplemented with 2.5-��M BA, 2.5-��M TDZ, and 2.5-��M gibberellic acid.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.107-120
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• 2022

The purpose of this study is to analyze the net effect and the combined effect of the determinants of the likelihood of start-up success of researchers at public research institutes. Based on the existing literature, the determinants of the researcher's likelihood of start-up success were reviewed, and a conceptual relationship between the determinants of the likelihood of start-up success was established. Data collection was conducted through a survey targeting researchers at public research institutes, and a total of 114 data were collected. The partial least squares (PLS) analysis method was used to analyze the net effect of the likelihood of start-up success determinant, and the fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the combined effect of the likelihood of start-up success determinant. In the PLS analysis results, it was found that technology commercialization probability and creative self-efficacy had a significant positive effect independently on the likelihood of start-up success. In the fsQCA results, we found a combined effect of increasing the likelihood of start-up success when the technology commercialization probability, technology commercialization capability, and creative self-efficacy were high. These research results provide academic implications for understanding the determinants of the likelihood of start-up success of researchers in public research institutes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.