The Journal of Korean Institute of Communications and Information Sciences
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v.35
no.3B
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pp.408-420
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2010
On a Mobile Ad hoc NETwork(MANET), it is difficult to detect and prevent misbehaviors nodes existing between end nodes, as communication between remote nodes is made through multiple hop routes due to lack of a fixed networked structure. Therefore, to maintain MANET's performance and security, a technique to identify misbehaving middle nodes and nodes that are compromise by such nodes is required. However, previously proposed techniques assumed that nodes comprising MANET are in a friendly and cooperative relationship, and suggested only methods to identify misbehaving nodes. When these methods are applied to a larger-scale MANET, large overhead is induced. As such, this paper suggests a system model called Secure Cluster-based MANET(SecCBM) to provide secure communication between components aperANET and to ensure eed. As such, this pand managems suapemisbehavior nodes. SecCBM consists apetwo stages. The first is the preventis pstage, whereemisbehavior nodes are identified when rANET is comprised by using a cluster-based hierarchical control structure through dynamic authentication. The second is the post-preventis pstage, whereemisbehavior nodes created during the course apecommunication amongst nodes comprising the network are dh, thed by using FC and MN tables. Through this, MANET's communication safety and efficiency were improved and the proposed method was confirmed to be suitable for MANET through simulation performance evaluation.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.20
no.5
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pp.113-120
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2020
Safety accidents, called industrial accidents in construction work, are causing a lot of casualties, property damage and social controversy in the event of an accident, causing the construction to lose public confidence. The risk of safety accidents at construction sites may continue to increase as the construction of high-rise, large-scale, and multi-purpose complex buildings has increased in recent years. In particular, the most frequently constructed apartment construction among reinforced concrete buildings is designed and constructed with a wall-like structure with no beams for each floor, while the lower floors are made of lamen with columns and beams. As a result, the transfer beam or transfer slab to withstand the upper load is installed on the upper part of the Ramen structure, so the system Dongbari, which is installed as a temporary material during concrete laying construction, may collapse at any time during plowing and curing. The purpose of this study is to apply IT convergence technology to prevent the collapse of the system Dongbari during concrete installation, and to apply many of the variables that may occur during construction on a case-by-case basis to check the stability of the system Dongbari and to propose a model of the anti-conducting prediction system.
In this paper, it was analyzed the variation of hydraulic characteristics through changing discharge at main channel and lateral channel and state of hydraulic structure at the natural channel junction by experiment. The experimental area is chosen at the channel junction of Nam-Han river and Pyeongchang river. The scale of the experiment is 1/200 in horizontal, and 1/66.7 in vortical, so the distoration rate is 3. From the experiment, the reduction effect of the water level is $12\%$ in the case of removing intank dam, and $5\%$ at the hydro-electronic dam removing case. Furthermore, in the case of two hydraulic structures removing, the reduction effect of water level is $18\%$ at the channel junction. Also, the stagnation zone, which is cased diminution of the channel at the junction, is decreasing through removing the structures.
Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.
Ye-Eun, Lee;Seung-Hwa, Han;Dong-Gyu, Lee;Ho-Joon, Kim
KIPS Transactions on Software and Data Engineering
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v.12
no.1
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pp.51-58
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2023
In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.
The Framework Act on the Management of Disasters and Safety 2004(FAMDS) currently underpins Korean civil protection system, and under this FAMDS, Korean civil protection establishes a three-tiered government structure for dealing with crises and disasters: central government, provincial & metropolitan government, and local government tiers. In particular, the concept of Integrated Emergency Management(IEM) emphasizes that emergency response organizations should work and act together to respond to crises and disasters effectively, based on the coordination and cooperation model, not the command and control model. In tune with this trend, civil protection matters are, first, dealt with by local responders at the local level without direct involvement of central or federal government in the UK or USA. In other words, central government intervention is usually implemented in the UK and the USA, only when the scale or complexity of a civil protection issue is so vast, and thus requires a degree of central government coordination and support, resting on the severity and impact of the event. In contrast, it appears that civil protection mechanism in Korea has adopted a rigid centralized system within the command and control model, and for this reason, central government can easily interfere with regional or local command and control arrangements; there is a high level of central government decision-making remote from a local area. The principle of subsidiarity tends to be ignored. Under these circumstances, it is questionable whether such top-down arrangements of civil protection in Korea can manage uncertainty, unfamiliarity and unexpectedness in the age of Risk Society and Post-modern society, where interactive complexity is increasingly growing. In this context, the study argues that Korean civil protection system should move towards the decentralized model, based on coordination and cooperation between responding organizations, loosening the command and control structure, as with the UK or the USA emergency management arrangements. For this argument, the study basically explores mechanisms of civil protection arrangements in Korea under current legislation, and then finally attempts to make theoretical suggestions for the future of the Korean civil protection system.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.5
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pp.125-141
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2021
The rapidly changing social structure of the digital environment is having a significant impact on economic activities. That is also an important issue for Individuals who want to sustain economic activities and countries that support policies. Non-face-to-face industries have been revitalized due to the problem of human capital utilization attributed to aging population, the real economic recession caused by Corona 19, contraction of face-to-face economic activities, reduction of employment, and job instability. Accordingly, digital media contents based economic activities have become commonplace, and the government's main policy issue is to use human capital effectively for media contents based economic activities. Adaptation to the digital environment has become a necessity, not a choice, for those who wish to continue to be in employment. Therefore, this study analyzed the effects of digital and individual abilities on intention to sustain the economic activity and verified the modulation effect of the role model. In order to achieve the purpose of this research, an online survey was conducted on men and women aged 20 to 80 nationwide, and 382 of the 385 collected questionaires were analyzed. The SPSS 23.0 program was used to analyze this study, and the questionaire questions were measured using the Likert 5-point scale. As a result of the analysis, first, the ability to utilize media contents in digital capacity has a positive impact on the intention to sustain economic activity, and that the higher the ability to utilize the latest digital media contents such as SNS, the more likely the intention to sustain economic activity. Secondly, it was found that the financial strength of individuals' abilities was affected by the negative impact, and that the experiences were affected by positive(+) impact on the intention to sustain economic activity. Thirdly, the social environment has no significant effect on the intention to sustain economic activity. Fourth, it was found that family support amongst social support has a positive impact on the intention to sustain economic activity, and that various emotional support for families has increased intention to sustain economic activity. Fifth, the role model was found to have a positive(+) impact on economic sustainability, while the ability to utilize media content and family support played a modulating role on economic sustainability. Therefore, as a result of this research, the government's policy support for employment and entrepreneurship is required in accordance with digital media content based digital education and human structure in order to sustain economic activities.
Journal of Korean Society of Coastal and Ocean Engineers
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v.29
no.2
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pp.109-120
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2017
A discounted cost model for preventive maintenance of armor units of rubble-mound breakwaters is mathematically derived by combining the deterioration model based on a discrete-time stochastic process of shock occurrence with the cost model of renewal process together. The discounted cost model of condition-based maintenance proposed in this paper can take into account the nonlinearity of cumulative damage process as well as the discounting effect of cost. By comparing the present results with the previous other results, the verification is carried out satisfactorily. In addition, it is known from the sensitivity analysis on variables related to the model that the more often preventive maintenance should be implemented, the more crucial the level of importance of system is. However, the tendency is shown in reverse as the interest rate is increased. Meanwhile, the present model has been applied to the armor units of rubble-mound breakwaters. The parameters of damage intensity function have been estimated through the time-dependent prediction of the expected cumulative damage level obtained from the sample path method. In particular, it is confirmed that the shock occurrences can be considered to be a discrete-time stochastic process by investigating the effects of uncertainty of the shock occurrences on the expected cumulative damage level with homogeneous Poisson process and doubly stochastic Poisson process that are the continuous-time stochastic processes. It can be also seen that the stochastic process of cumulative damage would depend directly on the design conditions, thus the preventive maintenance would be varied due to those. Finally, the optimal periods and scale for the preventive maintenance of armor units of rubble-mound breakwaters can be quantitatively determined with the failure limits, the levels of importance of structure, and the interest rates.
Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.
The purpose of this study was to validate the Korean Implementation Fidelity Checklist of Tier 1 School-Wide Positive Behavior Support (KIFC-T1) for use in the Korean educational system. Tier 1 support, which is universal supports, within a multi-tiered, school-wide positive behavior support (SWPBS) model, aims to provide support to and prevent problem behaviors among all students in a school. The initial KIFC-T1 consisted of 48 items and 11 factors and was developed based on a literature review. Its content was validated by experts. The validated KIFC-T1 was introduced to 185 special school teachers who had experience implementing SWPBS and who used the instrument to assess the degree to which their schools had implemented Tier 1 support. Based on their responses, the construct validity of the KIFC-T1 was examined using factor, item, and internal consistency reliability analyses. The concurrent validity of the tool was examined using the PBS Evaluation Tool, School Climate Questionnaire, School Discipline Practice Scale, and PBS Effectiveness Scale. The analyses revealed that KIFC-T1 had a stable five-factor structure with 35 items, had good reliability (Cronbach's α=.956, each factor's Cronbach's α=.834-.951), and its results were statistically significantly correlated with those of the PBS Evaluation Tool, School Discipline Practice Scale, and the PBS Effectiveness Scale. However the KIFC-T1's results were not statistically significantly correlated with the results of the School Climate Questionnaire. These results suggest that KIFC-T1 is a reliable and valid tool for assessing the fidelity of universal support implementations.
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