• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3738-3760
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• 2022

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.15-24
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• 2022

At present, there are few studies on signal control of pedestrian traffic flow and non-motor traffic flow at intersections. Research on the optimization scheme of mixed traffic flow signal control can coordinate and control the overall traffic flow of pedestrians, non-motor vehicles and motor vehicles, which is of great significance to improve the congestion at intersections. For the traffic optimization of intersections, this paper starts from two aspects: channelization optimization and phase design, and reduces the number of conflict points at intersections from spatial and temporal right-of-way allocation respectively. Taking the classical signal timing method as the theoretical basis, and aiming at ensuring the safety and time benefit of traffic travelers, a channelization optimization and signal control scheme of the intersection is proposed. The channelization and phase design methods of intersections with motor vehicles, non-motor vehicles and pedestrians as objects are discussed, and measures to improve the channelization optimization of intersections are proposed. A multi-objective optimization model of intersection signal control was established, and the model was solved based on NSGA-II algorithm.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.8-16
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• 2022

This paper presents the orbital control for positioning micro synthetic aperture radar (SAR) satellites for all-weather monitoring around the Korean Peninsula. In Small SAR technology experimental project (S-STEP) developed in Korea, multiple satellites are placed at equal intervals in multiple orbital planes to secure an average revisit period for the region around the Korean Peninsula. Satellites entering the same orbital plane use ion thrusters to control their orbits and the separation velocity from the launch vehicle to distribute them evenly across the orbit. For an orbital that places the satellites equally spaced in the same orbital plane, the shape of the satellite constellation is formed by adjusting the difference in drift rates between the satellites. This paper presents, different types of satellite constellations, and the results of satellite constellation placement according to launch strategies are presented. In addition, a method and limitations in shortening the duration of orbital deployment are presented.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.409-416
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• 2009

This paper presents a tool called Quality-Cost optimization system (QCOS), which integrates Multi-Objective Genetic Algorithm (MOGA) and Quality Function Deployment (QFD), for tradeoff between quality and cost of the unitized metal curtain-wall unit. A construction owner as the external customer pursues to maximize the quality of the curtain-wall unit. However, the contractor as the internal customer pursues to minimize the cost involved in designing, manufacturing and installing the curtain-wall unit. It is crucial for project manager to find the tradeoff point which satisfies the conflicting interests pursued by the both parties. The system would be beneficial to establish a quality plan satisfying the both parties. Survey questionnaires were administered to the construction owner who has an experience of curtain-wall project, the architects who are the independent assessor, and the contractors who were involved in curtain-wall design and installation. The Customer Requirements (CRs) and their importance weights, the relationship between CRs and Technical Attributes (TAs) consisting of a curtain-wall unit, and the cost ratios of each components consisting curtain-wall unit are obtained from the three groups mentioned previously. The data obtained from the surveys were used as the QFD input to compute the Owner Satisfaction (OS) and Contractor Satisfaction (CS). MOGA is applied to optimize resource allocation under limited budget when multi-objectives, OS and CS, are pursued at the same time. The deterministic multi-objective optimization method using MOGA and QFD is extended to stochastic model to better deal with the uncertainties of QFD input and the variability of QFD output. A case study demonstrates the system and verifies the system conformance.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.6
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• pp.636-642
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• 2022

The "Hydrogen Economic Activation Road map" was announced in 2019, and hydrogen demand is expected to exceed 470,000 tons per year in 2022 and keep increasing. Under this circumstance, it has become important to understand the greenhouse gas (GHG) emissions associated with various hydrogen production pathways. In this study, the evaluation of life cycle GHG emissions regarding the hydrogen produced as by-product from coke oven gas (COG) in steel mill is conducted. To cover the possible range of operations, three literatures were reviewed and their data of inputs and outputs for the process were adopted for calculation. Life cycle inventories and emission factors were mostly referred to GaBi and Intergovernmental Panel on Climate Change (IPCC) guidelines, respectively. When there are multiple products from a single process, the energy allocation method was applied. Based on these sources and the assumptions, the life cycle emission values of COG-based hydrogen were found to be 3.8 to 4.7 kg/CO₂-eq./kg-H₂.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• Korean Journal of Social Welfare
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• v.69 no.4
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• pp.99-125
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• 2017

Recent social studies on space have focused on changing the social relations that activate in space. In general, these studies have been based on the concept of social space on which is grounded the power-relation analysis such as power, oppression, resource allocation, and so on. Social work practice has traditionally recognized the importance of the environment surrounding human beings. Nonetheless, social work practice has tended to comprehend space in a neutral and abstract way because it has insufficiently considered modern spatial theories. For this reason, this study focusing on Lefebvre's social space theory reviewed the contemporary discourses on space in the area of social work practice. Following the review, this study attempted to establish the concept of "Space-based Social Work Practice". Specifically, this study analyzed the actual cases in social work field and explored the applicability of "SSWP". According to the results, this study delivered the implications of Space-based Social Work Practice as an alternative method and suggested the practical direction of SSWP.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.539-543
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• 2008

The Directional sign system in Korean high speed railway stations has a lot of problems. For an example, It lacks of consistency in the shape or allocation. Also, the signs do not match with the actual directions sometimes. Last but not least, the view is blocked by the other signs such as advertisement or other barriers. We suggested the methods to standardize the sign systems that include visibility, accuracy, consistency, and simplicity. First, we categorized signs into directional signs, locational signs, and infomational signs. Then, we examined the actual high speed railway stations in Korea to learn the real situation. Finally, we suggested the methods to standardize the sign systems considering the factors that are visibility, accuracy, consistency, and simplicity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.307-315
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• 2008

The aim of this study is to develop travel time estimation model by using Self-Organized Neural network(in brief, SON) algorithm. Travel time data based on vehicles equipped with GPS and number-plate matching collected from National road number 3 (between Jangji-IC and Gonjiam-IC), which is pilot section of National Highway Traffic Management System were employed. We found that the accuracies of travel time are related to location of detector, the length of road section and land-use properties. In this paper, we try to develop travel time estimation using SON to remedy defects of existing neural network method, which could not additional learning and efficient structure modification. Furthermore, we knew that the estimation accuracy of travel time is superior to optimum located detectors than based on existing located detectors. We can expect the results of this study will make use of location allocation of detectors in highway.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.57-64
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• 2023

This study analyzed the perceptions of elementary and secondary school teachers regarding the importance of SW/AI education in fostering students' fundamental knowledge and the necessity of integrating SW/AI into education. A total of 830 elementary and secondary school teachers were selected as study subjects using the judgment sampling method. The analysis of survey data revealed that elementary and secondary teachers exhibited a strong awareness of the importance and necessity of SW/AI education, irrespective of school characteristics, region, educational experience, or prior involvement in SW and AI education. Nevertheless, the primary reasons for not implementing SW/AI education were identified as excessive workload and a lack of pedagogical expertise. An analysis of opinions on the essential conditions for implementing SW/AI education revealed that workload reduction, budget support, teacher training to enhance teacher competency, content distribution, expansion of subject-linked courses, and dedicated instructional time allocation were the major influencing factors. These findings indicate a significant demand for comprehensive instructional support and teacher capacity-building programs.