• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3438-3457
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• 2022

As location-based services (LBS) are widely used in vehicular ad-hoc networks (VANETs), location privacy has become an utmost concern. Spatial cloaking is a popular location privacy protection approach, which uses a cloaking area containing k-1 collaborative vehicles (CVs) to replace the real location of the requested vehicle (RV). However, all CVs are assumed as honest in k-anonymity, and thus giving opportunities for dishonest CVs to submit false location information during the cloaking area construction. Attackers could exploit dishonest CVs' false location information to speculate the real location of RV. To suppress this threat, an edge-assisted Trusted Collaborative Anonymity construction scheme called TCA is proposed with trust mechanism. From the design idea of trusted observations within variable radius r, the trust value is not only utilized to select honest CVs to construct a cloaking area by restricting r's search range but also used to verify false location information from dishonest CVs. In order to obtain the variable radius r of searching CVs, a multiple linear regression model is established based on the privacy level and service quality of RV. By using the above approaches, the trust relationship among vehicles can be predicted, and the most suitable CVs can be selected according to RV's preference, so as to construct the trusted cloaking area. Moreover, to deal with the massive trust value calculation brought by large quantities of LBS requests, edge computing is employed during the trust evaluation. The performance analysis indicates that the malicious response of TCA is only 22% of the collaborative anonymity construction scheme without trust mechanism, and the location privacy leakage is about 32% of the traditional Enhanced Location Privacy Preserving (ELPP) scheme.

• Safety and Health at Work
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• v.13 no.3
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• pp.308-314
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• 2022

Background: Occupational cancer is a global health issue. The Korean CARcinogen EXposure (K-CAREX), a database of CARcinogen EXposure, was developed for the Korean labor force to estimate the number of workers exposed to carcinogens by industry. The present study aimed to estimate the intensity of exposure to carcinogens by industry, in order to supply complementary information about CARcinogen EXposure intensity to the K-CAREX. Methods: We used nationwide workplace monitoring data from 2014 to 2016 and selected target carcinogens based on the K-CAREX list. We computed the 95th percentile levels of measurements for each industry by carcinogens. Based on the 95th percentile level relative to the occupational exposure limit, we classified the CARcinogen EXposure intensity into five exposure ratings (1-5) for each industry. Results: The exposure ratings were estimated for 21 carcinogenic agents in each of the 228 minor industry groups. For example, 3,058 samples were measured for benzene in the manufacturing industry of basic chemicals. This industry was assigned a benzene exposure rating of 3. Conclusions: We evaluated the CARcinogen EXposure ratings across industries in Korean workers. The results will provide information on the exposure intensity to carcinogens for integration into the K-CAREX. Furthermore, it will aid in prioritizing control efforts and identifying industries of concern.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.214-222
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• 2022

In these proceedings, we will address the problem of air pollution on the premises of the Cement factory SHARRCEM L.L.C. in Hani Elezit in the Republic of Kosovo respectively around the clinker cooler, rotary kiln, and raw material mill. By air pollution, we mean the introduction of chemicals, particles, or other harmful materials into the atmosphere which in one way or another causing damage to the development of plants and organisms. Air pollution occurs when certain substances are released into the air, which depending on the quantitative level, can be harmful to human health, animals, and the environment in general. The analysis of air shows the influence of the extractive and processing industry on the chemical composition of air. Parameters analyzed though under control such as the case of carbon dioxide, due to the increasing production capacity of cement, the production of hundreds of thousands of cubic meters of CO₂ gas made CO₂ production a concern. With the purchase of the latest technology by the SHARCEM Factory in Hani Elezit, the amount of air pollution has been reduced and the allowed parameters of environmental pollution have been kept under control. Air pollutants are introduced into the atmosphere from various sources which change the composition of the atmosphere and affect the biotic environment.The concentration of air pollutants depends not only on the quantities that are emitted from the sources of air pollution but also on the ability of the atmosphere to absorb or disperse these emissions. Sources of air pollutants include vehicles, industry, indoor sources, and natural resources. There are some natural pollutants, such as natural fog, particles from volcanic eruptions, pollen grains, bacteria, and so on.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.1-11
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• 2022

Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.135-140
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• 2022

Scientific and technological progress is also fundamental to the evolving merchant shipping industry, both in terms of the size and speed of modern ships and in the level of their technical capabilities. While the freight performance of ships is growing, the number of crew on board is steadily decreasing, as more work processes are being automated through the implementation of information technologies, including ship management systems. Although there have been repeated appeals from international maritime organizations to focus on building effective maritime security defenses against cyber attacks, the problems have remained unresolved. Owners of shipping companies do not disclose information about cyberattack attempts or incidents against them due to fear of commercial losses or consequences, such as loss of image, customer and insurance claims, and investigations by independent international organizations and government agencies. Issues of cybersecurity of control systems in the world today have gained importance, due to the fact that existing threats concern not only the security of technical means and devices, but also issues of environmental safety and safety of life at sea. The article examines the implementation of cyber risk management in the shipping industry, providing recommendations for the safe ship operation and its systems in order to improve vulnerability to external threats related to cyberattacks, and to ensure the safety and security of such a technical object as a seagoing ship.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.179-188
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• 2010

The concern of Software Product Line(SPL) engineering is spreading widely because the program or product developers are able to satisfy the customer's demands quickly and give a way to handle maintenance efficiently. SPL is a reuse paradigm that reuse common parts and adopts variable parts optionally to form a differentiated product by analyzing domains. Purposes of this paper are to design an architecture which has a dynamic reconfiguration function and to develop basic components which are the basic unit of reconfiguration to raise the reuse level of the guided weapon system using the SPL. Initially we design an architecture and define basic components for developing a dynamic reconfigurable components based on SPL. Then we develop the composer for physical components and behavior components referenced by behavior models of OneSAF.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1226-1236
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• 2022

Because students majoring in construction-related fields must develop a broad repository of knowledge and skills, effective transferal of these is the primary focus of most academic programs. While inculcation of this body of knowledge is certainly critical, actual construction projects are complicated ventures that involve levels of risk and uncertainty, such as resistant neighboring communities, unforeseen weather conditions, escalating material costs, labor shortages and strikes, accidents on jobsites, challenges with emerging forms of technology, etc. Learning how to develop a level of discernment about potential ways to handle such uncertainty often takes years of costly trial-and-error in the proverbial "school of hard knocks." There is therefore a need to proactively expedite the development of a sharpened intuition when making decisions. The AGC Education and Research Foundation case study committee was formed to address this need. Since its inception in 2011, 14 freely downloadable case studies have thus far been jointly developed by an academics and industry practitioners to help educators elicit varied responses from students about potential ways to respond when facing an actual project dilemma. AGC case studies are typically designed to focus on a particular concern and topics have thus far included: ethics, site logistics planning, financial management, prefabrication and modularization, safety, lean practices, preconstruction planning, subcontractor management, collaborative teamwork, sustainable construction, mobile technology, and building information modeling (BIM). This session will include an overview of the history and intent of the AGC case study program, as well as lively interactive demonstrations and discussions on how case studies can be used both by educators within a typical academic setting, as well as by industry practitioners seeking a novel tool for their in-house training programs.

• Journal of the Korean Geotechnical Society
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• v.23 no.10
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• pp.109-119
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• 2007

As the number of CFRD constructions increases, the necessity of an accurate assessment on its behavior also has been increasing. The performance of concrete faced rockfill dam (CFRD) under different water levels is a great concern of dam engineers and designers in the world. However, domestic research on CFRD design and construction has not been performed sufficiently. This study deals with three centrifuge model tests, mainly investigates quantitatively the deformation of the concrete faced slabs and settlements on the crest with different face slab stiffness. The prototype of a centrifugal model dam is half size of domestic CFRD dam. Detailed material preparation, model design, model set-up, model instrumentation and testing procedures are presented. In order to simulate the prototype concrete faced slab, three kinds of thin fiberglass plates with different thickness were adopted in three model tests. Finally, the centrifuge test results were compared with field measurements of domestic dams, which showed that the centrifuge tests were performed successfully.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.318-325
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• 2023

The detection of antibiotics in treated wastewater is a global concern as it enters water bodies and causes the development of antibiotic resistance genes in humans and marine life. The study specifically aims to explore the potential of ferrate (VI) in eliminating tetracycline (TCL). The degradation of TCL is optimized with parametric studies, viz., the effect of pH and concentration, which provide insights into TCL elimination. The increase in pH (from 7.0 to 10.0) favors the percentage removal of TCL; however, the increase in TCL concentrations from 0.02 to 0.3 mmol/L caused a decrease in percentage TCL removal from 97.4 to 29.1%, respectively, at pH 10.0. The time-dependent elimination of TCL using ferrate (VI) followed pseudosecond-order rate kinetics, and an apparent rate constant (kapp) was found at 1978.8 L² /mol² /min. Coexisting ions, i.e., NaNO₃, Na₂HPO₄, NaCl, and oxalic acid, negligibly affect the oxidation of TCL by ferrate (VI). However, EDTA and glycine significantly inhibited the elimination of TCL using ferrate (VI). The mineralization of TCL using ferrate (VI) was favored at higher pH, and it increased from 18.57 to 32.52% when the solution pH increased from pH 7.0 to 10.0. Additionally, the real water samples containing a relatively high level of inorganic carbon spiked with TCL revealed that ferrate (VI) performance in the removal of TCL was unaffected, which further inferred the potential of ferrate (VI) in real implications.