• Particle and aerosol research
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• v.18 no.4
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• pp.109-127
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• 2022

Recently, low-cost particulate matter (PM) sensors have been widely used in monitoring mass concentration. Maintaining the accuracy of the sensors is important and requires rigorous performance evaluation and calibration. In this study, two commercial low-cost PM sensors(LCS), Plantower PMS3003 and Plantower PMS7003, were evaluated in the laboratory and field with a reference-grade PM monitor (GRIMM 11-D). Laboratory evaluation was conducted with single/mixed particles of PSL (Poly Styrene Latex) in an acrylic chamber at 20℃ and relative humidity of 20%. Field evaluation was conducted inside a building of Yonsei University (Shinchon) from February 12 to March 31, 2022. In both evaluations, LCS measured values became different from reference measured values when the relative humidity was high or the outdoor air PM10/PM2.5 ratio was high. Based on the field evaluation, the LCS measured values were corrected through four different regression analysis models. As a result, the multivariate polynomial regression analysis model showed highest matching with the reference PM monitor (PM2.5 >0.9, PM10 >0.85). In this model, the PM10/PM2.5 ratio and relative humidity were chosen as independent variables.

• Korean Journal of Materials Research
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• v.32 no.10
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• pp.429-434
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• 2022

There is ongoing research to develop lithium ion batteries as sustainable energy sources. Because of safety problems, solid state batteries, where electrolytes are replaced with solids, are attracting attention. Sulfide electrolytes, with a high ion conductivity of 10^-3 S/cm or more, have the highest potential performance, but the price of the main materials is high. This study investigated lithium hydride materials, which offer economic advantages and low density. To analyze the change in ion conductivity in polymer electrolyte composites, PVDF, a representative polymer substance was used at a certain mass ratio. XRD, SEM, and BET were performed for metallurgical analyses of the materials, and ion conductivity was calculated through the EIS method. In addition, thermal conductivity was measured to analyze thermal stability, which is a major parameter of lithium ion batteries. As a result, the ion conductivity of LiH was found to be 10^-6 S/cm, and the ion conductivity further decreased as the PVDF ratio increased when the composite was formed.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.2
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• pp.255-269
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• 2023

Compared to operational wastes, nuclear power plant (NPP) decommissioning wastes are generated in larger quantities within a short time and include diverse types with a wider range of radiation characteristics. Currently used 200 L drums and IP-2 type transport containers are inefficient and restrictive in packaging and transporting decommissioning wastes. Therefore, new packaging and transport containers with greater size, loading weight, and shielding performance have been developed. When transporting radioactive materials, radiological safety should be assessed by reflecting parameters such as the type and quantity of the package, transport route, and transport environment. Thus far, safety evaluations of radioactive waste transport have mainly targeted operational wastes, that have less radioactivity and a smaller amount per transport than decommissioning wastes. Therefore, in this study, the possible radiation effects during the transport from NPP to disposal facilities were evaluated to reflect the characteristics of the newly developed containers and decommissioning wastes. According to the evaluation results, the exposure dose to transport workers, handling workers, and the public was lower than the domestic regulatory limit. In addition, all exposure dose results were confirmed, through sensitivity analysis, to satisfy the evaluation criteria even under circumstances when radioactive materials were released 100% from the container.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.97-119
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• 2023

The number of industrial Internet of Things (IoT) users is increasing rapidly. Lightweight block ciphers have started to be used to protect the privacy of users. Hardware-oriented security design should fully consider the use of fewer hardware devices when the function is fully realized. Thus, this paper designs a lightweight block cipher IIoTBC for industrial IoT security. IIoTBC system structure is variable and flexibly adapts to nodes with different security requirements. This paper proposes a 4×4 S-box that achieves a good balance between area overhead and cryptographic properties. In addition, this paper proposes a preprocessing method for 4×4 S-box logic gate expressions, which makes it easier to obtain better area, running time, and power data in ASIC implementation. Applying it to 14 classic lightweight block cipher S-boxes, the results show that is feasible. A series of performance tests and security evaluations were performed on the IIoTBC. As shown by experiments and data comparisons, IIoTBC is compact and secure in industrial IoT sensor nodes. Finally, IIoTBC has been implemented on a temperature state acquisition platform to simulate encrypted transmission of temperature in an industrial environment.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.313-323
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• 2023

The wearable robot system is designed to assist human skeletal and muscular systems for enhancing user's abilities in various fields, including medical, industrial, and military. The military has an expanding need for wearable robots with the integration of surveillance/control systems and advanced equipment in unstructured battlefield environments. However, there is a lack of research on the design and mechanism of wearable robots, especially for power assist systems. This study proposes a lightweight wearable robot system that provides comfortable wear and muscle support effects in various movements for soldiers performing high-strength and endurance missions. The Power assist mechanism is described and verified, and the tasks that require power assist are analyzed. This study explain the system including its driving mechanism, control system, and mechanical design. Finally, the performance of the robot is verified through experiments and evaluations, demonstrating its effectiveness in muscle support.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.285-301
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• 2023

During the construction of E75 highway through Grdelica gorge in Serbia, a major failure occurred in the zone of reinforced rock slope. Excavation was performed in highly anisotropic Paleozoic schist rock formation. The reinforcement consisted of the two rows of micropile wall with pre-stressed anchors. Forces in anchors were monitored with load cells while benchmarks were installed for superficial displacement measurements. The aim of the study is to investigate possible causes of instability considering different probability distributions of the strength of discontinuities and anchor bond strength by applying different optimization techniques for finding the critical failure surface. Even though the deterministic safety factor value is close to unity, the probability of failure is governed by variability of shear strength of anisotropic planes and optimization method used for locating the critical sliding surface. The Cuckoo search technique produces higher failure probabilities compared to the others. Depending on the assigned statistical distribution of input parameters, various performance functions of the factor of safety are obtained. The probability of failure is insensitive to the variation of bond strength. Different sampling techniques should yield similar results considering that the sufficient number of safety factor evaluations is chosen to achieve converged solution.

• The Journal of Information Systems
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• v.32 no.3
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• pp.133-150
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• 2023

Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.1-17
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• 2023

This study aimed to examine the characteristics of ESG activities among major domestic companies in the carbon-emitting industry compared to industries with lower emissions, as ESG has emerged as a significant agenda across various industries. Departing from the traditional focus on the "why" of ESG, which primarily centers around financial performance, this research sought to uncover the "how" of effective ESG management in domestic companies. The analysis involved studying the sustainability reports of 124 companies using the Global Reporting Initiative (GRI) indicators and comparing high-emitting and non-high-emitting industries. The findings revealed industry-specific patterns in companies' ESG activities, providing valuable insights for future ESG evaluations and assessments. Furthermore, the advancement of rating analysis methods holds implications for ESG rating agencies and financial authorities in terms of policy-making.

• Fourth Industrial Review
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• v.4 no.1
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• pp.11-18
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• 2024

Purpose: The purpose of this study is to develop a geography class teaching and learning guide that enables learners to realistically explore the characteristics of the world's climate and geographical environment using digital tools. Research design, data and methodology: We review previous research on classes using goal-based scenario learning models, gamification, and digital tools, and explore tools that can be applied to world geography classes. Based on the exploration results, a goal-based scenario learning module is designed and a strategy for promoting educational gamification is established based on the ADDIE instructional design model. Results: The study comprises four sessions. Sessions 1-3 involve performance evaluations using a goal-based scenario learning module. Learners create game characters reflecting geographical characteristics, present results, and proceed with 3D modeling. In Session 4, a gamification class using Google Sites on the CoSpaces metaverse platform will be conducted. Conclusions: The study introduces a goal-based scenario learning model and a gamification class using digital tools to empower learners in exploring geographical diversity and its impact on lifestyles. Utilizing an accessible online platform, the study provides practical measures for integrating digital tools into geography education, addressing the current importance of digital technology in teaching.