• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.216-222
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• 2021

Recently, various robots are being used for the purpose of structural inspection or safety diagnosis, and their needs are also rising rapidly. Among the structural inspection using robots, a lot of researches has recently been conducted on inspection of various facilities and structures using an unmanned aerial vehicle (UAV). However, since GNSS (Global Navigation Satellite System) signals cannot be received in an environment near or below structures, the operation of UAVs has been done manually. For a stable autonomous flight without GNSS signals, additional technologies are required. This paper proposes the autonomous flight system for structural inspection consisting of simultaneous localization and mapping (SLAM), path planning, and controls. The experiments were conducted on an actual large bridge to verify the feasibility of the system, and especially the performance of the proposed SLAM algorithm was compared through comparative analysis with the state-of-the-art algorithms.

• Journal of Industrial Convergence
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• v.13 no.1
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• pp.75-79
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• 2015

This paper investigates two important relationships relating to firm behaviour and performance using econometric methods. First, the relationship between product market competition and innovation is examined, and then the association between innovation and productivity is separately investigated. Data from the Australian Bureau of Statistics' Business Longitudinal Database are used in the analysis. For every measure of competition considered except one, the results of the modelling are consistent with an anti-Schumpeterian relationship between competition and innovation - that is, firms appear more likely to innovate if they face stronger competition. The results examining the relationship between innovation and productivity, although weaker than those between competition and innovation, suggest that innovation is associated with better productivity outcomes.

• Steel and Composite Structures
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• v.33 no.2
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• pp.277-298
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• 2019

Concrete filled steel tubular (CFST) column joints with composite beams have been widely used as lateral loading resisting elements in civil infrastructure. To better utilize these innovative joints for the application of structural seismic design and analysis, it is of great importance to investigate the dynamic behavior of the joint under cyclic loading. With this aim in mind, a novel phenomenal model has been put forward in this paper, in which a Bouc-Wen hysteresis component is employed to portray the strength and stiffness deterioration phenomenon caused by increment of loading cycle. Then, a modified chicken swarm optimization algorithm was used to estimate the optimal model parameters via solving a global minimum optimization problem. Finally, the experimental data tested from five specimens subjected to cyclic loadings were used to validate the performance of the proposed model. The results effectively demonstrate that the proposed model is an easy and more realistic tool that can be used for the pre-design of CFST column joints with reduced beam section (RBS) composite beams.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.239-244
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• 2022

R-Mode is terrestrial based Global Navigation Satellite System (GNSS) backup radio navigation technology which used existing maritime information service infrastructure. It has advantages on reduce the cost and reutilize the frequency resource. In this paper, we propose a method to develop a medium-frequency (MF) band R-Mode transmitting station by utilizing the currently operating Differential GNSS (DGNSS) reference station infrastructure. To this end, the considerations for co-operating the DGNSS reference station and the MF R-Mode transmitting station are analyzed. In this process, we also analyze what is necessary to configure the communication system as a navigation system for range measurement. Based on the analysis result, MF R-Mode transmitting station system is designed and architecture is proposed. The developed system is installed in the field, and the performance evaluation results is presented.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.97-108
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• 1996

Optimal design of fault-tolerant, spatial type redundant manipulators is treated in this paper. Design objective is to guarantte three degree-of -freedom translational motions in the task space, upon failure of one arbitrary joint of 4 degree-of-freedom manipulators. Noticing the nonfault-tolerant characteristics of current, wrist-type industrial manipulators, five different fault-tolerant spatial-type manipulators which have 4 degree-of-freedom structures with one joint redundancy are suggested. Faault-tolerant character-sitics of two redundant manipulators anr investigated based on the analysis of the self-motion and the null-space elements. Finally, in order to maximize the fault-tolerant capability, optimal design is performed for a spatial-type manipulator with respect to the global isotropic index, and the performance enhancement of the optimized case is shown by simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.198-200
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• 2022

With the expansion of the global supply chain, the efficiency of maritime logistics is considered a crucial factor for countries' trade and competitiveness. Nevertheless, prior research has not thoroughly evaluated the efficiency of maritime logistics, including countries' ports and shipping capacities. Accordingly, this study examines integrated maritime logistics efficiency at the national level using DEA-CCR, BCC, and super-efficiency DEA. Furthermore, this study identifies a difference between the selected countries' maritime logistics efficiency and LPI (Logistics Performance Index) through Spearman's correlation test as an ad-hoc analysis. From this, Asian countries showed higher efficiency and European countries showed higher LPI scores. These results might be derived from this difference in port-city development patterns. Additionally, the main cause of inefficiency in Europe and Japan might be attributed to high fleet capacity of control. Consequently, this study can provide valuable implications for coastal countries to set more efficient directions for maritime logistics investment and policy.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.319-320
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• 2023

In a reinforced concrete structure, coupler construction is easier to install than jointing or welding reinforcing bars, so it is possible to work by one person. When constructing a reinforcing bar coupler, the coupler construction method must be different for each member that receives a large tensile force or a member that receives a small tensile strength. Various coupler products are used in the global construction market, and the quality, performance, and cost of reinforcing bar joints vary from product to product. This study compares and analyzes the quality and cost of representative rebar couplers according to the requirements using the quality house of QFD-HOQ. The case study presents a quality and cost improvements strategy through QFD-HOQ analysis of rebar couplers.

• ETRI Journal
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• v.46 no.3
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• pp.513-525
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• 2024

Deep neural networks trained on labeled medical data face major challenges owing to the economic costs of data acquisition through expensive medical imaging devices, expert labor for data annotation, and large datasets to achieve optimal model performance. The heterogeneity of diseases, such as Alzheimer's disease, further complicates deep learning because the test cases may substantially differ from the training data, possibly increasing the rate of false positives. We propose a reconstruction-based self-supervised anomaly detection model to overcome these challenges. It has a dual-subnetwork encoder that enhances feature encoding augmented by skip connections to the decoder for improving the gradient flow. The novel encoder captures local and global features to improve image reconstruction. In addition, we introduce an entropy-based image conversion method. Extensive evaluations show that the proposed model outperforms benchmark models in anomaly detection and classification using an encoder. The supervised and unsupervised models show improved performances when trained with data preprocessed using the proposed image conversion method.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.35-44
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• 2024

This investigation primarily focuses on the generational characteristics of satellites utilized in the existing Global Navigation Satellite System (GNSS) and Regional Navigation Satellite System (RNSS), with a central emphasis on comparing the operational status of the latest generation satellites. Variations among satellite generations in physical attributes, energy consumption, and timekeeping are observed, enabling an exploration of the developmental trends over successive generations. Through a comparative analysis of the latest generation satellites, particularly in terms of performance, this study aims to furnish essential insights into the satellites employed within each system. Consequently, it will contribute to a foundational understanding of the past, present, and future GNSS satellites.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.5
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• pp.1081-1088
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• 2024

While metaheuristics have profoundly impacted various fields, domestic financial portfolio optimization research, particularly in asset allocation, remains underdeveloped. This study investigates metaheuristic algorithms for investment strategy optimization. Results reveal that metaheuristic-optimized portfolios outperform the Dow Jones Index in Sharpe ratios, highlighting their potential to significantly enhance risk-adjusted returns. A comparative analysis of Ant Colony Optimization (ACO) and Cuckoo Search Algorithm (CSA) shows CSA's slight superiority in risk-adjusted performance. This advantage is attributed to CSA's maintained randomness and Lévy flight model, which effectively balance local and global search, whereas ACO may converge prematurely due to path reinforcement. These findings underscore metaheuristics' capacity to maximize expected returns at given risk levels, offering flexible, robust solutions for investment strategy optimization.