• International conference on construction engineering and project management
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• 2020.12a
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• Steel and Composite Structures
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• v.48 no.1
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• pp.1-17
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• 2023

The main goal of this paper is to study vibration of damaged core laminated sectorial plates with Functionally graded (FG) face sheets based on three-dimensional theory of elasticity. The structures are made of a damaged isotropic core and two external face sheets. These skins are strengthened at the nanoscale level by randomly oriented Carbon nanotubes (CNTs) and are reinforced at the microscale stage by oriented straight fibers. These reinforcing phases are included in a polymer matrix and a three-phase approach based on the Eshelby-Mori-Tanaka scheme and on the Halpin-Tsai approach, which is developed to compute the overall mechanical properties of the composite material. Three complicated equations of motion for the sectorial plates under consideration are semi-analytically solved by using 2-D differential quadrature method. Using the 2-D differential quadrature method in the r- and z-directions, allows one to deal with sandwich annular sector plate with arbitrary thickness distribution of material properties and also to implement the effects of different boundary conditions of the structure efficiently and in an exact manner. The fast rate of convergence and accuracy of the method are investigated through the different solved examples. The sandwich annular sector plate is assumed to be simply supported in the radial edges while any arbitrary boundary conditions are applied to the other two circular edges including simply supported, clamped and free. Several parametric analyses are carried out to investigate the mechanical behavior of these multi-layered structures depending on the damage features, through-the-thickness distribution and boundary conditions.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.26 no.2
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• pp.144-148
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• 2022

Backgrounds/Aims: Splenectomy in patients with non-Hodgkin lymphoma (NHL) is performed to relieve abdominal symptoms, treat hypersplenism or confirm diagnosis. Excision of a very large spleen is technically challenging and data on outcomes of surgery in patients with NHL are scanty. The aim of study was to evaluate the impact of spleen size on the surgical outcome of splenectomy in patients with NHL. Methods: Patients with NHL who underwent splenectomy, between 2006 and 2017, were included and divided into two groups: group 1, spleen ≤ 20 cm; group 2, spleen > 20 cm. Surgical approach, operative time, postoperative morbidity, mortality, hospital stay and re-admission rates were retrospectively compared between groups. Non-parametric data were evaluated with the Mann-Whitney U test. Differences in frequencies were analyzed with Fisher's exact test. Results: Sixteen patients were included (group 1, 6; group 2, 10). Laparoscopy was successful in three patients of group 1, none of group 2 (p = 0.035), the intraoperative time did not differ significantly between groups. One patient in each group developed postoperative complications. The patient in group 1 died of pneumonia. Median length of stay was 8 days (range, 3-16 days) for group 1, 5.5 days (range, 3-10 days) for group 2, showing no significant difference between the two groups. No patient was readmitted to hospital. Conclusions: Spleen size does not affect the outcome of splenectomy in patients with NHL. If a mini-invasive approach is to be chosen, laparoscopy may not be feasible when the spleen size is > 20 cm.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.4
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• pp.231-239
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• 2007

This paper presents the trade-off relationship between area and performance in the hardware design space exploration for the Korean national standard 128-bit block cipher algorithm SEED. In this paper, we compare the following four hardware design types of SEED algorithm : (1) Design 1 that is 16 round fully pipelining approach, (2) Design 2 that is a one round looping approach, (3) Design 3 that is a G function sharing and looping approach, and (4) Design 4 that is one round with internal 3 stage pipelining approach. The Design 1, Design 2, and Design 3 are the existing design approaches while the Design 4 is the newly proposed design in this paper. Our new design employs the pipeline between three G-functions and adders consisting of a F function, which results in the less area requirement than Design 2 and achieves the higher performance than Design 2 and Design 3 due to pipelining and module sharing techniques. We design and implement all the comparing four approaches with real hardware targeting FPGA for the purpose of exact performance and area analysis. The experimental results show that Design 4 has the highest performance except Design 1 which pursues very aggressive parallelism at the expanse of area. Our proposed design (Design 4) shows the best throughput/area ratio among all the alternatives by 2.8 times. Therefore, our new design for SEED is the most efficient design comparing with the existing designs.

• Journal of Oriental Neuropsychiatry
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• v.34 no.2
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• pp.71-82
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• 2023

Objectives: The existing reductionist approach has not reached complete understanding of the cause of schizophrenia. The objective of this study was to investigate yin-yang and five-element characteristics reflected on four time pillars of birth of patients with schizophrenia through comparison with the general population in the perspective of consilience-based holistic approach. Methods: This study was conducted using a random sequential recruitment method for the general population and individuals with schizophrenia aged 18 to 64 based on the exact date and time of birth using structured questionnaires. Relative positional relations of yin-yang and five-element with day master were primarily examined. In addition, the strength of day master with a score range of 0~100 points was assessed through operational score allocation. Results: Of 591 participants, 576 (346: general population, 230: individuals with schizophrenia) were analyzed. Between-group analyses showed no significant difference in the distribution of types of day master (χ²=10.41, df=9, p=0.318). However, significant between-group differences were shown in the distribution of the strength of day master (t=2.14, p=0.032) and frequency of restraining month branch (χ²=5.23, df=1, p=0.022). In logistic regression analysis, 10-point increase on the strength of day master decreased the probability of onset of schizophrenia over the age of 30 by 29.6% (p=0.002; 95% confidence interval, 0.566~0.876). Conclusions: Findings in this study suggest that four time pillars of birth might be associated with schizophrenia through yin-yang and five-element theory and synchronicity principle, implicating the plausibility of consilience-based holistic approach in the determination of risk factors or cause of schizophrenia.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.287-295
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• 2022

As low altitude long-range artillery threat has been strengthened, the development of anti-artillery interception system to protect assets against its attacks will be kicked off. We view the defense of long-range artillery attacks as a typical dynamic weapon target assignment (DWTA) problem. DWTA is a sequential decision process in which decision making under future uncertain attacks affects the subsequent decision processes and its results. These are typical characteristics of Markov decision process (MDP) model. We formulate the problem as a MDP model to examine the assignment policy for the defender. The proximity of the capital of South Korea to North Korea border limits the computation time for its solution to a few second. Within the allowed time interval, it is impossible to compute the exact optimal solution. We apply approximate dynamic programming (ADP) approach to check if ADP approach solve the MDP model within processing time limit. We employ Shoot-Shoot-Look policy as a baseline strategy and compare it with ADP approach for three scenarios. Simulation results show that ADP approach provide better solution than the baseline strategy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.4
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• pp.375-380
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• 2009

Bit error rate(BER) performance of each bit for hierarchical M-ary phase shift keying(H-MPSK) modulation scheme is changed according to the phase parameters. Thus, a method to find the phase parameters appropriate to the requests of the system is needed. In this paper, we propose a method to obtain the phase parameters from an approximate approach of BER for H-MPSK and verify a validity of the proposed method through the previously provided expression for analyzing an exact error probability of H-MPSK.

• Structural Engineering and Mechanics
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• v.42 no.2
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• pp.175-189
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• 2012

This paper presents an algorithm for structural reliability with the response surface method. For this aim, an approach with three stages is proposed named as improved response surface method. In the algorithm, firstly, a quadratic approximate function is formed and design point is determined with First Order Reliability Method. Secondly, a point close to the exact limit state function is searched using the design point. Lastly, vector projected method is used to generate the sample points and Second Order Reliability Method is performed to obtain reliability index and probability of failure. Five numerical examples are selected to illustrate the proposed algorithm. The limit state functions of three examples (cantilever beam, highly nonlinear limit state function and dynamic response of an oscillator) are defined explicitly and the others (frame and truss structures) are defined implicitly. ANSYS finite element program is utilized to obtain the response of the structures which are needed in the reliability analysis of implicit limit state functions. The results (reliability index, probability of failure and limit state function evaluations) obtained from the improved response surface are compared with those of Monte Carlo Simulation, First Order Reliability Method, Second Order Reliability Method and Classical Response Surface Method. According to the results, proposed algorithm gives better results for both reliability index and limit state function evaluations.

• Journal of the Korean Ceramic Society
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• v.53 no.3
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• pp.317-324
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• 2016

Continued miniaturization and increasingly exact requirements for thin film deposition in the semiconductor industry is driving the search for new effective, efficient, selective precursors and processes. The requirements of defect-free, conformal films, and precise thickness control have focused attention on atomic layer deposition (ALD). ALD precursors so far have been developed through a trial-and-error experimental approach, leveraging the expertise and tribal knowledge of individual research groups. Precursors can show significant variation in performance, depending on specific choice of co-reactant, deposition stage, and processing conditions. The chemical design space for reactive thin film precursors is enormous and there is urgent need for the development of computational approaches to help identify new ligand-metal architectures and functional co-reactants that deliver the required surface activity for next-generation thin-film deposition processes. In this paper we discuss quantum mechanical simulation (e.g. density functional theory, DFT) applied to ALD precursor reactivity and state-of-the-art automated screening approaches to assist experimental efforts leading toward optimized precursors for next-generation ALD processes.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.