Recently, interest in and demand for sensors that recognize physical activity and their products are increasing. In particular, the development of wearable materials that are flexible, stretchable, and able to detect the user's biological signals is drawing attention. In this study, an experiment was conducted to improve the dip-coating efficiency of a single-walled carbon nanotube dispersion solution after fine holes were made in a hydrophobic material with a micro needle. In this study, dip-coating was performed with a material that was not penetrated, and comparative analysis was performed. The electrical conductivity of the sensor was measured when the sensor was stretched using a strain universal testing machine (Dacell Co. Ltd., Seoul, Korea) and a multimeter (Keysight Technologies, Santa Rosa, CA, USA) was used to measure resistance. It was found that the electrical conductivity of a sensor that was subjected to needling was at least 16 times better than that of a sensor that was not. In addition, the gauge factor was excellent, relative to the initial resistance of the sensor, so good performance as a sensor could be confirmed. Here, the dip-coating efficiency of hydrophobic materials, which have superior physical properties to hydrophilic materials but are not suitable due to their high surface tension, can be adopted to more effectively detect body movements and manufacture sensors with excellent durability and usability.
The creep behavior of a rapidly solidified and consolidated Al-9.45wt%Fe-4.45wt%Cr alloy were investigated in the stress range 40 to 115 MPa and temperature range 300(0.53Tm) to 441$^{\circ}C$(0.66Tm). It is of use to available aerospace and automobile industries for the improved performance of materials used at high temperature. Because Al alloys with improved creep resistance offer the potential for lower weight and reduced costs in aerospace and automobile components (e.g., structural members and engine parts) through the replacement of heavier and more costly materials, the safety in use at high temperature is good. The alloy is characterized by high stress exponents and activation energies for creep, which are greatly dependent on the stress and temperature. Because the creep stress is seen to cause a strongly significant enhancement of coarsening, the coarsening rate of the dispersed particles in all crept specimens is faster than that in isothermally annealed specimens. Dislocations connecting dispersoids are observed more cofrequently in crept specimens with higher stress and lower temperature. The creep strain rates in the power law creep regime were found to be predicted much better by the Shorty and Rosler/Arzt equation with the inclusion of a threshold stress and dislocation detachment mechanism. The dispersoids in this alloy were acting a source of void nucleation that finally leaded to ductile fracture within the grain so called intergranular. Each void was initiated, grown and failed at the dispersoids in the aluminium matrix. Grain boundary accommodation of the slip produced, which result in initiation of the void and then final transgranular fracture. Therefore, it was confirmed that these dispersoids played an important role in the fracture mechanism by the formation of $Al_{13}Fe_4$, $Al_{13}Cr_2$ and $Al_2O_3$.
Korean Journal of Construction Engineering and Management
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v.24
no.6
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pp.63-65
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2023
BIM and AR technologies have been assessed as a means of enhancing productivity within the construction industry, through the provision of effortless access to critical data on site, achieved via the projection of 3D models and associated information onto actual structures. However, most of the previous researches for applying AR technology in construction quality management has been performed for construction projects in general, resulting in only overall on-site management solutions. Also, a few previous researches for the application of AR in the quality management of specific elements like reinforcements focused only on simple projection, so conducting specific quality inspection was impossible. Hence, this study aimed to develop a practically applicable BIM-based AR quality management system targeted for reinforcements. For the development of this system, the reinforcement inspection items on the quality checklist used at railway construction sites were analyzed, and four types of AR functions that can effectively address these items were developed and installed. The validation result of the system for the actual railway bridge showed a degradation of projection stability. This problem was solved through model simplification and enhancement of the AR device's hardware performance, and then the normal operation of the system was validated. Subsequently, the final developed reinforcement quality inspection system was evaluated for practical applicability by on-site quality experts, and the efficiency of inspection would significantly increase when using the AR system compared to the current inspection method for reinforcements.
Journal of the Microelectronics and Packaging Society
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v.30
no.4
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pp.105-111
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2023
Electronic devices have been evolved to be mechanically flexible that can be endured repetitive deformation. This evolution emphasizes the importance of long-term reliability in metal wiring connecting electronic components, especially under bending fatigue in compressed environments. This study investigated methods to enhance adhesion between copper (Cu) and polyimide (PI) substrates, aiming to improve the reliability of copper wiring under such conditions. We applied oxygen plasma treatment and introduced a chromium (Cr) adhesion layer to the polyimide substrate. Our findings revealed that these adhesion enhancement methods significantly affect compression fatigue behavior. Notably, the chromium adhesion layer, while showing weaker fatigue characteristics at 1.5% strain, demonstrated superior performance at 2.0% strain with no delamination, outperforming other methods. These results offer valuable insights for improving the reliability of flexible electronic devices, including reducing crack occurrence and enhancing fatigue resistance in their typical usage environments.
Journal of the Korea Institute of Building Construction
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v.23
no.5
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pp.607-618
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2023
Pervasive research underscores the direct correlation between an enhanced safety climate and a marked reduction in accidents. The intricacies of safety climate are governed by three pivotal strata: organizational management, on-site operations, and the broader enterprise framework. Within an organizational context, sustaining optimal performance across these layers poses a considerable challenge, often attributable to the constraints of available managerial bandwidth. It becomes imperative, then, to conceive a phased enhancement blueprint for the safety climate. To orchestrate this blueprint with precision, a discerning understanding of the hierarchy of safety climate metrics is essential, which subsequently guides judicious managerial resource allocation. This investigation is anchored in elucidating the hierarchical significance of safety climate metrics through the Analytical Hierarchy Process(AHP). Implementing the AHP framework, both a questionnaire was disseminated and a subsequent analysis undertaken, culminating in the extraction of relative priorities of safety climate determinants. Consequent to this analysis, "workers' safety prioritization and risk aversion" emerged as the foremost dimension, holding a significance weight of 0.1900. Furthermore, within the detailed elements, "unwavering adherence to safety mandates amidst demanding operational constraints" ranked supreme, manifesting a weight of 0.6663. The findings encapsulated in this study are poised to be foundational in sculpting improvements at an institutional level and devising policies, all with the end goal of fostering an exemplar safety climate within construction arenas.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.18
no.4
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pp.177-191
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2023
This study analyzes the types of linkages between major projects used by firms that attracted venture capital among firms that received government support in the field of SME startups. It identifies the types of linkages between support programs related to attracting venture investment and verifies the usefulness of integrated and cooperative support. The main findings of this study are as follows. First, Startup Success Packages, Startup Foundation Funds*, Youth Entrepreneurship Centers, and Training are the main programs used by startups and venture firms, and support-implementing agencies use these programs to provide support for each stage of growth. Second, the majority of startups and venture firms receiving policy support for job creation and manpower enhancement projects. Third, export-type growth companies receive continuous support from MSS, MOTIE, MSIT, and KIPO. Fourth, job creation programs drive the employment performance and creation of companies. Fifth, local government support projects tend to rely heavily on central government support programs. Sixth, growth companies in the startup and venture sector have a clear link to credit guarantee scheme by KIBO. These findings provide empirical evidence on the necessity and feasibility of integrated and collaborative support, and are expected to contribute to the direction of better support policies.
Dong Ik Cha;Kyung Mi Jang;Seong Hyun Kim;Young Kon Kim;Honsoul Kim;Soo Hyun Ahn
Korean Journal of Radiology
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v.21
no.4
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pp.402-412
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2020
Objective: To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors. Materials and Methods: We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models for early HCC recurrence determined by stepwise variable selection methods based on Akaike information criterion were built, either based on preoperative factors alone or both pre-/postoperative factors. Area under the curve (AUC) for each receiver operating characteristic curve of the two models was calculated, and the two curves were compared for non-inferiority testing. The predictive models of early HCC recurrence were internally validated by bootstrap resampling method. Results: Multivariable analysis on preoperative factors alone identified aspartate aminotransferase/platelet ratio index (OR, 1.632; 95% CI, 1.056-2.522; p = 0.027), tumor size (OR, 1.025; 95% CI, 0.002-1.049; p = 0.031), arterial rim enhancement of the tumor (OR, 2.350; 95% CI, 1.297-4.260; p = 0.005), and presence of nonhypervascular hepatobiliary hypointense nodules (OR, 1.983; 95% CI, 1.049-3.750; p = 0.035) on gadoxetic acid-enhanced magnetic resonance imaging as significant factors. After adding postoperative histopathologic factors, presence of microvascular invasion (OR, 1.868; 95% CI, 1.155-3.022; p = 0.011) became an additional significant factor, while tumor size became insignificant (p = 0.119). Comparison of the AUCs of the two models showed that the prediction model built on preoperative factors alone was not inferior to that including both pre-/postoperative factors {AUC for preoperative factors only, 0.673 (95% confidence interval [CI], 0.623-0.723) vs. AUC after adding postoperative factors, 0.691 (95% CI, 0.639-0.744); p = 0.0013}. Bootstrap resampling method showed that both the models were valid. Conclusion: Risk stratification solely based on preoperative imaging and laboratory factors was not inferior to that based on postoperative histopathologic risk factors in predicting early recurrence after curative resection in within Milan criteria single HCC patients.
So Hyun Park;Subin Heo;Bohyun Kim;Jungbok Lee;Ho Joong Choi;Pil Soo Sung;Joon-Il Choi
Korean Journal of Radiology
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v.24
no.3
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pp.190-203
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2023
Objective: We aimed to assess and validate the radiologic and clinical factors that were associated with recurrence and survival after curative surgery for heterogeneous targetoid primary liver malignancies in patients with chronic liver disease and to develop scoring systems for risk stratification. Materials and Methods: This multicenter retrospective study included 197 consecutive patients with chronic liver disease who had a single targetoid primary liver malignancy (142 hepatocellular carcinomas, 37 cholangiocarcinomas, 17 combined hepatocellular carcinoma-cholangiocarcinomas, and one neuroendocrine carcinoma) identified on preoperative gadoxetic acid-enhanced MRI and subsequently surgically removed between 2010 and 2017. Of these, 120 patients constituted the development cohort, and 77 patients from separate institution served as an external validation cohort. Factors associated with recurrence-free survival (RFS) and overall survival (OS) were identified using a Cox proportional hazards analysis, and risk scores were developed. The discriminatory power of the risk scores in the external validation cohort was evaluated using the Harrell C-index. The Kaplan-Meier curves were used to estimate RFS and OS for the different risk-score groups. Results: In RFS model 1, which eliminated features exclusively accessible on the hepatobiliary phase (HBP), tumor size of 2-5 cm or > 5 cm, and thin-rim arterial phase hyperenhancement (APHE) were included. In RFS model 2, tumors with a size of > 5 cm, tumor in vein (TIV), and HBP hypointense nodules without APHE were included. The OS model included a tumor size of > 5 cm, thin-rim APHE, TIV, and tumor vascular involvement other than TIV. The risk scores of the models showed good discriminatory performance in the external validation set (C-index, 0.62-0.76). The scoring system categorized the patients into three risk groups: favorable, intermediate, and poor, each with a distinct survival outcome (all log-rank p < 0.05). Conclusion: Risk scores based on rim arterial enhancement pattern, tumor size, HBP findings, and radiologic vascular invasion status may help predict postoperative RFS and OS in patients with targetoid primary liver malignancies.
Objective: This study aimed to develop and validate models using radiomics features on a native T1 map from cardiac magnetic resonance (CMR) to predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods: Data from 274 patients with NIDCM who underwent CMR imaging with T1 mapping at Severance Hospital between April 2012 and December 2018 were retrospectively reviewed. Radiomic features were extracted from the native T1 maps. LVRR was determined using echocardiography performed ≥ 180 days after the CMR. The radiomics score was generated using the least absolute shrinkage and selection operator logistic regression models. Clinical, clinical + late gadolinium enhancement (LGE), clinical + radiomics, and clinical + LGE + radiomics models were built using a logistic regression method to predict LVRR. For internal validation of the result, bootstrap validation with 1000 resampling iterations was performed, and the optimism-corrected area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) was computed. Model performance was compared using AUC with the DeLong test and bootstrap. Results: Among 274 patients, 123 (44.9%) were classified as LVRR-positive and 151 (55.1%) as LVRR-negative. The optimism-corrected AUC of the radiomics model in internal validation with bootstrapping was 0.753 (95% CI, 0.698-0.813). The clinical + radiomics model revealed a higher optimism-corrected AUC than that of the clinical + LGE model (0.794 vs. 0.716; difference, 0.078 [99% CI, 0.003-0.151]). The clinical + LGE + radiomics model significantly improved the prediction of LVRR compared with the clinical + LGE model (optimism-corrected AUC of 0.811 vs. 0.716; difference, 0.095 [99% CI, 0.022-0.139]). Conclusion: The radiomic characteristics extracted from a non-enhanced T1 map may improve the prediction of LVRR and offer added value over traditional LGE in patients with NIDCM. Additional external validation research is required.
Among the Foley sound generation models that have recently begun to be studied, a sound generation technique using the Vector Quantized-Variational AutoEncoder (VQ-VAE) structure and generation model such as Pixelsnail are one of the important research subjects. On the other hand, in the field of deep learning-based acoustic signal compression, residual vector quantization technology is reported to be more suitable than the conventional VQ-VAE structure. Therefore, in this paper, we aim to study whether residual vector quantization technology can be effectively applied to the Foley sound generation. In order to tackle the problem, this paper applies the residual vector quantization technique to the conventional VQ-VAE-based Foley sound generation model, and in particular, derives a model that is compatible with the existing models such as Pixelsnail and does not increase computational resource consumption. In order to evaluate the model, an experiment was conducted using DCASE2023 Task7 data. The results show that the proposed model enhances about 0.3 of the Fréchet audio distance. Unfortunately, the performance enhancement was limited, which is believed to be due to the decrease in the resolution of time-frequency domains in order to do not increase consumption of the computational resources.
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