• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.23-29
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• 2021

The purpose of this study is to reduce the probability of occurrence of electric fires as a preemptive preventive measure, and to strengthen the capability of preventing electric fires by strengthening the cooperative function between electric fire-related departments and establishing a cooperative system. In this study, the general aspects of electric fires were identified by reviewing the literature such as ignition mechanisms of electric fires. And the major electrical fires that occurred in the last 10 years were classified into ignition factors (short circuit, overload/overcurrent, and earth leakage/ground fault) and ignition sources (wiring/wiring appliances, electrical equipment/household appliances). And the 4M technique was used to analyze the potential causes of ignition at the fire site and to suggest preventive measures. In the case In this study, out of 48 electrical fires in the past 10 years, 16 short-circuit fires, 3 overload/overcurrent fires, 3 short-circuit and earth fault fires, 16 fires in wiring/wiring appliances, and 10 fires in electrical equipment/home appliances classified as cases. And prevention measures were presented in terms of human, machine, media, and management by using the 4M technique. For the preemptive prevention of electric fires, strengthening the compulsory electrical safety inspection and making it mandatory to report when new or expanding electric facilities, charging a fee for electric safety inspection for detached houses and granting benefits subject to inspection completion, improvement of the electric safety voluntary inspection table and safety indications; It was suggested as a policy to organize and operate electrical safety inspection personnel in a two-person team (mixed), establish a close work cooperation system with related organizations, and strengthen electrical safety education and publicity.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.25-31
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• 2022

By an aid of needle coating, we have fabricated a spherical microlens array using poly(methyl methacrylate) for potential applications in light extraction of organic light-emitting diodes. With an attempt to achieve high-density and high-aspect-ratio microlens arrays, we have investigated the coating behaviors by varying the material parameters such as the solute concentration and wettability of the poly(methyl methacrylate) solution and process parameters such as the dwell time of needle near the substrate, retract distance of needle from the substrate, and coating gap between the needle and substrate. Under the optimized coating conditions, it is demonstrated that high-aspect-ratio microlens arrays can be obtained using a coating solution with high solute concentration and a small amount of a hydrophobic solvent. It is found that the diameter and height of microlens array are decreased with increasing poly(methyl methacrylate) concentration, yet the overall aspect ratio is rather enhanced. By the addition of 5 wt% hexylamine in 35 wt% poly(methyl methacrylate) solution, we have achieved a spherical microlens with the height of 7.7 ㎛ and the width of 94.24 ㎛ (the aspect ratio of 0.082). To estimate the capability of light extraction by the microlens array, we have performed ray tracing simulations and demonstrated that the light extraction efficiency of organic light-emitting diode is expected to be enhanced up to 24%.

• Iberoamérica
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• v.23 no.2
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• pp.273-307
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• 2021

The covid 19 pandemic led to an economic collapse and multiple impacts upon Argentina's labour dynamics. As well as in other parts of the region, falls in employment rates (both due to an increase in unemployment and significant withdrawals from the labour force) were combined with wage reductions for those who were able to keep their jobs. Thus, two important processes for the labour market complimented each other: a structural shock associated with a tasks automation as a reorganisation and substitution of factors, with a cyclical recession caused by the pandemic. The international experience shows the amplifying impact the latter has on the former, generating long-term consequences mainly in routine-intensive jobs. However, the knowledge-intensive services sector appears to be the most capable of cushioning the recessionary shock (both in terms of wages and labour absorption), even with nuances within the sector depending on the extent of the shutdown measures and its capability to switch to remote work. Finally, the task approach is decisive in capturing the ability to adapt both the cyclical and structural processes, absorbing a large part of the explanatory potential that sectoral classifications tend to bring about.

• Fisheries and Aquatic Sciences
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• v.25 no.8
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• pp.450-461
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• 2022

A randomized, double-blind, and placebo-controlled clinical study was used to determine the cognitive functions related to working memory (WM) and antioxidant properties of fermented Laminaria japonica (FLJ) on healthy volunteers. Eighty participants were divided into a placebo group (n = 40) and FLJ group (n = 40) that received FLJ (1.5 g/day) for 6 weeks. Memory-related blood indices (brain-derived neurotrophic factor, BDNF; angiotensin-converting enzyme; human growth hormone, HGH; insulin-like growth factor-1, IGF-1) and antioxidant function-related indices (catalase, CAT; malondialdehyde, MDA; 8-oxo-2'-deoxyguanosine, 8-oxo-dG; thiobarbituric acid reactive substances, TBARS) were determined before and after the trial. In addition, standardized cognitive tests were conducted using the Cambridge Neuropsychological Test Automated Batteries. Furthermore, the Korean Wechsler Adult Intelligence Scale (K-WAIS)-IV, and the Korean version of the Montreal Cognitive Assessment (MoCA-K) were used to assess the pre and post intake changes on WM-related properties. According to the results, FLJ significantly increased the level of CAT, BDNF, HGH, and IGF-1. FLJ reduced the level of TBARS, MDA, and 8-oxo-dG in serum. Furthermore, FLJ improved physical activities related to cognitive functions such as K-WAIS-IV, MoCA-K, Paired Associates Learning, and Spatial Working Memory compared to the placebo group. Our results suggest that FLJ is a potential candidate to develop functional materials reflecting its capability to induce antioxidant mechanisms together with WM-related indices.

• Medical Lasers
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• v.10 no.2
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• pp.96-105
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• 2021

Background and Objectives Skin aging is reportedly associated with regulation in collagen and elastin synthesis. This study investigated the potential of combining light-emitting diode (LED) treatments using a 630-nm and 850-nm LED with simultaneous microcurrent application. Materials and Methods The dorsal skin of female pigs was treated with a home-use device. We examined the treatment effects using photography, thermocamera, microscopic pathology, and histological examination to determine the mechanism of action, efficacy, and safety of the procedure. A histological observation was performed using hematoxylin and eosin, Masson's trichrome, Victoria blue, and immunohistochemical staining. We also used the Sircol soluble collagen and elastin assay kit to measure the amounts of collagen and elastin in the porcine back skin tissue after 2 and 6 weeks. Results Evaluation by visual inspection and devices showed no skin damage or heat-induced injury at the treatment site. Histological staining revealed that accurate treatment of the targeted dermis layer effectively enhanced collagen and elastin deposition. Collagen type I, a protein defined by immunohistochemical staining, was overexpressed in the early stages of weeks 2 and 6. Combined therapy findings showed the superior capability of the 630-nm and 850-nm LED procedures to induce collagen; in contrast, elastin induction was more pronounced after microcurrent treatments. Conclusion The home-use LED device, comprising a combination of 630-nm and 850-nm LEDs and microcurrent, is safe and can be used as an adjunctive treatment for self-administered facial rejuvenation.

• BMB Reports
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• v.55 no.11
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• pp.559-564
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• 2022

Diabetes mellitus is one of the most prevalent diseases in modern society. Many complicationssuch as hepatic cirrhosis, neuropathy, cardiac infarction, and so on are associated with diabetes. Although a relationship between diabetes and hair loss has been recently reported, the treatment of diabetic hair loss by Wnt/β-catenin activators has not been achieved yet. In this study, we found that the depilation-induced anagen phase was delayed in both db/db mice and high-fat diet (HFD) and streptozotocin (STZ)-induced diabetic mice. In diabetic mice, both hair regrowth and wound-induced hair follicle neogenesis (WIHN) were reduced because of suppression of Wnt/β-catenin signaling and decreased proliferation of hair follicle cells. We identified that KY19382, a small molecule that activates Wnt/β-catenin signaling, restored the capabilities of regrowth and WIHN in diabetic mice. The Wnt/β-catenin signaling activator also increased the length of the human hair follicle which was decreased under high glucose culture conditions. Overall, the diabetic condition reduced both hair regrowth and regeneration with suppression of the Wnt/β-catenin signaling pathway. Consequently, the usage of Wnt/β-catenin signaling activators could be a potential strategy to treat diabetes-induced alopecia patients.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.483-493
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• 2022

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R² of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.

• Smart Structures and Systems
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• v.29 no.2
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• pp.301-309
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• 2022

Protective coatings are most widely used anticorrosive structures for steel structures. The corrosion under the coating damages the host material, but this damage is completely hidden. Therefore, a field-applicable under-coating-corrosion visualization method has been desired for a long time. Laser ultrasonic technology has been studied in various fields as an in situ nondestructive inspection method. In this study, a comparative analysis was carried out between a guided-wave ultrasonic propagation imager (UPI) and pulse-echo UPI, which have the potential to be used in the field of under-coating-corrosion management. Both guided-wave UPI and pulse-echo UPI were able to successfully visualize the corrosion. Regarding the field application, the guided-wave UPI performing Q-switch laser scanning and piezoelectric sensing by magnetic attachment exhibited advantages owing to the larger distance and incident angle in the laser measurement than those of the pulse-echo UPI. Regarding the corrosion visualization methods, the combination of adjacent wave subtraction and variable time window amplitude mapping (VTWAM) provided acceptable results for the guided-wave UPI, while VTWAM was sufficient for the pule-echo UPI. In addition, the capability of multiple sensing in a single channel of the guided-wave UPI could improve the field applicability as well as the relatively smaller size of the system. Thus, we propose a guided-wave UPI as a tool for under-coating-corrosion management.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.