• Earthquakes and Structures
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• 제22권6호
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• pp.539-548
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• 2022

Steel plate shear walls (SPSWs) are one of the most important and widely used lateral load-bearing systems. The reason for this is easier execution than reinforced concrete (RC) shear walls, faster construction time, and lower final weight of the structure. However, the main drawback of SPSWs is premature buckling in low drift ratios, which affects the energy absorption capacity and global performance of the system. To address this problem, two groups of SPSWs under cyclic loading were investigated using the finite element method (FEM). In the first group, several series of circular rings have been used and in the second group, a new type of SPSW with concentric circular rings (CCRs) has been introduced. Numerous parameters include in yield stress of steel plate wall materials, steel panel thickness, and ring width were considered in nonlinear static analysis. At first, a three-dimensional (3D) numerical model was validated using three sets of laboratory SPSWs and the difference in results between numerical models and experimental specimens was less than 5% in all cases. The results of numerical models revealed that the full SPSW undergoes shear buckling at a drift ratio of 0.2% and its hysteresis behavior has a pinching in the middle part of load-drift ratio curve. Whereas, in the two categories of proposed SPSWs, the hysteresis behavior is complete and stable, and in most cases no capacity degradation of up to 6% drift ratio has been observed. Also, in most numerical models, the tangential stiffness remains almost constant in each cycle. Finally, for the innovative SPSW, a relationship was suggested to determine the shear capacity of the proposed steel wall relative to the wall slenderness coefficient.

• Journal of Preventive Medicine and Public Health
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• 제55권1호
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• pp.10-18
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• 2022

Disability-adjusted life-year (DALY) estimates may vary according to factors such as the standard life expectancy, age weighting, time preference and discount rate, calculation of disability weights, and selection of the estimation method. DALY estimation methods are divided into the following 3 approaches: the incidence-based approach, the pure prevalence-based approach, and the hybrid approach. These 3 DALY estimation approaches each reflect different perspectives on the burden of disease using unique characteristics, based on which the selection of a suitable approach may vary by the purpose of the study. The Global Burden of Disease studies, which previously estimated DALYs using the incidence-based approach, switched to using the hybrid approach in 2010, while the National Burden of Disease studies in Korea still mainly apply the incidence-based approach. In order to increase comparability with other international burden of disease studies, more DALY studies using the prevalence-based approach need to be conducted in Korea. However, with the limitations of the hybrid approach in mind, it is necessary to conduct more research using a disease classification system suitable for Korea. Furthermore, more detailed and valid data sources should be established before conducting studies using a broader variety of DALY estimation approaches. This review study will help researchers on burden of disease use an appropriate DALY estimation approach and will contribute to enhancing researchers' ability to critically interpret burden of disease studies.

• Journal of Preventive Medicine and Public Health
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• 제54권3호
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• pp.199-207
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• 2021

Objectives: Physical inactivity is the fourth leading global risk factor for mortality, followed by obesity. The combination of these risk factors is associated with non-communicable diseases, impaired physical function, and declining mental function. The World Health Organization recommends physical activity to reduce the mortality rate. Thus, this study examined the effects on anthropometric measurements of a 12-week walking program for elderly people in Samarahan, Sarawak, Malaysia with a 7000-step goal and weekly group walking activities. Methods: A quasi-experimental study was conducted involving 109 elderly people with a body mass index (BMI) ≥25.0 kg/m². BMI, body composition, and average daily steps were measured at baseline, 6 weeks, and 12 weeks. Data were analyzed using SPSS version 26.0, and repeated-measures analysis of variance with the paired t-test for post-hoc analysis was conducted. Results: In total, 48 participants in the intervention group and 61 participants in the control group completed the study. A significant interaction was found between time and group. The post-hoc analysis showed a significant difference between pre-intervention and post-intervention (within the intervention group). The post-intervention analysis revealed an increase in the mean number of daily steps by 3571.59, with decreases in body weight (-2.20 kg), BMI (-0.94 kg/m²), body fat percentage (-3.52%), visceral fat percentage (-1.29%) and waist circumference (-2.91 cm). Skeletal muscle percentage also showed a significant increase (1.67%). Conclusions: A 12-week walking program combining a 7000-step goals with weekly group walking activities had a significant effect on the anthropometric measurements of previously inactive and overweight/obese elderly people.

• 한국융합학회논문지
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• 제12권7호
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• pp.31-36
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• 2021

중국 우한발 코로나 19 바이러스로 인하여 세계 경제가 침체하여, 미국연방준비제도를 비롯한 대부분 국가에서는 통화량을 늘려 경기를 부양하는 정책을 내놓았다. 주식 투자자들 대부분은 기업에 대한 재무제표 분석이 없이 유명 유튜버의 추천종목이나 지인의 말만 듣고 투자하는 경향이 있어서 주식투자의 손실 가능성이 크다. 따라서, 본 연구에서는 기존 자동매매 조건에서 발전된 인공지능 딥러닝 기법을 이용하여 주가에 영향을 미치는 거시지표를 분석하고 예측하여 주가에 미치는 상관관계를 통한 개별주가예측에 가중치를 부여하고 주가를 예측한다. 또한, 주가는 실시간 증시뉴스에 민감하게 반응하기 때문에 증시뉴스 텍스트 마이닝을 통하여 인공지능으로 예측된 주가에 가중치를 반영하여 더 정확한 주가 예측을 하여 주식 투자자에게 매매의 판단 근거를 제공하여 건전한 주식투자가 되도록 이바지하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Computers and Concrete
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• 제30권6호
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• pp.421-432
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• 2022

Recently, the interminable ozone depletion and the global warming concerns has led to construction industries to seek for construction materials which are eco-friendly. Regarding this, Geopolymer Concrete (GPC) is getting great interest from researchers and scientists, since it can operate by-product waste to replace cement which can lead to the reduction of greenhouse gas emission through its production. Also, compared to ordinary concrete, geopolymer concrete belongs improved mechanical and durability properties. In spite of its positive properties, the practical use of geopolymer concrete is currently limited. This is primarily owing to the scarce structural, design and application knowledge. This study investigates the Mechanical and Durability of Geopolymer Concrete Containing Fibers and Recycled Aggregate. Mixtures of elastoplastic fiber reinforced geopolymer concrete with partial replacement of recycled coarse aggregate in different proportions of 10, 20, 30, and 40% with natural aggregate were fabricated. On the other hand, geopolymer concrete of 100% natural aggregate was prepared as a control specimen. To consider both strength and durability properties and to evaluate the combined effect of recycled coarse aggregate and elastoplastic fiber, an elastoplastic fiber with the ratio of 0.4% and 0.8% were incorporated. The highest compressive strength achieved was 35 MPa when the incorporation of recycled aggregates was 10% with the inclusion of 0.4% elastoplastic fiber. From the result, it was noticed that incorporation of 10% recycled aggregate with 0.8% of the elastoplastic fiber is the perfect combination that can give a GPC having enhanced tensile strength. When specimens exposed to freezing-thawing condition, the physical appearance, compressive strength, weight loss, and ultrasonic pulse velocity of the samples was investigated. In general, all specimens tested performed resistance to freezing thawing. the obtained results indicated that combination of recycled aggregate and elastoplastic fiber up to some extent could be achieved a geopolymer concrete that can replace conventional concrete.

• 운동영양학회지
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• 제25권3호
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• pp.36-43
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• 2021

[Purpose] Exercise is a key factor in preventing obesity and metabolic syndrome. Sumo wrestlers increase their body size from childhood for athletic advantage; however, the risk of metabolic syndrome in junior sumo wrestlers is undetermined. Preventive measures against pediatric obesity should be initiated during childhood to prevent obesity in adulthood, considering its high global incidence. We comparatively evaluated the risk factors for metabolic syndrome in junior sumo wrestlers and children with obesity. [Methods] We enrolled 70 male children (age 9-17 years [sumo group, n = 14] and 9-14 years [other sports and non-exercise groups, n = 28 each]) and evaluated their anthropometric parameters (height, weight, body mass index z-score, obesity rate, waist circumference, waist to height ratio) and hematological parameters (total, low-density, high-density, and non-high-density lipoprotein-cholesterol; triglycerides; plasma glucose, and glycated hemoglobin levels). [Results] The BMI z-score, obesity rate, waist circumference (p < 0.05, along with the non-exercise group), and systolic blood pressure were significantly higher and the high-density cholesterol level was lower in the sumo group than in the other sports group (p < 0.05). The waist to height ratio was significantly higher in the non-exercise group than in the other sports group (p < 0.05). No significant difference was found in other blood lipid, plasma glucose (significantly lower level than the reference range in the sumo group, p < 0.05), and glycated hemoglobin (within the reference range in all groups) levels among the three groups. [Conclusion] Junior sumo wrestlers had a larger body size and higher blood pressure than children with obesity who exercised regularly. This provides direction for future research into targeted preventive interventions against metabolic syndrome for junior sumo wrestlers with large body size.

• International journal of advanced smart convergence
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• 제11권3호
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• pp.222-228
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• 2022

As a means to cope with the climate change crisis caused by global warming, automobile manufacturers continue to make efforts to use the driving energy of vehicles as electricity. As a result, parts industry such as battery, motor, and controller are attracting attention. China is often seen in large cities, with electric vehicles such as electric bicycles, electric motorcycles, and small electric vehicles popularized and commercialized, mainly in large cities. However, small electric vehicles are not popular in Korea, which is why the country's topography is high in hills. In order to drive the hilly domestic roads, power performance including vehicle climbing ability should be improved. In order to improve the power performance and the climbing capacity of small electric vehicles, the capacity of the motor should be increased. However, when the performance of the motor is improved, the weight of the motor becomes heavy and the price competitiveness is likely to decrease. In addition, in order to operate a high-performance motor, the power consumption of the battery is rapidly increased, so various problems must be solved. In order to commercialize a small electric vehicle for one or two people who do not emit harmful exhaust gas to the human body in a hilly domestic terrain, it is effective to have a separate transmission system. In this study, we were conducted dynamometer test to produce a continuously variable transmission(CVT) system prototype using a spring that can be applied to a small electric vehicle and to install a CVT system prototype manufactured in a small electric vehicle. The dynamometer test results showed that the maximum speed performance, acceleration performance, and climbing performance were improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3738-3760
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• 2022

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.175-181
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• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.