• Earthquakes and Structures
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• 제15권6호
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• pp.639-654
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• 2018

Rocking motion have been used for achieving the 'resilient buildings' against earthquakes in recent studies. Low-rise buildings, unlike the tall ones, because of their small aspect ratio tend to slide rather than move in rocking mode. However, since rocking is more effective in seismic response reduction than sliding, it is desired to create rocking motion in low-rise buildings too. One way for this purpose is making the building's structure rock on its internal bay(s) by reducing the number of bays at the lower part of the building's skeleton, giving it a mushroom form. In this study 'mushroom skeleton' has been used for creating multi-story rocking regular steel buildings with square plan to rock on its one-by-one bay central lowest story. To show if this idea is effective, a set of mushroom buildings have been considered, and their seismic responses have been compared with those of their conventional counterparts, designed based on a conventional code. Also, a set of similar buildings with skeleton stronger than code requirement, to have immediate occupancy (IO) performance level, have been considered for comparison. Seismic responses, obtained by nonlinear time history analyses, using scaled three-dimensional accelerograms of selected earthquakes, show that by using appropriate 'mushroom skeleton' the seismic performance of buildings is upgraded to mostly IO level, while all of the conventional buildings experience collapse prevention (CP) level or beyond. The strong-skeleton buildings mostly present IO performance level as well, however, their base shear and absolute acceleration responses are much higher than the mushroom buildings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4290-4309
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• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• Structural Monitoring and Maintenance
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• 제8권4호
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• pp.329-344
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• 2021

The use of structural control devices to minimize structural response to seismic/dynamic excitations has attracted increased attention in recent years. The use of magnetorheological (MR) dampers as a control device have captured the attention of researchers in this field due to its flexibility, adaptability, easy control, and low power requirement compared to other control devices. However, little attention has been paid to the effect of configuration and number of dampers installed in a structure on responses reduction. This study assesses the control of a five-story structure using one and two MR dampers at different stories to determine the optimal damper positions and configurations based on performance indices. This paper also addresses the fail-safe current value to be applied to the MR damper at each floor in the event of feedback or control failure. The model is mathematically simulated in SIMULINK/MATLAB environment. Linear control strategies for current at 0 A, 0.5 A, 1 A, 1.5 A, 2 A, and 2.5 A are implemented for MR dampers, and the response of the structure to these control strategies for different configurations of dampers is compared with the uncontrolled structure. Based on the performance indices, it was concluded that the dampers should be positioned starting from the ground floor, then the 2^nd floor followed by 1^st and rest of the floors sequentially. The failsafe value of current for MR dampers located in lower floors (G+1) should be kept at a higher value compared to dampers at top floors for effective passive control of multi-story structures.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제49권2호
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• pp.86-90
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• 2023

Objectives: An ectopic tooth is a rare eruption of a tooth out of the normal dental apparatus and occurs commonly with the third molar. Thus, in this study, we reported a case series of ectopic teeth in rare jaw locations and highlight the associated pathology and our experience in the surgical management. Patients and Methods: All cases of ectopic tooth managed at the Department of Oral and Maxillofacial Surgery, University of Maiduguri Teaching Hospital from January 2011 to December 2020 were reviewed. The information retrieved includes biodata, location of the ectopic tooth, signs, symptoms, type of tooth and associated pathology, surgical approach and complications. Results: Ten cases of ectopic teeth were identified over the study period. This comprised 80.0% males with a mean age was 23.3 years. The antrum and lower border of the mandible accounted for 50.0% and 40.0% of the ectopic locations, respectively. Dentigerous cyst was the most associated pathology (70%) and usually presented with pain and swelling. Surgical intervention predominantly via the intraoral route was performed if indicated. Conclusion: Ectopic teeth are rare and not always associated with pathology. A high index of suspicion and radiological investigation are necessary for diagnosis. A more extensive multi-center study is however recommended to determine the prevalence of ectopic teeth other than the third molar.

• Computers and Concrete
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• 제32권2호
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• Steel and Composite Structures
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• 제45권2호
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.

• Journal of Veterinary Science
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• 제25권3호
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• pp.43.1-43.13
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• 2024

Importance: Haemaphysalis longicornis is an obligate blood-sucking ectoparasite that has gained attention due its role of transmitting medically and veterinary significant pathogens and it is the most common tick species in Republic of Korea. The preferred strategy for controlling ticks is a multi-antigenic vaccination. Testing the efficiency of a combination antigen is a promising method for creating a tick vaccine. Objective: The aim of the current research was to analyze the role of subolesin and enolase in feeding and reproduction of H. longicornis by gene silencing. Methods: In this study, we used RNA interference to silence salivary enolase and subolesin in H. longicornis. Unfed female ticks injected with double-stranded RNA targeting subolesin and enolase were attached and fed normally on the rabbit's ear. Real-time polymerase chain reaction was used to confirm the extent of knockdown. Results: Ticks in the subolesin or enolase dsRNA groups showed knockdown rates of 80% and 60% respectively. Ticks in the combination dsRNA (subolesin and enolase) group showed an 80% knockdown. Knockdown of subolesin and enolase resulted in significant depletion in feeding, blood engorgement weight, attachment rate, and egg laying. Silencing of both resulted in a significant (p < 0.05) reduction in tick engorgement, egg laying, egg hatching (15%), and reproduction. Conclusions and Relevance: Our results suggest that subolesin and enolase are an exciting target for future tick control strategies.

• Journal of Preventive Medicine and Public Health
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• 제57권3호
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• pp.223-233
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• 2024

Objectives: The coronavirus disease 2019 pandemic has exacerbated the rate of tuberculosis (TB) infection among close contacts of TB patients in remote regions. However, research on preventive behaviors, guided by the Health Belief Model (HBM), among household contacts of TB cases is scarce. This study aimed to employ the HBM as a framework to predict TB preventive behaviors among household contacts of TB patients in the border areas of Northern Thailand. Methods: A cross-sectional study with multi-stage random sampling was conducted in Chiang Rai Province. The study included 422 TB patients' household contacts aged 18 years or older who had available chest X-ray (CXR) results. A self-administered questionnaire was used to conduct the survey. Results: The participants' mean age was 42.93 years. Pearson correlation analysis showed that TB preventive behavior scores were significantly correlated with TB knowledge (r=0.397), perceived susceptibility (r=0.565), perceived severity (r=0.452), perceived benefits (r=0.581), self-efficacy (r=0.526), and cues to action (r=0.179). Binary logistic regression revealed that the modeled odds of having an abnormal CXR decreased by 30.0% for each 1-point score increase in preventive behavior (odds ratio, 0.70; 95% confidence interval, 0.61 to 0.79). Conclusions: HBM constructs were able to explain preventive behaviors among TB patients' household contacts. The HBM could be used in health promotion programs to improve TB preventive behaviors and avoid negative outcomes.

• Steel and Composite Structures
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• 제51권4호
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• 생물환경조절학회지
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• 제13권4호
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• pp.217-225
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• 2004

본 조사는 최근 급격히 증가하고 있는 새송이버섯 재배농가의 안정적 영농을 위해 재배사 설계, 시공 및 환경조절과 관련한 기초 자료를 마련하기 위해 서부 경남지역을 대상으로 새송이버섯 재배사의 재배사 규모, 환경조절시스템 등의 실태조사 및 검토를 하였다. 재배사의 형태는 반영구재배사와 영구재배사로 대별 할수 있었고, 반영구재배사는 대부분 단동이었고, 영구재배사의 경우는 단동에 비해 상대적으로 연동이 많았다. 그리고 재배사의 규모는 형태에 관계없이 다양하였지만, 길이, 폭 및 동고는 각각 20m, $6.6\~7.0m$ 및 $4.6\~5.0m$정도의 농가가 가장 많았으며, 동당 바닥면적은 $132\~140m^2$(40-42평)정도의 범위로서 대부분 콘크리트로 처리하여 각종 균에 의한 버섯의 오염을 방지 할 수 있도록 되어 있었다. 반영구 및 영구재배사의 지붕경사각은 각각 $41.5^{\circ}$ 및 $18.6\~28.6^{\circ}$로 나타나 반영구재배사의 지붕경사도가 더 큰 것으로 나타났다. 그리고 재배상의 폭 및 단수는 재배사의 형태에 관계없이 각각 $1.2\~1.6m$정도와 4단이 주류를 이루고 있었다. 버섯을 연중재배 하는 재배사에는 모두 냉${\cdot}$난방시설, 가습장치 및 환기팬이 설치되어 있었다. 난방방식의 경우, 온수보일러, 전기히터, 증기보일러 순으로 나타났다. 냉방장치의 경우는 모두 산업용 에어컨을 설치하여 운용하고 있었다. 그리고 가습은 초음파가습기와 원심분리가습기를 사용하고 있었으며, 보조 장치로 분무노즐을 사용하는 농가도 일부 있었다. 또한 온${\cdot}$습도 조절 및 탄산가스 조절을 위한 장치의 제어는 동별 제어시스템을 많이 채택하고 있었다. 그리고 온도센서 이외는 모두 타이머를 이용하고 있음을 알 수 있었다. 배지병의 크기는 850 cc 및 1,100 cc를 사용하는 농가가 주류를 이루고 있었고, 이 밖에도 800cc와 950 cc, 1,200 cc병을 사용하는 농가도 있었다. 출하형태는 대부분 유통회사와 공판장을 동시에 이용하고 있었다.