• Safety and Health at Work
• /
• v.14 no.4
• /
• pp.384-389
• /
• 2023

Background: Exposure to welding fume is associated with adverse effects on worker health. The use of various control measures can reduce levels of exposure and the resulting health effects. However, little is known about the factors that may influence workers' use of control measures in the workplace and their perceived intervention needs. This study aimed to investigate workers' and other stakeholders' views on ways to improve the use of welding fume control measures in Australian workplaces. Methods: We conducted a series of online focus group discussions and individual interviews with participants who have some occupational involvement in welding, whether as workers, employers or industry representatives, union representatives, or regulators. A semi-structured question guide was used, and all discussions and interviews were recorded and transcribed for analysis. Results: Five focus group discussions and five individual interviews were conducted with a total of 21 participants. Three major themes emerged. The first addressed the current awareness of welding fume harms and concern about exposure; the second focussed on the current use of control measures, and barriers and facilitators to their use; and the last centred around intervention needs and the contents of a potential effective intervention. Conclusion: Improving the use of control measures to prevent exposure to welding fume requires knowledge around the barriers and facilitators of control, use, and the intervention needs of stakeholders. This study has provided such knowledge, which will facilitate the design and implementation of an intervention to reduce welding fume exposure and ultimately protect the health of workers.

• Membrane and Water Treatment
• /
• v.15 no.3
• /
• pp.107-115
• /
• 2024

This study proposes the recycling of MVS as a value-added product for the removal of phosphate from aqueous solutions. By comparing the phosphate adsorption capacity of each calcined adsorbent at each temperature of MVS, it was determined that the optimal heat treatment temperature of MVS to improve the phosphate adsorption capacity was 800 ℃. MVS-800 suggests an adsorption mechanism through calcium phosphate precipitation. Subsequent kinetic studies with MVS-800 showed that the PFO model was more appropriate than the PSO model. In the equilibrium adsorption experiment, through the analysis of Langmuir and Freundlich models, Langmuir can provide a more appropriate explanation for the phosphate adsorption of MVS-800. This means that the adsorption of phosphate by MVS-800 is uniform over all surfaces and the adsorption consists of a single layer. Thermodynamic analysis of thermally activated MVS-800 shows that phosphate adsorption is an endothermic and involuntary reaction. MVS-800 has the highest phosphate adsorption capacity under low pH conditions. The presence of anions in phosphate adsorption reduces the phosphate adsorption capacity of MVS-800 in the order of CO 3 2-, SO 4 2-, NO 3- and Cl-. Based on experimental data to date, MVS-800 is an environmentally friendly adsorbent for recycling waste resources and is considered to be an adsorbent with high adsorption capacity for removing phosphates from aqueous solutions. This paper combines the advantages of gray predictor and AI fuzzy. The gray predictor can be used to predict whether the bear point exceeds the allowable deviation range, and then perform appropriate control corrections to accelerate the bear point to return to the boundary layer and achieve.

• Annals of Hepato-Biliary-Pancreatic Surgery
• /
• v.26 no.4
• /
• pp.333-338
• /
• 2022

Backgrounds/Aims: Bile duct stones (BDS) can be managed either prior to laparoscopic cholecystectomy (LC) using endoscopic retrograde cholangiopancreatography (ERCP) or with laparoscopic bile duct exploration (LBDE) at the time of LC. The latter is underutilised. The aim of this study was to use the dataset of the previously performed CholeS study to investigate LBDE hospital volumes, LBDE-to-LC rates, and LBDE outcomes. Methods: Data from 166 United Kingdom/Republic of Ireland hospitals were used to study the utilisation of LBDE in LC patients. Results: Of 8,820 LCs performed, 932 patients (10.6%) underwent preoperative ERCP and 256 patients (2.9%) underwent LBDE. Of the 256 patients who underwent LBDE, 73 patients (28.5%) had undergone prior ERCP and 112 patients (43.8%) had undergone prior magnetic resonance cholangiopancreatography. Fifteen (9.0%) of the 166 included hospitals performed less than five LBDEs in the two-month study period. LBDEs were mainly performed by upper gastrointestinal surgeons (84.4%) and colorectal surgeons (10.0%). Eighty-seven percent of the LBDEs were performed by consultants and 13.0% were performed by trainees. The laparoscopic-to-open conversion rate was 12.5%. The median operation time was 111 minutes (range: 75-155 minutes). Median hospital stay was 6 days (range: 4-11 days) for emergency LBDEs and 1 day (range: 1-4 days) for elective LBDEs. Overall morbidity was 21.5%. Bile leak rate was 5.3%. Thirty-day readmission and mortality rates were 12.1% and 0.4%, respectively. Conclusions: The single-stage approach to managing BDS was underutilised. An additional prospective study with a longer study period is needed to verify this finding.

• Smart Structures and Systems
• /
• v.33 no.4
• /
• pp.291-300
• /
• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.

• Smart Structures and Systems
• /
• v.33 no.5
• /
• pp.365-374
• /
• 2024

This paper adopts a new approach in which nonlinear vibrations can be controlled using fuzzy controllers by optimal grey evolutionary algorithm. If the fuzzy controller cannot stabilize the systems, then the high frequency is injected into the system to assist the controller, and the system is asymptotically stabilized by adjusting the parameters. This paper uses the GM (grey model) and the neural network prediction model. The structure of the neural network is improved from a single factor, and multiple data inputs are extended to various factors and numerous data inputs. The improved model expands the applicable range of uncontrolled elements and improves the accuracy of controlled prediction, using the model that has been trained and stabilized by multiple learning. The simulation results show that the improved gray neural network model has higher prediction accuracy and reliability than the traditional GM model, improving controlled management and pre-control ability. In the combined prediction, the time series parameters and the predicted values obtained from the GM (1,1) (Grey Model of first order and one variable) are simultaneously used as the input terms of the neural network, considering the influence of the non-equal spacing of the data, which makes the results of the combined gray neural network model more rationalized. By adjusting the model structure and system parameters to simulate and analyze the controlled elements, the corresponding risk change trend graphs and prediction numerical calculation results are obtained, which also realize the effective prediction of controlled elements. According to the controlled warning principle and objective, the fuzzy evaluation method establishes the corresponding early warning response method. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage.

• Korean Journal of Agricultural Science
• /
• v.50 no.3
• /
• pp.437-448
• /
• 2023

The large amount of energy required for successful crop production is the main challenge in greenhouse cropping systems. As a response to this challenge a comprehensive evaluation of greenhouse energy consumption was carried out in two structurally similar single-span greenhouses with different thermal curtain positions, with particular attention to energy productivity, specific energy, net energy, and energy ratio. The greenhouses are used for strawberry production. In the R-greenhouse (RGH), the thermal curtain hanged directly at the roof ridge, whereas in the Q-greenhouse (QGH), the thermal curtain was placed 5° from an imaginary vertical axis, from the middle of the roof ridge downwards to the north side of the greenhouse roof. The relevant data were recorded using standard methods. The results indicated that the energy expended in the RGH and QGH systems was 2,186.48 and 2,189.26 MJ/m², respectively. Electricity and nitrogen fertilizer contributed the highest energy input in both greenhouses and in all seasons. The output energy was 3.12 and 3.82 MJ/m², respectively, in RGH and QGH in season I and 4.40 and 4.87 MJ/m² in season II. In terms of energy expended, there was no significant difference between the two greenhouses, nor between the two seasons. These results indicate that greenhouses of the size used in this investigation are not viable in terms of energy productivity, energy-use efficiency, and subsequent economic performance. However, further studies should be conducted to scale-up the information obtained from this investigation.

• Steel and Composite Structures
• /
• v.53 no.1
• /
• pp.103-114
• /
• 2024

This study proposes a new hybrid approach that utilizes post-earthquake survey data and numerical analysis results from an evolving finite element routing model to capture vulnerability processes. In order to achieve cost-effective evaluation and optimization, this study introduced an online data evolution data platform. The proposed method consists of four stages: 1) development of diagnostic sensitivity curve; 2) determination of probability distribution parameters of throughput threshold through optimization; 3) update of distribution parameters using smart evolution method; 4) derivation of updated diffusion parameters. Produce a blending curve. The analytical curves were initially obtained based on a finite element model used to represent a similar RC building with an estimated (previous) capacity height in the damaged area. The previous data are updated based on the estimated empirical failure probabilities from the post-earthquake survey data, and the mixed sensitivity curve is constructed using the update (subsequent) that best describes the empirical failure probabilities. The results show that the earthquake rupture estimate is close to the empirical rupture probability and corresponds very accurately to the real engineering online practical analysis. The objectives of this paper are to obtain adequate, safe and affordable housing and basic services, promote inclusive and sustainable urbanization and participation, implement sustainable and disaster-resilient buildings, sustainable human settlement planning and management. Therefore, with the continuous development of artificial intelligence and management strategy, this goal is expected to be achieved in the near future.

• Steel and Composite Structures
• /
• v.52 no.6
• /
• pp.647-656
• /
• 2024

This paper discusses the study of concrete composite walls of algorithmic modeling, in which steel tubes are embedded. The load-bearing capacity of STHC composite walls increases with the increase of axial load coefficient, but its ductility decreases. The load-bearing capacity can be improved by increasing the strength of the steel pipes; however, the elasticity of STHC composite walls was found to be slightly reduced. As the shear stress coefficient increases, the load-bearing capacity of STHC composite walls decreases significantly, while the deformation resistance increases. By analyzing actual cases, we demonstrate the effectiveness of the research results in real situations and enhance the persuasiveness of the conclusions. The research results can provide a basis for future research, inspire more explorations on seismic design and construction, and further advance the development of this field. Emphasize the importance of research results, promote interdisciplinary cooperation in the fields of structural engineering, earthquake engineering, and materials science, and improve overall seismic resistance. The emphasis on these aspects will help highlight the practical impact of the research results, further strengthen the conclusions, and promote progress in the design and construction of earthquake-resistant structures. The goals of this work are access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient architecture, sustainable planning and management of human settlements. Simulation results of linear and nonlinear structures show that this method can detect structural parameters and their changes due to damage and unknown disturbances. Therefore, it is believed that with the further development of fuzzy neural network artificial intelligence theory, this goal will be achieved in the near future.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.30 no.1
• /
• pp.43-48
• /
• 2010

This study was conducted to compare the chemical composition, dry matter digestibility (DMD), dry matter intake, and utilization of nitrogen and energy of dairy goats (Saanen), when fed on imported timothy hay (IT), mixture grass hay (MG) and native grass hay (NG), respectively. The experimental trials were conducted from April, 2008 to December, 2008 at the environmental controlled barn of Chungnam National University. Twelve dairy goats (Saanen) were selected which had nearly the same body weight (24.2kg, male). The content of crude protein (CP) of MG hay was higher than that of other diets (p<0.05), but the contents of NDF, ADF, cellulose and lignin of IT and NG diet were higher than those of MG diet (p<0.05). The voluntary DM intake of dairy goats fed with herbage from MG diet (30.7/$BW_{kg}$/day) was higher than that of other diets, but no significant difference was observed between that of IT diet and NG diet (p>0.05). The DMD of MG diet (69.8%) was higher than that of NG diet (62.2%) and IT diet (60.8%) (p<0.05), but no significant difference was observed between that of IT diet and NG diet (p>0.05). In nitrogen utilization, the apparently digested N %, retained % and biological value of dairy goats fed with herbage from MG diet were higher and TG diet was lower (p<0.05). In energy utilization, digestible energy and the energy of apparently digested minus urinary losses of MG diet were higher than those of IT diet and NG diet (p<0.05), but no significant difference was found between IT diet and NG diet (p>0.05). Based on the results, the dry matter intake, DMD and utilization of nitrogen and energy of dairy goats of MG were higher than those of IT diet and NG diet (p<0.05), the DMD and biological value (%) of NG diet was higher than that of IT diet (p<0.05).

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.26 no.2
• /
• pp.113-120
• /
• 2006

This study was conducted to select the optimum seed mixture for beef cattle (Hanwoo) grazing in middle mountain area at 450m from sea level during 2 years from October 1, 1999. Seed mixtures were composed of four different treatment according to main species such as orchardgrass (T1), perennial ryegrass (T2), timothy (T3) and Italian ryegrass (T4). Grass composition rate of different seed mixtures was decreased mostly at first year of grazing, like 44.9% of orchardgrass in T1 plot, 27.6% of perennial ryegrass in T2 plot, 40.9% of timothy in T3 plot and 40.7% of Italian ryegrass in T4 plot, respectively. Main species in seed mixture were decreased in grazing pasture, but kentucky bluegrass and tall fescue were increased in all plots. Italian ryegrass in T4 plot was well grown in early grown stage and inhibited the growth of other grass species, and 44.2% of Italian ryegrass was maintained in second year in the grazing plot. Average dry matter yields of first you showed 6,673 kg/ha and second year was 10,177 kg/ha. Average TDN yields of different seed mixtures were 6,399 kg/ha in T1, 7,769 kg/ha in T2, 4,383 kg/ha in T3 and 7,146 kg/ha in T4 plot. Average herbage dry matter intakes by different seed mixtures during 2 years were 5,937 kg/ha in T1, 6,375 kg/ha in T2, 4,925 kg/ha in T3 and 6,456 kg/ha in T4. This result indicated that perennial ryegrass would recommended in main species of Hanwoo grazing pasture.