In view of the knowledge gap between what students learn in a design studio and what they do in their future work in the labor market, this study assumed that live projects supported architectural education, contributed to the development of students' capabilities, prepared them to enter the labor market, and were complementary to their knowledge acquired in traditional design studio. This study aimed to evaluate the importance of live projects and find out the extent to which students benefit from them in overcoming employment difficulties to easily get into the labor market. A descriptive and analytical approach similar to global experiences was used to monitor the progress of senior students in live projects. Measurement mechanism, such as questionnaire and observation, was used to know the skills of students acquired during the experiment. The experiment results showed that most of the students agreed that live projects provided realistic learning experiences different from the traditional design studio. In addition, the results showed that live projects helped students develop many skills, such as negotiation, persuasion, teamwork, etc. which they did not acquire through virtual projects. In the design studio, live projects were considered as a successful educational method that simulated reality and prepared the students for their professional practice.
Responsible use of social media requires a level of culture and awareness on the part of the user themselves that allows them to understand and absorb the enormous amount of information they receive through these mediums, verify it, and then share it with their friends and users. This leads to numerous problems related to public health and safety. This research aims to identify the most significant effects of the dissemination of fake news in times of crisis on public health and safety, as well as to propose strategies to overcome this phenomenon. A hybrid Grey-ARAS (Additive Ratio Assessment) model was used to rank the potential impacts and propose strategies to overcome them. Four experts in the field of public health, data analysis, and contagious diseases participated in this study to determine the weights. Eight factors affecting public health and safety were proposed, along with seven strategies to mitigate these impacts. The results showed that the most important factors are creating panic and anxiety among people along with the contribution to the misleading public policy decisions. The results also showed that the most appropriate strategies to overcome the impact of fake news are to encourage people to check facts and monitor social media. A sensitivity analysis of the results obtained was also performed, proposing 20 different scenarios to adjust the relative weights of the criteria. The results showed a certain stability when using different scenarios.
Unsustainable fossil fuels are mainly used to generate power in compression ignition (CI) engines in industry now. Due to fossil fuel depletion and potential environmental hazards, it is necessary for researchers to find alternative energy resources to adequately substitute hydrocarbon fossil fuels in current engines. A huge number of studies have focused on the use of renewable fuels in CI engines along with conventional petroleum fuels. Therefore, this paper aimed to analyze the effect of gaseous fuels added to CI engines as a supplement, such as H2, biogas and syngas, in dual fuel mode with diesel as an alternative fuel. This paper analyzed several important characteristics, on which engine evaluation of CI engines using gaseous fuel as an additive is based, such as combustion, performance and emissions, and compared them with those of CI engines operating in single-fuel mode. The findings of numerous empirical studies are shown in graphs of particular parameters, which were crucial for investigating and assessing the case. The main conclusions indicated that gaseous fuel enrichment caused slight decline of performance in CI dual-fuel engine but actually improved emissions. In addition, this paper thoroughly analyzed various methods to assess the performance of biogas in CI dual-fuel engines and investigated dangerous emission pollution.
As environmental awareness grows, consumers' green and low-carbon preferences have become essential factors for market enterprises to consider in decision-making. This paper conducts a literature review of dual-channel supply chain pricing decisions under the influence of consumers' low-carbon preference. The analysis is carried out from two aspects: dual-channel supply chain types and consumers' low-carbon preference. By combining psychological games and analyzing relevant literature, this paper provides insights into the factors that affect consumers' low-carbon preference and explores the synergies among various factors, including government policies. Moreover, this paper suggests future research directions, such as conducting empirical research on relevant models, to support the diversified development of the dual-channel field.
This study applies the FMEA-QFD approach to assess risks in the distribution process, with a focus on warehouse and transport processes, which are commonly associated with user dissatisfaction and customer loss. The methodology identifies the forms, effects, and causes of failures and determines priorities for each category. In that manner, for the warehousing process, long reception time, additional costs, and lack of experience have the highest priority. In the transportation process, time losses, generating additional costs, and longer vehicle retention time are the three failure effects with the highest priorities. Corrective and preventive measures are also defined. The proposed approach is highly applicable in practice and can be modified for use in other industries. This paper contributes both theoretically and practically to the field of logistics.
The concept of “green supply chain” has gained increasing attention in the pursuit of sustainable development by enterprises globally, leading to the optimization of supply chain management. However, the behavior patterns of some members in green supply chains exhibit differences. Hence, analyzing the choices of different behavior patterns among green supply chain members is of practical significance in improving supply chain governance and achieving sustainable development. In this study, a differential game model is constructed using differential game theory to analyze the behavior patterns among members of a green supply chain. Analytical solutions under different models are obtained with the aid of Bellman continuous dynamic programming theory, and comparative analysis and numerical examples are carried out to explore the operation strategies of green supply chain members and the choice of short-sighted and far-sighted behavior patterns. Our findings indicate that suppliers playing a leading role in the green supply chain should exhibit far-sighted behavior as decision makers, while retailers should also display far-sighted behavior. This study adopts a dynamic perspective and is innovative and cutting-edge, providing targeted recommendations for enterprises and serving as a reference for the future development of green supply chain management.
In order to further improve the vibration energy harvesting efficiency of piezoelectric energy harvester under low frequency environmental excitation, this paper, based on the traditional magnetic tri-stable piezoelectric energy collector model, proposes a tri-stable piezoelectric energy harvester (TPEH+DEM) model with two elastic amplifiers which are installed between the U-shaped frame and the base and between the fixed end of the piezoelectric cantilever beam and the U-shaped frame respectively. Based on Hamilton principle, the motion equation of electromechanical coupling of TPEH+DEM system is established, and the analytical solutions of displacement, output voltage and power of the system are obtained by harmonic balance method. The effects of the mass of elastic amplifier, spring stiffness, magnet spacing and load resistance on the dynamic characteristics of energy harvesting of TPEH+DEM system are analyzed. The result shows that there are two peaks in the response output power of TPEH+DEM system in the operating frequency range. By adjusting the mass and stiffness of the elastic amplifier reasonably, the system can move into the inter-well motion under low external excitation intensity, and produce high output power. Compared with the traditional model which only has an elastic amplifier on the base of piezoelectric energy harvester, TPEH+DEM model has better energy harvesting performance under low frequency and low intensity external excitation.
This paper aimed to point out not only the main sources of water pollution in the Drina River basin, but also the inevitability and importance of an integrative transboundary solution to water management issues, thus maintaining good quality surface and underground water in the context of overall environmental protection and health. This paper did qualitative research of existing water protection situation and made a top-bottom analysis, ranging from European to national, regional, and local levels, using geospatial and geosystemic differentiation analysis methods of spatial-temporal contents. It was concluded that bilateral cooperation agreements between countries in the basin should be reached to eliminate the causes of water pollution and possibly restore water quality.
Purpose: To analyze the usefulness or quality of annual reports formulated by the municipalities in the context of decision-making and accountability in the KwaZulu-Natal province in South Africa. Methodology: In this study, we employ a 21-index research tool designed by Beest, Braam, and Boelens (2009). Findings: The results of the study indicate that the quality of the KwaZulu-Natal municipalities' annual reports is quite satisfactory. However, there is scope for enhancement as far as the quality of the annual reports is concerned. Originality/Value: This study contributes to the current body of knowledge and further contributes to the enhancement in the usefulness and quality of financial reporting in public sector and belyond. This study has also provided a very robust plan for future researchers.
Helical microtubes are commonly used in micro-electronic cooling techniques and micro-heat exchangers because of the creation of secondary flows, which leads to greater temperature and velocity gradients. It is of great significance to further improve the overall efficiency of the helical microtubes so as to diminish energy consumption. This experimental work mainly focuses on exergy analysis of air flow through adiabatic helical microtubes with circle, triangle, square, and pentagon geometries with circular cross section. The temperature rises due to viscose dispassion and pressure drops have been measured for all adiabatic helical coils in the laminar flow range. To identify irreversibility of flow, rate of air flow, coil diameter and Dean number are varied to investigate their influences on the entropy generation. Also, the second law of thermodynamics was applied to recognize exergy efficiencies and to determine true magnitudes of exergy losses. Results indicate that entropy generation increases by increasing the flow rate and the coil diameters in all geometries, however, the exergy efficiency decreases. By considering geometry, in constant flow rate and identical coil diameter, the highest entropy generation can be approximately observed in the triangles, squares, pentagons, and circles, respectively. Moreover, the proportions of theoretical exergy losses to actual exergy losses have been computed for all geometries in order to probe the viscous heating effects and it is found that the predicted exergy losses distinguish substantially from measured amounts due to viscose dispassion.
With the help of vector equations and MATLAB software, this paper studied the kinematics and kinetostatics of toggle-type transmission mechanism (hereinafter referred to as “toggle mechanism” for short) and attained the analytical expressions of displacement, speed, and acceleration of slider punch, and the force and moment balance equations of each component in the toggle mechanism with their inertia force taken into consideration. Then, the toggle mechanism was compared with conventional crank-link mechanism and their kinematic characteristics were comparatively analyzed. The proposed kinematics analysis method of toggle mechanism could figure out the kinematic characteristics of the target mechanism and reveal its operating advantages on the basis that its functional requirements are met, in this way, the research purpose of optimizing the design of the mechanism could be realized, and the attained conclusions could provide useful evidence for the design of other types of transmission mechanisms.
Air quality monitoring is fundamental to mitigating the impacts of air pollution on human health and the environment. This ensures that air quality management is effective and that the potential negative effects on the environment and human health associated with poor air quality are understood and mitigated. Despite this, Africa continues to struggle with a lack of sufficient air pollution exposure data that can influence the understanding of air pollution status. The purpose of this research is to look at the progress made by African countries in developing monitoring techniques for pollutants such as particulate matter and nitrogen oxides in urban settings. The study conducted meta-analyses of studies that looked at technological advancements in monitoring PM and NOx exposure levels on the African continent. Every country in the African continent that has monitored both PM and NOx ambient pollutants was included in the review. Furthermore, in an attempt to include the most recent studies that monitored PM and NOx only ambient air quality studies published between 2010 to 2022 were eligible for inclusion in the current study. From eligible studies, authors, publication year, exposure characterization method, study setting, pollutants and technique used were extracted. Microsoft Excel 2019 was used for data analysis. To this end, the data was presented using graphs and numerical techniques. The results of this study show that 67% of African countries use fixed monitoring systems, which has a serious limitation. Whilst, on the other hand only 10% of the countries, geographically located within North Africa (Tunisia, and Algeria), and Southern Africa (South Africa) regions used the mixed monitoring techniques, such as active sampling and remote sensing. In conclusion, most African regions rarely conduct air quality exposure assessments that incorporate air quality modelling techniques.
Linear programming problems (LPP) have been widely used to address real-world problems, including the stock portfolio problem. In this study, an approach is proposed that incorporates Pythagorean fuzzy numbers (PFN) in the rate of risked return, portfolio risk amount, and expected return rate. The problem is transformed into a deterministic form using the scoring function, and a solution algorithm is being developed to provide portfolio investment choices. One of the key features of this study is the investor's ability to choose risk coefficients to increase expected returns and set their circumstances while determining their strategies. The optimum return rate is identified using the TORA program. An example is provided to demonstrate the efficiency and reliability of the method.
For the wounded triage, transport and cooperative scheduling problem of emergency surgery in urban emergency rescue, this study uses the idea of supply chain collaborative scheduling, considers factors such as the number of the wounded, rescue vehicle capacity and hospital operation time to achieve the optimization goals of the shortest rescue response time and the most economical transportation capacity, establishes a mixed integer programming model, and designs a two-stage scheduling algorithm to solve the model. It uses the relative gap between the maximum time span of the entire rescue process and the optimal performance under ideal conditions to measure the performance of the algorithm. The simulation experiments show that the two-stage scheduling algorithm has better problem-solving ability for scenarios with larger number of the wounded and stronger carrying capacity, and has better performance than MFF algorithm and MBF algorithm.
Brain tumors are a critical public health concern, often resulting in limited life expectancy for patients. Accurate diagnosis of brain tumors is crucial to develop effective treatment strategies and improve patients' quality of life. Computer-aided diagnosis (CAD) systems that accurately classify tumor images have been challenging to develop. Deep convolutional neural network (DCNN) models have shown significant potential for tumor detection, and outperform traditional deep neural network models. In this study, a novel framework based on two pre-trained deep convolutional architectures (VGG16 and EfficientNetB0) is proposed for classifying different types of brain tumors, including meningioma, glioma, and pituitary tumors. Features are extracted from MR images using each architecture and merged before feeding them into machine learning algorithms for tumor classification. The proposed approach achieves a training accuracy of 98% and a test accuracy of 99% on the brain-tumor-classification-mri dataset available on Kaggle and btc_navoneel. The model shows promise to improve the accuracy and generalizability of medical image classification for better clinical decision support, ultimately leading to improved patient outcomes.
The activity of the world community in the field of climate and environmental conservation is increasing every year. The Paris Agreement, signed in 2015 by the majority of governments, and the additional goals set on COP26 in 2021 set the objectives of maximum reduction of greenhouse gas emissions into the atmosphere and the transition to renewable energy sources (RES). Consequently, the energy sector, as the largest sector of the world economy and the largest environmental polluter, is undergoing the greatest change. The development and implementation of an effective policy in the field of RES, which is part of the energy development strategy, is one of the factors of renewable energy market’s rapid development and stimulating the transition to clean energy. However, despite the measures taken by the world community to reduce the environmental impact of the energy sector and the development of renewable energy, the volume of greenhouse gas emissions continues to show an upward trend: from 2000 to 2021, the volume of CO2 emissions produced by the power sector increased by 74.7%. This trend might be associated with a low level of elaboration of the current renewable energy policy, with barriers to the development of the renewable energy market or with the specifics of the energy sector. The purpose of this study is to review and analyze renewable energy policies in the European Union, Russia, and the United States in order to identify specific approaches to the development of renewable energy, key tools, and barriers. The current state of the energy sectors of the considered countries was analyzed, their features were identified, and a review as well as a comparative analysis of their renewable energy policies were conducted.
An accurate technique of driving cycle development is important. Such a technique should be dominantly based on real-world driving behavior to ensure it represents the profile of the selected route. A driving cycle often is the combination of analyses of huge numbers of micro-trips under different conditions of traffic. This research is an initiative to improve the accuracy of the method of data collection; this contributes directly to one of the major procedures of driving cycle development, namely data collection. A driving cycle tracking device (DC-TRAD) is a device developed to improve the data collection strategy with integration of Internet-of-Things to manage the huge amount of data collected. A conceptual design of DC-TRAD is developed, and the flexibility of the device is made use in this research to compare and analyze the driving cycle of Kinta district.
Open Access
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