The interrelation between logistics and international trade is crucial for understanding a country's ability to increase its share in global trade. An adequate and well-integrated logistics sector and infrastructure are required for this purpose. This study employs the novel Multi-Criteria Decision Analysis (MCDA) approach known as REF-III and two distinct models to investigate the activities of countries in terms of infrastructure, logistics, international trade, and economic growth. The results from both models indicate that China and Russia are leading the rankings. However, when focusing on the efficiency of trade and economic growth, the United States occupies the first place. Notably, several Caucasian and Balkan countries rank poorly in both models, possibly due to the multiple crises, wars, and turmoil they have experienced over the past forty years. The investments and improvements made in infrastructure and logistics by the countries excelling in global trade and logistics should serve as a model for other nations to emulate.
This paper aimed to analyze the properties of rubber agglomerate panel, a heterogeneous material. After making three adjustments using three classical differential fractional models, namely, the Scott-Blair model, the generalized fractional Maxwell model (FMM), and the 1D standard fractional viscoelastic order for fluids (SFVOF), this paper assessed the number of parameters in those models for rubber agglomerate panel, made from rubber grains and urea thermoplastic elastomer (TPE). Combining data published from an undergraduate thesis with Microsoft Excel software and the solver command, this paper obtained better sample results using four parameters, rather than two or three complicated material function equations. Data of Ribeiro Alves in 2019 came from hardness experiments. Then this paper transformed deformation data into creep compliance in accordance with equation $J(t)=\varepsilon / t$ (mm/s), and obtained graphical adjustment representations, parameter values, and eventually adjustment equations. However, results from the modified FMM and 1D SFVOF were more comparable, and certain hypotheses were investigated to choose the better model. It was determined that the generalized FMM fit the data the best for this time period. With a certain margin of error, this model could be used for constructing new recycled materials and rubber agglomerate panel using Salvadori equipment. However, it is suggested that new and recent materials should be tested in order to solve environmental problems.
Purpose of this research is to identify the nature of loyalty, the valence/dimensionality of this concept, and the factors that determine customers of banking products/services in the Republic of Moldova to establish long-term relationships with the bank and remain loyal to it, thereby proposing targeted measures the banks could take to keep their customers. Online survey data of 363 customers of financial-banking products/services in the country was extracted, counted, and analyzed, and the statistical results reveal that loyalty to a banking service is similar to that in interpersonal relationships, and bank-client relationships can generate friendships or even lasting partnerships over time due to proper behavior. Based on analysis results, this paper identifies manifestations of loyalty, figures out factors for developing loyalty and trusting relationships and for improving customer attitude, and innovatively proposes a few suggestions for financial institutions to formulate customer loyalty problems and develop long-term relationships with their customers, including measuring customer loyalty level to identify genuinely loyal customers, ensuring the bank’s efforts to build customer loyalty is recognized in the entire institution, relating the value of each customer to the value of rewards provided in the loyalty program, and rewarding customer loyalty according to customer priorities. Research results attained in the paper could assist bank managers in the Republic of Moldova in making managerial decisions to prevent customers from migrating to competitors and establish long-term relationships with them, and the conclusions and suggestions might be applicable to banks in other counties with similar problems around the globe.
This study aims to assess the safety level of the Automatic Dependent Surveillance-Broadcast (ADS-B) signal quality during airplane departures at Sultan Mahmud Badaruddin II Airport. The Aero-track application was utilized to monitor commercial aircraft departures and collect observation data. The collected data underwent processing using data analysis algorithms and labeling processes, resulting in a comprehensive dataset for evaluating ADS-B signal quality. Signal quality was categorized into four levels, and a model was built using the Random Forest algorithm, achieving an accuracy of 99%. Comparative analysis with SVM and Naive Bayes algorithms showed accuracy values of 93% and 97% respectively. Consequently, the Random Forest Model was chosen for estimating ADS-B signal quality during commercial aircraft takeoff and landing.
Cervical cancer is the second most common cancer among women globally. Colposcopy plays a vital role in assessing cervical intraepithelial neoplasia (CIN) and screening for cervical cancer. However, existing colposcopy methods mainly rely on physician experience, leading to misdiagnosis and limited medical resources. This study proposes a cervical lesion recognition method based on ShuffleNetV2-CA. A dataset of 6,996 cervical images was created from Hebei University Affiliated Hospital, including normal, cervical cancer, low-grade squamous intraepithelial lesions (LSIL, CIN 1), high-grade squamous intraepithelial lesions (HSIL, CIN 2/CIN 3), and cervical tumor data. Images were preprocessed using data augmentation, and the dataset was divided into training and validation sets at a 9:1 ratio during the training phase. This study introduces a coordinate attention mechanism (CA) to the original ShuffleNetV2 model, enabling the model to focus on larger areas during the image feature extraction process. Experimental results show that compared to other classic networks, the ShuffleNetV2-CA network achieves higher recognition accuracy with smaller model parameters and computation, making it suitable for resource-limited embedded devices such as mobile terminals and offering high clinical applicability.
The purpose of this study was to devise a more efficient system for data storage and exchange in the Computer System and Network (CSN) Laboratory at Ibn Khaldun Bogor University. Open Media Vault (OMV) software and Raspberry Pi 3B+ were employed to establish a Network Attached Storage (NAS) system. The performance and file transfer speeds of the Raspberry Pi were evaluated in the context of this implementation. The implementation of the NAS system was intended to offer students of the CSN laboratory swifter and more efficient access to data, thereby reducing dependence on USB media. The findings of this study could hold substantial implications for enhancing the efficiency and effectiveness of data storage and exchange in educational environments.
In Tanzania, seed infection by bacterial leaf spot (BLS) pathogen (Xanthomonas perforans) causes yield losses up to 45% in tomato (Lycopersicon esculentum L.; Solanaceae family). Several studies have been conducted and wedged ecological organic agriculture (EOA) technologies (i.e., on botanicals/ biopesticides) which are significant to organic farmers in Tanzania. Nevertheless, these studies have been conducted in laboratory and greenhouse conditions, hence the technology cannot be disseminated to organic farmers for application before being validated. The current study was laid out as a 2x3 factorial experiment with five replications. Factor A was two common tomato cultivars “Rio grande” and “Malkia F1”, while factor B was seed treatment with three levels of crude plant extracts namely A. vera, C. arabica, and A. vera + C. arabica and untreated/control. To make the individual crude extracts, the roasted C. arabica beans powder (5g) and A. vera juice (5 ml) were mixed into 50 ml of clean water to get 10% weight/volume (w/v), respectively, while A. vera + C. arabica combination was obtain at a volume (ml) ratio (1:1). Tomato seeds were then soaked in 1 ml of the 10% w/v plant extracts for 12 hours, then air-dried for 1 hour before sowing. The highest efficacy against Xanthomonas perforans was obtained from a combination of extracts from A. vera + C. arabica at volume (ml) ratio (1:1) hence, recommended for seed treatment. Organic tomato farmers need to adopt seed treatment practices that ensure seedlings’ start-up and enhance crop growth and productivity. Although the results of validation comply with the recommendations from previous research findings, further study is needed to evaluate the effectiveness of plant extracts subject to seasonal variability among the production areas.
This study aimed to investigate the impact of using ChatGPT as an auxiliary learning tool on university students' learning motivation. Structural equation modeling and regression analysis were employed as the data analysis methods. Questionnaire surveys were conducted to collect data on 196 university students. The results indicated that after using ChatGPT, a negative correlation was found between tension-pressure and interest-enjoyment. Perceived competence was significantly positively correlated with interest-enjoyment, while the correlation between perceived value and interest-enjoyment was insignificant. These three variables were found to have varying degrees of influence on interest-enjoyment in the regression analysis. The study concluded that ChatGPT had a certain impact on learning motivation, but university students' frequency of use and proficiency was relatively low, requiring further training. The significance of this study lies in providing a new pedagogical approach that enables students to keep up with contemporary trends. The findings of this study have substantial theoretical and practical implications, offering novel perspectives and avenues for research on university students' learning motivation and contributing to educational reforms by providing valuable insights and directions.
Thermal Energy Storage (TES) system has emerged as a promising solution of energy demand and supply management, which stores excess thermal energy and releases it when energy demand is high, making it an efficient and cost-effective energy storage solution when combined with renewable energy sources, such as solar and wind power. This study aimed to evaluate the thermal performance of TES units using Computational Fluid Dynamics (CFD) simulations in the ANSYS CFX software package. After comparing the heat storage capacity of conventional Phase Change Material (PCM) and iron oxide/paraffin wax composite (2%) using industrial residual water, temperature distribution plots and heat flux data were generated in simulations for both cases. Addition of iron oxide nanoparticles significantly improved the heat absorption performance of TES units. Both materials initially exhibited a higher heat absorption rate, which gradually decreased over time. CFD data analysis revealed that iron oxide/paraffin wax material enhanced heat absorption performance by up to 1.3%, which demonstrated the potential of iron oxide nanoparticles in improving the efficiency of TES system and highlighted the advantages of TES system combined with renewable energy sources. By improving heat absorption properties, the incorporation of iron oxide nanoparticles had the potential to increase the lifespan of TES units and significantly reduced maintenance and replacement expenses. This breakthrough, along with the cost savings and energy efficiency offered by TES technology, may encourage its widespread application, thus reducing reliance on fossil fuels and promoting sustainable energy practices.
Recent transmission of large volumes of data through mobile ad hoc networks (MANETs) has resulted in degraded Quality of Service (QoS) due to factors such as packet loss, delay, and packet drop in multipath routing. To address this issue, a traffic-aware Enhanced QoS-Aware Multipath Routing Protocol (EQMRP) has been proposed for real-time IoT applications in MANETs. EQMRP efficiently switches between multiple paths and monitors traffic conditions to maintain an optimal data transmission rate. The proposed method considers different delay sensitivity levels and link expiration time (LTE) to maintain QoS in each path. Through IoT application data analysis, EQMRP maintains QoS in each path more efficiently than conventional methods. The proposed method has been simulated and validated using MATLAB, and the performance analysis shows that EQMRP achieves a higher packet delivery ratio, lower delay, and reduced packet drop compared to conventional methods. In conclusion, the traffic-aware EQMRP protocol offers a significant improvement in QoS for real-time IoT applications in MANETs.
This paper presents a strategy implemented for preparation of the national User Requirements Specifications (URS) for European Train Control System (ETCS) with Level 2 in the Republic of Serbia. The requirements were the result of several parallel activities: gaining experience from similar implementations of the ETCS in the framework of the European TEN-T corridor railway lines, consultations about the specific technical solutions with the institutions and several suppliers of signalling equipment. The process resulted with a comprehensive specification, which will be used as a firm basis for further implementation of the ETCS system on Serbian railway network.
Purpose: this study aimed at measuring the sustainable consumption behaviors of generations X, Y and Z using various descriptive variables. Methodology: the convenience sampling method was used for the data of this cross-sectional study collected during March 15-20, 2023, which obtained 244 usable survey data. The data were analyzed using the Statistical Package for the Social Sciences (SPSS) 26. Descriptive statistics and parametric tests were used in the study, such as t, Analysis of Variance (ANOVA) and Pearson correlation analysis. Results: the participants exhibited sustainable consumption behaviors at a moderate level (3.03). Positive and significant relationships (p<0.05) existed between the Sustainable Consumption Behavior Scale and its “environmental sensitivity” (r: 0.789), “saving” (r: 0.725), and "reusability” (r: 0.616) sub-dimensions. There was no statistically significant difference in the sustainable consumption behavior levels of the participants in terms of the variables, such as gender, educational level, income level and family type (p>0.05). However, statistically significant difference existed in the sustainable consumption behavior levels of the participants in terms of the variables, such as marital status, place of residence and generation (p<0.05). Conclusions: married participants living in the city in generation Y exhibited significantly more sustainable consumption behaviors than others. Implications: the study results revealed that the participants did not have sufficient environmental awareness. In this age of continuous consumption, it is of great importance to make necessary efforts on the issue. Within this context, environmental communities and educational institutions should provide more seminars and trainings on this issue.
This paper aimed to explore the current research trends in circular innovation (CI) through scientometric analysis of data, acquired from the Web of Science (WoS) database, using the VOSviewer program. By applying some filters to draw boundaries, this paper found 917 journal articles related to CI in the Social Sciences Citation Index. Tables and maps were used to visualize and illustrate the keywords occurrence, leading journals, authors, and countries that made the greatest contribution to the research field. As the first scientometric analysis of CI research, this paper provided an up-to-date and inclusive big picture of related literature, indicating its unique and primary value. In addition, this paper understood and visualized research patterns and trends and identified main topics, countries and journals, which added value to the innovation and sustainability literature. The research results showed that the number of citations and publications about CI increased rapidly after 2010, and the most prominent issues related to CI were circular economy (CE), circular business models, sustainability, and sustainable development. Finally, the paper presented future research directions of CI linked to business management.
Open Access
