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Fused Filament Fabrication (FFF) is one of the growing technologies in additive manufacturing, that can be used in a number of applications. In this method, process parameters can be customized and their simultaneous variation has conflicting impacts on various properties of printed parts such as dimensional accuracy (DA) and surface finish. These properties could be improved by optimizing the values of these parameters.

In this paper, four process parameters, namely, print speed, build orientation, raster width, and layer height which are referred to as “input variables” were investigated. The conflicting influence of their simultaneous variations on the DA of printed parts was investigated and predicated. To achieve this goal, a hybrid Genetic Algorithm – Artificial Neural Network (GA-ANN) model, was developed in C#.net, and three geometries, namely, U-shape, cube and cylinder were selected. To investigate the DA of printed parts, samples were printed with a central through hole. Design of Experiments (DoE), specifically the Rotational Central Composite Design method was adopted to establish the number of parts to be printed (30 for each selected geometry) and also the value of each input process parameter. The dimensions of printed parts were accurately measured by a shadowgraph and were used as an input data set for the training phase of the developed ANN to predict the behavior of process parameters. Then the predicted values were used as input to the Desirability Function tool which resulted in a mathematical model that optimizes the input process variables for selected geometries. The mean square error of 0.0528 was achieved, which is indicative of the accuracy of the developed model.

The results showed that print speed is the most dominant input variable compared to others, and by increasing its value, considerable variations resulted in DA. The inaccuracy increased, especially with parts of circular cross section. In addition, if there is no need to print parts in vertical position, the build orientation should be set at 0° to achieve the highest DA. Finally, optimized values of raster width and layer height improved the DA especially when the print speed was set at a high value.

By using ANN, it is possible to investigate the impact of simultaneous variations of FFF machines’ input process parameters on the DA of printed parts. By their optimization, parts of highly accurate dimensions could be printed. These findings will be of significant value to those industries that need to produce parts of high DA on FFF machines.

The aim of this paper is to provide a simple yet accurate and efficient geometric method for thermal homogenization of impregnated and non-impregnated coil winding technologies based on the concept of thermal resistance.

For regular windings, the periodic microscopic cell in the winding space is identified. Also, for irregular windings, the average microscopic cell of the winding is determined. An approximation is used to calculate the thermal resistance of the winding cell. Based on this approximation, the winding insulation is considered as a circular ring around the wire. Mathematical equations are obtained to calculate the equivalent thermal resistance of the cell. The equivalent thermal conductivity of the winding is calculated using equivalent thermal resistance of the cell. Winding thermal homogenization is completed by determining the equivalent thermal properties of the cell.

The thermal pattern of different windings is simulated and compared with the results of different homogenization methods. The results show that the proposed method is applicable for a wide range of windings in terms of winding scheme, packing factor and winding insulation. Also, the results show that the proposed method is more accurate than other winding homogenization methods in calculating the equivalent thermal conductivity of the winding.

In this paper, the change of electrical resistance of the winding with temperature and thermal contact between the sub-components are ignored. Also, liquid insulators, such as oils, and rectangular wires were not investigated. Research in these topics is considered as future work.

Unlike other homogenization methods, the proposed method can be applied to non-impregnated and irregular windings. Also, compared to other homogenization methods, the proposed method has a simpler formulation that makes it easier to program and implement. All of these indicate the efficiency of the proposed method in the thermal analysis of the winding.

This paper aims to develop precise statements (standards) to describe the knowledge and skills that should be possessed by Islamic education (IE) teacher candidates who receive their initial preparation in various international higher-education institutions. These statements must be compatible with the requirements and guidelines for building specialized standards set by the Council for Accreditation of Educator Preparation (CAEP), so that they can be used for accreditation and improving quality.

Two panels of IE experts participated in developing and validating the standards, using a combination of Delphi and content validity methods. Alongside this research activity, management activity ensured that the process ran smoothly, as the researcher coordinated panels, allocated resources and tracked progress during standard development.

Twenty-six components divided into five standards were developed into a final list based on the panels.

This study provides standards for the preparation of IE teachers in higher-education institutions that can be applied in different countries and geographical regions. Furthermore, it aims to make the subject of IE more comparable with other academic disciplines, and appropriate for CAEP accreditation.

Material selection, driven by wide and often conflicting objectives, is an important, sometimes difficult problem in material engineering. In this context, multi-criteria decision-making (MCDM) methodologies are effective. An approach of MCDM is needed to cater to criteria of material assortment simultaneously. More firms are now concerned about increasing their productivity using mathematical tools. To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material. In addition, by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the inherent ambiguities of decision-makers in paired evaluations are considered in this research. It goes on to construct a mathematical bi-objective model for determining the best item to purchase.

The entropy perspective is implemented in this paper to evaluate the weight parameters, while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system. The intermediate pipes are used to join the components of the exhaust systems. The materials usually used to manufacture intermediate pipe are SUS 436LM, SUS 430, SUS 304, SUS 436L, SUH 409 L, SUS 441 L and SUS 439L. These seven materials are evaluated based on tensile strength (TS), hardness (H), elongation (E), yield strength (YS) and cost (C). A hybrid methodology combining entropy-based criteria weighting, with the TOPSIS for alternative ranking, is pursued to identify the optimal design material for an engineered application in this paper. This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes. After that, the authors searched for and considered eight materials and evaluated them on the following five criteria: (1) TS, (2) YS, (3) H, (4) E and (5) C. The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes, on their performance and on the cost. In this structure, the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment. This essentially measures the quantity of information each criterion contribution, indicating the relative importance of these criteria better. Subsequently, the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative. The results show that SUS 309, SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.

The material matrix of the decision presented in Table 3 was normalized through Equation 5, as shown in Table 5, and the matrix was multiplied with weighting criteria ß_j. The obtained weighted normalized matrix V_ij is presented in Table 6. However, the ideal, worst and best value was ascertained by employing Equation 7. This study is based on the selection of material for the development of intermediate pipe using MCDM, and it involves four basic stages, i.e. method of translation criteria, screening process, method of ranking and search for methods. The selection was done through the TOPSIS method, and the criteria weight was obtained by the entropy method. The result showed that the top three materials are SUS 309, SUS 432L and SUS 436 LM, respectively. For the future work, it is suggested to select more alternatives and criteria. The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality (ELECTRE), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE).

The results provide important conclusions for material selection in this targeted application, verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

Some studies have been reported in the past on diaphragmatic hernia (DH) surgery techniques using additive manufacturing (AM) technologies, symptoms of a hernia and post-surgery complications. But hitherto little has been reported on bibliographic analysis (BA) for health monitoring of bovine post-DH surgery for long-term management. Based on BA, this study aims to explore the sensor fabrication integrated with innovative AM technologies for health monitoring assistance of bovines post-DH surgery.

A BA based on the data extracted through the Web of Science database was performed using bibliometric tools (R-Studio and Biblioshiny).

After going through the BA and a case study, this review provides information on various 3D-printed meshes used over the sutured site and available Internet of Things-based solutions to prevent the recurrence of DH.

Research gaps exist for 3D-printed conformal sensors for health monitoring of bovine post-DH surgery.

Scientific knowledge is rich with literature on the antecedent role of social capital on resilience. However, empirical evidence has overlooked the role of the individual dimensions of bonding and bridging social capital on its outcomes. This study aims to extend empirical research on the influence of social capital facets of bonding social capital and bridging social capital on financial resilience and more specifically in the aftermath of the COVID-19 pandemic where women SMEs mostly need bonding.

The study uses an explanatory research design to determine the hypothesized effect of social capital on financial resilience. The authors used regression to test the hypothesized relationship using a sample of three hundred and eight four women-owned SMEs in Kampala registered with Kampala City Traders Association.

According to the findings, the social bonding provides female entrepreneurs with emotive encouragement and inspiration through personal connections and responsibility sharing. Furthermore, women entrepreneurs bridging, which consisted of business networks, made it easier for them to identify new financial opportunities, which ultimately led to an increase in their financial resilience. The findings placed an emphasis on the significance of fellow business owners as sources of knowledge and assets that are crucial to maintaining one's financial resilience.

Data were collected from women owned SMEs, and the application of the findings may be limited to women SMEs in Kampala District. Therefore, future research should replicate the current study findings using a sample drawn from other SMEs owned by both male and female from outside Kampala because of changes in operating environment. The study was cross-sectional, and financial resilience of a firm changes was periodical. This study paves the way for future longitudinal research in the same topic area, which will allow for a more complete comprehension of the financial resiliency of SMEs throughout a range of different time periods.

Research findings shape trajectory for current practitioners of SMEs to establish relevant social bonding and bridging as social capital in preparation for financial resilience in case of any pandemic.

To the best of the authors' knowledge, this study is the first to establish the antecedent role of social capital on financial resilience during an economic crisis induced by the COVID-19 pandemic, using a sample of women-owned medium- and small-sized businesses in Kampala.

Learning organization (LO) concept has received much attention in the last decades. The purpose of an LO is to proactively shape its future by fostering a culture of continuous learning among its members. This approach empowers the organization to adapt, evolve and innovate, aligning with the needs and aspirations of both internal and external stakeholders. As a result, the assessment of an organization’s LO level, whether strong or weak, becomes a matter of significance. This study aims to use Senge’s LO Questionnaire (SLOQ) in conjunction with latent profile analysis (LPA) to identify latent classes within the organization. This approach seeks to enhance the organization‘s learning potential and facilitate its evolution.

This research was a cross-sectional study conducted at Hamadan University of Medical Sciences, Iran. The statistical population consisted of 451 managers and employees across seven departments based at the university headquarters. The sample included 295 individuals, and data was collected using the SLOQ.

The LPA has shown an excellent accuracy (97%) in identifying SLOQ cut-off points (three classes of good, moderate and low). Most of the participants are considered as a moderate LO (55.9%), which implies the possibility of improving learning, especially enhancing “common vision” and “systemic thinking.” Also, individuals belonging to the high-class category were more likely to be male and hold associate degree than individuals in other categories.

This study depends on self-report, and different perceptions of questions can cause percept bias. Another limitation is about the nature of this research, which is cross-sectional, which may bring back causality among variables. The other is only three demographic variables have been considered, and it is necessary to pay attention to other influential variables in future studies.

The originality of this study lies in its use of the SLOQ in combination with LPA to identify latent classes in an organization to improve learning potentials.

This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian supply chains (HSCs). It identifies the status of existing research in the field and suggests a roadmap for academicians to undertake further research in HOs and HSCs using MCDM techniques.

The paper systematically reviews the research on MCDM applications in HO and HSC domains from 2011 to 2022, as the field gained traction post-2004 Indian Ocean Tsunami phenomena. In the first step, an exhaustive search for journal articles is conducted using 48 keyword searches. To ensure quality, only those articles published in journals featuring in the first quartile of the Scimago Journal Ranking were selected. A total of 103 peer-reviewed articles were selected for the review and then segregated into different categories for analysis.

The paper highlights insufficient high-quality research in HOs that utilizes MCDM methods. It proposes a roadmap for scholars to enhance the research outcomes by advocating adopting mixed methods. The analysis of various studies revealed a notable absence of contextual reference. A contextual mind map specific to HOs has been developed to assist future research endeavors. This resource can guide researchers in determining the appropriate contextual framework for their studies.

This paper will help practitioners understand the research carried out in the field. The aspiring researchers will identify the gap in the extant research and work on future research directions.

To the best of the authors’ knowledge, this is the first literature review on applying MCDM in HOs and HSCs. It summarises the current status and proposes future research directions.

This study investigates the influence of social media marketing (SMM) functionalities on perceived destination image (DI) and its dimensions, which in turn impact residents’ support for sustainable tourism development (SSTD). The study also examines the moderated mediation effect of the residency length and resident’s income in the indirect relationship between SMM and SSTD through the DI.

The best technique found appropriate for this study was the survey approach. To gather empirical data, people who currently reside in Alexandria completed 351 questionnaires via an online survey. The questionnaire was translated into Arabic while adhering to back-translation guidelines. SPSS and AMOS software were used to analyze the collected data.

It is found that there is a direct effect of SMM and its functionalities on overall DI and its dimensions. In addition, DI mediates the relationship between SMM and SSTD. These results hold valuable insights for academicians and practitioners in the tourism industry, potentially informing SMM strategies to support tourism activities.

This research introduces a novel framework emphasizing the functionalities of the SMM as a tool for enhancing both affective and cognitive DI and supporting sustainable tourism development. It contributes to the SMM and SSTD literature by examining the links between SMM functionalities and sustainable tourism development in emerging countries such as Egypt.