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The purpose of the paper is to investigate photochemical machining characteristics of stainless steel (AISI 304-SS304) parts with a novel design are investigated experimentally from the aspect of process parameters. The effects of phototool pattern geometry, ultraviole (UV) exposure time and etching time on of AISI 304 were evaluated.

The designed semi-automated photochemical manufacturing (PCM) equipment consists of 4 units, which include UV exposure, etching, developing and surface cleaning units. Experimental procedure has been designed via Taguchi method. Results were evaluated via Analysis of Variance (ANOVA) method.

Etching time is the most effective factor in PCM quality of AISI 304 stainless steel. Surface roughness is sensitive to geometrical pattern of the phototool for PCM of AISI 304 UV exposure time is less influential on the PCM quality for stainless steel.

The designed PCM equipment prototype is not fully automated, which requires automation for part replacements into units. The effects of the temperature inside chemical processing units on process characteristics cannot be evaluated due to equipment limitations. The effects of surface cleaning time inside surface cleaning unit are not analyzed.

The utilized PCM equipment is semi-automated equipment, with which the process parameters such as etching time, surface cleaning time, UV exposure time and developing time can be controlled. Different from literature, the effects of phototool pattern geometries on the photochemical machining quality parameters are evaluated for the processing of AISI 304. The effects of processing parameters on dimensional accuracy, which is not common in the literature for AISI 304 stainless steel, are also evaluated.

This paper aims to present the results of energy management and optimization studies in one Turkish textile factory. In a case study of a print and dye factory in Istanbul, the authors identified energy-sensitive processes and proposed energy management applications.

Appropriate energy management methods have been implemented in the factory, and the results were examined in terms of energy efficiency and cost reduction.

By applying the methods for fuel distribution optimization, the authors demonstrated that energy costs could be decreased by approximately.

Energy management is a vital issue for industries particularly in developing countries such as Turkey. Turkey is an energy poor country and imports more than half of its energy to satisfy its increasing domestic demands. An important share of these demands stems from the presence of a strong textile industry that operates throughout the country.

Cancer is the foremost disease that causes death. The objective of hyperthermia in cancer therapy is to raise the temperature of cancerous tissue above a therapeutic value while maintaining the surrounding normal tissue at sublethal temperature values in cases where surgical intervention is dangerous or impossible. The malignant tissue is heated up to 42°C in the treatment. In this method, the unaffected tissues are aimed to have minimum damage, while the affected ones are destroyed. Therefore, it is very important for the optimization of the method to know the temperature profiles in both tissues. Accurately estimating the tissue temperatures has been a very important issue for tumor hyperthermia treatment planning. This paper, proposes to theoretically predict the temperature response of the biological tissues subject to external EM heating by using the space‐dependent blood perfusion term in Pennes bio‐heat equation.

The bio‐heat transfer equation is parabolic partial differential equation. Grid points including independent variables are initially formed in solution of partial differential equation by finite element method. In this study, one dimensional bio‐heat transfer equation is solved by flex‐PDE finite element method.

In this study, the bio‐heat transfer equation is solved for variable blood perfusion values and the temperature field resulting after a hyperthermia treatment is obtained. Homogeneous, non‐homogeneous tissue and constant, variable blood perfusion rates are considered in this study to display the temperature fields in the biological material exposed to externally induced electromagnetic irradiation.

Temperature‐dependent tissue thermophysical properties have been used and the Pennes equation is solved by FEM analysis. Variable blood perfusion and heat generation values have been used in calculations for healthy tissue and tissue with tumor.

This study aims to derive a novel spatial numerical method based on multidimensional local Taylor series representations for solving high-order advection-diffusion (AD) equations.

The parabolic AD equations are reduced to the nonhomogeneous elliptic system of partial differential equations by utilizing the Chebyshev spectral collocation method (ChSCM) in the temporal variable. The implicit-explicit local differential transform method (IELDTM) is constructed over two- and three-dimensional meshes using continuity equations of the neighbor representations with either explicit or implicit forms in related directions. The IELDTM yields an overdetermined or underdetermined system of algebraic equations solved in the least square sense.

The IELDTM has proven to have excellent convergence properties by experimentally illustrating both h-refinement and p-refinement outcomes. A distinctive feature of the IELDTM over the existing numerical techniques is optimizing the local spatial degrees of freedom. It has been proven that the IELDTM provides more accurate results with far fewer degrees of freedom than the finite difference, finite element and spectral methods.

This study shows the derivation, applicability and performance of the IELDTM for solving 2D and 3D advection-diffusion equations. It has been demonstrated that the IELDTM can be a competitive numerical method for addressing high-space dimensional-parabolic partial differential equations (PDEs) arising in various fields of science and engineering. The novel ChSCM-IELDTM hybridization has been proven to have distinct advantages, such as continuous utilization of time integration and optimized formulation of spatial approximations. Furthermore, the novel ChSCM-IELDTM hybridization can be adapted to address various other types of PDEs by modifying the theoretical derivation accordingly.

The purpose of this article is to derive an implicit-explicit local differential transform method (IELDTM) in dealing with the spatial approximation of the stiff advection-diffusion-reaction (ADR) equations.

A direction-free numerical approach based on local Taylor series representations is designed for the ADR equations. The differential equations are directly used for determining the local Taylor coefficients and the required degrees of freedom is minimized. The complete system of algebraic equations is constructed with explicit/implicit continuity relations with respect to direction parameter. Time integration of the ADR equations is continuously utilized with the Chebyshev spectral collocation method.

The IELDTM is proven to be a robust, high order, stability preserved and versatile numerical technique for spatial discretization of the stiff partial differential equations (PDEs). It is here theoretically and numerically shown that the order refinement (p-refinement) procedure of the IELDTM does not affect the degrees of freedom, and thus the IELDTM is an optimum numerical method. A priori error analysis of the proposed algorithm is done, and the order conditions are determined with respect to the direction parameter.

The IELDTM overcomes the known disadvantages of the differential transform-based methods by providing reliable convergence properties. The IELDTM is not only improving the existing Taylor series-based formulations but also provides several advantages over the finite element method (FEM) and finite difference method (FDM). The IELDTM offers better accuracy, even when using far less degrees of freedom, than the FEM and FDM. It is proven that the IELDTM produces solutions for the advection-dominated cases with the optimum degrees of freedom without producing an undesirable oscillation.

The objective of this study is to investigate the role of blockchain in reducing the impact of barriers to humanitarian supply chain management (HSCM) using a list of blockchain benefits.

A decision aid was used to explore the suitability of blockchain in humanitarian supply chains. To achieve that, first, a list of barriers to HSCM was identified. Then, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF–DEMATEL) method was utilized to determine the relationships and the level of interdependencies among the criteria. Finally, the intuitionistic fuzzyanalytic network process (IF–ANP) technique was employed, as it successfully handles dependencies among the criteria.

The findings of this study suggest that interorganizational barriers are the most suitable ones, the impacts of which blockchain may alleviate. This study further suggests that trust turned out to be the most significant benefit criterion for the analysis.

The readers should construe the findings of this study with caution since it was carried out using the data collected from the experts of a particular country. Moreover, the proposed decision aid contemplates a limited set of criteria to assess a possible role of blockchain in overcoming the barriers to HSCM.

The findings of this study can assist humanitarian supply chain managers to make more judicious assessments on whether they implement the blockchain in humanitarian supply chain operations. Specifically, this research may help decision makers to identify the certain barriers, the impact of which may be reduced by using the blockchain. The findings of this research will also help various decision makers make more rational decisions and allocate their resources more effectively.

To the best of authors’ knowledge, no single study exists to investigate the role of blockchain in reducing the impact of barriers to HSCM using an intuitionistic fuzzy multi-criteria decision-making approach.

The objective of this study is to assess quantitatively how feasible blockchain is for various industries, such as logistics and supply chain, health, energy, finance, automotive, pharmaceutical and agriculture and food using a comprehensive list of indicators.

A decision aid was applied to the problem of identifying the feasibility of blockchain in Turkish industries. To this end, first, a set of indicators was identified. Then, the fuzzy AHP and fuzzy TOPSIS were utilized to assess the feasibility comparatively using the data gathered from a group of experts. Finally, a scenario analysis was conducted to ensure the consistency of our evaluation.

The findings of this study suggest that comparatively, logistics and supply chain, finance and health industries are the most feasible industries for blockchain. This study further suggests that blockchain is the least feasible for the automotive industry compared to the rest of the identified industries.

It is cumbersome to find out the respondents who have sufficient knowledge of both blockchain and the identified industries. Even if we took the utmost care in identifying the right respondents, we limited our search to the biggest industrial hubs of Turkey.

The findings of this research may help various decision-makers employed in governments, conglomerates, software and consulting firms and national research institutions make more informed decisions and allocate their resources more effectively.

To this date, the current studies have solely investigated possible research opportunities in blockchain and demonstrated several blockchain applications in stand-alone cases. To the best of our knowledge, however, no single study exists that evaluates the feasibility of blockchain comparatively and holistically among a group of industries using various indicators.

Workplace flourishing and withdrawal behavior are important concepts for human resource practitioners in today’s multicultural and multilingual work atmosphere. Despite the prevalence of linguistic ostracism, only a handful of studies have considered its impact on workplace flourishing and withdrawal behavior. This paper embarks on unveiling the nature of these associations.

A sample of n = 395 employee responses was obtained from Jordanian tourism and hospitality organizations. The data were analyzed with the variance-based structural equation modeling (VB-SEM) technique using ADANCO software.

VB-SEM results indicate that linguistic ostracism reduces workplace flourishing and indirectly increases withdrawal behavior through the mediating role of workplace flourishing. Decreased feelings of workplace flourishing resulted in increased withdrawal behavior.

This paper is among the first to empirically examine the association between linguistic ostracism, workplace flourishing and withdrawal behavior and the mediating role of workplace flourishing using ethnolinguistic identity and stressor–emotion theories as a theoretical framework. Implications for practice and theory are discussed alongside future research directions.