Search results

This paper follows a systematic literature review (SLR) method covering the published studies until March 2021. The authors have extracted the related studies from different online databases utilizing quality-assessment-criteria. In order to review high-quality studies, 32 papers have been chosen through the paper selection process. The selected papers have been categorized into three main groups, decision-making methods (17 papers), meta-heuristic methods (8 papers) and fuzzy-based methods (7 papers). The existing methods in each group have been examined based on important qualitative parameters, namely, time, cost, scalability, efficiency, availability and reliability.

Cloud computing is known as one of the superior technologies to perform large-scale and complex computing. With the growing tendency of network service users to utilize cloud computing, web service providers are encouraged to provide services with various functional and non-functional features and supply them in a service pool. In this regard, choosing the most appropriate services to fulfill users' requirements becomes a challenging problem. Since the problem of service selection in a cloud environment is known as a nondeterministic polynomial time (NP)-hard problem, many efforts have been made in recent years. Therefore, this paper aims to study and assess the existing service selection approaches in cloud computing.

The obtained results indicate that in decision-making methods, the assignment of proper weights to the criteria has a high impact on service ranking accuracy. Also, since service selection in cloud computing is known as an NP-hard problem, utilizing meta-heuristic algorithms to solve this problem offers interesting advantages compared to other approaches in discovering better solutions with less computational effort and moving quickly toward very good solutions. On the other hand, since fuzzy-based service selection approaches offer search results visually and cover quality of service (QoS) requirements of users, this kind of method is able to facilitate enhanced user experience.

Although the current paper aimed to provide a comprehensive study, there were some limitations. Since the authors have applied some filters to select the studies, some effective works may have been ignored. Generally, this paper has focused on journal papers and some effective works published in conferences. Moreover, the works published in non-English formats have been excluded. To discover relevant studies, the authors have chosen Google Scholar as a popular electronic database. Although Google Scholar can offer the most valid approaches, some suitable papers may not be observed during the process of article selection.

The outcome of the current paper will be useful and valuable for scholars, and it can be a roadmap to help future researchers enrich and improve their innovations. By assessing the recent efforts in service selection in cloud computing and offering an up-to-date comparison of the discussed works, this paper can be a solid foundation for understanding the different aspects of service selection.

Although service selection approaches have essential impacts on cloud computing, there is still a lack of a detailed and comprehensive study about reviewing and assessing existing mechanisms in this field. Therefore, the current paper adopts a systematic method to cover this gap. The obtained results in this paper can help the researchers interested in the field of service selection. Generally, the authors have aimed to specify existing challenges, characterize the efficient efforts and suggest some directions for upcoming studies.

The lattice Boltzmann method is used to simulate the nanofluid flow and heat transfer inside a finned multi-pipe heat exchanger.

The heat exchanger is filled with CuO-water nanofluid. The Koo–Kleinstreuer–Li (KKL) model is used to estimate the dynamic viscosity and considering the Brownian motion in the simulation. On the other hand, the influence of nanoparticles’ shapes on the heat transfer rate is considered, and the best efficient shape is selected to be used in the investigation.

The Rayleigh number, nanoparticle concentration and the thermal arrangements of internal active fins and bodies are the governing parameters. In addition, the impacts of these two parameters on the nanofluid flow, heat transfer rate, local and total entropy generation and heatline visualization are analyzed, comprehensively.

The originality of this work is using of lattice Boltzmann method for simulation of nanofluid flow and heat transfer during natural convection in a heat exchanger. Furthermore, influence of the shape of nanoparticles on the thermo-physical properties of nanofluid is analyzed using Koo–Kleinstreuer–Li correlation.

Given the growing popularity of virtual human resources development (VHRD) in organizations and among human resource development (HRD) professionals, it is highly essential to deeply examine the nature and scope of the affective dimensions of the VHRD approach. Over the past decade, VHRD has become an important part of the HRD process.

The present study used an integrative literature review to investigate the nature of VHRD in the literature, present a descriptive analysis of the literature and categorize the existing VHRD research.

The results indicated three major themes, namely, VHRD and socialization, VHRD and learning and VHRD and the psychological characteristics of the work environment. In addition, a new conceptual model was developed based on the findings.

This study has reviewed the main concepts of VHRD. The potential actions which HRD researchers can take to address the identified challenges are discussed.

This integrative literature review could provide a roadmap for future research. Based on this model, the VHRD position is within the organizational context and different tools and processes in constant interaction are introduced. Finally, a general view of the VHRD approach was provided, which can help human resources experts deal with a wide range of technologies in the organization.

The effectiveness of non-governmental organization (NGO) participation in the healthcare sector has been demonstrated globally. The purpose of this paper is to investigate the status of Iranian NGOs’ contribution to health policy-making, the barriers to and strategies for developing their contribution.

In this qualitative study, 25 participants were recruited from health-related NGOs in Tabriz, Iran. Semi-structured, in-depth qualitative interviews were conducted. Furthermore, a set of relevant documents were collected and their contents evaluated. The text of documents and interviews were analyzed using a thematic (deductive–inductive) approach using NVivo software.

Most NGO activity has been in the area of providing services, whereas the least amount of activity has been in the domain of policy-making. Factors that were influential for NGO participation in policy-making were divided into three categories: those related to government, to civil society and within NGOs themselves. The primary barriers to participation in policy-making were related to government and the way that NGOs operated. Recommendations include the production of supportive law, financial aid to NGO and infrastructure that facilitates NGO participation.

Financial support from the government and legislation of supportive laws could help to realize the potential of NGOs.

No such research has been undertaken before to evaluate what activities health-related NGOs undertake, their contribution in health policy-making and obstacles and facilitators of this contribution. NGOs can play a key role in ensuring accountability, transparency and empower citizens to demand basic health services from government.

In stereolithography (SL), the total exposure absorbed by photopolymer is variable and is a function of height. This phenomenon causes heterogeneous properties and develops residual stresses during process. Consequently, a pronounced deformation occurs especially when small and more intricate objects are fabricated. The purpose of this paper is to predict this deformation when miniature and complicated parts are fabricated.

In this paper classical lamination theory is employed to model mechanical properties of layers, layers shrinkage and residual stress growth during SL process. Distortion is predicted based on the developed model.

Results show that final distortion is proportional to part thickness and it increases exponentially as parts thickness or layers thickness decrease.

To verify the results, several test pieces were built with SLA 5000 machine and SOMOS 11120 resins. Their distortions were measured with video measuring machine (VMM‐3020D machine). The estimation agrees very well with the experimental results (less than 10 per cent error).

The paper considers the heterogeneous properties of SL parts during fabrication process; an item which was ignored in previous researches. This theoretical and experimental study provides useful information about estimation of deformation of SL parts after building. This information helps the SL machine user to select the best parameters when fabricating miniature and intricate features, especially for biomechanics parts.

Logistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in order to respond to customers' needs effectively and efficiently. The main concern for logistics is to ensure that the correct product is placed at the right time. This paper introduces a linear model of shipping focused on decision-making, which includes configuration of shipping network, choosing of transport means and transfer of individual customer shipments through a particular transport system.

In this study, authors try to address the problem of supply chain network (SCN) where the primary goal is to determine the appropriate order allocation of products from different sources to different destinations. They also seek to minimize total transportation cost and inventory cost by simultaneously determining optimal locations, flows and shipment composition. The formulated problem of getting optimal allocation turns out to be a problem of multi-objective programming, and it is solved by using the max-addition fuzzy goal programming approach, for obtaining optimal order allocation of products. Furthermore, the problem demand and supply parameters have been considered random in nature, and the maximum likelihood estimation approach has been used to assess the unknown probabilistic distribution parameters with a specified probability level (SPL).

A case study has also been applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. Results of this study are very relevant for the manufacturing sector in particular, for those facing logistics issues in SCN. It enables researchers and managers to cope with various types of uncertainty and logistics risks associated with SCN.

The principal contribution of the proposed model is the improved modelling of transportation and inventory, which are affected by different characteristics of SCN. To demonstrate computational information of the suggested methods and proposed model, a case illustration of SCN is provided. Also, environmentalism is increasingly becoming a significant global concern. Hence, the concept proposed could be extended to include environmental aspects as an objective function or constraint.

Efficient integration of logistical cost components, such as transportation costs, inventory costs, with mathematical programming models is an important open issue in logistics optimization. This study expands conventional facility location models to incorporate a range of logistic system elements such as transportation cost and different types of inventory cost, in a multi-product, multi-site network. The research is original and is focused on case studies of real life.

The purpose of this paper is to study thermal performance of metal foam/phase change materials composite under the influence of the enclosure aspect ratios (ratio of enclosure height: length). In this study, a compound metal foam/phase change material (PCM), which has been proved to be one of the most promising approaches for thermal conductivity promotion on PCMs, was used.

The PCM is considered initially at its melting temperature. The enclosure for all the cases has a constant volume with various aspect ratios. The left side of the enclosure is suddenly exposed to a thermal source having a constant heat flux, while the other three surfaces are kept thermally insulated. A two-dimensional numerical model considering the non-equilibrium thermal factor, non-Darcy effect and local natural convection was proposed. The coupling between velocity and pressure is solved using the SIMPLEC, and the Rhie and Chow interpolation is used to avoid the checker-board solutions for the pressure.

The effects of foam porosity and aspect ratio of the enclosure on the PCM’s melting time were investigated. The results indicated that enclosure aspect ratio plays a fundamental role in phase change of copper foam/PCM composites. For higher porosities, enclosures with bigger aspect ratios proved to led to optimal melting time. Besides, the best enclosure aspect ratio and foam porosity for a fixed-volume enclosure to have the shortest melting time are 2.1 and 91.66 per cent, respectively. However, for a specific amount of PCM inside a variable volume enclosure, the optimal melting time was for foam with ε = 95 per cent. The achieved results prove the great importance of selection of aspect ratio to benefit both conduction and convection heat transfer simultaneously.

The area of energy storage systems is original.

The purpose of this paper is to examine the influence of socio-psychological factors from different theoretical perspectives, as well as the roles of technological and cultural facilitators on knowledge sharing (KS) behaviors and whether it leads to superior employees’ innovative work behaviors.

Partial least squares analysis was used to investigate the research model based on a survey of 257 employees from 22 high-tech companies (including companies in pharmaceutical, nano technological, biotechnological, aviation, and aerospace industries) in Iran.

The results supported the effects of three motivational factors, i.e. perceived loss of knowledge power, perceived reputation enhancement, and perceived enjoyment in helping others, and two social capital factors, i.e. social interaction ties and trust, on employees’ attitude toward KS. Findings also indicated that employees’ KS behaviors enhance their innovative work behaviors.

Since the survey used cross-sectional data and samples here were limited to some Iranian companies, the results of this study may prove not to be generalizable and should be confirmed using larger samples and/or longitudinal studies.

The findings provide useful insights into how managers should encourage employees’ KS attitudes, intentions, and behaviors to foster innovative work behaviors of employees.

This study is one of the first attempts to fill the void in integrative research for examining relationships among KS determinants, behaviors, and outcomes.