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The high demand for fast, energy-efficient, compact computational blocks in digital electronics has led the researchers to use approximate computing in applications where inaccuracy of outputs is tolerable. The purpose of this paper is to present two ultra-high-speed current-mode approximate full adders (FA) by using carbon nanotube field-effect transistors.

Instead of using threshold detectors, which are common elements in current-mode logic, diodes are used to stabilize voltage. Zener diodes and ultra-low-power diodes are used within the first and second proposed designs, respectively. This innovation eliminates threshold detectors from critical path and makes it shorter. Then, the new adders are employed in the image processing application of Laplace filter, which detects edges in an image.

Simulation results demonstrate very high-speed operation for the first and second proposed designs, which are, respectively, 44.7 per cent and 21.6 per cent faster than the next high-speed adder cell. In addition, they make a reasonable compromise between power-delay product (PDP) and other important evaluating factors in the context of approximate computing. They have very few transistors and very low total error distance. In addition, they do not propagate error to higher bit positions by generating output carry correctly. According to the investigations, up to four inexact FA can be used in the Laplace filter computations without a significant image quality loss. The employment of the first and second proposed designs results in 42.4 per cent and 32.2 per cent PDP reduction compared to when no approximate FA are used in an 8-bit ripple adder.

Two new current-mode inexact FA are presented. They use diodes as voltage regulators to design current-mode approximate full-adders with very short critical path for the first time.

Many people have been dying as a result of medical errors. Offering clinical learning can lead to better medical care. Clinics have conventionally incorporated direct modality to teach personnel. However, they are now starting to take electronic learning (e-learning) mechanisms to facilitate training at work or other suitable places. The objective of this study is to identify and prioritize the medical learning system in developing countries. Therefore, this paper aims at describing a line of research for developing medical learning systems.

Nowadays, organizations face fast markets' changing, competition strategies, technological innovations and accessibility of medical information. However, the developing world faces a series of health crises that threaten millions of people's lives. Lack of infrastructure and trained, experienced staff are considered essential barriers to scaling up treatment for these diseases. Promoting medical learning systems in developing countries can meet these challenges. This study identifies multiple factors that influence the success of e-learning systems from the literature. The authors have presented a systematic literature review (SLR) up to 2019 on medical learning systems in developing countries. The authors have identified 109 articles and finally selected 17 of them via article choosing procedures.

The paper has shown that e-learning systems offer significant advantages for the medical sector of developing countries. The authors have found that executive, administrative and technological parameters have substantial effects on implementing e-learning in the medical field. Learning management systems offer a virtual method of augmented and quicker interactions between the learners and teachers and fast efficient instructive procedures, using computer and Internet technologies in learning procedures and presenting several teaching-learning devices.

The authors have limited the search to Scopus, Google Scholar, Emerald, Science Direct, IEEE, PLoS, BMC and ABI/Inform. Many academic journals probably provide a good picture of the related articles, too. This study has only reviewed the articles extracted based on some keywords such as “medical learning systems,” “medical learning environment” and “developing countries.” Medical learning systems might not have been published with those specific keywords. Also, there is a requirement for more research with the use of other methodologies. Lastly, non-English publications have been removed. There could be more potential related papers published in languages other than English.

This paper helps physicians and scholars better understand the clinical learning systems in developing countries. Also, the outcomes can aid hospital managers to speed up the implementation of e-learning mechanisms. This research might also enable the authors to have a role in the body of knowledge and experience, so weakening the picture of the developing country's begging bowl is constantly requesting help. The authors hoped that their recommendations aid clinical educators, particularly in developing countries, adopt the trends in clinical education in a changing world.

This paper is of the pioneers systematically reviewing the adoption of medical learning, specifically in developing countries.

Nowadays, communications, products, services and costs are customized through the internet technology. The main theory to continue competitiveness in the organizations is customer relationship management (CRM). CRM enables organizations to efficiently interact with customers and gather, store and examine their data for providing a complete view of them. On the other hand, the subject of cloud computing has increasingly become the bridge for the success of the CRM implementation. Therefore, this study aims to investigate the impact of cloud computing (new cloud facility, knowledge of information technology (IT), cloud security and cost) on the success of CRM systems.

The model and the questioners-based data are analyzed using the Smart PLS 3.0. The data were gathered based on 80 employees of three main agricultural companies in Iran.

The obtained results have indicated that all of the considered factors, new cloud facilities, knowledge of IT, cloud security and cost, play an important role in CRM systems’ success. Also, the evaluation and examination of the consistency and validity of the model are performed through the structural equation model.

First, the authors have conducted a study in a single region. It cannot be guaranteed that the results can be generalized to other regions. Second, for this cross-sectional study, the research design was conducted that showed constant relationships between variables. The research done for this study is cross-sectional. Third, because of time and financial restrictions, the authors have gathered data using a sample from a single location.

Proposing a new model for investigating of the impact of cloud computing (new cloud facility, knowledge of Information Technology (IT), cloud security and cost) on the success of CRM systems is the main originality of this paper.

The purpose of this paper is to develop a slack-based measure (SBM) model in the presence of dual-role factor. Then it is applied in supplier selection problem.

The developed model in this paper is based on data envelopment analysis (DEA) technique.

The proposed evaluation platform is capable of identifying ill-performing suppliers which seek to future improvement. The findings provide valuable insights for practitioners, as well as academicians, policy makers and also integrate selection criteria under the supply chain.

This is the first time that a non-radial DEA model considers dual-role factors. The proposed model does not deal with dual-role factor as a non-discretionary factor. The proposed model considers dual-role factors on both the input and output sides in a similar manner. The proposed model can fully measure the inefficiency of suppliers. The proposed model can give a complete ranking of suppliers.

This paper aims to propose a new method for evaluating the success of the recommender systems based on customer history, product classification and prices criteria in the electronic commerce. To evaluate the validity of the model, the structural equation modeling technique is employed.

A method has been suggested to evaluate the impact of customer history, product classification and prices on the success of the recommender systems in electronic commerce. After that, the authors investigated the relationship between these factors. To achieve this goal, the structural equation modeling technique was used for statistical conclusion validity. The results of gathered data from employees of a company in Iran is indicated the impact of the customer history on the success of recommender systems in e-commerce which is related with the user profile, expert opinion, neighbors, loyalty and clickstream. These factors positively influence the success of recommender systems in ecommerce.

The obtained results demonstrated the efficiency and effectiveness of the proposed model in term of the success of the recommender systems in the electronic commerce.

In this paper, the effective factors of success of recommender systems in electronic commerce are pointed out and the approach to increase the efficiency of this system is applied into a practical example.

The paper analyzes the relative performance of provincial gas distribution companies with different types of inputs and outputs. A data envelopment analysis (DEA)-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables.

A DEA-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables.

It has been shown that using this single equilibrium efficient frontier, a trade-off is made between efficient and inefficient companies so as to make all companies as efficient.

The study analyzes the relative performance of provincial gas distribution companies with different types of inputs and outputs. A DEA-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables. It has been shown that using this single equilibrium efficient frontier, a trade-off is made between efficient and inefficient companies so as to make all companies as efficient.

The purpose of this paper is to develop a systematic approach to predict service quality dimension’s influence on service quality using a novel analysis based on data envelopment and SERVQUAL.

To assess hospital service quality in Tehran, expectation and perception of those who received the services were evaluated using SERVQUAL. The hospital service quality dimensions were found by exploratory factor analysis (EFA). To compare customer expectation and perception, perceived service quality index (PSQI) was measured using a new method based on common weights. A novel sensitivity approach was used to test the service quality factor’s impact on the PSQI.

A new service quality dimension named “trust in services” was found using EFA, which is not an original SERVQUAL factor. The approach was applied to assess the hospital’s service quality. Since the PSQI value was 0.76 it showed that improvements are needed to meet customer expectations. The results showed the factor order that affect PSQI. “Trust in services” has the strongest influence on PSQI followed by “tangibles,” “assurance,” “empathy,” and “responsiveness,” respectively.

This work gives managers insight into service quality by following a systematic method; i.e., measuring perceived service quality from the customer viewpoint and service factors’ impact on customer perception.

The procedure helps managers to select the required service quality dimensions which need improvement and predict their effects on customer perception.

This paper addresses special reliability-centered maintenance (RCM) strategies for one-shot devices by providing fuzzy inferences system with the assumption that, to data, there is no data available on their maintenance. As far as one-shot devices are concerned, the relevant data is inadequate.

In this paper, a fuzzy expert system is proposed to effectively select RCM strategies for one-shot devices. In this research: (1) a human expert team is provided, (2) spatial RCM strategies for one-shot devices and parameters bearing upon those strategies are determined, (3) the verbal variables of the expert team are transformed into fuzzy sets, (4) the relationship between parameters and strategies are designed whereupon a model is developed by MATLAB software, (5) Finally, the model is applied to a real-life one-shot system.

The finding of this study indicates that the proposed fuzzy expert system can determine the parameters affecting the choice of the appropriate one-shot RCM strategies, and a fuzzy inference system can help for effective decision making.

The developed model can be used as a fast and reliable method for determining an appropriate one-shot RCM strategy, whose results can be relied upon with a suitable approximation in respect of the behavior test. To the best authors’ knowledge, this problem is not addressed yet.

The purpose of this paper is to perform numerical simulations based on the incompressible smoothed particle hydrodynamics (ISPH) method for thermo-diffusion convection in a hexagonal-shaped cavity saturated by a porous medium and suspended by a nano-encapsulated phase change material (NEPCM). Here, the solid particles are inserted into a phase change material to enhance its thermal performance.

Superellipse rotated shapes with variable lengths are embedded inside a hexagonal-shaped cavity. These inner shapes are rotated around their center by a uniform circular velocity and their conditions are positioned at high temperature and concentration. The controlling equations in a non-dimensional form were analyzed by using the ISPH method. At first, the validation of the ISPH results is performed. Afterward, the implications of a fusion temperature, lengths/types of the superellipse shapes, nanoparticles parameter and time parameter on the phase change heat transfer, isotherms, isoconcentration and streamlines were addressed.

The achieved simulations indicated that the excess in the length of an inner superellipse shape augments the temperature, concentration and maximum of the streamlines in a hexagonal-shaped cavity. The largest values of mean Nusselt number are attained at the inner rhombus shape with convex (n = 1.5) and the largest values of mean Sherwood number are attained at the inner rectangle shape with rounded corners (n = 4).

The ISPH method is developed to emulate the influences of the uniform rotation of the novel geometry shapes on heat/mass transport inside a hexagonal-shaped cavity suspended by NEPCM and saturated by porous media.

The purpose of this paper is to find the impact of various design variables on the composite shaft, and also the effect of newly developed resin (NDR) on the strength of the fibers of the composite shaft.

The Taguchi method is used to optimize the design variables. Also, GRG approach is used to validate the result.

NDR improves the bonding strength of fiber than the epoxy resin. With the grey relational analysis (GRA) method, the initial setting (A1B4C4D1) was having grey relational grade 0.957. It was enhanced by using a new optimum combination (A2B2C4D2) to 0.965. It indicates that there is an enhancement in the grade by 0.829 percent. Thus, using the GRA approach of analysis, design variables have been successfully optimized to achieve improved dynamic properties of hybrid composite shaft.

The findings of this research are helping to optimize the design variables for the composite shaft. Also, the NDR gives the good bonding strength of carbon/glass fibers in dynamic loading condition than the epoxy resin.