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The primary aim of this study is to provide actionable guidance for augmenting profitability in photovoltaic power plant investments within Iran’s solar energy sector. By emphasizing prudent capital management and strategic investment decisions, our research seeks to assist emerging businesses in attaining sustained success in this domain.

This study presents a comprehensive approach to refined decision-making in Iran’s solar energy sector. Our methodology integrates the best-worst method, ArcGIS software for site selection, and the TOPSIS method for decision-making, aiming to enhance precision and reliability.

Our research has identified ten promising regions suitable for photovoltaic power plant installations in Iran. Leveraging the TOPSIS method, we have made optimal selections among these alternatives. Furthermore, our exhaustive cost analysis, incorporating factors like land prices, system maintenance, revenue estimation, and various financial scenarios, has yielded insights into project cost-effectiveness.

By filling a notable gap in the literature regarding optimal site selection and investment strategies for photovoltaic power plants in Iran, our research contributes to the sustainable development of solar energy infrastructure. Through a thorough literature review and the development of a novel methodology, we offer valuable guidance for businesses and investors seeking success in Iran’s solar energy sector. Our study represents a significant advancement by introducing a novel methodology that integrates the best-worst method, ArcGIS software, and the TOPSIS method for site selection and investment analysis. These findings furnish valuable guidance for businesses seeking success in the solar energy sector, thereby contributing to the sustainable development of renewable energy infrastructure in Iran and beyond.

Removing the bone flap is a compulsory step in open skull surgeries and is very cumbersome and time-consuming. Exerting large forces during the milling and cutting of the skull renders the surgeon exhausted and consequently increases probable errors in further task of manipulating the sensitive brain tissue. This paper aims to present the development of a robotic system capable of perforating and cutting the required bone flap without restraining the surgeon.

For the purpose of optimization, the target workspace is estimated by 3D modeling of the sample skull and bone flaps of targeted surgeries. The optimization considers kinematic performance matrices and the extracted workspace requirements by assigning scores to each possible design and finally selects the design with highest score.

The design utilizes a parallel remote center of motion mechanism. Coordinating the remote center of motion (RCM) of the mechanism with the center of a sphere which circumscribes the skull, the milling tool is always nearly perpendicular to the skull bone. The paper presents the concept design, optimization criteria and finally the optimal design of the robot and the fabricated prototype. Tests indicate that the prototype is able to sweep the target workspace and to exert the required forces for bone milling.

The workspace requirements of the craniotomy/craniectomy surgeries are investigated and converted into one quantitative target workspace. An optimized design for a surgical robot is developed which satisfies the workspace requirements of the targeted surgeries.

Although quality orientation is one of the main priorities of any progressive organization, quality evaluation in organizations providing services such as hospitals is one of the key challenges, because in this sector quality is determined by many intangible factors. Applying the service quality gap model is one of the common tools for quality evaluation in the service sector. This paper seeks to evaluate this issue.

The present descriptive study was carried out through a cross‐sectional method in 2008. The participants of this study were patients who had been referred to Kerman University of Medical Sciences hospitals. The sample comprised 385 patients, the data were collected by SERVQUAL as a standard questionnaire, and data analysis was carried out on 385 completed questionnaires.

In all five dimensions of quality, a gap was observed between patients' perceptions and expectations as follows: Assurance: −1.28, Empathy: −1.36, Responsiveness: −1.80, Tangibles: −1.86 and Reliability: −1.69. A paired T‐test showed that the differences between quality perceptions and expectations are significant (p value<0.05). Based on the findings of this research, the hospitals in the study did not meet the expectations of patients and were unable to provide health care services according to patients' expectations. Hence rearranging the service delivery and deploying better facilities and equipment in order to decrease the gap between patients' perceptions and expectations may be helpful.

The paper reports an original application of the SERVQUAL approach to hospital services of a developing country.

This paper aims to present the design and implementation of VirSense, a novel six-DOF haptic interface system, with an emphasis on its gravity compensation and fixed-base motors.

In this paper, the design and manufacture of the VirSense robot and its comparison with the existing haptic devices are presented. The kinematic analysis of the robot, design of the components, and manufacturing of the robot are explained as well.

The proposed system is employed to generate a Virtual Sense (VirSense) with fixed-base motors and a spring compensation system for counterbalancing the torques generated by the weight of the links. The fixed bases of the motors reduce the system's effective mass and inertia, which is an important factor in haptic interface systems. A novel cabling system is used to transmit the motor torques to the end-effector. The spring-based gravity compensation system causes more reduction in the effective mass and inertia.

This paper provides the details of the VirSense haptic device, its gravity compensation system, and a novel cabling power transmission.

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this approach became the basis for the development and strategic directions of companies in various fields of the company such as finance and accounting. The purpose of this study is sustainable intellectual capital reporting framework and evaluation of key examples in the context of capital market companies.

The methodology of this study was exploratory from the point of view of the developmental result and based on the type of objective and qualitative and quantitative basis was used to collect the data. The statistical population in the qualitative part was university experts and in the quantitative part financial managers of capital market companies. Data collection tools were interviews in the qualitative part and fuzzy scales and language comparison checklists in the quantitative part. Therefore, first through three stages of coding, the dimensions of the model were identified, and based on the fuzzy Delphi analysis, the reliability level was determined through the average between the first round and the second round of Delphi. Finally, through the default tests, the appropriate fuzzy model was first determined, and then hierarchical fuzzy analysis based on TODIM's approach was used to determine the most favorable axis of sustainable intellectual capital reporting.

The results in the qualitative part indicate the existence of 3 categories and 6 components and 39 conceptual themes in the form of a six-dimensional model. In the quantitative part, the results showed that by confirming the dimensions identified through fuzzy Delphi analysis, the most desirable axis of intellectual capital reporting is the component of technological capital reporting, which can play a more effective role in sustainable reporting.

This study, relying on the importance of the consequences of sustainable intellectual capital reporting, tries to evaluate the consequences of this field of financial reporting due to the lack of a coherent theoretical framework about capital market companies. In addition, the framework presented in this study promotes integrated thinking for firms to it would provide some level of incentive to those charged with governance concerning the voluntary compliance with the sustainable intellectual capital reporting framework.

The best algorithm that was implemented on this Brazilian dataset was artificial immune system (AIS) algorithm. But the time and cost of this algorithm are high. Using asexual reproduction optimization (ARO) algorithm, the authors achieved better results in less time. So the authors achieved less cost in a shorter time. Their framework addressed the problems such as high costs and training time in credit card fraud detection. This simple and effective approach has achieved better results than the best techniques implemented on our dataset so far. The purpose of this paper is to detect credit card fraud using ARO.

In this paper, the authors used ARO algorithm to classify the bank transactions into fraud and legitimate. ARO is taken from asexual reproduction. Asexual reproduction refers to a kind of production in which one parent produces offspring identical to herself. In ARO algorithm, an individual is shown by a vector of variables. Each variable is considered as a chromosome. A binary string represents a chromosome consisted of genes. It is supposed that every generated answer exists in the environment, and because of limited resources, only the best solution can remain alive. The algorithm starts with a random individual in the answer scope. This parent reproduces the offspring named bud. Either the parent or the offspring can survive. In this competition, the one which outperforms in fitness function remains alive. If the offspring has suitable performance, it will be the next parent, and the current parent becomes obsolete. Otherwise, the offspring perishes, and the present parent survives. The algorithm recurs until the stop condition occurs.

Results showed that ARO had increased the AUC (i.e. area under a receiver operating characteristic (ROC) curve), sensitivity, precision, specificity and accuracy by 13%, 25%, 56%, 3% and 3%, in comparison with AIS, respectively. The authors achieved a high precision value indicating that if ARO detects a record as a fraud, with a high probability, it is a fraud one. Supporting a real-time fraud detection system is another vital issue. ARO outperforms AIS not only in the mentioned criteria, but also decreases the training time by 75% in comparison with the AIS, which is a significant figure.

In this paper, the authors implemented the ARO in credit card fraud detection. The authors compared the results with those of the AIS, which was one of the best methods ever implemented on the benchmark dataset. The chief focus of the fraud detection studies is finding the algorithms that can detect legal transactions from the fraudulent ones with high detection accuracy in the shortest time and at a low cost. That ARO meets all these demands.

One of the most emerging areas of audit knowledge is sustainable quality, which can comprehensively cover the development of audit reports inclusiveness for stakeholders. The purpose of this study is to present the sustainable audit quality (SAQ) framework based on the UK Financial Reporting Council.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

The results of the study showed that the SAQ is more effective based on the two criteria of going concern and disclosure of key audit items. It was also determined that, based on total interpretive structural modeling, the two themes of debt covenants disclosure and assessment of firms’ leverage ratio have a higher priority for SAQ in the Tehran Stock Exchange.

This paper contributes to the discussion on the use of data mining for microarray databases and specifically for studying the present SAQ framework based on the UK Financial Reporting Council. An area that has not been paid attention to by prior research studies, and to the best of the authors’ knowledge, this study is the first research that attempts to provide the SAQ framework.