Introduction: From a long time ago, benefiting from technology has been an inevitable thing for human interests, which is born and based on science. It can be claimed that there is harmony between ethics, science and technology, which promote each other. In this article, the researcher discusses this harmony and compatibility. Material and Methods: The current review study was descriptive and using the study of sources and research keywords among the books and articles published in the databases of Thomson Information Institute, Science Direct and Pub Med. Conclusion: As science and technology continue to advance and become more integrated into our daily lives, ethical considerations become increasingly important. For example, the rise of artificial intelligence (AI) has raised questions about the potential implications of creating machines that can make autonomous decisions and take actions. If science and technology were considered as a tool, it should have been able to subjugate humans and influence all aspects of behavior and values. While it has become a problem that eventually becomes aligned with morality by applying reason, and people now seek help from it as a tool.

This paper introduces a method to find the optimal solution of technology selection model with fuzzy data. The paper suggests a simple computational method to obtain the optimal solution of fuzzy linear programming (LP) problem used in technology selection without the need for solving any fuzzy LP. Clearly the contribution of this research is that it reduces the fuzzy computational complexity, which is significant when dealing with more complex computations.

Cloud computing is a new discussion in enterprise IT. It is becoming popular in terms of distributed technology in some companies. It helps managers who intend to setup business in cyberspace need not to provide high capital to buy computers, software and hire experts staff, instead they can run their business with low cost. Cloud computing also helps users pay for their use of services without needing to spend massive amounts for integration, maintenance or management of the IT infrastructure. In this paper, we have tried to present a model for evaluating user’s satisfaction in cloud computing. Therefore, a conceptual model has been constructed considering attributes such as (security, efficiency and performance, adaptability, and cost) to evaluate cloud computing user's satisfaction in an Internet Service Provider (ISP) companies in Iran. To avoid any ambiguities which are caused by linguistic methods, in this evaluation model we have used Fuzzy Inference System (FIS).

Efficient distribution of service requests between fog and cloud nodes considering user mobility and fog nodes’ overload is an important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance rate. In addition, to prevent requests from being rejected when the mobile user leaves the coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog nodes and outperforms the existing methods in terms of response time and acceptance rate.

Cloud computing technology is of particular importance in service businesses, especially security applications for the police, due to its role in reducing energy consumption, reducing capital costs, increasing security and integrated access to information from other intelligent systems. As such, the current study set out to identify the components which impact cloud computing technology in providing intelligent services in the rail transportation system. Using Delphi technique, this cross-sectional and descriptive-analytical study was conducted in 1399. The panel of experts in this study included eight managers in Tehran Urban and Suburban Metro Company. The Delphi study was conducted in three rounds. Validity was assessed using CVI and CVR, while the reliability was assessed using Cronbach's alpha. During the study, 33 components were proposed by the research team and via a comprehensive literature review. In addition, 10 components were suggested by the panel of experts. The results of the study showed that 23 components were selected in the form of four dimensions of access, strategy, security and services as the most important components affecting cloud computing technology in providing intelligent services in the selected rail transportation system. In other words, the most important challenge related to the service and infrastructure sectors, but strategically there were fewer challenges. The results can be useful for decision makers in the field of security policy-making and the maintenance of security in the community (authentication and keeping privacy) by the police.

In today’, s world, the competition between all business areas and companies including pharma distributor companies has increased dramatically, so it is very important for active companies in the pharma distribution industry which deal with a large number of customers in a B2B market to establish a deep and long-term relationship with their customers and manage that relationship effectively. Since the CRM which now is enriched by new emerging technologies in terms of e-CRM and m-CRM is under developing rapidly, it can play a critical role for empowering these companies to strengthen their relationship with their customers. In this research it has been tried to have a complete review of mobile computing technology concept and its effect on CRM. The research methodology is basically qualitative. After a literature review, using qualitative research methods and deep interviews with a group of 8 industry experts, the whole concept of the initial model was derived using Thematic Analysis method. The Grounded Theory approach was applied to extract the main factors and sub-factors of the final model. Additionally, some of \research techniques such as Dematel, ANP and Super Decision software were used to investigate the interdependency, importance and priority of factors and sub-factors. At the last stage a new model for e-CRM in pharma distribution industry based on mobile computing technology has been proposed. The four key components of the model are Quality of Content and Services, Organizational Readiness, Quality of System and Communication, Customer Mobile App.

Background and Objectives: With the increase of population in the world along with the decrease of natural resources, agricultural land and the increase of unpredictable environmental conditions, it causes concerns in the field of food supply, which is one of the serious concerns for all countries of the world. Therefore, the agricultural industry has moved towards smart agriculture. Smart agriculture using the Internet of Things, which uses different types of sensors to collect data (such as temperature, humidity, light, etc.), a communication network to send and receive data, and information systems to manage and analyze data. Smart agriculture deals with a huge amount of data collected from farms, which has fundamental challenges for analysis using old systems such as lack of storage space, processing delay. Computational paradigm is a key solution to solve the problems of time delay, security, storage space management, real-time analysis. computing paradigms include cloud, fog and edge computing, which by combining each of them in smart agriculture has caused a great transformation in this industry. The purpose of this article is to provide a comprehensive review of the architecture of computing paradigms in smart agriculture applications.Methods: To achieve the goals of this article, the methodology is divided into two parts: article selection and review of the selected articles. The computational paradigms used in the selected articles are from 2019 to 2022. Each selected paper is then reviewed in detail in terms of categories of computing paradigms, architectures, key points, advantages, and challenges.Results: Computational paradigms have significant advantages. Combining these paradigms with each other in a complementary way covers many challenges. The architecture based on the combination of edge-fog-cloud computing is one of the best architectures combined with smart agriculture.Conclusion: By combining computing paradigms and smart agriculture, the challenges based on traditional and old systems are overcome. Combining these paradigms complement each other's challenges.