Arman Process Journal (APJ)

Abstract Today, the increasing use of software systems in organizations, companies and small and large industries has left software developers confused about how to develop software with old development methods. With the increasing use of architecture-based process models, software architecture design has become particularly important challenge. Software architecture is one of the key parts of software production, especially its commercial type, which, of course, has been developed in recent years by creating classic models of software production to larger software. Software architecture is a structural system or structures of an operating system that includes software elements, properties visible from outside those elements, and the relationships between them. A good architectural design is a design that meets the quality needs expected by the customer. Achieving the alterability ability is one of the most important quality features in the design of modern software systems. In this article, first the various methods of software architecture design will be examined and then the qualitative feature of alterability and changeability will be introduced in detail. Finally, software architecture design based on achieving the alterability will be discussed.

Abstract Nowadays, with the increasing use of information systems and the movement of organizations towards knowledge-based information systems, the effective management of data and information is one of the important concerns and fundamental operational areas of information and communication technology. In different fields of application, database management can be done with different techniques and approaches. Fuzzy logic as an effective technique is able to create an effective infrastructure and approach for the systematic management of distributed database systems. One of these fields is related to the application of fuzzy systems theory in databases, information retrieval,  expert systems and knowledge base. The most important issue that arises in fuzzy databases is how to deal with the phenomenon of uncertainty. In fuzzy logic applications, non-numeric values are often used to facilitate the expression of rules and facts of databases. In this article, the effective management framework of the fuzzy database is examined.

Abstract With the entry into the age of technology, the optimal recovery of information from the vast ocean of information available on the web is of particular importance and today, relevance has become an important issue in information recovery systems. In the meantime, the increasing number of web pages has created the problem of searching and choosing the best required pages for users. This is while search engines rush to help users and help them in obtaining the required and appropriate information. Being on search engine results pages is the first important step to the development of an online business. It is natural that if you use a suitable search strategy, you can get better and more relevant results with information needs. Therefore, according to the importance of the optimal search strategy used by users in searching for information from search engines and specialized databases, in this article we will examine this issue of related optimization strategies. After the review, at the end of the article, solutions are presented to optimize search engines and improve rankings, which can be useful for managers and designers of search engines and databases, as well as users of these databases in order to effectively achieve information requirements.

Abstract Background and objectives: Due to the digitalization of life and the fiercely competitive global market, the fourth industrial revolution was inevitable. Industry 4.0 utilizes several interconnected technologies such as artificial intelligence (AI), machine learning (ML), big data (BD) and so on to provide new solutions. The aim of this article is to provide an overview of the vital role that Business Intelligence (BI) play in the realization and adoption of Industry 4.0.

Methods: The present paper addresses this shortcoming by systematically reviewing scholarly articles published in this research domain. It integrates previous insights on the topic to provide a far-reaching theoretical framework that highlights antecedents, practices, and outcomes of BI & Industry 4.0 research.

Findings: Our framework shapes a holistic approach of the BI & I4.0 domain and illuminates different relevant elements up on which future studies in this area be developed.

Conclusion: it addresses the future expected for Industry 4.0 primarily in BI and how companies should face this revolution. This article provides knowledge contribution about the current state and positive consequences of Industry 4.0, and high development in business intelligence when implemented in the organization and the harmonization between production and intelligent digital technology.

Abstract Today, modern logistics is moving towards the web-based services. Nowadays, e-commerce is growing rapidly in the digital economy and customers expect to be able to make purchases quickly and easily. This technology has evolved over the years and is still evolving, so that many businesses have decided to enter their business in this space. On the other side, the widespread growth of the Internet has created a wider platform, called the Internet of Things (IoT), which seeks to create a powerful infrastructure for collecting, processing and transmitting distributed information in the shortest possible time. The impact of the IoT on the payment industry and e-commerce is no secret, to both buyers and sellers. Although examining the technical aspects of the Internet of Things for the development of e-commerce is sometimes a vague issue and has not been fully clarified. In this regard and in order to achieve this goal, in this article we intend to examine the role of the IoT in the development of e-commerce functions and the technical aspects of the problem.

Abstract Blockchain is a new technology whose purpose is to store and transfer any type of data in a decentralized manner. In this system, nodes are responsible for confirming and registering transactions, each of these nodes are distributed around the world and use different algorithms to perform their tasks correctly. In blockchain technology, data security has a very high value, and this technology can make our private information more secure and prevent the disclosure of this information. Blockchain security is ensured through various mechanisms, including advanced encryption techniques and mathematical models of behavior and decision making. Blockchain technology is the basic structure of most cryptosystems and what prevents the repetition or destruction of this type of digital currency and interference in the cycle of purchasing digital currency. In this article, in particular, blockchain security in the field of e-commerce is examined and cyber attacks against blockchain and challenges in this field are introduced.

Abstract Social networks are primarily represented and analyzed in the form of graphs with a large number of vertices and edges, structured as an adjacency matrix. The edges indicate relationships between individuals and act as connections between the vertices. The structural characteristics of each network are determined by the features of the edges and vertices within it. In this research, conducted on various types of social network data from the Stanford University database, a preprocessing method was employed using a competitive colonial algorithm for feature selection with the highest merit (lowest cost). To evaluate the impact of feature selection on the final output, experiments were conducted both with and without feature selection operations using various algorithms commonly used in this field. Valid metrics such as accuracy, precision, sensitivity, and recall were independently measured on the output results with an average of 10 program executions. The comparison of results between scenarios with and without feature selection showed a significant impact on all metrics of the final outcome. Many features in the datasets were either unused or contained minimal information. Not removing these features not only increased the computational burden but also affected the accuracy of the output results due to time-consuming execution.

Abstract Background and Objectives: With the advancement of vehicular networks and the increasing demand for accurate and timely data, challenges such as data retrieval delays and security concerns have garnered significant attention. Traditional cloud-based storage methods are unable to meet temporal and security requirements due to the considerable distance between vehicles and servers. Although edge computing offers a solution for reducing latency, it requires improvements due to limitations in storage and distributed management. Previous research has primarily focused on one aspect of optimization (reducing delay or enhancing security), with less attention paid to combining these two objectives. This paper aims to propose an innovative hybrid optimization model using deep learning and blockchain that considers both security and delay reduction. This is achieved by optimizing caching locations, storage, retrieval processes, and storing critical information on the blockchain, ensuring a scalable and flexible model adaptable to traffic changes and user demands.

Methods: The study population and sample include mobile vehicular networks (VANETs), considering edge servers and vehicular nodes. An LSTM model was used to predict traffic patterns and data popularity, while blockchain with a Proof of Authority (PoA) consensus mechanism and smart contracts was employed for secure data storage. Performance was evaluated based on delay, security, and scalability metrics, and compared with existing methods such as Tabu Search, CCS-AGP, and Random Caching in terms of delay and security.

Findings: The proposed model significantly reduced delay (by 10% to 30% compared to baseline methods). The use of blockchain introduced only an 8% additional delay while elevating security to a "very high" level. The system demonstrated stability and scalability under increasing numbers of nodes and data volume. Simulation results indicated that the combination of deep learning and blockchain achieves an optimal balance between performance and security.

Conclusion: The proposed model, integrating deep learning and blockchain, not only reduces delay but also ensures data security and integrity. This framework can serve as a foundation for developing intelligent systems in domains such as the Internet of Things (IoT), smart cities, and next-generation transportation.

Abstract Ambiguity in technology projects is one of the major challenges of modern management and directly affects decision-making, communication, teamwork, and innovation. Using a systematic review approach, this study examines research published between 2010 and 2024 and identifies four main types of ambiguity: requirements ambiguity, technological ambiguity, market ambiguity, and organizational ambiguity. Based on the findings, a three-stage framework for managing ambiguity is proposed, consisting of “recognition and acceptance,” “analysis and prioritization,” and “action and iteration.” In addition, the ADAPT model is introduced as a five-step approach that helps transform uncertain situations into opportunities for innovation. The results indicate that success in technology projects does not depend on eliminating ambiguity, but on the ability to adapt, engage in continuous learning, and make effective decisions under uncertain conditions. The study emphasizes that teams and organizations capable of embracing ambiguity and converting it into a driver of innovation demonstrate stronger and more resilient performance in dynamic and unpredictable technological environments.

Abstract Software engineering affects all aspects of our daily lives. Software development is the basis of activity in the world of software engineering and information technology. Software development involves a set of steps called the software development cycle.
For the success of any software it is significant that each stage of the software development cycle be without errors and defects. But it is unfortunate that we cannot proceed without any uncertainty in the software development cycle. Therefore, it is important that we can identify and evaluate the risks of the initial steps of this cycle.
Requirements engineering are preliminary stage of software development cycle, that it's basic needs are collected from customer. If the risks are ignored in the requirements engineering stage, it will have negative effects on the ability of projects to achieve performance goals and efficiency and so the results.
The main topic of this article is to identify the risk factors in software development projects focusing on the requirements engineering stage. It also refers to the impact of requirements on the outcome and final product performance and also examine the importance of uncertainty requirements role on the quality of the final product. Then, the risk management steps and its role in strengthening the requirements engineering phase will be described.
Conclusion of this article reviews the importance of identifying harmful factors in the early stage of software development and also emphasizes the need to implement the risk management in the requirements engineering.

Abstract Background and Objectives: The cryptocurrencies, including bitcoins, are the fruits of the development of information technology in the international and even domestic financial system in the last decade. Have brought with them. In the present study, From the point of view of individual jurisprudence, the cryptocurrencies are a kind of property, their transactions are not usury and arrogance, and therefore, if the transaction basis of the cryptocurrencies is correct from the religious point of view, its exchange is permissible, but if the transaction basis of the cryptocurrencies is not legitimate, Their transaction is void and forbidden.
Methods: In this study which is descriptive-analytical; we reviewed most of the governmental jurisprudence documents about cryptocurrency trading.
Findings: The result of the present study is that based on arguments such as the no-harm rule, the rule of respect and the rule of maintaining order, and the rule of action and the rule of justice, which all prevent the implementation of incorrect monetary policies and increase the problematic amount of money in the Islamic economic system.
Conclusion: It is advisable to prevent transactions in the field of currency cryptocurrency until the legal order is established by the government to control the cryptocurrency in the country's economy.

Abstract  The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Internet of Things security is a subset of cybersecurity that focuses on protecting, monitoring and remediating threats related to the Internet of Things, or the network of connected devices that collect, store, and share data over the Internet. IoT security challenges can be very controversial because many IoT devices are not built with strong security. Security risk in IoT is critical because the sensitivity of the data IoT devices collect and store, as well as the systems they manage, is much greater than traditional personal network security strategies. In this article, we discuss the functions of the security aspects of the Internet of Things.
 

Abstract The Internet of Things is a novel and popular technology in which the ability to send data through communication networks, either the Internet or intranet, is provided. Connecting more devices to the Internet will lead to security threats, and providing security in the Internet of Things is recognized as a necessity and can be considered as one of the most important challenges of the Internet of Things. Cyber security has always been one of the concerns of the Internet of Things field. Cyber security of the Internet of Things is a specific part of the technology field that focuses on the protection of devices and networks connected to the Internet of Things and includes various equipment, including mechanical machines and He mentioned digital, computing devices, technologies such as artificial intelligence, etc. Also, security breaches and privacy violations are some of the major challenges in this field that sometimes prevent the widespread use of the Internet of Things. Therefore, according to the necessity of research in this article, we will examine some related attacks and solutions in the field of Internet of Things cyber security.

Abstract In recent years, the unlimited and borderless vision has been a prominent feature of the intelligentization based on the Internet of Things (IoT) architecture in the world, and due to the ever-increasing advances in infrastructure and the improvement of security issues, the limitations in this sector have been minimized. The IoT is a term to describe the world in which objects will be able to interact with other objects by connecting to the internet or with the help of communication tools and share their information with each other or with humans, and a new class of capabilities, applications provide applications and services. A world in which all objects and disparate devices are addressable and controllable. Due to its specific operational characteristics, IoT is extremely challenging and risky in the field of realizing smart cities, and so far extensive researches have been introduced in this field. Although each of these researches have somehow succeeded in solving the existing challenges, the studies indicate the existence of some other key requirements and challenges in this field. In this research, we intend to provide a comprehensive review of the realization of smart cities based on the IoT, the challenges, requirements, and opportunities. For this purpose, first, the dimensions of the smart city and the existing challenges will be discussed in detail, and then all kinds of practical requirements will be introduced and examined to realize the target. We will also introduce some of the most important past researches and analyze and explain the problem from different perspectives. At the end of the article, suggestions for the realization of smart cities and conclusions from the investigations are presented.

Abstract In this article, the challenges of software development in the agile method were examined by focusing on non-functional requirements. Non-functional requirements are an important research area that mainly occurs due to the frequency of project failures caused by ignoring the qualitative characteristics related to user values. In the investigations carried out, the increase in development cost and time, the decrease in system flexibility, the increase in complexity and the problems of maintenance and subsequent development, and finally the increase in security risks and software errors, including the damage of neglecting non-functional requirements, have been identified. Effective coordination and cooperation between development groups and other stakeholders have also been identified. It is very important. By following the best practices and non-functional requirements management methods, you can have a significant improvement in the software development process in an agile way with higher accuracy and quality. The study field of software engineering is considered as one of the attractive and practical fields. Undoubtedly, the research conducted in this field will expand day by day and will provide better results. Among the proposed fields for further relevant studies in this field, we can mention the examination of agile management models and methods and improvement of development processes.

Abstract Background and Objectives: Website clicks that redirect Android phone users to malicious ‎websites with fake virus warnings or phishing attacks are increasing exponentially. Although a ‎Uniform Resource Locator (URL) blacklist is considered as a suitable countermeasure for such ‎attacks, it is difficult to efficiently identify malicious websites. To the best of our knowledge, no ‎research has focused on detecting attacks that redirect Android phone users to malicious ‎websites. Therefore, we propose a redirection detection method that focuses on the URL bar ‎change interval of the Android-based Google Chrome browser.‎
Methods: The proposed method, which can be easily installed as an Android application, uses ‎the Android Accessibility Service to detect unwanted redirects to malicious websites without ‎collecting information about these websites in advance. This paper describes the details of the ‎design, implementation, and evaluation results of the proposed application on a real Android ‎device. We set threshold values for the number of times the URL bar changes and the elapsed ‎time to detect redirects to malicious websites for the proposed method.‎
Finding: Based on the results, we investigated the causes of false positive detections of ‎redirects to safe websites and proposed solutions to manage them. We also present threshold ‎values that can minimize the false positive and negative rates, as well as the detection accuracy ‎of the proposed method based on these threshold values. In addition, we present evaluation ‎results based on access reports of real users participating in the WarpDrive project experiment, ‎which show that the proposed method minimizes false positives and successfully detects most ‎redirects to malicious websites.‎

Abstract As a smart and effective technology, the Internet of Things (IoT) plays a very important role in today's technology-driven world. This technology refers to a set of computer and technology-driven communications and interactions such as sensors, processing units, software and hardware with other devices and systems, that are connected and linked via the Internet or other communication networks. On the other hand, blockchain is a decentralized and distributed ledger that records transactions on many computers. This structure ensures that no single entity can access the entire chain to commit fraud. Each block in the chain contains a list of transactions, a time stamp and a cryptographic hash of the previous block, so each record created is unchangeable in a secure way. Blockchain technology, as one of the great innovations of the digital world, has been applied in many areas, including cybersecurity. Security is one of the fundamental challenges in the field of IoT, which can be enhanced and improved through blockchain. The purpose of this research is to analyze the solutions to improve security and privacy and to apply it in creating a privacy monitoring system in the Internet of Things based on blockchain technology. Finally, blockchain, with its unique features, can be an important tool in strengthening the security of the IoT against various threats and reducing risks. Using this technology in areas such as data protection, preventing information manipulation, and increasing the security of cloud systems can help reduce threats and improve digital security. Although there are challenges in the path of blockchain adoption and implementation, its benefits, especially in this area, are very significant.

Abstract Wireless Sensor Networks (WSNs) have emerged as one of the key technologies in recent decades due to their rapid deployability, low cost, and wide range of applications in fields such as the Internet of Things (IoT), environmental monitoring, smart agriculture, and critical systems. However, the hardware and software limitations of sensor nodes — including low processing power and limited energy resources — make these networks vulnerable to failures and disruptions, turning reliability into a fundamental challenge.



In this study, a novel framework based on Tiny Machine Learning (TinyML) is proposed to enhance reliability and optimize energy consumption in WSNs. The proposed architecture consists of four key modules — anomaly detection, failure prediction, intelligent data compression, and adaptive routing — which are deployed locally at the node level to enable fast processing, reduce communication overhead, and enable intelligent resource management.



Simulation results demonstrated that the proposed method not only increases the network lifetime and significantly reduces energy consumption but also improves data quality, communication stability, and responsiveness to abnormal events.



The findings of this research indicate that leveraging TinyML can open new horizons in the design of intelligent WSNs and provide a solid foundation for developing future large-scale applications in dynamic environments.

Abstract Today, most technology-oriented applications are dependent on large and complex software systems. Software architecture provides a systematic framework for managing software complexities and dependencies. Software architecture contains key decisions about the structure of a target software system, which includes the selection of software components, modules and the relationships between these components. Moreover, the software architecture specifies the behavior of these components as the interaction they perform together to build a monolithic software system. Nowadays, one of the issues of concern to software developers is the correct and principled implementation of software architecture and accordingly, the accurate evaluation of architectural dimensions. Also, one of the main roles and functions of information technology units in different organizations is to provide assurance in terms of technical structure and software architecture. The requirement for the basic implementation of software architecture is a clear understanding of the goals and requirements of the architecture. Therefore, in order to make sure, architectural requirements should be fundamentally assessed and evaluated. Due to the importance of this issue, in this article we discuss the feasibility checking and assessment of software architecture requirements.

Abstract Multimedia systems with built-in error tolerance and H.264 compression algorithm have some error tolerance capabilities that are generally used in data compression and transmission. These capabilities can maintain the quality and functionality of the system when errors occur in the system. H264 or AVC, which is used to reduce video volume while maintaining image quality, uses various methods such as homogeneous conversion, asymmetric conversion, predictive processing and word encryption, and HD speed is used to support high resolutions. The use of error tolerance to reduce the bit rate of images in multimedia systems is given. It is also mentioned that it is improved by using filters and simpler methods for image recovery and error tolerance, and depth search method is also used to improve image quality in complex scenes. This algorithm is also error tolerant in dealing with possible errors in compression and transmission. Our review article is based on the fault-tolerant low-power approach, which is proposed to reduce the memory power consumption in the multimedia system. This approach involves changing the supply voltage suddenly to a value greater than what is considered safe under operating conditions while maintaining efficiency. This article offers a review on improving performance and reducing power consumption in multimedia systems using fault tolerance. We start with the H.264 sample as a base model and use the model to construct a fault-tolerant low-power approach. H.264 is a compression algorithm with an acceptable error that uses different methods such as homogeneous conversion, asymmetric conversion, predictive processing, word encoder. This algorithm dynamically calculates the size optimization of the video file at every moment. In the proposed algorithm, we reduce the bit rate of the images, reduce the amount of noise and thus reduce the bandwidth consumption. The algorithm includes intermediate and internal coding, and we change the built-in memories of special multimedia integrated circuit, ASIC. Error tolerance has been applied through image filtering by reducing and improving PSNR and using simple filters for image recovery. The results of the article on H266, H265, H264 decoders show that the amount of power storage is more than 40% possible.

Abstract Blockchain is a holistic system consisting of peer-to-peer connected and distributed blocks of data that eliminates the need for a centralized management entity to manage technological transactions. Blockchain's open-source, impermeable configuration paves the way for an unparalleled level of transparency. Each piece of data is distributed among millions of computers around the world and its authenticity is verified. This relatively new technology is revolutionizing various industries and providing an automated process for managing processes and interactions. The use of blockchain is a cheap and fast solution and it is very attractive that it has experienced a lot of development in recent years. In today's era, the use of blockchain technology plays a very important role in the development of businesses. This powerful technology improves the quality of business and also increases their income and profit. Maintaining business security, authenticity, speed and increasing quality are among the benefits that arise with the help of blockchain in businesses. According to the importance of the issue, in this article we intend to examine the convergence of blockchain with technology-oriented services and related functions.

Abstract Background and Objectives: Cardiovascular diseases have been identified as one of the most prevalent global health issues, and delays in treatment can lead to increased mortality among patients. The primary objective of this study has been to enhance the identification of heart disease patients using a machine learning classification system.
Methods: In this research, machine learning classification systems with rule-based learning techniques have been employed. These techniques are built upon two fundamental principles, reinforcement learning, and genetic algorithms. The Mishgan style has been selected as the optimization method, and a dataset of heart disease patients from the Afshar Research Center has been utilized for the training and learning of the system.
Findings: Following the training of the system, a set of valuable rules has been generated and utilized in the testing phase for predicting heart disease patients. The experimental results indicate that using the Mishgan-style machine learning classification system has improved the identification of heart disease patients, resulting in an 88% increase in prediction accuracy. In other words, this approach enables a more comprehensive identification of heart disease patients.
Conclusion Considering the study's outcomes, the use of the Mishgan-style machine learning classification system as an optimal approach has enhanced the identification of heart disease patients and increased prediction accuracy. This method can contribute significantly to timely treatment of heart disease patients and the reduction of morbidity and mortality associated with these diseases.

Abstract Nowadays, the development of international scientific activities is one of the main concerns of universities to increase credibility, quality and branding. However, the situation of scientific-international cooperation, especially in developing countries, is not very favorable. In the present research, after a brief review of the obstacles of scientific cooperation in developing countries, a user interface has been presented in order to expand international cooperation in the context of scientific social networks. This user interface has the ability to be implemented and added to scientific social networks and also provides an integrated structure for establishing international cooperation. In this short research, the steps of the mechanism of the user interface have been shown precisely from the first stage, i.e. the registration of the cooperation request by the user of the scientific social network to the end of a scientific collaboration. In the user interface, three main concepts of cooperation agreement, support team and reliability index are defined.

Abstract Recent advances in the speed and ease of use of the Internet and the speed and power of software platforms and personal computers lead to the rapid growth of collaborative environments and other distributed education systems. Nowadays, the Internet is a powerful educational resource in educational media and is generally able to evaluate, match and modify the use of computers for all users, anywhere in the world at any time. The popularity of using the Internet as an information and educational resource is growing. With increasing speed and security and advances in technology, the need for the Internet in everyday life increases. In this regard, various efforts have been made in the world and in Iran to design, implement and develop e-learning systems and the content management system of education is the main focus of an e-learning unit through which other departments provide services. This work tries to review the specifications of a proper education content management system and international standards and provide a suitable framework for a standard and comprehensive e-learning system.

Abstract Nowadays, due to the expansion of computer networks and the widespread use of services based on them, we are faced with a variety and large number of users, which is why user satisfaction is of great importance. Therefore, quality of user experience (QoE) is important satisfaction metric. QoE is a criterion for measuring the pleasure or annoyance of customer experiences from a service that focuses on the entire service experience. It is a holistic concept, similar to the field of user experience, but has its roots in telecommunications. In video streaming, QoE is referred to as the end user's assessment of the quality of a video service. This concept depends on factors that affect the user experience and were examined and described in this study, including things such as video loading time (buffering), frame rate, bit rate, image resolution, etc. For streaming service providers and content producers, evaluating and optimizing QoE is of great importance because this can have a direct impact on the level of user interaction, retention, and ultimately revenue. QoE is measured through various techniques and metrics, such as buffering rate, video freeze rate, playback start time, and direct user feedback. By identifying weaknesses in this area, video quality and overall user experience can be improved. Given the importance and necessity of the concept of quality of experience in technology management, this study presents an approach to improving the quality of experience of video streams and the influencing factors based on previous studies. In this study, the effect of influencing factors on the quality of user experience has also been investigated and formulated.