Arman Process Journal (APJ)

Abstract The Internet of Things (IoT) is one of the fastest technologies to be used in a variety of applications in the last decade and is in fact a large distributed network in which billions of intelligent devices are connected. Smart devices connect wirelessly or wirelessly to communicate, process, compute and monitor various real-time scenarios. The Internet of Things promises a world in which intelligent communication from most devices is possible via the Internet anywhere, anytime with the least possible human assistance. However, security and privacy are the main concerns of the Internet of Things that can affect its sustainable development. Inadequate device updates, lack of efficient and robust security protocols, user ignorance, and active device monitoring are some of the major security challenges that the Internet of Things faces. In this article, we have dealt with the issue of IoT security from different dimensions and examined the related challenges and solutions.

Abstract Basically, the foundation of every scientific society is based on research and research is actually the driver of progress and sustainable development of today's information-oriented societies. Statistical researches are generally carried out in two ways: quantitative and qualitative. Knowing the types of research methods and the characteristics of each of them, as well as understanding the difference between quantitative research and qualitative research, helps the researcher to choose the right and appropriate research method. Qualitative research is a research that is based on non-numerical and experimental, physical and exploratory analyzes to understand concepts, opinions, thoughts and experiences in a completely natural and real context. Qualitative researches use different software infrastructures to analyze information. Understanding these software infrastructures leads to greater success and development of research achievements. According to the necessity of the research, in this article we examine the most important software infrastructures in qualitative analysis research.

Abstract Cloud computing is one of the newest and most successful computing technologies in recent years. However, despite the increasing use of cloud computing, it is difficult to take full advantage of its unique potential, due to inherent problems such as quality challenges, lack of shared resources, performance interactions and efficiency. Today, the quality of service for cloud computing is a key factor in improving support for a large number of users. It should be noted that the satisfaction of users in the field of cloud computing and providing the desired level of quality in providing services, are the main factors for the success, progress and development of this paradigm. Therefore, cloud service providers, using different methods and techniques, try to provide the best quality services with different and varied prices to customers. Hence, adopting a proper quality management perspective will attract more customers and higher revenues for cloud providers. This paper focuses on examining quality-oriented cloud computing business models, quality challenges and strategies, as well as comparing the most important perspectives on improving service quality by highlighting the associated advantages and disadvantages. Finally, after describing quality challenges in environments cloud computing introduces suggestions for improving the service quality management in cloud services.

Abstract Blockchain is a fundamental technology that has changed the recent digital world. In fact, blockchain technology is a digital ledger that records transactions in a secure and transparent manner and provides a decentralized method for verifying and maintaining records. In the field of digital economy, blockchain and digital currencies are intrinsically related to each other. Digital currency is a special form of digital money created on the basis of cryptography. Digital currency has a wide range of uses from online transactions, remittances, decentralized applications to commerce. Most digital currencies use blockchain technology to benefit from basic features such as decentralization, transparency, and immutability. In fact, blockchain is a technology that enables the effective use of digital currencies such as Bitcoin, Ethereum and other digital currencies. The purpose of this article is a science-based study based on blockchain developments and examining the use of blockchain in the digital currency industry, regulations, opportunities and upcoming challenges.

Abstract In this article, a method is proposed for diagnosing children with Attention Deficit Hyperactivity Disorder (ADHD) using deep learning concepts and analyzing the correlation between segmented areas of functional brain images. The proposed method includes preprocessing medical images to remove distorted, noisy, incomplete, and problematic images, generating new functional brain images using autoencoders, which are applicable in artificial intelligence and deep learning, to assist in better analysis of medical images and address the limitations of medical image availability. It also involves segmenting images and creating separate networks to enhance the diagnostic accuracy of the condition and calculate the correlation between regions, ultimately leading to an effective diagnosis of ADHD in children. The conclusion of this study indicates that this combined method has a high capability for timely and accurate diagnosis of this condition in children and can serve as an effective tool in the field of child neurology and psychiatry.

Abstract  
Nowadays, with the increasing use of real-time applications and multimedia content such as online videos and live streaming, the need for optimization-based approaches to manage resources and enhance the quality of end-user experience has become one of the important requirements and main challenges of network service providers. This research first examines the challenges and solutions to improve the quality of user experience in software-defined networks for video streams, and then designs and proposes a new classification perspective and a multi-objective model to evaluate different dimensions of the problem of managing the quality of user experience in common video services in distributed networks. The proposed approach provides a documented and structured framework for optimal resource allocation and efficient management of this network. Covering such approaches in high-level network management not only helps improve the quality of end-user experience, optimize video streams, and reduce latency, but also increases network efficiency and reduces operating costs by creating a multidimensional and comprehensive perspective and optimal use of available resources.

Abstract Recently, due to the increasing use of smart communication devices, every day more companies and people are moving towards the production of mobile applications, so that their products can be used more. The Android operating system is one of the new technologies that is updated in a short time, it is upgraded and more features are quickly added to make it more efficient. The Android operating system is the first comprehensive and complete mobile operating system that has been published as an open source. Although the development of mobile applications based on the Android operating system, in addition to undeniable advantages, also brings challenges that were among the motivations and goals of this research. Therefore, according to the popularity and importance of different aspects of this operating system and inspired by the work done in this field, in this study we have tried to review the capabilities, functions, versions, challenges, perspectives and solutions to solve this problem and challenges in the Android operating system.

Abstract Configuration management is one of the fundamentals of the software project management, which provides a self control and synchronization center for project managers. Because through configuration management, the project manager can access processes and change history of the project. Control of software evolution process in order to use the valid and tested software items in the final version can be considered as the main domain of software configuration management. In this regard, software configuration management should be able to provide solutions for tasks such as software configuration item detection, software version control, software development and development management and so on. While SCM helps manage the evolution of software products and their documentation, traceability helps manage knowledge about the process of developing software products. In fact, in this article we intend to provide an integrated perspective for managing software configuration. We propose the integration of traceability and SCM to help integrate configuration management during the development and evolution of software products. This model demonstrates the elements of knowledge that are essential for the comprehensive management of tracked changes in SCM tool change management performance. This approach can lead to the organization of existing solutions in a parametric manner that increases the reuability of the software resources.

Abstract In the digital age we are witnessing, artificial intelligence (AI) has emerged as a key factor in the evolution of e-commerce. This article examines how to use AI to improve the experience of using data-driven web apps and combine it with artificial intelligence packages, as well as a more dynamic user interface with smart and dynamic parts and create a competitive advantage for businesses. For this research, we used forms that are designed dynamically and collect data from the user, and finally analyze the data and display it in the form of charts and graphs. Our findings show that AI has been able to Increase accuracy of predictions. Using data and advanced algorithms, AI is able to predict customer behavior and market demand with high accuracy. Automation of processes and reduction of the need for manpower has reduced operating costs. Recommender systems and intelligent customer support have led to faster and more personalized service. It has emerged as a powerful e-commerce tool that can help businesses succeed in today's competitive marketplace. As technology continues to advance, we can expect AI to play an even greater role in this industry.

Abstract Artificial intelligence is a branch of the science of producing and studying machines that aim to stimulate human intelligence processes. The main goal of artificial intelligence is to optimize routine processes, improve their speed and efficiency. As a result, the number of functions and services that use artificial intelligence continues to increase worldwide. Today, artificial intelligence has entered the field of education and training and is rapidly replacing traditional methods with modern methods. In this article, we discuss the functions of artificial intelligence in the field of education and electronic knowledge transfer. Considering the increasing development of virtual education in today's world, artificial intelligence can play an effective role in the field of education and electronic knowledge transfer. Artificial intelligence as a powerful tool can be used to improve the quality of education, reduce costs and increase the speed of education. This technology allows students and teachers to provide the best solutions to improve the quality of teaching and learning through intelligent and data-based systems. With the use of artificial intelligence, virtual education can become an effective and affordable method. In general conclusion, it can be said that this technology is very useful in all stages of education, including lesson planning and design, content presentation, exercises and evaluation, and it will soon become an integral part of education.

Abstract In today's knowledge-oriented world, there are many problems that need to be solved in a structured and systematic way. In this regard, an effective solution is to use suitable algorithmic approaches and perspectives. Algorithm includes a set of processes and instructions that can be used to solve many computer problems or real world problems in a regular and effective way. The use of algorithms in solving systematic problems saves time and money and provides new and valuable solutions. In fact, the algorithm is considered the beating heart of potentially powerful technologies such as artificial intelligence and today, instead of thinking about the future of algorithms, people consider the future to belong to algorithms. Although algorithms have relatively the same concept in different fields of implementation, but in order to achieve specific applications of the desired algorithm in different fields, we must take advantage of the approaches and perspectives of appropriate algorithms. Therefore, according to the importance of the subject, in this article, we intend to investigate the different dimensions of algorithmic perspectives and describe the common operational and practical classifications of important algorithms in computer science and related technology-oriented fields.

Abstract Recently, recommender systems have expanded more and more as a new and fundamental technology to support users in choosing the right resources. These systems provide a personalized environment for selecting the desired resources by examining the past interactions of users and identifying interests. Of course, user behavior modeling and the recommendation mechanism are fundamental and decisive issues in the efficiency of recommender systems. In the field of e-commerce, the use of recommender systems plays an essential role in improving the user experience, attracting potential customers, increasing sales, and optimizing the efficiency of related service systems. Therefore, considering the importance of these systems in today's electronic businesses, knowing the functional dimensions of recommender systems is of particular importance. In this article, we are going to review the basic dimensions of recommender systems in the field of e-commerce and introduce some practical tools in this field. Certainly, by moving towards e-commerce systems based on intelligent recommender systems, we will witness huge and revolutionary changes in the infrastructure of the digital economy and related services.

Abstract Distributed operating systems are a very important part of the software design and implementation work for managing systems with a large number of processors. On the other hand, research in the areas of computer science research on distributed systems has increased significantly in the past few decades. One of the topics discussed in such operating systems is the discussion of resource management through process management. For process management in a distributed operating system, there are mechanisms that allow process transfer, download, remote debugging, state vectoring, and remote emulation of the operating system. Process management facilities can be realized by the distributed operating system kernel, and resource utilization improvement is possible through this. In this research, we intend to examine the evolution of distributed operating systems, how to manage processes, migration, clustering, how to transact messages, and other topics about distributed operating systems. We also consider an example of such operating systems called Amoeba, and we examine process management, inter-process communication, and its efficient mechanisms for improving resource management.

Abstract Today's systems, approaches, and technologies leveraged for managing oil and gas supply chain operations fall short of providing operational transparency, traceability, audit, security, and trusted data provenance features. Also, a large portion of the existing systems are centralized, manual, and highly disintegrated, which make them vulnerable to manipulation and the single point of failure problem. Emerging technologies such as the Internet of Things (IoT), fog computing, cloud computing, and block chain can play a vital role in boosting the operational efficiency of the oil and gas industry. In this paper, we explore the potential opportunities and applications of Artificial Intelligence technology in managing the exploration, production, and supply chain and logistics operations in the Natural Gas industry as it can offer traceability, immutability, transparency, and audit features in a decentralized, trusted, and secure manner. This research highlights the use cases of AI in decentralized Block chain with smart contracts, the company’s trading policies, and its advantages for effectively handling market risk assessments during socio-economic crisis. Results spotlight the use of AI in decision accuracy for the developed smart contract-based Natural Gas Industry, thereby qualitatively limiting the threshold level of costs, energy and other control functions in procurement, production and distribution.

Abstract One of the most important consequences of internationalization is the increase in competition at the international level of the economy, because in these conditions, we will always be faced with the reduction of transportation costs, the surprising growth of information technology, and the ever-increasing expansion of electronic commerce, and the minimization of geographic restrictions and the growth of competition. As a result, the efficiency of the international economy will increase. The use of electronic commerce in the field of exports of countries is a major part of the global economy and will bring great benefits. Although in order to use this new technology, it is necessary to measure the feasibility of e-commerce development in the export sector of commercial products, the present research aims to investigate the feasibility of e-commerce development in the export sector of the countries by examining the general functions. Also, the achievements and challenges of this style of globalization have been assessed and analyzed. 

Abstract Service-oriented architecture is a type of organizational architecture that uses service-based functions to simplify and implement activities and integrate work flows. Service-oriented approach is a service-based way of thinking and service-oriented development and their results. On the other side, cloud computing technology has become popular in recent years and large technology-oriented companies around the world have started designing its infrastructure. Cloud solutions are more and more popular nowadays due to their cost-effectiveness and the many possibilities they provide to businesses. Choosing cloud services should be done according to business needs, budget and service provider; Because things like security and service speed are very important. In new researches, the integration of some technological fields such as service-oriented services in cloud computing have also been proposed. Because cloud computing architectures are inherently based on service-oriented approaches and fit the style of architectures that support service-oriented; Therefore, the integration of these two approaches has been considered in many recent researches. In order to better understand such an approach, it is necessary to first understand the relationship between service-oriented architecture and the concept of cloud computing, which is not only limited to the architectural level, but also important at the solution and service levels. In addition, this approach has achievements and challenges that need to be analyzed and investigated. In this article, an attempt has been made to review the fundamental concepts in cloud computing and service orientation, establish a relationship between these two concepts, and then establish a relationship between the basic components, and point out the achievements and challenges ahead in this approach. It should be noted that this approach is still at the beginning of its development. By considering the overlap of service-oriented services and cloud computing, ontologies and parameters can be obtained, which in the future will lead to improvements in the execution structures of services and related performance capabilities in cloud computing and bring forward new innovations.

Abstract Blockchain technology, with its unique features such as decentralization, transparency, security, and immutability, has brought about a significant transformation in various technological fields. This article aims to comprehensively review the security aspects of blockchain, its challenges, and future prospects. First, the fundamental concepts of blockchain, various consensus algorithms, and cryptographic techniques used in it are described. Then, the diverse applications of blockchain in fields such as finance, IoT, energy, health, and privacy are analyzed. An important part of the article is dedicated to blockchain security issues, including network attacks, code vulnerabilities, smart contract attacks, and data protection. Finally, security measures and vulnerability analysis tools are introduced, and research trends are presented to develop more scalable and secure systems. The results show that while blockchain has high potential, it cannot be used sustainably and widely without considering the existing security issues and challenges. Therefore, addressing these challenges, along with leveraging new technologies, will be the key to success in the future development of blockchain. This paper can be used as a reference for further research in the field of blockchain security and the development of related technologies.

Abstract Nowadays, wireless networks can be used in interaction with many novel applications such as, traffic monitoring, battlefield survey, monitoring based on sensors and distribution networks. Wireless sensor networks are one of the important applications of cyber-physical systems in which information is collected from the surrounding environment by using a large number of sensor nodes in a wide environment. A wireless network can be a community of sensor networks with computing and information devices. These systems can intelligently monitor the state of the surrounding environment and react with an intelligent response to the events of the surrounding environment. Due to the technological limitations and environmental influences, the sensor data collected by these systems are inherently noisy and may have may issues and false alarms, and it is highly desirable to sift meaningful information from a large set of noisy data. Target tracking in these systems is a critical problem that has occupied many researches and in recent years, with the realization of the possibility of building wireless sensor networks, the use of these networks in different environments for tracking moving targets has also been proposed, and one of the most important issues in this Networks are considered. In this research, we investigate the approaches of tracking targets on wireless sensor network. We present the issues and problems of tracking, then we continue to review the common tracking methods in these networks and related qualitative parameters.

Abstract In the current technology based era, after e-commerce, education has also entered the realm of virtual space. Virtual education, along with advantages such as not depending on place and time, electronic presence, preserving the environment, etc., has brought valuable achievements and, of course, various challenges for teachers and students. E-learning is one of the new educational methods based on information and communication technology that can solve many limitations and exclusions of education and put an end to the challenge of social demand for education and the lack of sufficient educational resources. The strong and increasing tendency towards electronic learning indicates the various advantages of this method compared to traditional methods of education. The current research with a descriptive-analytical method and with a practical purpose is to examine the advantages and challenges of virtual education and to suggest the requirements and solutions needed to improve the implementation and quality capabilities of virtual education. In order to improve the qualitative and operational capabilities of virtual education, the level of attention to technologies and virtual space should be increased. In particular, social networks and their content should be increased, and in addition to this, media literacy should also be explained to the audience, families, and relevant officials. Also, at the end of the article, we have suggested ways to improve and improve the effectiveness of education in virtual classes. By using these methods, teaching and learning can be made more attractive and easier, and teaching efficiency can be increased.

Abstract The emergence of data mining science has made data become one of the most valuable assets of organizations and with the correct use of this trump card, software systems can produce results in a different and effective way. The process of extracting and discovering patterns and correlations from a large volume of raw data from one or more databases is called data mining. Data mining is an important and fundamental part in the analysis of distributed information of today's organizations. The data obtained from data mining can be used in business intelligence and advanced analysis. Increasing capacity, finding hidden patterns, trends and correlations in data sets is one of the main advantages of data mining tools. Due to the evolution of data storage technology and the growth of big data, the use of data mining techniques has increased dramatically in the last two decades. Using the best data mining tools helps businesses to make decisions and implement knowledge-based processes more efficiently by identifying hidden relationships and patterns in the data. Despite the technology constantly evolving to handle large-scale data, leaders still face challenges around scalability and automation. According to the importance of the topic in this article, we are going to examine the applications of data mining, requirements, process and important tools in this field. In the end, we will examine the technological perspective of data mining.

Abstract  With the expansion of the cyber world, issues are directly and indirectly entered into this area and are studied; The Internet of Things and Blockchain are two developing technologies that create opportunities for new topics including smart contracts. A smart contract is a computer protocol based on blockchain technology to create or improve a contract. In these contracts, valid transactions are defined as programmed code and applied automatically without the need for intermediaries. In this research, we will first introduce the Internet of Things, blockchain, and then smart contracts created from the combination of these two technologies and the advantage of making smart contracts. The method of this research is descriptive and data analysis. The Internet of Things, which is undergoing growth in the IT industry; It provides limitless opportunities for smart contracts; So, in the absence of IoT sensors, these contracts have limited potential. Of course, the technical challenges of smart contracts are a set of programs that are self-verifying, self-executing, and tamper-resistant. By integrating blockchain technology, the smart contract is able to perform a task in real time at a low cost and provide a higher degree of security. Examining a few scenarios in real life shows; The technical challenges of smart contracts are very few along with the advantages of using these contracts. By identifying and analyzing the performance measurement of smart contracts, significant results are obtained for the development of these contracts.

Abstract Nowadays, cyber-physical systems can be used for many new technological applications such as traffic monitoring, battlefield surveillance, and monitoring based on sensors and distribution networks. These systems intelligently monitor and monitor the state of the surrounding environment and react with an intelligent response to the events of the surrounding environment. Wireless sensor network is one of the important applications of cyber-physical systems, in which it starts collecting information from the surrounding environment by using a large number of sensor nodes in a wide environment. Tracking moving targets is a fundamental and challenging issue in this field. In this article, we investigate the tracking of targets on the wireless sensor networks, then we will review and present the issues and problems of tracking in this area. for this purpose, we will first have a comprehensive definition of cyber physical systems as well as the wireless sensor network, then we will continue to review We will track targets in the sensor network and we will examine the methods of tracking in the network and related quality parameters.

Abstract Internet of things is considered as the most important high-level technology in the recent decades. Smart devices that are added to the Internet of Things ecosystem create a significant capacity for the development of electronic businesses. Currently, we are witnessing the impact of the Internet on all sectors of society. With the growth of communication networks and the Internet of Things, tremendous changes are taking place in e-commerce. In this area, the effective integration of Internet of Things technology in electronic business inventory management systems has the potential to create a huge transformation in the industrial and commercial parts. This article examines the effective integration of Internet of Things in the inventory management sector in the field of electronic businesses and highlights its impact on system productivity, operational accuracy and customer satisfaction. By reviewing related research, this study presents how the Internet of Things can improve real-time inventory tracking, reduce operating costs and increase user satisfaction. However, challenges such as high initial costs, data security concerns and the need for technical expertise still exist, and future researches should focus on solving existing challenges and discovering new applications of the Internet of Things in the field of inventory management, in order to obtain its full and optimal potential.

Abstract With the rising demand for high-quality video services such as live streaming, virtual reality, and UHD videos, efficient video coding methods have become increasingly critical. Standards like H.264, H.265, and H.266 aim to reduce data volume while preserving image quality, yet they face challenges such as computational complexity, bandwidth management, and compression resilience. This paper provides a comprehensive review of neural network-based approaches for optimizing video coding. The reviewed methods include convolutional neural networks (CNNs) for intra-mode prediction, LSTM and Seq2Seq models for video traffic modeling, and inverse neural networks (INNs) for robust video hiding. Findings indicate that these techniques can reduce encoding time by up to 70%, enhance frame size prediction accuracy to 13.6%, and improve the resilience of stego videos against compression. Practical applications in bandwidth management, coding optimization for resource-constrained devices, and video security are explored. This study underscores the significant potential of deep learning in advancing video coding standards and suggests future research directions.

Abstract The integration of artificial intelligence into strategic decision-making processes enhances accuracy, speed, and efficiency; however, it simultaneously introduces unprecedented challenges to the traditional accountability framework within corporate governance. Employing a critical analytical approach and drawing upon findings from authoritative research in the fields of artificial intelligence and corporate governance, this article argues that existing legal and ethical systems are ill-prepared to address three structural gaps arising from algorithmic decision-making at the board level.
Accountability is defined as a tripartite relationship among an agent, the board of directors, and the general assembly of shareholders, wherein the agent is obligated to justify and explain their conduct, while the assembly holds the authority to question, judge, evaluate performance, decide on the continuation of cooperation, and take legal action if necessary. The first gap concerns the absence of a clear rule for determining responsibility when AI systems make errors, as responsibility is a "bundle" concept comprising multiple components, and merely attributing it cannot resolve ethical dilemmas. This gap manifests acutely in augmented intelligence and reinforcement learning contexts. The second gap involves the lack of a mechanism to monitor the board itself in its capacity as the overseer of AI systems—referred to herein as the "monitor of the monitor" dilemma. The third gap stems from the temporal misalignment between board decision-making cycles and AI system processing speeds, which undermines effective oversight and timely accountability.
This study proposes three policy-oriented solutions: the non-delegable rule of ultimate human responsibility; the establishment of a specialized AI committee within the board, endowed with continuous auditing authority; and the redefinition of fiduciary duty such that algorithmic literacy and oversight over the lifecycle of AI models become integral components of directors' legal responsibilities. These three solutions are analyzed within the framework of accountability's four objectives: compliance, reporting, monitoring, and enforcement.