Amir Rajabzadeh

   The rapid growth of social commerce as an emerging branch of e-commerce has created extensive opportunities for businesses and users. However, this expansion has been accompanied by a significant rise in cybercrime incidents, exposing users to serious security challenges. The increasing sophistication of malicious behaviors, the exploitation of emerging technologies by cyber attackers, users’ limited cybersecurity awareness, and the absence of adequate security infrastructures are among the key factors that heighten the vulnerability of social commerce environments. Accordingly, the primary objective of this study is to identify the major challenges contributing to cybercrime occurrence in social commerce and to propose effective countermeasures with a specific emphasis on user empowerment. This research adopts a mixed-method approach (qualitative–quantitative). In the qualitative phase, a systematic content analysis of authoritative sources along with expert consultation through the Delphi method was conducted to identify the most influential challenges and components. Subsequently, in the quantitative phase, the extracted factors were evaluated using a structured questionnaire and statistical analysis to determine the significance and impact of each variable on social commerce security. The findings reveal seven key components—user awareness and training, security infrastructures and technologies, user trust and interaction, legal and policy-related challenges, technical challenges and specific cyberattacks, user empowerment, human-resource-related factors, and emerging technologies—that play a critical role in both enabling and mitigating cyber threats. The results indicate that user empowerment across three core dimensions—enhancing digital and security literacy, improving threat-detection capabilities, and promoting safe behavioral practices in online social interactions—can substantially reduce the likelihood of users becoming victims of cybercrime. Furthermore, strategies such as developing targeted educational programs, designing user-centric security mechanisms, strengthening protective regulations, and employing advanced technologies such as artificial intelligence for threat monitoring are essential for establishing a secure social commerce ecosystem. Ultimately, the conceptual model proposed in this research can serve as a practical framework for platforms, policymakers, and businesses operating in the field of social commerce and contribute meaningfully to reducing cybercrime and improving user security.

   Today, unemployment is a major economic challenge in Iran, significantly impacting the country's economic performance and creating various economic difficulties. E-commerce, as a sector influenced by technological advancements, plays a substantial role in generating new employment opportunities for the economy. However, the development of this sector is not solely dependent on the level of a country's digitalization but is also related to the speed of technology adoption and its integration into business environments.E-commerce has led to the formation of new businesses and is characterized by the diminished role of distance, reduced transaction costs, facilitated information gathering, balanced supply and demand, decreased need for intermediaries, and reduced necessity for physical presence. As a symbol of the modern economy, e-commerce is considered one of the most critical drivers of societal progress and holds a significant share in global trade.The objective of this research is to examine the effect of e-commerce development on employment in Iran using the Generalized Method of Moments (GMM) and the EViews software. For this purpose, monthly data from the years 2015 to 2023 (1394 to 1402 in the Persian calendar) has been utilized. This study is descriptive in nature and applied in terms of its purpose. The current research is based on the hypothesis that e-commerce development has a positive effect on employment. Therefore, considering the positive impact of e-commerce on Gross Domestic Product (GDP), the estimation results indicate that the development of e-commerce has had a positive effect on employment in Iran.

   On the one hand, the world is developing and the role of information and communication technology (ICT) and e-commerce is increasing day by day, and on the other hand, the environmental issue is an important issue at the global level. The aim of this study is to investigate the direct and indirect effects of information and communication technology on carbon dioxide emissions of large Asian emitters. This study uses panel econometrics to examine the relationship between information and communication technology and environmental quality in selected Asian countries over the period 1990-2022. The selected Asian countries are: China, India, Japan, Iran, Indonesia, South Korea, Saudi Arabia, Vietnam, Thailand, Malaysia, Kazakhstan, United Arab Emirates, Pakistan, Iraq, Philippines, Uzbekistan, Bangladesh, Kuwait, Qatar, Oman, which respectively have the largest share in CO2 emissions in the world. In this study, the ICT indicators are: fixed telephone, mobile, Internet. The results of the cross-sectional dependence test indicate the existence of cross-sectional dependence between countries. In accordance with result of the result of unit root test, the cointegration test is used to examine the existence of a long-run relationship between the research variables. The results of this test indicate the existence of a long-run relationship between the model variables. Given the existence of   heterogeneity and autocorrelation, the FGLS estimator is used to estimate the model. According to the results obtained, renewable energy significantly reduces carbon dioxide and helps improve environmental quality. The N-shaped environmental Kuznets curve is confirmed in these countries. The results show that the direct effects of ICT indicators on carbon dioxide emissions are negative and significant, and the indirect effects from the trade channel are positive and significant. The net effect is negative and significant up to the threshold level of trade. At the threshold level, the net effect is zero and becomes positive after that. It is suggested to policymakers to consider information and communication technology and its benefits in formulating measures for sustainable development programs. It is also recommended that as economies move towards globalization and increased trade, the use of renewable energy instead of fossil energy is recommended.

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  With the size of transistors reaching the nanometer scale, a large number of processing units (PEs) can be embedded in one chip. With the increase in the number of PE in a chip, the existence of a scalable and powerful communication infrastructure for communication between these cores is necessary. Network-on-chip (NoC) is proposed to meet this need. However, like any other electronic component, the network-on-chip is prone to transient and permanent faults. Among the transient and permanent faults, the transient faults have a higher rate. These faults can reduce the performance of the network-on-chip, and if the rate of faults increases, the whole system is susceptible to failure. Most of the past solutions in the field of fault-tolerance network-on-chip, which have worked in the field of router design, have investigated the problem of single-bit faults. This is despite the fact that due to the shrinking size of transistors, the probability of multi-bit transient faults has increased. Therefore, in this thesis, we have used the Flexible Unequal Error Control (FUEC) coding method in our proposed router to correct single-bit, two-bit, and three-bit faults in the channel and the router's input buffers. We have also used the Triple Module Redundancy (TMR) technique to deal with the problems of router control units. Also, to correct the faults on the multiplexers of cro  ar, we have used redundant information and redundant time to discover and correct the faults, respectively. However, all fault tolerance techniques are associated with hardware overheads. These overheads increase power consumption, while power consumption is an important challenge in today's world. Therefore, it is very necessary to have mechanisms that are power-aware to reduce power consumption. Therefore, in this thesis, a power-aware mechanism has been proposed, which reduces the energy consumption by turning off the idle input buffers in the routers. To evaluate the proposed router, we have implemented it in the Noxim simulator and in this simulator, we have randomly injected faults for synthetic traffic and 8x8 two-dimensional mesh. On the other hand, using the SystemVerilog language, we have synthesized the hardware design of the router in the Vivado2019.1 and obtained the hardware overheads and power consumption using this tool. Using this router in the on-chip network can increase fault tolerance by 5 times and reduce energy consumption by 12% compared to the basic router. On the other hand, this router requires 57% more hardware overhead than the basic router. It also increases the average network delay up to 2 times.

Advances in Blockchain and distributed ledger technologies are driving the rise of incentivized social media platforms over Blockchains. Blockchain-based online social media is decentralized social media that uses blockchain technology to reward users' social activities and store information. In order to protect the privacy of users and expose fake news.    In this study, presents an empirical analysis of Steemit, a key representative of these emerging platforms, to understand and evaluate the actual level of decentralization in these modern social media platforms. Similar to Bitcoin, Steemit is operated by a decentralized community, where 21 members are periodically elected to cooperatively operate the platform through the Delegated Proof-of-Stake (DPoS) consensus protocol.    Our study performed on 539 million operations performed by 1.12 million Steemit users during the period 2016/03 to 2018/08 reveals that the actual level of decentralization in Steemit is far lower than the ideal level, indicating that the DPoS consensus protocol may not be a desirable approach for establishing a highly decentralized social media platform. For this reason, in this dissertation, we tried to provide a solution to the problem of decentralization of the consensus algorithm used in Steemit social media. Our solution to this problem is to replace its consensus algorithm with a more advanced consensus algorithm called the Algorand, which can form a committee without elections involving user interaction. Algorand is a new cryptography that proposes a new Byzantine agreement algorithm that allows choices to be made by randomly validated cryptographic functions rather than by users.    Using the simulator design as well as the API published by Algorand's team, we explored its three main aspects of decentralization, high scalability and security, and show that Algrand can be a good alternative to the DPOS algorithm. Be in Steemit.      

بدون شك امروزه يكي از چالش ­هاي مهم مراكز داده ابري مصرف انرژي بسيار زياد است. از طرفي احتمال خرابي يك سرور در يك مركز داده با تعداد زياد سرور و از دست رفتن ماشين ­هاي مجازي روي آن امري اجتناب ناپذير است. يك روش سنتي براي افزايش قابليت دسترسي سرورها و در نتيجه افزايش قابليت اطمينان ماشين مجازي استفاده از افزونگي مي­ باشد بطوريكه تعداد ماشين مجازي يكسان روي سرورهاي مختلف اجرا شوند كه در صورت بروز خرابي در يك سرور نسخه ­هاي پشتيبان روي سرورهاي ديگر كار مورد نظر را انجام دهند. استفاده از افزونگي منجر به افزايش مصرف انرژي در مراكز داده ابري مي­ شود، لذا بهينه ­سازي اين دو پارامتر نياز به مصالحه دارد. اين پايان نامه روشي جهت تخصيص ماشين ­هاي مجازي با در نظر گرفتن مصرف انرژي و قابليت اطمينان را تحت عنوان روش P21(Placement method with 2 active replication and 1 inactive replication) ارائه مي ­دهد. ايده اصلي روش پيشنهادي در نظر گرفتن دو نسخه­ ي فعال و يك نسخه­ ي غيرفعال افزونگي مي ­باشد. جايگذاري ماشين­ هاي مجازي روي سرورهايي با بالاترين مقدار تابع هدف صورت مي ­گيرد. در همين راستا روش ارائه شده، 2 نسخه­ ي فعال از افزونگي را به عنوان نسخه ­ي اصلي و نسخه­ ي اول پشتيبان در نظر مي­ گيرد و يك نسخه­ ي غير فعال افزونگي را به صورت رزرو دارد. در ابتداي كار، زماني كه ماشين مجازي بر روي سرور نسخه ­ي اصلي جايگذاري مي­ شود همزمان يك نسخه­ ي پشتيبان به صورت سينك روي نسخه­ ي پشتيبان فعال پردازش مي­ شود. زماني كه سرور دچار مشكل شود به دليل حفظ دسترس ­پذيري، عمليات فعال سازي سرور پشتيبان غير فعال آغاز مي­ گردد. بلافاصله، از اطلاعات و پردازش ­هاي صورت گرفته بر روي سرور نسخه­ ي فعال يك نسخه (image) تهيه مي­ شود و پس از فعال سازي سرور غير فعال به آن منتقل مي­ گردد. به همين روش مي­ توان قابليت اطمينان سيستم را بالا برد و با استفاده از قابليت رزرو بودن نسخه­ ي پشتيبان مي­توان از تعداد سرور كمتري استفاده كرد. به دليل عدم پشتيباني قابليت اطمينان در شبيه ­ساز كلودسيم، جهت ارزيابي روش پيشنهادي يك شبيه ­ساز به زبان جاوا پياده ­سازي شده ­است. در اين ارزيابي 8 آزمايش با باركاري مختلف از جمله زمان ورود و پايان تسك­ ها، تعداد هسته­ هاي مورد نياز هر تسك و تاخير بين تسك­ ها مورد بررسي قرار گرفته­ است. اين 8 آزمايش به ازاي تفاوت در تعداد سرورها، توان، دسترس پذيري و تعداد هسته مي­ باشند. نتايج شبيه ­سازي نشان مي­ دهد كه مصرف انرژي براي حالت­ هاي مختلف بين 38-1 درصد كمتر و قابليت اطمينان بين 58/2-01/0 درصد افزايش را نسبت به روش­ هاي مشابه دارد.كلمات كليدي: رايانش ابري، جايگذاري ماشين ­هاي مجازي، قابليت اطمينان، مصرف انرژي، افزونگي

different places (e.g. emergency rooms, bank branches, etc.) is long queues which cause them to waste their time. By designing a system that can provide people with information about the state of congestion in different places, if it used by people, it can help them to avoid wasting their time. This system can be very useful when citizens are asked not to be present in crowded places due to the spread of infectious diseases such as coronavirus. In this thesis, an IoT system based on edge computing architecture is designed to solve the issue of queue formation and population overcrowding. In this system, a Windows-based software receives images by connecting to wireless CCTV cameras and counts the number of people with the help of an image processing method, and then, sends the location status to the server. In this thesis, the background, studies conducted, and challenges of IoT-based people counting systems and image processing algorithms are discussed, and three image processing methods for counting people are proposed. Two methods are based on eliminating the background and counting people based on the background pixels, and the third method is a model based on the MRCNN networks, which is taught to count people’s heads. The places that this system is implemented to detect congestion in them are indoor places where there is rarely the problem of people’s shadows. The mean errors of the best method based on the MAE and RMSE scales in all the test frames obtained as 1.51 and 1.89, respectively.

In recent years, internet traffic is growing extremely rapidly with the rapid growth of internet users and the emergence of new applications. As a result, the problem of identifying the applications on the network has become a complex task. The detection and classification of flow patterns and applications on network traffic plays an important role in network security and network management. The purpose of classification is to create a link between packet packets with a particular service or application. The problem with most of the methods is to rely on property extraction by experts. It is difficult and time consuming to find desirable features that lead to high accuracy. In general, most of the traffic classification methods are based on extracted features by an expert on computer networks. These features include port number, packet overhead, packet header and extracted statistical features of flow. The main problem of traffic classification is finding suitable features in traffic network. The process of finding suitable features is time consuming and cost and needs a qualified person to identify and extract these features and to solve these problems, one of the most recent fields in machine learning is deep learning that is based on artificial neural networks and that feature extraction is done in a hierarchical and automatic mode. In this situation, extracting the automatic feature from the expert will be eliminated and the possibility of human errors is reduced. In this work, our solution show that this approach is capable to identify encrypted traffic and surpass the accuracy achieved by almost every classical method in this area of research. We have used Deep Belief Networks and Convolutional Neural Network that can accurately identify and classification on ISCX vpn-nonvpn dataset.

   It is very time consuming to use deterministic methods for test generation as they use backtrack. The simulation-based test generation methods only analyze the circuit in forward path and this has made them popular. Random Test Generation Methods, which are among simulation-based methods, need a short time for test generation, but the number of test vectors produced in random methods is high. A suitable solution to reduce the number of these vectors is through using the Fault Coverage Index to evaluate the competency of test vectors and trimming test vectors that are inadequate. But calculating the Fault Coverage Index for each test vector requires a fault simulation that is a time consuming process. Also, the genetic algorithm can reach a very compact test set because of the optimized search it performs over a large space of test vectors. But this method, which is simulation based, again requires the time consuming simulation of fault as it uses the fault coverage index as a fitness function. The main purpose of this thesis is to reduce the test generation time in simulation-based methods by maintaining their quality for combinational circuits. The idea behind this thesis is to study the competency of test vectors using a new index based on Probabilistic  ystem that is fast and low-cost to calculate. To evaluate the accuracy of the proposed competency index, the concept of statistical correlation was used. The results showed that there is a correlation between the proposed competency index and the Fault Coverage Index for all circuits and the correlation was greater than 0.7 for 6 circuits out of 10 ISCAS85 circuits, which indicates high correlation.   The results of using the proposed competency index in simulation-based test generation methods showed that the basic method of trimming test vectors can be accelerated to 86% on average by maintaining the quality of test generation and the basic method of test generation based on genetic algorithm can be accelerated to 49.85% on average with an additional test vector.

 design interactive IoT smart toy based on Persian language

بررسي تاثير ويژگي هاي تسهيلات خياباني بر شاخص هاي ايمني در مناطق شهري ، مطالعه موردي : ايلام

  Deep Packet I  ection has always been a challenge of performance and a matter of throughput in computer networks. Therefor a lot of different methods have been invented to enhance the operation of DPI in networks. Using probabilistic filters for DPI is an approach which has been taken is recent years. Probabilistic filters are some kind of data structure which are used for membership test among a set of items. These filters can result a false positive answer. One of constraints of using probabilistic filters is incapability of efficient scaling specially when they are used in a software running by CPU. To solve this problem implementing DPI utility on a scalable parallel architecture can be a good solution. On the other hand, emergence of new networks paradigms like software defined networks added new difficulties in monitoring networks. In the base situation, to perform deep packet i  ection in a software defined network, the whole task is delegated to the controller and this makes the controller overloaded thus creating a network bottleneck. This situation created an intensive need for an architecture and new design of deep packet i  ection which is fast, scalable and flexible to fit in SDN networks. The new design should also decrease the workload of controller which is related to deep packet i  ection. In this thesis we try to design, implement, and evaluate a new method that hits needed criteria.

In this thesis design and fabrication of real time powersystem emulator for power transformer study was presented. Real time powersystem emulator historical studying and review on this emulator advantages inpower system analysis and scenario of hardware in the loop examining clearlyshow the subject importance. Many efforts have been devoted in this field andtodays trends in Field Programmable Gate Array(FPGA) utilization for itsendless advantages was increasingly reported in IEEE literatures and industrialapplications. A. Benigni and A. Monti in a paper named A Parallel Approach to Real Time Simulation of PowerElectronics System (2015)

Communication problem with a simple idea can be transferred to a facility management network infrastructure / system / centralized system, solved, so that hardware can remain as part of the network data (like hardware available) and tooling to the control unit to Annie on the device. Hadoop has given birth several years, the question arises whether its functioning can be improved. The answer can be quite overwhelming with the composition and performance of Hadoop-based software and networking replied. with the networking issues, the work will pay its processing and network-based software this task is delegated.

ارائه يك مدل بهينه سازي فرا ابتكاري و استفاده آن در زمانبندي وظايف سيستم هاي ناهمگن