Browsing by Author "Navimipour, Nima Jafari"

Now showing 1 - 20 of 96

Citation - WoS: 4
Citation - Scopus: 8
Quantum-based serial-parallel multiplier circuit using an efficient nano-scale serial adder
(Soc Microelectronics, Electron Components Materials-midem, 2024) Wu, Hongyu; Jiang, Shuai; Seyedi, Saeid; Navimipour, Nima Jafari
Quantum dot cellular automata (QCA) is one of the newest nanotechnologies. The conventional complementary metal oxide semiconductor (CMOS) technology was superbly replaced by QCA technology. This method uses logic states to identify the positions of individual electrons rather than defining voltage levels. A wide range of optimization factors, including reduced power consumption, quick transitions, and an extraordinarily dense structure, are covered by QCA technology. On the other hand, the serialparallel multiplier (SPM) circuit is an important circuit by itself, and it is also very important in the design of larger circuits. This paper defines an optimized circuit of SPM circuit using QCA. It can integrate serial and parallel processing benefits altogether to increase efficiency and decrease computation time. Thus, all these mentioned advantages make this multiplier framework a crucial element in numerous applications, including complex arithmetic computations and signal processing. This research presents a new QCAbased SPM circuit to optimize the multiplier circuit's performance and enhance the overall design. The proposed framework is an amalgamation of highly performance architecture with efficient path planning. Other than that, the proposed QCA-based SPM circuit is based on the majority gate and 1-bit serial adder (BSA). BCA circuit has 34 cells and a 0.04 mu m2 area and uses 0.5 clock cycles. The outcomes showed the suggested QCA-based SPM circuit occupies a mere 0.28 mu m 2 area, requires 222 QCA cells, and demonstrates a latency of 1.25 clock cycles. This work contributes to the existing literature on QCA technology, also emphasizing its capabilities in advancing VLSI circuit layout via optimized performance.
Citation - WoS: 1
Citation - Scopus: 1
Scalable and Low-Power Reversible Logic for Future Devices: QCA and IBM-Based Gate Realization
(Elsevier, 2025) Ahmadpour, Seyed-Sajad; Navimipour, Nima Jafari; Zohaib, Muhammad; Misra, Neeraj Kumar; Pour, Mahsa Rastegar; Rasmi, Hadi; Das, Jadav Chandra
One such revolutionary approach to changing the nano-electronic landscape is integrating reversible logic with quantum dot technology that will replace the conventional complementary metal-oxide semiconductors (CMOS) circuits for ultra-high speed, low density, and energy-efficient digital designs. The implementation of the reversible structure under the most inflexible conditions, as executed by quantum laws, is a highly challenging task. Furthermore, the enormous occupying areas seriously compromise the accuracy of the output in quantum dot circuits. Because of this challenge, quantum circuits can be employed as fundamental building blocks in highperformance digital systems since their implementation has a key impact on overall system performance. This study discusses a paradigm shift in nanoscale digital design by using a 4 x 4 reversible gate that redefines the basis of efficiency and precision. This reversible gate is elaborately used in a reversible full-adder circuit, fully symbolizing the core of minimum area, ultra-low energy consumption, and perfect output accuracy. The proposed reversible circuits have been fully realized using quantum-dot cellular automata technology (QCA), simulated, and verified by the highly reliable tool such as Qiskit IBM and QCADesigner 2.0.3. Furthermore, simulations results demonstrated the superiority of the QCA-based proposed adder, which reduced occupied area by 7.14 %, and cell count by 11.57 %, respectively. This work resolves some problems and opens new boundaries toward the future of digital circuits by addressing the main challenges of stability and pushing the boundaries of reversible logic design.
Citation - Scopus: 2
Machine/Deep Learning Techniques for Multimedia Security
(inst Engineering Tech-iet, 2023) Heidari, Arash; Navimipour, Nima Jafari; Azad, Poupak
Multimedia security based on Machine Learning (ML)/ Deep Learning (DL) is a field of study that focuses on using ML/DL techniques to protect multimedia data such as images, videos, and audio from unauthorized access, manipulation, or theft. Developing and implementing algorithms and systems that use ML/DL techniques to detect and prevent security breaches in multimedia data is the main subject of this field. These systems use techniques like watermarking, encryption, and digital signature verification to protect multimedia data. The advantages of using ML/DL in multimedia security include improved accuracy, scalability, and automation. ML/DL algorithms can improve the accuracy of detecting security threats and help identify multimedia data vulnerabilities. Additionally, ML models can be scaled up to handle large amounts of multimedia data, making them helpful in protecting big datasets. Finally, ML/DL algorithms can automate the process of multimedia security, making it easier and more efficient to protect multimedia data. The disadvantages of using ML/DL in multimedia security include data availability, complexity, and black box models. ML and DL algorithms require large amounts of data to train the models, which can sometimes be challenging. Developing and implementing ML algorithms can also be complex, requiring specialized skills and knowledge. Finally, ML/DL models are often black box models, which means it can be difficult to understand how they make their decisions. This can be a challenge when explaining the decisions to stakeholders or auditors. Overall, multimedia security based on ML/DL is a promising area of research with many potential benefits. However, it also presents challenges that must be addressed to ensure the security and privacy of multimedia data.
Citation - WoS: 8
Citation - Scopus: 11
A Nano-Scale Design of Vedic Multiplier for Electrocardiogram Signal Processing Based on a Quantum Technology
(Aip Publishing, 2025) Wang, Yuyao; Darbandi, Mehdi; Ahmadpour, Seyed-Sajad; Navimipour, Nima Jafari; Navin, Ahmad Habibizad; Heidari, Arash; Anbar, Mohammad
An electrocardiogram (ECG) measures the electric signals from the heartbeat to diagnose various heart issues; nevertheless, it is susceptible to noise. ECG signal noise must be removed because it significantly affects ECG signal characteristics. In addition, speed and occupied area play a fundamental role in ECG structures. The Vedic multiplier is an essential part of signal processing and is necessary for various applications, such as ECG, clusters, and finite impulse response filter architectures. All ECGs have a Vedic multiplier circuit unit that is necessary for signal processing. The Vedic multiplier circuit always performs multiplication and accumulation steps to execute continuous and complex operations in signal processing programs. Conversely, in the Vedic multiplier framework, the circuit speed and occupied area are the main limitations. Fixing these significant defects can drastically improve the performance of this crucial circuit. The use of quantum technologies is one of the most popular solutions to overcome all previous shortcomings, such as the high occupied area and speed. In other words, a unique quantum technology like quantum dot cellular automata (QCA) can easily overcome all previous shortcomings. Thus, based on quantum technology, this paper proposes a multiplier for ECG using carry skip adder, half-adder, and XOR circuits. All suggested frameworks utilized a single-layer design without rotated cells to increase their operability in complex architectures. All designs have been proposed with a coplanar configuration in view, having an impact on the circuits' durability and stability. All proposed architectures have been designed and validated with the tool QCADesigner 2.0.3. All designed circuits showed a simple structure with minimum quantum cells, minimum area, and minimum delay with respect to state-of-the-art structures.
Citation - WoS: 46
Citation - Scopus: 53
Everything You Wanted To Know About Chatgpt: Components, Capabilities, Applications, and Opportunities
(John Wiley & Sons Ltd, 2024) Heidari, Arash; Navimipour, Nima Jafari; Zeadally, Sherali; Chamola, Vinay
Conversational Artificial Intelligence (AI) and Natural Language Processing have advanced significantly with the creation of a Generative Pre-trained Transformer (ChatGPT) by OpenAI. ChatGPT uses deep learning techniques like transformer architecture and self-attention mechanisms to replicate human speech and provide coherent and appropriate replies to the situation. The model mainly depends on the patterns discovered in the training data, which might result in incorrect or illogical conclusions. In the context of open-domain chats, we investigate the components, capabilities constraints, and potential applications of ChatGPT along with future opportunities. We begin by describing the components of ChatGPT followed by a definition of chatbots. We present a new taxonomy to classify them. Our taxonomy includes rule-based chatbots, retrieval-based chatbots, generative chatbots, and hybrid chatbots. Next, we describe the capabilities and constraints of ChatGPT. Finally, we present potential applications of ChatGPT and future research opportunities. The results showed that ChatGPT, a transformer-based chatbot model, utilizes encoders to produce coherent responses.
Citation - WoS: 49
Citation - Scopus: 64
Resilient and Dependability Management in Distributed Environments: a Systematic and Comprehensive Literature Review
(Springer, 2023) Amiri, Zahra; Heidari, Arash; Navimipour, Nima Jafari; Unal, Mehmet
With the galloping progress of the Internet of Things (IoT) and related technologies in multiple facets of science, distribution environments, namely cloud, edge, fog, Internet of Drones (IoD), and Internet of Vehicles (IoV), carry special attention due to their providing a resilient infrastructure in which users can be sure of a secure connection among smart devices in the network. By considering particular parameters which overshadow the resiliency in distributed environments, we found several gaps in the investigated review papers that did not comprehensively touch on significantly related topics as we did. So, based on the resilient and dependable management approaches, we put forward a beneficial evaluation in this regard. As a novel taxonomy of distributed environments, we presented a well-organized classification of distributed systems. At the terminal stage, we selected 37 papers in the research process. We classified our categories into seven divisions and separately investigated each one their main ideas, advantages, challenges, and strategies, checking whether they involved security issues or not, simulation environments, datasets, and their environments to draw a cohesive taxonomy of reliable methods in terms of qualitative in distributed computing environments. This well-performed comparison enables us to evaluate all papers comprehensively and analyze their advantages and drawbacks. The SLR review indicated that security, latency, and fault tolerance are the most frequent parameters utilized in studied papers that show they play pivotal roles in the resiliency management of distributed environments. Most of the articles reviewed were published in 2020 and 2021. Besides, we proposed several future works based on existing deficiencies that can be considered for further studies.
Citation - WoS: 82
Citation - Scopus: 112
A new lung cancer detection method based on the chest CT images using Federated Learning and blockchain systems
(Elsevier, 2023) Heidari, Arash; Javaheri, Danial; Toumaj, Shiva; Navimipour, Nima Jafari; Rezaei, Mahsa; Unal, Mehmet
With an estimated five million fatal cases each year, lung cancer is one of the significant causes of death worldwide. Lung diseases can be diagnosed with a Computed Tomography (CT) scan. The scarcity and trustworthiness of human eyes is the fundamental issue in diagnosing lung cancer patients. The main goal of this study is to detect malignant lung nodules in a CT scan of the lungs and categorize lung cancer according to severity. In this work, cutting-edge Deep Learning (DL) algorithms were used to detect the location of cancerous nodules. Also, the real-life issue is sharing data with hospitals around the world while bearing in mind the organizations' privacy issues. Besides, the main problems for training a global DL model are creating a collaborative model and maintaining privacy. This study presented an approach that takes a modest amount of data from multiple hospitals and uses blockchain-based Federated Learning (FL) to train a global DL model. The data were authenticated using blockchain technology, and FL trained the model internationally while maintaining the organization's anonymity. First, we presented a data normalization approach that addresses the variability of data obtained from various institutions using various CT scanners. Furthermore, using a CapsNets method, we classified lung cancer patients in local mode. Finally, we devised a way to train a global model cooperatively utilizing blockchain technology and FL while maintaining anonymity. We also gathered data from real-life lung cancer patients for testing purposes. The suggested method was trained and tested on the Cancer Imaging Archive (CIA) dataset, Kaggle Data Science Bowl (KDSB), LUNA 16, and the local dataset. Finally, we performed extensive experiments with Python and its well-known libraries, such as Scikit-Learn and TensorFlow, to evaluate the suggested method. The findings showed that the method effectively detects lung cancer patients. The technique delivered 99.69 % accuracy with the smallest possible categorization error.
Citation - WoS: 18
Citation - Scopus: 19
A Nano-Scale Design of Arithmetic and Logic Unit for Energy-Efficient Signal Processing Devices Based on a Quantum-Based Technology
(Springer, 2025) Zohaib, Muhammad; Navimipour, Nima Jafari; Aydemir, Mehmet Timur; Ahmadpour, Seyed-Sajad
Signal processing had a significant impact on the development of many elements of modern life, including telecommunications, education, healthcare, industry, and security. The semiconductor industry is the primary driver of signal processing innovation, producing ever-more sophisticated electronic devices and circuits in response to global demand. In addition, the central processing unit (CPU) is described as the "brain" of a computer or all electronic devices and signal processing. CPU is a critical electronic device that includes vital components such as memory, multiplier, adder, etc. Also, one of the essential components of the CPU is the arithmetic and logic unit (ALU), which executes the arithmetic and logical operations within all types of CPU operations, such as addition, multiplication, and subtraction. However, delay, occupied areas, and energy consumption are essential parameters in ALU circuits. Since the recent ALU designs experienced problems like high delay, high occupied area, and high energy consumption, implementing electronic circuits based on new technology can significantly boost the performance of entire signal processing devices, including microcontrollers, microprocessors, and printed devices, with high-speed and low occupied space. Quantum dot cellular automata (QCA) is an effective technology for implementing all electronic circuits and signal processing applications to solve these shortcomings. It is a transistor-less nanotechnology being explored as a successor to established technologies like CMOS and VLSI due to its ultra-low power dissipation, high device density, fast operating speed in THz, and reduced circuit complexity. This research proposes a ground-breaking ALU that upgrades electrical devices such as microcontrollers by applying cutting-edge QCA nanotechnology. The primary goal is to offer a novel ALU architecture that fully utilizes the potential of QCA nanotechnology. Using a new and efficient approach, the fundamental gates are skillfully utilized with a coplanar layout based on a single cell not rotated. Furthermore, this work presents an enhanced 1-bit and 2-bit arithmetic logic unit in quantum dot cellular automata. The recommended design includes logic, arithmetic operations, full adder (FA) design, and multiplexers. Using the powerful simulation tools QCADesigner, all proposed designs are evaluated and verified. The simulation outcomes indicates that the suggested ALU has 42.48 and 64.28% improvements concerning cell count and total occupied area in comparison to the best earlier single-layer and multi-layer designs.
Citation - WoS: 5
Citation - Scopus: 5
Blockchain Systems in Embedded Internet of Things: Systematic Literature Review, Challenges Analysis, and Future Direction Suggestions
(Mdpi, 2022) Darbandi, Mehdi; Al-Khafaji, Hamza Mohammed Ridha; Nasab, Seyed Hamid Hosseini; AlHamad, Ahmad Qasim Mohammad; Ergashevich, Beknazarov Zafarjon; Navimipour, Nima Jafari
Internet of Things (IoT) environments can extensively use embedded devices. Without the participation of consumers; tiny IoT devices will function and interact with one another, but their operations must be reliable and secure from various threats. The introduction of cutting-edge data analytics methods for linked IoT devices, including blockchain, may lower costs and boost the use of cloud platforms. In a peer-to-peer network such as blockchain, no one has to be trusted because each peer is in charge of their task, and there is no central server. Because blockchain is tamper-proof, it is connected to IoT to increase security. However, the technology is still developing and faces many challenges, such as power consumption and execution time. This article discusses blockchain technology and embedded devices in distant areas where IoT devices may encounter network shortages and possible cyber threats. This study aims to examine existing research while also outlining prospective areas for future work to use blockchains in smart settings. Finally, the efficiency of the blockchain is evaluated through performance parameters, such as latency, throughput, storage, and bandwidth. The obtained results showed that blockchain technology provides security and privacy for the IoT.
A Nano-Design of Image Masking and Steganography Structure Based on Quantum Technology
(Elsevier, 2025) Salahov, Huseyn; Ahmadpour, Seyed-Sajad; Navimipour, Nima Jafari; Das, Jadav Chandra; Rasmi, Hadi
Secure image storage and transmission require sound encryption methods that resist key exposure while maintaining high image quality. Various encryption approaches have been developed to protect image content and its transmission from unauthorized access. One such method is image masking, where a special mask is generated to conceal information within the original image. Instead of hiding the image visually, the mask creates an intermediate layer that obfuscates the encryption key, eliminating the need to transmit it directly. However, implementing such masking techniques efficiently at the hardware level poses particular challenges. Traditional Complementary Metal-Oxide-Semiconductor (CMOS)-based Very-Large-Scale-Integration (VLSI) systems face scalability issues, excessive heat, and high-power consumption. To overcome these challenges, this study utilizes a nano-scale image masking architecture based on Quantum-dot Cellular Automata (QCA), offering reduced area, lower power dissipation, and faster processing. The core operations utilize a three-input XOR gate, designed as a single-layer QCA structure without rotated cells. While QCA-based approaches improve hardware efficiency, most existing implementations focus only on grayscale images, leaving a gap in colorful image encryption. To address this, the work presents a QCA-based encryption and masking architecture for colored images. The method encrypts an image using a random key to generate a cipher image, which is then XORed with the original image to produce a mask. This process, applied independently to each RGB channel, produces three cipher-mask pairs, embedding steganographic property by concealing key information within the image. The keys are generated using a true random number generator (TRNG) based on cross-coupled loops and crossoriented structures, ensuring high entropy. The design was modeled in QCADesigner 2.0.3, with the encryption/decryption algorithms implemented in Python. Experimental results demonstrated a meaningful reduction in cell count and consumed area compared to the prior designs. Image quality and security analysis confirmed visual fidelity and improved robustness.
Citation - WoS: 1
Citation - Scopus: 1
The role of new ICT-based systems in modern management special issue editors
(Cambridge Univ Press, 2023) Navimipour, Nima Jafari; Wan, Shaohua; Pasumarti, Srinivas Subbarao; Fazio, Maria
In this special issue, we have collected eight articles that offer new points for research on information and communications technology (ICT)-based systems. We focused on the intuitive nature of the relationship between new ICT-based systems and contemporary management, forming an integrative unit of analysis instead of focusing solely on new ICT-based systems and leaving contemporary management as a moderating or mediating factor. This special issue promoted interdisciplinary research at the intersection of new ICT-based systems and contemporary management, including cybernetics systems and knowledge management, service managing and the Internet of things, cloud and marketing management, business process re-engineering and management, knowledge management, and strategic business management, among others.
Citation - WoS: 6
Citation - Scopus: 7
A Radio Frequency Identification Reader Collision Avoidance Protocol for Dense Reader Environments in the Context of Industry 4.0
(Wiley, 2023) Rezaie, Hadiseh; Golsorkhtabaramiri, Mehdi; Navimipour, Nima Jafari
In the new industrial revolution known as Industry 4.0, radio frequency identification (RFID) systems are a key component of automatic detection. These systems have two main elements, namely Reader and Tag. In many Internet of Things (IoT) applications, the RFID system is used with lots of readers working together in a dense environment to read tags. The simultaneous operation of readers with a common sensory range increases the likelihood of reader-to-tag collision and reader-to-reader collision and reduces the number of successful reading and as a result, reduces network performance and average waiting time for each reader increased. Collisions happen when readers are in the interference range and start reading tags simultaneously, so it is necessary to use the right solution to control channel access in these systems. So far, various solutions have been proposed to control readers' access to the communication channel. Some of them have not considered the existing standards for this type of system or have not been efficient enough to be used in the IoT. In this study, we propose a method that, by considering the distance between readers and the number of neighbourhoods, and the possibility of information sharing, allows readers to successfully read more tags with fewer collisions in a certain time frame. The results of the performance study in a real-world environment showed that the suggested method outperformed similar methods in terms of network performance and has much better throughput, making it a superior choice for usage in IoT-based RFID systems.
Citation - WoS: 16
Citation - Scopus: 18
A New Nano-Design of 16-Bit Carry Look-Ahead Adder Based on Quantum Technology
(Iop Publishing Ltd, 2023) Ahmadpour, Seyed-Sajad; Navimipour, Nima Jafari
There is a requirement and a desire to develop reliable and energy-efficient circuit designs that adapt to the expanding field of low-power circuit engineering in the VLSI domain based on nanotechnology. The quantum-dot cellular automata (QCA) technology possesses the potential to supplant the conventional, complementary metal-oxide-semiconductor (CMOS) technology in low-power nano-scale applications due to its diminutive cell dimensions, dependable circuitry architecture, and robust structural integrity. On the other hand, the carry look-ahead adder (CLA) is one of the vital circuits in digital processing utilized in diverse digital applications. In addition, for the design of this essential circuit, the occupied area and the delay play the primary role because using a simple formulation can reduce the occupied area, energy consumption, and the number of gates count. In the previous structures, high delay and use of traditional technology (like CMOS) caused an increase in the number of gate counts and occupied areas. Using QCA technology, simple quantum cells, and a low delay, all the previous shortcomings can be resolved to reduce the number of gate counts and low occupied area in the CLA circuit. This paper proposes a new method that helps the propagation characteristics generate suitable signals to reduce the number of gate counts based on adders in QCA technology. Several new blocks are used to design fast binary adders. Finally, an optimal four and 16-bit CLA circuit will be proposed based on the adder circuit. Furthermore, the execution and experimentation of outcomes are carried out utilizing QCADesigner-2.0.3. The simulation-based comparison of values justified the proposed design's accuracy and efficiency. The simulation results demonstrate that the proposed circuit has a low area and quantum cell.
Citation - WoS: 40
Citation - Scopus: 55
A Comprehensive and Systematic Literature Review on the Big Data Management Techniques in the Internet of Things
(Springer, 2023) NaghibnAff, Arezou; Navimipour, Nima Jafari; Hosseinzadeh, Mehdi; Sharifi, Arash
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for BDM in IoT. This paper aims to study the important mechanisms in this area systematically. This paper studies articles published between 2016 and August 2022. Initially, 751 articles were identified, but a paper selection process reduced the number of articles to 110 significant studies. Four categories to study BDM mechanisms in IoT include BDM processes, BDM architectures/frameworks, quality attributes, and big data analytics types. Also, this paper represents a detailed comparison of the mechanisms in each category. Finally, the development challenges and open issues of BDM in IoT are discussed. As a result, predictive analysis and classification methods are used in many articles. On the other hand, some quality attributes such as confidentiality, accessibility, and sustainability are less considered. Also, none of the articles use key-value databases for data storage. This study can help researchers develop more effective BDM in IoT methods in a complex environment.
Citation - WoS: 3
Citation - Scopus: 4
An Energy-Aware Resource Management Strategy Based on Spark and YARN in Heterogeneous Environments
(Ieee-inst Electrical Electronics Engineers inc, 2024) Shabestari, Fatemeh; Navimipour, Nima Jafari
Apache Spark is a popular framework for processing big data. Running Spark on Hadoop YARN allows it to schedule Spark workloads alongside other data-processing frameworks on Hadoop. When an application is deployed in a YARN cluster, its resources are given without considering energy efficiency. Furthermore, there is no way to enforce any user-specified deadline constraints. To address these issues, we propose a new deadline-aware resource management system and a scheduling algorithm to minimize the total energy consumption in Spark on YARN for heterogeneous clusters. First, a deadline-aware energy-efficient model for the considered problem is proposed. Then, using a locality-aware method, executors are assigned to applications. This algorithm sorts the nodes based on the performance per watt (PPW) metric, the number of application data blocks on nodes, and the rack locality. It also offers three ways to choose executors from different machines: greedy, random, and Pareto-based. Finally, the proposed heuristic task scheduler schedules tasks on executors to minimize total energy and tardiness. We evaluated the performance of the suggested algorithm regarding energy efficiency and satisfying the Service Level Agreement (SLA). The results showed that the method outperforms the popular algorithms regarding energy consumption and meeting deadlines.
Citation - WoS: 3
Citation - Scopus: 3
A New Energy-Aware Method for Gas Lift Allocation in IoT-Based Industries Using a Chemical Reaction-Based Optimization Algorithm
(Mdpi, 2022) Zanbouri, Kouros; Bastak, Mostafa Razoughi; Alizadeh, Seyed Mehdi; Navimipour, Nima Jafari; Yalcin, Senay
The Internet of Things (IoT) has recently developed opportunities for various industries, including the petrochemical industry, that allow for intelligent manufacturing with real-time management and the analysis of the produced big data. In oil production, extracting oil reduces reservoir demand, causing oil supply to fall below the economically viable level. Gas lift is a popular artificial lift system that is both efficient and cost-effective. If gas supplies in the gas lift process are not limited, a sufficient amount of gas may be injected into the reservoir to reach the highest feasible production rate. Because of the limited supply of gas, it is essential to achieve the sustainable utilization of our limited resources and manage the injection rate of the gas into each well in order to enhance oil output while reducing gas injection. This study describes a novel IoT-based chemical reaction optimization (CRO) technique to solve the gas lift allocation issue. The CRO algorithm is inspired by the interaction of molecules with each other and achieving the lowest possible state of free energy from an unstable state. The CRO algorithm has excellent flexibility, enabling various operators to modify solutions and a favorable trade-off between intensification and diversity. A reasonably fast convergence rate serves as a powerful motivator to use as a solution. The extensive simulation and computational study have presented that the proposed method using CRO based on IoT systems significantly improves the overall oil production rate and reduces gas injection, energy consumption and cost compared to traditional algorithms. Therefore, it provides a more efficient system for the petroleum production industry.
Citation - WoS: 6
Citation - Scopus: 4
Leveraging Explainable Artificial Intelligence for Transparent and Trustworthy Cancer Detection Systems
(Elsevier, 2025) Toumaj, Shiva; Heidari, Arash; Navimipour, Nima Jafari
Timely detection of cancer is essential for enhancing patient outcomes. Artificial Intelligence (AI), especially Deep Learning (DL), demonstrates significant potential in cancer diagnostics; however, its opaque nature presents notable concerns. Explainable AI (XAI) mitigates these issues by improving transparency and interpretability. This study provides a systematic review of recent applications of XAI in cancer detection, categorizing the techniques according to cancer type, including breast, skin, lung, colorectal, brain, and others. It emphasizes interpretability methods, dataset utilization, simulation environments, and security considerations. The results indicate that Convolutional Neural Networks (CNNs) account for 31 % of model usage, SHAP is the predominant interpretability framework at 44.4 %, and Python is the leading programming language at 32.1 %. Only 7.4 % of studies address security issues. This study identifies significant challenges and gaps, guiding future research in trustworthy and interpretable AI within oncology.
Citation - WoS: 2
Citation - Scopus: 7
Multimedia big data computing mechanisms: a bibliometric analysis
(Springer, 2023) Rivai, Faradillah Amalia; Navimipour, Nima Jafari; Yalcin, Senay
Massive multimedia data are being created due to the rising amount of the Internet and user-generated content, low-cost commodity devices with cameras (like cellphones, surveillance systems, and so on), and the proliferation of social networks, forming a unique type of big data. Several studies have been conducted in this research area using a survey and event analysis approach; however, none has been conducted to investigate the status of knowledge, its features, evolution, and emerging trend of multimedia big data. Therefore, in this paper, a bibliometric study using VOSviewer software is carried out with 1,865 documents from 2008 to 2020. Based on the result, 2013 is the starting year where the total publication excess of 100 articles and the configuration of leading countries, productive organizations, and authors are investigated. The most cited journals, popular publications venues, and hot research topics are also included in the investigations. Our investigation uncovered useful information, such as annual publishing patterns, the hottest research topic, the top 10 important authors and articles, and the most helpful funding organizations and venues.
Citation - WoS: 24
Citation - Scopus: 23
The History of Computing in Iran (persia)-Since the Achaemenid Empire
(Mdpi, 2022) Heidari, Arash; Navimipour, Nima Jafari; Unal, Mehmet
Persia was the early name for the territory that is currently recognized as Iran. Iran's proud history starts with the Achaemenid Empire, which began in the 6th century BCE (c. 550). The Iranians provided numerous innovative ideas in breakthroughs and technologies that are often taken for granted today or whose origins are mostly unknown from the Achaemenid Empire's early days. To recognize the history of computing systems in Iran, we must pay attention to everything that can perform computing. Because of Iran's historical position in the ancient ages, studying the history of computing in this country is an exciting subject. The history of computing in Iran started very far from the digital systems of the 20th millennium. The Achaemenid Empire can be mentioned as the first recorded sign of using computing systems in Persia. The history of computing in Iran started with the invention of mathematical theories and methods for performing simple calculations. This paper also attempts to shed light on Persia's computing heritage elements, dating back to 550 BC. We look at both the ancient and current periods of computing. In the ancient section, we will go through the history of computing in the Achaemenid Empire, followed by a description of the tools used for calculations. Additionally, the transition to the Internet era, the formation of a computer-related educational system, the evolution of data networks, the growth of the software and hardware industry, cloud computing, and the Internet of Things (IoT) are all discussed in the modern section. We highlighted the findings in each period that involve vital sparks of computing evolution, such as the gradual growth of computing in Persia from its early stages to the present. The findings indicate that the development of computing and related technologies has been rapidly accelerating recently.
Citation - WoS: 21
Citation - Scopus: 26
An Energy-Aware Iot Routing Approach Based on a Swarm Optimization Algorithm and a Clustering Technique
(Springer, 2022) Sadrishojaei, Mahyar; Navimipour, Nima Jafari; Reshadi, Midia; Hosseinzadeh, Mehdi
The Internet of Things (IoT) comprises many nodes dispersed around a particular target region, and it has lately been applied in a variety of sectors such as smart cities, farming, climatology, smart metering, waste treatment, and others. Even though the IoT has tremendous potential, some difficulties must be addressed. When building the clustering and routing protocol for huge-scale IoT networks, uniform energy usage and optimization are two significant concerns. Clustering and routing are well-known NP-hard optimization challenges applied to the IoT. The ease with which chicken can be implemented has garnered much interest compared to other population-based metaheuristic algorithms in solving optimization problems in the IoT. Aiming to reduce and improve node energy consumption in the IoT network by choosing the most suitable cluster head, the current effort seeks to extend the life of a network by selecting the most appropriate cluster head. A new cost function for homogenous dispersion of cluster heads was proposed in this research, and a good balance among exploration and exploitation search skills to create a node clustering protocol based on chicken search. This procedure is a big step forward from previous state-of-the-art protocols. The number of packets received, the total power consumption, the number of active nodes, and the latency of the suggested integrated clustered routing protocol are all used to evaluate the protocol's overall performance. The proposed strategy has been demonstrated to improve power consumption by at least 16 percent.