Nima Jafari Navimipour

Jafari Navimipour, Nima

Name Variants

Jafari Navimipour,Nima
JAFARI NAVIMIPOUR, Nima
N. Jafari Navimipour
Jafari Navimipour, Nima
Jafari Navimipour,N.
J.,Nima
JAFARI NAVIMIPOUR, NIMA
Jafari Navimipour, N.
Nima Jafari Navimipour
Nima JAFARI NAVIMIPOUR
Jafari Navimipour, NIMA
Jafari Navimipour N.
NIMA JAFARI NAVIMIPOUR
J., Nima
Nima, Jafari Navimipour
Navimipour, Nima Jafari
Navimipour, N.J.
Navimpour, Nima Jafari
Navımıpour, Nıma Jafarı

Job Title

Doç. Dr.

Email Address

nima.navimipour@khas.edu.tr

Full item page

Scholarly Output

86

Articles

69

Citation Count

32

Supervised Theses

1 Scholarly Output Search Results

Now showing 1 - 10 of 86

Multimedia big data computing mechanisms: a bibliometric analysis
(Springer, 2023) Rivai, Faradillah Amalia; Jafari Navimipour, Nima; 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.
A New Fog-Based Transmission Scheduler on the Internet of Multimedia Things Using a Fuzzy-Based Quantum Genetic Algorithm
(IEEE Computer Society, 2023) Zanbouri, K.; Jafari Navimipour, Nima; Al-Khafaji, H.M.R.; Jafari Navimipour, N.; Yalcin, S.
The Internet of Multimedia Things (IoMT) has recently experienced a considerable surge in multimedia-based services. Due to the fast proliferation and transfer of massive data, the IoMT has service quality challenges. This paper proposes a novel fog-based multimedia transmission scheme for IoMT using the Sugano interference system with a quantum genetic optimization algorithm. The fuzzy system devises a mathematically organized strategy for generating fuzzy rules from input and output variables. The Quantum Genetic Algorithm (QGA) is a metaheuristic algorithm that combines genetic algorithms and quantum computing theory. It combines many critical elements of quantum computing, such as quantum superposition and entanglement. This provides a robust representation of population diversity and the capacity to achieve rapid convergence and high accuracy. As a result of the simulations and computational analysis, the proposed fuzzy-based QGA scheme improves packet delivery ratio and throughput by reducing end-to-end latency and delay when compared to traditional algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Heterogeneous Earliest-Finish-Time (HEFT) and Ant Colony Optimization (ACO). Consequently, it provides a more efficient scheme for multimedia transmission in IoMT. IEEE
Adventures in Data Analysis: a Systematic Review of Deep Learning Techniques for Pattern Recognition in Cyber-Physical Systems
(Springer, 2023) Amiri, Zahra; Jafari Navimipour, Nima; Heidari, Arash; Navimipour, Nima Jafari; Unal, Mehmet; Mousavi, Ali
Machine Learning (ML) and Deep Learning (DL) have achieved high success in many textual, auditory, medical imaging, and visual recognition patterns. Concerning the importance of ML/DL in recognizing patterns due to its high accuracy, many researchers argued for many solutions for improving pattern recognition performance using ML/DL methods. Due to the importance of the required intelligent pattern recognition of machines needed in image processing and the outstanding role of big data in generating state-of-the-art modern and classical approaches to pattern recognition, we conducted a thorough Systematic Literature Review (SLR) about DL approaches for big data pattern recognition. Therefore, we have discussed different research issues and possible paths in which the abovementioned techniques might help materialize the pattern recognition notion. Similarly, we have classified 60 of the most cutting-edge articles put forward pattern recognition issues into ten categories based on the DL/ML method used: Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Generative Adversarial Network (GAN), Autoencoder (AE), Ensemble Learning (EL), Reinforcement Learning (RL), Random Forest (RF), Multilayer Perception (MLP), Long-Short Term Memory (LSTM), and hybrid methods. SLR method has been used to investigate each one in terms of influential properties such as the main idea, advantages, disadvantages, strategies, simulation environment, datasets, and security issues. The results indicate most of the articles were published in 2021. Moreover, some important parameters such as accuracy, adaptability, fault tolerance, security, scalability, and flexibility were involved in these investigations.
A Secure Intrusion Detection Platform Using Blockchain and Radial Basis Function Neural Networks for Internet of Drones
(IEEE-Inst Electrical Electronics Engineers Inc, 2023) Jafari Navimipour, Nima; Navimipour, Nima Jafari; Unal, Mehmet
The Internet of Drones (IoD) is built on the Internet of Things (IoT) by replacing Things with Drones while retaining incomparable features. Because of its vital applications, IoD technologies have attracted much attention in recent years. Nevertheless, gaining the necessary degree of public acceptability of IoD without demonstrating safety and security for human life is exceedingly difficult. In addition, intrusion detection systems (IDSs) in IoD confront several obstacles because of the dynamic network architecture, particularly in balancing detection accuracy and efficiency. To increase the performance of the IoD network, we proposed a blockchain-based radial basis function neural networks (RBFNNs) model in this article. The proposed method can improve data integrity and storage for smart decision-making across different IoDs. We discussed the usage of blockchain to create decentralized predictive analytics and a model for effectively applying and sharing deep learning (DL) methods in a decentralized fashion. We also assessed the model using a variety of data sets to demonstrate the viability and efficacy of implementing the blockchain-based DL technique in IoD contexts. The findings showed that the suggested model is an excellent option for developing classifiers while adhering to the constraints placed by network intrusion detection. Furthermore, the proposed model can outperform the cutting-edge methods in terms of specificity, F1, recall, precision, and accuracy.
Quantum-based serial-parallel multiplier circuit using an efficient nano-scale serial adder
(Soc Microelectronics, Electron Components Materials-midem, 2024) Jafari Navimipour, Nima; 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.
Evaluating the Effect of Human Factors on Big Data Analytics and Cloud of Things Adoption in the Manufacturing Micro, Small, and Medium Enterprises
(IEEE Computer Soc, 2022) Jafari Navimipour, Nima; Gardas, Bhaskar B.; Narwane, Vaibhav S.; Navimipour, Nima Jafari; Yalcin, Senay
The purpose of the study is to explore and analyze human factors that influence big data analytics and the cloud of things adoption across Indian micro, small, and medium enterprises (MSMEs). The human factors were identified through a literature survey and experts' opinions. In order to develop a hierarchical structural model of identified human factors indicating the mutual relationship and classify the factors into cause-effect groups, a hybrid ISM-DEMATEL approach has been employed. Results of the study stated that Lack of training and development programs (HF11), Lack of vision of top management and ineffective corporate governance (HF13), and Communication barrier between management and workforce (HF4) are the most significant factors. The study's findings would be helpful to human resource managers and decision-makers of the firm to understand human-related factors responsible for technology adoption. Further, results can be validated with the investigation in other emerging economies.
Blockchain Systems in Embedded Internet of Things: Systematic Literature Review, Challenges Analysis, and Future Direction Suggestions
(Mdpi, 2022) Darbandi, Mehdi; Jafari Navimipour, Nima; 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.
The role of new ICT-based systems in modern management special issue editors
(Cambridge Univ Press, 2023) Jafari Navimipour, Nima; 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.
A Radio Frequency Identification Reader Collision Avoidance Protocol for Dense Reader Environments in the Context of Industry 4.0
(Wiley, 2023) Rezaie, Hadiseh; Jafari Navimipour, Nima; 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.
A New Nano-Design of 16-Bit Carry Look-Ahead Adder Based on Quantum Technology
(Iop Publishing Ltd, 2023) Ahmadpour, Seyed-Sajad; Jafari Navimipour, Nima; 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.