Jafari Navimipour, Nima
Loading...
Profile URL
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
Jafari Navimipour, Nima Jafari
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
Jafari Navimipour, Nima Jafari
Job Title
Doç. Dr.
Email Address
Main Affiliation
Computer Engineering
Computer Engineering
05. Faculty of Engineering and Natural Sciences
01. Kadir Has University
Computer Engineering
05. Faculty of Engineering and Natural Sciences
01. Kadir Has University
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
15
LIFE ON LAND
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
10
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
18
Research Products
4
QUALITY EDUCATION
0
Research Products
2
ZERO HUNGER
5
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
1
NO POVERTY
0
Research Products
5
GENDER EQUALITY
0
Research Products
14
LIFE BELOW WATER
2
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
10
REDUCED INEQUALITIES
1
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
5
Research Products
13
CLIMATE ACTION
1
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
9
Research Products
3
GOOD HEALTH AND WELL-BEING
12
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output
115
Articles
102
Views / Downloads
45/0
Supervised MSc Theses
3
Supervised PhD Theses
1
WoS Citation Count
3293
Scopus Citation Count
4123
WoS h-index
32
Scopus h-index
34
Patents
0
Projects
0
WoS Citations per Publication
28.63
Scopus Citations per Publication
35.85
Open Access Source
30
Supervised Theses
4
| Journal | Count |
|---|---|
| Nano Communication Networks | 6 |
| Sustainable Computing-Informatics & Systems | 5 |
| Cluster Computing | 5 |
| Multimedia Tools and Applications | 4 |
| International Journal of Communication Systems | 4 |
Current Page: 1 / 14
Scopus Quartile Distribution
Competency Cloud
115 results
Scholarly Output Search Results
Now showing 1 - 10 of 115
Article Citation - WoS: 22Citation - Scopus: 34A Quality-of-Service-Aware Service Composition Method in the Internet of Things Using a Multi-Objective Fuzzy-Based Hybrid Algorithm(Mdpi, 2023) Hamzei, Marzieh; Khandagh, Saeed; Navimipour, Nima Jafari; Jafari Navimipour, NimaThe Internet of Things (IoT) represents a cutting-edge technical domain, encompassing billions of intelligent objects capable of bridging the physical and virtual worlds across various locations. IoT services are responsible for delivering essential functionalities. In this dynamic and interconnected IoT landscape, providing high-quality services is paramount to enhancing user experiences and optimizing system efficiency. Service composition techniques come into play to address user requests in IoT applications, allowing various IoT services to collaborate seamlessly. Considering the resource limitations of IoT devices, they often leverage cloud infrastructures to overcome technological constraints, benefiting from unlimited resources and capabilities. Moreover, the emergence of fog computing has gained prominence, facilitating IoT application processing in edge networks closer to IoT sensors and effectively reducing delays inherent in cloud data centers. In this context, our study proposes a cloud-/fog-based service composition for IoT, introducing a novel fuzzy-based hybrid algorithm. This algorithm ingeniously combines Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC) optimization algorithms, taking into account energy consumption and Quality of Service (QoS) factors during the service selection process. By leveraging this fuzzy-based hybrid algorithm, our approach aims to revolutionize service composition in IoT environments by empowering intelligent decision-making capabilities and ensuring optimal user satisfaction. Our experimental results demonstrate the effectiveness of the proposed strategy in successfully fulfilling service composition requests by identifying suitable services. When compared to recently introduced methods, our hybrid approach yields significant benefits. On average, it reduces energy consumption by 17.11%, enhances availability and reliability by 8.27% and 4.52%, respectively, and improves the average cost by 21.56%.Article Citation - WoS: 33Citation - Scopus: 38Implementation of a Product-Recommender System in an Iot-Based Smart Shopping Using Fuzzy Logic and Apriori Algorithm(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Yan, Shu-Rong; Pirooznia, Sina; Heidari, Arash; Navimipour, Nima Jafari; Unal, MehmetThe Internet of Things (IoT) has recently become important in accelerating various functions, from manufacturing and business to healthcare and retail. A recommender system can handle the problem of information and data buildup in IoT-based smart commerce systems. These technologies are designed to determine users' preferences and filter out irrelevant information. Identifying items and services that customers might be interested in and then convincing them to buy is one of the essential parts of effective IoT-based smart shopping systems. Due to the relevance of product-recommender systems from both the consumer and shop perspectives, this article presents a new IoT-based smart product-recommender system based on an apriori algorithm and fuzzy logic. The suggested technique employs association rules to display the interdependencies and linkages among many data objects. The most common use of association rule discovery is shopping cart analysis. Customers' buying habits and behavior are studied based on the numerous goods they place in their shopping carts. As a result, the association rules are generated using a fuzzy system. The apriori algorithm then selects the product based on the provided fuzzy association rules. The results revealed that the suggested technique had achieved acceptable results in terms of mean absolute error, root-mean-square error, precision, recall, diversity, novelty, and catalog coverage when compared to cutting-edge methods. Finally, themethod helps increase recommender systems' diversity in IoT-based smart shopping.Article Citation - WoS: 53Citation - Scopus: 58A hybrid approach for latency and battery lifetime optimization in IoT devices through offloading and CNN learning(Elsevier, 2023) Heidari, Arash; Navimipour, Nima Jafari; Jamali, Mohammad Ali Jabraeil; Akbarpour, ShahinOffloading assists in overcoming the resource constraints of specific elements, making it one of the primary technical enablers of the Internet of Things (IoT). IoT devices with low battery capacities can use the edge to offload some of the operations, which can significantly reduce latency and lengthen battery lifetime. Due to their restricted battery capacity, deep learning (DL) techniques are more energy-intensive to utilize in IoT devices. Because many IoT devices lack such modules, numerous research employed energy harvester modules that are not available to IoT devices in real-world circumstances. Using the Markov Decision Process (MDP), we describe the offloading problem in this study. Next, to facilitate partial offloading in IoT devices, we develop a Deep Reinforcement learning (DRL) method that can efficiently learn the policy by adjusting to network dynamics. Convolutional Neural Network (CNN) is then offered and implemented on Mobile Edge Computing (MEC) devices to expedite learning. These two techniques operate together to offer the proper offloading approach throughout the length of the system's operation. Moreover, transfer learning was employed to initialize the Qtable values, which increased the system's effectiveness. The simulation in this article, which employed Cooja and TensorFlow, revealed that the strategy outperformed five benchmarks in terms of latency by 4.1%, IoT device efficiency by 2.9%, energy utilization by 3.6%, and job failure rate by 2.6% on average.Review Citation - WoS: 15Citation - Scopus: 29Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Mohammadian, Vahid; Navimipour, Nima Jafari; Hosseinzadeh, Mehdi; Darwesh, AsoNowadays, cloud computing is growing daily and has been developed as an effective and flexible paradigm in solving large-scale problems. It has been known as an Internet-based computing model in which computing and virtual resources, such as services, applications, storage, servers, and networks, are shared among numerous cloud users. Since the number of cloud users and their requests are increasing rapidly, the loads on the cloud systems may be underloaded or overloaded. These situations cause different problems, such as high response time and power consumption. To handle the mentioned problems and improve the performance of cloud servers, load balancing methods have a significant impact. Generally, a load balancing method aims to identify under-loaded and overloaded nodes and balance the load among them. In the recent decade, this problem has attracted a lot of interest among researchers, and several solutions have been proposed. Considering the important role of fault-tolerant in load balancing algorithms, there is a lack of an organized and in-depth study in this field yet. This gap prompted us to provide the current study aimed to collect and review the available papers in the field of fault tolerance load balancing methods in cloud computing. The existing algorithms are divided into two categories, namely, centralized and distributed, and reviewed based on vital qualitative parameters, such as scalability, makespan, reliability, resource utilization, throughput, and overhead. In this regard, other criteria such as the type of detected faults and adopted simulation tools are taken into account.Article Citation - WoS: 13Citation - Scopus: 12Leveraging Explainable Artificial Intelligence for Transparent and Trustworthy Cancer Detection Systems(Elsevier, 2025) Toumaj, Shiva; Heidari, Arash; Navimipour, Nima Jafari; Jafari Navimipour, NimaTimely 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.Article Citation - WoS: 3Citation - Scopus: 3Sustainable IoT Solutions: Developing a Quantum-Aware Circuit for Improving Energy Efficiency Based on Atomic Silicon(Elsevier, 2025) Rasmi, Hadi; Ahmadpour, Seyed Sajad; Seyyedabbasi, Amir; Navimipour, Nima Jafari; Khan, Wasiq; Jafari Navimipour, NimaInternet of Things (IoT) can be described as a network of physical objects equipped with sensors, processing power, software, and any other types of technology that allows them to communicate and share data with other devices and systems. The proliferation of IoT is conditional on developing energy-saving blocks of computation with sustained connectivity and real-time information processing capabilities. Traditional technologies like CMOS and VLSI circuits face critical failures at scales below 4 nm, including excessive current leakages, high energy consumption, and thermal instability, which make them less appropriate for future micro-scale IoT chips. To overcome such limitations, a new alternative technology called Atomic Silicon Dangling Bond (ASDB) nanotechnology has been developed, leveraging atomistic accuracy in countering CMOS-related inefficiencies and supporting quantum-inspired computational processes. Since Arithmetic and Logic Unit (ALU) is a primary unit of any digital system like IoT, this work introduces the necessity of quantum-aware ALU development, taking a quantum-inspired computational mechanism and leveraging ASDB's native quantum behavior for increased performance, accuracy, and efficiency in IoT systems. A single-bit ALU for micro-IoT blocks is developed using ASDB nanotechnology with robust computational design to guarantee operational integrity. The design is analyzed through SiQAD simulator in terms of energy consumption, logical accuracy, and area consumption. The proposed ALU in this work demonstrates a reduction in occupied area and quantum cell count, highlighting a significant step toward ultra-dense integration. Furthermore, with an energy consumption reduction of 3.19% compared to the best design, this ALU offers a sustainable and practical solution for lowpower IoT applications in the future.Letter Citation - WoS: 49Citation - Scopus: 55Everything You Wanted To Know About Chatgpt: Components, Capabilities, Applications, and Opportunities(John Wiley & Sons Ltd, 2024) Heidari, Arash; Navimipour, Nima Jafari; Zeadally, Sherali; Chamola, VinayConversational 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.Article Citation - WoS: 10Citation - Scopus: 13Nano-Design of Ultra-Efficient Reversible Block Based on Quantum-Dot Cellular Automata(Zhejiang Univ Press, 2023) Ahmadpour, Seyed Sajad; Navimipour, Nima Jafari; Mosleh, Mohammad; Yalcin, SenayReversible logic has recently gained significant interest due to its inherent ability to reduce energy dissipation, which is the primary need for low-power digital circuits. One of the newest areas of relevant study is reversible logic, which has applications in many areas, including nanotechnology, DNA computing, quantum computing, fault tolerance, and low-power complementary metal-oxide-semiconductor (CMOS). An electrical circuit is classified as reversible if it has an equal number of inputs and outputs, and a one-to-one relationship. A reversible circuit is conservative if the EXOR of the inputs and the EXOR of the outputs are equivalent. In addition, quantum-dot cellular automata (QCA) is one of the state-of-the-art approaches that can be used as an alternative to traditional technologies. Hence, we propose an efficient conservative gate with low power demand and high speed in this paper. First, we present a reversible gate called ANG (Ahmadpour Navimipour Gate). Then, two non-resistant QCA ANG and reversible fault-tolerant ANG structures are implemented in QCA technology. The suggested reversible gate is realized through the Miller algorithm. Subsequently, reversible fault-tolerant ANG is implemented by the 2DW clocking scheme. Furthermore, the power consumption of the suggested ANG is assessed under different energy ranges (0.5Ek, 1.0Ek, and 1.5Ek). Simulations of the structures and analysis of their power consumption are performed using QCADesigner 2.0.03 and QCAPro software. The proposed gate shows great improvements compared to recent designs.Master Thesis Kuantum Teknolojisine Dayalı Görüntü Steganografisi(2025) Salahov, Huseyn; Navimipour, Nima JafariSteganografi, bilgilerin bir örtü ortamında gizlenerek tespit edilmeden saklandığı bir veri gizleme tekniğidir. Bu tür tekniklerin performansını değerlendiren önemli bir ölçüt, gizli mesajın tespit edilmesine karşı direnç, yani güvenliktir. Güvenli steganografi tekniklerinden biri, görüntü maskelenmesidir. Bu yöntemde, bir görüntü önce rastgele bir anahtar ile şifrelenerek şifreli bir görüntü elde edilir. Ardından, bu şifreli görüntü, orijinal görüntü kullanılarak tekrar şifrelenir ve anahtarın yerine geçen bir maske üretilir. Bu süreç, anahtarın gizli kalmasını sağlar ve yöntemin güvenliğini artırır. Bu algoritmalar, kırmızı, yeşil ve mavi (RGB) kanalları ayrı ayrı işlenerek renkli görüntüler üzerinde gerçekleştirilecek ve üç şifreli kanal ile üç maske kanalı elde edilecektir. Geleneksel olarak, steganografi, tamamlayıcı metal-oksit-yarı iletken (CMOS) transistörleri ve çok büyük ölçekli tümleşik devre (VLSI) donanımı kullanılarak uygulanır. Ancak, VLSI'nin yonga yoğunluğundan kaynaklanan aşırı ısınma gibi doğal sorunları nedeniyle, kuantum teknolojileri, steganografide VLSI'nin yerini alabilecek yeni nesil teknolojiler olarak değerlendirilmektedir. Alternatif olarak, kuantum nokta hücresel otomataları (QCA), steganografik sistemleri güç analizi saldırılarına karşı korumak için kritik olan yüksek hız, bütünlük ve düşük güç tüketimi sunar. Bu çalışmada, hem şifreleme hem de maske üretimi için kullanılan XOR kapısı temel yapı taşı olan, QCA tabanlı bir görüntü maskesi nano-tasarımı öneriyoruz. Tasarım, QCADesigner 2.0.3 yazılımı kullanılarak geliştirilmiş, şifreleme mantığı ise Python diliyle yazılmıştır. Tasarım, döndürülmemiş hücreler içeren tek katmanlı bir yapı kullanır. Görüntü kalitesini değerlendirmek için Yapısal Benzerlik İndeksi (SSIM) ve Yapısal Farklılık İndeksi (DSSIM) kullanılmıştır. Sonuçlarımız, önceki QCA tabanlı tasarımlara kıyasla hücre sayısında %57,3 ve alanda %40,7 azalma ile iyileşmeler gösterdi. Güvenlik analizleri, diferansiyel saldırılar dışında çeşitli saldırılara karşı artırılmış direnç sağlandığını ortaya koymuştur. Anahtar Sözcükler: Steganografi, Görüntü Maskelenmesi, QCA, XOR Kapısı, Görüntü Şifreleme, RGB, Kriptografi.Article Citation - WoS: 42Citation - Scopus: 48A New Energy-Efficient Design for Quantum-Based Multiplier for Nano-Scale Devices in Internet of Things(Pergamon-elsevier Science Ltd, 2024) Ahmadpour, Seyed-Sajad; Noorallahzadeh, Mojtaba; Al-Khafaji, Hamza Mohammed Ridha; Darbandi, Mehdi; Navimipour, Nima Jafari; Javadi, Bahman; Yalcin, Senay; Jafari Navimipour, NimaAn enormous variety of items and things are connected via wired or wireless connections and specific addressing schemes, which is known as the Internet of Things (IoT). However, IoT devices that adopt aggressive duty-cycling for high power efficiency and prolonged lifespan necessitate the incorporation of ultra-low power consumption always-on blocks. The multiplier plays a crucial role in enhancing the capabilities of low-power IoT devices, particularly those operating with energy-efficient batteries that offer extended battery life. The previous multipliers have a struggling speed, enormous occupied area, and high energy consumption; therefore, all prior flaws must be fixed by implementing it in a suitable technology, like the quantum computing. Therefore, this paper examines the ultra-low power circuit for nano-scale IoT platforms. It also suggests novel quantum-based adders for multiplier structure. The proposed designs are simulated using the QCADesignerE 2.2 tool by focusing on energy-efficient and occupied areas for miniaturizing IoT systems.
