Wireless Personal Communications
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SCImago
Q2
WOS
Q3
Impact factor
1.9
SJR
0.588
CiteScore
5.8
Categories
Computer Science Applications
Electrical and Electronic Engineering
Areas
Computer Science
Engineering
Years of issue
1994-2025
journal names
Wireless Personal Communications
WIRELESS PERS COMMUN
Top-3 citing journals

Wireless Personal Communications
(10440 citations)

IEEE Access
(4289 citations)

Sensors
(2478 citations)
Top-3 organizations

Anna University
(216 publications)

SRM Institute of Science and Technology
(197 publications)

Vellore Institute of Technology University
(192 publications)

Vellore Institute of Technology University
(139 publications)

SRM Institute of Science and Technology
(129 publications)

Anna University
(93 publications)
Top-3 countries
Most cited in 5 years
Found
Publications found: 607
Q3

An adaptive anti-predatory algorithm-based model to enhance the efficiency of software effort estimation
Sharma A., Rajpoot D.S.
Q3
Innovations in Systems and Software Engineering
,
2025
,
citations by CoLab: 0

Q3

Access-adaptive priority search tree
Massa H., Uhlmann J.
In this paper we introduce the notion of explicit worst-case bounded adaptive algorithms for applications with fixed process-completion requirements. Such applications demand that a process be guaranteed to complete within an established time interval while adaptively reducing computational overhead during that interval, e.g., so as to reduce total energy usage. Our principal contribution is the Access-Adaptive Priority Search Tree (AAPST), which can provide efficient distribution-sensitive performance comparable to the splay tree, but do so within strict—and $$O(\log n)$$ optimal—worst-case per-query bounds. More specifically, while the splay tree is conjectured to offer optimal adaptive amortized query complexity, it may require O(n) for individual queries, whereas the AAPST offers competitive distribution-sensitive performance with strict $$O(\log n)$$ time complexity. This makes the AAPST more suitable for certain interactive (e.g., online and real-time) applications such as space system modules with reliability constraints involving rigid process-completion time intervals with secondary energy-minimization incentives.
Q3

Discovering smell relations between temporary field and design smells: an empirical analysis
Gupta R.
Code smells have an adverse impact on the quality of source code. Martin Fowler initially identified a set of 22 code smells. Since the term "code smell", there have been multiple attempts to understand them through their detection and to discover relationships between them using correlation and other approaches. The literature demonstrates multiple studies in which code smells have been found to exhibit relationships with other code smells. Nevertheless, the temporary field is one of the 22 code smells that has not been analysed to determine its relationship with other code smells. It is important to consider temporary field, as it has a detrimental impact on the maintainability of the source code. The study has conducted a review of the 7 smell relations identified by Pietrzak and Walter and proposed 3 new smell relations. It has evaluated these smell relations between temporary field and 17 design smells in 10 popular open-source Java applications that are widely cited in the literature and publicly accessible. The study has also done a correlation analysis of temporary field with 17 design smells. All code smells in the study were detected using an open-source tool called "TFfinder". The study reveals 18 significant smell relations between temporary field and design smells. Utilization of smell relations can facilitate an in-depth comprehension of code smells and aid in the prioritization of code smells for refactoring purposes. In addition, it can assist a developer in identifying classes that need more maintenance effort and impact the maintainability of the code.
Q3

Towards variability process model for agile product line configuration engineering
Kiani A.A., Hafeez Y., Hashmi A.S., Iqbal J.
Integration of Software Product Line (SPL) and Agile Software Development (ASD) results in a new direction called Agile Product Line Engineering (APLE). Even though some studies in the literature have suggested efficient methods for integrating ASD and SPL, they have not yet addressed every facet of APLE’s characteristics, and these methods hardly ever take into account the SPL configuration process or the reuse of software resources when developing new products or expanding existing product lines. Despite extensive research efforts, a unified and holistic APLE methodology that integrates agile concepts across both Application Engineering (AE) and Domain Engineering (DE) phases remains elusive. Given this, we suggest a new APLE methodology to integrate ASD and SPL more effectively. The suggested approach iteratively builds the product line, and the system architecture grows over time. We have outlined a new variability mechanism called Variability on DemAnd (VODA) to boost the SPL configuration process. We performed the two-phased evaluation. (1) In the first phase, we considered empirical investigation to validate the proposed APLE methodology. We performed a randomized experiment to compare the proposed approach to a traditional system that typically applies agile principles within a proactive SPL but lacks agile-based variability mechanisms, dynamic product line architectures, and robust feedback. (2) In second phase, the proposed algorithm is tested for efficiency, performance, and effectiveness. We conduct the experiments to evaluate the proposed process (VODA) and obtained results are evaluated with Precision, Recall, Accuracy, and F-Measure. The findings indicate that the suggested approach offers benefits such as adaptable demand management, improved software resource reuse, lower configuration costs, and a shorter time to market. The second step (i.e. second phase of evaluation) results confirm the effectiveness of the proposed algorithm. The average precision value is 0.887, the average Recall value is 0.884 and the average F-Measure value is 0.878%.
Q3

Anomaly detection in software-defined networking utilizing multi-verse deer hunting optimization enabled deep q-network for traffic flow rate prediction
Raja N.M., Vegad S.
For the consolidated management and supervising of massive networks, software-defined networking (SDN) is seen to be the best option. Nonetheless, it should be highlighted that SDN design experiences the same security problems as conventional networks. To bridge this gap, an efficient model for anomaly detection (AD) in SDN named Multi-verse Deer Hunting Optimization (MVDHO) is introduced. Firstly, SDN nodes are simulated. After that, SDN switches are controlled by the control plane to identify the condition of switches like ON, IDLE, or OFF conditions based on the detection plane. Secondly, the detection plane module consists of two modules, such traffic flow detection and AD. In the detection plane, the SDN switch flow rate is recorded in the form of time-series data and the condition of the switch is predicted based on time-series data using Deep Long short-term memory (LSTM). Similarly, in AD, the behaviour of the communication is recorded as a log file by extracting the significant features. Moreover, appropriate features are selected by mutual information. Finally, the detection of anomaly is performed employing Deep Q-Network, which is trained using MVDHO. Here, MVDHO is obtained by the combination of a Multi-verse Optimizer (MVO) and Deer Hunting Optimization Algorithm (DHOA). The detected anomalies are Denial of Service (DoS), Buffer_overflow, Guess_password, SQL attack and Named attack. The metrics utilized in this research namely, Traffic flow detection accuracy (TFDA), accuracy, true positive rate (TPR), and true negative rate (TNR) attained maximum values with 91.6%, 94.7%, 90.8%, and 86.5%, and also, the minimum value of computational time is 52.99s.
Q3

Taming the frame problem: an automated approach for robust UML class diagram specification and verification
Rosales Viesca A., Al Lail M.
AbstractIt is vital to have precise specifications and verification of UML class diagrams to ensure the correctness of complex software systems. However, current specification and verification methods often face a challenge known as the frame problem. This problem occurs due to incomplete operation specifications that can lead to unintended system behavior. To tackle this issue, we have developed an automated solution to autonomously identify and define frame conditions, effectively minimizing the frame problem’s impact on class diagram verification. Frame conditions are explicit contracts that meticulously outline the permissible effects of operations within the system. Our approach carefully analyzes the behavioral blueprint of a class diagram and extracts crucial information to create these conditions. Through rigorous evaluations encompassing diverse UML diagrams and simulated execution scenarios, we have demonstrated the effectiveness of our approach in preventing unintended system behavior caused by the frame problem. We have integrated the approach into the Temporal Property Validator tool, empowering practitioners to leverage its benefits for practical class diagram specification and verification.
Q3

Comparative analysis of various fuzzy clustering algorithms for linearly and non-linearly separable data
Sethia K., Gosain A., Singh J.
Fuzzy clustering is an unsupervised technique in which an object belongs to more than one cluster. In this paper, we have implemented and compared eight fuzzy clustering algorithms, FCM, IFCM, KFCM, and KIFCM with the Euclidean distance metric and same algorithms with the weighted mean distance metric, i.e., FCM-ϭ, IFCM-ϭ, KFCM-ϭ, and KIFCM-ϭ. None of the previous reviews in the literature have assessed the effectiveness of these algorithms on linearly and nonlinearly separable data. So, in this comparative analysis, we are focusing on data separability, also considering other factors such as noise-free and noisy data, the presence, and absence of outliers (if any), as well as clusters of varied size, shape, and density. We have conducted the experiment on twelve 2-D synthetic datasets and five real datasets from the UCI repository. It is observed that for linearly separable data, KIFCM and IFCM-ϭ perform considerably better in the presence of noise and outliers whereas for non-linearly separable data, KFCM, KFCM-ϭ, KIFCM, and KIFCM-ϭ perform better.
Q3

A Multimodal conceptual framework to achieve automated software evolution for context-rich intelligent applications
Yue S.
AbstractWhile AI is extensively transforming Software Engineering (SE) fields, SE is still in need of a framework to consider overall all phases to facilitate Automated Software Evolution (ASEv), particularly for intelligent applications that are context-rich instead of conquering each division independently. Its complexity comes from the intricacy of the intelligent applications, the heterogeneity of the data sources, and the constant changes in the context. This study proposes a conceptual framework for achieving automated software evolution, emphasizing the importance of multimodality learning. A Selective Sequential Scope Model (3 S) model is developed based on the conceptual framework, and it can be used to categorize existing and future research when it covers different SE phases and multimodal learning tasks. This research is a preliminary step toward the blueprint of a higher-level ASEv. The proposed conceptual framework can act as a practical guideline for practitioners to prepare themselves for diving into this area. Although the study is about intelligent applications, the framework and analysis methods may be adapted for other types of software as AI brings more intelligence into their life cycles.
Q3

Design and application of a novel Improved Fire Hawk Optimization technique-tuned ANFIS for optimal regulation of energy of a composite microgrid system
Bandopadhyay J., Roy P.K.
The operation of hybrid microgrid systems without sufficient control can result in system synchronization issues within renewable energy sources (RESs) and the power network. This impact on the synchronization can drastically affect the whole equilibrium, stability, and reliability. Hence, to eliminate such issues, this paper has focussed on the development of a novel, improved fire hawk optimization technique (IFHOT) for preparing three ANFIS regulators for a stable energy management system of a utility network-connected hybrid non-conventional system. The hybrid system features the combination of a battery unit + wind power generator (W) + photovoltaic (PV) array + fuel cell (FC) stack. The IFHOT-trained ANFIS-based monitoring control system determines the switching of the various RESs, thereby regulating the power they generate. Load power requirement, grid power need, and condition of the battery, also known as SOC, are considered for the operation of the ANFIS-based management system. The research work carried out here aims to optimize the switching and power generation of the various RESs. It also ensures fast instability mitigation that can be observed from the voltage, current, and power graphs. Furthermore, successful comparisons with other intelligent controllers, such as fire hawk optimization technique (FHOT) tuned ANFIS and circle search algorithm (CSA) tuned ANFIS, are executed in the proposed work. Concerning voltage, current, power control and harmonics alleviation, IFHOT-tuned ANFIS has yielded superior results compared to FHOT-tuned ANFIS and CSA-tuned ANFIS. All the experiments have been performed on the MATLAB/SIMULINK platform.
Q3

Publisher Correction: Distributed Petri nets for model-driven verifiable robotic applications in ROS
Ebert S., Mey J., Schöne R., Götz S., Aßmann U.
Q3
Innovations in Systems and Software Engineering
,
2024
,
citations by CoLab: 0

Q3

Empowering model repair: a rule-based approach to graph repair without side effects—extended version
Lauer A., Kosiol J., Taentzer G.
AbstractWorking with models can lead to inconsistencies, e.g., due to erroneous or contradictory actions during concurrent modeling processes. Modern modeling environments typically tolerate inconsistencies and support their detection. However, at a later stage of development, models are expected to be consistent, meaning their inconsistencies should be considered and resolved. The process of resolving model inconsistencies is commonly referred to as model repair. Our approach to model repair is semi-automatic in the sense that the repair tool computes appropriate repair plans and the modeler decides which path to take. The speciality of our approach is that the repair process can register any small improvement in the model. This allows the interaction with the user to be optimized, resulting in an approach with a high level of automation on the one hand and flexible configuration options on the other. The approach focuses on providing repair plans that do not have side effects, i.e., the computed repair plans do not inadvertently introduce a new inconsistency of already repaired constraints into the model. Since models often have a graph-like structure, we present our approach to model repair based on graphs. Our approach is completely formal—we use the algebraic graph transformation approach to prove its correctness. We also present a prototype implementation of our repair approach based on the Eclipse Modeling Framework and Henshin, a model transformation engine based on graph transformation, to perform the actual model repair. A first performance evaluation shows that graphs with up to 1000 nodes can be repaired in about 10 s.
Q3

Classification of functional and nonfunctional requirements based on convolutional neural network with flower pollination optimizer
Sonawane S.N., Puthran S.M.
Accurate and efficient classification of software requirements is crucial for the success of system, as functional and nonfunctional requirements define the fundamental characteristics and constraints of a system. Documenting software requirements in natural language can lead to uncertainties such as ambiguity, inconsistency, or poor readability. Additionally, manual extraction of requirements can be tedious and prone to errors due to the need for precise interpretation, which increases the risk of miscommunication and mistakes during the development process. So, it is vital to use effective techniques like natural language processing to clearly understand the requirements. This paper proposes the use of deep learning models in conjunction with natural language processing, followed by flower pollination optimizer, to automate the classification task. The methodology leverages natural language processing to extract meaningful features used to train a convolutional neural network model. The convolution neural network model is enhanced using the flower pollination optimizer algorithm to ensure better convergence. The approach is implemented using an industry SmartNet dataset. To tackle the challenge of class imbalance, the synthetic minority oversampling technique is used. The approach is validated on both balanced and unbalanced datasets to demonstrate its effectiveness. Results show that the CNN-FPO framework performs exceptionally well, with accuracies ranging between 94.48% and 97.13% for balanced and 87.45% to 98% for unbalanced dataset.
Q3

Optimization of time-dependent MORRAP for series–parallel system using improved NSGA-II in interval environment
De S.
This research proposes a novel time-dependent interval-valued function-based multi-objective reliability redundancy allocation problem (TIVF-MORRAP) focused on multi-stage series–parallel systems. Time is a critical factor in assessing system reliability and cost. The novel contribution of this study is the use of an interval-valued function (IVF) approach to manage uncertainties in component reliability, cost, and repair costs, with time as a key variable. The objective is to boost system reliability and minimize costs over time by efficiently allocating redundant components at each stage. The process ensures a restricted allocation of duplicates across all stages and the entire system. In this problem the reduction in component reliability and cost are modeled by the varying radius length along the inverse logarithmic spiral over time. Likewise, the escalation in component repair costs is depicted by the logarithmic spiral. In this study, NSGA-II-AGDV is introduced, a multi-objective evolutionary algorithm (MOEA) that combines NSGA-II (Non-dominated Sorting Genetic Algorithm-II) with agglomerative and divisive clustering algorithms and the Topsis method to solve the problem. Unlike NSGA-II, which utilizes crowding distance, many researchers have adopted a single clustering technique to improve diversity and limit the solution set size. The proposed algorithm integrates two clustering techniques, enhancing functionality while also reducing execution time. A benchmark problem verifies the proposed method, showing enhanced performance and better convergence to true Pareto optimal solutions compared to NSGA-II and NSGA-II with crowding distance elimination (NSGA-II-CDE) across various time values.
Q3

ARIA-QA: AI-agent based requirements inspection and analysis through question answering
Biswas C., Das S.
Due to their predominant use of natural language, requirements are prone to defects like inconsistency and incompleteness. Consequently, quality assurance processes are commonly applied to requirements manually. However, manual execution of these processes can be laborious and may inadvertently overlook critical quality issues due to time and budget constraints. This paper introduces ARIA, an innovative question–answering (QA) approach designed to automate support for stakeholders, including requirements engineers, during the analysis of NL requirements. The ability to ask questions and get immediate answers is extremely useful in many quality assurance situations, especially for incompleteness detection. The challenge of automating the answering of requirements-related questions is considerable, given the potential scope of the search for answers extending beyond the provided requirements specification. To overcome this challenge, ARIA integrates support for mining external domain knowledge resources like internet search results. Evaluation of seven diverse use cases drawn from the PURE dataset demonstrates ARIA’s robustness and applicability across a range of real-life scenarios, highlighting its potential to significantly improve the quality and effectiveness of requirements analysis processes. This work represents one of the initial endeavors to seamlessly blend QA and external domain knowledge, effectively addressing complexities in requirements engineering through a flexible framework designed to readily integrate with evolving, advanced-level Generative LLMs.
Q3

A modified ResNet152v2 framework for bird species classification
Adhikari N., Bhattacharya S., Sultana M.
Ornithology, the study of birds, plays a crucial role in understanding the complex interplay between avian species and their ecosystems, offering insights into biodiversity and global ecological systems. In recent years, the conservation of bird species has become increasingly critical, particularly as habitat degradation poses a significant threat to endangered species. Accurate identification and classification of bird species are essential components of conservation strategies. This research presents a modified ResNet152v2 framework designed to enhance the precision and efficiency of bird species classification. By leveraging advanced deep learning techniques, this framework aims to support conservation efforts by facilitating the accurate monitoring and protection of diverse avian populations. This study introduces a transfer learning approach for bird species identification using a modified ResNet152v2 framework, leveraging a publicly available dataset of 87,874 images spanning 515 bird species. The model achieved an impressive test accuracy of 97.67% and a categorical accuracy of 98.81%. A key contribution lies in the utilization of principal component analysis (PCA) for dimensionality reduction, optimizing the feature vector by 15%. Additionally, root mean squared propagation (RMSProp) was employed to enhance the feature vector. L2 regularization and dropout at the input and the subsequent layer were introduced to mitigate overfitting. The model underwent rigorous training, resulting in a minimum training loss of 0.0397 and a validation loss of 0.0044. The achieved average precision (98.66%), recall (97.73%), and F1-score (98.2%) values further validate the model’s effectiveness. This study presents a novel combination of techniques, emphasizing the integration of transfer learning, dimensionality reduction, and dropout for improved accuracy, resulting in a robust model with potential applications in ecological research and environmental monitoring.
Top-100
Citing journals
2000
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Wireless Personal Communications
10440 citations, 9.11%
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|
IEEE Access
4289 citations, 3.74%
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Sensors
2478 citations, 2.16%
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Wireless Networks
1564 citations, 1.36%
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International Journal of Communication Systems
1390 citations, 1.21%
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Multimedia Tools and Applications
1269 citations, 1.11%
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Lecture Notes in Networks and Systems
1070 citations, 0.93%
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Electronics (Switzerland)
1053 citations, 0.92%
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Lecture Notes in Electrical Engineering
999 citations, 0.87%
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IEEE Transactions on Vehicular Technology
950 citations, 0.83%
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Wireless Communications and Mobile Computing
863 citations, 0.75%
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IEEE Transactions on Wireless Communications
812 citations, 0.71%
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Applied Sciences (Switzerland)
788 citations, 0.69%
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Lecture Notes in Computer Science
780 citations, 0.68%
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Journal of Optical Communications
742 citations, 0.65%
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Peer-to-Peer Networking and Applications
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391 citations, 0.34%
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Sustainability
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325 citations, 0.28%
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Citing publishers
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Springer Nature
31010 citations, 27.06%
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Institute of Electrical and Electronics Engineers (IEEE)
30152 citations, 26.31%
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Elsevier
11148 citations, 9.73%
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MDPI
7569 citations, 6.61%
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Wiley
4316 citations, 3.77%
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3203 citations, 2.8%
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Taylor & Francis
2017 citations, 1.76%
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IGI Global
1345 citations, 1.17%
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1043 citations, 0.91%
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803 citations, 0.7%
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SAGE
695 citations, 0.61%
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496 citations, 0.43%
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467 citations, 0.41%
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444 citations, 0.39%
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388 citations, 0.34%
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315 citations, 0.27%
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171 citations, 0.15%
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165 citations, 0.14%
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154 citations, 0.13%
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146 citations, 0.13%
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103 citations, 0.09%
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102 citations, 0.09%
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99 citations, 0.09%
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79 citations, 0.07%
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71 citations, 0.06%
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68 citations, 0.06%
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64 citations, 0.06%
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63 citations, 0.05%
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61 citations, 0.05%
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55 citations, 0.05%
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50 citations, 0.04%
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50 citations, 0.04%
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50 citations, 0.04%
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JMIR Publications
42 citations, 0.04%
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40 citations, 0.03%
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36 citations, 0.03%
|
|
33 citations, 0.03%
|
|
China Science Publishing & Media
31 citations, 0.03%
|
|
Hans Publishers
31 citations, 0.03%
|
|
Inventive Research Organization
30 citations, 0.03%
|
|
29 citations, 0.03%
|
|
Science Alert
29 citations, 0.03%
|
|
Korean Institute of Electrical Engineers
28 citations, 0.02%
|
|
Tsinghua University Press
26 citations, 0.02%
|
|
Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences
25 citations, 0.02%
|
|
American Society of Civil Engineers (ASCE)
24 citations, 0.02%
|
|
23 citations, 0.02%
|
|
Royal Society of Chemistry (RSC)
20 citations, 0.02%
|
|
Engineering and Technology Publishing
20 citations, 0.02%
|
|
Brazilian Microwave and Optoelectronics Society
20 citations, 0.02%
|
|
Engineering, Technology & Applied Science Research
20 citations, 0.02%
|
|
Instrument Society of America
18 citations, 0.02%
|
|
17 citations, 0.01%
|
|
F1000 Research
17 citations, 0.01%
|
|
American Physical Society (APS)
15 citations, 0.01%
|
|
Academy Publisher
15 citations, 0.01%
|
|
Mary Ann Liebert
14 citations, 0.01%
|
|
Arizona State University
14 citations, 0.01%
|
|
Ovid Technologies (Wolters Kluwer Health)
13 citations, 0.01%
|
|
OAE Publishing Inc.
13 citations, 0.01%
|
|
SAE International
13 citations, 0.01%
|
|
National Institute of Telecommunications
12 citations, 0.01%
|
|
American Institute of Aeronautics and Astronautics (AIAA)
11 citations, 0.01%
|
|
Shanghai Jiaotong University Press
11 citations, 0.01%
|
|
ASME International
11 citations, 0.01%
|
|
The Royal Society
10 citations, 0.01%
|
|
Acoustical Society of America (ASA)
10 citations, 0.01%
|
|
Copernicus
10 citations, 0.01%
|
|
Cold Spring Harbor Laboratory
10 citations, 0.01%
|
|
The Electrochemical Society
10 citations, 0.01%
|
|
University of Suceava
9 citations, 0.01%
|
|
conference record - asilomar conference on signals, systems and computers
9 citations, 0.01%
|
|
Ain Shams University
9 citations, 0.01%
|
|
Ediciones Universidad de Salamanca
8 citations, 0.01%
|
|
8 citations, 0.01%
|
|
8 citations, 0.01%
|
|
Institute of Measurement Science
8 citations, 0.01%
|
|
8 citations, 0.01%
|
|
Allerton Press
8 citations, 0.01%
|
|
SciELO
8 citations, 0.01%
|
|
Bonch-Bruevich State University of Telecommunications
8 citations, 0.01%
|
|
North Atlantic University Union (NAUN)
8 citations, 0.01%
|
|
7 citations, 0.01%
|
|
Japan Society of Applied Physics
7 citations, 0.01%
|
|
Vilnius Gediminas Technical University
7 citations, 0.01%
|
|
ComSIS Consortium
7 citations, 0.01%
|
|
Show all (70 more) | |
5000
10000
15000
20000
25000
30000
35000
|
Publishing organizations
50
100
150
200
250
|
|
Anna University
216 publications, 1.66%
|
|
SRM Institute of Science and Technology
197 publications, 1.51%
|
|
Vellore Institute of Technology University
192 publications, 1.47%
|
|
Aalborg University
155 publications, 1.19%
|
|
Menoufia University
144 publications, 1.1%
|
|
Thapar Institute of Engineering and Technology
141 publications, 1.08%
|
|
Beijing University of Posts and Telecommunications
137 publications, 1.05%
|
|
Xidian University
126 publications, 0.97%
|
|
Southeast University
111 publications, 0.85%
|
|
University of Electronic Science and Technology of China
110 publications, 0.84%
|
|
Indian Institute of Technology (Indian School of Mines) Dhanbad
99 publications, 0.76%
|
|
Aarhus University
93 publications, 0.71%
|
|
Koneru Lakshmaiah Education Foundation
87 publications, 0.67%
|
|
COMSATS University Islamabad
86 publications, 0.66%
|
|
Iran University of Science and Technology
83 publications, 0.64%
|
|
National Institute of Technology Kurukshetra
76 publications, 0.58%
|
|
Nanjing University of Posts and Telecommunications
76 publications, 0.58%
|
|
Mehran University of Engineering and Technology
74 publications, 0.57%
|
|
Islamic Azad University, Science and Research Branch
72 publications, 0.55%
|
|
Nanyang Technological University
72 publications, 0.55%
|
|
Islamic Azad University, Tehran
71 publications, 0.54%
|
|
University of Technology, Malaysia
68 publications, 0.52%
|
|
National Technical University of Athens
68 publications, 0.52%
|
|
University of Delhi
67 publications, 0.51%
|
|
Sathyabama Institute of Science and Technology
66 publications, 0.51%
|
|
Birla Institute of Technology, Mesra
66 publications, 0.51%
|
|
University of Science and Technology Beijing
64 publications, 0.49%
|
|
University Putra Malaysia
61 publications, 0.47%
|
|
Nanjing University of Aeronautics and Astronautics
60 publications, 0.46%
|
|
National Institute of Technology Tiruchirappalli
59 publications, 0.45%
|
|
Amirkabir University of Technology
52 publications, 0.4%
|
|
Indian Institute of Technology Kharagpur
52 publications, 0.4%
|
|
Jaypee Institute of Information Technology
52 publications, 0.4%
|
|
National Cheng Kung University
52 publications, 0.4%
|
|
Shanmugha Arts, Science, Technology & Research Academy
51 publications, 0.39%
|
|
Korea University
51 publications, 0.39%
|
|
Panjab University
49 publications, 0.38%
|
|
Delhi Technological University
47 publications, 0.36%
|
|
King Saud University
46 publications, 0.35%
|
|
National Institute of Technology Durgapur
46 publications, 0.35%
|
|
National Taiwan University of Science and Technology
45 publications, 0.34%
|
|
Sungkyunkwan University
45 publications, 0.34%
|
|
Beijing Jiaotong University
44 publications, 0.34%
|
|
PSG College of Technology
43 publications, 0.33%
|
|
University of Malaya
43 publications, 0.33%
|
|
University of Oulu
43 publications, 0.33%
|
|
Punjabi University
42 publications, 0.32%
|
|
Inha University
42 publications, 0.32%
|
|
San Francisco State University
42 publications, 0.32%
|
|
Shanghai Jiao Tong University
41 publications, 0.31%
|
|
Amity University, Noida
41 publications, 0.31%
|
|
University of Tehran
40 publications, 0.31%
|
|
Chonnam National University
40 publications, 0.31%
|
|
Oregon State University
40 publications, 0.31%
|
|
Netaji Subhas University of Technology
40 publications, 0.31%
|
|
University of Carthage
40 publications, 0.31%
|
|
Tsinghua University
39 publications, 0.3%
|
|
Jadavpur University
38 publications, 0.29%
|
|
National Institute of Technology Patna
38 publications, 0.29%
|
|
Zhejiang University
38 publications, 0.29%
|
|
Sejong University
38 publications, 0.29%
|
|
Aristotle University of Thessaloniki
38 publications, 0.29%
|
|
National Institute of Technology Rourkela
37 publications, 0.28%
|
|
Atal Bihari Vajpayee Indian Institute of Information Technology and Management
37 publications, 0.28%
|
|
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology
37 publications, 0.28%
|
|
University of Rome Tor Vergata
37 publications, 0.28%
|
|
Chandigarh University
36 publications, 0.28%
|
|
Guru Gobind Singh Indraprastha University
36 publications, 0.28%
|
|
Chongqing University of Posts and Telecommunications
36 publications, 0.28%
|
|
Chitkara University
36 publications, 0.28%
|
|
Electronics and Telecommunications Research Institute
36 publications, 0.28%
|
|
University of Ulsan
36 publications, 0.28%
|
|
Jawaharlal Nehru University
35 publications, 0.27%
|
|
Sri Sivasubramaniya Nadar College of Engineering
35 publications, 0.27%
|
|
Indian Institute of Information Technology, Allahabad
35 publications, 0.27%
|
|
Multimedia University
35 publications, 0.27%
|
|
PLA Army Engineering University
35 publications, 0.27%
|
|
National University of Malaysia
34 publications, 0.26%
|
|
Toronto Metropolitan University
34 publications, 0.26%
|
|
Khajeh Nasir Toosi University of Technology
33 publications, 0.25%
|
|
Gandhi Institute of Technology and Management
33 publications, 0.25%
|
|
Thiagarajar College of Engineering
33 publications, 0.25%
|
|
Birla Institute of Technology and Science, Pilani
32 publications, 0.25%
|
|
National Institute of Technology Silchar
32 publications, 0.25%
|
|
Jaypee University of Information Technology
32 publications, 0.25%
|
|
Jaypee University of Engineering and Technology
32 publications, 0.25%
|
|
National Taipei University of Technology
32 publications, 0.25%
|
|
National Chung Cheng University
32 publications, 0.25%
|
|
Chaoyang University of Technology
32 publications, 0.25%
|
|
Shahid Beheshti University
31 publications, 0.24%
|
|
Indian Institute of Technology Roorkee
31 publications, 0.24%
|
|
China University of Mining and Technology
31 publications, 0.24%
|
|
Central South University
31 publications, 0.24%
|
|
Cairo University
31 publications, 0.24%
|
|
Mae Fah Luang University
31 publications, 0.24%
|
|
Korea Advanced Institute of Science and Technology
31 publications, 0.24%
|
|
Chungbuk National University
31 publications, 0.24%
|
|
PLA Information Engineering University
31 publications, 0.24%
|
|
Motilal Nehru National Institute of Technology Allahabad
30 publications, 0.23%
|
|
Guru Nanak Dev University
30 publications, 0.23%
|
|
Show all (70 more) | |
50
100
150
200
250
|
Publishing organizations in 5 years
20
40
60
80
100
120
140
|
|
Vellore Institute of Technology University
139 publications, 3.09%
|
|
SRM Institute of Science and Technology
129 publications, 2.87%
|
|
Anna University
93 publications, 2.07%
|
|
Koneru Lakshmaiah Education Foundation
67 publications, 1.49%
|
|
Thapar Institute of Engineering and Technology
57 publications, 1.27%
|
|
Aarhus University
44 publications, 0.98%
|
|
Menoufia University
41 publications, 0.91%
|
|
University of Delhi
39 publications, 0.87%
|
|
Birla Institute of Technology, Mesra
38 publications, 0.85%
|
|
Delhi Technological University
35 publications, 0.78%
|
|
Sathyabama Institute of Science and Technology
34 publications, 0.76%
|
|
Amity University, Noida
34 publications, 0.76%
|
|
COMSATS University Islamabad
32 publications, 0.71%
|
|
National Institute of Technology Tiruchirappalli
31 publications, 0.69%
|
|
Shanmugha Arts, Science, Technology & Research Academy
31 publications, 0.69%
|
|
Panjab University
30 publications, 0.67%
|
|
Netaji Subhas University of Technology
30 publications, 0.67%
|
|
National Institute of Technology Patna
27 publications, 0.6%
|
|
Islamic Azad University, Tehran
27 publications, 0.6%
|
|
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology
27 publications, 0.6%
|
|
Mehran University of Engineering and Technology
26 publications, 0.58%
|
|
Indian Institute of Technology (Indian School of Mines) Dhanbad
26 publications, 0.58%
|
|
National Institute of Technology Kurukshetra
26 publications, 0.58%
|
|
Gandhi Institute of Technology and Management
25 publications, 0.56%
|
|
Chitkara University
25 publications, 0.56%
|
|
Chandigarh University
24 publications, 0.53%
|
|
Punjabi University
24 publications, 0.53%
|
|
Xidian University
24 publications, 0.53%
|
|
Lovely Professional University
22 publications, 0.49%
|
|
Islamic Azad University, Science and Research Branch
22 publications, 0.49%
|
|
Jaypee Institute of Information Technology
22 publications, 0.49%
|
|
Guru Gobind Singh Indraprastha University
22 publications, 0.49%
|
|
PSG College of Technology
22 publications, 0.49%
|
|
National Institute of Technology Silchar
21 publications, 0.47%
|
|
National Institute of Technology Durgapur
21 publications, 0.47%
|
|
Guru Nanak Dev University
21 publications, 0.47%
|
|
San Francisco State University
21 publications, 0.47%
|
|
King Khalid University
19 publications, 0.42%
|
|
Birla Institute of Technology and Science, Pilani
18 publications, 0.4%
|
|
Saveetha Institute of Medical and Technical Sciences
18 publications, 0.4%
|
|
Mepco Schlenk Engineering College
18 publications, 0.4%
|
|
Iran University of Science and Technology
17 publications, 0.38%
|
|
Motilal Nehru National Institute of Technology Allahabad
17 publications, 0.38%
|
|
Sri Sivasubramaniya Nadar College of Engineering
17 publications, 0.38%
|
|
Visvesvaraya Technological University
17 publications, 0.38%
|
|
Indian Institute of Information Technology, Allahabad
17 publications, 0.38%
|
|
Thiagarajar College of Engineering
17 publications, 0.38%
|
|
Madan Mohan Malaviya University Of Technology
17 publications, 0.38%
|
|
Tunis El Manar University
17 publications, 0.38%
|
|
University of Petroleum and Energy Studies
16 publications, 0.36%
|
|
GLA University
16 publications, 0.36%
|
|
University of Science and Technology Beijing
16 publications, 0.36%
|
|
Mae Fah Luang University
15 publications, 0.33%
|
|
Galgotias University
15 publications, 0.33%
|
|
University of Carthage
15 publications, 0.33%
|
|
King Saud University
14 publications, 0.31%
|
|
King Abdulaziz University
14 publications, 0.31%
|
|
Princess Nourah bint Abdulrahman University
14 publications, 0.31%
|
|
Jadavpur University
14 publications, 0.31%
|
|
National Institute of Technology Rourkela
14 publications, 0.31%
|
|
National Institute of Technology Hamirpur
14 publications, 0.31%
|
|
National Institute of Technology Raipur
14 publications, 0.31%
|
|
Graphic Era University
14 publications, 0.31%
|
|
Dr. A.P.J. Abdul Kalam Technical University
14 publications, 0.31%
|
|
Cadi Ayyad University
14 publications, 0.31%
|
|
Jawaharlal Nehru University
13 publications, 0.29%
|
|
Dr. B. R. Ambedkar National Institute of Technology Jalandhar
13 publications, 0.29%
|
|
Shri Mata Vaishno Devi University
13 publications, 0.29%
|
|
B.S. Abdur Rahman Crescent Institute of Science and Technology
13 publications, 0.29%
|
|
Bennett University
13 publications, 0.29%
|
|
The Islamia University of Bahawalpur
12 publications, 0.27%
|
|
Banaras Hindu University
12 publications, 0.27%
|
|
University of Hyderabad
12 publications, 0.27%
|
|
Bharathiar University
12 publications, 0.27%
|
|
Kalasalingam Academy of Research and Education
12 publications, 0.27%
|
|
Christ University
12 publications, 0.27%
|
|
Indian Institute of Engineering Science and Technology, Shibpur
12 publications, 0.27%
|
|
Karunya Institute of Technology and Sciences
12 publications, 0.27%
|
|
REVA University
12 publications, 0.27%
|
|
University of Tehran
11 publications, 0.24%
|
|
University of Sharjah
11 publications, 0.24%
|
|
Shahid Beheshti University
11 publications, 0.24%
|
|
Indian Institute of Technology Kharagpur
11 publications, 0.24%
|
|
Amrita Vishwa Vidyapeetham
11 publications, 0.24%
|
|
Savitribai Phule Pune University
11 publications, 0.24%
|
|
Malaviya National Institute of Technology Jaipur
11 publications, 0.24%
|
|
National Institute of Technology Delhi
11 publications, 0.24%
|
|
Kalinga Institute of Industrial Technology
11 publications, 0.24%
|
|
I. K. Gujral Punjab Technical University
11 publications, 0.24%
|
|
Vignan's Foundation for Science, Technology & Research
11 publications, 0.24%
|
|
Nanjing University of Aeronautics and Astronautics
11 publications, 0.24%
|
|
Lanzhou University of Technology
11 publications, 0.24%
|
|
National Engineering School of Tunis
11 publications, 0.24%
|
|
Taif University
10 publications, 0.22%
|
|
Saudi Electronic University
10 publications, 0.22%
|
|
University of Engineering and Technology, Taxila
10 publications, 0.22%
|
|
National Institute of Technology Karnataka, Surathkal
10 publications, 0.22%
|
|
Maulana Azad National Institute of Technology Bhopal
10 publications, 0.22%
|
|
National Institute of Technology Goa
10 publications, 0.22%
|
|
University of Allahabad
10 publications, 0.22%
|
|
Show all (70 more) | |
20
40
60
80
100
120
140
|
Publishing countries
500
1000
1500
2000
2500
3000
3500
4000
4500
|
|
India
|
India, 4358, 33.4%
India
4358 publications, 33.4%
|
China
|
China, 2814, 21.57%
China
2814 publications, 21.57%
|
Republic of Korea
|
Republic of Korea, 825, 6.32%
Republic of Korea
825 publications, 6.32%
|
Iran
|
Iran, 681, 5.22%
Iran
681 publications, 5.22%
|
USA
|
USA, 627, 4.81%
USA
627 publications, 4.81%
|
Pakistan
|
Pakistan, 418, 3.2%
Pakistan
418 publications, 3.2%
|
Malaysia
|
Malaysia, 321, 2.46%
Malaysia
321 publications, 2.46%
|
United Kingdom
|
United Kingdom, 320, 2.45%
United Kingdom
320 publications, 2.45%
|
Egypt
|
Egypt, 292, 2.24%
Egypt
292 publications, 2.24%
|
Denmark
|
Denmark, 278, 2.13%
Denmark
278 publications, 2.13%
|
Canada
|
Canada, 272, 2.08%
Canada
272 publications, 2.08%
|
Saudi Arabia
|
Saudi Arabia, 272, 2.08%
Saudi Arabia
272 publications, 2.08%
|
Greece
|
Greece, 233, 1.79%
Greece
233 publications, 1.79%
|
Turkey
|
Turkey, 216, 1.66%
Turkey
216 publications, 1.66%
|
Spain
|
Spain, 211, 1.62%
Spain
211 publications, 1.62%
|
France
|
France, 190, 1.46%
France
190 publications, 1.46%
|
Japan
|
Japan, 170, 1.3%
Japan
170 publications, 1.3%
|
Italy
|
Italy, 163, 1.25%
Italy
163 publications, 1.25%
|
Algeria
|
Algeria, 141, 1.08%
Algeria
141 publications, 1.08%
|
Germany
|
Germany, 140, 1.07%
Germany
140 publications, 1.07%
|
Finland
|
Finland, 123, 0.94%
Finland
123 publications, 0.94%
|
Tunisia
|
Tunisia, 120, 0.92%
Tunisia
120 publications, 0.92%
|
Australia
|
Australia, 113, 0.87%
Australia
113 publications, 0.87%
|
Iraq
|
Iraq, 113, 0.87%
Iraq
113 publications, 0.87%
|
Portugal
|
Portugal, 112, 0.86%
Portugal
112 publications, 0.86%
|
Singapore
|
Singapore, 106, 0.81%
Singapore
106 publications, 0.81%
|
Vietnam
|
Vietnam, 81, 0.62%
Vietnam
81 publications, 0.62%
|
Thailand
|
Thailand, 81, 0.62%
Thailand
81 publications, 0.62%
|
Jordan
|
Jordan, 76, 0.58%
Jordan
76 publications, 0.58%
|
Sweden
|
Sweden, 63, 0.48%
Sweden
63 publications, 0.48%
|
Brazil
|
Brazil, 58, 0.44%
Brazil
58 publications, 0.44%
|
Morocco
|
Morocco, 56, 0.43%
Morocco
56 publications, 0.43%
|
UAE
|
UAE, 55, 0.42%
UAE
55 publications, 0.42%
|
Norway
|
Norway, 53, 0.41%
Norway
53 publications, 0.41%
|
South Africa
|
South Africa, 52, 0.4%
South Africa
52 publications, 0.4%
|
Netherlands
|
Netherlands, 49, 0.38%
Netherlands
49 publications, 0.38%
|
Belgium
|
Belgium, 45, 0.34%
Belgium
45 publications, 0.34%
|
Bangladesh
|
Bangladesh, 42, 0.32%
Bangladesh
42 publications, 0.32%
|
Serbia
|
Serbia, 35, 0.27%
Serbia
35 publications, 0.27%
|
New Zealand
|
New Zealand, 34, 0.26%
New Zealand
34 publications, 0.26%
|
Mexico
|
Mexico, 33, 0.25%
Mexico
33 publications, 0.25%
|
Nigeria
|
Nigeria, 32, 0.25%
Nigeria
32 publications, 0.25%
|
Romania
|
Romania, 32, 0.25%
Romania
32 publications, 0.25%
|
Poland
|
Poland, 31, 0.24%
Poland
31 publications, 0.24%
|
Bulgaria
|
Bulgaria, 30, 0.23%
Bulgaria
30 publications, 0.23%
|
Ireland
|
Ireland, 30, 0.23%
Ireland
30 publications, 0.23%
|
North Macedonia
|
North Macedonia, 27, 0.21%
North Macedonia
27 publications, 0.21%
|
Montenegro
|
Montenegro, 27, 0.21%
Montenegro
27 publications, 0.21%
|
Czech Republic
|
Czech Republic, 26, 0.2%
Czech Republic
26 publications, 0.2%
|
Switzerland
|
Switzerland, 23, 0.18%
Switzerland
23 publications, 0.18%
|
Croatia
|
Croatia, 21, 0.16%
Croatia
21 publications, 0.16%
|
Israel
|
Israel, 17, 0.13%
Israel
17 publications, 0.13%
|
Yemen
|
Yemen, 17, 0.13%
Yemen
17 publications, 0.13%
|
Lebanon
|
Lebanon, 17, 0.13%
Lebanon
17 publications, 0.13%
|
Russia
|
Russia, 16, 0.12%
Russia
16 publications, 0.12%
|
Indonesia
|
Indonesia, 16, 0.12%
Indonesia
16 publications, 0.12%
|
Oman
|
Oman, 16, 0.12%
Oman
16 publications, 0.12%
|
Ethiopia
|
Ethiopia, 16, 0.12%
Ethiopia
16 publications, 0.12%
|
Hungary
|
Hungary, 14, 0.11%
Hungary
14 publications, 0.11%
|
Palestine
|
Palestine, 12, 0.09%
Palestine
12 publications, 0.09%
|
Qatar
|
Qatar, 11, 0.08%
Qatar
11 publications, 0.08%
|
Cyprus
|
Cyprus, 11, 0.08%
Cyprus
11 publications, 0.08%
|
Kuwait
|
Kuwait, 10, 0.08%
Kuwait
10 publications, 0.08%
|
Austria
|
Austria, 9, 0.07%
Austria
9 publications, 0.07%
|
Slovakia
|
Slovakia, 9, 0.07%
Slovakia
9 publications, 0.07%
|
Mauritius
|
Mauritius, 8, 0.06%
Mauritius
8 publications, 0.06%
|
Uruguay
|
Uruguay, 8, 0.06%
Uruguay
8 publications, 0.06%
|
Kazakhstan
|
Kazakhstan, 7, 0.05%
Kazakhstan
7 publications, 0.05%
|
Slovenia
|
Slovenia, 7, 0.05%
Slovenia
7 publications, 0.05%
|
Chile
|
Chile, 7, 0.05%
Chile
7 publications, 0.05%
|
Ghana
|
Ghana, 6, 0.05%
Ghana
6 publications, 0.05%
|
Luxembourg
|
Luxembourg, 6, 0.05%
Luxembourg
6 publications, 0.05%
|
Sudan
|
Sudan, 6, 0.05%
Sudan
6 publications, 0.05%
|
Azerbaijan
|
Azerbaijan, 5, 0.04%
Azerbaijan
5 publications, 0.04%
|
Libya
|
Libya, 5, 0.04%
Libya
5 publications, 0.04%
|
Tanzania
|
Tanzania, 5, 0.04%
Tanzania
5 publications, 0.04%
|
Estonia
|
Estonia, 4, 0.03%
Estonia
4 publications, 0.03%
|
Bosnia and Herzegovina
|
Bosnia and Herzegovina, 4, 0.03%
Bosnia and Herzegovina
4 publications, 0.03%
|
Kenya
|
Kenya, 4, 0.03%
Kenya
4 publications, 0.03%
|
Lithuania
|
Lithuania, 4, 0.03%
Lithuania
4 publications, 0.03%
|
Uzbekistan
|
Uzbekistan, 4, 0.03%
Uzbekistan
4 publications, 0.03%
|
Ukraine
|
Ukraine, 3, 0.02%
Ukraine
3 publications, 0.02%
|
Argentina
|
Argentina, 3, 0.02%
Argentina
3 publications, 0.02%
|
Cameroon
|
Cameroon, 3, 0.02%
Cameroon
3 publications, 0.02%
|
North Korea
|
North Korea, 3, 0.02%
North Korea
3 publications, 0.02%
|
Colombia
|
Colombia, 3, 0.02%
Colombia
3 publications, 0.02%
|
Trinidad and Tobago
|
Trinidad and Tobago, 3, 0.02%
Trinidad and Tobago
3 publications, 0.02%
|
Faroe Islands
|
Faroe Islands, 3, 0.02%
Faroe Islands
3 publications, 0.02%
|
Venezuela
|
Venezuela, 2, 0.02%
Venezuela
2 publications, 0.02%
|
Zambia
|
Zambia, 2, 0.02%
Zambia
2 publications, 0.02%
|
Nepal
|
Nepal, 2, 0.02%
Nepal
2 publications, 0.02%
|
Philippines
|
Philippines, 2, 0.02%
Philippines
2 publications, 0.02%
|
Sri Lanka
|
Sri Lanka, 2, 0.02%
Sri Lanka
2 publications, 0.02%
|
Bahrain
|
Bahrain, 1, 0.01%
Bahrain
1 publication, 0.01%
|
Botswana
|
Botswana, 1, 0.01%
Botswana
1 publication, 0.01%
|
Burundi
|
Burundi, 1, 0.01%
Burundi
1 publication, 0.01%
|
Zimbabwe
|
Zimbabwe, 1, 0.01%
Zimbabwe
1 publication, 0.01%
|
Iceland
|
Iceland, 1, 0.01%
Iceland
1 publication, 0.01%
|
Cambodia
|
Cambodia, 1, 0.01%
Cambodia
1 publication, 0.01%
|
Lesotho
|
Lesotho, 1, 0.01%
Lesotho
1 publication, 0.01%
|
Show all (70 more) | |
500
1000
1500
2000
2500
3000
3500
4000
4500
|
Publishing countries in 5 years
500
1000
1500
2000
2500
|
|
India
|
India, 2371, 52.75%
India
2371 publications, 52.75%
|
China
|
China, 534, 11.88%
China
534 publications, 11.88%
|
Iran
|
Iran, 193, 4.29%
Iran
193 publications, 4.29%
|
Pakistan
|
Pakistan, 157, 3.49%
Pakistan
157 publications, 3.49%
|
Saudi Arabia
|
Saudi Arabia, 137, 3.05%
Saudi Arabia
137 publications, 3.05%
|
Egypt
|
Egypt, 95, 2.11%
Egypt
95 publications, 2.11%
|
Turkey
|
Turkey, 91, 2.02%
Turkey
91 publications, 2.02%
|
USA
|
USA, 79, 1.76%
USA
79 publications, 1.76%
|
Republic of Korea
|
Republic of Korea, 66, 1.47%
Republic of Korea
66 publications, 1.47%
|
United Kingdom
|
United Kingdom, 65, 1.45%
United Kingdom
65 publications, 1.45%
|
Iraq
|
Iraq, 62, 1.38%
Iraq
62 publications, 1.38%
|
Malaysia
|
Malaysia, 59, 1.31%
Malaysia
59 publications, 1.31%
|
Algeria
|
Algeria, 54, 1.2%
Algeria
54 publications, 1.2%
|
Tunisia
|
Tunisia, 49, 1.09%
Tunisia
49 publications, 1.09%
|
Denmark
|
Denmark, 46, 1.02%
Denmark
46 publications, 1.02%
|
Thailand
|
Thailand, 45, 1%
Thailand
45 publications, 1%
|
France
|
France, 44, 0.98%
France
44 publications, 0.98%
|
Jordan
|
Jordan, 33, 0.73%
Jordan
33 publications, 0.73%
|
Canada
|
Canada, 31, 0.69%
Canada
31 publications, 0.69%
|
Morocco
|
Morocco, 26, 0.58%
Morocco
26 publications, 0.58%
|
UAE
|
UAE, 26, 0.58%
UAE
26 publications, 0.58%
|
Vietnam
|
Vietnam, 24, 0.53%
Vietnam
24 publications, 0.53%
|
Spain
|
Spain, 24, 0.53%
Spain
24 publications, 0.53%
|
Nigeria
|
Nigeria, 22, 0.49%
Nigeria
22 publications, 0.49%
|
Australia
|
Australia, 20, 0.44%
Australia
20 publications, 0.44%
|
Bangladesh
|
Bangladesh, 18, 0.4%
Bangladesh
18 publications, 0.4%
|
Brazil
|
Brazil, 18, 0.4%
Brazil
18 publications, 0.4%
|
Ethiopia
|
Ethiopia, 16, 0.36%
Ethiopia
16 publications, 0.36%
|
Portugal
|
Portugal, 14, 0.31%
Portugal
14 publications, 0.31%
|
South Africa
|
South Africa, 14, 0.31%
South Africa
14 publications, 0.31%
|
Greece
|
Greece, 13, 0.29%
Greece
13 publications, 0.29%
|
Italy
|
Italy, 13, 0.29%
Italy
13 publications, 0.29%
|
Germany
|
Germany, 12, 0.27%
Germany
12 publications, 0.27%
|
Bulgaria
|
Bulgaria, 12, 0.27%
Bulgaria
12 publications, 0.27%
|
Oman
|
Oman, 11, 0.24%
Oman
11 publications, 0.24%
|
Japan
|
Japan, 11, 0.24%
Japan
11 publications, 0.24%
|
Ireland
|
Ireland, 10, 0.22%
Ireland
10 publications, 0.22%
|
Finland
|
Finland, 10, 0.22%
Finland
10 publications, 0.22%
|
Indonesia
|
Indonesia, 9, 0.2%
Indonesia
9 publications, 0.2%
|
Norway
|
Norway, 8, 0.18%
Norway
8 publications, 0.18%
|
Belgium
|
Belgium, 7, 0.16%
Belgium
7 publications, 0.16%
|
Lebanon
|
Lebanon, 7, 0.16%
Lebanon
7 publications, 0.16%
|
Mauritius
|
Mauritius, 7, 0.16%
Mauritius
7 publications, 0.16%
|
Romania
|
Romania, 7, 0.16%
Romania
7 publications, 0.16%
|
Serbia
|
Serbia, 7, 0.16%
Serbia
7 publications, 0.16%
|
Mexico
|
Mexico, 6, 0.13%
Mexico
6 publications, 0.13%
|
Singapore
|
Singapore, 6, 0.13%
Singapore
6 publications, 0.13%
|
Russia
|
Russia, 5, 0.11%
Russia
5 publications, 0.11%
|
Kuwait
|
Kuwait, 5, 0.11%
Kuwait
5 publications, 0.11%
|
Azerbaijan
|
Azerbaijan, 4, 0.09%
Azerbaijan
4 publications, 0.09%
|
Kenya
|
Kenya, 4, 0.09%
Kenya
4 publications, 0.09%
|
Cyprus
|
Cyprus, 4, 0.09%
Cyprus
4 publications, 0.09%
|
Palestine
|
Palestine, 4, 0.09%
Palestine
4 publications, 0.09%
|
Uzbekistan
|
Uzbekistan, 4, 0.09%
Uzbekistan
4 publications, 0.09%
|
Uruguay
|
Uruguay, 4, 0.09%
Uruguay
4 publications, 0.09%
|
Kazakhstan
|
Kazakhstan, 3, 0.07%
Kazakhstan
3 publications, 0.07%
|
Ukraine
|
Ukraine, 3, 0.07%
Ukraine
3 publications, 0.07%
|
Estonia
|
Estonia, 3, 0.07%
Estonia
3 publications, 0.07%
|
Qatar
|
Qatar, 3, 0.07%
Qatar
3 publications, 0.07%
|
North Korea
|
North Korea, 3, 0.07%
North Korea
3 publications, 0.07%
|
Libya
|
Libya, 3, 0.07%
Libya
3 publications, 0.07%
|
Luxembourg
|
Luxembourg, 3, 0.07%
Luxembourg
3 publications, 0.07%
|
North Macedonia
|
North Macedonia, 3, 0.07%
North Macedonia
3 publications, 0.07%
|
Sudan
|
Sudan, 3, 0.07%
Sudan
3 publications, 0.07%
|
Czech Republic
|
Czech Republic, 3, 0.07%
Czech Republic
3 publications, 0.07%
|
Hungary
|
Hungary, 2, 0.04%
Hungary
2 publications, 0.04%
|
Venezuela
|
Venezuela, 2, 0.04%
Venezuela
2 publications, 0.04%
|
Ghana
|
Ghana, 2, 0.04%
Ghana
2 publications, 0.04%
|
Israel
|
Israel, 2, 0.04%
Israel
2 publications, 0.04%
|
Yemen
|
Yemen, 2, 0.04%
Yemen
2 publications, 0.04%
|
Colombia
|
Colombia, 2, 0.04%
Colombia
2 publications, 0.04%
|
Nepal
|
Nepal, 2, 0.04%
Nepal
2 publications, 0.04%
|
Netherlands
|
Netherlands, 2, 0.04%
Netherlands
2 publications, 0.04%
|
New Zealand
|
New Zealand, 2, 0.04%
New Zealand
2 publications, 0.04%
|
Slovakia
|
Slovakia, 2, 0.04%
Slovakia
2 publications, 0.04%
|
Tanzania
|
Tanzania, 2, 0.04%
Tanzania
2 publications, 0.04%
|
Croatia
|
Croatia, 2, 0.04%
Croatia
2 publications, 0.04%
|
Sweden
|
Sweden, 2, 0.04%
Sweden
2 publications, 0.04%
|
Bosnia and Herzegovina
|
Bosnia and Herzegovina, 1, 0.02%
Bosnia and Herzegovina
1 publication, 0.02%
|
Botswana
|
Botswana, 1, 0.02%
Botswana
1 publication, 0.02%
|
Burundi
|
Burundi, 1, 0.02%
Burundi
1 publication, 0.02%
|
Zambia
|
Zambia, 1, 0.02%
Zambia
1 publication, 0.02%
|
Cambodia
|
Cambodia, 1, 0.02%
Cambodia
1 publication, 0.02%
|
Cameroon
|
Cameroon, 1, 0.02%
Cameroon
1 publication, 0.02%
|
Lesotho
|
Lesotho, 1, 0.02%
Lesotho
1 publication, 0.02%
|
Malta
|
Malta, 1, 0.02%
Malta
1 publication, 0.02%
|
Mongolia
|
Mongolia, 1, 0.02%
Mongolia
1 publication, 0.02%
|
Panama
|
Panama, 1, 0.02%
Panama
1 publication, 0.02%
|
Papua New Guinea
|
Papua New Guinea, 1, 0.02%
Papua New Guinea
1 publication, 0.02%
|
Peru
|
Peru, 1, 0.02%
Peru
1 publication, 0.02%
|
Poland
|
Poland, 1, 0.02%
Poland
1 publication, 0.02%
|
Slovenia
|
Slovenia, 1, 0.02%
Slovenia
1 publication, 0.02%
|
Faroe Islands
|
Faroe Islands, 1, 0.02%
Faroe Islands
1 publication, 0.02%
|
Philippines
|
Philippines, 1, 0.02%
Philippines
1 publication, 0.02%
|
Montenegro
|
Montenegro, 1, 0.02%
Montenegro
1 publication, 0.02%
|
Chile
|
Chile, 1, 0.02%
Chile
1 publication, 0.02%
|
Sri Lanka
|
Sri Lanka, 1, 0.02%
Sri Lanka
1 publication, 0.02%
|
Show all (67 more) | |
500
1000
1500
2000
2500
|
9 profile journal articles
Tabatabaei Shayesteh
35 publications,
288 citations
h-index: 10
7 profile journal articles
NEOGY SARMISTHA
119 publications,
592 citations
h-index: 12
5 profile journal articles
Alabady Salah

University of Mosul
40 publications,
243 citations
h-index: 7
3 profile journal articles
Dutta Nitul
🥼 🤝
SRM Institute of Science and Technology
66 publications,
350 citations
h-index: 10
2 profile journal articles
Christofilakis Vasilis
PhD in Engineering, Senior lecturer

University of Ioannina
63 publications,
384 citations
h-index: 12
2 profile journal articles
Palanichamy Naveen
🥼 🤝
PhD in Engineering, Associate Professor
60 publications,
124 citations
h-index: 6
Research interests
Computer vision
Machine learning
1 profile journal article
Barakat Haroon

Zagazig University
133 publications,
867 citations
h-index: 16
1 profile journal article
FRANCIS ARUN
23 publications,
9 citations
h-index: 2
1 profile journal article
Chronopoulos Spyridon
🤝
PhD in Engineering, Senior lecturer

University of Ioannina

University of Peloponnese
65 publications,
501 citations
h-index: 13
Research interests
Digital signal processing
Telecommunications
Turbo Codes
1 profile journal article
MORELLI MICHELE
110 publications,
4 566 citations
h-index: 27
1 profile journal article
Mohammed Wafaa
27 publications,
215 citations
h-index: 8
1 profile journal article
Shehadeh Hisham
31 publications,
526 citations
h-index: 12
1 profile journal article
Elsharkawy Zeinab
17 publications,
192 citations
h-index: 8