Computer Engineering, Computer Science Applications, Information Systems, Artificial Intelligence
13
Scopus Publications
1224
Scholar Citations
16
Scholar h-index
24
Scholar i10-index
Scopus Publications
Exploring Machine Learning and Deep Learning for Brain Tumor Detection: A Review Uma Vishwakarma, Pritaj Yadav, Anurag Jain Proceedings of International Conference on Visual Analytics and Data Visualization Icvadv 2025, 2025 Brain tumor detection has emerged as a critical field of research, given the increasing incidence of tumors and their impact on patients' lives. Recent advancements in machine learning (ML) and deep learning (DL) have revolutionized medical imaging, offering enhanced accuracy and efficiency in diagnosing brain tumors. This review comprehensively explores various ML and DL techniques employed for brain tumor detection, with a focus on supervised and unsupervised learning methods. Key algorithms such as convolutional neural networks (CNNs), random forests, and support vector machines (SVMs) are evaluated in terms of their classification performance, segmentation capabilities, and diagnostic accuracy. Moreover, the paper highlights the role of pre-processing methods, feature extraction techniques, and the challenges of imbalanced datasets in achieving robust models.
Systematic Analysis based on Conflux of Machine Learning and Internet of Things using Bibliometric analysis , Nasib Nasib, , , , , , Santosh Reddy Addula, Anurag Jain, Preeti Gulia, Nasib Singh Gill, Bala Dhandayuthapani. V. Journal of Intelligent Systems and Internet of Things, 2024 IoT devices produce a gigantic amount of data and it has grown exponentially in previous years. To get insights from this multi-property data, machine learning has proved its worth across the industry. The present paper provides an overview of the variety of data collected through IoT devices. The conflux of machine learning with IoT is also explained using the bibliometric analysis technique. This paper presents a systematic literature review using bibliometric analysis of the data collected from Scopus and WoS. Academic literature for the last six years is used to explore research insights, patterns, and trends in the field of IoT using machine learning. This study analyses and assesses research for the last six years using machine learning in seven IoT domains like Healthcare, Smart City, Energy systems, Industrial IoT, Security, Climate, and Agriculture. The author’s and country-wise citation analysis is also presented in this study. VOSviewer version 1.6.18 is used to provide a graphical representation of author citation analysis. This study may be quite helpful for researchers and practitioners to develop a blueprint of machine learning techniques in various IoT domains.
A decision tree C4.5-based voltage security events classifier for electric power systems Sanjiv Kumar Jain, Shweta Agrawal, Prashant Kumar Shukla, Piyush Kumar Shukla, Anurag Jain International Journal of Engineering Systems Modelling and Simulation, 2022 Static voltage security classification has emerged as a potential field of research, due to large interconnections and more power demand. The paper presents a model to deal with static voltage security assessment problem through machine learning algorithm and decision tree C4.5. Using this algorithm, security classifications of power system operating states is achieved under vast load variations. N – 1 line outages contingencies are considered for the knowledge-base generation using the offline continuation power flow method. Mainly, the credible contingency cases are considered for security classification. The proposed approach is tested on IEEE-30 bus and IEEE-118 bus systems. The work will be useful for system operators in control decisions and prevent the occurrence of grid failure. Percentage classification accuracy of 100% is achieved for line outage nos. 8, 12 and 13 for IEEE-30 bus system and the accuracy is 98% for line outages no. 93 for IEEE-118 bus test system.
Personalized Liver Cancer Risk Prediction Using Big Data Analytics Techniques with Image Processing Segmentation Anurag Jain, Ahmed Nadeem, Huda Majdi Altoukhi, Sajjad Shaukat Jamal, Henry kwame Atiglah, Haitham Elwahsh Computational Intelligence and Neuroscience, 2022 A technology known as data analytics is a massively parallel processing approach that may be used to forecast a wide range of illnesses. Many scientific research methodologies have the problem of requiring a significant amount of time and processing effort, which has a negative impact on the overall performance of the system. Virtual screening (VS) is a drug discovery approach that makes use of big data techniques and is based on the concept of virtual screening. This approach is utilised for the development of novel drugs, and it is a time‐consuming procedure that includes the docking of ligands in several databases in order to build the protein receptor. The proposed work is divided into two modules: image processing‐based cancer segmentation and analysis using extracted features using big data analytics, and cancer segmentation and analysis using extracted features using image processing. This statistical approach is critical in the development of new drugs for the treatment of liver cancer. Machine learning methods were utilised in the prediction of liver cancer, including the MapReduce and Mahout algorithms, which were used to prefilter the set of ligand filaments before they were used in the prediction of liver cancer. This work proposes the SMRF algorithm, an improved scalable random forest algorithm built on the MapReduce foundation. Using a computer cluster or cloud computing environment, this new method categorises massive datasets. With SMRF, small amounts of data are processed and optimised over a large number of computers, allowing for the highest possible throughput. When compared to the standard random forest method, the testing findings reveal that the SMRF algorithm exhibits the same level of accuracy deterioration but exhibits superior overall performance. The accuracy range of 80 percent using the performance metrics analysis is included in the actual formulation of the medicine that is utilised for liver cancer prediction in this study.
A Machine Learning-Based Big EEG Data Artifact Detection and Wavelet-Based Removal: An Empirical Approach Shalini Stalin, Vandana Roy, Prashant Kumar Shukla, Atef Zaguia, Mohammad Monirujjaman Khan, Piyush Kumar Shukla, Anurag Jain Mathematical Problems in Engineering, 2021 The electroencephalogram (EEG) signals are a big data which are frequently corrupted by motion artifacts. As human neural diseases, diagnosis and analysis need a robust neurological signal. Consequently, the EEG artifacts’ eradication is a vital step. In this research paper, the primary motion artifact is detected from a single-channel EEG signal using support vector machine (SVM) and preceded with further artifacts’ suppression. The signal features’ abstraction and further detection are done through ensemble empirical mode decomposition (EEMD) algorithm. Moreover, canonical correlation analysis (CCA) filtering approach is applied for motion artifact removal. Finally, leftover motion artifacts’ unpredictability is removed by applying wavelet transform (WT) algorithm. Finally, results are optimized by using Harris hawks optimization (HHO) algorithm. The results of the assessment confirm that the algorithm recommended is superior to the algorithms currently in use.
A survey on cost aware task allocation algorithm for cloud environment Manisha Gupta, Anurag Jain 4th IEEE International Conference on Signal Processing Computing and Control Ispcc 2017, 2017 Cloud computing is a reliable computing platform for large computational intensive or data intensive tasks. This has been accepted by many industrial giants of software industry for their software solutions, companies like Microsoft, Accenture, Ericson etc has adopted cloud computing as their first choice for cheap and reliable computing. But which increase in number of clients adopting this there is requirement of much more cost efficient and high performance computing for more trust and reliability among the client and the service provide to guarantee cheap and more efficient solutions. So the tasks in cloud need to be allocated in an efficient manner to provide high resource utilization and least execution time for high performance, at the same time provide least computational cost as cloud follows pay-per use model. Many resource algorithms are been proposed to improve the performance, but are not cost efficient at same time. Algorithms like genetic, particle swarm and ant colony algorithm are efficient solutions but not cost efficient. So this paper presets an study of various existing algorithms.
SMS text compression and encryption on Android O.S Manoj Patil, Vinay Sahu, Anurag Jain 2014 International Conference on Computer Communication and Informatics Ushering in Technologies of Tomorrow Today Iccci 2014, 2014 Today in the world of globalization mobile communication is one of the fastest growing medium though which one sender can interact with other in short time. During the transmission of data from sender to receiver, size of data is important, since more data takes more time. But one of the limitations of sending data through mobile devices is limited use of bandwidth and number of packets transmitted. Also the security of these data is important. Hence various protocols are implemented which not only provides security to the data but also utilizes bandwidth. Here we proposed an efficient technique of sending SMS text using combination of compression and encryption. The data to be send is first encrypted using Elliptic curve Cryptographic technique, but encryption increases the size of the text data, hence compression is applied to this encrypted data so the data gets compressed and is send in short time. The Compression technique implemented here is an efficient one since it includes an algorithm which compresses the text by 99.9%, hence a great amount of bandwidth gets saved.The hybrid technique of Compression-Encryption of SMS text message is implemented for Android Operating Systems.
Effective dictionary based data compression and pattern searching in dictionary based compressed data Pooja Jain, Anurag Jain, Chetan Agrawal 2013 4th International Conference on Computing Communications and Networking Technologies Icccnt 2013, 2013 Effective data compression is the most important concern in data management methods. The LZW Compression method is one of the most popular algorithms in different compression method. There is one more concern i.e. compressed pattern matching. Compressed pattern matching is an emerging research area that addresses the problem in which finding patterns in the compressed data and report all the occurrences of the patterns without decompressing the compressed data. In this thesis has developed, analyzed and test a new data compression technique “Compression data Based on Dictionary” and "Searching Algorithm in Compressed data". This Algorithm generates the compression codes for words and maintains a dictionary for compression as well as decompression. Searching algorithm uses the quick search string matching algorithm for finding the required patterns.
Hybrid association-classification algorithm for anomaly extraction Gaurav Shelke, Anurag Jain, Shubha Dubey 2013 4th International Conference on Computing Communications and Networking Technologies Icccnt 2013, 2013 Knowledge extraction is a process of filtering some informative knowledge from the database so that it can be used wide variety of applications and analysis. Due to this highly efficient algorithm is required for data mining and for accessing data from large datasets. Although there are various techniques implemented for the detection of anomalies using frequent item sets using apriori algorithm but the technique applied are not suitable for large database and contains more error rate and also the classification ratio is less. Hence in this paper an efficient technique is implemented using the combinatorial method of Classification and association rule mining. First the fuzzy apriori algorithm is applied to generate frequent item sets and then CART algorithm is applied for the classification of the network anomalies.
A efficient key strategy for prolonging network lifetime in wireless network Neha Gupta, Anurag Jain, Harsh Kumar Singh 2013 4th International Conference on Computing Communications and Networking Technologies Icccnt 2013, 2013 This paper provides on introduction on key strategy for wireless sensor network. Many key Strategy are focus on proposed pair wise based on key strategy technique. Key management Mechanism Provide a security over a Wireless sensor network. Many Scheme are focus on proposing new pair wise based key management strategy. The key management mechanism combines trusted-server and key pre-distribution scheme which meets the security requirement of WSN. Some features of key management strategy we need a lot of energy to communicate a node with each other and increase a network size over a network through a insert a new node. Many Scheme provide a various protocol over a network. The key management Scheme contain a static and dynamic key management Strategy. We use a particular Protocol to select and analysis a accurate performance of sensor network. We use a AODV (ADHOC on demand distance vector routing protocol) Protocol use a network model. AODV Protocol basically use a network layer.
Exploring Machine Learning and Deep Learning for Brain Tumor Detection: A Review U Vishwakarma, P Yadav, A Jain 2025 International Conference on Visual Analytics and Data Visualization … , 2025 2025
Crop yield prediction using automated analytical and predictive techniques B Patidar, SK Sinha, A Jain Artificial Intelligence and Information Technologies, 441-446 , 2024 2024 Citations: 4
Systematic Analysis based on Conflux of Machine Learning and Internet of Things using Bibliometric analysis A Chahal, SR Addula, A Jain, P Gulia, NS Gill Journal of Intelligent Systems and Internet of Things 13 (1), 196-224 , 2024 2024 Citations: 42
Enhancing Beyond-5G and 6G Network Backhaul through Hybrid RF-FSO Communication: An Examination of HAPS and LEO Satellite Integration A Jain INTERNATIONAL JOURNAL 10 (6), 2246-2249 , 2024 2024 Citations: 2
An Intelligent Breast Cancer Classification and Prediction Model Using Deep Learning Approach D Sharma, R Kumar, A Jain International Conference on Mobile Radio Communications & 5G Networks, 363-370 , 2023 2023
Effective Cardiovascular Disease Prediction on Different Parameters MT Jain, A Jain International Journal of Scientific Research in Science, Engineering and … , 2023 2023 Citations: 3
Comparison of machine learning methods for OHSUMED -F Data Set: A Cardiovascular Diseases Simulation Study V Gupta, A jain, SK Sinha NeuroQuantology 20 (15), 385-390 , 2022 2022 Citations: 1
Impact of Minimum Support Price on Cropping Pattern B Patidar, SK Sinha, A Jain International Journal of Engineering Research in Current Trends (IJERCT) 4 (4) , 2022 2022
A Prototype Classification Algorithm for Stock Price Prediction using Optimized Variance of Attributes J Bhangre, A Jain Mathematical Statistician and Engineering Applications 71 (4), 1574-1586 , 2022 2022 Citations: 1
Optimized the Variation of Attribute for Stock Market Prediction Using Machine Learning J Bhangre, A Jain Mathematical Statistician and Engineering Applications 71 (4), 423-437 , 2022 2022
DETECTION OF CYBER-ATTACKS IN CLOUD COMPUTING USING OPTIMIZATION OF TRAFFIC CONTENT AND ENSEMBLE CLASSIFIER JK GHAI, A JAIN Stochastic Modeling & Applications 26 (4), 157 – 164 , 2022 2022 Citations: 1
OPTIMIZATION OF BAG-OF-RESOURCE SCHEDULING IN CLOUD COMPUTING USING CLUSTERING ALGORITHM & PARTICLE SWARM OPTIMIZATION KS PATIL, A JAIN Stochastic Modeling & Applications 26 (3), 165 – 172 , 2022 2022
A decision tree C4. 5-based voltage security events classifier for electric power systems SK Jain, S Agrawal, PK Shukla, PK Shukla, A Jain International Journal of Engineering Systems Modelling and Simulation 13 (4 … , 2022 2022 Citations: 4
Personalized Liver Cancer Risk Prediction Using Big Data Analytics Techniques with Image Processing Segmentation A Jain, A Nadeem, H Majdi Altoukhi, SS Jamal, H Atiglah, H Elwahsh Computational Intelligence and Neuroscience 2022 (1), 8154523 , 2022 2022 Citations: 5
Performance Analysis Of Load Balancing Algorithms Based On Swarm Intelligence In Cloud Computing KS Patil, A Jain Design Engineering, 2515-2529 , 2021 2021
A Comprehensive Review Of Cloud Computing Security Threats And Mitigation JK Ghai, A Jain Design Engineering, 2530-2544 , 2021 2021
A Machine Learning‐Based Big EEG Data Artifact Detection and Wavelet‐Based Removal: An Empirical Approach S Stalin, V Roy, PK Shukla, A Zaguia, MM Khan, PK Shukla, A Jain Mathematical Problems in Engineering 2021 (1), 2942808 , 2021 2021 Citations: 381
A Secure DSR Routing against Blackhole Attack to Improve Traffic in VANET R Singhai, R Pachouri, A Jain International Journal of Computer Applications 177 (32), 36-41 , 2020 2020
A comprehensive review on online news popularity prediction using machine learning approach P Rathord, A Jain, C Agrawal SMART MOVES JOURNAL IJOSCIENCE 10 (20), 50 , 2019 2019 Citations: 17
A Literature Survey on Privacy-Preserving in Cloud Storage A Reley, DA Jain JOURNAL OF COMPUTING TECHNOLOGIES (JCT) 7 (2), 7-14 , 2018 2018
MOST CITED SCHOLAR PUBLICATIONS
A Machine Learning‐Based Big EEG Data Artifact Detection and Wavelet‐Based Removal: An Empirical Approach S Stalin, V Roy, PK Shukla, A Zaguia, MM Khan, PK Shukla, A Jain Mathematical Problems in Engineering 2021 (1), 2942808 , 2021 2021 Citations: 381
A Review of Content Based Image Classification using Machine Learning Approach S Kumar, Z Khan, A Jain International Journal of Advanced Computer Research 2 (5), 55-60 , 2012 2012 Citations: 44
Systematic Analysis based on Conflux of Machine Learning and Internet of Things using Bibliometric analysis A Chahal, SR Addula, A Jain, P Gulia, NS Gill Journal of Intelligent Systems and Internet of Things 13 (1), 196-224 , 2024 2024 Citations: 42
A survey of IDS classification using KDD CUP 99 dataset in WEKA MU Modi, A Jain International Journal of Scientific & Engineering Research 6 (11), 947-954 , 2015 2015 Citations: 39
A novel defense scheme against DDOS attack in VANET A Jain, A Pathre, C Agrawal Wireless and Optical Communications Networks (WOCN), 2013 Tenth … , 2013 2013 Citations: 37
Identification of malicious vehicle in vanet environment from ddos attack A Pathre, A Jain Journal of Global Research in Computer Science 4 (6), 30-34 , 2013 2013 Citations: 37
A Review: Image Encryption Techniques and its Terminologies A Oad, H Yadav, A Jain International Journal of Engineering and Advanced Technology (IJEAT) ISSN 3 … , 2014 2014 Citations: 33
Design Hybrid method for intrusion detection using Ensemble cluster classification and SOM network D Rathore, A Jain International Journal of Advanced Computer Research 2 (3), 181 , 2012 2012 Citations: 31
Anomaly Intrusion Detection Techniques: A Brief Review A Jain, B Verma, JL Rana International Journal of Scientific & Engineering Research 5 (7), 1372-1383 , 2014 2014 Citations: 27
An Improved Method to Detect Intrusion Using Machine Learning Algorithms U Modi, A Jain Informatics Engineering, an International Journal (IEIJ) 4 (2), 17-29 , 2016 2016 Citations: 24
Mining Interesting Positive and Negative Association Rule Based on Improved Genetic Algorithm (MIPNAR_GA) N Rai, S Jain, A Jain Network and Complex Systems, IISTE journals 3 (10), 17-26 , 2013 2013 Citations: 22
Ensemble Neural Network and K-NN Classifiers for Intrusion Detection S Chaurasia, A Jain International Journal of Computer Science and Information Technologies 5 (2 … , 2014 2014 Citations: 21
Review: Ensemble Neural Network and KNN Classifiers for Intrusion Detection S Chaurasia, A Jain International Journal of Scientific & Engineering Research 4 (12), 213-217 , 2013 2013 Citations: 21
Classifier Selection Models for Intrusion Detection System (IDS) A Jain, B Verma, JL Rana Informatics Engineering, an International Journal (IEIJ) 4 (1), 1-11 , 2016 2016 Citations: 19
A Survey: Detection of Duplicate Record D Bharambe, S Jain, A Jain nternational Journal of Emerging Technology and Advanced Engineering 2 (11 … , 2012 2012 Citations: 19
A comprehensive review on online news popularity prediction using machine learning approach P Rathord, A Jain, C Agrawal SMART MOVES JOURNAL IJOSCIENCE 10 (20), 50 , 2019 2019 Citations: 17
Location based Energy Efficient Scheme for Maximizing Routing Capability of AODV Protocol in MANET S Goswami, C Agrawal, A Jain International Journal Wireless and Microwave Technologies 5 (3), 33-44 , 2015 2015 Citations: 16
An Enhanced Text to Image Encryption Technique using RGB Substitution and AES S Singh, A Jain International Journal of Engineering Trends and Technology (IJETT) 4 (5 … , 2013 2013 Citations: 14
An Assessment of Fuzzy Temporal Association Rule Mining S Jain, S Jain, A Jain International Journal of Application or Innovation in Engineering … , 2013 2013 Citations: 14
Digital Watermarking Method Using Replacement of Second Least Significant Bit (LSB) with Inverse of LSB A Singh, S Jain, A Jain International Journal of Emerging Technology and Advanced Engineering 3 (2 … , 2013 2013 Citations: 13
