Bioinspired Algorithms: Opportunities and Challenges Shweta Agarwal, Neetu Rani, Amit Vajpayee Bio Inspired Optimization for Medical Data Mining, 2024 Bioinspired algorithms have received a lot of attention recently because of their potential to solve complex optimization problems by emulating the principles and behaviors found in nature. These algorithms, inspired by biological processes, such as evolution, swarm intelligence, and neural networks, have demonstrated promising results in various domains, including optimization, machine learning, robotics, and data mining. This chapter aims to give a brief summary of the opportunities and challenges associated with bioinspired algorithms. The chapter will begin by introducing the concept of bioinspired algorithms and their underlying principles. It will then explore the opportunities that these algorithms offer, such as their capacity to locate the best answers in very big and intricate search fields, their robustness in dealing with uncertainty and noise, and their potential for parallel and distributed computing. The chapter will also highlight the application areas where bioinspired algorithms have shown promising results, including in optimization problems, pattern recognition, and swarm robotics. However, along with the opportunities, bioinspired algorithms also present several challenges. The chapter will discuss these challenges, such as the need for parameter tuning, the lack of theoretical analysis and understanding, the risk of premature convergence, and the computational cost associated with large-scale problems. It will also address the ethical considerations and limitations of bioinspired algorithms, including concerns about fairness, transparency, and interpretability. To provide a comprehensive understanding, the chapter will discuss some of the prominent bioinspired algorithms, including artificial neural networks, ant colony optimization, particle swarm optimization and genetic algorithms. It will highlight their key features, advantages, and limitations, and provide examples of their applications in various domains. In conclusion, bioinspired algorithms offer exciting opportunities for solving complex problems in diverse domains. However, their effective utilization requires addressing the associated challenges and considering ethical considerations.
Boosting Feature Selection Using Modified Grasshopper Algorithm: Emphasizing Social Interaction Shweta Agarwal, Bobbinpreet Kaur, Bhoopesh Singh Bhati Proceedings of the 2024 International Conference on Artificial Intelligence and Emerging Technology Global AI Summit 2024, 2024 Feature Selection is a way of improving machine learning models in terms of efficacy and accuracy. The process involves identifying the most relevant features within a dataset to improve the efficiency of the model. Traditionally, the approaches have had issues in selecting the most relevant features to the case in most instances with accuracy. This paper, therefore, looks to develop and evaluate a novel approach for feature selection based on the Grasshopper Algorithm (GH). The idea is to address some specific problems of feature selection tasks and assess its performance against traditional swarm intelligence techniques. In this regard, the modified GH has been comprehensively assessed against the traditional or common techniques like ABC, GA and PSO. The results which are obtained reveal that modified GH algorithm outperformed PSO, GA and ABC in all the feature selection tasks. It improved the accuracy to 92.01%, which is 10.84% higher than PSO, 25.12% higher than GA, and 12.92% higher than ABC. That means the GH algorithm performs very well in feature selection. Consequently, swarms of algorithms are rather competitive for the optimization performance of various machine learning applications. To this end, this paper reveals the pertinent knowledge of swarm intelligence in feature selection to researchers and readers.
Electromyography-based Hand Gesture Classification Using IGOA and DNN Shweta Agarwal, Bobbinpreet Kaur, Bhoopesh Singh Bhati 2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024 The most significant improvement in human-computer interfaces revolves around the accurate decoding of hand gestures from electromyography signals. The existing methods of doing this have a number of limitations. These include: feature redundancy and diminishing estimation accuracy for new users when pre-trained models are applied. Therefore, the current study focuses on enhancing the EMGbased recognition of hand gestures by developing a swarm intelligence based model to select features. In this model, a feature extractor, feature selector, and label classifier interface are integrated. The proposed model uses time domain (TD), frequency domain (FD), and time-frequency domain (TFD) analyses to establish the basic information of gesture recognition. Improved Grasshopper Optimization Algorithm (IGOA) chooses the most discriminative features from the EMG data. It is noteworthy that a DNN classifier improves the classification result of the EMG-based gesture classification using the created feature set. It evaluates the proposed model from an 8-channel Myo Armband dataset. The proposed approach, on average improves by $2.4 \\%, \\mathbf{9. 6 \\%, 6. 1 \\%,}$ and 8% in precision, recall, F-measure, and accuracy respectively compared with a common KNN, NB, and RF estimators. Moreover, the average enhancements in recall by 7.3%, in precision by 4.9%, in accuracy by 4.1%, and in F-measure by 6.2% over popular optimization techniques like PSO, GA, and GH demonstrate the strength of the DNN and label the IGOA + DNN combination as a very effective strategy for EMG-based gesture classification.
Algorithmic Analysis and Implementation Strategies For Targeted Advertising on Diverse Social Media Platform Binayak Kumar Mahato, Shweta Agarwal, Rajnish Kumar, Abhinav Paswan, Amar Kumar Mandal, Prince Thakur 2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024 In this paper, we analyze the current state of targeted advertising on various social media platforms using algorithmic analysis and implementing strategies. Social media plays an increasingly important role in modern marketing, especially in the wake of COVID-19, which hastened the transition to online platforms. Drawing on advances in technology, including machine learning and natural language processing (NLP), we demonstrate the value of personalized advertising in increasing user engagement and brand affinity. Drawing on recent research and case studies, we highlight the need to balance targeted advertising with user privacy. In summary, we call for innovation and ethical considerations as we navigate the ever-changing advertising landscape.
EMG Feature Selection Approach to Improve Classification Accuracy - A Review Shweta Agarwal, Raman Chadha, Bhoopesh Singh Bhati Icsccc 2023 3rd International Conference on Secure Cyber Computing and Communications, 2023 Nowadays, many computing systems are a part of daily life; therefore, it is more comfortable to communicate with them naturally. The field of human-computer interaction (HCI) was created in order to break down the obstacles to human-computer communication. One of the types of HCI that is, Hand Gesture Recognition (HGR), which predicts the type of a certain hand action. The electrical activity of skeletal muscles is one potential input for these types of models. The purpose of movement produced by the human brain is communicated through electromyography (EMG) signals. In order to identify EMG data that is precise for any class, the most pertinent collection of EMG attribute values must be used to train a system. With the aid of a combination of machine learning and EMG data, this paper aims to present the most recent real-time feature selection techniques and classification algorithms in a comprehensive review of the literature. Finally, several gaps have been found that may point the way for fresh lines of inquiry in the field of EMG-based gesture detection, and a proposed approach for improving the overall classification accuracy of the EMG signal is presented.
Classifying Hand Gestures through EMG Data with Machine Learning Proceedings of the 17th Indiacom 2023 10th International Conference on Computing for Sustainable Global Development Indiacom 2023, 2023
Introduction to computational intelligence in healthcare: Applications, challenges, and management Chander Prabha, Jaspreet Singh, Shweta Agarwal, Amit Verma, Neha Sharma Computational Intelligence in Healthcare Applications Challenges and Management, 2023 With the evolution of lots of data in healthcare, the complexity of managing and handling the data also increases. To manage this complex issue, computational techniques (CI) nowadays can be applied in the healthcare field. The applications for health information help us to support patient care systems and reduce human error. Many CI techniques are already in use by life science companies, and care providers and users are paying for them to get the facilitation. The key applications of these technologies include the treatment and diagnosis of patients, adherence and engagement of patients, and many management activities. Many healthcare tasks are performed with greater care and accuracy using CI techniques; however, the healthcare industry requires 100% accuracy for medical diagnosis and further treatment which is still a challenging problem. In this chapter, from a management perspective, various CI healthcare applications, along with their challenges, have been discussed in brief. It has been observed that there are many instances that prove that the use of CI improves accuracy in healthcare tasks compared to humans. However, various implementation issues of CI in healthcare will prevent its large-scale automation. Ethical issues are also explored in this chapter.
Student's Academic Performance Prediction by Using Ensemble Techniques Nidhi, Mukesh Kumar, Disha Handa, Shweta Agarwal Aip Conference Proceedings, 2022 Data Mining is a discipline of Machine Learning which is used to find or extract the information from the huge database of any organization by using some informative techniques. These informative techniques are then divided into different categories like clustering, classification, regression and association rule mining etc. Data Mining is widely used techniques in different fields like education, telecommunication, hospital, hospitality industry etc. As education plays a crucial role in the life of a human being therefore its proper monitoring is also very important. Thus, to predict the academic performance of any student on time and to help students improve their academic perform different researcher is working in the field and tried to develop a system which help to improve the prediction result. In this paper, different classification algorithms are used on academic dataset of the student in conjunction with different ensemble learning algorithm to improve the prediction result as compared to prediction result given by simple classification algorithm. At the end a comparison is also given which show the performance improvement by ensemble learning as compared to simple classification. The maximum improvement is shown by Multilayer perceptron algorithm and it is up to 15%.
Blood cancer detection through deep learning A Gorai, R Walia, S Agarwal Artificial Intelligence and Sustainable Innovation, 334-340 , 2026 2026
Introduction to IoT and AI for Providing Healthcare Solutions S Agarwal, K Sharma, CS Dash IoT and AI-Enabled Healthcare Solutions for Intelligent Disease Prediction, 1-15 , 2025 2025
Emerging Areas and Applications in the Field of Earth Sciences S Agarwal, N Rani Emerging AI Applications in Earth Sciences: Challenges, Impact and Analysis … , 2025 2025
Quantum Computing in the Field of Earth Sciences N Rani, S Agarwal Emerging AI Applications in Earth Sciences: Challenges, Impact and Analysis … , 2025 2025 Citations: 1
Handwave: an EMG-powered system for intuitive gesture recognition S Agarwal, B Kaur, BS Bhati SN Computer Science 5 (8), 1038 , 2024 2024 Citations: 2
Boosting Feature Selection Using Modified Grasshopper Algorithm: Emphasizing Social Interaction S Agarwal, B Kaur, BS Bhati 2024 International Conference on Artificial Intelligence and Emerging … , 2024 2024
Bioinspired algorithms: opportunities and challenges S Agarwal, N Rani, A Vajpayee Bio‐Inspired Optimization for Medical Data Mining, 1-30 , 2024 2024 Citations: 6
Algorithmic analysis and implementation strategies for targeted advertising on diverse social media platform BK Mahato, S Agarwal, R Kumar, A Paswan, AK Mandal, P Thakur 2024 15th International Conference on Computing Communication and Networking … , 2024 2024 Citations: 3
Electromyography-based Hand Gesture Classification Using IGOA and DNN S Agarwal, B Kaur, BS Bhati 2024 15th International Conference on Computing Communication and Networking … , 2024 2024 Citations: 3
EMG feature selection approach to improve classification accuracy—a review S Agarwal, R Chadha, BS Bhati 2023 Third International Conference on Secure Cyber Computing and … , 2023 2023 Citations: 5
Classifying Hand Gestures through EMG Data with Machine Learning S Agarwal, R Chadha, BS Bhati 2023 10th International Conference on Computing for Sustainable Global … , 2023 2023 Citations: 4
Introduction to computational intelligence in healthcare: Applications, challenges, and management C Prabha, J Singh, S Agarwal, A Verma, N Sharma Computational intelligence in healthcare, 1-15 , 2023 2023 Citations: 17
Student’s academic performance prediction by using ensemble techniques Nidhi, M Kumar, D Handa, S Agarwal AIP Conference Proceedings 2555 (1), 050004 , 2022 2022 Citations: 1
Analysis of lung cancer prediction at an early stage: A systematic review S Agarwal, C Prabha Congress on Intelligent Systems: Proceedings of CIS 2021, Volume 1, 701-711 , 2022 2022 Citations: 14
The Effect of COVID-19 Epidemic Pandemic and Preventive Measures in India: A Review C Prabha, S Agarwal, A Goel International Journal of Management and Humanities 8 (12), 14-18 , 2022 2022 Citations: 1
Diseases prediction and diagnosis system for healthcare using IoT and machine learning S Agarwal, C Prabha Smart Healthcare Monitoring Using IoT with 5G, 197-228 , 2021 2021 Citations: 6
Comparative analysis of heterogeneous ensemble learning using feature selection techniques for predicting academic performance of students N Nidhi, M Kumar, S Agarwal 2021 2nd International Conference on Computational Methods in Science … , 2021 2021 Citations: 7
Chronic diseases prediction using machine learning–A review S Agarwal, C Prabha, M Gupta Annals of the Romanian Society for Cell Biology 25 (1), 3495-3511 , 2021 2021 Citations: 16
Accelerometer-Based Hand Gesture Control Robot Using Arduino and 3-Axis Accelerometer Ankit, S Agarwal International Conference on Smart Technologies for Energy, Environment, and … , 2020 2020 Citations: 2
Door Automation System (Using Arduino and Fingerprint Sensor) MSA Ms. Monika Chauhan, Ms. Neha Sardana, Mr. Dheeraj Kumar, Mr. Tijender Kumar Journal of Android and IOS Applications and Testing 5 (3), 5-9 , 2020 2020
MOST CITED SCHOLAR PUBLICATIONS
Voice based online examination for physically challenged S Khan, S Verma, S Agarwal, P Krishnatrey, S Sharma MIT International Journal of Computer Science and Information Technology 5 … , 2015 2015 Citations: 23
Introduction to computational intelligence in healthcare: Applications, challenges, and management C Prabha, J Singh, S Agarwal, A Verma, N Sharma Computational intelligence in healthcare, 1-15 , 2023 2023 Citations: 17
Chronic diseases prediction using machine learning–A review S Agarwal, C Prabha, M Gupta Annals of the Romanian Society for Cell Biology 25 (1), 3495-3511 , 2021 2021 Citations: 16
Analysis of lung cancer prediction at an early stage: A systematic review S Agarwal, C Prabha Congress on Intelligent Systems: Proceedings of CIS 2021, Volume 1, 701-711 , 2022 2022 Citations: 14
Comparative analysis of heterogeneous ensemble learning using feature selection techniques for predicting academic performance of students N Nidhi, M Kumar, S Agarwal 2021 2nd International Conference on Computational Methods in Science … , 2021 2021 Citations: 7
Bioinspired algorithms: opportunities and challenges S Agarwal, N Rani, A Vajpayee Bio‐Inspired Optimization for Medical Data Mining, 1-30 , 2024 2024 Citations: 6
Diseases prediction and diagnosis system for healthcare using IoT and machine learning S Agarwal, C Prabha Smart Healthcare Monitoring Using IoT with 5G, 197-228 , 2021 2021 Citations: 6
EMG feature selection approach to improve classification accuracy—a review S Agarwal, R Chadha, BS Bhati 2023 Third International Conference on Secure Cyber Computing and … , 2023 2023 Citations: 5
An Improvement on page ranking based on visits of links S Agarwal, BB Agarwal International Journal of Science and Research 2 (6), 265-268 , 2013 2013 Citations: 5
Classifying Hand Gestures through EMG Data with Machine Learning S Agarwal, R Chadha, BS Bhati 2023 10th International Conference on Computing for Sustainable Global … , 2023 2023 Citations: 4
Algorithmic analysis and implementation strategies for targeted advertising on diverse social media platform BK Mahato, S Agarwal, R Kumar, A Paswan, AK Mandal, P Thakur 2024 15th International Conference on Computing Communication and Networking … , 2024 2024 Citations: 3
Electromyography-based Hand Gesture Classification Using IGOA and DNN S Agarwal, B Kaur, BS Bhati 2024 15th International Conference on Computing Communication and Networking … , 2024 2024 Citations: 3
Authentication and key management in wireless mesh network S Agarrwal, N Gupta MIT International Journal of Computer Science & Information Technology 2 (2 … , 2012 2012 Citations: 3
Handwave: an EMG-powered system for intuitive gesture recognition S Agarwal, B Kaur, BS Bhati SN Computer Science 5 (8), 1038 , 2024 2024 Citations: 2
Accelerometer-Based Hand Gesture Control Robot Using Arduino and 3-Axis Accelerometer Ankit, S Agarwal International Conference on Smart Technologies for Energy, Environment, and … , 2020 2020 Citations: 2
Quantum Computing in the Field of Earth Sciences N Rani, S Agarwal Emerging AI Applications in Earth Sciences: Challenges, Impact and Analysis … , 2025 2025 Citations: 1
Student’s academic performance prediction by using ensemble techniques Nidhi, M Kumar, D Handa, S Agarwal AIP Conference Proceedings 2555 (1), 050004 , 2022 2022 Citations: 1
The Effect of COVID-19 Epidemic Pandemic and Preventive Measures in India: A Review C Prabha, S Agarwal, A Goel International Journal of Management and Humanities 8 (12), 14-18 , 2022 2022 Citations: 1
Blood cancer detection through deep learning A Gorai, R Walia, S Agarwal Artificial Intelligence and Sustainable Innovation, 334-340 , 2026 2026
Introduction to IoT and AI for Providing Healthcare Solutions S Agarwal, K Sharma, CS Dash IoT and AI-Enabled Healthcare Solutions for Intelligent Disease Prediction, 1-15 , 2025 2025
