Sentimental Analysis of Tweets Using Machine Learning S.K. Lokesh Naik, Ajmeera Kiran, Mohammad Arshad, Kamjula Lakshmi Kanth Reddy Proceedings of 2nd International Conference on Advancements in Smart Secure and Intelligent Computing Assic 2024, 2024 The social media platforms Instagram, Facebook, Twitter, WhatsApp, and Telegram are some of the most effective for international communication. Individuals frequently share their ideas and feelings on Twitter and other social networks at various times. In order to determine if user-generated language reflects a positive, negative, or neutral view about an entity, this effort aims to develop a model that can analyses user- generated text utilizing voice conversation and emojis. A dataset of tweets from Twitter was generated using a Python Twitter scraper. To analyses people's emotions, machine learning techniques and approaches are applied and Text Blob to add a positive, negative, or neutral emoji to each tweet. The proposed system performs sentiment analysis using naive Bayes machine learning techniques.
Automating ML Models Using MLOPS N Sirisha, Ajmeera Kiran, Mohammad Arshad, Mounika M Proceedings of 2nd International Conference on Advancements in Smart Secure and Intelligent Computing Assic 2024, 2024 Machine learning engineering relies on MLOps, a collection of best practises for commercializing models. As fresh data is added, machine learning models can become less effective. ML models can't use all data. To do this, we must reimagine the model by changing the front and back ends. Our project regularly tracks and trains models to overcome this constraint. MLOps (Machine Learning Operations) can help. ML pipeline automation integrates the trained model into the cloud, which can take a dataset as input and output. To quickly update the cloud ML algorithm in response to fresh data, we don't need to change the model. This guarantees the chosen model is valid and can be used with fewer flaws, improving performance. Our main objective is to build a reliable automated pipeline and install, maintain, and optimise machine learning models and systems securely and efficiently.
Sentiment Analysis of Online Reviews in the Field of Tourism for Hyderabad Popular Places K. Pushpa Rani, G. Roja, E. Lalitha, B. Deepika, C. Dastagiriah, Mohammad Arshad Proceedings of 2nd International Conference on Advancements in Smart Secure and Intelligent Computing Assic 2024, 2024 Nowadays all most all users are using the internet for any information. The main objective of this paper is used to collecting the opinions from customers are useful for both travelers and consultants. Creating a new model of approach is profitable for business organizations and also customer satisfaction. Collecting the opinions, feelings of customer by creating online blogs, forum and website. In this model we developed a new algorithm regarding facilities such as accommodation, weather, number of places to visits, hotels. Based on this analysis the consultants improve their performance to get more profits. This algorithm extracting all features and efficiently classify the given training data by observing more hidden features in the given training data set.
Signature Forgery Detection using Convolutional Neural Networks Mohammad Arshad, B. Devananda Rao, M. Ratna Sirisha, S. Lingaiah, Kukunoor Shekar, T. Benarji Proceedings of the 5th International Conference on Data Intelligence and Cognitive Informatics Icdici 2024, 2024 Signature of a person can uniquely identify the person and it is widely used in social situations and monetary transactions with individuals and financial entities. Many fraud cases have been appearing in society where signature of a person is forged for financial and other benefits. There is need for detecting forged signatures with technology driven approaches. With the emergence of Artificial Intelligence (AI), there are unprecedented possibilities in solving problems of the real world with responsible usage of AI. Deep learning (DL) is one part of AI which extends neural networks has become very significant in computer vision applications. From the existing approaches, it is observed that there is need for a complete framework for end to end processing of signatures for efficient detection of forgeries. Towards this end, we proposed a DL based framework for automatic detection of signature forgery. The framework is designed to leverage performance of the models. We proposed an algorithm known as Learning based Signature Forgery Detection (LbSFD) which exploits pipeline of multiple DL models such as CNN, VGG16 and Siamese. All the models are CNN variants used to improve efficiency in signature forgery detection. A benchmark signature dataset is used for our empirical study. Our experiments revealed that the CNN based models are highly efficient in signature forgery detection. Highest accuracy with 98.26% is achieved when VGG16 model is employed with transfer learning.
Smart Surveillance System Using Machine Learning Mohammad Arshad, C. Dastagiriah, D. Ramya Krishna, J. Vamsinath, K. Pushpa Rani, Sushruta Mishra Proceedings of 2nd International Conference on Advancements in Smart Secure and Intelligent Computing Assic 2024, 2024 Video surveillance plays a significant role in protecting and securing modern communities. Smart cameras with sophisticated video analysis can monitor events and capturing unusual behaviors and events in modern cities for security and protection. Many cameras have been installed today for surveillance purposes all around the world. So, by providing video contents that include early fire event detection, abnormal activity detection, smart parking system, and burglary actions, we will adopt an emphasis on video surveillance. we will be able to overcome the current shortcomings of post investigation procedures for video surveillance systems. Our approach uses CNN for more effective video analysis.
Improving the Performance of Routing Protocols in MANETs: A Mathematical Model for Evaluating Intermediate Bottleneck Nodes Arshad Ahmad Khan Mohammad, Mohammad Arshad, Anusha M, Krishna R K, Mazher Khan, Amairullah Khan Lodhi Ssrg International Journal of Electronics and Communication Engineering, 2023 This study analyses an intermediate bottleneck node’s performance using a random poison process mathematical model to solve Mobile Ad-Hoc Networks (MANETs’) battery life problem. The goal is to make routing protocols in MANETs work better by dealing with the problem of bottleneck nodes and reducing packet loss. In MANETs, a bottleneck node is a node that has to forward packets from multiple sources, which causes packet loss. This paper gives a mathematical model for figuring out how well intermediate bottleneck nodes in MANETs work by figuring out the average length of the queue at the input buffer and the average delay time in the buffer. This evaluation tells if a node will become a bottleneck. This evaluation also decides whether or not the node should be added to the route. So, this model is used to make routing protocols in MANETs work better by getting rid of the problem of bottleneck nodes and cutting down on packet loss.
Early Detection of lung Cancer Using Machine Learning Technique B.Devananda Rao, Mahammad Arshad 2023 International Conference on Computer Communication and Informatics Iccci 2023, 2023 The study and diagnosis of the lung diseases is the investigating point of interest for the medical experts existing from the a foretime to the current day. A diagnostic system is required to overcome this approach to reduce the time in diagnosis of lung cancers that is putting human life at risk. Few projects are proposed for this purpose and many other are under trails. To identify the cancer cells in the CT images a neural network model is proposed. It is also used to recognize issues in therapeutic imaging applications. A framework is originated for the identification of lung cancer that includes application of deep neural network system and AI. For staging of lung cancer classification of CNN is required. Deep learning methods are used on supervised learning to obtain better results. The proposed framework includes neural network that comprises of many steps like collection of images, pre-preparation, pixel enhancement, segmentation of images, and feature extraction. To outline the present research, it explains that to attain accurate results in detection and treatment of lung cancer cases at a low cost machine learning plays an unpredictable role.
Diagnosis of Lung and Pleural Diseases by Machine Learning Algorithms B.Devananda Rao, Mahammad Arshad 2023 International Conference on Computer Communication and Informatics Iccci 2023, 2023 This present work employs the classification equipment for detection of pleural carcinoma with an accuracy of 98.30%. The data collected from the lung cancer patients is divided into health data and clinical data for analyzing the efficacy of the Algorithms of Machine learning. To direct the physicians in early detection and providing suitable treatment for the lung cancer patients, the machine learning algorithms are utilized and analyzed based on the data collected from the health and medical data of the patients. Separation process applied with various algorithms of machine learning to increase the success levels. To attain about 98.30% of success rate many algorithms are evaluated. Among the numerous algorithms tried the most productive isolation process is the Linear Discriminant Analysis.
AI based Scarecrow Preventing from Crop Vandalization Y.Alekya Rani, T Bhaskar, Mohammad Arshad, Balaram Allam 2023 4th International Conference on Electronics and Sustainable Communication Systems Icesc 2023 Proceedings, 2023 Crop harm as a result of animal assaults is one of the foremost threats in decreasing the crop yield. Crop in farms is often broken via local animals like buffalos, cows, goats, wild animals like bears, monkeys, wild pigs, elephants, etc and many other birds like sparrows, crows, pigeons. These may cause serious damage to crops which in turn ends in large losses for the farmers. It is difficult for the field owners to build physical barriers to entire field and monitor it. The existing systems mainly based on observation. Farmers take actions according to the animal that entered. The other ways farmers use to prevent the crop destruction by virtue of animals include constructing barricades, electrical fences and manual surveillance. Farmers also use human puppets in middle of fields to ward off animals or birds. So here this study proposes an AI based Scarecrow that protects the crops from wild animals with the help of scanning using camera, it detects the stray animals or birds and when it detects the stray animals or birds then it produces a sound of animal extermination. This study makes a program with the help of live video detecting object using yolov3, coco names, cv2 modules. It ensures complete safety of crops from animals causing damage to it.
Design Services at Home-Tailor Application U. M. Fernandes Dimlo, Mohammad Arshad, D. Paulraj, Balaram Allam, M Silpa Raj 2023 IEEE International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2023, 2023 Cloths are one of the basic needs of humans and everyone require them at their sense of fashion. Searching out for the best Tailors within a large city is a very tiresome task. Also, visiting a Tailor without appointment can keep you waiting in a queue which take away consumer’s precious time. To solve the issue, we are developing an android based Tailors application. Application asks for the login credentials of customers and tailors and access for location. By giving access to the location this android app will generate a list of Tailors who are nearby us. Booking of services can be done if customer satisfies with details and work of tailor. Main objective of this project is to build an easy, convenient, efficient and user friendly Application where a customer can find a tailor who can fulfil their requirement and a tailor can find the customers which can increase their growth.
An efficient attack defensive models for web security International Journal of Engineering and Advanced Technology, 2019
A real-time LAN/WAN and web attack prediction framework using hybrid machine learning model International Journal of Engineering and Technology Uae, 2018
A novel probabilistic based DDOS attack detection and prevention framework for dynamic LAN/WLAN networks Journal of Advanced Research in Dynamical and Control Systems, 2017
RECENT SCHOLAR PUBLICATIONS
Signature Forgery Detection using Convolutional Neural Networks M Arshad, BD Rao, MR Sirisha, S Lingaiah, K Shekar, T Benarji 2024 5th International Conference on Data Intelligence and Cognitive … , 2024 2024 Citations: 2
Sentimental Analysis of Tweets Using Machine Learning SKL Naik, A Kiran, M Arshad, KLK Reddy 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024 Citations: 3
Smart surveillance system using machine learning M Arshad, C Dastagiriah, DR Krishna, J Vamsinath, KP Rani, S Mishra 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024 Citations: 8
Sentiment Analysis of Online Reviews in the Field of Tourism for Hyderabad Popular Places KP Rani, G Roja, E Lalitha, B Deepika, C Dastagiriah, M Arshad 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024
Automating ML models using MLOps N Sirisha, A Kiran, M Arshad 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024 Citations: 9
Data mining application in task scheduling system AS Harsha, M Arshad, V Sankara Rao, KP Babu, NR Medikondu, ... AIP Conference Proceedings 2821 (1), 070013 , 2023 2023
Design Services at Home-Tailor Application UMF Dimlo, M Arshad, D Paulraj, B Allam, MS Raj 2023 International Conference on Research Methodologies in Knowledge … , 2023 2023 Citations: 28
AI based scarecrow preventing from crop vandalization YA Rani, T Bhaskar, M Arshad, B Allam 2023 4th International Conference on Electronics and Sustainable … , 2023 2023 Citations: 14
Diagnosis of lung and pleural diseases by machine learning algorithms BD Rao, M Arshad 2023 International Conference on Computer Communication and Informatics … , 2023 2023 Citations: 3
Early detection of lung cancer using machine learning technique BD Rao, M Arshad 2023 International Conference on Computer Communication and Informatics … , 2023 2023 Citations: 21
Improving the Performance of Routing Protocols in MANETs: A Mathematical Model for Evaluating Intermediate Bottleneck Nodes MA Arshad Ahmad Khan Mohammad International Journal of Electronics and Communication Engineering 10 (4), 63-70 , 2023 2023
Detection of Cyberattack in Network Using Machine Learning SKL Naik, M Arshad 2022 International Conference on Advancements in Smart, Secure and … , 2022 2022
Retracted: Pothole Detection Using YOLO (You Only Look Once) Algorithm KP Rani, M Arshad, A Sangeetha 2022 International Conference on Advancements in Smart, Secure and … , 2022 2022 Citations: 9
Analysis of machine learning based renewable energy systems M Arshad, MA Hussain ECS Transactions 107 (1), 19853 , 2022 2022 Citations: 1
A Progressive approach to multi cast crypto systems M Arshad https://www.amazon.com/Progressive-Approach-Multi-Crypto-Systems/dp/6202554428 , 2020 2020
Neuro-Fuzzy with feature extraction based medical disease analysis DBDCNP R Madhukanth, RamgopalMusunuru, Mohammad Arshad International Journal of Advanced Science and Technology 29 (5), 10647-10655 , 2020 2020
Impact of Bottleneck Intermediate Node of MANETs and WSNs Performance DMAH Mohammad Arshad, Arshad Ahmad Khan Mohammad Test Engineering & Management 83 (May/June 2020), 11111-1116 , 2020 2020
A Reliable Intrusion Detection System in Wide Area Networks against the assault of DDOS M mohammad arshad International Journal of Innovative technology and exploring engineering … , 2019 2019 Citations: 2
A Hybrid Model for detecting DDOS attacks in Wide area Networks M mohammad arshad International Journal of recent technology and Engineering (IJRTE) https … , 2019 2019
An efficient attack defensive models for web security M mohammad arshad International Journal of Engineering and Advanced Technology (IJEAT) https … , 2019 2019
MOST CITED SCHOLAR PUBLICATIONS
Design Services at Home-Tailor Application UMF Dimlo, M Arshad, D Paulraj, B Allam, MS Raj 2023 International Conference on Research Methodologies in Knowledge … , 2023 2023 Citations: 28
Early detection of lung cancer using machine learning technique BD Rao, M Arshad 2023 International Conference on Computer Communication and Informatics … , 2023 2023 Citations: 21
AI based scarecrow preventing from crop vandalization YA Rani, T Bhaskar, M Arshad, B Allam 2023 4th International Conference on Electronics and Sustainable … , 2023 2023 Citations: 14
Automating ML models using MLOps N Sirisha, A Kiran, M Arshad 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024 Citations: 9
Retracted: Pothole Detection Using YOLO (You Only Look Once) Algorithm KP Rani, M Arshad, A Sangeetha 2022 International Conference on Advancements in Smart, Secure and … , 2022 2022 Citations: 9
Smart surveillance system using machine learning M Arshad, C Dastagiriah, DR Krishna, J Vamsinath, KP Rani, S Mishra 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024 Citations: 8
A Real-time LAN/WAN and Web Attack Prediction Framework Using Hybrid Machine Learning Model DMAH Mohammad Arshad International Journal of Engineering & Technology (UAE) 7 (3.12), 1128-1136 , 2018 2018 Citations: 6
Sentimental Analysis of Tweets Using Machine Learning SKL Naik, A Kiran, M Arshad, KLK Reddy 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024 Citations: 3
Diagnosis of lung and pleural diseases by machine learning algorithms BD Rao, M Arshad 2023 International Conference on Computer Communication and Informatics … , 2023 2023 Citations: 3
Secure Framework to Mitigate Man-in-the-Middle Attack over SSL Protocol M Arshad, MA Hussain Indian Journal of Science and Technology 9, 47 , 2016 2016 Citations: 3
Signature Forgery Detection using Convolutional Neural Networks M Arshad, BD Rao, MR Sirisha, S Lingaiah, K Shekar, T Benarji 2024 5th International Conference on Data Intelligence and Cognitive … , 2024 2024 Citations: 2
A Reliable Intrusion Detection System in Wide Area Networks against the assault of DDOS M mohammad arshad International Journal of Innovative technology and exploring engineering … , 2019 2019 Citations: 2
A novel probabilistic based DDOS attack detection and prevention framework for dynamic LAN/WLAN networks M Arshad, MA Hussain J. Adv. Res. Dyn. Cont. Syst 9 (2), 272-286 , 2017 2017 Citations: 2
Analysis of machine learning based renewable energy systems M Arshad, MA Hussain ECS Transactions 107 (1), 19853 , 2022 2022 Citations: 1
A Novel multi-level attack detection and prevention model for Dynamic LAN/WLAN networks. M Arshad, A Hussain Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia 41 (1), 59-66 , 2018 2018 Citations: 1
Sentiment Analysis of Online Reviews in the Field of Tourism for Hyderabad Popular Places KP Rani, G Roja, E Lalitha, B Deepika, C Dastagiriah, M Arshad 2024 International Conference on Advancements in Smart, Secure and … , 2024 2024
Data mining application in task scheduling system AS Harsha, M Arshad, V Sankara Rao, KP Babu, NR Medikondu, ... AIP Conference Proceedings 2821 (1), 070013 , 2023 2023
Improving the Performance of Routing Protocols in MANETs: A Mathematical Model for Evaluating Intermediate Bottleneck Nodes MA Arshad Ahmad Khan Mohammad International Journal of Electronics and Communication Engineering 10 (4), 63-70 , 2023 2023
Detection of Cyberattack in Network Using Machine Learning SKL Naik, M Arshad 2022 International Conference on Advancements in Smart, Secure and … , 2022 2022
A Progressive approach to multi cast crypto systems M Arshad https://www.amazon.com/Progressive-Approach-Multi-Crypto-Systems/dp/6202554428 , 2020 2020
