1st Edition
Algorithms in Advanced Artificial Intelligence ICAAAI-2023
The most common form of severe dementia, Alzheimer’s disease (AD), is a cumulative neurological disorder because of the degradation and death of nerve cells in the brain tissue, intelligence steadily declines and most of its activities are compromised in AD. Before diving into the level of AD diagnosis, it is essential to highlight the fundamental differences between conventional machine learning (ML) and deep learning (DL). This work covers a number of photo-preprocessing approaches that aid in learning because image processing is essential for the diagnosis of AD. The most crucial kind of neural network for computer vision used in medical image processing is called a Convolutional Neural Network (CNN). The proposed study will consider facial characteristics, including expressions and eye movements using the diffusion model, as part of CNN’s meticulous approach to Alzheimer’s diagnosis. Convolutional neural networks were used in an effort to sense Alzheimer’s disease in its early stages using a big collection of pictures of facial expressions.
1. Convolutional Neural Networks Detect Alzheimer’s disease by Analyzing Facial Expressions and
Eye Movements
S. V. Swamy Kadali, R. N. V. Jagan Mohan and Lakshmi M.
2. Self-caring Autonomous Medicinal and Aromatic Plants (MAP) Nursery Using Arduino Microcontroller
Gidla Sudheer Babu, A. V. S. S. Varma, B. V. Ramana and Srilali Siragam
3. Segment Anything: GPT-3 and Logistic Regression Approach for Skin Cancer Detection
V. N. V. Sri Harsha, S. Rao Chintalapudi and V. S. Manoj Kumar Chenna
4. Enhancing Metric Learning Reliability for Pose-Oriented Face Recognition by Visual
Assessment of Tendency
Pinisetty Rajasekhar and V. Ravindranath
5. Verifiable Secure Vehicle Connectivity Using Machine Learning Framework for Internet of Vehicles
Lanka Divya, Priyadarshini Voosala, R. Shiva Shankar, Ch. Ravi Swaroop
6. Disease Detection In Dental Patients Using Machine Learning Algorithms Through Image Analysis
Khadar Alisha Sheik and V. Kiran Kumar
7. Early Disease Diagnosis in Tomato Crops Using AI-Based Deep CNN
T. V. K. P. Prasad, V Dilip Kumar, T. Srinivasa Rao, Gude Sujatha and T. K. Priyanka
8. Improvement Over K-Means Algorithm Over Complex Data
D. D. D. Suribabu, T. Hitendra Sarma and B. Eswara Reddy
9. Visual Representation of Lung Cancer Image Classification Using Artificial Neural Network
B. Nandana Kumar, K. Surya Ram Prasad and G. V. Satya Sriram
10. Machine Learning Improve Predictive Analysis of Diabetes Disease
K. Durga Bhavani, CH. Vinod Varma and B. Mounika
11. Tackle Comorbid Obesity in T2DM by Applying New Strategies to Optimize Glycaemic Control and
Weight Management
Yugandhar Bokka, R. N. V. Jagan Mohan and M. Chandra Naik
12. A Literature Survey on Deep Learning Approach Used for Audio-to-Sign Conversion with
Gesture Recognition for the Deaf and Dumb
B. Veerendra and D. Ramakrishna
13. Federated Learning Approach Based on the MFCC for Speech Emotion Recognition
Banda SNV Ramana Murthy and Veluri Ravi Kishore
14. Automated Object Recognition with IoT for Visually Impaired Users
JMSV Ravi Kumar, M. Babu Reddy, M. Srikanth and D. Ratna Giri
15. Deep Learning Approach for Early Detection and Diagnosis of Teenager Interstitial Lung Disease
Ramesh Alladi, R. N. V. Jagan Mohan and K. V. Ramana
16. Robust Object Detection in Medical Imaging: Cross-Measure Refinement with Edge Detection and SSD
Bhanurangarao M. and Mahaveerakannan R.
17. AI-Based Breast Cancer X-Ray Image Detection Using Generative Adversarial Attacks
V. S. R. K. Raju Dandu, R. N. V. Jagan Mohan and M. Chandra Naik
18. Promotion of Graduate Placement Through Academics by Improving Performance Using
Artificial Neural Networks 1
Chandra Sekhar K., K. Satyanarayana Raju, P. Subba Raju, M. Krishna Satya Varma and
K. Laxmipathi Raju
19. Open AI’s Large Language Model to Improve Payroll and HR Processes
Lokesh Sai Kiran Vatsavai and Srihari Varma Mantena
20. A Novel Blockchain-Based Approach for Secure and Efficient Electronic Medical Record Sharing
Hussein EL Ghor, Mohamed Daher and Bilal Nakhal
21. A Classifying Gender Crimes with AdaBoost and Back Propagation Algorithms
Dileep Kumar Kadali, R. N. V. Jagan Mohan and M. Chandra Naik
22. Identifying Tremor Disease in Neurological Disorders Using Finger Gesture Images
P. Sumithabhashini, M. V. Vijaya Saradhi, Ramesh Alladi and Swajan Reddy
23. An Effective Machine Learning Technique that uses Emotive Faces in order to Study Crimes
C. Syamsundar Reddy and G. Anjan Babu
24. Increasing the Reliability of Intercropping in Agriculture Using Machine Learning
M. Srikanth, R. N. V. Jagan Mohan and M. Chandra Naik
25. Retrieval Augmented Generation Classification Algorithm for Fake News Detection
Ravisankar Malladi, V. T. Ram Pavankumar, M. Arulselvi and Konatham Sumalatha
26. Predictive AI Treatment for Kidney Tumors with Privacy Protection
K. V. Nageswari, R. N. V. Jagan Mohan and Bhramara Bar Biswal
27. Developing a Hybrid Approach to Assess Changes in Pomegranate Quality
Sai Prapulla Seshank Adivi, V. M. N. S. S. V. K. R. Gupta and A. Bala Krishna
28. Artificial Intelligence-Based Communication through Cat Facial Expressions
K. Bhargavi, Ch. V. Phani Krishna and Bandla Srinivasa Rao
29. Convolutional Neural Networks for the Identification of Skin Disorders
A. Aswini Priyanka
30. Machine Learning-Based Approach for Detecting Online Payment Fraud
V. S. Naresh, G. Venkata Sridevi, P. Srinivasarao, N. Hema Kiran,
CH. Sai Babu and P. Lazar Dan
31. Secure Loan Approval Prediction: A Privacy-Preserving Machine Learning Approach
V. S. Naresh, K. Sushmadi Lakshmi, S. Swathi Rathnam, G. Lakshmi Ishwarya,
D. Kirankumar and T. Swathi Ratnam
32. AI with Edge Computing-Driven Development in Healthcare Analysis
K. Vijaya Naga Valli and L. Sujihelen
33. Big Image: Large-Scale Skin Disease Image Classification in Medical Imaging and
Healthcare Using CNN and Transformers
K. Satyanarayana Raju, K. Chandra Shekar, K. Laxmipathi Raju, M. Krishna Satya Varma,
P. Subba Raju and Sumitra Srinivas Kotipalli
34. AI Driven Load Distribution for Federated Network on Electronic Health Records
S. Suryanarayanaraju, M. Chandra Naik and R. N. V Jagan Mohan
35. Smartphone-based Deep Learning Models for the Early Detection of Bubonic Plague and
Skin Diseases: A Safer, More Accessible, and Affordable Approach
N. V. Ratnakishor Gade and Mahaveerakannan R.
36. Kids Affected by Uncommon Illnesses Like Autism: Pregnant Women’s Identification
through Lasso Regression
P. Jahnavi, M. Chandra Naik and P. Bharat Siva Varma
37. Blind People Assistant: Real-Time Objects Detection and Distance Estimation with Voice Feedback
Hemalatha Indukuri, K. Kishore Raju, P. KavyaSri, M. Srija, K. Srujana and P. SivaPriya
38. Standard Encryption Methodologies to Process Multi-Modality Medical Images for
Diagnosing in Telemedicine
P. Shyamala Madhuri, B. Amutha and D. J. Nagendrakumar
39. Enhancing Dyslexia Detection and Intervention through Deep Learning: A Comprehensive
Review and Future Directions
Pavan Kumar Varma Kothapalli, Cheepurupalli Raghuram and Boddu LV Siva Rama Krishna
40. A Study of YOLO (You Only Look Once) to YOLOv8
Immidisetty V. Prakash and M. Palanivelan
41. Prediction of Endangered Species Using Artificial Intelligence
Yallamati Prakasa Rao, M. V. V. S. Subrahmanyam and Tvramana
42. Early Detection of Alzheimer’s Disease through Tau-PET Image Analysis Using CNN
M. Janakidevi, Ramalinga Swamy Cheruku and Ch. Rami Naidu
43. Computational Analysis and Identification of Specific MMP Targets in Tumours at Multiple Stages
G. Nirmala, Deepak Nedunuri, K. Satyanarayana, Ch. Madhava Rao and Y. Butchi Raju
44. Exploring the Rise of Cryptocurrencies with Blockchain Technology
V. Priyadarshini, R. Shiva Shankar, P. Neelima, N. Deshai and D. Ravibabu
45. Mitigating Misinformation: An Advanced Analytics Framework for Proactive Detection of
Fake News to Minimize Misrepresentation Risks
R. Shiva Shankar, G. Mahesh, V. Maheswararao, N. Silpa and K V S Murthy
46. Summarization of Legal Texts by Using Deep Learning Approaches
Nilambar Sethi, V. Sivarama Raju Vetukuri, R. Shiva Shankar and R. Rajender
47. Optimizing Diabetes Prediction through Intelligent Feature Selection: A Comparative Analysis of
Grey Wolf Optimization with AdaBoost and Ant Colony Optimization with XGBoost
Chigurupati Ravi Swaroop, Vemuri Jayamanasa, R. Shiva Shankar, M. Ganesh Babu,
Vahiduddin Shariff and N S Koti Mani Kumar
48. Real-Time Sign Language Translation through Deep Learning
Sujatha B., Leelavathy N., K. Navya Sri, G. Jagan Mohan and K. Bosu Babu
49. Ensuring Data Privacy in the Cloud: Authprivacychain’s Blockchain Access Control
R. Tamilkodi, K. Surya Kala, T. Durga Sukanthika, B. Aanantha Sai Datta Kiran,
V. Hemanth Reddy and K. Srimani Neha
50. Optimizing Cloud Load Balancers for Reduced Network Latency
V. Murali Mohan, Radha Yaraguti, Silpa Sharon Chinta and Bhargavi Jonnavithula
51. Boosting Precision: Strategies for Improving Spam Detection in Cloud-Based Email Services
V Murali Mohan, Rohitha papolu, Sowjanya Malleboina and Sravya Madiraju
52. Crafting Personalized Film Suggestions
R. Tamilkodi, A. Harika, Ch. Rohith, G. Nithin, K. Mahesh, A. Anvitha and N. Lohitha
53. A Comprehensive Approach to Detect SQL Injection Attacks Using Enhanced Snort Rules
T. Srinivasarao, Shrija Madhu, K. Kalyani Vishalakshi, Preetish Madhu,
K. Satya Sai DurgaManikanta and P. Sumanth Yadav
54. ARP and DNS Spoofing Detection with Attacker IP Capturing
T. Srinivasarao, N. Leelavathy, S. Kailash Chandra Sri Satya Dev, I. Om Ganesh,
P. Sai Aditya and P. Sai Krishna
55. A Comprehensive Review of Advanced Artificial Intelligence Integration in ICT Systems:
Methodologies, Applications, and Future Directions
Gopisetty Pardhavika and Prisicilla.R
56. Enhanced Network Security: Machine Learning-Based DDOS Detection
R. Tamilkodi, A. Harika, B. S. L. D. V. Mythili, G. KarunaKumar,
B. Dileep Kumar and S. Sri Harshitha
57. Enhancing Network Security: Deep Ensemble-Based Attack Detection Framework
R. Tamilkodi, S. Ratalu, Gandham Santoshi, Vysyaraju Sarath Raju, Allampalli V M Mukesh Rao, and
Rampa Aditya Raghava Koundinya
58. Early-Stage Chronic Kidney Disease Detection using Machine Learning with Bigdata
Mamatha B and Sujatha P Terdal
59. An MDB-KMC and Firefly-Based Clustering Approach for Energy Optimization in
Wireless Sensor Networks
Veeraiah T., Sudhamsu Mouli and M. P. Singh
60. Software Requirements Based Software Effort Estimation using RSLU-GNL-GRU in
Software Project Management
K. Harish Kumar and K. Srinivas
61. The Evolution and Impact of Large Language Models in Artificial Intelligence
Chaitanya K. and Krishna Jayanth Rolla
62. Several Machine Learning Techniques Used to Forecast Parkinson Disease
O. Sri Nagesh, B. Rajarao and Voore Subrahmanyam
63. Fungal Disease Risk Assessment using Data-Driven Methods: Impacts on Food Security and
Crop Devastation
Kamidi Jeswanth Kumar
64. Redefining Glaucoma Identification using State-of-the- Art Machine Learning
D. Ratna Giri, P. Syamala Rao, J. V. Rama Kumar and JMSV Ravi Kumar
65. Probe Method: A Dependable Economy Data Methodology Feature Selection for Machine Learning
Chiranjeevi S. P. Rao Kandula and Srinivas Rao Parnadi
66. Estimating Human Life Expectancy through Sentiment Analysis, Population-based Optimisation,
and Machine Learning Models
Meduri Raghu Chandra, G. Jaya Raju, Lanka Atri Datta Ravi Tez and K.Lakshmaji
67. A Distributed-Back Propagation Procedure that uses Climate while Predicting the Spread of
Mosquitoes Using Least Squares Estimation
K. Gopala Varma, M. Chandra Naik and R. N. V. Jagan Mohan
68. Unveiling the Efficacy of Machine Learning in Addressing Imbalances in Credit Card
Fraud Detection Data
Ch Siva Subrahmanyam, N. Deshai, K. Samatha and J. Tulasi Rajesh
69. Blockchain-driven Security Paradigm: A Robust System Harnessing the Internet of
Medical Things (IoMT) Network for Enhanced E-Healthcare Monitoring
Tulasi Rajesh Jonnapalli, N. Deshai K Samatha and B. V. D. S. Shekar
70. Estimating Foreign Export Volume Using Machine Learning for Big Data Business Analytics
Yendrapati Geetha
71. Unmasking Deceit: Pioneering Deep Learning Hybrids to Expose Fabricated Reviews in the
Digital Realm
N. Deshai and B. Bhaskara Rao
72. YOLO CNN Approach for Object Detection
Aluri Dev Ananth, Abhiram Seemakurthi, Sasank Tumma and Prasanthi Boyapati
73. Multi-Crop Analysis Using Multi-Regression via AI-based Federated Learning
Mouna Penmetsa and R.N.V. Jagan Mohan
74. Empowering Inclusive Communication: Advancements in Wearable Technology with
GloSign—A Glove-Based Solution for Seamless Sign Language Interaction
L V Srinivas, R. Shiva Shankar, N. Deshai, K. Sravani and V. Maheswararao
75. AI-Based Voice Assistant Application for B5G and 6G Free Space Optic Technology is
Competent of Detecting Fake Words
R. N. V. Jagan Mohan and Vasamsetty Chandra Sekhar
76. GenerativeAI in Personal Dairy Information Retrieval for Criminal Investigation
KVSS Murthy, J. Rajanikanth, R. Shiva Shankar, CH. Ravi Swaroop and D. Ravibabu
77. PCACSO Feature Selection for Prediction of Breast Cancer NAC Response
Susmitha Uddaraju, G. P. Saradhi Varma and I.Hemalatha
Biography
Dr. R. N. V. Jagan Mohan
working as Professor in Computer Science and Engineering Department from Sagi Rama Krishnam Raju Engineering College, China Amiram, Bhimavaram. I have Ph.D completed from Acharya Nagarjuna University since 2015 under the esteemed guidance of Dr.Kurra Raja Sekhara Rao, M.Tech in CSE, University College of Engineering, Jawaharlal Nehru Technological University, 2020. I have published papers around 43 in various international Journals and national journals. I have published patents around 6 and 1 is Granted international. Published Books in various international publishers 2 and 6 National publishers. I have guidance in Ph.D from J.N.T.U, Kakinada as Supervisor since 2022 to till date. One Research Project Completed Project on Dissecting Autism Trajectories in Longitudinal Electronic Health Records, collaboratively in India and Israel, Govt of India, Ministry of Science and Technology, Dept of Science and Technology. DST-SERB Sponsored International Conference on Algorithms in Advanced Artificial Intelligence, Organized dates at 22nd -24th December 2023, Dept of CSE, SRKR Engineering College, Bhimavaram-534204. AICTE Sponsored National Conference on Productivity, Quality, Reliability, Optimization and Computational Modelling, Organized dates at 18th – 20th December 2019, Dept of CSE & IT, SRKR Engineering College, Bhimavaram-534204. Three Faculty programs organized Webinar on Blockchain Technology: Insights and Applications,13th August, 2022 at Dept of CSE, SRKR Engineering College, Bhimavaram. Resource Person by Dr. Hussein El Ghor, Professor in CSE, Lebanese University, Lebanon. Faculty Development Program on Data Science and Its Application, Dept of CSE, Sponsored by SRKR Engineering College, June 10th – 15th, 2021. National Seminar Symposia DST□SERB Workshop on Machine Learning Evolve Predictive Data Analytics, Dept of IT, SRKR Engineering College, Sanction Order No: SSY/2017/001121, Sanctioned Date: 13-12-2017, Organized Date:23rd to 28th, July, 2018. Attended many Faculty Development Programs.
Dr. Vasamsetty Chandra Sekhar
PhD is Professor and Head of the Department of Computer Science and Engineering Department of Sagi Ramakrishnam Raju Engineering College, Andhra Pradesh, India. He has written and co written multiple articles for IEEE and Elsevier, two peer-reviewed SCI journals for which he has also served as a reviewer. Additionally, he has taken part in numerous international conferences. Software engineering and machine learning are two of his research interests. His main area of study is investigating various IoT and software engineering techniques to address a number of difficult issues in summarization, design, and analysis.Dr.V. Chandra Sekhar received his M.Tech (Computer Science and Technology) and PhD degrees from Andhra University in Visakhapatnam. He has over 26 research papers, over book chapters, and one patent published, one authored book published in peer-reviewed publications. Faculty Development Programs were arranged by him. Software engineering, machine learning, and the Internet of Things are some of his research interests. Vice-Chair, Computer Society, IEEE Vizag Bay Section.
Dr. V. M. N. S. S. V. K. R. Gupta
PhD is Associate Professor of Computer Science and Engineering Department of Sagi Ramakrishnam Raju Engineering College, Andhra Pradesh, India. He has written and co-written multiple articles for IEEE and Elsevier, two peer-reviewed SCI journals for which he has also served as a reviewer. Additionally, he has taken part in numerous international conferences. Data Mining and Healthcare are two of his research interests. His main area of study is investigating various techniques to address a number of difficult issues in summarization, and analysis. Dr. Gupta received his M.Tech (Computer Science and Technology) from Andhra University and PhD degrees from K. L. University in Guntur. He has over 22 research papers, over three book chapters, and three patents published in peer-reviewed publications. He organized faculty development programs. Among his areas of interest in research is machine learning.
