Annals of Computer Science and Information Systems, Volume 38
Proceedings of the Eighth International Conference on Research in Intelligent Computing in Engineering
Preface
Dear Reader, we are delighted to share with you a glimpse of the 8th International Conference on Research in Intelligent Computing in Engineering (RICE 2023). RICE 2023 is organized by the Department of Computer Science and Information Technology, School of Technology, Maulana Azad National Urdu University (A Central University), Hyderabad, Telangana, India; Jointly co-organized by Universidad Don Bosco, El Salvador, CA, during December 1st–2nd, 2023.
We are truly thankful to the Polish Information Processing Society (PTI), Poland for approving the proceedings of the 8th International Conference on Research in Intelligent Computing in Engineering (RICE 2023). It is appearing in the Annals of Computer Science and Information Systems series by PTI (ISSN-2300-5963). The series has been submitted to Copernicus, DBLP, Cross Ref, Scholar, BazEkon, Open Access Library, Academic Keys, Journal Click, PBN, and ARIANTE. At this stage, the efforts, whole-hearted support, and suggestions given by Editor-in-Chief Prof. Marcin Paprzycki and Prof. Maria Ganzha are highly applaudable and commendable.
We are pleased to report that various researchers are interested in participating in the 8th edition of RICE 2023. It is a privilege for us to hear five keynote speakers from different countries share their insightful perspectives on conference-related topics. The information is provided below:
- Dr. Le Anh Ngoc, Director of Innovations, Swinburne Vietnam Alliance.
- Dr. A. Govardhan, Senior Professor & Rector, Jawaharlal Nehru Technical University, Hyderabad, India.
- Dr. Tran Duc Tan, Vice Dean, Phenikaa University, Hanoi, Vietnam.
- Dr. Atul Negi, Professor, CSIS, University of Hyderabad, India.
- Dr. Bui Tien Son, Hanoi University of Industry, Hanoi, Vietnam.
Finally, we would like to take this opportunity to express our sincere appreciation to the Advisory Board, Technical Program Committee, Organizing Committee, International Scientific Committee, institutions, industries, and volunteers, who contributed to the success of this conference either directly or indirectly.
Proceeding’s Editors – RICE 2023:
Pradeep Kumar, Maulana Azad National Urdu University, Hyderabad, Telangana, India.
Manuel Cardona, Universidad Don Bosco, El Salvador, Central America.
Vijender Kumar Solanki, CMR Institute of Technology, Hyderabad, Telangana, India.
Tran Duc Tan, Phenikaa University, Hanoi, Vietnam.
Abdul Wahid, Maulana Azad National Urdu University, Hyderabad, Telangana, India.
The Eighth International Conference on Research in Intelligent Computing in Engineering
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Applications of Machine Learning for Diabetes Prediction
43 Machine Learning, Data Mining, Diabetes Prediction, Support Vector Machine, Neural Networks Nayeem Ahmed, Syed Imtiyaz Hassan, Md. Zair Hussain, pages 1–6. -
Classification of Plant Species with Iris Dataset Using ANN, KNN and K-Means Algorithms
63 iris, plant species, ann, knn, k-means, classification M. Hanefi Calp, Vijender Kumar Solanki, pages 7–10. -
An Efficient Ontology Based Drug Prescription Model
59 drug, medicine, prescription, ontology, interactions Md. Gulzar, Muqeem Ahmed, pages 11–15. -
Machine Learning Algorithms for Retinal Image Analysis and Glaucoma Detection
25 Retinal image, SVM, K-NN, segmentation, FC-CRF Akhter Hussain Syed, Pratap Mohanrao Mohite, Sandip Eknathrao Ingle, Mohammad Waseem Ahmed Siddiqui, Zeeshan Raziuddin Mohammed, pages 17–22. -
A Review on Software Engineering: Perspective of Emerging Technologies & Challenges
51 Software Engineering, blockchain, cloud computing, deep learning, game development Kulashekar Inkollu, Sai Kiran Gorle, Sai Ram Kondabattula, Pagalla Bhavani Shankar, M. Babu Reddy, pages 23–27. -
Detection of Copy-Move Image Forgery Using Local Binary Pattern from Detailed Wavelet Coefficient
29 Image Forgery, DILBP (Detailed image local binary pattern), local binary patterns (LBP), set difference, Wavelet Decomposition Daljeet Kaur, Ajay Lala, Kamaljeet Singh Kalsi, pages 29–33. -
AI-driven rental bicycle system: An Ensemble learning approach
87 bicycle rental system, BSS, artificial intelligence, ensemble technique, feedback Cu Kim Long, Trinh Thi Thu Hoang, Gloria Jeanette Rinco'n Aponte, Vikram Puri, pages 35–39. -
Immersive Virtual Painting: Pushing Boundaries in Real-Time Computer Vision using OpenCV with C++
58 Computer Vision, OpenCV, Real-time Interaction, Virtual Painting, Color Detection Algorithms, Digital Canvas Rendering Satyam Mishra, Vu Duy Trung, Le Anh Ngoc, Phung Thao Vi, Sundaram Mishra, pages 41–50. -
Herbal Drug Medicines in the Prevention and Management of COVID Pandemic: A Case Study of ZINDA TILISMATH using Clustering Approach
30 Complementary Therapy, Covid Pandemic, Herbal Plants, Zinda Tilismath Reshma Nikhat, Fahmina Taranum, Mariyam Arshia, pages 51–55. -
Fake News Identification Using Supervised Machine Learning Algorithms
27 Natural language processing, Passive Aggressive Classifier, Supervised Machine Learning Md Nooruddin Rabbani, Abdul Wahid, Fareeha Rasheed, pages 57–61. -
Data Aggregation Techniques and Challenges in the Internet of Things: A Comprehensive Review
20 Data Aggregation, Tree based mechanism, Cluster based mechanism, centralized based mechanism, Internet of Things Fatima Shaheen, Ahamed Jameel, pages 63–72. -
Supply Chain for Agriculture Products Using Blockchain Technology
74 Blockchain Technology, cyberattacks, encryption, supply chain Pagalla Bhavani Shankar, M. Babu Reddy, Yarlagadda Divya Vani, pages 73–77. -
Survey of Big Data Analytics in IoT-Driven Healthcare Applications: A Comparative Approach
19 Big Data, Internet of Things, Big Data Analytics, Healthcare J R Shruti, Shubha Vibhu Malige, pages 79–84. -
Machine Learning Approach for Forecasting Job Appeasement and Employee Corrosion
17 Support Vector Machine (SVM), Random Forest, Decision tree, Logistic Regression M S Swetha, S Mahalakshmi, S K Pushpa, Amrutha T Madihalli, Ananya, Anand Bhardwaj, pages 85–91. -
Emerging Trends In Pulsar Star Studies: A Synthesis Of Machine Learning Techniques In Pulsar Star Research
66 Machine Learning, Ensemble Learning, Boosting, Deep Convolutional Network S. Thanu, Dr. V. Subha, pages 93–98. -
MACCHIEF—Machine learning-based Algorithm Classification for Complaint Handling and Improved Efficiency in Firms
56 Classification Algorithms, Machine Learning Models, Algorithm Evaluation, LGBMClassifier, LinearSVC, CatBoost Algorithm Vu Duy Trung, Yan Chi Toh, Satyam Mishra, Le Anh Ngoc, Phung Thao Vi, pages 99–103. -
DICKT—Deep Learning-Based Image Captioning using Keras and TensorFlow
55 Image Captioning, Deep Learning, Keras, TensorFlow, BLEU Phung Thao Vi, Satyam Mishra, Le Anh Ngoc, Sundaram Mishra, Vu Minh Phuc, pages 105–110. -
Unemployment Rate Future Forecasting Using Supervised Machine Learning Models
12 Unemployment rate, SVM, Random Forest, Gradient Boosting, and Extreme Machine Learning Nareddy Vinaya, Vijender Kumar Solanki, L Arokia Jesu Prabhu, Sivadi Balakrishna, pages 111–114. -
Utilizing Flex Sensors for the Evaluation of Parkinson's Disease
75 Flex Sensor, Glove, Microcontroller, Parkinson’s Disease Quan Vu, To-Hieu Dao, Manh-Cuong Nguyen, Duc-Tan Tran, pages 115–120.
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