• Optimizing Pricing Strategies in E-commerce Supply Chain Management 

  Kumari, Prema; Raj, Antony (2024-07-25)

  In the competitive realm of e-commerce, optimizing pricing strategies within supply chain man agement is essential for maximizing revenue while remaining competitive. This study provides a thorough analysis of pricing ...
• Instruction-Level Customization and Automatic Generation of Embedded Systems Cores for FPGA 

  Yehia, Omar; Raafat, Sandra; El-kharashi, Watheq; Wahba, Ayman; Salama, Cherif (2024-07-24)

  Reducing power consumption and improving performance are crucial requirements for many applications, especially power hungry and time-consuming applications. This is particularly true when these applications are running ...
• Human Resource Information Systems in Higher Education Institutions 

  Mascariñas, Redeen; Daniel Solatorio, Jervene; Franz Rafols, Erick; Marc Ramos, Jaerold; Mordeno, Emelyn; Lin Aung, Nay; Rarugal, Junil; Clark Velasco, Lemuel (2024-07-24)

  This study explores the growing interest in Human Resource Information Systems (HRIS) within Higher Education Institutions (HEIs). A structured review following PRISMA 2020 guidelines analyzed 21 journal articles to ...
• Toward a New Similarity Measure Based on Combining Tourist Check-ins and Their Trip Path for a Point-Of-Interest Recommendations in a LBSN 

  Bettache, Djelloul; Nassim, Dennouni (2024-07-19)

  In recent years, tourists have tended to share their travel experiences with friends through location-based social networks (LBSNs). However, these networks accumulate large masses of data, making them ineffective in ...
• Towards Trustworthy Healthcare Systems: Designing Blockchain-Based Secure Electronic Health Records 

  Singh, Puneeta; Sagar, Shrddha (2024-07-19)

  Detecting fraudulent medical documents remains a significant challenge in the Web2 industry. This project proposes the use of blockchain technology and soul-bound tokens (SBTs) to automate and secure medical document ...
• Enhancing Heart Disease Prediction Based on B-Spline Curves and Machine Learning Algorithms 

  Abdul Ameer Jabbar, Mohammed; Jaber Almaaly, Abdul mohssen; Tareq Abd, Mustafa; Merhej Radhi, Abdulkareem (2024-07-19)

  Predicting heart attacks, is crucial as it can save lives and reduce the personal and societal impact of cardiovascular diseases. Early detection allows for timely intervention, enabling individuals to make lifestyle ...
• Data to Cartography new MDE-based approach for urban satellite image classification 

  Ouchra, Hafsa; Belangour, Abdessamad; Erraissi, Allae; Labied, Maria (2024-06-19)

  Monitoring the earth's surface is greatly enhanced using optical remote sensing via satellites such as SPOT, Landsat and Sentinel2. These satellites capture images from a variety of sources and at different dates, creating ...
• Generative AI with ensemble machine learning framework for computer science graduates employability prediction using educational big data 

  Rattan, Vikas; Mittal, Ruchi; Singh, Jaiteg (2024-07-19)

  The employability of graduates has become a measure, for institutions because of the increasing number of graduates entering the job market and the intense competition for good job opportunities. Many studies have attempted ...
• An Improved Particle Swarm Optimization integrated Dilation Convolutional Neural Network for Automatic Soybean Leaf Disease Identification 

  Jena, Bhabanisankar; Ranjan Routray, Ashanta; Nayak, Janmenjoy (2024-07-19)

  Leaf disease is a prominent and destructive ailment that affects plants. Timely identification and early detection are crucial for enhancing the future probability of leaf diseases that impact plants. The investigation ...
• Automatic Deep-Sea Amphorae Detection Using Optimal 2D Ultralytics Deep Learning 

  kamal Al-anni, Maad; DRAP, Pierre (2024-07-19)

  Despite the challenges in modern digital documentation, current research prioritizes computer-aided semantic segmentation in underwater environments and temporal monitoring, particularly for the digital documentation of ...
• Towards a new generation of intelligent, adaptive e-learning platforms 

  Omar, Abdennour; Hassane, Kemouss; Mohamed, Khaldi (2024-07-19)

  Learning Management Systems (LMS) have evolved considerably, offering flexible and affordable access to learning and training. However, limitations persist in current solutions, such as a lack of personalisation, limited ...
• Review on colorectal cancer biomarkers 

  Kumar, Anand; Kaur, Savleen (2024-07-19)

  The integration of artificial intelligence (AI) into healthcare holds significant potential for enhancing colon cancer detection, prediction, and patient care. AI can significantly improve decision-making processes, ...
• Predicting Big data Drug Interactions and associated side effects by Using Artificial Neural Networks (ANN) over Traditional Graph Convolutional Networks (GCNs) 

  Abed Mohammed, Tareq; Nabeel DARA, Omer (2024-07-19)

  Rapid advances in machine learning have enabled the prediction of complex drug-drug interactions (DDIs) and associated harmful effects. This study aims to develop a neural network model that can predict drug-drug ...
• Word sense disambiguation task for Bodo language using Attention based Deep CNN architecture 

  Basumatary, Subungshri; Barman, Manas; Kumar Barman, Anup; Nag, Amitava; Brahma, Bihung (2024-07-19)

  Interest in Natural Language Processing (NLP) has grown very quickly over the last decades, mainly because it provides tools to represent and analyze human languages computationally. A key challenge in NLP is word ...
• Optimized Efficiency of IoT-Based Next Generation Smart Wireless Sensor Networks Using a Machine Learning Algorithm 

  H.B, Mahesh; Ahammed, Ali; S.M, Usha; S, Mallikarjunaswamy (2024-07-13)

  The rapid advancement of IoT-based smart wireless sensor networks has necessitated optimized efficiency to meet the growing demands of various applications. In our daily lives, smart devices increasingly depend on these ...
• An IoT and Machine Learning-driven Advanced Greenhouse Farming System for Precision Agriculture 

  Hemal, Moniruzzaman; Saha, Suman; Nur, Kamruddin (2024-07-13)

  With the world population projected to reach 9.8 billion by 2050, sustainable food production has become a significant concern. Adverse climatic changes and increasing pressure on food security have led to the search for ...
• Cardiovascular disease prediction: Ranking the significant features using Hybrid Accumulated Feature Selection (HAFS) Method 

  Omkari, Yaso; Shinde, Snehal; Diwan, Tausif; K Pikle, Nileshchandra; Borkar, Pradnya (2024-07-13)

  Heart disease has become a major problem recently, lowering people’s standard of living. There is a pressing need to improve prediction models for cardiac data, machine learning has achieved outstanding results in predicting ...
• A Systematic Review of Multilingual Numeral Recognition Using Machine and Deep Learning Methodology 

  Jabde, Meenal; Patil, Chandrashekhar; D. Vibhute, Amol; R. Saini, Jatinderkumar (2024-07-13)

  The COVID-19 epidemic has altered how people live and interact with one another and tangible objects. The offline optical character recognition (OCR) system has been affected in this regard. Due to its practical uses, ...
• Enhancing the Scalable Asynchronous Cache Consistency Scheme with the Clock Algorithm 

  A. Haraty, Ramzi; G. Tchangoulian, and Meghry (2024-07-13)

  : In recent years, mobile computing has seen significant advancements, largely driven by the development and expansion of wireless networks. This technological evolution has given rise to various models and strategies ...
• Multimodal Graph-based Recommendation System using Hybrid Filtering Approach 

  Gupta, Sorabh; Kumar Bindal, Amit; Prasad, Devendra (2024-07-13)

  This paper proposes a multimodal graph based recommendation system using a hybrid filtering approach. The proposed approach uses various sources of data and advanced graph based deep learning algorithms to provide more ...

View more