MALARIA PREDICTION USING BAYESIAN AND OTHER MACHINE LEARNING TECHNIQUES
Abstract:
Malaria continues to be a significant public health concern worldwide, particularly in tropical and subtropical regions. Early detection and accurate prediction of malaria outbreaks are crucial...
AUTOMATIC DETECTION OF INJECTON ATTACK IN HTTP REQUESTS
Abstract:
Injection attacks, such as SQL injection and cross-site scripting (XSS), continue to pose significant security threats to web applications. These attacks exploit vulnerabilities in...
SEMANTIC SENTIMENT ANALYSIS BASED ON PROBABILISTIC GRAPHICAL MODELS AND RECURRENT NEURAL...
Abstract:
Semantic sentiment analysis is a vital task in natural language processing, aiming to extract and analyze the sentiment expressed in textual data. In recent years, the...
EMPLOYING PROBABILISTIC MATCHING ALGORITHMS FOR IDENTITY MANAGEMENT IN THE TELECOMMUNICATION INDUSTRY
Abstract:
In the telecommunication industry, effective identity management is crucial for maintaining secure and reliable communication services. With the increasing prevalence of digital services and the proliferation...
OBSERVATORY SYSTEM FOR MONITORING ELECTRIC POWER DEMAND AND DELIVERY
Abstract:
The rapid growth of electricity demand and the increasing complexity of power delivery systems necessitate the development of advanced monitoring systems to ensure efficient...
CLASSIFICATION OF BREAST CANCER USING LOGISTIC REGRESSION
Abstract:
Breast cancer is a critical health issue affecting women worldwide, making early and accurate diagnosis crucial for effective treatment and improved patient outcomes. Machine...
STUDY OF SCALABLE DEEP NEURAL NETWORK FOR WILDLIFE ANIMAL RECOGNITION AND...
Abstract:
The rapid advancement of deep learning techniques has opened up new possibilities for wildlife conservation and research. In this study, we investigate the application...
INTELLIGENT TUTORING SYSTEM FOR LEARNING OBJECT ORIENTED PROGRAMMING LANGUAGE
Abstract:
The field of computer programming has seen a significant rise in demand for skilled professionals proficient in object-oriented programming (OOP) languages. However, learning OOP concepts can...
TEXT MINING OF TWITTER DATA
Abstract:
Twitter has emerged as a valuable source of real-time information and a platform for expressing opinions, sharing news, and discussing various topics. The massive volume and...
COMPARATIVE STUDY OF ANNOTATION TOOLS AND TECHNIQUES
Abstract:
Annotation tools and techniques play a crucial role in various domains, such as natural language processing, computer vision, and machine learning, where labeled data...
PREDICTION OF HEART DISEASE USING BAYESIAN NETWORK MODEL
Abstract:
Heart disease continues to be a leading cause of mortality worldwide, emphasizing the importance of accurate early detection and prediction. This abstract presents a...
DESIGN AND IMPLEMENTATION OF FAST AND ACCURATE FEATURE-BASED REGION IDENTIFICATION
Abstract:
Feature-based region identification plays a crucial role in various computer vision and image processing applications, such as object recognition, image segmentation, and scene understanding. The ability...
OBSERVATORY SYSTEM FOR MONITORING HEPATITIS C DEVELOPMENT IN NIGERIA
Abstract:
Hepatitis C is a significant public health concern globally, including in Nigeria, where the prevalence of the disease is relatively high. To combat the...
SENTIMENT ANALYSIS BASED ON SOCIAL MEDIA DATA
Abstract:
Sentiment analysis, also known as opinion mining, is a rapidly growing field in natural language processing (NLP) that aims to automatically determine the sentiment...
A FUZZY-BASED APPROACH FOR MODELLING PREFERENCES OF USERS IN MULTI-CRITERIA RECOMMENDER...
Abstract:
In recent years, recommender systems have gained significant attention due to their ability to assist users in finding relevant and personalized recommendations in various...
