Computer Science Research Papers/Topics

Mobile Based Image Analysis System For Cervical Cancer Detection

ABSTRACT Cervical cancer is the third major killer disease in developed and developing countries. Whereas screening and other preventive measures reduce the mortality rate in developed countries, mortality rates still remain very high in developing countries. This project focuses on the analysis of a digital image of the cervix; captured with a low-level camera, under a contrast agent: the visual inspection with acetic acid (VIA) is known as one of the reference methods to detect cervical ca...

A Hybridized Recommendation System On Movie Data Using Content-Based And Collaborative Filtering

ABSTRACT In recent times, the rate of growth in information available on the internet has resulted in large amounts of data and an increase in online users. The Recommendation System has been employed to empower users to make informed and accurate decisions from the vast abundance of information. In this Research, we propose a hybrid recommender engine which combines Content-Based and Collaborative filtering recommendations. This seeks to explore how prediction accuracy can be enhanced in ex...

Semantic Sentiment Analysis Based On Probabilistic Graphical Models And Recurrent Neural Networks

ABSTRACT Sentiment Analysis is the task of classifying documents based on the sentiments expressed in textual form, this can be achieved by using lexical and semantic methods. The purpose of this study is to investigate the use of semantics to perform sentiment analysis based on probabilistic graphical models and recurrent neural networks. In the empirical evaluation, the classification performance of the graphical models was compared with some traditional machine learning classifiers and a ...

Intelligent Tutoring System For Learning Object Oriented Programming Language

ABSTRACT Taking Nigeria as a case study, most educational institutions, be it at the primary, secondary or tertiary level are faced with the challenge of over population of student’s in a single classroom. Also, the teacher who teaches an over populated class finds it quite difficult to have a one on one interaction or communication with each student in order to learning challenges. As a result of that, most students find it difficult to understand in the classroom. This research is concer...

On Big Data Management In Internet Of Things

ABSTRACT The Internet of Things (IoT) has generated a large amount of research interest across a wide variety of technical areas. These include the physical devices themselves, communications among them, and relationships between them. One of the effects of ubiquitous sensors networked together into large ecosystems has been an enormous flow of data supporting a wide variety of applications. In this work, we propose a new “IntelliFog-Cloud” approach to IoT Big Data Management by leveragi...

Implementation Of New Fault Tolerance Solution In Wireless Sensor Networks In A Multi-Channel Context

ABSTRACT Wireless sensor network is application specific, which is deployed in an interested area like about hundred or thousands of sensor nodes. All the sensor nodes communicate via a wireless medium and works cooperatively to sense the environment in order to achieve the required task. Such sensor nodes which is application specific needs a good fault tolerance scheme to keep the system working. Since this sensor nodes are battery operated, have a small memory, deployed in harsh environme...

A Smart Media-Based Recommendation System

Abstract Smart media devices such as: smartphones and tablets are getting more powerful, smarter, cheaper and hence more popular. Recommendation systems become very common in e-business and e-Commerce, for example: Amazon, Google, eBay, Facebook, etc. all are using recommendation systems to promote their business. Recommendation systems are rarely used in learning; however it can be very useful.

Hardware Emulation Study Of Neuronal Processing In Cortex For Pattern Recognition

ABSTRACT Artificial Neural network (ANN) is an area of computing that is modeled after the neural network of the biological brain and over the last few decades, has experienced huge success in its application in areas such as business, Medicine, Industry, Automotive, Astronomy, Finance, etc. Since Neural Networks are inherently parallel architectures, there have been several earlier researches to build custom ASIC based systems that include multiple parallel processing units. However, these ...

A Fuzzy-Based Approach For Modelling Preferences Of Users In Multi-Criteria Recommender Systems

ABSTRACT Recommender systems are web-based platforms or software that use various machine learning methods to propose useful items to users. Several techniques have been used to develop such a system for generating a list of recommendations. Multi-criteria is a new technique that recommends items based on multiple characteristics or attributes of the items. This technique has been used to solve many recommendation problems and its predictive performance has been tested and proven to be more ...

Wireless Sensor Networks For Environmental Monitoring Applications

ABSTRACT After many years of rigorous research and development in wireless sensor network (WSN) technology with numerous responses to innovative applications, WSNs still have some interesting unanswered questions. In this thesis we explain the challenges of the state of art in WSN for environmental monitoring applications using open-source hardware platforms, Arduino UNO, DHT11 temperature-humidity sensor, XBee and Raspberry Pi. The system is not only low cost but scalable enough to accept m...

Face Verification With Statistical Models Of Shape And Appearance

ABSTRACT Research in computer vision and machine learning is a significant part of research in computer science departments of many leading institutions resulting in ideas and products that have direct applications in different industries such as medical image segmentation in the medical industry, and face recognition and tracking in the entertainment and security industry. Face recognition is a significant part of research in computer vision and machine learning and has a wide range of appl...

Employing Probabilistic Matching Algorithms For Identity Management In The Telecommunication Industry

ABSTRACT The telecommunication industry has a lot of data related to households, individuals and devices. Advertisers pay a premium to ensure they advertise to their target audience. To ensure that content is personalized, it is necessary to accurately predict who is using a device in real time. A probabilistic matching algorithm to determine the profile of an individual based on behavioural analytics is developed and implemented. Two datasets ‘People data’ and ‘Device data’ were lin...

Machine Learning Text Analyzer - Text Classification Using Supervised And Un-Supervised Algorithms

ABSTRACT Text analysis is a branch of data mining that deals with text documents. This project brings to light the classification of texts into their various categories. The structured and unstructured data seems to on a high rise in this era. Thus, to be able to classify this data is important. Classification however starts from collection, preprocessing, and feature extraction. There are several techniques that can be used for text classification, but machine learning algorithms will be em...

Combining Machine Learning Techniques With Statistical Shape Models In Medical Image Segmentation

ABSTRACT In this thesis, we implemented Point Distribution Model and basic Active Shape Model algorithm and contributed this to the AUST Computer Vision and Machine Learning code library. We applied the Active Shape Model to segmenting lateral ventricles of 2D brain images and used machine learning – specifically K-Nearest Neighbour algorithm- to improve segmentation results. A statistical shape model is created from a training dataset which is used to search for an object of interest in a...

Interactive Simulation Of Well Placement Technology

Abstract We attempt the design and development of an educational game based on the Input-ProcessOutcome model. This tool helps students and other professionals to learn and appreciate the decision-making processes carried out by geophysicists and petroleum engineers, concerned with the activity of well placement, to maximize production from oil fields. It also stimulates learning and application of technology to support decision making.


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