Evaluating Hybrid Model Performance in Predicting the Impact of Lockdown on Controlling Covid-19 Cases Progression in Middle Income Settings
A Method for the Identification of Denial of Service (DoS) Attack in Network Traffic using Machine Learning Techniques
Agriculture Management System
Unveiling Sentiment Analysis: A Comparative Study of LSTM and Logistic Regression Models with XAI Insights
Resume Screener System
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
Integrated Atlas Based Localisation Features in Lungs Images
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
Auction is a system used for buying and selling where the goods are sold to the highest bidder in a list of bidders according to a pre-defined scheme. Over the years, auction systems have dominated the e-commerce arena by providing a more convenient platform for users to purchase and sell products over the internet than traditional markets. Even though the online platform proves convenient, determining an auction winner and allocating such items to the winner with timely notification is a challenge. Therefore, this research proposes the use of Fuzzy Logic Technique to intelligently rate the bidders in an auction process and determine the winner. In this research, the Fuzzy Triangular Membership Function was used for membership grading using four input variables with associated degrees of membership to the linguistic terms of the fuzzy input-output relationship. The system is implemented using Hyper-Text Markup Language 5 (HTML5) and Cascading Style Sheet 3 (CSS3) for client-side application interface, jQuery, AJAX, and PHP for the server-side interface and MySQL relational database management system as the back-end engine while WAMP Apache Server was used as a web server for testing and deployment purposes. However, an online performance survey was carried out based on several parameters such as easy navigation, user-friendliness, speed, functionality, reliability, effectiveness, and so on. Data obtained from user surveys were gathered and used to evaluate the system performance. The results obtained showed the practicality of the system for rating auction users and determining the winner. Comparative results also revealed that the system performs better based on previous findings in the reported literature.
Face detection and Expression recognition are few the ongoing research areas in computer vision. Most of the time, face detection precedes facial expression recognition, i.e., the result of face detection is fed as input into expression recognition. This paper presents face detection based on Viola and Jones algorithm and the issues relating to expression recognition. A facial expression recognition system based on Local Binary Pattern (LBP) for feature extraction and Support Vector Machine (SVM) for classification is presented. Different Facial expressions of the staff and students of the Federal University of Technology, Akure (FUTA) were captured and used as training samples. Matrix laboratory 2016a was used for implementation. The designed system achieved an overall 95.4% recognition rate, which is improvement over an existing systems.
The navigational behaviors of online users are used to improve the design and quality of web pages. For this purpose, the researcher should identify the frequent patterns over a period of time. This paper proposes a numeric matrix based on an approach namely Frequent Page Patterns from Matrix algorithm (FPPM). It yields frequent page patterns that diminish the time intricacy during the processing without degrading the accuracy of results. Navigational behaviors of users are stored in the log file. It can able to produce the associated web pages. There are three various Phases of proposed work. In the first phase, authors pre-process the raw web log dataset. It removes irrelevant data from the dataset. It identifies the sessions according to the interval-based time-limit. In the second phase, the data are clustered, using k-means clustering. Finally, authors apply the FPPM algorithm to mine associated web pages, and it consumes less time. By doing this work, the authors can identify which web pages are really associated with each other. Authors can able to know how to improve the quality of a specific web page based on association results. The relevant records are only progress by this proposed algorithm.
Most of the optimization techniques come under evolutionary and swarm intelligence techniques inspired by the behavior of different species around the world. These techniques play a vital role in solving a wide range of nondeterministic complex optimization problems and intellectually solving various real-world problems. This research paper includes a novel approach inspired by the successive hunting ability of lion from cub to predator is called Evolution of Cub to Predator (ECP). ECP algorithm based on evolving hunting ability of cub learned from parent-lion, environment, and siblings. In the proposed algorithm, lion-cub learns their hunting ability in two ways; initially from parents and resident mate cubs called infant-maturity. Later on, the cub gets matured by develop their hunting ability through real-world executions. The interpretations of cub's intellectual, social behaviour towards its environment place them on top position in the survival of the fittest later on. The investigation includes ten different benchmark test functions for evaluating the performance of the ECP. The result exhibits the proficient execution of ECP for searching the global optimum with several benchmark functions.
This paper brings out the interrelation between three main streams of Artificial Intelligence, Machine Learning, and Deep Learning. It emphasizes the significance of machine learning. On further, it deeply analyses the three types of machine learning,which are Supervised Learning, Unsupervised Learning, and Reinforcement Learning. A prediction machine learning algorithm is implemented using Google Colab, which is the current inventory tool. The potential and the computational capability of the machine an described in this paper. In this world of technologies, it is must to be aware of machine learning. Artificial intelligence (AI) is an area of computer science that empasizes the creation of intelligent machines that work and reacts like humans. Before considering the necessary policies of AI, it is very important to know about neural networks and machine learning. The impact of AI has almost reached greater heights. Self correction is possible using this technique. Research is going on regarding Artificial Intelligence whether it is beneficial for us or not.
