This research delves into the innovative application of feed-forward neural networks (FNNs) specifically the multi-layer perceptron (MLP). MLP is a flexible algorithm due to its ability to adapt to different realworld problems amongst other features, and this makes it a preferred machine learning algorithm in the early detection of mental health disorders. MLP’s number of layers and the number of neurons per layer changes to accommodate these abilities. MLP was chosen for this work becau...
Abstract: This paper presents a semi supervised clustering technique with incremental and decremented affinity propagation (ID-AP) that structures labeled exemplars into the AP algorithm and a new method for actively selecting informative constraints to make available of improved clustering performance. The clustering and active learning methods are both scalable to large data sets, and can hold very high dimensional data. In this paper, the active learning challenges are examined to choose ...
Abstract: Natural language processing (NLP) is widely used in multi-media real-time applications for understanding human interactions through computer aided-analysis. NLP is common in auto-filling, voice recognition, typo-checking applications, and so forth. Multilingual NLP requires vast data processing and interaction recognition features for leveraging content retrieval precision. To strengthen this concept, a predictive typological content retrieval method is introduced in this article. ...
Abstract: In the living organism, almost entire cell functions are performed by protein-protein interactions. As experimental and computing technology advances, yet more Protein-Protein Interaction (PPI) data becomes processed, and PPI networks become denser. The traditional methods utilize the network structure to examine the protein structure. Still, it consumes more time and cost and creates computing complexity when the system has gene duplications and a complementary interface. This res...
Abstract: Android applications are indispensable resources that facilitate communication, health monitoring, planning, data sharing and synchronization, social interaction, business and financial transactions. However, the rapid increase in the smartphone penetration rate has consequently led to an increase in cyberattacks. Smartphone applications use permissions to allow users to utilize different functionalities, making them susceptible to malicious software (malware). Despite the rise in ...
Abstract: In the world, the man matters, not the machine, people need to be care, not data. There is transition from information technology to human technology. The answer is internet of everything (IoE). The int ernet of everything (IoE) is a concept that extends the internet of things (IOT) by encompassing the machine-to-machine (M2M) communication, machine-to-people (M2P) and technology-assisted people-to-people (P2P) with expended digital features. It includes different types of devices,...
Abstract: Traditional frequent itemsets mining (FIM) suffers from the vast memory cost, small processing speed and insufficient disk space requirements. FIM assumes only binary frequency value for items in the dataset and assumes equal importance value for items. In order to target all these limitations of FIM, high-utility itemsets (HUIs) mining has been presented. HUIs mining is more complicated and difficult than FIM. HUIs mining algorithms spend more execution time because of large searc...
Abstract: We propose a novel face recognition using Dual Tree Complex Wavelet Transform (DTCWT), which is used to extract features from face images. The Complex Wavelet Transform is a tool that uses a dual tree of wavelet filters to find the real and imaginary parts of complex wavelet coefficients. The DT-CWT is, however, less redundant and computationally efficient. CWT is a relatively recent enhancement to the discrete wavelet transform (DWT). We show that it is a well-suited basis for thi...
Abstract: The cloud computing offers dynamically scalable resources provided as a service over the Internet. It promises the drop in capital expenditure. But practically speaking if this is to become reality there are still some challenges which is to be still addressed. Amongst, the main issues are related to security and trust, since the user's data has to be released to the Cloud and thus leaves the secured area of the data owner. The users must trust the providers. There must be a str...
A computer network comprises of a group of computers connected to each other for different purposes. In this way, resources and data can be exchanged between computers. Recent years have seen a rapid advancement in computer technology, which has led organisations to look for more resilient networks that can support both their present and future applications (Al-Bayati, 2013). Strong networking and thoughtful office building design go hand in hand in today's workplace to enhance organisational...
Abstract: Prudence is one of the important features of software quality, as it can affect the stability of software. The cost and reuse of software is also likely to make sense. To maintain software, programmers have to understand the source code. The understanding of source code depends on the psychological complexity of the software, and cognitive abilities are required to understand the source code. The understanding of source code is influenced by so many factors, here we have taken var...
Recruiters’ decisions in the selection of candidates for specific job roles are not only dependent on physical attributes and academic qualifications but also on the fitness of candidates for the specified tasks. In this paper, we propose and develop a simple neuro-fuzzy-based task performance and fitness model for the selection of candidates. This is accomplished by obtaining from Kaggle (an online database) samples of task performance-related data of employees in various firms. Data were ...
Fraud detection is used in various industries, including banking institutes, finance, insurance, government agencies, etc. Recent increases in the number of fraud attempts make fraud detection crucial for safeguarding financial information that is confidential or personal. Many types of fraud problems exist, including card-not-present fraud, fake Marchant, counterfeit checks, stolen credit cards, and others. We proposed an ensemble feature selection technique based on Recursive feature el...
Detecting brain tumors early is crucial for precise diagnosis and the development of effective treatment strategies, given the severity of the condition involving the uncontrolled growth of abnormal cell clusters in the brain.This research introduces an innovative Convolutional Neural Network (CNN) model augmented with an attention mechanism for the classification of brain tumor images, utilizing a comprehensive dataset of 3,000 Magnetic Resonance Imaging (MRI) scans sourced from Kaggle. Rigo...
The frequency and severity of cyber- attacks have surged, causing detrimental impacts on businesses and their operations. To counter the ever-evolving cyber threats, there's a growing need for robust risk assessment systems capable of ef ectively pinpointing and mitigating potential vulnerabilities. This paper introduces an innovative risk assessment technique rooted in both Machine Learning and graph theory, which of ers a method to evaluate and foresee companies' susceptibility to ...