Abstract This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation nucleus cytoplasm lymphocytes/lymphoblasts. Specifically, the evaluation formulated based on trade-off several well-known feature extraction methods. The SDM are used in...

The recent expansion of pervasive computing technology has contributed with novel means to pursue human activities in urban space. dynamics unveiled by these generate an enormous amount data. These data are mainly endowed portable and radio-frequency devices, transportation systems, video surveillance, satellites, unmanned aerial vehicles, social networking services. This opened a new avenue opportunities, understand predict detail, plan various real-time services applications response that....

Purpose Phishing attacks have evolved in recent years due to high-tech-enabled economic growth worldwide. The rise all types of fraud loss 2019 has been attributed the increase deception scams and impersonation, as well sophisticated online such phishing. global impact phishing will continue intensify, thus, a more efficient detection method is required protect user activities. To address this need, study focussed on design development deep learning-based solution that leveraged universal...

This paper presents an investigation into the development of intelligent mobile-enabled expert system to perform automatic detection tuberculosis (TB) disease in real-time. One third global population are infected with TB bacterium, and prevailing diagnosis methods either resource-intensive or time consuming. Thus, a reliable easy–to-use has become essential make world free by 2030, as envisioned World Health Organisation. In this work, challenges implementing efficient image processing...

Classification Data Mining (DM) Techniques can be a very useful tool in detecting and identifying e-banking phishing websites. In this paper, we present novel approach to overcome the difficulty complexity predicting website. We proposed an intelligent resilient effective model that is based on using association classification algorithms. These algorithms were used characterize identify all factors rules order classify website relationship correlate them with each other. implemented six...

The term “Liver disease” refers to a broad category of disorders affecting the liver. There are variety common liver ailments, such as hepatitis, cirrhosis, and cancer. Accurate early diagnosis is an emergent demand for prediction disease. Conventional diagnostic techniques, radiological, CT scan, function tests, often time-consuming prone inaccuracies in several cases. An application machine learning (ML) deep (DL) techniques efficient approach diagnosing diseases wide range medical fields....

Phishing Websites are forged Web pages that created by malicious people to mimic of real and it attempts defraud their personal information. Detecting identifying is really a complex dynamic problem involving many factors criteria, because the subjective considerations ambiguities involved in detection, Fuzzy Logic model can be an effective tool assessing phishing than any other traditional since offers more natural way dealing with quality rather exact values. In this paper, we present...

Over time for the past few years, facial expression identification has been a promising area. However, darkness, lighting conditions, and other factors make emotion challenging to detect. As result, thermal images are suggested as solution such problems variety of benefits. Furthermore, focusing on significant regions face rather than entire is sufficient reducing processing improving accuracy at same time. This research introduces novel infrared image-based approaches recognition. First,...

Phishers sometimes exploit users' trust of a known website's appearance by using similar page that looks like the legitimate site. In recent times, researchers have tried to identify and classify issues can contribute detection phishing websites. This study focuses on design development deep learning based solution leverages Universal Resource Locator website content such as images frame elements. A Convolutional Neural Network (CNN) Long Short-Term Memory (LSTM) algorithm were used build...

The automatic facial expression tracking method has become an emergent topic during the last few decades. It is a challenging problem that impacts many fields such as virtual reality, security surveillance, driver safety, homeland security, human-computer interaction, medical applications. A remarkable cost-efficiency can be achieved by considering some areas of face. These are termed Active Regions Interest (AROIs). This work proposes recognition framework investigates five types...

Human injuries and deaths occur often during public events like concerts, religious services, political rallies because of a lack proper crowd safety oversight. A small disaster can trigger panic in huge crowd. Many intelligent video surveillance solutions identify things, but despite the recent developments artificial intelligence approaches deep learning processes, it is very probable to track congested crowds their mobility avoid future detection disasters. Searching for points interest...