Abstract Determining the grade of colon cancer from tissue slides is a routine part pathological analysis. In case colorectal adenocarcinoma (CRA), grading partly determined by morphology and degree formation glandular structures. Achieving consistency between pathologists difficult due to subjective nature assessment. An objective using computer algorithms will be more consistent, able analyse images in detail. this paper, we measure shape glands with novel metric that call Best Alignment...

Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells energy, resulting high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide 2019, with over four fatalities documented. Blood levels (BGL) are usually measured, as standard protocols, through invasive procedures. Recently, Artificial Intelligence (AI) based techniques have demonstrated the potential estimate BGL using data collected non-invasive Wearable Devices (WDs),...

Harmonic estimation in a distorted signal along with additive noise has been an area of interest for researchers many disciplines science and engineering. This paper presents new algorithm to estimate the harmonics power systems using genetic algorithms (GAs). The harmonic problem is linear amplitude nonlinear phase. proposed hybrid takes advantage this structure iterates between least squares GA-based phase estimation. Improvement both convergence solution as well processing time...

Background: Fuzzy logic is a multi-valued which similar to human thinking and interpretation.It has the potential of combining heuristics into computerassisted decision making, applicable individual patients as it takes account all factors complexities individuals.Fuzzy been applied in disciplines medicine some form recently its applicability neurosciences also gained momentum.Methods: This review focuses on use this concept various branches including basic neuroscience, neurology,...

Fuzzy rule-based systems interpret data in low-dimensional domains, providing transparency and interpretability. In contrast, deep learning excels complex tasks like image speech recognition but is prone to overfitting sparse, unstructured, or data. This interpretability crucial fields healthcare finance. Traditional systems, especially ANFIS with grid partitioning, suffer from exponential rule growth as dimensionality increases. We propose a strategic rule-reduction model that applies...

This work addresses the critical need for early detection of breast cancer, a significant health concern worldwide. Through combination advanced deep learning and machine techniques, we offer comprehensive solution to enhance cancer accuracy. By leveraging state-of-the-art convolutional neural networks (CNNs) like GoogLeNet, AlexNet, ResNet18, alongside traditional classifiers such as k-nearest neighbors (KNN) support vector (SVM), ensure robust prediction capabilities. Our preprocessing...

This work addresses the critical need for early detection of breast cancer, a significant health concern worldwide. Using combination advanced deep learning and machine techniques, we offer comprehensive solution to enhance cancer accuracy. By leveraging state-of-the-art convolutional neural networks (CNNs) like GoogLeNet, AlexNet, ResNet18, alongside traditional classifiers such as k-nearest neighbors (KNN) support vector (SVM), ensure robust prediction capabilities. Our preprocessing...

Increasing number of skyscrapers along with the large tall bridges in urban setting throughout world also increases demand robust and autonomously controlled structural health monitoring (SHM) order to enhance reliability such structures their surroundings. In this paper, an unmanned aerial vehicle (UAV)-based autonomous SHM system has been investigated, which images site captured by UAV were stitched together form complete view structure. The image-stitching task done using a well-known...

The advent of inexpensive digital cameras with depth sensing capabilities (RGB-D cameras) has opened the door to numerous useful applications that need quantitative measures dynamic fields whose simultaneous time history quantification (at many points as dictated by resolution camera) provides were previously accessible only through expensive sensors (e.g., laser scanners). This paper presents a comprehensive experimental and computational study evaluate performance envelope representative...

Children with autism face challenges in various skills (e.g., communication and social) they exhibit challenging behaviours. These behaviours represent a challenge to their families, therapists, caregivers, especially during therapy sessions. In this study, we have investigated several machine learning techniques data modalities acquired using wearable sensors from children interactions social robots toys potential detect Each child wore device that collected data. Video annotations of the...

Internet of Things (IoT) deployments face significant security challenges due to the limited energy and computational power IoT devices. These are more serious in quantum communications era, where certain attackers might have computing capabilities, which renders devices vulnerable. This paper addresses problem by investigating key distribution (QKD) beyond 5G networks. An algorithm for detecting an attacker between a transmitter receiver is proposed, with side effect interrupting QKD...

Abstract Among the most leading causes of mortality across globe are infectious diseases which have cost tremendous lives with latest being coronavirus (COVID-19) that has become recent challenging issue. The extreme nature this virus and its ability to spread without control made it mandatory find an efficient auto-diagnosis system assist people who work in touch patients. As fuzzy logic is considered a powerful technique for modeling vagueness medical practice, Adaptive Neuro-Fuzzy...

This article shares my experiences with the project-based methodology of teaching same material that a standard text in robotics would teach and will comparatively elaborate improvement observed group students involved. Other than understanding course material, use learning has shown great increase motivation focus on subject towards engineering education. The performance is presented this work as comparison respect to underlying program educational outcomes between previous years...

Information security has become a major issue during the last decades where new algorithms based on algebraic methods or chaotic dynamics were suggested for encryption. This paper presents an algorithm encoding binary images using one-dimensional maps. In order to perform pixel value permutation, approach presented uses diffusion property of maps, local information is spread out. Comparison in terms correlation between initial image and transformed provided different degrees chaocity which...

Grading of breast cancer is often done by an expert pathologist based on their analysis micro-level structural features the cancerous tissue specimen as well level presence certain protein molecules in specimen. The process assessment estrogen and progesterone receptors subjective its very nature therefore, causes large inter-expert sometimes even intra-expert variability, potentially adding noise to selecting treatment regime for patient. Quantification immunohistochemical stains critical...

Roaming complexity in terrains and unexpected environments pose significant difficulties robotic exploration of an area. In a broader sense, robots have to face two common tasks during exploration, namely, walking on the drylands swimming through water. This research aims design develop amphibious robot, which incorporates webbed duck feet walk different terrains, swim water, tackle obstructions its way. The designed robot is compact, easy use, also has abilities work autonomously. Such...