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Although numerous amounts of research have been done to find alternate sources of energy consumption and its applications. But in times of energy crisis and global warming urgency, it is needed to pace towards methods of less dependency on fossil fuels in the …

This study basically presents a review of robotic hands and its applications based on human hand motion. In the context of the review, different kinds of articles are analyzed. There are some hand motion-sensing methods, which are noncontact and direct contact…

Digital image processing has become popular research area recently because of its widespread application compatibility such as security, robotics, quality control, face authentication. Skin segmentation methodology, which is a tool of digital image processing,…

The successful estimation of future electricity consumption has a crucial importance in the energy planning. Because, in order to meet rising energy demand, policy makers should formulate electricity supply policies and make critical decisions and develop ne…

The rapid urbanization and exponential growth in vehicle numbers have significantly increased the demand for parking spaces in metropolitan areas, creating challenges for drivers and urban planners alike. Effective detection of available parking spaces is cruc…

Early detection of lung cancer remains a critical challenge in medical imaging, where accurate classification between benign and malignant pulmonary nodules can significantly impact patient outcomes. This study presents a comprehensive comparative analysis of …

This article presents a comprehensive survey on the integration of Generative Artificial Intelligence (AI) technologies in radar applications, with a focus on enhancing radar data processing and system capabilities. Generative AI techniques, particularly Gener…

We propose using support vector machines (SVMs) as a machine learning classifier in a grain-conditionmonitoring system. This system is used to proactively monitor the silobag-stored grain condition. The system consists of a wireless sensor network (WSN) and a …

Diabetes is a chronic disease affecting millions worldwide, necessitating early and accurate diagnosis for effective management. Traditional diagnostic methods, while reliable, often struggle with efficiency and early-stage detection. Deep learning has emerged…

In this study, diabetes prediction was conducted using XGBoost, Support Vector Machines (SVM), and a Multilayer Artificial Neural Network (ANN). Attributes that cannot be biologically ‘0’ (e.g. glucose, BMI) were first marked as NaN. After filling the missing …

Social networks are formed from interactions of peoples. Measuring the degree of those relationships requires interpreting connectivity of vertices and extracting information from it. Generally individuals form smaller sub-communities in those networks. Identi…

Accurate and transparent blood glucose forecasting is crucial for effective diabetes management. This paper presents an interpretable deep learning (DL) framework based on multi-task learning (MTL) for forecasting glucose levels at multiple prediction horizons…

Over the past century, before and after the pandemic of COVID-19, workers in multiple sectors, such as medical, chemical, and nuclear, have been required to wear face masks during duties. However, physical 24/7 supervision is nearly impossible in public places…

Ball and beam system is an experimental set for control system design that the position of the ball on a beam is changed with respect to the reference direction by changing the angle of the beam. The PID controller is applied to this problem. The performance o…

Hyperspectral images offer a good separability among land cover classes, owing to their advantages to provide spectral bands with narrow wavelength intervals. It is also possible to further increase classification accuracy of hyperspectral images by integrat…

The incidence of skin cancer is increasing. Early detection of cases of skin cancer is vital for treatment. Recently, computerized methods have been widely used in cancer diagnosis. These methods have important advantages such as no human error, short diagnosi…

The main goal of this research is to investigate the potential and current role of generative AI in improving and developing avionics systems, and aviation-related applications. Avionics, a vital part of aviation industry, consists of a set of equipment and el…

Deep learning can provide successful results in detecting manipulations made with bot accounts on the X (Twitter) platform and preventing disinformation. As a method for applying deep learning algorithms, numerical values in the data set can be visualized and …

In the last decade, deep learning in general and Convolutional Neural Networks (CNN) have achieved a human level and outstanding performance in almost all computer-based systems such as classification(text, images, and videos). Building an efficient CNN archit…

The purpose of this study is to examine the software libraries and data sets used for Deep Learning architectures. Deep Learning brings a different perspective to the field of artificial intelligence. It has begun to be used an incredibly wide field in recent …