SN Computer Science

Deep learning has grabed more and more interest in recent year’s in order to the development and implementation of big data. Convolutional neural networks that are deep learning neural networks are crucial for facial picture identification. In ...

Virtual machine (VM) clusters are used in cloud computing models to safeguard resources from failure and provide redundancy. Tasks for cloud users are planned by choosing appropriate resources to carry out the work within the virtual machine ...

The popularity of multi-paradigm languages is on the rise, enabling developers to select the most appropriate paradigm for each task. While object-oriented and functional programming are commonly combined, other paradigms can also be hybridized. ...

The convolution layer in a convolutional neural network (CNN) is highly computationally intensive. It is crucial to design reusable low-cost hardware IP for convolutional layer for enabling hardware-based feature extraction. However, the ...

Sports players strive to be the epitome of human excellence, pushing the barrier of skill and execution with training, focus and direction, amplified by regular training and practice. This could be attributed to various factors such as response to ...

Task planning algorithms are essential for maximizing efficiency and enhancing performance in modern computing systems, given the escalating demand for computational resources. This paper delves into the effectiveness of various scheduling ...

This study presents a slotted compact microstrip antenna with reconfigurable feature to provide either a single, dual or triple band notch function. The antenna is specifically developed for applications that require a large frequency range, known ...

An effective task scheduling method can accommodate user needs, boost resource usage, and boost cloud computing's overall efficiency. However, the unchanging task needs are generally the focus of grid computing's job scheduling, leading to low ...

Healthcare has undergone a revolution from version 1.0 to version 4.0, with version 2.0 introducing electronic health records (EHRs) to replace the analysis ones and version 3.0 focusing more on patients. Telehealth, cloud computing, fog computing,...

Counting the people in a moving camera video or picture is difficult since the positions of the people and the camera overlap in the frame. Traditional object recognition techniques use feature matching or optical flow mechanisms, but unable to ...

The COVID-19 pandemic forced rigorous social distancing measures to be put in place to halt the virus’s spread; compliance was extremely difficult. In response, we have designed a highly advanced intelligent drone system that maintains and ...

Demand Response (DR) has become a key strategy for enhancing energy system sustainability and reducing costs. Deep Learning (DL) has emerged as crucial for managing DR's complexity and large data volumes, enabling near real-time decision-making. ...

The vehicular ad hoc networks (VANET) based considered a practical resolution for enhancing the current transportation system’s critical situation, due to the advances of intelligent transportation and a wireless local area network. Drivers can ...

Artificial intelligence (AI) technology is the greatest option for medical applications since it improves data security and reliability. As a result, several AI-driven security procedures are implemented by standard IoT cloud framework ...

In cybersecurity, machine learning-based detection has emerged as a pivotal approach for discovering and mitigating various cyber dangers. The proposed PCA-SVM model demonstrates significant proficiency in distinguishing between normal and ...

Applications for WSN are numerous and include medical status monitoring, military sensing and tracking, and traffic flow monitoring, where sensory devices are frequently moving between different sites. An appropriate encryption key protocol is ...

In distributed Software-Defined Networks (SDN), using multiple controllers brings many benefits but raises new challenges such as scalability and reliability. Mainly, challenges such as the QoS satisfaction and the network load balancing are still ...

Deep learning techniques allow us to learn about a person’s behavior based on pictures and videos. Using digital cameras, the system can identify and classify a person’s behavior based on images and videos. This paper aims to present a method for ...$$

COVID-19 is a highly infectious respiratory illness caused by the novel coronavirus. It was first identified in Wuhan, China in December 2019 and has since spread globally, infecting and killing a vast number of people, leading to a worldwide ...

Diabetes is a non-communicable disease and people face many health issues due to diabetes. Worldwide, more than 500 million people have diabetes today. Currently, most devices measure blood glucose levels from a person’s blood, collected by ...

The world population is anticipated to increase by 2 billion by 2050, causing a rapid escalation of food demand. A recent projection shows that the world is lagging in accomplishing the “Zero Hunger” goal despite some advancements. Socioeconomic ...

In the healthcare industry, early identification of diabetes is a critical task to safeguard human life. Many individuals suffer the consequences of undetected diabetes due to the lack of consistent early identification of the disease's nature. ...

Wireless Rechargeable Sensor Networks (WRSNs) are pivotal to providing sustainable power to an extensive array of recent technologies. Herein, energy replenishment of nodes takes place via Mobile chargers (MCs). However, optimizing their ...

Being the most deadly kind of skin cancer, melanoma presents a serious risk to life and is increasingly prevalent, particularly among men. It is characterized by aggressive cell multiplication that can spread within the body if left untreated, ...

This paper presents a comprehensive study on the contribution of various factors in “League of Legends” (LoL) matches. The research focuses on multiple aspects, including match analysis, data reduction strategies, predictive models, and ...

Effective event correlation is essential for network management systems to promptly identify and address issues. However, conventional algorithms face performance challenges in scenarios with high bandwidth demand, leading to latency, packet ...

We implement an innovative strategy for metaphor identification and interpretation in texts using three different GPT OpenAI models. Metaphors are a very frequent cognitive and linguistic resource, pervasive in multiple types of human ...

Ad creative is one of the main mediums for e-commerce advertising. Ad creative with good visuals may increase a product’s click-through rate(ctr). In recent years, unlike artificially produced ad creatives, advertising platforms can automatically ...

Representation of compound information in a truthful, coarse way forms the layout of the granular computing paradigm. In granular computing, the continuous variables are mapped into intervals to be utilized in the extraction of fuzzy graphs from ...$\mathrm{}$$\mathrm{}$$\mathrm{}$$\mathrm{}$

Potatoes are an essential global staple, but their susceptibility to various diseases poses a major threat to agricultural productivity. Thus, it is imperative to detect these diseases in good time to implement effective management strategies. In ...