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Reflects downloads up to 21 Dec 2024Bibliometrics
research-article
Performance of Landsat 8 OLI and Sentinel 2 MSI Images Based on MNF Versus PCA Algorithms and Convolution Operators for Automatic Lithuanian Coastline Extraction
Abstract

Faced with the increasing coastalization in the world, exposing populations and activities to coastal risks, decision-support tools based on the extraction of coastlines by remote sensing have become essential for measuring coastal dynamics and ...

research-article
Task-Level Checkpointing and Localized Recovery to Tolerate Permanent Node Failures for Nested Fork–Join Programs in Clusters
Abstract

Exascale supercomputers consist of millions of processing units, and this number is still growing. Therefore, hardware failures, such as permanent node failures, become increasingly frequent. They can be tolerated with system-level Checkpoint/...

research-article
Simulation of Routing Protocols for IoV in Real-Time Mobility Model Environment
Abstract

Vehicles in the Internet of Vehicles (IoV) create wireless connections and participate in routing by sending information to other nodes. Despite the recent growth in popularity of IoV, there are still issues with high vehicle speeds, frequent ...

research-article
pCTFusion: Point Convolution-Transformer Fusion with Semantic Aware Loss for Outdoor LiDAR Point Cloud Segmentation
Abstract

LiDAR-generated point clouds are crucial for perceiving outdoor environments. The segmentation of point clouds is also essential for many applications. Previous research has focused on using self-attention and convolution (local attention) ...

research-article
Hand and Sign Recognition of Alphabets Using YOLOv5
Abstract

Deaf and dumb people who apply visual gestures can communicate using hand, facial, and body gestures. As there are various ways to communicate but still no compatible technologies available that aid in linking this group of deaf and dumb people to ...

research-article
Enhancing DeepFake Detection: Leveraging Mesonet for Video Fraud Identification
Abstract

Machine learning, while a successful and helpful approach, has now sparked widespread public concern because of the availability of technology that can modify photographs and videos of individuals in ways that the average person cannot distinguish ...

research-article
Performance Optimization Across the Edge-Cloud Continuum: A Multi-agent Rollout Approach for Cloud-Native Application Workload Placement
Abstract

The advancements in virtualization technologies and distributed computing infrastructures have sparked the development of cloud-native applications. This is grounded in the breakdown of a monolithic application into smaller, loosely connected ...

research-article
Private Verification in Multi-stakeholder Environment and its Application to Stable Matching
Abstract

This paper provides a solution to mitigate mistrust that arises from untransparency in a multi-stakeholder environment. This work is related to a kind of verifiable computation. When considering the multi-stakeholder environment, not only the ...

research-article
A Literature Perspective of Stakeholder’s Perceptions of Value and Risks for the Secondary Use of Health Data
Abstract

Scientific literature and practice emphasize the need for a robust framework for the secondary use of health data, one that unifies standards and practices. Multiple reviews focus on secondary health data use from the technological perspective; ...

research-article
An Approach for Detection of Botnet Based on Machine Learning Classifier
Abstract

Botnet detection systems are becoming more important as cybercriminals continue to develop new Bot tools and applications. A botnet is a collection of several compromised systems that are connected to the central controller called a botmaster. ...

research-article
Reliable and Accurate Implicit Neural Representation of Multiple Swept Volumes with Application to Safe Human–Robot Interaction
Abstract

In automated production using collaborative robots in a manufacturing cell, a crucial aspect is to avoid collisions to ensure the safety of workers and robots in human–robot interaction. One approach for detecting collisions is using the swept ...

research-article
A Bilateral Assessment of Human Activities Using PSO-Based Feature Optimization and Non-linear Multi-task Least Squares Twin Support Vector Machine
Abstract

Human activity recognition (HAR) is an essential part of many applications, including smart surroundings, sports analysis, and healthcare. Accurately categorizing intricate actions from sensor data is still difficult, though. This method infers an ...

research-article
PRAY So You Don’t Become Prey
Abstract

Cloned journals refer to deceptive or counterfeit scientific journals that imitate genuine scholarly publications with the intention of misleading scholars into submitting their works. As early career researchers fall prey to these hijacked/cloned ...

research-article
Almost: Predicting “Natural" Sequences
Abstract

Neural networks have remained the most widely used learning method for at least one decade thanks to their flexibility in solving problems across fields. Neural networks attempt to model learning based on a simplified version of neural activity in ...

research-article
A Bagging Ensemble Algorithm for Seasonal Time Series Forecasting
Abstract

Time series forecasting is valuable in making informed decisions, improving financial planning, optimizing resource allocation, increasing operational efficiency, and managing risks. But accurate forecasting is difficult, as the amount of out-of-...

research-article
Speech Processing for Arabic Speech Synthesis Based on Concatenation Rules
Abstract

The purpose of this paper is to address speech processing phase of the synthesizer to produce artificial speech from the phonetic sequences generated at the linguistic processing level. This research work is part of the realization of a text-to-...

research-article
Drone Swarm Coordination Using Reinforcement Learning for Efficient Wildfires Fighting
Abstract

Natural events, such as wildfires, pose a serious threat to the human population and cause significant environmental and economic damage. As climate change increases the frequency and intensity of extreme natural events, more efficient solutions ...

research-article
Comparative Assessment of Image Super-Resolution Techniques for Spatial Downscaling of Gridded Rainfall Data
Abstract

With an increasing focus on improving localized understanding of weather and climate phenomena and the computation cost involved in high-resolution modelling, spatial downscaling of data has proven to be a viable alternative method to obtain high-...

research-article
A Lightweight Authentication Protocol for a Blockchain-Based Off-Chain Medical Data Access in Multi-server Environment
Abstract

Presently, blockchain technology is used to secure electronic medical records (EMR) and an arrangement of multiple servers as off-chain storage is advocated to minimize the storage overhead of the medical blockchain. Therefore, an authorized ...

research-article
Lung Cancer Detection by Employing Adaptive Entropy Variance Dropout Regularization in GAN Variants
Abstract

Lung cancer segmentation using Deep Neural Networks (DNN) needs accurate pixel-level data which is typically small. This leads to overfitting issue, and in order to alleviate this, the research is been done on L2 regularization and dropout ...

research-article
Implementation of DEWMA-Based Hello Packet for AODV to Improve the Performance of FANET with 3D-GMM
Abstract

Flying ad hoc network (FANET) is a new sub-domain of MANET (mobile ad hoc network) with moving nodes known as automated flying vehicles (AFV) carrying various loads such as cameras and sensors to work in a limited geographical area. AFV are ...

research-article
Frame Selection Using Spatiotemporal Dynamics and Key Features as Input Pre-processing for Video Super-Resolution Models
Abstract

This paper presents a novel approach to video super-resolution (VSR) by focusing on the selection of input frames, a process critical to VSR. VSR methods typically rely on deep learning techniques, those that are able to learn features from a ...

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