In terms of social, psychological, physical, technological, and other elements, the educational system is undergoing significant transformation. Today, education becoming a joint venture between state, market, community. Alternative training providers that place greater emphasis on employability provide problem, university professors represent particular breed career academics remain cut off from developments in outside world. The sentiment analysis student comments presented this work using...

This research aims to develop a Machine Learning model for predicting soil moisture levels, which may be used construct smart irrigation systems. The was evaluated and trained using data from the "Smart Irrigation System Dataset" made publicly available by University of California, Irvine. A transfer-learned ResNet50 is various classification measures like accuracy, recall, precision, area under ROC curve (AUC). proposed has an AUC 0.95, meaning it correctly identifies positive negative...

Data anomalies are found using anomaly detection. Generative adversarial networks (GANs) can produce synthetic data and learn complex patterns. Temporal dependencies relevant features needed to identify timeseries anomalies. A GAN is trained detect in data. The model performs better with Traditional ML models struggle the difficulties of identification time-series due issues such as dealing high dimensionality, capturing temporal correlations, detecting infrequent events skewed class...

This study investigates the advantages and disadvantages of using a variety machine learning approaches to estimate an individual person's risk Cardiovascular Disease (CVD). Not all relevant variables specific may be considered by conventional assessment methods because they rely on predetermined factors. Algorithms trained big data sets can identify trends anticipate risks, allowing for more precise targeted measures against CVD. Different algorithms are tested their ability predict CVD...

Significant threats to property, human life, and the environment arise from fire events. For fires have as minimal of an impact possible, quick discovery effective action are essential. AI-based smoke detection security control systems use cutting-edge technology algorithms accomplish early precise event detection. AI-proposed computer vision techniques analyze sensor data in real time find visual signs smoke. Based on hue, Fire is located. detection, contours bounding boxes utilized. The...

Most machine learning models have had tremendous success in implementing prediction analysis on dePD end diseases such as brain tumors, making it an ambitious goal to apply medical research discoveries. In the case of Parkinson's disease, for example, early diagnosis and understanding might allow patients adopt preventative measures before onset clinical symptoms. cases when no effective therapies exist, mPDe provides a means thereby improving patient outcomes. A loss function, like...

Health care is playing a major role in designing any kind of prediction model and there large amount data related to different diseases available over the globe. A part machine learning lies identification make them helpfulfor people. The implementation ofthe safest medical systems if new challenging task where we can implement quantum computing as main lead process making which are most secured manage useful identify fastest method form drug also safe mechanism for thedisease not even...

Speech data can help Machine Learning (ML) systems diagnose Parkinson's disease (PD). This study predicted PD progression using the Progression Markers Initiative (PPMI) dataset and Deep Belief Networks (DBN). healthy control voice inputs formed a Convolutional Neural Network (CNN) model. DBN model was compared to others numerous performance metrics. outperformed other algorithms. It accurately early detected PD. DBN-based models may enhance diagnosis. Complex neurodegeneration affects...

One of the most challenging problems in robotics and autonomous vehicles is navigation complex dynamic environments. Deep Reinforcement Learning (DRL), which enables agents to learn complicated behaviors autonomously through trial error, has demonstrated that it potential be an effective solution this problem. By utilizing Waymo open dataset Proximal Policy Optimisation (PPO) algorithm, research paper aims investigate DRL for In first step process, we conduct a literature review focuses on...

This research used a wearable sensor to gather photoplethysmography (PPG) signals from 15 healthy subjects. The dataset includes 7,308 PPG segments, each containing 8 seconds of data and corresponding labels indicating the type physical activity subject performed. article proposes convolutional neural network (CNN) model classify signals. proposed several layers: batch normalization, convolutional, max-pooling, dropout, fully connected. output layer uses softmax activation function compute...

Numerous studies have connected air pollution to various health problems, including asthma, COPD, and reduced lung function. Particulate Matter (PM), Nitrogen Dioxide (NO2), Ozone are three of the most notable pollutants that contribute significantly worsening chronic diseases. Recent research has revealed patients with respiratory disorders can their COVID-19 symptoms made worse by increased levels in environments. U.S. scientists studying this connection will benefit from Air Quality...

Critical data and systems are now more frequently kept analyzed in the cloud as a result of computing industry's quick development. As enterprises trust valuable information to third-party service providers, this presents significant security risks. This article's goal is outline issues that raises suggest solutions safeguard private cloud-based environments for businesses. The article will give brief overview along with its numerous issues, such insider threats, privacy, breaches. study...

Sign language is an essential means of communication for people with hearing disabilities. However, there often a gap between and non-hearing individuals, which can lead to social exclusion discrimination. To bridge this gap, They proposed deep learning-based sign interpreter using TensorFlow. The system recognize different signs interpret them into text or speech output, allowing individuals communicate more effectively. evaluate the on publicly available dataset achieve accuracy 95%...

The creation of Deep Fakes, which are altered videos, audio, and photographs capable disseminating false information fake news modifying sensitive records, is the result rapid advancements in artificial intelligence machine learning. DeepFakes may also be used for interactive learning visual effects entertainment education. As a result, numerous deep models, such as Convolutional Neural Networks (CNN) Generative Adversarial (GAN), being detection. detection removal have become essential...

The degenerative condition known as Chronic Kidney Disease (CKD) impairs kidney function and causes waste products to build up in the body. Early CKD prediction identification can stop or slow disease's progression. This study uses demographic, clinical, lab data provide a machine learning-based method for prediction. suggested approach mix of feature selection classification algorithms pinpoint important risk factors very accurate predictions CKD. Effective therapies delay course illness...

In recent years, there have been significant advancements in Remotely Operated Vehicles (ROVs), particularly air and underwater applications. However, the progress land-based ROVs has slow, necessitating innovative approaches to address existing challenges. This research paper presents a comprehensive analysis of current state ROV technology, focusing on its limitations. A solution is proposed, which combines well-established technology from gaming industry, such as steering wheel controls...

The research proposes improving night-time driving safety by handling high-resolution car projector lights. Internet of Things (IoT) and Computer Vision technology are employed in this strategy. constantly monitors traffic data to adjust the light output leave room for incoming prevent accidents. proposed approach integrates computer vision, IoT, projection lighting enhance lower likelihood system will be managed You Only Look Once (YOLO) algorithm response presence other cars on road,...

Objectives: This article reviews and provides an exhaustive examination of task offloading trajectory control techniques in unmanned aerial vehicles (UAVs) integrated with Internet Things (IoT), highlighting their significance impact on the UAV ecosystem. The paper begins by introducing fundamental concepts UAVs, IoT, integration, emphasizing potential benefits challenges this union. Subsequently, it delves into extensive exploration offloading, a critical aspect that optimizes operations...