Machine Learning (ML) models, particularly Deep Learning (DL), have made rapid progress and achieved significant milestones across various applications, including numerous safety-critical contexts. However, these mode...
详细信息
This systematic review gave special attention to diabetes and the advancements in food and nutrition needed to prevent or manage diabetes in all its forms. There are two main forms of diabetes mellitus: Type 1 (T1D) a...
详细信息
The task of identifying key skills from job vacancies descriptions is considered in the article. The source data consists of vacancy texts from the 'Jobs in Russia' portal, in which skill-related entities were...
详细信息
In social networks groups play a crucial role and making decisions based on majority consensus. Which influencer nodes should we select if our goal is to broadcast a subject in a target group and increase the number o...
详细信息
Autism Spectrum Disorder (ASD) refers to a neuro-disorder wherean individual has long-lasting effects on communication and interaction *** informationtechnologywhich employs artificial intelligence(AI) model has assi...
详细信息
Autism Spectrum Disorder (ASD) refers to a neuro-disorder wherean individual has long-lasting effects on communication and interaction *** informationtechnologywhich employs artificial intelligence(AI) model has assisted in early identify ASD by using pattern *** advances of AI models assist in the automated identification andclassification of ASD, which helps to reduce the severity of the *** study introduces an automated ASD classification using owl searchalgorithm with machine learning (ASDC-OSAML) model. The proposedASDC-OSAML model majorly focuses on the identification and classificationof ASD. To attain this, the presentedASDC-OSAML model follows minmaxnormalization approach as a pre-processing stage. Next, the owl searchalgorithm (OSA)-based feature selection (OSA-FS) model is used to derivefeature subsets. Then, beetle swarm antenna search (BSAS) algorithm withIterative Dichotomiser 3 (ID3) classification method was implied for ASDdetection and classification. The design of BSAS algorithm helps to determinethe parameter values of the ID3 classifier. The performance analysis of theASDC-OSAML model is performed using benchmark dataset. An extensivecomparison study highlighted the supremacy of the ASDC-OSAML modelover recent state of art approaches.
Employing machine learning techniques in predicting the parameters of metamaterial antennas has a significant impact on the reduction of the time needed to design an antenna with optimal parameters using simulation **...
详细信息
Employing machine learning techniques in predicting the parameters of metamaterial antennas has a significant impact on the reduction of the time needed to design an antenna with optimal parameters using simulation *** this paper,we propose a new approach for predicting the bandwidth of metamaterial antenna using a novel ensemble *** proposed ensemble model is composed of two levels of regression *** first level consists of three strong models namely,random forest,support vector regression,and light gradient boosting *** the second level is based on the ElasticNet regression model,which receives the prediction results from the models in the first level for refinement and producing the final optimal *** achieve the best performance of these regression models,the advanced squirrel search optimization algorithm(ASSOA)is utilized to search for the optimal set of hyper-parameters of each *** results show that the proposed two-level ensemble model could achieve a robust prediction of the bandwidth of metamaterial antenna when compared with the recently published ensemble models based on the same publicly available benchmark *** findings indicate that the proposed approach results in root mean square error(RMSE)of(0.013),mean absolute error(MAE)of(0.004),and mean bias error(MBE)of(0.0017).These results are superior to the other competing ensemble models and can predict the antenna bandwidth more accurately.
Smart agriculture systems leverage the possibilities offered by cutting-edge technologies such as IoT, AI, and remote sensing to revolutionize conventional farming by enhancing resource utilization, production, and cr...
详细信息
ISBN:
(纸本)9798331509675
Smart agriculture systems leverage the possibilities offered by cutting-edge technologies such as IoT, AI, and remote sensing to revolutionize conventional farming by enhancing resource utilization, production, and crop damage mitigation. Real-time monitoring of soil and crop health, predictive analytics, pest control, and precision irrigation measures are all enabled by these systems. They are able to address major Indian agriculture issues, consequently boosting yield and profitability and promoting environmental sustainability. The largescale deployment of intelligent agriculture systems will change the agriculture landscape in India and will assure long-term food security for an ever-growing population. Challenges include adequate research and future studies in order to better install and achieve smart agricultural systems to protect crops. Intelligent agriculture involves all advanced research, including science and innovations, in national development through space technologies to enhance soil quality, conserve water, and facilitate agriculture information. Space ventures will undergo improved modernization through the introduction of crop sprayers, precision gene editors, epigenetics, big data analytics, IoT, wind and photovoltaic smart energy, AI-enabled robotic applications, and wide-scale desalination technologies. Implementing digital farming systems in developing economies will help their sectors as 85 percent of the global population is set to live in developing countries by 2030. Automation will prove to be necessary since food scarcity is on the rise along with resource wastage. Control strategies such as the IoT, aerial imagery, machine learning, and artificial intelligence will boost production and prevent soil degradation. These advanced technologies are also able to alleviate such issues as plant disease detection, pesticide management, and water application. The introduction of the Internet of Things in the agricultural research world has started
Alzheimer's disease(AD)is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function,but the etiology of AD is still *** the explosive growth of electronic health data,the...
详细信息
Alzheimer's disease(AD)is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function,but the etiology of AD is still *** the explosive growth of electronic health data,the application of artificial inteligence(Al)in the healthcare setting provides excellent potential for exploring etiology and personalized treatment approaches,and improving the disease's diagnostic and prognostic *** paper first briefly introduces Al technologies and applications in medicine,and then presents a comprehensive review of Al in *** simple,it includes etiology discovery based on genetic data,computer-aided diagnosis(CAD),computer-aided prognosis(CAP)of AD using multi-modality data(genetic,neuroimaging and linguistic data),and pharmacological or non-pharmacological approaches for treating ***,some popular publicly available AD datasets are introduced,which are important for advancing Al technologies in AD ***,core research challenges and future research directions are discussed.
In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse *** the convenience and efficiency offered by IoT technology...
详细信息
In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse *** the convenience and efficiency offered by IoT technology,the growing number of IoT devices escalates the likelihood of attacks,emphasizing the need for robust security tools to automatically detect and explain *** paper introduces a deep learning methodology for detecting and classifying distributed denial of service(DDoS)attacks,addressing a significant security concern within IoT *** effective procedure of deep transfer learning is applied to utilize deep learning backbones,which is then evaluated on two benchmarking datasets of DDoS attacks in terms of accuracy and time *** leveraging several deep architectures,the study conducts thorough binary and multiclass experiments,each varying in the complexity of classifying attack types and demonstrating real-world ***,this study employs an explainable artificial intelligence(XAI)AI technique to elucidate the contribution of extracted features in the process of attack *** experimental results demonstrate the effectiveness of the proposed method,achieving a recall of 99.39%by the XAI bidirectional long short-term memory(XAI-BiLSTM)model.
Bat Algorithm (BA) is a nature-inspired metaheuristic search algorithm designed to efficiently explore complex problem spaces and find near-optimal solutions. The algorithm is inspired by the echolocation behavior of ...
详细信息
暂无评论