Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the ***,the abundance of reviews and the risk of encounte...
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Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the ***,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic *** study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie *** allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language *** adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better *** distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for *** proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and *** SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both *** indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English *** study helps deepen the understanding of sentiments across various linguistic *** many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.
Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions i...
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Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd datas
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...
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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
Emerging technologies of Agriculture 4.0 such as the Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI), and 5G network services are being rapidly deployed to address smart farming implementation-...
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Efficient interfacial charge transfer and robust interfacial interactions are crucial for achieving the superior spatial separation of carriers and developing efficient heterojunction ***,BiOBr/AgBr S-scheme heterojun...
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Efficient interfacial charge transfer and robust interfacial interactions are crucial for achieving the superior spatial separation of carriers and developing efficient heterojunction ***,BiOBr/AgBr S-scheme heterojunctions are synthesized via the co-sharing of Br atoms using an ion-exchange approach,which involves the in-situ growth of AgBr nanoparticles on the surfaces of BiOBr *** is revealed that successful construction of a high-quality interface with strong interactions via Br atom bridge between BiOBr and AgBr,which provided a rapid migration channel for charge *** addition,in-situ XPS,Kelvin probe force microscopy,and electron spin resonance evaluations confirmed the establishment of an S-scheme charge-transfer pathway in this tightly contacted heterojunction,which could efficiently prevent the recombination of photogenerated carriers while retaining carriers with a high redox ***,the photocatalytic test confirmed that the BiOBr/AgBr heterojunction showed excellent photocatalytic performance and wide applicability thanks to the construction of high quality ***,this work highlights the importance of rational designing of heterogeneous interfaces at the atomic level in photocatalysis,and contributes to rationally design BiOBr-based S-scheme heterojunctions photocatalytic materials with high quality atomic cosharing interfaces.
In order to comprehend the applicability of microwave irradiation for recovering coalbed methane,it is necessary to evaluate the microwave irradiation-induced alterations in coals with varying levels of *** this work,...
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In order to comprehend the applicability of microwave irradiation for recovering coalbed methane,it is necessary to evaluate the microwave irradiation-induced alterations in coals with varying levels of *** this work,the carbon molecular sieve combined with KMnO_(4)oxidation was selected to fabricate carbon molecular sieve with diverse oxidation degrees,which can serve as model substances toward ***,the microwave irradiation dependences of pores,functional groups,and highpressure methane adsorption characteristics of model substances were *** results indicated that microwave irradiation causes rearrangement of oxygen-containing functional groups,which could block the micropores with a size of 0.40-0.60 nm in carbon molecular sieve;meanwhile,naphthalene and phenanthrene generated by macro-molecular structure pyrolysis due to microwave irradiation could block the micropores with a size of 0.70-0.90 *** alterations in micropore structure weaken the saturated methane adsorption capacity of oxidized carbon molecular sieve by 2.91%-23.28%,suggesting that microwave irradiation could promote methane ***,the increased mesopores found for oxidized carbon molecular sieve after microwave irradiation could benefit CH4 *** summary,the oxidized carbon molecular sieve can act as model substances toward coals with different ***,microwave irradiation is a promising technology to enhance coalbed methane recovery.
The Internet of Things(IoT)has taken the interconnected world by *** to their immense applicability,IoT devices are being scaled at exponential proportions ***,very little focus has been given to securing such *** the...
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The Internet of Things(IoT)has taken the interconnected world by *** to their immense applicability,IoT devices are being scaled at exponential proportions ***,very little focus has been given to securing such *** these devices are constrained in numerous aspects,it leaves network designers and administrators with no choice but to deploy them with minimal or no security at *** have seen distributed denial-ofservice attacks being raised using such devices during the infamous Mirai botnet attack in *** we propose a lightweight authentication protocol to provide proper access to such *** have considered several aspects while designing our authentication protocol,such as scalability,movement,user registration,device registration,*** define the architecture we used a three-layered model consisting of cloud,fog,and edge *** have also proposed several pre-existing cipher suites based on post-quantum cryptography for evaluation and *** also provide a fail-safe mechanism for a situation where an authenticating server might fail,and the deployed IoT devices can self-organize to keep providing services with no human *** find that our protocol works the fastest when using ring learning with *** prove the safety of our authentication protocol using the automated validation of Internet security protocols and applications *** conclusion,we propose a safe,hybrid,and fast authentication protocol for authenticating IoT devices in a fog computing environment.
Data collection using mobile sink(s) has proven to reduce energy consumption and enhance the network lifetime of wireless sensor networks. Generally speaking, a mobile sink (MS) traverses the network region, sojournin...
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To address the challenges of detecting small traffic signs, low detection accuracy, complex detection network models, and large parameter counts, this paper proposes a lightweight traffic sign detection framework call...
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CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computationa...
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CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computational model to predict the associations between circRNAs and diseases. And there is existing more and more evidence indicates that the combination of multi-biomolecular information can improve the prediction accuracy. We propose a novel computational model for CDA prediction named MBCDA, we collect the multi-biomolecular information including circRNA, disease, miRNA and lncRNA based on 6 databases, and construct three heterogeneous network among them, then the multi-heads graph attention networks are applied to these three networks to extract the features of circRNAs and diseases from different views, the obtained features are put into variational graph auto-encoder(VGAE) network to learn the latent distributions of the nodes, a fully connected neural network is adopted to further process the output of VGAE and uses sigmoid function to obtain the predicted probabilities of circRNA-disease *** a result, MBCDA achieved the values of AUC and AUPR under 5-fold cross-validation of 0.893 and 0.887. MBCDA was applied to the analysis of the top-25 predicted associations between circRNAs and diseases, these experimental results show that our proposed MBCDA is a powerful computational model for CDA prediction.
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