The movie recommender system is a highly influential and practical tool that assists individuals in efficiently choosing films to watch. Although recommender systems have been extensively used in academic research for...
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The smart world under Industry 4.0 is witnessing a notable spurt in sleep disorders and sleep-related issues in patients. Artificial intelligence and IoT are taking a giant leap in connecting sleep patients remotely w...
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Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive ***,the AMR of radiation source signals at low SNRs still faces a great ***,the AMR method of radiation so...
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Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive ***,the AMR of radiation source signals at low SNRs still faces a great ***,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this ***,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing ***,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR ***,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation *** analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR *** recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.
A prevalent diabetic complication is Diabetic Retinopathy(DR),which can damage the retina’s veins,leading to a severe loss of *** treated in the early stage,it can help to prevent vision *** since its diagnosis takes...
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A prevalent diabetic complication is Diabetic Retinopathy(DR),which can damage the retina’s veins,leading to a severe loss of *** treated in the early stage,it can help to prevent vision *** since its diagnosis takes time and there is a shortage of ophthalmologists,patients suffer vision loss even before ***,early detection of DR is the necessity of the *** primary purpose of the work is to apply the data fusion/feature fusion technique,which combines more than one relevant feature to predict diabetic retinopathy at an early stage with greater *** procedures for diabetic retinopathy analysis are fundamental in taking care of these *** profound learning for parallel characterization has accomplished high approval exactness’s,multi-stage order results are less noteworthy,especially during beginning phase *** Connected Convolutional Networks are suggested to detect of Diabetic Retinopathy on retinal *** presented model is trained on a Diabetic Retinopathy Dataset having 3,662 images given by *** results suggest that the training accuracy of 93.51%0.98 precision,0.98 recall and 0.98 F1-score has been achieved through the best one out of the three models in the proposed *** same model is tested on 550 images of the Kaggle 2015 dataset where the proposed model was able to detect No DR images with 96%accuracy,Mild DR images with 90%accuracy,Moderate DR images with 89%accuracy,Severe DR images with 87%accuracy and Proliferative DR images with 93%accuracy.
Nowadays, multimedia technology is progressing everyday. It is very easy to duplicate, distribute and modify digital images with online editing software. Image security and privacy are critical aspects of the multimed...
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Nowadays, multimedia technology is progressing everyday. It is very easy to duplicate, distribute and modify digital images with online editing software. Image security and privacy are critical aspects of the multimedia revolution. Therefore, digital image watermarking offers an alternative way out for image authentication. Currently, watermarking methods are crucial for safeguarding digital images. Several traditional watermarking approaches have been developed to protect images using spatial domains and transformations. Watermarking techniques that are more traditional are less resistant to repeated attacks. Deep learning-based watermarking has recently gained traction, greatly improving the safety of visual images in a variety of common applications. This study presents a robust and secure digital watermarking method for multimedia content protection and authentication. The watermark image is first transformed using the hybrid wavelet transform, and then it is encrypted using a chaos encryption algorithm. The cover image is simultaneously subjected to neighborhood-based feature extraction. Leveraging these extracted features, a novel Adaptive Gannet Optimization algorithm (AGOA) is employed to determine the optimal embedding location. Subsequently, the watermarked image is seamlessly integrated and extracted using the hybrid Generative adversarial network-based long short-term memory (GAN-LSTM) approach within the identified optimal region. Decryption and Inverse transformation are then used to get the original watermark image. Several previous methods, such as DNN, Deep-ANN, and Deep-CNN, are used to evaluate the performance of the proposed method. This technique improves multimedia content protection and authentication by guaranteeing strong and secure watermarking. The proposed method for digital image watermarking produced a peak signal-to-noise ratio of 46.412 and a mean square error of 24.512. Therefore, the proposed method performs well in digital image wa
Feature engineering is critical for improving machine learning performance (ML), especially when handling categorical data. Traditional encoding methods, such as one-hot and label encoding, often result in challenges ...
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This research study aims to create a smart child activity recognition device combines a Raspberry Pi-pico, sensors for Internet of things (IoT). The system includes several sensors for monitoring human motion, pulse, ...
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This paper surveys some of the most important recent works related to micro-expression analysis. It includes discussions on algorithms for spotting and recognizing micro-expressions, their performances, databases, and...
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Recently several authors paid attention towards Scopus Data analysis for intellectual measurement of institutes or authors. It is well known that the SCOPUS contains more than 34,346 peer reviewed Journals from differ...
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Rational design and production of materials for highly effective and environmental-friendly electrocatalytic hydrogen evolution reaction（HER） play a pivotal role in advancing renewable energy utilization. Structural...
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Rational design and production of materials for highly effective and environmental-friendly electrocatalytic hydrogen evolution reaction（HER） play a pivotal role in advancing renewable energy utilization. Structural engineering of noble metal nanomaterials can significantly boost catalytic performance through atomic rearrangement, electronic structure modification and surface reactivity modulation. Here, RuNi alloy is synthesized using a novel high temperature liquid shock method（HTLS） with instant Joule heating treatment at 1073 K under the mixed atmosphere of Argon（Ar） and CO. The synthesis process involves an aqueous solution containing metal precursors, capping agents, reductant agents and carbon black. Particularly, the as-prepared RuNi-HTS nanostructures with hexagonal close-packed（hcp） phase demonstrate impressive electrocatalytic HER activity in alkaline conditions, requiring only 28 mV of overpotentials at a current density of 10 mA cm-2. Note that the Tafel slope is 159.2 mV dec-1. Furthermore, this versatile HTLS method can be extended to synthesize other catalysts, including Ru-HTS, PtRu, and PtZn, all of which show commendable performance for HER as well. This study lays the groundwork for the strategic design and high-throughput synthesis of novel materials with finetuned structure and refined size, enabling highly efficient and environmental-friendly electrocatalysis.
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