The Internet of Things (IoT) has gained attention for its rapid growth in the past few years. IoT devices such as temperature and humidity sensors and voice controllers are implemented widely, from household appliance...
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Pneumothorax is a life-threatening and urgent chest disease than can be detected using Chest X-Ray (CXR) image. CXR images are low resolution and diagnosis of pneumothorax based on them is error prone. Deep learning-b...
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Pneumothorax is a life-threatening and urgent chest disease than can be detected using Chest X-Ray (CXR) image. CXR images are low resolution and diagnosis of pneumothorax based on them is error prone. Deep learning-based computer aided diagnosis systems can improve diagnosis performance of pneumothorax. Convolutional Neural Networks (CNNs) are default networks in deep learning-based medical image process. However, CNNs fail to capture long range features. On the other side, Transformer are proposed to exploit long range feature, but they cannot capture local features. In this paper, we propose a general method with a convolution and a transformer module which can classify CXR images to diagnose pneumothorax by extracting local features, global features and global features attended by local ones using a novel architecture. Results show that the proposed method outperforms base architectures and the other previous works.
Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comp...
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In the digital era of information systems, emotion detection from audio signals is crucial for forensic services and operator or driver emotion monitoring in large-scale companies' safety and security. Speech is a...
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For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more...
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Prior study has developed the RouteSegmentation algorithm to identify the perimeter area surrounding a route. In this study, a comparative experiment was carried out to investigate the performance of the RouteSegmenta...
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ISBN:
(数字)9798350375817
ISBN:
(纸本)9798350375824
Prior study has developed the RouteSegmentation algorithm to identify the perimeter area surrounding a route. In this study, a comparative experiment was carried out to investigate the performance of the RouteSegmentation algorithm implementation in contrast to the RouteBoxer algorithm. Both algorithms play a crucial role in geographical information systems (GIS), particularly in enhancing navigational tools by identifying points of interest along specified routes. Through systematic experimentation using various perimeter distance values and types of route, the trade-offs between processing efficiency and the granularity of the area identified by these algorithms were evaluated. The results demonstrate that RouteSegmentation maintained relatively consistent performance across different perimeter distance values and statistically significantly faster processing time than RouteBoxer. Furthermore, while the RouteBoxer algorithm benefits from larger perimeter distance values by reducing processing time, it compromises the coverage results of the algorithm and potentially undermines its usefulness in practical scenarios. This study not only provides insights into the optimal use of perimeter distance values for each algorithm but also guides users in selecting the appropriate algorithm based on their specific application needs, balancing detailed geographical analysis and runtime efficiency.
In recent years, the rapid development of medical imaging technology has brought medical image analysis into the era of big data. CT imaging technology is one of the most common imaging methods for disease screening. ...
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Vehicular Ad Hoc Networks (VANETs) is an origination of Mobile Ad-Hoc Network (MANET), where road vehicles will distribute messages and provide safety alerts to notice hazardous circumstances to the drivers. One of it...
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In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer...
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In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer phenomenon is ***’s law of heat conduction has been used as the foundation for predicting the heat transfer behavior in a variety of real-world *** model’s production of a parabolic energy expression,which means that an initial disturbance would immediately affect the system under investigation,is one of its main ***,numerous researchers worked on such problem to resolve this *** last,this problem was resolved by Cattaneo by adding relaxation time for heat flux in Fourier’s law,which was defined as the time required to establish steady heat conduction once a temperature gradient is *** offered a material invariant version of Cattaneo’s model by taking into account the upper-connected derivative of the Oldroyd ***,both models are combinedly known as the Cattaneo-Christov(CC)*** this attempt,the mixed convective MHD Falkner-Skan Sutterby nanofluid flow is addressed towards a wedge surface in the presence of the variable external magnetic *** CC model is incorporated instead of Fourier’s law for the examination of heat transfer features in the energy expression.A two-phase nanofluid model is utilized for the implementation of *** nonlinear system of equations is tackled through the bvp4c technique in the MATLAB software *** influence of pertinent flow parameters is discussed and displayed through different *** and important results are summarized in the conclusion ***,in both cases of wall-through flow(i.e.,suction and injection effects),the porosity parameters increase the flow speed,and decrease the heat transport and the influence of drag forces.
This study explores methods to efficiently summarize extensive Arabic texts, addressing the growing need to condense large volumes of content across various fields. Three primary techniques are evaluated: Word Frequen...
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ISBN:
(数字)9798350367775
ISBN:
(纸本)9798350367782
This study explores methods to efficiently summarize extensive Arabic texts, addressing the growing need to condense large volumes of content across various fields. Three primary techniques are evaluated: Word Frequency Analysis, K-means Clustering based on Sentence Proximity, and the PageRank Algorithm. The research finds the PageRank Algorithm to be the most effective, delivering higher compression ratios while maintaining strong recall and precision metrics. In particular, the PageRank method achieved the highest compression ratio of 0.562 while maintaining a population standard deviation of 2.0, compared to other techniques. Evaluation metrics such as population standard deviation, F1 score, and compression ratio support these findings. The study also examines advanced approaches like fuzzy logic-based methods, transformers, and multi-document summarization, aiming to enhance Arabic text summarization.
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