Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic *** have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volu...
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Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic *** have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs *** clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature *** goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)*** final review included 133 *** research themes include question quality,answer quality,and expert *** terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack *** scope of most articles was confined to just one platform with few cross-platform *** with ML outnumber those with ***,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.
In recent years, the number of devices connected to the Internet (and hence the data traffic) has significantly increased. The adoption of the Internet of Things paradigm, the use of the MicroServices Architecture for...
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With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,...
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With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,manual screening has several limitations,including the propensity for errors,and raises concerns about passenger *** address these drawbacks,researchers have leveraged recent advances in deep learning to design threatsegmentation ***,these models require extensive training data and labour-intensive dense pixelwise annotations and are finetuned separately for each dataset to account for inter-dataset ***,this study proposes a semi-supervised contour-driven broad learning system(BLS)for X-ray baggage security threat instance segmentation referred to as *** research methodology involved enhancing representation learning and achieving faster training capability to tackle severe occlusion and class imbalance using a single training routine with limited baggage *** proposed framework was trained with minimal supervision using resource-efficient image-level labels to localize illegal items in multi-vendor baggage *** specifically,the framework generated candidate region segments from the input X-ray scans based on local intensity transition cues,effectively identifying concealed prohibited items without entire baggage *** multi-convolutional BLS exploits the rich complementary features extracted from these region segments to predict object categories,including threat and benign *** contours corresponding to the region segments predicted as threats were then utilized to yield the segmentation *** proposed C-BLX system was thoroughly evaluated on three highly imbalanced public datasets and surpassed other competitive approaches in baggage-threat segmentation,yielding 90.04%,78.92%,and 59.44%in terms of mIoU on GDXray,SIXray,and Compass-XP,***,the lim
Wearable computers can be used in different domains including healthcare. However, due to suffering from challenges such as faults their applications may be limited in real practice. So, in designing wearable devices,...
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Kazakhstan's deputy member is vast, and is one of sparse population, scattering and creating an overwhelming challenge to map and assess the water resources. Most of the waters are in remote and poorly equipped ar...
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This article introduces an open-source software stack designed for autonomous 1:10 scale model *** developed for the Bosch Future Mobility Challenge(BFMC)student competition,this versatile software stack is applicable...
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This article introduces an open-source software stack designed for autonomous 1:10 scale model *** developed for the Bosch Future Mobility Challenge(BFMC)student competition,this versatile software stack is applicable to a variety of autonomous driving *** stack comprises perception,planning,and control modules,each essential for precise and reliable scene understanding in complex environments such as a miniature smart city in the context of *** the limited computing power of model vehicles and the necessity for low-latency real-time applications,the stack is implemented in C++,employs YOLO Version 5 s for environmental perception,and leverages the state-of-the-art Robot Operating System(ROS)for inter-process *** believe that this article and the accompanying open-source software will be a valuable resource for future teams participating in autonomous driving student *** work can serve as a foundational tool for novice teams and a reference for more experienced *** code and data are publicly available on GitHub.
We consider a Network Operator (NO) that owns Edge Computing (EC) resources, virtualizes them and lets third party Service Providers (SPs) run their services, using the allocated slice of resources. We focus on one sp...
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Migrating from Monolithic architecture to Microservices architecture is a major change in how applications are designed, developed, and managed. This paper introduces an innovative approach for Microservices identific...
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For medical analysis and interpretation, MR brain image categorization that is automated and accurate is essential. The most significant part of the human body that MRI, or magnetic resonance imaging, allows us to see...
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Predicting water quality is essential to preserving human health and environmental sustainability. Traditional water quality assessment methods often face scalability and real-time monitoring limitations. With accurac...
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