The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict su...
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The Internet of Things (IoT) was evaluated as part of this study. The IoT system in this study is the air quality monitoring system. The system consists of three layers, three end devices with air quality monitoring s...
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In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company's busin...
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Online transactions are significant in the pandemic era. Using online transactions can minimize the risk of physical contact with disease transmission between buyers and sellers. However, with so many choices of items...
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Stemming is the process of cutting affixes, both prefixes and suffixes from a term to get the root of the word that has affixes. Stemming can be done in any language, especially in Indonesia Language. Indonesian which...
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This study aims to identify the processes of UX designing a mobile application, Augmented Reality based on Gamification for Cultural Heritage Tourism, and to provide the prototype design and the testing result;this re...
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Protein structure prediction in three dimensions represents a fundamental challenge in Structural Bioinformatics. Leveraging problem-specific information such as fragment insertion, secondary structure, and contact ma...
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Stroke is becoming one of the most common diseases in modern society. Stroke caught in the early phase has a higher potential for recovery as it can be treated before the worsening of the patient’s condition. Detecti...
ISBN:
(数字)9781837242863
Stroke is becoming one of the most common diseases in modern society. Stroke caught in the early phase has a higher potential for recovery as it can be treated before the worsening of the patient’s condition. Detection through brain CT images with deep learning has a favorable impact. Residual Attention Network (RAN) architecture is proposed to perform stroke detection. RAN builds upon the regular ResNet architecture by incorporating an attention layer within each residual block to extract meaningful information. RAN combines the advantages of residual connections and attention mechanisms. RAN is able to prevent vanishing gradient problem while focusing on the most important features. RAN yields an accuracy of 96.12% surpassing the regular ResNet with an accuracy of 94.40%. RAN shows great potential, especially in fields that require high accuracy and efficient feature extraction. This paper explores the effectiveness of Residual Attention Networks and their potential applications in areas requiring robust and accurate feature extraction.
In this paper, we exploit caches on intermediate nodes for QoE enhancement of multi-view video and audio transmission over ICN/CCN by controlling the content request start timing of consumers. We assume the selected s...
Low Earth Orbit satellite constellations are highly mobile and thus have time-varying network topologies. Such time-varying networks face various challenges due to intermittently available links and devices. Consequen...
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