The proceedings contain 13 papers. The special focus in this conference is on information, Communication and computingtechnology. The topics include: Analysing the Role of Post Click Factors in Generating Leads Throu...
ISBN:
(纸本)9783031724824
The proceedings contain 13 papers. The special focus in this conference is on information, Communication and computingtechnology. The topics include: Analysing the Role of Post Click Factors in Generating Leads Through Search Advertising;mCLIP: Multimodal Approach to Classify Memes;Enhancing Marine Litter Management in the Gulf of Aqaba Through AI;solving the Rush Hour Puzzle Problem by Different Heuristics;advancing Precision Agriculture: Machine Learning-Based Crop Recommendation for Optimal Yield;Low-Cost Biodegradable Composite-Shaped Split Ring Resonator (SRR) Based Sensor for Breast Cancer Assessment;XR-Menu: Food Ordering System in Extended Reality Application;Predicting Crime Hot Spots Using Machine Learning Algorithms: Cities in USA and South Africa;Experience with the Implementation of Machine Learning on ESP32-Based Edge Devices;Stock Open Price Prediction of Software Companies in the BSE SENSEX 50 Index;implementation of Morphological Fractional Order Darwinian Operator for Brain Tumour Localization.
Streaming media is important in modern information consumption industry. However the limited and varied computing resources and bandwidth of client devices pose challenges for video coding. To make a balance between s...
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The international Classification of Diseases (ICD) coding assigns standardized codes to diseases. Automating this process enhances the efficiency and accuracy of clinical records processing. However, current methods s...
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Channel coding is a technique used to boom the performance and reliability of records transmission. It is able to be used for facts compression and source coding, that are the procedures of reducing the amount of reco...
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3D object detection leverages sensors like LiDAR and cameras to capture scene information, enabling precise determination of objects' spatial positions and orientations. This technology finds extensive application...
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3D object detection leverages sensors like LiDAR and cameras to capture scene information, enabling precise determination of objects' spatial positions and orientations. This technology finds extensive applications in autonomous driving, smart homes, industrial automation, and intelligent security systems. However, high-precision 3D object detection algorithms often require substantial computational resources, posing limitations for deployment on resource-constrained devices. In this paper, we devise an efficient computation offloading and data transmission framework specifically tailored for edge computing networks to address this challenge. Our framework takes into account both the computing and communication capabilities of terminal devices and network conditions, offloading suitable computation tasks to the edge for processing. This approach mitigates the algorithm's performance requirements on terminal devices. Furthermore, we propose a data transmission scheme that incorporates attention mechanisms and hardware-accelerated coding. This scheme effectively reduces detection time and enhances overall system performance. Experimental results demonstrate that our proposed framework significantly enhances the efficiency of 3D object detection on resource-constrained devices within edge computing networks, while maintaining high detection accuracy.
This article presents a systematic literature review (SLR) aimed at exploring green computing initiatives in the information and Communication technology (ICT) sector. From an initial pool of 258 candidate studies, 35...
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With the rapid development of cloud computingtechnology, software engineering and mobile application development have ushered in new opportunities and challenges. This paper analyzes the application of cloud computin...
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Electric power computing resources are distributed in the respective regions of provincial data centers and transmission and transformation equipment, and the scheduling efficiency of computing resources is limited by...
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Trusted computingtechnology represents a significant element of cyber security systems, serving to guarantee the integrity and accessibility of data and systems. The incorporation of Trusted computing introduces a se...
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Automatically assigning multiple international Classification of Diseases (ICD) codes to a clinical note is challenging due to the unstructured and verbose nature of medical records. Currently, most methods employ dee...
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ISBN:
(纸本)9789819794393;9789819794409
Automatically assigning multiple international Classification of Diseases (ICD) codes to a clinical note is challenging due to the unstructured and verbose nature of medical records. Currently, most methods employ deep neural networks to learn the representation of clinical notes from a single perspective. These single-view-based methods overlook the exploitation and fusion of multiview features to enhance the precision of ICD coding. In this paper, we propose a new Multiview Attention Network (MANet) to extract and fuse multiview features for ICD coding. MANet includes a specially designed multiview attention scheme to extract and fuse coarse, global, and local features from clinical notes. Additionally, a novel cascaded multilayer perceptron (MLP) block and a multiscale convolution block are designed to extract global and local features, respectively. Self-attention and cross-attention are integrated to effectively fuse these multiview features, generating more informative and discriminative representations. Extensive experiments conducted on the popular MIMIC-III and MIMIC-IV-ICD9 datasets demonstrate the superiority of our proposed MANet over state-of-the-art methods. On MIMIC-III, MANet achieves a Macro-AUC of 0.953, Micro-AUC of 0.993, Macro-F1 of 0.135, Micro-F1 of 0.596, precision at top 8 (P@8) of 0.773, and precision at top 15 (P@15) of 0.617. On MIMIC-IV-ICD9, MANet achieves a Macro-AUC of 0.968, Micro-AUC of 0.996, Macro-F1 of 0.146, Micro-F1 of 0.614, P@8 of 0.698, and P@15 of 0.526.
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