In multi-sensor tracking, tracking targets stably and accurately is one of the primary tasks. Aiming at the problems of outlier interference during measurement and unstable tracking filtering in complex scenarios, thi...
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This paper presents a novel method that combines cloud computing infrastructure and Reinforcement Learning (RL) algorithms to improve public safety lighting in smart cities. By dynamically adjusting lighting levels in...
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The proceedings contain 44 papers. The topics discussed include: big data technologies using SVM (Case study: surface water classification on regional water utility company in Surabaya);image mapping detection of gree...
ISBN:
(纸本)9781728134369
The proceedings contain 44 papers. The topics discussed include: big data technologies using SVM (Case study: surface water classification on regional water utility company in Surabaya);image mapping detection of green areas using speed up robust features;evaluative study of integration of clinic management information system with Pcare BPJS of health using COBIT 4.1 approach;determination of RGB in fingernail image as early detection of diabetes mellitus;development of IoT for automated water quality monitoring system;and application of best first search method to search nearest business partner location (case study: PT Coca Cola Amatil Indonesia, Bandar Lampung).
Due to the broad spectrum of content and evolving tactics of spammers, identifying spam in YouTube comments has become a challenging task. If it goes undetected it may hamper the security and integrity of the applicat...
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The imaging tasks performed by Earth Observation Satellites (EOSs) are highly dynamic in terms of task success uncertainties arising from sensor malfunctions or weather conditions and emergence due to unexpected event...
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The ease and high availability of public and personal data in the existing automated and digital environments have made our technological systems vulnerable to security threats. The conventional approach of passwords ...
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multi-modal Sentiment Analysis (MSA) aims to analyze sentiments expressed across different modalities to gain deeper insights into emotional content. Previous researches have addressed numerous challenges in multi-mod...
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In recent years, the spread of multi-agent Systems (MAS) and Reinforcement Learning (RL) as a subdomain of Machine Learning (ML) has affected many fields, such as Cyber-Physical Systems (CPS) and the Internet of Thing...
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This paper analyzes the defects of managed flooding and traditional AODV (Ad-hoc On-Demand Distance Vector, AODV) routing protocol in Bluetooth Mesh networking, and proposes an AODV routing protocol based on multi-par...
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Medication errors are one of the leading causes of patient harm in the healthcare system. Nowadays, there are many tools and solutions available to reduce the occurrence rate of medication errors that might be caused ...
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ISBN:
(纸本)9798350381771;9798350381764
Medication errors are one of the leading causes of patient harm in the healthcare system. Nowadays, there are many tools and solutions available to reduce the occurrence rate of medication errors that might be caused by Look-Alike, Sound-alike (LASA) drugs. This study focuses on the problem of drug identification by using a machine learning approach. First, a dataset is manually collected of commonly used drugs in Thailand. Then the object detection models are trained and evaluated based on the different version of pretrained YOLO models. The objective of this study is to develop and compare the performance of different versions of the trained model. The results show that YOLOv8-nano achieves the highest accuracy in drug identification, with a mAP score of 99.5%, a recall of 99.7%, and an F-1 score of 99.4%, compared to other versions.
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