Tumor segmentation in MRI images is a crucial process in medical imaging, aimed at accurately identifying and delineating tumor regions within the brain or other tissues. Hence proposed a modified U-Net++ based segmen...
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Glaucoma is one of the leading causes of visual impairment worldwide. If diagnosed too late, the disease can irreversibly cause severe damage to the optic nerve, resulting in permanent loss of central vision and blind...
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Glaucoma is one of the leading causes of visual impairment worldwide. If diagnosed too late, the disease can irreversibly cause severe damage to the optic nerve, resulting in permanent loss of central vision and blindness. Therefore, early diagnosis of the disease is critical. Recent advancements in machine learning techniques have greatly aided ophthalmologists in timely and efficient diagnosis through the use of automated systems. Training the machine learning models with the most informative features can significantly enhance their performance. However, selecting the most informative feature subset is a real challenge because there are 2n potential feature subsets for a dataset with n features, and the conventional feature selection techniques are also not very efficient. Thus, extracting relevant features from medical images and selecting the most informative is a challenging task. Additionally, a considerable field of study has evolved around the discovery and selection of highly influential features (characteristics) from a large number of features. Through the inclusion of the most informative features, this method has the potential to improve machine learning classifiers by enhancing their classification performance, reducing training and testing time, and lowering system diagnostic costs by incorporating the most informative features. This work aims in the same direction to propose a unique, novel, and highly efficient feature selection (FS) approach using the Whale Optimization Algorithm (WOA), the Grey Wolf Optimization Algorithm (GWO), and a hybridized version of these two metaheuristics. To the best of our knowledge, the use of these two algorithms and their amalgamated version for FS in human disease prediction, particularly glaucoma prediction, has been rare in the past. The objective is to create a highly influential subset of characteristics using this approach. The suggested FS strategy seeks to maximize classification accuracy while reducing the t
Water quality assessment is a complex endeavour that involves identifying pollutants in water resources. The importance of this process lies in its objective to evaluate water quality for human use. Machines and deep ...
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This paper presents a random forest-feature sensitivity and feature correlation (RF-FSFC) technique for enhanced heart disease prediction. The proposed methodology is implemented using the Cleveland heart disease data...
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Building Automation Systems(BASs)are seeing increased usage in modern society due to the plethora of benefits they provide such as automation for climate control,HVAC systems,entry systems,and lighting *** BASs in use...
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Building Automation Systems(BASs)are seeing increased usage in modern society due to the plethora of benefits they provide such as automation for climate control,HVAC systems,entry systems,and lighting *** BASs in use are outdated and suffer from numerous vulnerabilities that stem from the design of the underlying BAS *** this paper,we provide a comprehensive,up-to-date survey on BASs and attacks against seven BAS protocols including BACnet,EnOcean,KNX,LonWorks,Modbus,ZigBee,and *** studies of secure BAS protocols are also presented,covering BACnet Secure Connect,KNX Data Secure,KNX/IP Secure,ModBus/TCP Security,EnOcean High Security and Z-Wave *** and ZigBee do not have security *** point out how these security protocols improve the security of the BAS and what issues remain.A case study is provided which describes a real-world BAS and showcases its vulnerabilities as well as recommendations for improving the security of *** seek to raise awareness to those in academia and industry as well as highlight open problems within BAS security.
The abstract Data security is of most importance, in the present day- the introduction of high-level wireless communication channels has led to generation and transfer of massive amounts of data. Data security must ke...
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In an effort to increase computing efficiency, this work presents an improved spectral clustering technique that approximates the affinity matrix using Toeplitz and Circulant matrices. To preserve the quality of the c...
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Emotions are a vital semantic part of human correspondence. Emotions are significant for human correspondence as well as basic for human–computer cooperation. Viable correspondence between people is possibly achieved...
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In this research, Koopman operator theory is employed to achieve faster training time and improved performance of a reinforcement learning (RL) based linear quadratic controller (LQ). The proposed methodology, called ...
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Detecting sarcasm in social media presents challenges in natural language processing (NLP) due to the informal language, contextual complexities, and nuanced expression of sentiment. Integrating sentiment analysis (SA...
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