Abstract: Online monitoring and counseling have helped patients and made digital health management possible. However, the vulnerability of medical data gathered via devices, especially in the Internet of Things (IoT) ...
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Digital pathology employing Whole Slide Images (WSIs) plays a pivotal role in cancer detection. Nevertheless, the manual examination of WSIs for the identification of various tissue regions presents formidable challen...
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Price comparison websites (PCWs) have become integral to the online shopping experience, enabling consumers to make informed decisions by comparing prices, features, and reviews from multiple retailers. These platform...
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We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the c...
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We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the coupling strength via a unidirectional waveguide(IWG)can induce chaotic *** underlying reason for this phenomenon is that adjusting the phase and coupling strength via the phase shifter and IWG bring the system close to an exceptional point(EP),where field localization dynamically enhances the optomechanical nonlinearity,leading to the generation of chaotic *** addition,due to the sensitivity of chaos to phase in the vicinity of the EP,we propose a theoretical scheme to measure the optical phase perturbations using *** work may offer an alternative approach to chaos generation with current experimental technology and provide theoretical guidance for optical signal processing and chaotic secure communication.
Brain tumor identification and categorization serve a precarious role in early diagnosis and treatment planning. This study suggests a new deep learning (DL)-based structure for the automatic detection and categorizat...
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The art of hiding secret text within an innocuous cover medium is steganography. Steganalysis is the counterpart of steganography which focuses on the detection and extraction of the secret text from the medium. Featu...
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ISBN:
(数字)9783031612985
ISBN:
(纸本)9783031612978
The art of hiding secret text within an innocuous cover medium is steganography. Steganalysis is the counterpart of steganography which focuses on the detection and extraction of the secret text from the medium. Feature engineering is the crucial field in Stegware Analysis which intends to identify more specific features, focusing on the accuracy and efficiency. Feature engineering is a process in Machine learning where the features of any dataset are selected and extracted for further use. Feature engineering is the process of extracting, transforming and selecting the most relevant features form the data that aids in discriminating between the stego and cover image. This is because, most of the time, the data will be in a raw format. Any ML model needs the data to be pre-processed and kept ready to train the model. Thus, from the pool of raw data, the required data needs to be selected and can be used in training the model. Further, the data at point needs to be extracted to get the precise data. The scope of the work is to identify the various feature engineering techniques available in practice and efficiently use them to achieve high accuracy and precision in the system. The survey focuses on the several feature selection and extraction techniques like filter method, wrapper method and embedded methods. Correlation being one of the feature selection methods is focused;while statistical moments computes the mean, variance and skewness of the feature. The extraction method holds the Computation of Invariants and other such. Comparative study is made on both the methods to understand the concepts with ease. The work starts by taking a sample from the dataset and few feature extraction techniques are applied on the same. Then the original image is compared with the extracted images with the view of histogram. The paper gives valuable insights into the effectiveness of different feature engineering techniques using the dataset and underscores the importance of featu
Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare *** patient data pro-cessing from remote places may lead to severe privacy ***,the existing cl...
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Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare *** patient data pro-cessing from remote places may lead to severe privacy ***,the existing cloud-based healthcare system takes more latency and energy consumption during diagnosis due to offloading of live patient data to remote cloud *** the privacy *** proposed research introduces the edge-cloud enabled privacy-preserving healthcare system by exploiting additive homomorphic encryption *** can help maintain the privacy preservation and confidentiality of patients’medical data during diagnosis of Parkinson’s *** addition,the energy and delay aware computational offloading scheme is proposed to minimize the uncertainty and energy consumption of end-user *** proposed research maintains the better privacy and robustness of live video data processing during prediction and diagnosis compared to existing health-care systems.
A heat dissipation model of a rectangular porous fin is established based on constructal theory. First, the constructal design of rectangular porous fin is conducted by selecting a complex function minimization, which...
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A heat dissipation model of a rectangular porous fin is established based on constructal theory. First, the constructal design of rectangular porous fin is conducted by selecting a complex function minimization, which composed of linear weighting sum of maximum temperature difference and pumping power consumption, as optimization objective. Effects of gap height, air inlet velocity, total porous fin volume and porosity on the optimal constructs are investigated, respectively. The findings show that the complex function can attain its double minimum at a value of 0.802 when the fin length and number are optimized, and the corresponding optimal fin length and number are 8.01 mm and 10, respectively. In comparison to original design, the complex function and maximum temperature difference after twice optimization are decreased by 19.80% and 66.31%, ***, the comprehensive performance of porous fin is improved by simultaneously optimizing the fin length and number. The artificial neural network is applied to predict the fin performances, which is used to conduct multi-objective optimization based on NSGA-II algorithm. Optimal structure of porous fin for multiple requirements is gained by LINMAP and TOPSIS decisionmaking strategies. The findings in this study can serve as theoretical guides for fin thermal designs of electronic devices.
The Smart Parking System is an innovative solution designed to tackle the challenges of parking in densely populated urban areas. By integrating advanced technologies such as RFID (Radio Frequency Identification) sens...
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Face recognition under occlusion presents a persistent challenge in computer vision, primarily due to difficulties in capturing and effectively integrating visible and obscured facial features. This paper introduces a...
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