Internet of Things (IoT) functionality integrated into smart homes has transformed residents' ways of engaging with homes, from comfort, security, and energy saving aspects. This study aims at understanding the ro...
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ISBN:
(数字)9798331542375
ISBN:
(纸本)9798331542382
Internet of Things (IoT) functionality integrated into smart homes has transformed residents' ways of engaging with homes, from comfort, security, and energy saving aspects. This study aims at understanding the role played by IoT based smart automation and control in enhancing people's living standards within homes. Smart homes are designed utilizing applications that centralize the control of other smart devices like smart manage thermostat, smart lighting, home security cameras and smart voice assistant. These systems allow people to automate jobs, conserve and manage energy, and design environments to people's specific needs. Moreover, the study investigates threat mechanisms of IoT in smart home with respect to data privacy issues as well as the weaknesses of devices and the possibility of cyber threats. One of the major considerations of this work is focused on ways through which IoT systems can be designed to learn about users and their requirements as well as make decisions on their own using machine learning techniques. Thus, the study shows that through IoT technology not only by providing convenience and energy-saving opportunities, but also giving homeowners control to create and establish safer and more comfortable home environment. In this research, recommendations are made for the need to bring improvement on the reliability, security, and accessibility of IoT in home automation market it has made.
With the rapid growth of network technology and data storage, big data applications have expanded significantly, making data mining essential for extracting valuable insights. However, protecting sensitive information...
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Metal implants in patients cause severe streaking artifacts in computed tomography (CT) images, significantly compromising image quality. Deep learning methods have been successfully applied to metal artifact reductio...
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The increasing sophistication of deepfake technology poses significant risks to privacy, security, and public trust in digital media. As a result, deepfake detection has become a critical research area, with artificia...
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ISBN:
(数字)9798331531935
ISBN:
(纸本)9798331531942
The increasing sophistication of deepfake technology poses significant risks to privacy, security, and public trust in digital media. As a result, deepfake detection has become a critical research area, with artificial intelligence -driven approaches playing a central role. This paper presents a comprehensive analysis of convolutional neural network -based deepfake detection methods, highlighting key challenges such as dataset limitations, social media compression effects, real-time detection constraints, and the rapid evolution of manipulation techniques. While existing detection models demonstrate promising accuracy, challenges remain in terms of generalizability, computational efficiency, and robustness against complex manipulations, including audio and full-body deepfakes. This study explores strategies to enhance detection performance through data augmentation and optimized architectural design. Furthermore, it discusses potential future directions, such as leveraging multimodal analysis, federated learning, and explainable AI, to improve the reliability and adaptability of deepfake detection systems.
Language model compression through knowledge distillation has emerged as a promising approach for deploying large language models in resource-constrained environments. However, existing methods often struggle to maint...
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India is one of the leading producers of various millet cultivars. Indian millets are a class of highly nutritious, drought-resistant crops that are mostly cultivated in the country's semi-arid and drought-prone r...
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ISBN:
(数字)9798331512965
ISBN:
(纸本)9798331512972
India is one of the leading producers of various millet cultivars. Indian millets are a class of highly nutritious, drought-resistant crops that are mostly cultivated in the country's semi-arid and drought-prone regions. The most popularly cultivated millet varieties in India are Sorghum (Jowar), Pearl millet (Bajra), Barnyard Millet (Bhagar), Foxtail millet (Kangi), Amaranth (Rajgira), Red sorghum (Chikani), Finger millet (Nachani), and White sorghum (Dadar). In addition to being a wholesome dietary source, millets offer several health advantages. Since they don't contain gluten, they're an excellent alternative for anyone with gluten sensitivity or coeliac disease. Additionally low in glycemic index; millets are a great meal choice for diabetics. Each cultivar has a different nutritional composition and uses. Also, the majority of the time the farmers adapted the millet seeds obtained from their crop hence to preserve the purity of seeds and quality of produce it is very important to classify different millet cultivars. However, the classification of millet cultivars is a complex and time-consuming process. Automation in millet cultivar classification becomes greatly beneficial with improved accuracy and efficiency. This study presents the effective classification of eight different millet cultivars using different machine-learning classifiers along with image processing techniques, based on the derived color features.
This paper delves into deep learning approaches for gender and age prediction from voice data. We discuss a comparison of logistic regression and long short-term memory networks to predict gender, with Kmeans clusteri...
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ISBN:
(数字)9798331527518
ISBN:
(纸本)9798331527525
This paper delves into deep learning approaches for gender and age prediction from voice data. We discuss a comparison of logistic regression and long short-term memory networks to predict gender, with Kmeans clustering along with logistic regression to predict the age of the speaker. In the obtained results, it is found that the LSTM model performs better than logistic regression in predicting the gender, we also compared it with machine learning models and Bayesian network and thus the hybrid approach successfully classifies the age groups. Some of these methods seem promising to be used in real-world applications in virtual assistants and healthcare.
The primary imaging modality, magnetic resonance imaging (MRI), has the potential to identify brain tumors accurately. This study focuses on applying deep learning to improve the accuracy of magnetic resonance imaging...
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The Dual Active Bridge (DAB) is a reliable and efficient converter capable of providing bi-directional power transfer and galvanic isolation. An ac-ac DAB can control both active and reactive power flow. The present w...
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ISBN:
(数字)9798331516116
ISBN:
(纸本)9798331516123
The Dual Active Bridge (DAB) is a reliable and efficient converter capable of providing bi-directional power transfer and galvanic isolation. An ac-ac DAB can control both active and reactive power flow. The present work introduces a combined feedback/feed-forward current control system, utilizing the calculated and measured converter currents translated into the dq reference frame, to control the output power. The system was simulated in PLECS to demonstrate the control algorithm’s ability to track the dq currents and provide the necessary output power.
The distributed denial-of-service (DDoS) attack stands out as a highly formidable cyber threat, representing an advanced form of the denial-of-service (DoS) attack. A DDoS attack involves multiple computers working to...
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