Machine Learning
We have obtained data from May 2022 to October 2023 for our suggested framework modelling. This set of data incorporates seasonality-related speech, which we convert into text, Facebook, and Twitter posts. On the whole, 4646 data elements have been acquired, comprising 3716 representing affected individuals and the remainder of 930 representing unaffected individuals, which generated a proportional 4:1 ratio.
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Distribution and power transformers are essential components of any electricity network, hence electrical and mechanical safety of the transformer unit is among the highest concerns of electricity providers. Over the course of their operation, transformers face with a wide range of internal and external disturbances which may lead to a partial or full malfunction of the equipment. The service life and condition requirements for distribution and power transformers are now changed and utilities altered their maintenance policy from time-based to condition-based approach.
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The enhanced dataset is a sophisticated collection of simulated data points, meticulously designed to emulate real-world data as collected from wearable Internet of Things (IoT) devices. This dataset is tailored for applications in safety monitoring, particularly for women, and is ideal for developing machine learning models for distress or danger detection.
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Acute myocardial infarction (AMI) is the main cause of death in developed and developing countries. AMI is a serious medical problem that necessitates hospitalization and sometimes results in death. Patients hospitalized in the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Many studies have been conducted on the prognosis of AMI with hemogram parameters. However, no study has investigated potential hemogram parameters for the diagnosis of AMI using an interpretable artificial intelligence-based clinical approach.
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5G Network slicing is one of the key enabling technologies that offer dedicated logical resources to different applications on the same physical network. However, a Denial-of-Service (DoS) or Distributed Denial-of-Service (DDoS) attack can severely damage the performance and functionality of network slices. Furthermore, recent DoS/DDoS attack detection techniques are based on the available data sets which are collected from simulated 5G networks rather than from 5G network slices.
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Gowers' Sign is a visual symptom exhibited by many neuromuscular dystrophies, including Becker muscular dystrophy, congenital muscular dystrophy, congenital myopathy, and Duchenne muscular dystrophy, which is the most aggressive, with a life expectancy of 20 to 30 years. Additionally, there is a 2.5-year gap between the onset of initial symptoms and a confirmed diagnosis. Early detection allows for the treatment of the disease, leading to a better quality of life. To the best of our knowledge, a non-invasive computer vision system for detecting Gowers' Sign has not yet been proposed.
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Recognizing and categorizing banknotes is a crucial task, especially for individuals with visual impairments. It plays a vital role in assisting them with everyday financial transactions, such as making purchases or accessing their workplaces or educational institutions. The primary objectives for creating this dataset were as follows:
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Physically unclonable functions (PUFs) are foundational components that offer a cost-efficient and promising solution for diverse security applications, including countering integrated circuit (IC) counterfeiting, generating secret keys, and enabling lightweight authentication. PUFs exploit semiconductor variations in ICs to derive inherent responses from imposed challenges, creating unique challenge-response pairs (CRPs) for individual devices. Analyzing PUF security is pivotal for identifying device vulnerabilities and ensuring response credibility.
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The risks to children of online predators in real time gaming environments have been an area of growing concern. Research towards the development of near real time capabilities has been the focus of most queries published in this area of study. In this paper, we present Protectbot, a comprehensive safety framework used to interact with users in online gaming chat rooms. Protectbot employs a variant of the GPT-2 model known as DialoGPT, a generative pre-trained transformer designed specifically for conversation.
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The Internet of Things (IoT) is the nova emergence of connecting devices, people, and objects over the internet as sensors and actuators for a targeted application. Among popular IoT applications, location based IoT services are curtailed. Where the geographical location of a moving object will be estimated based on signal strength values using algorithms. To estimate the locations using algorithms distance measurement such as Received Signal Strength Indicator (RSSI) is required.
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