Today, forecasting the stock market has been one of the most challenging issues for the ‘‘artificial intelligence’’ AI research community. Stock market investment methods are sophisticated and rely on analyzing massive volumes of data. In recent years, machine-learning techniques have come under increasing scrutiny to assess and improve market pred...
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Deep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art methods used to analyse and detect complex patterns in large datasets, such as credit card transactions.
However, most credit card fraud models in the literatu...
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Vehicular edge computing (VEC) has emerged as a solution that places computing resources at the edge of the network to address resource management, service continuity, and scalability issues in dynamic vehicular environments. However, VEC faces challenges such as task offloading, varying communication conditions, and data security.
To tackle thes...
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Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel formation conditions. DR can damage the retinal blood vessels and cause vision loss or even blindness.
If DR is detected early, ophthalmologists can use lasers to create tiny burns around the retinal tears to inhibit bleeding and prevent the formation of new blood vess...
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Breast cancer is one of the leading causes of death in women. Early detection through breast ultrasound images is important and can be improved using machine learning models, which are more accurate and faster than manual methods.
Previous research has shown that the use of the logistic regression, svm and random forest algorithms in breast can...
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Background: As per the census 2011, Disability is more common in elderly people. One of the major reasons for disability among the elderly people is falls. Every year, one-third of community-dwelling older adults (adults aged 65 and older) experience a fall.
Falls, defined as “unexpected event[s] in which the participant comes to rest on the grou...
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Background: Milk is perishable product, it requires immediate processing after few hours (2-4Hrs) of production, otherwise, bacterial load increases and milk gets deteriorate. At present Methytene Blue Dye Reduction Test, commonly known as MBRT test is used as a quick method to assess the microbiological quality of raw and pasteurized milk.
This ...
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Background: Yoga has gained global recognition for its numerous health benefits, including physical fitness, mental well-being, and stress reduction. As part of India's ancient heritage, yoga is a key component of the AYUSH (Ayurveda, Yoga & Naturopathy, Unani, Siddha, and Homoeopathy) systems of medicine, promoting holistic health practices.
In ...
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Background: As per the census 2011, Disability is more common in elderly people. One of the major reasons for disability among the elderly people is falls. Every year, one-third of community-dwelling older adults (adults aged 65 and older) experience a fall.
Falls, defined as “unexpected event[s] in which the participant comes to rest on the grou...
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Health is very important for human life. In particular, the health of the brain, which is the executive of the vital resource, is very important. Diagnosis for human health is provided by magnetic resonance imaging (MRI) devices, which help health decision makers in critical organs such as brain health.
Images from these devices are a source of...
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Building a quantum analog of classical deep neural networks represents a fundamental challenge in quantum computing.
A key issue is how to address the inherent non-linearity of classical deep learning, a problem in the quantum domain due to the fact that the composition of an arbitrary number of quantum gates, consisting of a series of sequenti...
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The deployment of automated deep-learning classifiers in clinical practice has the potential to streamline the diagnosis process and improve the diagnosis accuracy, but the acceptance of those classifiers relies on both their accuracy and interpretability.
In general, accurate deep-learning classifiers provide little model interpretability, whi...
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predicting stock market is one of the challenging tasks in the field of computation. Physical vs. physiological elements, rational vs. illogical conduct, investor emotions, market rumors, and other factors all play a role in the prediction.
All of these factors combine to make stock values very fluctuating and difficult to forecast accurately. ...
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Decades of research have shown machine learning superiority in discovering highly nonlinear patterns embedded in electroencephalography (EEG) records compared with conventional statistical techniques.
However, even the most advanced machine learning techniques require relatively large, labeled EEG repositories.
EEG data collection and lab...
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This is a panel paper which discusses the use of Artificial Intelligence (AI) techniques to address production level problems in semiconductor manufacturing.
We have gathered a group of expert semiconductor researchers and practitioners from around the world who have applied AI techniques to semiconductor problems and the paper provides their a...
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Cerebrovascular diseases such as stroke are among the most common causes of death and disability worldwide and are preventable and treatable.
Early detection of strokes and their rapid intervention play an important role in reducing the burden of disease and improving clinical outcomes.
In recent years, machine learning methods have attracte...
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To meet the requirements of high accuracy and low cost of target classification in modern warfare, and lay the foundation for target threat assessment, the article proposes a human-machine agent for target classification based on active reinforcement learning (TCARL_H-M), inferring when to introduce human experience guidance for model and how to au...
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In the ever-changing landscape of digital services and government initiatives, our project embarks on a mission to empower citizens with a revolutionary chatbot known as SchemeSetu.
This intelligent chatbot serves as a central information hub, consolidating crucial details on governmentsponsored loans and insurance schemes from various sources....
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In the ever-changing landscape of digital services and government initiatives, our project embarks on a mission to empower citizens with a revolutionary chatbot known as SchemeSetu.
This intelligent chatbot serves as a central information hub, consolidating crucial details on governmentsponsored loans and insurance schemes from various sources....
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Rust is a severe disease affecting many productive coffee regions. It is caused by pathogenic fungi that attack the underside of coffee leaves and it is characterized by the presence of yellow-orange and powdery points. If not treated, rust can cause a drop in coffee production of up to 45%. In this sense, this paper presents a contribution to th...
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The agriculture sector faces many challenges such as crop diseases, pest infestation, water shortage, weeds and many more. These problems lead to substantial crop loss, economic loss and also causes severe environmental hazards due to the current agriculture practices. The AI and Robotics technologies have the potential to solve these problems effi...
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Computationally expensive applications, including machine learning, chemical simulations, and financial modeling, are promising candidates for noisy intermediate scale quantum (NISQ) computers. In these problems, one important challenge is mapping a quantum circuit onto NISQ hardware while satisfying physical constraints of an underlying quantum ar...
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An optimized three-dimensional one-step leapfrog finite-difference time-domain (FDTD) method has been investigated, which is with a weakly conditional stability (WCS) to reduce numerical dispersion further. By introducing the artificial anisotropy parameters in a cross-correspondence manner, the phase velocity error is effectively limited without a...
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In current Data Science applications, the course of action has derived to adapt the system behavior for the human cognition, resulting in the emerging area of explainable artificial intelligence. Among different classification paradigms, those based on fuzzy rules are suitable solutions to stress the interpretability of the global systems. However,...
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The failure of complex artificial intelligence (AI) systems seems ubiquitous. To provide a model to describe these shortcomings, we define complexity in terms of a system's sensors and the number of environments or situations in which it performs. The complexity is not looked at in terms of the difficulty of design, but in the final performance of ...
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With the aim of reducing the reactive power for the dual-active-bridge (DAB) converter, this letter proposes an artificial intelligence (AI) aided minimum reactive power control scheme based on the harmonic analysis method. Specifically, as an advanced algorithm of the deep reinforcement learning (DRL), the deep deterministic policy gradient (DDPG)...
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Virtual synchronous generator (VSG) is a promising solution for inertia support of the future electricity grid to deal with the frequency stability issues caused by the high penetration of renewable generations. However, the power variation in power electronic interface converters caused by VSG emulation increases the stress on power semiconductor ...
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Recently, there have been many studies attempting to take advantage of advancements in Artificial Intelligence (AI) in Analog and Mixed-Signal (AMS) circuit design. Automated circuit sizing optimization and improving the accuracy of performance models are the two predominant uses of AI in AMS circuit design. This paper first introduces and explains...
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The AI chips increasingly focus on implementing neural computing at low power and cost. The intelligent sensing, automation, and edge computing applications have been the market drivers for AI chips. Increasingly, the generalisation, performance, robustness, and scalability of the AI chip solutions are compared with human-like intelligence abilitie...
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In this paper, a video service enhancement strategy is investigated under an edge-cloud collaboration framework, where video caching and delivery decisions are made in the cloud and edge respectively. We aim to guarantee the user fairness in terms of video coding rate under statistical delay constraint and edge caching capacity constraint. A hy...
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The human brain is the gold standard of adaptive learning. It not only can learn and benefit from experience, but also can adapt to new situations. In contrast, deep neural networks only learn one sophisticated but fixed mapping from inputs to outputs. This limits their applicability to more dynamic situations, where the input to output mapping...
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Passenger traffic fore casting and decision-making of investment and construction of the tourism highway under the background of artificial intelligence is studied in this paper. As an important information asset, big data is expected to provide people with comprehensive, accurate, and real-time business insights a...
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