Cloud computing has gained significant popularity as a platform for processing large-scale data analytics, offering benefits such as high availability, robustness, and cost-effectiveness. However, job scheduling in cl...
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Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutio...
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Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.
Artificial Intelligence (AI) is increasingly being employed in critical decision-making processes such as medical diagnosis, credit approval, criminal justice, and many more. However, many AI models exploit complex al...
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This research requires to improve the accuracy of early diabetic forecasting in a human body or patient by applying diverse machine learning approaches. Approaching to creation of machine learning models by using pati...
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Breast cancer is one of the deadly diseases prevailing in *** detection and diagnosis might prevent the death *** diagnosis of breast cancer remains a significant challenge,and early diagnosis is essential to avoid th...
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Breast cancer is one of the deadly diseases prevailing in *** detection and diagnosis might prevent the death *** diagnosis of breast cancer remains a significant challenge,and early diagnosis is essential to avoid the most severe manifestations of the *** existing systems have computational complexity and classification accuracy problems over various breast cancer *** order to overcome the above-mentioned issues,this work introduces an efficient classification and segmentation ***,there is a requirement for developing a fully automatic methodology for screening the cancer *** paper develops a fully automated method for breast cancer detection and segmenta-tion utilizing Adaptive Neuro Fuzzy Inference System(ANFIS)classification *** proposed technique comprises preprocessing,feature extraction,classifications,and segmentation ***,the wavelet-based enhancement method has been employed as the preprocessing *** texture and statistical features have been extracted from the enhanced ***,the ANFIS classification algorithm is used to classify the mammogram image into normal,benign,and malignant ***,morphological processing is performed on malignant mam-mogram images to segment cancer *** analysis and comparisons are made with conventional *** experimental result proves that the pro-posed ANFIS algorithm provides better classification performance in terms of higher accuracy than the existing algorithms.
Automatic Human Action Recognition (HAR) using RGB-D (Red, Green, Blue, and Depth) videos captivated a lot of attention in the pattern classification field due to low-cost depth cameras. Feature extraction in action r...
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This research paper has focused on the integration of promising stock market indicators such as the relative strength index (RSI) and different versions of the exponential moving average (EMA) (i.e., 50-day, 100-day, ...
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Open Radio Access Networks (O-RANs) represent a novel wireless access network architecture that decomposes traditional RAN functions and makes them openly accessible. O-RANs enable real-time coordination, RAN performa...
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High reliance on autonomous systems necessitates efficient and reliable data exchange through Vehicle-to-Infrastructure (V2I) communication to have appropriate and stable network performance in dynamic vehicular envir...
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Payment channels support off-chain transactions by enhancing transaction speed and reducing fees in the main blockchain. However, the costs and complexity of the network increase as we increase the size of the network...
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