ABSTRACT: Modern semiconductor circuits frequently encounter timing errors due to high clock frequencies and reduced supply voltages. Even minimal disturbances can threaten timing margins. While various correction techniques exist, most introduce delaysRead More…
ABSTRACT: Approximate computing significantly enhances digital circuit performance by reducing hardware complexity, especially in error-resilient applications like DSP, multimedia, and machine learning. To improve these applications, particularly Convolutional Neural Networks, we designedRead More…
ABSTRACT: Wearable sensor nodes continuously monitor biomedical signals and generate large volumes of data. Since data transmission consumes about 75% of a sensor node’s power, reducing power usage remains critical for longerRead More…
ABSTRACT: Dengue fever results from the bite of the Aedes aegypti mosquito, which belongs to the Flaviviridae virus family and includes four serotypes. Infected individuals typically experience a high fever of 40 °CRead More…
ABSTRACT: Every day, massive data volumes emerge from industries, social media, and communication platforms. This complex data—referred to as big data—requires advanced tools for storage, management, and analysis. While traditional approaches struggleRead More…
ABSTRACT: Soft Tissue Tumors (STT) are rare sarcomas that affect muscles, fat, nerves, and connective tissues. Due to their low frequency and heterogeneous appearance on MRI scans, doctors often misidentify them asRead More…
ABSTRACT: Prediction of Educational Data Using Deep learning models, particularly Deep Convolutional Neural Networks (DCNN), plays a vital role in analyzing student feedback and emotions to enhance the quality of education. SentimentRead More…
ABSTRACT: Speech Emotion Recognition (SER) is a key component in modern human-computer interaction systems. It enables machines to understand human emotions through speech, improving the quality of communication and user experience. ThisRead More…
ABSTRACT : Disease Identification using Machine Learning is transforming modern healthcare by enabling faster, more accurate diagnosis based on symptom analysis. This study explores a system that integrates Machine Learning (ML) andRead More…
ABSTRACT: The Improved Mathematical Model for Continuous COVID-19 prediction provides valuable insight into monitoring and managing pandemic trends. Since its emergence in December 2019, COVID-19 has disrupted global health and economies. AccurateRead More…
