The benefits of technology scaling have fueled interest in realizing time-domain oversampling(?∑) of Analog-to-Digital Converters(ADCs). Voltage-Controlled Oscillators(VCO) are increasingly used to design ?∑ADCs bec...
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The benefits of technology scaling have fueled interest in realizing time-domain oversampling(?∑) of Analog-to-Digital Converters(ADCs). Voltage-Controlled Oscillators(VCO) are increasingly used to design ?∑ADCs because of their simplicity, high digitization, and low-voltage tolerance, making them a promising candidate to replace the classical Operational Transconductance Amplifier(OTA) in ?∑ ADC design. This work aims to provide a summary of the fully VCO-based ?∑ ADCs that are highly digital and scaling-friendly. This work presents a review of first-order and high-order VCO-based ?∑ ADCs with several techniques and architectures to mitigate the nonidealities introduced by VCO, achieving outstanding power efficiency. The contributions and drawbacks of these techniques and architectures are also discussed.
Imbalanced data classification is one of the major problems in machine *** imbalanced dataset typically has significant differences in the number of data samples between its *** most cases,the performance of the machi...
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Imbalanced data classification is one of the major problems in machine *** imbalanced dataset typically has significant differences in the number of data samples between its *** most cases,the performance of the machine learning algorithm such as Support Vector Machine(SVM)is affected when dealing with an imbalanced *** classification accuracy is mostly skewed toward the majority class and poor results are exhibited in the prediction of minority-class *** this paper,a hybrid approach combining data pre-processing technique andSVMalgorithm based on improved Simulated Annealing(SA)was ***,the data preprocessing technique which primarily aims at solving the resampling strategy of handling imbalanced datasets was *** this technique,the data were first synthetically generated to equalize the number of samples between classes and followed by a reduction step to remove redundancy and duplicated *** is the training of a balanced dataset using *** this algorithm requires an iterative process to search for the best penalty parameter during training,an improved SA algorithm was proposed for this *** this proposed improvement,a new acceptance criterion for the solution to be accepted in the SA algorithm was introduced to enhance the accuracy of the optimization *** works based on ten publicly available imbalanced datasets have demonstrated higher accuracy in the classification tasks using the proposed approach in comparison with the conventional implementation of *** at an average of 89.65%of accuracy for the binary class classification has demonstrated the good performance of the proposed works.
With technologies that have democratized the production and reproduction of information, a significant portion of daily interacted posts in social media has been infected by rumors. Despite the extensive research on r...
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This paper presents the development of a scalable multi-hop Internet of Things (IoT) network utilizing ESP-NOW for remote zone monitoring applications. The proposed network employs ESP32 microcontrollers, where the so...
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Statistical models, enhanced by deep learning techniques, have become pivotal in various predictive tasks, including financial forecasting. This paper addresses the challenge of predicting cryptocurrency prices, utili...
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Airplanes are a social necessity for movement of humans,goods,and *** are generally safe modes of transportation;however,incidents and accidents occasionally *** prevent aviation accidents,it is necessary to develop a...
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Airplanes are a social necessity for movement of humans,goods,and *** are generally safe modes of transportation;however,incidents and accidents occasionally *** prevent aviation accidents,it is necessary to develop a machine-learning model to detect and predict commercial flights using automatic dependent surveillance–broadcast *** study combined data-quality detection,anomaly detection,and abnormality-classification-model *** research methodology involved the following stages:problem statement,data selection and labeling,prediction-model development,deployment,and *** data labeling process was based on the rules framed by the international civil aviation organization for commercial,jet-engine flights and validated by expert commercial *** results showed that the best prediction model,the quadratic-discriminant-analysis,was 93%accurate,indicating a“good fit”.Moreover,the model’s area-under-the-curve results for abnormal and normal detection were 0.97 and 0.96,respectively,thus confirming its“good fit”.
The efforts for data transparency and open government initiatives have resulted in a large amount of data being published on open data portals. These portals are organized to enhance published data accessibility by pr...
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Skin cancer is the most prevalent type of cancer worldwide, and detecting it early is crucial to a successful course of treatment. In recent years, machine learning methods have demonstrated great potential for making...
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Free-space optical (FSO) communication presents a promising solution for high-speed wireless communication, particularly in scenarios where traditional wired or radio frequency-based solutions are impractical or ineff...
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Fine-Tuning of large language models is often demanding in terms of computational resources and memory. Consequently, there is a need to explore new methods that can effectively fine-Tune these models without compromi...
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