Tuning the initial growth conditions of the low-temperature-InP (LT-InP) nucleation layer, we grew large-area InP laterally on SOI wafers using lateral aspect ratio trapping (LART) with high crystalline quality, on wh...
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While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. Howeve...
The thyroid is a show that plays a vital role in hormone regulation in the human body. If the thyroid is impaired, it affects the body's function and results in abnormal body functions. Some diseases caused by thy...
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The purpose of this study is to classify glaucoma and non-glaucoma images from REFUGE dataset of fundus images. Due to the imbalance of dataset, we did data augmentation and preprocessing for dataset first (including ...
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With the swift advancement of automotive technology, the need for efficient allocation of resources in V2V (vehicle-to-vehicle) communications has grown significantly. However, the dynamic nature of channels in vehicu...
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This work proposes a Smart Transfer planer (STP) installed on both sides of windows. It enables signal transmission between indoor and outdoor environments through electromagnetic coupling. The panel includes an array...
This work proposes a Smart Transfer planer (STP) installed on both sides of windows. It enables signal transmission between indoor and outdoor environments through electromagnetic coupling. The panel includes an array antenna, beamforming circuit, and path control circuit. With digital control, the panel allows beam direction switching for receiving millimeter-wave signals indoors.
Forecasting stock market volatility is a challenging task, primarily due to the influence of non-financial factors such as public opinion and sentiment. Social media platforms, particularly Twitter, have the potential...
Forecasting stock market volatility is a challenging task, primarily due to the influence of non-financial factors such as public opinion and sentiment. Social media platforms, particularly Twitter, have the potential to sway public sentiment and impact stock market prices. In this paper, we present a novel approach for predicting the volatility of multiple indices in the U.S. stock market by integrating historical closing prices with sentiment analysis of Twitter data using deep neural networks. Our approach involves extracting features from tweet metadata and analyzing the overall presence of authors on the platform to estimate future changes in index closing prices. Through our experiments, we observed a strong correlation between the predicted closing prices of an index, the sentiment expressed in tweets, and the extracted features. Despite the sparsity of the dataset, our applied neural networks exhibited robust per-formance. This study contributes to the expanding research on predicting stock market volatility through the utilization of social media sentiment analysis and deep learning techniques. The proposed approach holds promise for applications in financial decision-making and risk management.
Usually, the resolution loss is serious in light field display due to the spatial multiplexing of several neighboring pixels to display images from different directions. With the limitation in the resolution of the fl...
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The Heating, Ventilation and Air Conditioning (HVAC) System is a significant energy user of a building. The main factor that affects the energy consumption of the HVAC system is indoor air temperature, which also will...
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In cognitive radio networks(CRNs),multiple secondary users may send out requests simultaneously and one secondary user may send out multiple requests at one time,i.e.,request arrivals usually show an aggregate ***,a s...
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In cognitive radio networks(CRNs),multiple secondary users may send out requests simultaneously and one secondary user may send out multiple requests at one time,i.e.,request arrivals usually show an aggregate ***,a secondary user packet waiting in the buffer may leave the system due to impatience before it is transmitted,and this impatient behavior inevitably has an impact on the system *** to investigate the influence of the aggregate behavior of requests and the likelihood of impatience on a dynamic spectrum allocation scheme in CRNs,in this paper a batch arrival queueing model with possible reneging and potential transmission interruption is *** constructing a Markov chain and presenting a transition rate matrix,the steady-state distribution of the queueing model along with a dynamic spectrum allocation scheme is derived to analyze the stochastic behavior of the ***,some important performance measures such as the loss rate,the balk rate and the average delay of secondary user packets are ***,system experiments are carried out to show the change trends of the performance measures with respect to batch arrival rates of secondary user packets for different impatience parameters,different batch sizes of secondary user packets,and different arrival rates of primary user ***,a pricing policy for secondary users is presented and the dynamic spectrum allocation scheme is socially optimized.
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