The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive s...
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The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting(STAR)-RIS-aided simultaneous wireless information and power transfer(SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting(ES),time switching(TS), and mode switching(MS). The objective of this paper is to maximize the weighted sum power(WSP) of all energy harvesting receivers(EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station(BS)and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers(IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization(AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs *** findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided sy
Twitter, as is well known, is one of the most active social media platforms, with millions of tweets posted every day, in which different people express their opinions on topics such as travel, economic concerns, poli...
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Irrigation system (IS) is considered as a crucial component in the human society. It plays a crucial role for the supply of water to the cultivation fields. So, it is very much essential to predict the water pumping r...
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Smart technology have end up an increasing number of vital in today's rapidly evolving generation panorama. Automation, records-pushed decision-making, and streamlined operations are all being revolutionized by me...
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Parkinson's disease is a common neurological condition that predominantly im-pacts people who are older than fifty, leading to speech impairments and movement diffi-culties. Timely diagnosis of PD is essential for...
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With the vast development of Internet technology 2.0, millions of people share their opinions on different social networking sites. To obtain the necessary information from the large volume of user-generated data, the...
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With the vast development of Internet technology 2.0, millions of people share their opinions on different social networking sites. To obtain the necessary information from the large volume of user-generated data, the attention on sentiment analysis among the research community is growing. The growth and prominence of sentiment analysis are synchronized with an increase in social media and networking sites. Users generally use natural language for speaking, writing, and expressing their views based on various sentiment orientations, ratings, and the features of different products, topics, and issues. This helps produce ambiguity at the end of the customer's decision based on criticism to form an opinion based on such comments. To overcome the challenges of usergenerated content such as noisy, irrelevant information and fake reviews, there is a significant demand for a practical methodology that emphasizes the need for sentiment analysis. This study presents an exhaustive survey of the existing methodologies. It highlights the challenges and performance factors of various sentiment analysis approaches, including text preprocessing, opinion spam detection, and aspect level sentiment analysis. Users use social media as a medium for their activities and are passionate about their posts on social networking platforms on various issues, topics, and events. Sentiment analysis plays a significant role in online e-commerce servicing sites in which users share their views and rating on products and services. With the help of sentiment analysis, companies identify customer dissatisfaction and enhance the quality of the products and services. This study seeks diverse methods and performance measures on various application domains in sentiment analysis. The paper presents an exhaustive review that provides an overview of the pros and cons of the existing techniques and highlights the current techniques in sentiment analysis, namely text preprocessing, opinion spam detection, and
The demand for high-quality annotated data has surged in recent years for applications driven by real-world artificial intelligence, such as autonomous driving and embodied intelligence. Consequently, the development ...
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The demand for high-quality annotated data has surged in recent years for applications driven by real-world artificial intelligence, such as autonomous driving and embodied intelligence. Consequently, the development of a tool that can assist humans in the highly automated and high-quality annotation of large-scale, multi-modal data is of significant importance and urgency for both academic research and practical applications. Most existing multi-modal data annotation tools require frame-by-frame, object-by-object annotation with keyboard and mouse, making it challenging to provide high-quality and real-time annotations for 2D images and 3D point clouds in highly open scenarios like autonomous driving. To address these challenges, we propose OpenAnnotate2, which understands human intentions based on natural language prompt, and formulates plans to decompose and execute complex multi-modal data annotation tasks. Additionally, the tool can continually enhance its cognitive and annotation capabilities with minimal human-computer interaction, through an ever-updating external knowledge base. This significantly simplifies the annotation workflow, paving the way for the creation of massive datasets suitable for large-scale visual models. The source code will be released at https://***/Fudan-ProjectTitan/OpenAnnotate. IEEE
The project aims to enhance the security of cryptocurrency transactions through the implementation of advanced machine learning methodologies that are RNN(recurrent neural networks),LSTM,VGG16. We aim to create a stro...
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In the realm of Mobile Ad-Hoc Networks (MANETs), achieving optimal Quality of Service (QoS) amidst the challenges of security threats and dynamic network topology remains a paramount concern. This paper introduces a g...
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Epilepsy, a neurological disorder characterized by recurrent seizures, poses significant challenges in timely intervention and patient safety, affecting millions of individuals worldwide. Early and accurate detection ...
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