Human life relies heavily on emotions, as they influence our decision-making, social connections, and daily conduct. Current research has primarily focused on predicting emotions from social media data, neglecting to ...
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We present a robust process for fabricating high-Q, dispersion-engineered Si3N4 photonic chips using amorphous silicon hardmask etching with PECVD SiO2 cladding, achieving an intrinsic quality factor up to ∼ 17.5...
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Unmanned aerial vehicles (UAVs) are used as supportive edge computing for sparsely located user equipment on a large scale. In this work, we propose and address a collaborative edge computing system involving multiple...
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Large-scale pre-training has shown remarkable performance in building open-domain dialogue ***,previous works mainly focus on showing and evaluating the conversational performance of the released dialogue model,ignori...
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Large-scale pre-training has shown remarkable performance in building open-domain dialogue ***,previous works mainly focus on showing and evaluating the conversational performance of the released dialogue model,ignoring the discussion of some key factors towards a powerful human-like chatbot,especially in Chinese *** this paper,we conduct extensive experiments to investigate these under-explored factors,including data quality control,model architecture designs,training approaches,and decoding *** propose EVA2.0,a large-scale pre-trained open-domain Chinese dialogue model with 2.8 billion parameters,and will make our models and codes publicly *** and human evaluations show that EVA2.0 significantly outperforms other open-source *** also discuss the limitations of this work by presenting some failure cases and pose some future research directions on large-scale Chinese open-domain dialogue systems.
The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet ofThings(IoT)applications,particularly in terms of ultra-reliable,secure,and energyeffic...
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The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet ofThings(IoT)applications,particularly in terms of ultra-reliable,secure,and energyefficient *** study explores the integration of Reconfigurable Intelligent Surfaces(RIS)into IoT networks to enhance communication *** traditional passive reflector-based approaches,RIS is leveraged as an active optimization tool to improve both backscatter and direct communication modes,addressing critical IoT challenges such as energy efficiency,limited communication range,and double-fading effects in backscatter *** propose a novel computational framework that combines RIS functionality with Physical Layer Security(PLS)mechanisms,optimized through the algorithm known as Deep Deterministic Policy Gradient(DDPG).This framework adaptively adapts RIS configurations and transmitter beamforming to reduce key challenges,including imperfect channel state information(CSI)and hardware limitations like quantized RIS phase *** optimizing both RIS settings and beamforming in real-time,our approach outperforms traditional methods by significantly increasing secrecy rates,improving spectral efficiency,and enhancing energy ***,this framework adapts more effectively to the dynamic nature of wireless channels compared to conventional optimization techniques,providing scalable solutions for large-scale RIS *** results demonstrate substantial improvements in communication performance setting a new benchmark for secure,efficient and scalable 6G *** work offers valuable insights for the future of IoT networks,with a focus on computational optimization,high spectral efficiency and energy-aware operations.
In recent years, reinforcement learning (RL) based quadrupedal locomotion control has emerged as an extensively researched field, driven by the potential advantages of autonomous learning and adaptation compared to tr...
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This study bridges the gap between traditional linguistic studies, particularly phonology, and modern Machine Learning (ML) developments. It explores the mutually beneficial interactions between the two domains: by ut...
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Integrated microwave photonics to study the use of photonic integrated circuits (PICs) to implement microwave photonic subsystems and systems have been heavily studied for the last few years. In this talk, the evoluti...
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This paper presents a method of backscatter communication. Backscatter communication is a technology whereby a signal reflected back to the source is utilized to transmit information. An FMCW radar operating in the 60...
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Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on ...
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Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat
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