Aspect-based sentiment analysis (ABSA) is vital for text comprehension which benefits applications across various domains. This field involves the two main sub-tasks including aspect extraction and sentiment classific...
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We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbe...
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We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time ***,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by *** this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and *** image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image *** training and evaluation,the image dataset is annotated to produce the ground truth of all the ***,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the *** proves to be robust against the mentioned image variations compared with the traditional handcrafted *** proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.
We propose a novel bit-flipping (BF) decoder tailored for toric codes. We introduce the proximity vector as a heuristic metric for flipping bits, and we develop a new subroutine for correcting a particular class of ha...
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Driven by the imperative to reduce emissions from transportation, Electric Vehicles (EVs) are proliferating rapidly. However, the widespread adoption of EV charging facilities poses a potential threat to the stability...
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The fast and convenient demultiplex of optical vortex(OV) mode is crucial for its further application. We propose a novel approach that combines classic Young's doublet with an OV source to effectively identify th...
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The fast and convenient demultiplex of optical vortex(OV) mode is crucial for its further application. We propose a novel approach that combines classic Young's doublet with an OV source to effectively identify the OV mode through the analysis of interference patterns. The interference patterns of the OV source incident on the double slits can be perfectly illustrated by using both the classical double-slit interference method and the Huygens–Fresnel principle. The interference fringes will twist along the negative or positive direction of x axis when topological charge(TC)l>0 or l<0, and the degree of the movement varies with the TC, allowing for a quantitative display of the OV characteristics through the interference patterns. Additionally, we deduce analytically that the zeroth-order interference fringe has a linear relationship with the TC and the vertical position. These findings highlight the ability to identify the OV mode by analyzing the interference patterns produced by Young's doublet.
Recent advances in the Internet of Things (IoT), machine learning, and edge computing have led to the development of paradigms such as smart cities, smart grids, smart healthcare, and intelligent transportation system...
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The problem of achieving performance-guaranteed finite-time exact tracking for uncertain strict-feedback nonlinear systems with unknown control directions is addressed. A novel logic switching mechanism with monitorin...
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Today, malaria is a dangerous disease caused by Plasmodium parasites and transmitted by the bite of Anopheles mosquitoes. It is estimated that more than 200,000 cases of malaria will occur every day worldwide, and mor...
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Artificial intelligence is increasingly prevalent, in today's world. Machine learning techniques play a role, in the healthcare field as a whole and particularly, in the areas of obstetrics and gynecology. More sp...
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Photonic Random-Access Memories(P-RAM)are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data *** Phase-Change Materials(PCMs)have been sho...
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Photonic Random-Access Memories(P-RAM)are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data *** Phase-Change Materials(PCMs)have been showed multilevel memory capability,but demonstrations still yield relatively high optical loss and require cumbersome WRITE-ERASE approaches increasing power consumption and system package *** we demonstrate a multistate electrically programmed low-loss nonvolatile photonic memory based on a broadband transparent phase-change material(Ge2Sb2Se5,GSSe)with ultralow absorption in the amorphous state.A zero-staticpower and electrically programmed multi-bit P-RAM is demonstrated on a silicon-on-insulator platform,featuring efficient amplitude modulation up to 0.2 dB/μm and an ultralow insertion loss of total 0.12 dB for a 4-bit memory showing a 100×improved signal to loss ratio compared to other phase-change-materials based photonic *** further optimize the positioning of dual microheaters validating performance *** we demonstrate a half-a-million cyclability test showcasing the robust approach of this material and ***-loss photonic retention-of-state adds a key feature for photonic functional and programmable circuits impacting many applications including neural networks,LiDAR,and sensors for example.
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