With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can b...
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With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can be accessible *** this context,finding and writing a list of existing Web APIs that can collectively meet the functional needs of software developers has become a promising approach to economically and easily develop successful mobile ***,the number and diversity of candidate IoT Web APIs places an additional burden on application developers’Web API selection decisions,as it is often a challenging task to simultaneously ensure the diversity and compatibility of the final set of Web APIs *** this challenge and latest successful applications of game theory in IoT,a Diversified and Compatible Web APIs Recommendation approach,namely DivCAR,is put forward in this *** of all,to achieve API diversity,DivCAR employs random walk sampling technique on a pre-built“API-API”correlation graph to generate diverse“API-API”correlation ***,with the diverse“API-API”correlation subgraphs,the compatible Web APIs recommendation problem is modeled as a minimum group Steiner tree search problem.A sorted set of multiple compatible and diverse Web APIs are returned to the application developer by solving the minimum group Steiner tree search *** last,a set of experiments are designed and implemented on a real dataset crawled from *** results validate the effectiveness and efficiency of our proposed DivCAR approach in balancing the Web APIs recommendation diversity and compatibility.
The issue of brightness in strong ambient light conditions is one of the critical obstacles restricting the application of augmented reality(AR)and mixed reality(MR).Gallium nitride(GaN)-based micro-LEDs,renowned for ...
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The issue of brightness in strong ambient light conditions is one of the critical obstacles restricting the application of augmented reality(AR)and mixed reality(MR).Gallium nitride(GaN)-based micro-LEDs,renowned for their exceptional brightness and stability,are considered the foremost contenders for AR ***,conventional heteroepitaxial growth micro-LED devices confront formidable challenges,including substantial wavelength shifts and efficiency *** this paper,we firstly demonstrated the high-quality homoepitaxial GaN-on-GaN micro-LEDs microdisplay,and thoroughly analyzed the possible benefits for free-standing GaN substrate from the material-level characterization to device optoelectronic properties and microdisplay application compared with sapphire *** GaN-on-GaN structure exhibits a superior crystal quality with ultra-low threading dislocation densities(TDDs)of~105 cm^(-2),which is three orders of magnitude lower than that of *** an in-depth size-dependent optoelectronic analysis of blue/green emission GaN-on-GaN/Sapphire micro-LEDs from 100×100 shrink to 3×3μm^2),real that a lower forward voltage and series resistance,a consistent emission wavelength(1.21 nm for blue and 4.79 nm for green@500 A/cm2),coupled with a notable reduction in efficiency droop ratios(15.6%for blue and 28.5%for green@500 A/cm^(2))and expanded color gamut(103.57%over Rec.2020)within GaN-on-GaN 10μm *** but not least,the GaN-on-GaN micro-display with 3000 pixels per inch(PPI)showcased enhanced display uniformity and higher luminance in comparison to its GaN-on-Sapphire counterpart,demonstrating significant potentials for high-brightness AR/MR applications under strong ambient light.
In today's 5G era, the amount of data generated by the Internet of Things (IoT) devices is enormous. Data is processed and stored in the cloud under a traditional cloud computing architecture, and real-time proces...
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Decentralized identification is an interesting topic for Internet-based systems. Although the use of centralized systems for identification is prevalent, there is still a need for decentralized identification systems ...
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Convolutional neural networks (CNNs) and self-attention (SA) have demonstrated remarkable success in low-level vision tasks, such as image super-resolution, deraining, and dehazing. The former excels in acquiring loca...
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Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for smal...
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Quantum superposition lies at the core of quantum mechanics and has been applied to various quantum technologies. Over the past few decades, Wheeler's delayed-choice thought experiment has been extensively examine...
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The effectiveness of positioning techniques that utilize the receiver signal strength (RSS) is highly dependent on the instability of the received signal strength indicator (RSSI). Up to now, there is no strategy that...
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Wu Binghuang shallow acupuncture technique was selected as the sixth batch of intangible heritage items in Fujian Province in 2019, and Wu Binghuang shallow acupuncture technique has good effect on treating insomnia i...
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Wu Binghuang shallow acupuncture technique was selected as the sixth batch of intangible heritage items in Fujian Province in 2019, and Wu Binghuang shallow acupuncture technique has good effect on treating insomnia in clinical trials. The shallow acupuncture technique has three kinds of techniques: " drainage method", " tonic method", and " flat tonic and flat drainage", which can be used for different treatment purposes, and the three techniques have high operational similarity. In the development of the shallow needle instrument using modern electronic technology to simulate the shallow needle technique of Bing-Huang Wu, it is necessary to extract and distinguish the vibration signals of the three modes. To address the problem of difficulty in differentiating Wu’s shallow acupuncture techniques, a feature extraction method based on EMD sample entropy, energy occupation ratio after Pyramid decomposition and CV-SVM is proposed in this paper. The vibration signal is noise reduced by using wavelet noise reduction, firstly, the EMD decomposition is performed on the noise reduced data, the correlation coefficient between individual IMF and the original signal is calculated, the IMF with the correlation coefficient greater than 0.1 is selected as the effective component, the sample entropy of the effective component is calculated, then the Pyramid decomposition of the noise reduced vibration signal is divided into 9 layers, the relative energy of each layer is calculated, and the sample entropy of the effective component and the relative energy of each layer are calculated. The sample entropy of the effective component and the relative energy of each layer are formed into a Govett collection. The CV-SVM is then employed to identify the signal patterns, resulting in an average recognition rate of 76% that possesses engineering application value. The vibration data of Prof. Wu Binghuang’s treatment with shallow needles were analyzed, and the practical application of the p
Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp regions that wrap significant information and require effective methods ...
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Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp regions that wrap significant information and require effective methods for information *** defocus blur detection and segmentation methods have several limitations i.e.,discriminating sharp smooth and blurred smooth regions,low recognition rate in noisy images,and high computational cost without having any prior knowledge of images i.e.,blur degree and camera ***,there exists a dire need to develop an effective method for defocus blur detection,and segmentation robust to the above-mentioned *** paper presents a novel features descriptor local directional mean patterns(LDMP)for defocus blur detection and employ KNN matting over the detected LDMP-Trimap for the robust segmentation of sharp and blur *** argue/hypothesize that most of the image fields located in blurry regions have significantly less specific local patterns than those in the sharp regions,therefore,proposed LDMP features descriptor should reliably detect the defocus blurred *** fusion of LDMP features with KNN matting provides superior performance in terms of obtaining high-quality segmented regions in the ***,the proposed LDMP features descriptor is robust to noise and successfully detects defocus blur in high-dense noisy *** results on Shi and Zhao datasets demonstrate the effectiveness of the proposed method in terms of defocus blur *** and comparative analysis signify that our method achieves superior segmentation performance and low computational cost of 15 seconds.
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