This study aims to implement a machine learning technique in identifying the irregularities of customer behavior on the use of prepaid electricity pulses. The methods used are Linear Discriminant Analysis and Logistic...
详细信息
There is little doubt at this point that the growth and maturation of AI will be a major influence on the economy and society overall. Significant work is underway both on advancing AI and on combining human and artif...
There is little doubt at this point that the growth and maturation of AI will be a major influence on the economy and society overall. Significant work is underway both on advancing AI and on combining human and artificial intelligence to improve the functionality and user experience of AI-based methods, tools, and services. Advanced AI is successfully reshaping many transactional contexts such as image search and purchase recommendations, as well as contexts that involve repetitive activity, such as manufacturing. However, AI is progressing much more slowly in contexts that involve rich experiences aimed at advancing human intelligence and the overall human condition -- for example, in education. A potentially unintended consequence of this is increased emphasis on the lower-hanging fruit of transactional and repetitive contexts, and less emphasis on the more complex human-development contexts that are critical for a healthy society. This article proposes a design approach for tackling the integration of AI into human-development contexts while promoting the development of new forms of cyber-human intelligence.
The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway...
The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].
Certain neuronal spike trains may be viewed as stochastic, nonhomogeneous point process. Neuronal information may be encoded in the time-varying mean rate of the spike train in some cases. For this purpose the simulat...
详细信息
作者:
Ramamoorthy, C.V.Kim, K.H.Chen, W.T.Computer Science Division
Department of Electrical Engineering and Computer Sciences University of California Berkeley Calif 94720 United States Department of
Electrical Engineering Systems and Computer Science Program University of Southern California Los Angeles Calif. United States
The usefulness of software monitors in testing large ‘programs is discussed. Several types of testing strategies based on the use of monitors are surveyed. Since there is a computational overhead involved in employin...
详细信息
Image denoising,one of the essential inverse problems,targets to remove noise/artifacts from input *** general,digital image denoising algorithms,executed on computers,present latency due to several iterations impleme...
详细信息
Image denoising,one of the essential inverse problems,targets to remove noise/artifacts from input *** general,digital image denoising algorithms,executed on computers,present latency due to several iterations implemented in,e.g.,graphics processing units(GPUs).While deep learning-enabled methods can operate non-iteratively,they also introduce latency and impose a significant computational burden,leading to increased power ***,we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images–implemented at the speed of light propagation within a thin diffractive visual processor that axially spans<250×λ,whereλis the wavelength of *** all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features,causing them to miss the output image Field-of-View(FoV)while retaining the object features of *** results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of~30–40%.We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz *** to their speed,power-efficiency,and minimal computational overhead,all-optical diffractive denoisers can be transformative for various image display and projection systems,including,e.g.,holographic displays.
computer-aided diagnosis systems are increasingly used in the detection and segmentation of abnormalities in medical imaging. However, in many borderline cases, radiologists and physicians need to analyze the images t...
详细信息
Fourier transform-second harmonic generation imaging has previously been shown to be useful in quantifying collagen fiber organization in 2D. Here, we generalize this approach to 3D and calculate preferred fiber orien...
详细信息
The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analy...
详细信息
The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources.
Redox polymers are a class of high-capacity, low-cost electrode materials for electrochemical energy storage, butthe mechanisms governing their cycling stability are not well understood. Here we investigate the effect...
详细信息
Redox polymers are a class of high-capacity, low-cost electrode materials for electrochemical energy storage, butthe mechanisms governing their cycling stability are not well understood. Here we investigate the effect of anionson the longevity of a p-dopable polymer through comparing two aqueous zinc-based electrolytes. Galvanostaticcycling studies reveal the polymer has better capacity retention in the presence of triflate anions than that withsulfate anions. Based on electrode microstructural analysis and evolution profiles of the cell stacking pressure, theorigin of capacity decay is ascribed to mechanical fractures induced by volume change of the polymer activematerials during repeated cycling. The volume change of the polymer with the triflate anion is 61% less than thatwith the sulfate anion, resulting in fewer cracks in the electrodes. The difference is related to the different anionsolvation structures—the triflate anion has fewer solvated water molecules compared with the sulfate anion,leading to smaller volume expansion. This work highlights that anions with low solvation degree are preferablefor long-term cycling.
暂无评论