Controlling and guiding optical spins and pseudospins over an interface is of great importance in the emerging fields of spintronics and valleytronics, holding the promise for new degrees of freedom in the quest for e...
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Controlling and guiding optical spins and pseudospins over an interface is of great importance in the emerging fields of spintronics and valleytronics, holding the promise for new degrees of freedom in the quest for efficient information transport. Here we explore the general possibilities offered by metasurfaces to route optical momentum, spin and helicity through surface waves. We show how anisotropy and bianisotropy can be engineered to impart extreme directionality to local spin excitations. While most previous works have focused on out-of-plane spins, in-plane excitations have become particularly important for valleytronic applications relying on two-dimensional materials, and they offer specific challenges addressed here with suitably engineered nonlocality in metasurfaces.
Distinguishers have been used in Supervisory Control Theory (SCT) of Discrete Event Systems, as a way to simplify modeling tasks. Approximations complement this approach with an alternative to also reduce synthesis ef...
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We explored THz emission from $\mathrm{Si}^{2} / \mathrm{SiO}_{2} / / \mathrm{Ta} / \mathrm{Fe} / \mathrm{Ru} /$ $\mathrm{Ni} / \mathrm{Al}_{2} \mathrm{O}_{3}$ spintronic emitters. We tuned magnetization alignment of ...
We explored THz emission from $\mathrm{Si}^{2} / \mathrm{SiO}_{2} / / \mathrm{Ta} / \mathrm{Fe} / \mathrm{Ru} /$ $\mathrm{Ni} / \mathrm{Al}_{2} \mathrm{O}_{3}$ spintronic emitters. We tuned magnetization alignment of Fe and Ni layers by varying the interlayer exchange coupling (IEC) strength using a range of Ru layer thickness t. Depending on IEC strength, magnetization hysteresis shows either ferromagnetic $(t=1.1 \mathrm{~nm}, 1.5 \mathrm{~nm})$, antiferromagnetic $(t=1.3 \mathrm{~nm})$ or canted $(t=1.7 \mathrm{~nm}, 1.9 \mathrm{~nm})$ relative alignment. Competition between IEC and an external magnetic field results in a dramatic difference in THz emission from the ferromagnetically (FM) and anti-ferromagnetically (AFM) coupled structures. The resulting THz emission from IEC structures is a result of an interference of THz transiens generated by the individual $\mathrm{Fe} / \mathrm{Ru}$ and $\mathrm{Ru} / \mathrm{Ni}$ emitters.
In this work, our study comprises of design and investigation on negative capacitance (NC), metal-oxide-semiconductor (MOS) field effects transistors (MOSFETs) with spacer and source/drain (S/D) overlap engineering. T...
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ISBN:
(数字)9781728142326
ISBN:
(纸本)9781728142333
In this work, our study comprises of design and investigation on negative capacitance (NC), metal-oxide-semiconductor (MOS) field effects transistors (MOSFETs) with spacer and source/drain (S/D) overlap engineering. The scope of the work is to boost the performance and high-energy efficiency of the studied NC-MOSFETs by using the ferro electric material (FE). The NC-MOSFETs with the spacer technology can achieve the admirable I on /I off ratio and subthreshold swing (SS), compared with planar MOSFETs. It makes device scaling possible by eliminating the short channel effect (SCE). We further estimated the effect of FE thickness and spacer, which are another critical parameter of obtaining better electrical characteristics and reducing SS.
Convolutional neural networks (ConvNet or CNN) are deep learning algorithms that can process input images, assign meaning to various aspects or objects in the image (biases and learnable weight) and recognize one imag...
Convolutional neural networks (ConvNet or CNN) are deep learning algorithms that can process input images, assign meaning to various aspects or objects in the image (biases and learnable weight) and recognize one image from another. The bigger kernel size will take more time to process the *** present a novelty way to use a 4D rank tensor to improve a convolutional process. At the early stage of the Convolve4D development, the edge detection with 3×3 kernel and The Laplacian of Gaussian (LoG) with 5×5 kernel size was used to demonstrate the convolutional process improvement. The Convolve4D needs more elaboration to be used into a CNN algorithm. The advantage of convolve4D is only need 9 loops to calculate 81 outputs, whereas convolve2D need 9 × 9 × 3 × 1 × 7 × 7 = 11.907 loops. The result is 18.5% shorter when using a 5×5 kernel; it reduces from 0.54 seconds to 0.44 seconds for the edge detection convolution process.
Expression of concern for 'Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy' by Michael A. Casasanta , , 2021, , 7285-7293, https://***/10.1039/D1NR00388G.
Expression of concern for 'Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy' by Michael A. Casasanta , , 2021, , 7285-7293, https://***/10.1039/D1NR00388G.
Nowadays mixing one language with another language either in spoken or written communication has become a common practice for bilingual speakers in daily conversation as well as in social media. Lexicon based approach...
Nowadays mixing one language with another language either in spoken or written communication has become a common practice for bilingual speakers in daily conversation as well as in social media. Lexicon based approach is one of the approaches in extracting the sentiment analysis. This study is aimed to compare two lexicon models which are SentiNetWord and VADER in extracting the polarity of the code-mixed sentences in Indonesian language and Javanese language. 3,963 tweets were gathered from two accounts that provide code-mixed tweets. Pre-processing such as removing duplicates, translating to English, filter special characters, transform lower case and filter stop words were conducted on the tweets. Positive and negative word score from lexicon model was then calculated using simple mathematic formula in order to classify the polarity. By comparing with the manual labelling, the result showed that SentiNetWord perform better than VADER in negative sentiments. However, both of the lexicon model did not perform well in neutral and positive sentiments. On overall performance, VADER showed better performance than SentiNetWord. This study showed that the reason for the misclassified was that most of Indonesian language and Javanese language consist of words that were considered as positive in both Lexicon model.
Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the...
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This paper presents a two-phase hybrid prognostics approach; in the first phase, the model’s parameters are estimated using available training data in the least squares sense using the Levenberg-Marquardt algorithm. ...
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This paper presents a two-phase hybrid prognostics approach; in the first phase, the model’s parameters are estimated using available training data in the least squares sense using the Levenberg-Marquardt algorithm. The second phase consists of using a particle filter to update the knowledge acquired so far and to predict future states of the system using in the Bayesian sense. The approach is used for an accelerated ball bearing data set, the PRONOSTIA platform, where a general fractional polynomial model is proposed as degradation model. The results of the Remaining Useful Life estimation are compared with another work in the literature, indicating its suitability and competitiveness for prognostics in this data set.
Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for ide...
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