nils-herrmann/clean_scirepeval huggingface dataset:
Frequency dependence of performance in Ge negative capacitance PFETs achieving sub-30 mV/decade swing and 110 mV hysteresis at MHz

We report the first investigation of frequency dependence of performance in Ge HfZrOx (HZO) negative capacitance (NC) pFETs. For Ge NC pFETs with internal gate ], pulse measurement produces the significant increase in hysteresis compared to the DC measurement, but devices still remains sub-60 mV/decade subthreshold swing (SS). Ge NC pFETs without internal gate ] show the little dependence of hysteresis, SS, and capacitance characteristics on pulse measurement (from DC to 1 μs). Ge NC pFET without internal gate achieves sub-30 mV/decade SS and 110 mV hysteresis with 1 ¡is pulse measurement, and significant peak in gate capacitance due to the NC effect at MHz. The different frequency dependences of performance in NC devices with and without internal gate might be attributed to the difference in the magnitude of gate leakage currents.
High-Speed Multispectral Iris Capture System Design

Multispectral iris recognition is one of the most reliable biometrics in terms of recognition performance. This paper describes the design and implementation of a high-speed multispectral iris capture device, which consists of four parts, i.e., capture, illumination, interaction, and control units. A multispectral iris image database is created by the proposed capture device, and then, we use the iris image-level fusion to further investigate the effectiveness of the proposed capture device by the 1-D log-Gabor wavelet filter approach. Experimental results are also presented in this paper.
Monogenic Binary Coding: An Efficient Local Feature Extraction Approach to Face Recognition

Local-feature-based face recognition (FR) methods, such as Gabor features encoded by local binary pattern, could achieve state-of-the-art FR results in large-scale face databases such as FERET and FRGC. However, the time and space complexity of Gabor transformation are too high for many practical FR applications. In this paper, we propose a new and efficient local feature extraction scheme, namely monogenic binary coding (MBC), for face representation and recognition. Monogenic signal representation decomposes an original signal into three complementary components: amplitude, orientation, and phase. We encode the monogenic variation in each local region and monogenic feature in each pixel, and then calculate the statistical features (e.g., histogram) of the extracted local features. The local statistical features extracted from the complementary monogenic components (i.e., amplitude, orientation, and phase) are then fused for effective FR. It is shown that the proposed MBC scheme has significantly lower time and space complexity than the Gabor-transformation-based local feature methods. The extensive FR experiments on four large-scale databases demonstrated the effectiveness of MBC, whose performance is competitive with and even better than state-of-the-art local-feature-based FR methods.
Handheld System Design for Dual-Eye Multispectral Iris Capture With One Camera

This paper describes the design and implementation of a dual-eye multispectral iris capture handheld device with one camera, which consists of the following four parts: 1) capture unit; 2) illumination unit; 3) interaction unit; and 4) control unit. A multispectral iris image database is created by the proposed capture device, and then, we use the multispectral score-level fusion to further investigate the effectiveness of the proposed capture device by the 1-D Log-Gabor wavelet filter approach. Experimental results are also presented in this paper.
Data Infrastructure at LinkedIn

Linked In is among the largest social networking sites in the world. As the company has grown, our core data sets and request processing requirements have grown as well. In this paper, we describe a few selected data infrastructure projects at Linked In that have helped us accommodate this increasing scale. Most of those projects build on existing open source projects and are themselves available as open source. The projects covered in this paper include: (1) Voldemort: a scalable and fault tolerant key-value store, (2) Data bus: a framework for delivering database changes to downstream applications, (3) Espresso: a distributed data store that supports flexible schemas and secondary indexing, (4) Kafka: a scalable and efficient messaging system for collecting various user activity events and log data.
Ion implant technology for state-of-the-art high efficiency solar cell applications

For many years, Photovoltaic (PV) solar technology was believed not possible to be cost effective and not even close to the cost for electricity production compared to fossil fuels. Surprisingly, the fact is that low cost but powerful and long-lasting solar modules can now be mass produced at the scale of over 60GW per year which makes the LCOE (levelizedcost of electricity) of latest PV systemcost competitive with any other technologies. Similarly, for ion implant technology in solar applications, which were thought to be too slow and expensive, have been successfully been utilized in current solar cell mass production as well as producing of state-of-the-art high efficiency solar cells. The development of ion implant processes for solar cells and the latest high efficiency solar cell results will be presented in this paper.
Palm-line detection

Palm lines, which consist of principal lines and wrinkles, are stable and essential traits for palmprint-based individual identification and can be extracted in low-resolution images. However, the research on palm-line detection has done little. Due to special properties of palmprint, in addition to the structure feature, width of the palm-line, which generally reflects strength information, is important to identify palms especially when various palmprints have similar structures. In this paper, a palm-line detection approach is proposed to simultaneously extract structure and strength features of palm lines by minimizing a local image area which is of similar brightness to each individual pixel. The presented method has been tested on the PolyU palmprint database and compared with the canny edge detector and SUSAN edge finder. Experimental results illustrate the effectiveness of this approach.
Does EigenPalm work? A System and Evaluation Perspective

Recently, there are keen interests in EigenPalm, which, collectively, refers to those methods that extract palmprint features directly from the appearance by means of principal component analysis (PCA) for (dis)similarity matching. Encouraging results have been reported with the use of EigenPalm. However, we find a different story under a system and evaluation perspective. In this paper, we would like to introduce three issues that should be considered: the effects of templates from two different sessions, the effects of identical twins and the effects of unseen subjects. They are missing in the previous studies of EigenPalm
Necessary and sufficient condition for finite horizon H/sub /spl infin// estimation of time delay systems

This paper is concerned with the problems of finite horizon H/sub /spl infin// filtering, prediction and fixed-lag smoothing for linear continuous-time systems with multiple delays. By applying an innovation approach in Krein space, a necessary and sufficient condition for the existence of an H/sub /spl infin// filter, predictor or smoother is derived. The estimator is given in terms of the solution of a partial differential equation with boundary conditions. The innovation approach in Krein space enables us to convert the very complicated deterministic estimation problem into a stochastic one to which a simple H/sub 2/ innovation analysis method can be adapted. The result of this paper demonstrates that the Krein space approach is powerful in solving otherwise very complicated H/sub /spl infin// problems. Our result is in contrast with many recent sufficient conditions for H/sub /spl infin// filtering of delay systems.
An Analysis of IrisCode

IrisCode is an iris recognition algorithm developed in 1993 and continuously improved by Daugman. It has been extensively applied in commercial iris recognition systems. IrisCode representing an iris based on coarse phase has a number of properties including rapid matching, binomial impostor distribution and a predictable false acceptance rate. Because of its successful applications and these properties, many similar coding methods have been developed for iris and palmprint identification. However, we lack a detailed analysis of IrisCode. The aim of this paper is to provide such an analysis as a way of better understanding IrisCode, extending the coarse phase representation to a precise phase representation, and uncovering the relationship between IrisCode and other coding methods. Our analysis demonstrates that IrisCode is a clustering algorithm with four prototypes; the locus of a Gabor function is a 2-D ellipse with respect to a phase parameter and can be approximated by a circle in many cases; Gabor function can be considered as a phase-steerable filter and the bitwise hamming distance can be regarded as a bitwise phase distance. We also discuss the theoretical foundation of the impostor binomial distribution. We use this analysis to develop a precise phase representation which can enhance accuracy. Finally, we relate IrisCode and other coding methods.
TCPD based pulse monitoring and analyzing

This article presents pulse monitoring and analysis approaches on traditional Chinese pulse diagnosis (TCPD) by means of modern nonlinear signal processing technology. Pulse monitoring is significant for the research on cardiovascular and nervous system. But some interference, such as respiration, motion artifacts can be greatly brought into the long-term pulse acquisition. Thus, a cascaded adaptive wavelet filter is designed to solve this issue. Then analysis of long-term pulse waveform in TCPD is illustrated after being preprocessed. What's more, the chaos character of healthy heart rate variability (HRV) is validated.
Graphite planar resistive switching memory and its application in pattern recognition

Resistive switching memory with a planar graphene nanoribbon structure has shown steady memory characteristics. By mechanically exfoliating the graphene sheet over a layer of 300nm SiO2 substrate, the device was fabricated with one step of electron beam lithography and physical vapor deposition. The device has an on/off ratio over 103, and exhibits multilevel resistive switching characteristics, making it possible to act as a synaptic device. Here we designed an artificial neuron network (ANN) to recognize images of 6 different letters, and the images were successfully distinguished. This result proposes a way to implement neuromorphic computation with carbon electronics.
Digital tongue image analysis in medical applications using a new tongue ColorChecker

Digital tongue images are analyzed by researchers for disease detection. In order to ensure a better color representation of the tongue body leading to more accurate detection results, this paper proposes a new tongue ColorChecker. This ColorChecker will act as a color reference, and can be used in color calibration algorithms to standardize the captured digital tongue images. Initially, a statistical tongue color gamut is established based on a large tongue image dataset. Through experimentation, various quantities of color-patches on the tongue ColorChecker are determined. Afterwards, the results produced by the Munsell ColorChecker are compared with the proposed tongue ColorChecker by applying the color difference calculation formula of CIELAB 1976 as a reference for the mean color calibration error. The results demonstrate that the proposed tongue ColorChecker, which has 24 color-patches, produces a smaller error (CIELAB 1976 - 10.6058) compared with the Munsell ColorChecker (CIELAB 1976 - 14.7836).
Hysteresis Reduction in Negative Capacitance Ge PFETs Enabled by Modulating Ferroelectric Properties in HfZrOx

We experimentally demonstrate that hysteresis of negative capacitance (NC) Ge pFETs is reduced through modulating the ferroelectric properties in HfZrO<sub><italic>x</italic></sub> (HZO) by changing the post annealing temperature. As annealing temperature varies from 350 °C to 450 °C, HZO exhibits a significant increasing in the ratio of remnant polarization <inline-formula> <tex-math notation="LaTeX">$P_{r}$ </tex-math></inline-formula> to coercive field <inline-formula> <tex-math notation="LaTeX">$E_{c}$ </tex-math></inline-formula>, which results in the improvement of the magnitude of ferroelectric NC <inline-formula> <tex-math notation="LaTeX">$C_\mathrm{FE}$ </tex-math></inline-formula>, therefore contributing to the reduction of hysteresis of the ferroelectric NC Ge transistors. It is also reported that the NC Ge transistor annealed at 450 °C has a small hysteresis of 0.10 V, and achieves the improved SS and <inline-formula> <tex-math notation="LaTeX">$I_\mathrm{DS}$ </tex-math></inline-formula> compared to control device without HZO.
A Novel Subspace-Based Facial Discriminant Feature Extraction Method

This paper presented a novel subspace-based facial discriminant feature extraction method, i.e. Orthogonalized Direct Linear Discriminant Analysis (OD-LDA), whose discriminant vectors could be obtained by performing Gram-Schmidt orthogonal procedure on a set of discriminant vectors of D-LDA. Experimental studies conducted on ORL, FERET, Yale, and AR face image databases showed that OD-LDA could compete with prevailing subspace-based facial discriminant feature extraction methods such as Fisherfaces, N-LDA D-LDA, Uncorrelated LDA, Parameterized D-LDA, K-L expansion based the between-class scatter matrix, and Orthogonal Complimentary Space Method in terms of recognition rate.
Radius-margin based support vector machine with LogDet regularizaron

Theoretically, Support Vector Machine (SVM) has the generalization error bound of radius-margin ratio, while the standard SVM only maximizes the margin. Several SVM variants based on the radius-margin ratio error bound have been proposed. However, most of them either require the form of the transformation matrix to be diagonal, or the optimization is computationally expensive. In this paper, we propose a novel convex radius-margin based SVM model with-LogDet regularization, ie., L-S VM Our model not only takes radius into consideration, but also increases the stability by combing the individual inequality constraints into one integrated inequality constraint. In L-SVM, we introduce a-LogDet regularization term to make the model more effective and get a dosed-form solution of the transformation matrix. Furthermore, we extend the L-SVM model to kernel space for nonlinear cases with the advantages of kernel principal component analysis. The experimental results show that L-SVM achieves significantly better performance both in accuracy and efficiency, compared to the standard SVM and the state-of-the-art radius-margin based SVM methods, e.g., RMM, R-SVM+ and R-SVM+ μ.
Segmentation of fingerprint image by using polarimetric feature

Segmentation of fingerprint image is the first step of fingerprint recognition, and it plays an essential role which helps to preserve genuine and reduce false minutiae and further aids the performance of Automatic Fingerprint Identification System (AFIS). The problem of segmentation has been thoroughly studied but never been completely solved. During this paper, we propose a novel representation of fingerprint image with the added polari-metric information which is captured by Stokes Imaging System, and followed by a simple yet efficient segmentation of fingerprint image based on the polarimetric variance (Polvar). Polarimetric characteristic is another distinguishable feature beside intense that reflecting light carries, and it provides potential way to enhance the contrast between background and foreground, and between ridges and valleys as well. And therefore, there is a possibility to achieve a satisfactory segmentation results. Non-overlapping block Polvar feature is utilized to accelerate computation, and moreover the segmentation results that are based on other common used features are compared, that is block energy, block coherence, block cluster degree. Experimental results show that our proposed novel method is much efficient than the other features and simultaneously achieve higher accuracy especially it well segments the case of remaining ridges from previously scanned finger. Segmentation results are evaluated both visually by human inspire and quantitatively.
Facial color feature extraction for disease diagnosis using non-base colors

Disease diagnosis via an individual's facial color has been practiced in oriental medicine for thousands of years. This work tackles the issue of quantitative facial color feature extraction for diagnostic purposes. Existing work in this area directly utilizes classic methods found in the standard color analysis area. We believe that these standard chromatic methods are not the most suitable for describing facial colors. Hence, we propose a color extraction method specially designed for facial diagnosis. The main contribution of this work is to define the facial base colors and to present six non-base colors (centroid colors) to represent the facial color space. First, a facial color gamut in the CIEx-y chromatic diagram is formed. Next, an area composed of base colors is defined within the color gamut. Afterwards, some clusters are located outside the base colors area. Finally, six centroids are selected to form a set of components to describe the facial color features. Disease detection is performed to compare the performance of the proposed and existing methods. Overall, the experimental results show that the proposed method outperforms the existing methods, which verifies its validity and effectiveness.
Parallel versus Hierarchical Fusion of Extended Fingerprint Features

Extended fingerprint features such as pores, dots and incipient ridges have been increasingly attracting attention from researchers and engineers working on automatic fingerprint recognition systems. A variety of methods have been proposed to combine these features with the traditional minutiae features. This paper comparatively analyses the parallel and hierarchical fusion approaches on a high resolution fingerprint image dataset. Based on the results, a novel and more effective hierarchical approach is presented for combining minutiae, pores, dots and incipient ridges.
Image segmentation by improved level set evolution algorithm

This paper investigated a novel variational level set evolution mathematical model for image segmentation. Considering some drawbacks of existed level set approaches, such as the re-initialization time-consuming process and the weighted parameters for the area region term. By virtue of recent progress in level set evolution algorithms, we in this paper present two strategies that may be treated as our contributions towards variational level set method. Two scenarios are considered, namely, the fitting energy term in the new model is to weak the sensitives of heavy noise and blur effect. Second, the edge detector can detect the weak boundaries by revising two parameters to offer some suitable convergence and satisfy the necessaries for different type of image edge detection. Simulation studies are presented to verify our method for natural and synthetic degraded images, and to evaluate and compare the new proposed algorithm with existing algorithms.
Image Set-Based Collaborative Representation for Face Recognition

With the rapid development of digital imaging and communication technologies, image set-based face recognition (ISFR) is becoming increasingly important. One key issue of ISFR is how to effectively and efficiently represent the query face image set using the gallery face image sets. The set-to-set distance-based methods ignore the relationship between gallery sets, whereas representing the query set images individually over the gallery sets ignores the correlation between query set images. In this paper, we propose a novel image set-based collaborative representation and classification method for ISFR. By modeling the query set as a convex or regularized hull, we represent this hull collaboratively over all the gallery sets. With the resolved representation coefficients, the distance between the query set and each gallery set can then be calculated for classification. The proposed model naturally and effectively extends the image-based collaborative representation to an image set based one, and our extensive experiments on benchmark ISFR databases show the superiority of the proposed method to state-of-the-art ISFR methods under different set sizes in terms of both recognition rate and efficiency.
Fast block-based image restoration employing the improved best neighborhood matching approach

The best neighborhood matching (BNM) algorithm is an efficient approach for image restoration. However, its high computation overhead imposes an obstacle to its application. In this paper, a fast image restoration approach named jump and look around BNM (JLBNM) is proposed to reduce computation overhead of the BNM. The main idea of JLBNM is to employ two kinds of search mechanisms so that the whole search process can be sped up. Some optimization techniques for the restoration algorithm JLBNM are also developed, including adaptive threshold in the matching stage, the terminal threshold in the searching stage, and the application of an appropriate matching function in both the matching and recovering stages. Theoretical analysis and experiment results have shown that JLBNM not only can provide high quality for image restoration but also has low computation overhead.
Impact of geometric dimensions on the behavior of GaN MIS-HEMT fabricated on patterned sapphire substrate

In this paper, an AlGaN/GaN based MIS-HEMT using Al2O3 dielectric as gate insulator was fabricated. We adopted the patterned sapphire as the substrate (PSS) of high-quality AlGaN GaN epitaxial layers. We also studied the influence of different gate-drain space (L<sub>gd</sub>) on breakdown voltage (V<sub>BD</sub>) and on-state resistance (R<sub>on</sub>) of GaN HEMT fabricated on patterned sapphire substrate. A breakdown voltage of 105 V was obtained with the L<sub>gd</sub> of 2 μm and gate width of 32 μm. The specific on resistance was 4.7 Ω·mm when L<sub>gd</sub> equals 0.5 μm. Meanwhile, it is found that the devices fabricated on the wet-etched pyramidal patterned sapphire substrate GaN exhibit better drive current stability than that of the devices on the conventional GaN-on-Sapphire substrate.
An Anatomy of IrisCode for Precise Phase Representation

IrisCode, a widely deployed iris recognition algorithm, developed in 1993 and continuously modified by Daugman has attracted considerable attentions. IrisCode using a coarse phase representation has number of properties such as rapid matching, binomial imposter distribution and predictable false acceptance rate. Although many similar coding methods have been developed for irises and palmprintgs based on IrisCode, a theoretical analysis of IrisCode has not been provided. In this paper, we aim at studying (1) the nature of IrisCode, (2) the property of the phase of Gabor function, (3) the extension of bitwise Hamming distance and (4) the theoretical foundation of the binomial imposter distribution and extending the coarse phase representation to a precise phase representation. Precisely, we demonstrate that IrisCode is a clustering algorithm with four prototypes; the locus of a Gabor function is a two-dimensional ellipse with respect to the phase parameter and bitwise Hamming can be regarded as angular distance. Using these properties, we provide a precise phase representation for IrisCode with an effective implementation for filtering and matching. Practically, the imposter distribution of IrisCode follows binomial distribution. However, the theoretical evidence is incomplete according to our analysis