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Yu Fu

Publications and source records attributed to Yu Fu.

At least 127 records · Page 7Linked to original sources

Two-dimensional Cold Electron Transport for Steep-slope Transistors

Room-temperature Fermi-Dirac electron thermal excitation in conventional three-dimensional (3D) or two-dimensional (2D) semiconductors generates hot electrons with a relatively long thermal tail in energy distribution. These hot electrons set a fundamental obstacle known as the "Boltzmann tyranny" that limits the subthreshold swing (SS) and therefore the minimum power consumption of 3D and 2D field-effect transistors (FETs). Here, we investigated a novel graphene (Gr)-enabled cold electron injection where the Gr acts as the Dirac source to provide the cold electrons with a localized electron density distribution and a short thermal tail at room temperature. These cold electrons correspond to an electronic cooling effect with the effective electron temperature of ~145 K in the monolayer MoS2, which enable the transport factor lowering and thus the steep-slope switching (across for 3 decades with a minimum SS of 29 mV/decade at room temperature) for a monolayer MoS2 FET. Especially, a record-high sub-60-mV/decade current density (over 1 μA/μm) can be achieved compared to conventional steep-slope technologies such as tunneling FETs or negative capacitance FETs using 2D or 3D channel materials. Our work demonstrates the great potential of 2D Dirac-source cold electron transistor as an innovative steep-slope transistor concept, and provides new opportunities for 2D materials toward future energy-efficient nanoelectronics.

cond-mat.mes-hall

Evaluating the Effect of Audience in a Virtual Reality Presentation Training Tool

Public speaking is an essential skill in everyone's professional or academic career. Nevertheless, honing this skill is often tricky because training in front of a mirror does not give feedback or inspire the same anxiety as present-ing in front of an audience. Further, most people do not always have access to the place where the presentation will happen. In this research, we developed a Virtual Reality (VR) environment to assist in improving people's presentation skills. Our system uses 3D scanned people to create more realistic scenarios. We conducted a study with twelve participants who had no prior experience with VR. We validated our virtual environment by analyzing whether it was preferred to no VR system and accepted regardless of the existence of a virtual audience. Our results show that users overwhelmingly prefer to use the VR system as a tool to help them improve their public speaking skills than training in an empty environment. However, the preference for an audience is mixed.

cs.HC

End-to-End Energy Efficiency Evaluation for B5G Ultra Dense Networks

Energy efficiency (EE) is a major performance metric for fifth generation (5G) and beyond 5G (B5G) wireless communication systems, especially for ultra dense networks. This paper proposes an end-to-end (e2e) power consumption model and studies the energy efficiency for a heterogeneous B5G cellular architecture that separates the indoor and outdoor communication scenarios in ultra dense networks. In this work, massive multiple-input-multiple-output (MIMO) technologies at conventional sub-6 GHz frequencies are used for long-distance outdoor communications. Light-Fidelity (LiFi) and millimeter wave (mmWave) technologies are deployed to provide a high data rate service to indoor users. Whereas, in the referenced nonseparated system, the indoor users communicate with the outdoor massive MIMO macro base station directly. The performance of these two systems are evaluated and compared in terms of the total power consumption and energy efficiency. The results show that the network architecture which separates indoor and outdoor communication can support a higher data rate transmission for less energy consumption, compared to non-separate communication scenario. In addition, the results show that deploying LiFi and mmWave IAPs can enable users to transmit at a higher data rate and further improve the EE.

eess.SP

BER Performance of Spatial Modulation Systems Under a Non-Stationary Massive MIMO Channel Model

In this paper, the bit error rate (BER) performance of spatial modulation (SM) systems is investigated both theoretically and by simulation in a non-stationary Kronecker-based massive multiple-input-multiple-output (MIMO) channel model in multi-user (MU) scenarios. Massive MIMO SM systems are considered in this paper using both a time-division multiple access (TDMA) scheme and a block diagonalization (BD) based precoding scheme, for different system settings. Their performance is compared with a vertical Bell labs layered space-time (V-BLAST) architecture based system and a conventional channel inversion system. It is observed that a higher cluster evolution factor can result in better BER performance of SM systems due to the low correlation among sub-channels. Compared with the BD-SM system, the SM system using the TDMA scheme obtains a better BER performance but with a much lower total system data rate. The BD-MU-SM system achieves the best trade-off between the data rate and the BER performance among all of the systems considered. When compared with the V-BLAST system and the channel inversion system, SM approaches offer advantages in performance for MU massive MIMO systems.

eess.SP

On Chen's biharmonic conjecture for hypersurfaces in $\mathbb R^5$

A longstanding conjecture on biharmonic submanifolds, proposed by Chen in 1991, is that {\it any biharmonic submanifold in a Euclidean space is minimal}. In the case of a hypersurface $M^n$ in $\mathbb R^{n+1}$, Chen's conjecture was settled in the case of $n=2$ by Chen and Jiang around 1987 independently. Hasanis and Vlachos in 1995 settled Chen's conjecture for a hypersurface with $n=3$. However, the general Chen's conjecture on a hypersurface $M^n$ remains open for $n> 3$. In this paper, we settle Chen's conjecture for hypersurfaces in $\mathbb R^{5}$ for $n=4$.

math.DG

Diode-like Selective Enhancement of Carrier Transport through Metal-Semiconductor Interface Decorated by Monolayer Boron Nitride

Two-dimensional (2D) semiconductors are promising material candidates for next-generation nanoelectronics. However, there are fundamental challenges related to their metal-semiconductor (MS) contacts which limit the performance potential for practical device applications. In this work, we exploit 2D monolayer hexagonal boron nitride (h-BN) as an ultrathin decorating layer to form a metal-insulator-semiconductor (MIS) contact, and demonstrate a novel diode-like selective enhancement of the carrier transport through it. Compared to the conventional MS contact, the MIS contact dominated by both thermionic emission and quantum tunneling can significantly reduce the contact resistance and boost the electron transport from the semiconductor to the metal, but has negligible effects on the electron transport oppositely. We also investigate the negative barrier height with the concept of carrier collection barrier, and show its critical role at the drain end for determining the overall transistor performance.

physics.app-ph

Independence of the inverse spin Hall effect with the magnetic phase in thin NiCu films

Large spin Hall angles have been observed in 3d ferromagnets, but their origin, and especially their link with the ferromagnetic order, remain unclear. Here, we investigate the inverse spin Hall effect of Ni60Cu40 and Ni50Cu50 across their Curie temperature using spin pumping experiments. We evidence that the inverse spin Hall effect in these samples is comparable to that of platinum, and that it is insensitive to the magnetic order. These results points towards a Heisenberg localized model of the transition, and suggest that the large spin Hall effects in 3d ferromagnets can be independent of the magnetic phase.

cond-mat.mtrl-sci

Deep Model with Siamese Network for Viability and Necrosis Tumor Assessment in Osteosarcoma

Osteosarcoma is the most common primary malignant bone tumor, which has high mortality due to easy lung metastasis. Osteosarcoma is a highly anaplastic, pleomorphic tumor with a variety of tumor cell morphology, including fusiform, oval, epithelial, lymphocyte like, small round, transparent cells, etc. Due to the multiple patterns of osteosarcoma cell morphology, pathologists have differences in the classification (viable tumor, necrotic tumor, non-tumor) of osteosarcoma. Therefore, automatic and accurate recognition algorithms can help pathologists greatly reduce time and improve diagnostic accuracy. In recent years, deep learning technology has made great progress in the field of natural images and medical images, and has achieved excellent results beyond human performance in classification. In this paper, we propose a Deep Model with Siamese Network (DS-Net) for automatic classification in Hematoxylin and Eosin (H&E) stained osteosarcoma histology images.

physics.med-ph

Privacy Preserving Count Statistics

The ability to preserve user privacy and anonymity is important. One of the safest ways to maintain privacy is to avoid storing personally identifiable information (PII), which poses a challenge for maintaining useful user statistics. Probabilistic counting has been used to find the cardinality of a multiset when precise counting is too resource intensive. In this paper, probabilistic counting is used as an anonymization technique that provides a reliable estimate of the number of unique users. We extend previous work in probabilistic counting by considering its use for preserving user anonymity, developing application guidelines and including hash collisions in the estimate. Our work complements previous method by attempting to explore the causes of the deviation of uncorrected estimate from the real value. The experimental results show that if the proper register size is used, collision compensation provides estimates are as good as, if not better than, the original probabilistic counting. We develop a new anonymity metric to precisely quantify the degree of anonymity the algorithm provides.

cs.CR

Biharmonic hypersurfaces in a product space $L^m\times \mathbb{R}$

In this paper, we study biharmonic hypersurfaces in a product of an Einstein space and a real line. We prove that a biharmonic hypersurface with constant mean curvature in such a product is either minimal or a vertical cylinder generalizing a result of \cite{OW} and \cite{FOR}. We derived the biharmonic equation for hypersurfaces in $S^m\times \mathbb{R}$ and $H^m\times \mathbb{R}$ in terms of the angle function of the hypersurface, and use it to obtain some classifications of biharmonic hypersurfaces in such spaces. These include classifications of biharmonic hypersurfaces which are totally umbilical or semi-parallel for $m\ge 3$, and some classifications of biharmonic surfaces in $S^2\times \mathbb{R}$ and $H^2\times \mathbb{R}$ which are constant angle or belong to certain classes of rotation surfaces.

math.DG

Optimizing seed inputs in fuzzing with machine learning

The success of a fuzzing campaign is heavily depending on the quality of seed inputs used for test generation. It is however challenging to compose a corpus of seed inputs that enable high code and behavior coverage of the target program, especially when the target program requires complex input formats such as PDF files. We present a machine learning based framework to improve the quality of seed inputs for fuzzing programs that take PDF files as input. Given an initial set of seed PDF files, our framework utilizes a set of neural networks to 1) discover the correlation between these PDF files and the execution in the target program, and 2) leverage such correlation to generate new seed files that more likely explore new paths in the target program. Our experiments on a set of widely used PDF viewers demonstrate that the improved seed inputs produced by our framework could significantly increase the code coverage of the target program and the likelihood of detecting program crashes.

cs.CR

Composing Method for the Two-dimensional Scanning Spectra Observed by the New Vacuum Solar Telescope

In this paper we illustrate the technique used by the New Vacuum Solar Telescope to increase the spatial resolution of two-dimensional (2D) solar spectroscopy observation involving two dimensions of space and one of wavelength. Without an image stabilizer at the NVST, a large scale wobble motion is present during the spatial scanning, whose instantaneous amplitude could reach up to 1.3" due to the earth's atmosphere and the precision of the telescope guiding system, and seriously decreases the spatial resolution of 2D spatial maps composed with the scanning spectra. We make the following effort to resolve this problem: the imaging system (e.g., the TiO-band) is used to record and detect the displacement vectors of solar image motion during the raster scan, in both the slit and scanning directions. The spectral data (e.g., the Ha line) which are originally obtained in time sequence are corrected and re-arranged in space according to those displacement vectors. Raster scans are carried out in several active regions with different seeing conditions (two rasters are illustrated in this paper). Given a certain spatial sample and temporal resolution, the spatial resolution of the composed 2D map could be close to that of the slit-jaw image. The resulting quality after correction is quantitatively evaluated with two methods. Two-dimensional physical quantity, such as the line-of-sight velocities in multi-layer of the solar atmosphere, is also inferred demonstrating the effect of this technique.

astro-ph.IM

Precise Reduction of Solar Spectra Observed by the 1-meter New Vacuum Solar Telescope

We present a precise and complete procedure for processing spectral data observed by the 1-meter New Vacuum Solar Telescope (NVST). The procedure is suitable for both the sit-and-stare and raster-scan spectra. In this work, the geometric distortions of the spectra are firstly corrected for subsequent processes. Then, considering the temporal changes and the remnants of spectral lines in the flat-field, the original flat-field matrix is split into four independent components for ensuring a high precision flat-fielding correction, consisting of the continuum gradient matrix, slit non-uniform matrix, CCD dust matrix, and interference fringe matrix. Subsequently, the spectral line drifts and intensity fluctuations of the science data are further corrected. After precise reduction with this procedure, the measuring accuracies of the Doppler velocities for different spectral lines and of the oscillation curves of the chromosphere and photosphere are measured. The results show that the highest measuring accuracy of the Doppler velocity is within 100 ms-1, which indicates that the characteristics of the photosphere and chromosphere can be studied co-spatially and co-temporally with the reduced spectra of NVST.

astro-ph.SR

Using Markov Models and Statistics to Learn, Extract, Fuse, and Detect Patterns in Raw Data

Many systems are partially stochastic in nature. We have derived data driven approaches for extracting stochastic state machines (Markov models) directly from observed data. This chapter provides an overview of our approach with numerous practical applications. We have used this approach for inferring shipping patterns, exploiting computer system side-channel information, and detecting botnet activities. For contrast, we include a related data-driven statistical inferencing approach that detects and localizes radiation sources.

cs.CR

Stealthy Malware Traffic - Not as Innocent as It Looks

Malware is constantly evolving. Although existing countermeasures have success in malware detection, corresponding counter-countermeasures are always emerging. In this study, a counter-countermeasure that avoids network-based detection approaches by camouflaging malicious traffic as an innocuous protocol is presented. The approach includes two steps: Traffic format transformation and side-channel massage (SCM). Format transforming encryption (FTE) translates protocol syntax to mimic another innocuous protocol while SCM obscures traffic side-channels. The proposed approach is illustrated by transforming Zeus botnet (Zbot) Command and Control (C&C) traffic into smart grid Phasor Measurement Unit (PMU) data. The experimental results show that the transformed traffic is identified by Wireshark as synchrophasor protocol, and the transformed protocol fools current side-channel attacks. Moreover, it is shown that a real smart grid Phasor Data Concentrator (PDC) accepts the false PMU data.

cs.CR

A Covert Data Transport Protocol

Both enterprise and national firewalls filter network connections. For data forensics and botnet removal applications, it is important to establish the information source. In this paper, we describe a data transport layer which allows a client to transfer encrypted data that provides no discernible information regarding the data source. We use a domain generation algorithm (DGA) to encode AES encrypted data into domain names that current tools are unable to reliably differentiate from valid domain names. The domain names are registered using (free) dynamic DNS services. The data transmission format is not vulnerable to Deep Packet Inspection (DPI).

cs.CR

Biharmonic hypersurfaces with constant scalar curvature in space forms

Let $M^n$ be a biharmonic hypersurface with constant scalar curvature in a space form $\mathbb M^{n+1}(c)$. We show that $M^n$ has constant mean curvature if $c>0$ and $M^n$ is minimal if $c\leq0$, provided that the number of distinct principal curvatures is no more than 6. This partially confirms Chen's conjecture and Generalized Chen's conjecture. As a consequence, we prove that there exist no proper biharmonic hypersurfaces with constant scalar curvature in Euclidean space $\mathbb E^{n+1}$ or hyperbolic space $\mathbb H^{n+1}$ for $n<7$.

math.DG

Efficient spectral sparse grid approximations for solving multi-dimensional forward backward SDEs

This is the second part in a series of papers on multi-step schemes for solving coupled forward backward stochastic differential equations (FBSDEs). We extend the basic idea in our former paper [W. Zhao, Y. Fu and T. Zhou, SIAM J. Sci. Comput., 36 (2014), pp. A1731-A1751] to solve high-dimensional FBSDEs, by using the spectral sparse grid approximations. The main issue for solving high dimensional FBSDEs is to build an efficient spatial discretization, and deal with the related high dimensional conditional expectations and interpolations. In this work, we propose the sparse grid spatial discretization. We use the sparse grid Gaussian-Hermite quadrature rule to approximate the conditional expectations. And for the associated high dimensional interpolations, we adopt an spectral expansion of functions in polynomial spaces with respect to the spatial variables, and use the sparse grid approximations to recover the expansion coefficients. The FFT algorithm is used to speed up the recovery procedure, and the entire algorithm admits efficient and high accurate approximations in high-dimensions, provided that the solutions are sufficiently smooth. Several numerical examples are presented to demonstrate the efficiency of the proposed methods.

math.NA