B. Li - ICC, Durham

B. Li
Are you B. Li?

Claim your profile, edit publications, add additional information:

Contact Details

Name
B. Li
Affiliation
ICC, Durham
City
Durham
Country
United States

Pubs By Year

Pub Categories

 
Computer Science - Architecture (12)
 
Computer Science - Computer Vision and Pattern Recognition (9)
 
Physics - Materials Science (5)
 
Computer Science - Networking and Internet Architecture (2)
 
Computer Science - Learning (2)
 
Mathematics - Numerical Analysis (2)
 
Mathematics - Dynamical Systems (2)
 
Mathematics - Number Theory (2)
 
Mathematics - Statistics (1)
 
Computer Science - Computational Geometry (1)
 
Statistics - Theory (1)
 
Nuclear Experiment (1)
 
Computer Science - Computers and Society (1)
 
Computer Science - Human-Computer Interaction (1)
 
Cosmology and Nongalactic Astrophysics (1)
 
Physics - Other (1)
 
Nuclear Theory (1)
 
Mathematics - Classical Analysis and ODEs (1)
 
Mathematics - Probability (1)
 
Physics - Accelerator Physics (1)
 
Mathematics - Information Theory (1)
 
Computer Science - Information Theory (1)
 
Physics - Instrumentation and Detectors (1)
 
Computer Science - Other (1)
 
Mathematics - Analysis of PDEs (1)
 
Physics - Optics (1)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (1)
 
Solar and Stellar Astrophysics (1)
 
Physics - Strongly Correlated Electrons (1)

Publications Authored By B. Li

Statistical static timing analysis deals with the increasing variations in manufacturing processes to reduce the pessimism in the worst case timing analysis. Because of the correlation between delays of circuit components, timing model generation and hierarchical timing analysis face more challenges than in static timing analysis. In this paper, a novel method to generate timing models for combinational circuits considering variations is proposed. Read More

As semiconductor devices continue to scale down, process vari- ations become more relevant for circuit design. Facing such variations, statistical static timing analysis is introduced to model variations more accurately so that the pessimism in tra- ditional worst case timing analysis is reduced. Because all de- lays are modeled using correlated random variables, most statis- tical timing methods are much slower than corner based timing analysis. Read More

Post-Silicon Tunable (PST) clock buffers are widely used in high performance designs to counter process variations. By allowing delay compensation between consecutive register stages, PST buffers can effectively improve the yield of digital circuits. To date, the evaluation of manufacturing yield in the presence of PST buffers is only possible using Monte Carlo simulation. Read More

Level-sensitive latches are widely used in high- performance designs. For such circuits efficient statistical timing analysis algorithms are needed to take increasing process vari- ations into account. But existing methods solving this problem are still computationally expensive and can only provide the yield at a given clock period. Read More

In this paper, we investigate the challenges to apply Statistical Static Timing Analysis (SSTA) in hierarchical design flow, where modules supplied by IP vendors are used to hide design details for IP protection and to reduce the complexity of design and verification. For the three basic circuit types, combinational, flip-flop-based and latch-controlled, we propose methods to extract timing models which contain interfacing as well as compressed internal constraints. Using these compact timing models the runtime of full-chip timing analysis can be reduced, while circuit details from IP vendors are not exposed. Read More

Length-matching is an important technique to balance delays of bus signals in high-performance PCB routing. Existing routers, however, may generate dense meander segments with small distance. Signals propagating across these meander segments exhibit a speedup effect due to crosstalks between the segments of the same wire, thus leading to mismatch of arrival times even with the same physical wire length. Read More

Length-matching is an important technique to bal- ance delays of bus signals in high-performance PCB routing. Existing routers, however, may generate very dense meander segments. Signals propagating along these meander segments exhibit a speedup effect due to crosstalk between the segments of the same wire, thus leading to mismatch of arrival times even under the same physical wire length. Read More

Post-silicon clock tuning elements are widely used in high-performance designs to mitigate the effects of process variations and aging. Located on clock paths to flip-flops, these tuning elements can be configured through the scan chain so that clock skews to these flip-flops can be adjusted after man- ufacturing. Owing to the delay compensation across consecutive register stages enabled by the clock tuning elements, higher yield and enhanced robustness can be achieved. Read More

Flow-based microfluidic biochips are widely used in lab- on-a-chip experiments. In these chips, devices such as mixers and detectors connected by micro-channels execute specific operations. Intermediate fluid samples are saved in storage temporarily until target devices become avail- able. Read More

At submicron manufacturing technology nodes process variations affect circuit performance significantly. This trend leads to a large timing margin and thus overdesign to maintain yield. To combat this pessimism, post-silicon clock tuning buffers can be inserted into circuits to balance timing budgets of critical paths with their neighbors. Read More

With advancing process technologies and booming IoT markets, millimeter-wave CMOS RFICs have been widely developed in re- cent years. Since the performance of CMOS RFICs is very sensi- tive to the precision of the layout, precise placement of devices and precisely matched microstrip lengths to given values have been a labor-intensive and time-consuming task, and thus become a major bottleneck for time to market. This paper introduces a progressive integer-linear-programming-based method to gener- ate high-quality RFIC layouts satisfying very stringent routing requirements of microstrip lines, including spacing/non-crossing rules, precise length, and bend number minimization, within a given layout area. Read More

Single-shot real-time characterization of optical waveforms with sub-picosecond resolution is essential for investigating various ultrafast optical dynamics. However, the finite temporal recording length of current techniques hinders comprehensive understanding of many intriguing ultrafast optical phenomena that evolve over a time scale much longer than their fine temporal details. Inspired by the space-time duality and by stitching of multiple microscopic images to achieve a larger field of view in the spatial domain, here a panoramic-reconstruction temporal imaging (PARTI) system is devised to scale up the temporal recording length without sacrificing the resolution. Read More

At nanometer manufacturing technology nodes, process variations significantly affect circuit performance. To combat them, post- silicon clock tuning buffers can be deployed to balance timing bud- gets of critical paths for each individual chip after manufacturing. The challenge of this method is that path delays should be mea- sured for each chip to configure the tuning buffers properly. Read More

In static timing analysis, clock-to-q delays of flip-flops are considered as constants. Setup times and hold times are characterized separately and also used as constants. The characterized delays, setup times and hold times, are ap- plied in timing analysis independently to verify the perfor- mance of circuits. Read More

In this paper, we propose a Polar coding scheme for parallel Gaussian channels. The encoder knows the sum rate of the parallel channels but does not know the rate of any channel. By using the nesting property of Polar code, we design a coding/decoding scheme to achieve the sum rates. Read More

We present a general framework for the rigorous numerical analysis of time-fractional nonlinear parabolic partial differential equations, with a fractional derivative of order $\alpha\in(0,1)$ in time. The framework relies on three technical tools: a fractional version of the discrete Gr\"onwall-type inequality, discrete maximal regularity, and regularity theory of nonlinear equations. We establish a general criterion for showing the fractional discrete Gr\"onwall inequality, and verify it for the L1 scheme and convolution quadrature generated by BDFs. Read More

We study the structures of admissible words and full words for $\beta$-expansion. The distribution of full words are characterized by giving all the precise numbers of consecutive full words and non-full words with same lengths. Read More

At submicron manufacturing technology nodes, pro- cess variations affect circuit performance significantly. To counter these variations, engineers are reserving more timing margin to maintain yield, leading to an unaffordable overdesign. Most of these margins, however, are wasted after manufacturing, because process variations cause only some chips to be really slow, while other chips can easily meet given timing specifications. Read More

The ability to engineer the thermal conductivity of materials allows us to control the flow of heat and derive novel functionalities such as thermal rectification, thermal switching, and thermal cloaking. While this could be achieved by making use of composites and metamaterials at bulk scales, engineering the thermal conductivity at micro- and nano-scale dimensions is considerably more challenging. In this work we show that the local thermal conductivity along a single Si nanowire can be tuned to a desired value (between crystalline and amorphous limits) with high spatial resolution through selective helium ion irradiation with a well-controlled dose. Read More

Fully Programmable Valve Array (FPVA) has emerged as a new architecture for the next-generation flow-based microfluidic biochips. This 2D-array consists of regularly-arranged valves, which can be dynamically configured by users to realize microfluidic devices of different shapes and sizes as well as interconnections. Additionally, the regularity of the underlying structure renders FPVAs easier to integrate on a tiny chip. Read More

In this article, we first summarize and compare the phonon properties, such as phonon dispersion and relaxation time, of emerging pristine two-dimensional (2-D) materials with the single layer graphene to understand the role of crystal structure on their thermal conductivity. We then compare the phonon properties, between an idealized 2-D crystal, realistic 2-D crystals, and 3-D crystals, and present the physical picture on how the thermal conductivity of 2-D materials changes with sample sizes. The geometric effects, such as layer numbers and width, and other physical effects like defects, mechanical strains, and substrates, on the thermal properties of 2-D materials are discussed. Read More

The 10 MeV accelerator-driven subcritical system (ADS) Injector-I test stand at Institute of High Energy Physics (IHEP) is a testing facility dedicated to demonstrate one of the two injector design schemes [Injector Scheme-I, which works at 325 MHz], for the ADS project in China. The Injector adopted a four vane copper structure RFQ with output energy of 3.2 MeV and a superconducting (SC) section accommodating fourteen \b{eta}g=0. Read More

Flow-based microfluidic biochips have attracted much atten- tion in the EDA community due to their miniaturized size and execution efficiency. Previous research, however, still follows the traditional computing model with a dedicated storage unit, which actually becomes a bottleneck of the performance of bio- chips. In this paper, we propose the first architectural synthe- sis framework considering distributed storage constructed tem- porarily from transportation channels to cache fluid samples. Read More

Using the Galerkin method, we obtain the unique existence of the weak solution to a time fractional wave problem, and establish some regularity estimates which reveal the singularity structure of the weak solution in time. Read More

How the solar corona is heated to high temperatures remains an unsolved mystery in solar physics. In the present study we analyse observations of 50 whole active-region loops taken with the Extreme-ultraviolet Imaging Spectrometer (EIS) on board the Hinode satellite. Eleven loops were classified as cool (<1 MK) and 39 as warm (1-2 MK) loops. Read More

For large circuits, static timing analysis (STA) needs to be performed in a hierarchical manner to achieve higher performance in arrival time propagation. In hierarchical STA, efficient and accurate timing models of sub-modules need to be created. We propose a timing model extraction method that significantly reduces the size of timing models without losing any accuracy by removing redundant timing information. Read More

We have used soft x-ray photoemission electron microscopy to image the magnetization of single domain La$_{0.7}$Sr$_{0.3}$MnO$_{3}$ nano-islands arranged in geometrically frustrated configurations such as square ice and kagome ice geometries. Read More

Wireless sensor-actuator networks (WSANs) are gaining momentum in industrial process automation as a communication infrastructure for lowering deployment and maintenance costs. In traditional wireless control systems the plant controller and the network manager operate in isolation, which ignore the significant influence of network reliability on plant control performance. To enhance the dependability of industrial wireless control, we propose a holistic cyber-physical management framework that employs run-time coordination between the plant control and network management. Read More

For spectrally negative L\'evy processes, adapting an approach from \cite{BoLi:sub1}, we identify joint Laplace transforms involving local times evaluated at either the first passage times, or independent exponential times, or inverse local times. The Laplace transforms are expressed in terms of the associated scale functions. As an application, a Ray-Knight theorem type result is obtained. Read More

Multi-class supervised learning systems require the knowledge of the entire range of labels they predict. Often when learnt incrementally, they suffer from catastrophic forgetting. To avoid this, generous leeways have to be made to the philosophy of incremental learning that either forces a part of the machine to not learn, or to retrain the machine again with a selection of the historic data. Read More

Materials exhibiting large magnetoresistance may not only be of fundamental research interest, but also can lead to wide-ranging applications in magnetic sensors and switches. Here we demonstrate a large linear-in-field magnetoresistance, $\Delta \rho/\rho$ reaching as high as $\sim$600$\%$ at 2 K under a 9 Tesla field, in the tetragonal phase of a transiton-metal stannide $\beta$-RhSn$_4$. Detailed analyses show that its magnetic responses are overall inconsistent with the classical model based on the multiple electron scattering by mobility fluctuations in an inhomogenous conductor, but rather in line with the quantum effects due to the presence of Dirac-like dispersions in the electronic structure. Read More

This paper proposes a new residual convolutional neural network (CNN) architecture for single image depth estimation. Compared with existing deep CNN based methods, our method achieves much better results with fewer training examples and model parameters. The advantages of our method come from the usage of dilated convolution, skip connection architecture and soft-weight-sum inference. Read More

Dias and Silvera (Letters, p. 715, 2017) claim the observation of the Wigner-Huntington transition to metallic hydrogen at 495 GPa. We show that neither the claims of the record pressure or the phase transition to a metallic state are supported by any data and contradict the authors' own unconfirmed previous results. Read More

Type-I cathrate compounds with off-center guest ions realize the phonon-glass electron-crystal concept by exhibiting almost identical lattice thermal conductivities $\kappa_{\rm L}$ to those observed in network-forming glasses. This is in contrast with type-I clathrates with on-center guest ions showing $\kappa_{\rm L}$ of conventional crystallines. Glasslike $\kappa_{\rm L}$ stems from the peculiar THz frequency dynamics in off-center type-I clathrates where there exist three kinds of modes classified into extended(EX), weakly(WL) and strongly localized(SL) modes as demonstrated by Liu et. Read More

The dispersion problem has been widely studied in computational geometry and facility location, and is closely related to the packing problem. The goal is to locate n points (e.g. Read More

Action recognition from well-segmented 3D skeleton video has been intensively studied. However, due to the difficulty in representing the 3D skeleton video and the lack of training data, action detection from streaming 3D skeleton video still lags far behind its recognition counterpart and image based object detection. In this paper, we propose a novel approach for this problem, which leverages both effective skeleton video encoding and deep regression based object detection from images. Read More

We present an image classification based approach to large scale action recognition from 3D skeleton videos. Firstly, we map the 3D skeleton videos to color images, where the transformed action images are translation-scale invariance and dataset independent. Secondly, we propose a multi-scale deep convolutional neural network (CNN) for the image classification task, which could enhance the temporal frequency adjustment of our model. Read More

The Age-of-Information (AoI) has recently been proposed as an important metric for investigating the timeliness performance in information-update systems. Prior studies on AoI optimization often consider a Push model, which is concerned about when and how to "push" (i.e. Read More

In this paper, we focus on the COM-type negative binomial distribution with three parameters, which belongs to COM-type $(a,b,0)$ class distributions and family of equilibrium distributions of arbitrary birth-death process. Besides, we show abundant distributional properties such as overdispersion and underdispersion, log-concavity, log-convexity (infinite divisibility), pseudo compound Poisson, stochastic ordering and asymptotic approximation. Some characterizations including sum of equicorrelated geometrically distributed r. Read More

Personalized and content-adaptive image enhancement can find many applications in the age of social media and mobile computing. This paper presents a relative-learning-based approach, which, unlike previous methods, does not require matching original and enhanced images for training. This allows the use of massive online photo collections to train a ranking model for improved enhancement. Read More

In this paper, a class of neutral type competitive neural networks with mixed time-varying delays and leakage delays on time scales is proposed. Based on the exponential dichotomy of linear dynamic equations on time scales, Banach's fixed point theorem and the theory of calculus on time scales, some sufficient conditions that are independent of the backwards graininess function of the time scale are obtained for the existence and global exponential stability of almost periodic solutions for this class of neural networks. The obtained results are completely new and indicate that both the continuous time and the discrete time cases of the networks share the same dynamical behavior. Read More

In today's age of internet and social media, one can find an enormous volume of forged images on-line. These images have been used in the past to convey falsified information and achieve harmful intentions. The spread and the effect of the social media only makes this problem more severe. Read More

All people with diabetes have the risk of developing diabetic retinopathy (DR), a vision-threatening complication. Early detection and timely treatment can reduce the occurrence of blindness due to DR. Computer-aided diagnosis has the potential benefit of improving the accuracy and speed in DR detection. Read More

The stochastic time-fractional equation $\partial_t \psi -\Delta\partial_t^{1-\alpha} \psi = f + \dot W$ with space-time white noise $\dot W$ is discretized in time by a backward-Euler convolution quadrature for which the sharp-order error estimate \[ {\mathbb E}\|\psi(\cdot,t_n)-\psi_n\|_{L^2(\mathcal{O})}^2=O(\tau^{1-\alpha d/2}) \] is established for $\alpha\in(0,2/d)$, where $d$ denotes the spatial dimension, $\psi_n$ the approximate solution at the $n^{\rm th}$ time step, and $\mathbb{E}$ the expectation operator. In particular, the result indicates optimal convergence rates of numerical solutions for both stochastic subdiffusion and diffusion-wave problems in one spatial dimension. Numerical examples are presented to illustrate the theoretical analysis. Read More

Using the same approach proposed by Kolomeitsev \textit{et al} in their recent work\cite{Kolomeitsev16}, we examine how tightly the nuclear symmetry energy \esym at density $\rho$ is constrained by the universal equation of state (EOS) of the unitary Fermi gas $E_{\rm{UG}}(\rho)$, taking into account the higher order skewness parameters $J_0$ and $J_{\rm{sym}}$ and reexamining the uncertainty in $K_{\rm{sym}}$. We found that $E_{\rm{UG}}(\rho)$ does provide a useful lower boundary for the \esym confirming the finding by Kolomeitsev \textit{et al}. However, it does not tightly constrain the correlation between the magnitude $E_{\rm{sym}}(\rho_0)$ and slope $L$ unless the curvature $K_{\rm{sym}}$ of the symmetry energy at saturation density $\rho_0$ is more precisely known within its current uncertain range. Read More

Outdoor shopping complexes (OSC) are extremely difficult for people with visual impairment to navigate. Existing GPS devices are mostly designed for roadside navigation and seldom transition well into an OSC-like setting. We report our study on the challenges faced by a blind person in navigating OSC through developing a new mobile application named iExplore. Read More

The morphological properties of large scale structure of the Universe can be fully described by four Minkowski functionals (MFs), which provide important complementary information to other statistical observables such as the widely used 2-point statistics in configuration and Fourier spaces. In this work, for the first time, we present the differences in the morphology of large scale structure caused by modifications to general relativity (to address the cosmic acceleration problem), by measuring the MFs from N-body simulations of modified gravity and general relativity. We find strong statistical power when using the MFs to constrain modified theories of gravity: with a galaxy survey that has survey volume $\sim 0. Read More

Recent researches show that unmanned aerial vehicle (UAV) can offer an efficient solution to achieve wireless connectivity with high mobility and low cost. This paper investigates the secrecy energy efficiency (SEE) in an UAV-enabled communication network via a threshold-based access scheme and multi-antenna technique, where the UAV-enabled transmitters, legitimate receivers and eavesdroppers are deployed randomly. In particular, we first exploit the association probability of a randomly located receiver and the activation probability of UAV-enabled transmitters. Read More

Let $\beta > 1$ and the run-length function $r_n(x,\beta)$ be the maximal length of consecutive zeros amongst the first n digits in the $\beta$-expansion of $x\in[0,1]$. The exceptional set $$E_{\max}^{\varphi}=\left\{x \in [0,1]:\liminf_{n\rightarrow \infty}\frac{r_n(x,\beta)}{\varphi(n)}=0, \limsup_{n\rightarrow \infty}\frac{r_n(x,\beta)}{\varphi(n)}=+\infty\right\}$$ is investigated, where $\varphi: \mathbb{N} \rightarrow \mathbb{R}^+$ is a monotonically increasing function with $\lim\limits_{n\rightarrow \infty }\varphi(n)=+\infty$. We prove that the set $E_{\max}^{\varphi}$ is either empty or of full Hausdorff dimension and residual in $[0,1]$ according to the increasing rate of $\varphi$ . Read More

Traffic congestion is a widespread problem. Dynamic traffic routing systems and congestion pricing are getting importance in recent research. Lane prediction and vehicle density estimation is an important component of such systems. Read More