774 research outputs found
Designing Flexible, Energy Efficient and Secure Wireless Solutions for the Internet of Things
The Internet of Things (IoT) is an emerging concept where ubiquitous physical objects (things) consisting of sensor, transceiver, processing hardware and software are interconnected via the Internet. The information collected by individual IoT nodes is shared among other often heterogeneous devices and over the Internet.
This dissertation presents
flexible, energy efficient and secure wireless solutions in the IoT application domain. System design and architecture designs are discussed envisioning a near-future world where wireless communication among heterogeneous IoT devices are seamlessly enabled.
Firstly, an energy-autonomous wireless communication system for ultra-small, ultra-low power IoT platforms is presented. To achieve orders of magnitude energy efficiency improvement, a comprehensive system-level framework that jointly optimizes various system parameters is developed. A new synchronization protocol and modulation schemes are specified for energy-scarce ultra-small IoT nodes. The dynamic link adaptation is proposed to guarantee the ultra-small node to always operate in the most energy efficiency mode, given an operating scenario. The outcome is a truly energy-optimized wireless communication system to enable various new applications such as implanted smart-dust devices.
Secondly, a configurable Software Defined Radio (SDR) baseband processor is designed and shown to be an efficient platform on which to execute several IoT wireless standards. It is a custom SIMD execution model coupled with a scalar unit and several architectural optimizations: streaming registers, variable bitwidth, dedicated ALUs, and an optimized reduction network. Voltage scaling and clock gating are employed to further reduce the power, with a more than a 100% time margin reserved for reliable operation in the near-threshold region.
Two upper bound systems are evaluated. A comprehensive power/area estimation indicates that the overhead of realizing SDR flexibility is insignificant. The benefit of baseband SDR is quantified and evaluated.
To further augment the benefits of a flexible baseband solution and to address the security issue of IoT connectivity, a light-weight Galois Field (GF) processor is proposed. This processor enables both energy-efficient block coding and symmetric/asymmetric cryptography kernel processing for a wide range of GF sizes (2^m, m = 2, 3, ..., 233) and arbitrary irreducible polynomials. Program directed connections among primitive GF arithmetic units enable dynamically configured parallelism to efficiently perform either four-way SIMD GF operations, including multiplicative inverse, or a long bit-width GF product in a single cycle. This demonstrates the feasibility of a unified architecture to enable error correction coding flexibility and secure wireless communication in the low power IoT domain.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137164/1/yajchen_1.pd
Understanding Attitudes towards Proenvironmental Travel: An Empirical Study from Tangshan City in China
Understanding people’s attitudes towards proenvironmental travel will help to encourage people to adopt proenvironmental travel behavior. Revealed preference theory assumes that the consumption preference of consumers can be revealed by their consumption behavior. In order to investigate the influences on citizens’ travel decision and analyze the difficulties of promoting proenvironmental travel behavior in medium-sized cities in China, based on revealed preference theory, this paper uses the RP survey method and disaggregate model to analyze how individual characteristics, situational factors, and trip features influence the travel mode choice. The field investigation was conducted in Tangshan City to obtain the RP data. An MNL model was built to deal with the travel mode choice. SPSS software was used to calibrate the model parameters. The goodness-of-fit tests and the predicted outcome demonstrate the validation of the parameter setting. The results show that gender, occupation, trip purpose, and distance have an obvious influence on the travel mode choice. In particular, the male gender, high income, and business travel show a high correlation with carbon-intensive travel, while the female gender and a medium income scored higher in terms of proenvironmental travel modes, such as walking, cycling, and public transport
Multifractal scaling analyses of the spatial diffusion pattern of COVID-19 pandemic in Chinese mainland
Revealing spatiotemporal evolution regularity in the spatial diffusion of
epidemics is helpful for preventing and controlling the spread of epidemics.
Based on the real-time COVID-19 datasets by prefecture-level cities and date,
this paper is aimed at exploring the multifractal scaling in spatial diffusion
pattern of COVID-19 pandemic and its evolution characteristics in Chinese
mainland. The ArcGIS technology and box-counting method are employed to extract
spatial data and the least square calculation is used to calculate fractal
parameters. The results show multifractal distribution of COVID-19 pandemic in
China. The generalized correlation dimension spectrums are inverse S-shaped
curves, but the fractal dimension values significantly exceeds the Euclidean
dimension of embedding space when moment order q<<0. The local singularity
spectrums are asymmetric unimodal curves, which slant to right. The fractal
dimension growth curves are shown as quasi S-shaped curves. From these
spectrums and growth curves, the main conclusions can be drawn as follows.
First, self-similar patterns developed in the process of Covid-19 pandemic,
which seem be dominated by multi-scaling law. Second, the spatial pattern of
COVID-19 across China can be characterized by global clustering with local
disordered diffusion. Third, the spatial diffusion process of COVID-19 in China
experienced four stages, i.e., initial stage, the rapid diffusion stage, the
hierarchical diffusion stage, and finally the contraction stage. This study
suggests that multifractal theory can be utilized to characterize
spatio-temporal diffusion of COVID-19 pandemic, and the case analyses may be
instructive for further exploring natural laws of spatial diffusion.Comment: 22 pages,6 figures, 4 table
StyleBART: Decorate Pretrained Model with Style Adapters for Unsupervised Stylistic Headline Generation
Stylistic headline generation is the task to generate a headline that not
only summarizes the content of an article, but also reflects a desired style
that attracts users. As style-specific article-headline pairs are scarce,
previous researches focus on unsupervised approaches with a standard headline
generation dataset and mono-style corpora. In this work, we follow this line
and propose StyleBART, an unsupervised approach for stylistic headline
generation. Our method decorates the pretrained BART model with adapters that
are responsible for different styles and allows the generation of headlines
with diverse styles by simply switching the adapters. Different from previous
works, StyleBART separates the task of style learning and headline generation,
making it possible to freely combine the base model and the style adapters
during inference. We further propose an inverse paraphrasing task to enhance
the style adapters. Extensive automatic and human evaluations show that
StyleBART achieves new state-of-the-art performance in the unsupervised
stylistic headline generation task, producing high-quality headlines with the
desired style.Comment: Findings of EMNLP 202
Gravitational and Autoregressive Analysis Spatial Diffusion of COVID-19 in Hubei Province, China
The spatial diffusion of epidemic disease follows distance decay law in
geography, but different diffusion processes may be modeled by different
mathematical functions under different spatio-temporal conditions. This paper
is devoted to modeling spatial diffusion patterns of COVID-19 stemming from
Wuhan city to Hubei province. The methods include gravity and spatial
auto-regression analyses. The local gravity model is derived from allometric
scaling and global gravity model, and then the parameters of the local gravity
model are estimated by observational data and linear regression. The main
results are as below. The local gravity model based on power law decay can
effectively describe the diffusion patterns and process of COVID-19 in Hubei
Province, and the goodness of fit of the gravity model based on negative
exponential decay to the observation data is not satisfactory. Further, the
goodness of fit of the model to data entirely became better and better over
time, the size elasticity coefficient increases first and then decreases, and
the distance attenuation exponent decreases first and then increases. Moreover,
the significance of spatial autoregressive coefficient in the model is low, and
the confidence level is less than 80%. The conclusions can be reached as
follows. (1) The spatial diffusion of COVID-19 of Hubei bears long range
effect, and the size of a city and the distance of the city to Wuhan affect the
total number of confirmed cases. (2) Wuhan direct transmission is the main
process in the spatial diffusion of COVID-19 in Hubei at the early stage, and
the horizontal transmission between regions is not significant. (3) The effect
of spatial isolation measures taken by Chinese government against the
transmission of COVID-19 is obvious. This study suggests that the role of
gravity should be taken into account to prevent and control epidemic disease.Comment: 24 pages, 3 figures, 5 table
Effects of Encapsulated Propolis on Blood Glycemic Control, Lipid Metabolism, and Insulin Resistance in Type 2 Diabetes Mellitus Rats
The present study investigates the encapsulated propolis on blood glycemic control, lipid metabolism, and insulin resistance in type 2 diabetes mellitus (T2DM) rats. The animal characteristics and biological assays of body weight, fasting blood glucose (FBG), fasting serum insulin (FINS), insulin act index (IAI), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured and euglycemic hyperinsulinemic glucose clamp technique were used to determine these effects. Our findings show that oral administration of encapsulated propolis can significantly inhibit the increasing of FBG and TG in T2DM rats and can improve IAI and M value in euglycemic hyperinsulinemic clamp experiment. There was no significant effects on body weight, TC, HDL-C, and LDL-C in T2DM rats treated with encapsulated propolis. In conclusion, the results indicate that encapsulated propolis can control blood glucose, modulate lipid metabolism, and improve the insulin sensitivity in T2DM rats
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