Morphing Switched-Capacitor Converters with Variable Conversion Ratio

High-voltage-gain and wide-input-range dc-dc converters are widely used in various electronics and industrial products such as portable devices, telecommunication, automotive, and aerospace systems. The two-stage converter is a widely adopted architecture for such applications, and it is proven to have a higher efficiency as compared with that of the single-stage converter. This paper presents a modular-cell-based morphing switched-capacitor (SC) converter for application as a front-end converter of the two-stage converter. The conversion ratio of this converter is flexible and variable and can be freely extended by increasing more SC modules. The varying conversion ratio is achieved through the morphing of the converter's structure corresponding to the amplitude of the input voltage. This converter is light and compact, and is highly efficient over a very wide range of input voltage and load conditions. Experimental work on a 25-W, 6-30-V input, 3.5-8.5-V output prototype, is performed. For a single SC module, the efficiency over the entire input voltage range is higher than 98%. Applied into the two-stage converter, the overall efficiency achievable over the entire operating range is 80% including the driver's loss

On practical design for joint distributed source and network coding

This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. This work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. Our scheme is based on a careful combination of linear syndrome-based Slepian-Wolf coding and random linear mixing (network coding). It is in general suboptimal; however, its low complexity and robustness to network dynamics make it suitable for practical implementation

Turbulent convection model in the overshooting region: II. Theoretical analysis

Turbulent convection models are thought to be good tools to deal with the convective overshooting in the stellar interior. However, they are too complex to be applied in calculations of stellar structure and evolution. In order to understand the physical processes of the convective overshooting and to simplify the application of turbulent convection models, a semi-analytic solution is necessary. We obtain the approximate solution and asymptotic solution of the turbulent convection model in the overshooting region, and find some important properties of the convective overshooting: I. The overshooting region can be partitioned into three parts: a thin region just outside the convective boundary with high efficiency of turbulent heat transfer, a power law dissipation region of turbulent kinetic energy in the middle, and a thermal dissipation area with rapidly decreasing turbulent kinetic energy. The decaying indices of the turbulent correlations $k$, $\bar{u_{r}'T'}$, and $\bar{T'T'}$ are only determined by the parameters of the TCM, and there is an equilibrium value of the anisotropic degree $\omega$. II. The overshooting length of the turbulent heat flux $\bar{u_{r}'T'}$ is about $1H_k$($H_k=|\frac{dr}{dlnk}|$). III. The value of the turbulent kinetic energy at the convective boundary $k_C$ can be estimated by a method called \textsl{the maximum of diffusion}. Turbulent correlations in the overshooting region can be estimated by using $k_C$ and exponentially decreasing functions with the decaying indices.Comment: 32 pages, 9 figures, Accepted by The Astrophysical Journa

Isolation and Characterization of a CBF Gene from Perennial Ryegrass (Lolium Perenne L.)

Maximum freezing tolerance of many temperate plant species is achieved after exposure to a period of non-freezing low temperatures, a phenomenon called “cold acclimation”. Multiple mechanisms appear to operate in conferring freezing tolerance in plants. The discovery of a class of transcription factor genes, CBF genes (C-repeat binding factor), in Arabidopsis demonstrated that CBF genes can serve as ‘Master switches’ to activate downstream cold-related (COR) genes during cold-acclimation (Liu et al., 1998). They act by binding to the core sequence (CCGAC) which is present in COR genes and thus activate the expression of COR genes and enhance freezing tolerance. The components of this cold acclimation pathway are conserved across a number of plant species including both eudicot and monocot species (Jaglo et al., 2001). Perennial ryegrass (L. perenne L.) is an important turf and forage grass but it lacks adequate winter hardiness which is a limiting factor for its adaptation to the northern regions of the US. Development of improved germplasm with enhanced winter hardiness would be highly desirable. The objective of this research was to isolate and characterize CBF gene(s) in perennial ryegrass and to determine the genomic location and the function of the CBF gene(s)

A High Reliability Asymptotic Approach for Packet Inter-Delivery Time Optimization in Cyber-Physical Systems

In cyber-physical systems such as automobiles, measurement data from sensor nodes should be delivered to other consumer nodes such as actuators in a regular fashion. But, in practical systems over unreliable media such as wireless, it is a significant challenge to guarantee small enough inter-delivery times for different clients with heterogeneous channel conditions and inter-delivery requirements. In this paper, we design scheduling policies aiming at satisfying the inter-delivery requirements of such clients. We formulate the problem as a risk-sensitive Markov Decision Process (MDP). Although the resulting problem involves an infinite state space, we first prove that there is an equivalent MDP involving only a finite number of states. Then we prove the existence of a stationary optimal policy and establish an algorithm to compute it in a finite number of steps. However, the bane of this and many similar problems is the resulting complexity, and, in an attempt to make fundamental progress, we further propose a new high reliability asymptotic approach. In essence, this approach considers the scenario when the channel failure probabilities for different clients are of the same order, and asymptotically approach zero. We thus proceed to determine the asymptotically optimal policy: in a two-client scenario, we show that the asymptotically optimal policy is a "modified least time-to-go" policy, which is intuitively appealing and easily implementable; in the general multi-client scenario, we are led to an SN policy, and we develop an algorithm of low computational complexity to obtain it. Simulation results show that the resulting policies perform well even in the pre-asymptotic regime with moderate failure probabilities

Development of a prototype robot and fast path-planning algorithm for static laser weeding

To demonstrate the feasibility and improve the implementation of laser weeding, a prototype robot was built and equipped with machine vision and gimbal mounted laser pointers. The robot consisted of a mobile platform modified from a small commercial quad bike, a camera to detect the crop and weeds and two steerable gimbals controlling the laser pointers. Visible-one laser pointers were used to simulate the powerful laser trajectories. A colour segmentation algorithm was utilised to extract plants from the soil background; size estimation was used to differentiate crop from weeds; and an erosion and dilation algorithm was developed to separate objects that were touching. Conversely, another algorithm, which utilised shape descriptors, was able to distinguish plant species in non-touching status regardless of area difference. Next, in order to reduce route length and run time, a new path-planning algorithm for static weeding was proposed and tested. It was demonstrated to be more efficient especially when addressing a higher density of weeds. A model was then established to determine the optimal segmentation size, based on the route length for treatment. It was found that the segmentation algorithm has the potential to be widely used in fast path-planning for the travelling-salesman problem. Finally, performance tests in the indoor environments showed that the weeding mean positional error was 1.97 mm, with a 0.88 mm standard deviation. Another test indicated that with a laser traversal speed of 30 mm/s and a dwell time of 0.64 s per weed, it had a hit rate of 97%