1,262 research outputs found
Vehicle-to-vehicle charging system fundamental and design comparison
The popularisation of the Electric Vehicle (EV) is restrained by the stagnation of energy storage technology and inadequate plug-in charging stations. This paper proposes a new vehicle-to-vehicle (V2V) charging technology platform, that can achieve wireless charging working in harmony with plug-in charging technology, or operate independently. V2V charging technology can effectively solve the problem of the limited number of plug-in stations. Moreover, it can charge the car any-time, anywhere, like a power bank. V2V charging system design requires a number of technical challenges to be overcome including the power balancing between vehicles and charging circuit design to maximizing the power transfer efficiency. In this paper, the schematic of V2V charging system is proposed, and we also propose the fundamentals of calculating the power capacity and the cost of EV energy when an EV is a power source in a V2V charging system. The hardware circuit design is presented and a detailed comparison of different coil shapes/ combinations and compensation circuit topologies is provided using the simulation tool ANSYS
Macroscopic phase segregation in superconducting K0.73Fe1.67Se2 as seen by muon spin rotation and infrared spectroscopy
Using muon spin rotation (\muSR) and infrared spectroscopy we investigated
the recently discovered superconductor K0.73Fe1.67Se2 with Tc = 32 K. We show
that the combined data can be consistently described in terms of a
macroscopically phase segregated state with a matrix of ~88% volume fraction
that is insulating and strongly magnetic and inclusions with a ~12% volume
fraction which are metallic, superconducting and non-magnetic. The electronic
properties of the latter, in terms of the normal state plasma frequency and the
superconducting condensate density, appear to be similar as in other iron
selenide or arsenide superconductors.Comment: 22 pages, 8 figures. (citation list correction.
Knowledge Rich Natural Language Queries over Structured Biological Databases
Increasingly, keyword, natural language and NoSQL queries are being used for
information retrieval from traditional as well as non-traditional databases
such as web, document, image, GIS, legal, and health databases. While their
popularity are undeniable for obvious reasons, their engineering is far from
simple. In most part, semantics and intent preserving mapping of a well
understood natural language query expressed over a structured database schema
to a structured query language is still a difficult task, and research to tame
the complexity is intense. In this paper, we propose a multi-level
knowledge-based middleware to facilitate such mappings that separate the
conceptual level from the physical level. We augment these multi-level
abstractions with a concept reasoner and a query strategy engine to dynamically
link arbitrary natural language querying to well defined structured queries. We
demonstrate the feasibility of our approach by presenting a Datalog based
prototype system, called BioSmart, that can compute responses to arbitrary
natural language queries over arbitrary databases once a syntactic
classification of the natural language query is made
Vehicle to Vehicle Charging (V2V) Bases on Wireless Power Transfer Technology
The slow development of energy storage technology combined with a limited number of plug-in charging stations negatively affects people's desire to purchase pure battery electric vehicles. A new wireless vehicle-to-vehicle charging technology structure is proposed, which can function with plug-in electric vehicles or operate independently. With a limited number of charging stations this technology can be used to increase charging opportunities through vehicle-to-vehicle (V2V) charging. V2V charging requires a number of technical challenges to be overcome, including the angular offset of the wireless power transfer resonant coils. The mutual inductance between two resonant coils is a key parameter for high power and efficient transfer of power. This paper presents the theory of angular offset multi-turn coil design
A Non-Isolated Bipolar Gate Driver with Self-Driven Negative Bias Generator in High-Side-Only Application
With the development of power electronic converters, size reducing and reliability extending are desired. For modern converter that utilises inductors or transformers, the dimensions of magnetic components are commonly inversely proportional to its switching frequency. With the increase of switching frequency, higher dv/dt may cause miss-triggering faults and unstable turn-off. Those issues can be relieved by applying a negative bias to conduct the turn-off. However, a separate DC-DC converter is normally required to generate this negative voltage. In this paper, a novel self-driven negative bias generator for high-side switch is introduced. The novel gate driver can provide bipolar gate driving capability without the need for a separate negative voltage supply. A prototype converter has been built and verified that the proposed bipolar gate driver could effectively generates the required negative voltage for power semiconductor driving without using a charge pump or switching converter
Multitemporal Very High Resolution from Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest
In this paper, the scientific outcomes of the 2016 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society are discussed. The 2016 Contest was an open topic competition based on a multitemporal and multimodal dataset, which included a temporal pair of very high resolution panchromatic and multispectral Deimos-2 images and a video captured by the Iris camera on-board the International Space Station. The problems addressed and the techniques proposed by the participants to the Contest spanned across a rather broad range of topics, and mixed ideas and methodologies from the remote sensing, video processing, and computer vision. In particular, the winning team developed a deep learning method to jointly address spatial scene labeling and temporal activity modeling using the available image and video data. The second place team proposed a random field model to simultaneously perform coregistration of multitemporal data, semantic segmentation, and change detection. The methodological key ideas of both these approaches and the main results of the corresponding experimental validation are discussed in this paper
A dynamical stability limit for the charge density wave in K0.3MoO3
We study the response of the one-dimensional charge density wave in K0.3MoO3
to different types of excitation with femtosecond optical pulses. We compare
the response to direct excitation of the lattice at mid-infrared frequencies
with that to the injection of quasi-particles across the low-energy charge
density wave gap and to charge transfer excitations in the near infrared. For
all three cases, we observe a fluence threshold above which the amplitude-mode
oscillation frequency is softened and the mode becomes increasingly damped. We
show that all the data can be collapsed onto a universal curve in which the
melting of the charge density wave occurs abruptly at a critical lattice
excursion. These data highlight the existence of a universal stability limit
for a charge density wave, reminiscent of the empirical Lindemann criterion for
the stability of a crystal lattice
A comprehensive evaluation of full reference image quality assessment algorithms
2012 19th IEEE International Conference on Image Processing, ICIP 2012, Lake Buena Vista, FL, 30-3 October 2012Recent years have witnessed a growing interest in developing objective image quality assessment (IQA) algorithms that can measure the image quality consistently with subjective evaluations. For the full reference (FR) IQA problem, great progress has been made in the past decade. On the other hand, several new large scale image datasets have been released for evaluating FR IQA methods in recent years. Meanwhile, no work has been reported to evaluate and compare the performance of state-of-the-art and representative FR IQA methods on all the available datasets. In this paper, we aim to fulfill this task by reporting the performance of eleven selected FR IQA algorithms on all the seven public IQA image datasets. Our evaluation results and the associated discussions will be very helpful for relevant researchers to have a clearer understanding about the status of modern FR IQA indices. Evaluation results presented in this paper are also online available at http://sse.tongji.edu.cn/linzhang/IQA/IQA. htm.Department of ComputingRefereed conference pape
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