483 research outputs found
Design and implementation of two non-isolated high gain DC-DC converters
In most solar energy systems, the output voltage of a photovoltaic panel is usually between 20 to 40 Vdc. In order to interface the panels to a 400 Vdc bus, a high voltage gain dc-dc converter is required.
This thesis starts with analyzing and simulating several topologies that have been already introduced for this application. The voltage gain and efficiency are investigated analytically. A hardware prototype of one of the existing topologies, the interleaved boost converter with voltage multiplier cell, has been developed. Finally, a new topology with a higher voltage transfer ratio is proposed and its experimental results are compared with former topologies. Simulations are used to verify the design and predict the performance of each topology --Abstract, page iii
"Seed Science and Engineering" Exploration on the Construction of Curriculum Ideological and Political System
The specialty of "seed science and Engineering" has trained a large number of scarce seed talents for China. This paper summarizes the experience, existing problems and future improvement direction of the ideological and political system construction of the curriculum of "seed science and Engineering" in our university, in order to improve the ideological and political system construction of colleges and universities
Circular External Difference Families: Construction and Non-Existence
The circular external difference family and its strong version, which
themselves are of independent combinatorial interest, were proposed as variants
of the difference family to construct new unconditionally secure non-malleable
threshold schemes. In this paper, we present new results regarding the
construction and non-existence of (strong) circular external difference
families, thereby solving several open problems on this topic
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City in the park,” Greenway Network Concept of High-Density Cities: Adaptation of Singapore Park Connector Network in Chinese Cities
This paper uses the “Park Connector Network” (PCN) as a model, to analyze Singapore’s experience and to cope with the dramatic increase in population and urbanization, and then to apply this experience to Chinese high-density cities. The research goal is to provide guidance for the adaptation of “City in the Park” in China and the construction of high-density urban green space systems. The concept of “City in the Park” that was born in 2018 in China can be related directly to the “Park Connector Network” model
On the Performances of Estimating Stellar Atmospheric Parameters from CSST Broad-band Photometry
Deriving atmospheric parameters of a large sample of stars is of vital
importance to understand the formation and evolution of the Milky Way.
Photometric surveys, especially those with near-ultraviolet filters, can offer
accurate measurements of stellar parameters, with the precision comparable to
that from low/medium resolution spectroscopy. In this study, we explore the
capability of measuring stellar atmospheric parameters from CSST broad-band
photometry (particularly the near-ultraviolet bands), based on synthetic colors
derived from model spectra. We find that colors from the optical and
near-ultraviolet filter systems adopted by CSST show significant sensitivities
to the stellar atmospheric parameters, especially the metallicity. According to
our mock data tests, the precision of the photometric metallicity is quite
high, with typical values of 0.17 dex and 0.20 dex for dwarf and giant stars,
respectively. The precision of the effective temperature estimated from
broad-band colors are within 50 K.Comment: 16 pages, 18 figures, accepted by Research in Astronomy and
Astrophysic
The Circular Velocity Curve of the Milky Way from 5 to 25 kpc using luminous red giant branch star
We present a sample of 254,882 luminous red giant branch (LRGB) stars
selected from the APOGEE and LAMOST surveys. By combining photometric and
astrometric information from the 2MASS and Gaia surveys, the precise distances
of the sample stars are determined by a supervised machine learning algorithm:
the gradient boosted decision trees. To test the accuracy of the derived
distances, member stars of globular clusters (GCs) and open clusters (OCs) are
used. The tests by cluster member stars show a precision of about 10 per cent
with negligible zero-point offsets, for the derived distances of our sample
stars. The final sample covers a large volume of the Galactic disk(s) and halo
of kpc and kpc. The rotation curve (RC) of the Milky
Way across radius of kpc have been accurately measured
with 54,000 stars of the thin disk population selected from the LRGB
sample. The derived RC shows a weak decline along with a gradient of
km s kpc,
in excellent agreement with the results measured by previous studies. The
circular velocity at the solar position, yielded by our RC, is
km s, again in great consistent
with other independent determinations. From the newly constructed RC, as well
as constraints from other data, we have constructed a mass model for our
Galaxy, yielding a mass of the dark matter halo of =
()10 with a corresponding radius of
= kpc and a local dark matter density of
GeV cm.Comment: 16 pages, 13 figures and 5 tables, accepted by Ap
ExpCLIP: Bridging Text and Facial Expressions via Semantic Alignment
The objective of stylized speech-driven facial animation is to create
animations that encapsulate specific emotional expressions. Existing methods
often depend on pre-established emotional labels or facial expression
templates, which may limit the necessary flexibility for accurately conveying
user intent. In this research, we introduce a technique that enables the
control of arbitrary styles by leveraging natural language as emotion prompts.
This technique presents benefits in terms of both flexibility and
user-friendliness. To realize this objective, we initially construct a
Text-Expression Alignment Dataset (TEAD), wherein each facial expression is
paired with several prompt-like descriptions.We propose an innovative automatic
annotation method, supported by Large Language Models (LLMs), to expedite the
dataset construction, thereby eliminating the substantial expense of manual
annotation. Following this, we utilize TEAD to train a CLIP-based model, termed
ExpCLIP, which encodes text and facial expressions into semantically aligned
style embeddings. The embeddings are subsequently integrated into the facial
animation generator to yield expressive and controllable facial animations.
Given the limited diversity of facial emotions in existing speech-driven facial
animation training data, we further introduce an effective Expression Prompt
Augmentation (EPA) mechanism to enable the animation generator to support
unprecedented richness in style control. Comprehensive experiments illustrate
that our method accomplishes expressive facial animation generation and offers
enhanced flexibility in effectively conveying the desired style
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