370 research outputs found
Improved l1-SPIRiT using 3D walsh transform-based sparsity basis
l1-SPIRiT is a fast magnetic resonance imaging (MRI) method which combines parallel imaging (PI) with compressed sensing (CS) by performing a joint l1-norm and l2-norm optimization procedure. The original l1-SPIRiT method uses two-dimensional (2D) Wavelet transform to exploit the intra-coil data redundancies and a joint sparsity model to exploit the inter-coil data redundancies. In this work, we propose to stack all the coil images into a three-dimensional (3D) matrix, and then a novel 3D Walsh transform-based sparsity basis is applied to simultaneously reduce the intra-coil and inter-coil data redundancies. Both the 2D Wavelet transform-based and the proposed 3D Walsh transform-based sparsity bases were investigated in the l1-SPIRiT method. The experimental results show that the proposed 3D Walsh transform-based l1-SPIRiT method outperformed the original l1-SPIRiT in terms of image quality and computational efficiency
Optimal Control Policies of Pests for Hybrid Dynamical Systems
We improve the traditional integrated pest management (IPM) control strategies and formulate three specific management strategies, which can be described by hybrid dynamical systems. These strategies can not only effectively control pests but also reduce the abuse of pesticides and protect the natural enemies. The aim of this work is to study how the factors, such as natural enemies optimum choice in the two kinds of different pests, timings of natural enemy releases, dosages and timings of insecticide applications, and instantaneous killing rates of pesticides on both pests and natural enemies, can affect the success of IPM control programmes. The results indicate that the pests outbreak period or frequency largely depends on the optimal selective feeding of the natural enemy between one of the pests and the control tactics. Ultimately, we obtain the only pest needs to be controlled below a certain threshold while not supervising pest
An Autonomous Path Planning Method for Unmanned Aerial Vehicle based on A Tangent Intersection and Target Guidance Strategy
Unmanned aerial vehicle (UAV) path planning enables UAVs to avoid obstacles
and reach the target efficiently. To generate high-quality paths without
obstacle collision for UAVs, this paper proposes a novel autonomous path
planning algorithm based on a tangent intersection and target guidance strategy
(APPATT). Guided by a target, the elliptic tangent graph method is used to
generate two sub-paths, one of which is selected based on heuristic rules when
confronting an obstacle. The UAV flies along the selected sub-path and
repeatedly adjusts its flight path to avoid obstacles through this way until
the collision-free path extends to the target. Considering the UAV kinematic
constraints, the cubic B-spline curve is employed to smooth the waypoints for
obtaining a feasible path. Compared with A*, PRM, RRT and VFH, the experimental
results show that APPATT can generate the shortest collision-free path within
0.05 seconds for each instance under static environments. Moreover, compared
with VFH and RRTRW, APPATT can generate satisfactory collision-free paths under
uncertain environments in a nearly real-time manner. It is worth noting that
APPATT has the capability of escaping from simple traps within a reasonable
time
Comprehensive ab initio study of effects of alloying elements on generalized stacking fault energies of Ni and NiAl
Excellent high-temperature mechanical properties of Ni-based single crystal
superalloys (NSCSs) are attributed to the yield strength anomaly of NiAl
that is intimately related to generalized stacking fault energies (GSFEs).
Therefore, clarifying the effects of alloying elements on the GSFEs is of great
significance for alloys design. Here, by means of ab initio density functional
theory calculations, we systematically calculated the GSFEs of different slip
systems of Ni and NiAl without and with alloying elements using the alias
shear method. We obtained that for Ni, except for magnetic elements Mn, Fe, and
Co, most of alloying elements decrease the unstable stacking fault energy
() of the and slip systems
and also decrease the stable stacking fault energy () of the
slip system. For NiAl, most of alloying elements in
groups IIIB-VIIB show a strong Al site preference. Except for Mn and Fe, the
elements in groups VB-VIIB and the first column of group VIII increase the
values of of different slip systems of NiAl. On the other
hand, the elements in groups IIIB-VIIB also increase the value of
. We found that Re is an excellent strengthening alloying element
that significantly increases the slip barrier of the tailing slip process for
Ni, and also enhances the slip barrier of the leading slip process of three
slip systems for NiAl. W and Mo exhibit similar effects as Re. We
predicted that Os, Ru, and Ir are good strengthening alloying elements as well,
since they show the strengthening effects on both the leading and tailing slip
process for Ni and NiAl
Searching for Variable Stars in the Open Cluster NGC 2355 and Its Surrounding Region
We have investigated the variable stars in the field surrounding NGC 2355
based on the time-series photometric observation data. More than 3000 CCD
frames were obtained in the V band spread over 13 nights with the Nanshan
One-meter Wide-field Telescope. We have detected 88 variable stars, containing
72 new variable stars and 16 known variable stars. By analyzing these light
curves, we classified the variable stars as follows: 26 eclipsing binaries, 52
pulsating stars, 4 rotating variables, and 6 unclear type variable stars for
which their periods are much longer than the time baseline chosen. Employing
Gaia DR2 parallax, kinematics, and photometry, the cluster membership of these
variable stars were also analyzed for NGC 2355. In addition to the 11 variable
members reported by Cantat-Gaudin et al. (2018), we identify 4 more variable
member candidates located at the outer region of NGC 2355 and showed
homogeneity in space positions and kinematic properties with the cluster
members. The main physical parameters of NGC 2355 estimated from the two-color
and color-magnitude diagrams are log(age/yr) = 8.9, E(B - V) = 0.24 mag, and
[Fe/H] = - 0.07 dex.Comment: 15 pages, 11 figures. 6 tables,Accepted for publication in A
An Image Enhancement Method for Improving Small Intestinal Villi Clarity
This paper presents, for the first time, an image enhancement methodology
designed to enhance the clarity of small intestinal villi in Wireless Capsule
Endoscopy (WCE) images. This method first separates the low-frequency and
high-frequency components of small intestinal villi images using guided
filtering. Subsequently, an adaptive light gain factor is generated based on
the low-frequency component, and an adaptive gradient gain factor is derived
from the convolution results of the Laplacian operator in different regions of
small intestinal villi images. The obtained light gain factor and gradient gain
factor are then combined to enhance the high-frequency components. Finally, the
enhanced high-frequency component is fused with the original image to achieve
adaptive sharpening of the edges of WCE small intestinal villi images. The
experiments affirm that, compared to established WCE image enhancement methods,
our approach not only accentuates the edge details of WCE small intestine villi
images but also skillfully suppresses noise amplification, thereby preventing
the occurrence of edge overshooting
OccuQuest: Mitigating Occupational Bias for Inclusive Large Language Models
The emergence of large language models (LLMs) has revolutionized natural
language processing tasks. However, existing instruction-tuning datasets suffer
from occupational bias: the majority of data relates to only a few occupations,
which hampers the instruction-tuned LLMs to generate helpful responses to
professional queries from practitioners in specific fields. To mitigate this
issue and promote occupation-inclusive LLMs, we create an instruction-tuning
dataset named \emph{OccuQuest}, which contains 110,000+ prompt-completion pairs
and 30,000+ dialogues covering over 1,000 occupations in 26 occupational
categories. We systematically request ChatGPT, organizing queries
hierarchically based on Occupation, Responsibility, Topic, and Question, to
ensure a comprehensive coverage of occupational specialty inquiries. By
comparing with three commonly used datasets (Dolly, ShareGPT, and WizardLM), we
observe that OccuQuest exhibits a more balanced distribution across
occupations. Furthermore, we assemble three test sets for comprehensive
evaluation, an occu-test set covering 25 occupational categories, an estate set
focusing on real estate, and an occu-quora set containing real-world questions
from Quora. We then fine-tune LLaMA on OccuQuest to obtain OccuLLaMA, which
significantly outperforms state-of-the-art LLaMA variants (Vicuna, Tulu, and
WizardLM) on professional questions in GPT-4 and human evaluations. Notably, on
the occu-quora set, OccuLLaMA reaches a high win rate of 86.4\% against
WizardLM
A Highlight Removal Method for Capsule Endoscopy Images
The images captured by Wireless Capsule Endoscopy (WCE) always exhibit
specular reflections, and removing highlights while preserving the color and
texture in the region remains a challenge. To address this issue, this paper
proposes a highlight removal method for capsule endoscopy images. Firstly, the
confidence and feature terms of the highlight region's edges are computed,
where confidence is obtained by the ratio of known pixels in the RGB space's R
channel to the B channel within a window centered on the highlight region's
edge pixel, and feature terms are acquired by multiplying the gradient vector
of the highlight region's edge pixel with the iso-intensity line. Subsequently,
the confidence and feature terms are assigned different weights and summed to
obtain the priority of all highlight region's edge pixels, and the pixel with
the highest priority is identified. Then, the variance of the highlight
region's edge pixels is used to adjust the size of the sample block window, and
the best-matching block is searched in the known region based on the RGB color
similarity and distance between the sample block and the window centered on the
pixel with the highest priority. Finally, the pixels in the best-matching block
are copied to the highest priority highlight removal region to achieve the goal
of removing the highlight region. Experimental results demonstrate that the
proposed method effectively removes highlights from WCE images, with a lower
coefficient of variation in the highlight removal region compared to the
Crinimisi algorithm and DeepGin method. Additionally, the color and texture in
the highlight removal region are similar to those in the surrounding areas, and
the texture is continuous
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