85 research outputs found
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New advances in aircraft MRO services: data mining enhancement
Aircraft Maintenance, Repair and Overhaul (MRO) agencies rely largely on row-data based quotation systems to select the best suppliers for the customers (airlines). The data quantity and quality becomes a key issue to determining the success of an MRO job, since we need to ensure we achieve cost and quality benchmarks. This paper introduces a data mining approach to create an MRO quotation system that enhances the data quantity and data quality, and enables significantly more precise MRO job quotations.
Regular Expression was utilized to analyse descriptive textual feedback (i.e. engineer’s reports) in order to extract more referable highly normalised data for job quotation. A text mining based key influencer analysis function enables the user to proactively select sub-parts, defects and possible solutions to make queries more accurate. Implementation results show that system data would improve cost quotation in 40% of MRO jobs, would reduce service cost without causing a drop in service quality
Determination of the Ignorable Boundary Condition and Standard Sample for A Novel in-situ Dynamic Mechanical Analysis Method on Soft Matter
An in-situ Dynamic Mechanical Analysis (DMA) method for soft matter developed
by our group [Wu. et.al. 2022] encounters the problem of irregular samples,
which significantly vary in shape and size in practice, therefore a standard
sample "large enough" to ignore the boundary and size effects is necessary to
determine the baseline of test and build the correspondence between this new
method to classical mechanical tests. In this work, we use finite element
analysis to approach the optimal size of a brick sample where the stress on the
boundaries in three spatial directions are ignorable, and certified the results
by testing a series of silicone gel samples on the in-situ DMA device. The
stress-strain of tensile and compression are characterized. The material
properties of gel are chosen to be close to the biological soft tissue. The
size of 40mm(L)*40mm(W)*20mm(H) is determined to be the optimal result.Comment: 7 pages, 7 figure
A Brief Review and Perspective on the Functional Biodegradable Films for Food Packaging
High-performance, environmentally-friendly biodegradable packaging as
substitutes for conventional plastics becomes severe demand to nowadays economy
and society. As an aliphatic aromatic copolyester PBAT is recognized as the
preferred alternative to traditional plastics. However, the relatively high
cost and weak properties obstacles the widespread adoption of PBAT.
Modification pertaining to improve the properties, lower the cost, and include
the functional additives of PBAT is a continuous effort to meet the needs of
food accessibility, antibacterial properties, oxygen resistance, high
mechanical strength, stable size, low moisture absorption, and various gas
permeability for commercial competitiveness
Dilated Convolution based CSI Feedback Compression for Massive MIMO Systems
Although the frequency-division duplex (FDD) massive multiple-input
multiple-output (MIMO) system can offer high spectral and energy efficiency, it
requires to feedback the downlink channel state information (CSI) from users to
the base station (BS), in order to fulfill the precoding design at the BS.
However, the large dimension of CSI matrices in the massive MIMO system makes
the CSI feedback very challenging, and it is urgent to compress the feedback
CSI. To this end, this paper proposes a novel dilated convolution based CSI
feedback network, namely DCRNet. Specifically, the dilated convolutions are
used to enhance the receptive field (RF) of the proposed DCRNet without
increasing the convolution size. Moreover, advanced encoder and decoder blocks
are designed to improve the reconstruction performance and reduce computational
complexity as well. Numerical results are presented to show the superiority of
the proposed DCRNet over the conventional networks. In particular, the proposed
DCRNet can achieve almost the state-of-the-arts (SOTA) performance with much
lower floating point operations (FLOPs). The open source code and checkpoint of
this work are available at https://github.com/recusant7/DCRNet.Comment: This work has been submitted to the IEEE for possible publication.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
Contrastive Learning based Semantic Communication for Wireless Image Transmission
Recently, semantic communication has been widely applied in wireless image
transmission systems as it can prioritize the preservation of meaningful
semantic information in images over the accuracy of transmitted symbols,
leading to improved communication efficiency. However, existing semantic
communication approaches still face limitations in achieving considerable
inference performance in downstream AI tasks like image recognition, or
balancing the inference performance with the quality of the reconstructed image
at the receiver. Therefore, this paper proposes a contrastive learning
(CL)-based semantic communication approach to overcome these limitations.
Specifically, we regard the image corruption during transmission as a form of
data augmentation in CL and leverage CL to reduce the semantic distance between
the original and the corrupted reconstruction while maintaining the semantic
distance among irrelevant images for better discrimination in downstream tasks.
Moreover, we design a two-stage training procedure and the corresponding loss
functions for jointly optimizing the semantic encoder and decoder to achieve a
good trade-off between the performance of image recognition in the downstream
task and reconstructed quality. Simulations are finally conducted to
demonstrate the superiority of the proposed method over the competitive
approaches. In particular, the proposed method can achieve up to 56\% accuracy
gain on the CIFAR10 dataset when the bandwidth compression ratio is 1/48
Caching UAV-enabled small-cell networks
Unmanned aerial vehicles (UAVs) can be utilized to provide flexible wireless access in future wireless networks, with larger coverage and higher transmission rate. However, the wireless backhaul for UAVs is usually capacity-limited and congested, and UAVs cannot operate for a long time due to the limited battery life. In this paper, a framework of caching UAV-enabled small-cell networks is proposed, to offload data traffic for the small-cell base stations via caching. In the proposed scheme, the most popular contents are stored at the local caches of UAVs in advance, which can be delivered to mobile users directly from the caches when required. Thus, the congestion of wireless backhaul can be alleviated, the energy consumption can be reduced, and the quality of experience can be improved
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Global land surface temperature influenced by vegetation cover and PM2.5 from 2001 to 2016
Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 �g/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72�N and 48�S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature
Biocontrol of Sugarcane Smut Disease by Interference of Fungal Sexual Mating and Hyphal Growth Using a Bacterial Isolate
Sugarcane smut is a fungal disease caused by Sporisorium scitamineum, which can cause severe economic losses in sugarcane industry. The infection depends on the mating of bipolar sporida to form a dikaryon and develops into hyphae to penetrate the meristematic tissue of sugarcane. In this study, we set to isolate bacterial strains capable of blocking the fungal mating and evaluate their potential in control of sugarcane smut disease. A bacterial isolate ST4 from rhizosphere displayed potent inhibitory activity against the mating of S. scitamineum bipolar sporida and was selected for further study. Phylogenetic analyses and biochemical characterization showed that the isolate was most similar to Pseudomonas guariconensis. Methanol extracts from minimum and potato dextrose agar (PDA) agar medium, on which strain ST4 has grown, showed strong inhibitory activity on the sexual mating of S. scitamineum sporida, without killing the haploid cells MAT-1 or MAT-2. Further analysis showed that only glucose, but not sucrose, maltose, and fructose, could support strain ST4 to produce antagonistic chemicals. Consistent with the above findings, greenhouse trials showed that addition of 2% glucose to the bacterial inoculum significantly increased the strain ST4 biocontrol efficiency against sugarcane smut disease by 77% than the inoculum without glucose. The results from this study depict a new strategy to screen for biocontrol agents for control and prevention of the sugarcane smut disease
The role of tripartite motif-containing 28 in cancer progression and its therapeutic potentials
Tripartite motif-containing 28 (TRIM28) belongs to tripartite motif (TRIM) family. TRIM28 not only binds and degrades its downstream target, but also acts as a transcription co-factor to inhibit gene expression. More and more studies have shown that TRIM28 plays a vital role in tumor genesis and progression. Here, we reviewed the role of TRIM28 in tumor proliferation, migration, invasion and cell death. Moreover, we also summarized the important role of TRIM28 in tumor stemness sustainability and immune regulation. Because of the importance of TRIM28 in tumors, TIRM28 may be a candidate target for anti-tumor therapy and play an important role in tumor diagnosis and treatment in the future
A Search for Light Super Symmetric Baryons
We have searched for the production and decay of light super-symmetric
baryons produced in 800 GeV/c proton copper interactions in a charged hyperon
beam experiment. We observe no evidence for the decays R+(uud \g^~) -> S(uds
\g^~) pi+ and X-(ssd \g^~) -> S(uds \g^~) pi- in the predicted parent mass and
lifetime ranges of 1700-2500 Mev/c2 and 50-500 ps. Production upper limits for
R+ at xF=0.47, Pt=1.4 GeV/c2 and X- at xF=0.48, Pt=0.65 GeV/c2 of less than
10^-3 of all charged secondary particles produced are obtained for all but the
highest masses and shortest lifetimes predicted.Comment: 9 pages, uuencoded postscript 4 figures uuencoded, tar-compressed
file (submitted to PRL
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