2,018 research outputs found
Evaluation of Robust Feature Descriptors for Texture Classification
Texture is an important characteristic in real and
synthetic scenes. Texture analysis plays a critical role in inspecting
surfaces and provides important techniques in a variety of
applications. Although several descriptors have been presented to
extract texture features, the development of object recognition is still a
difficult task due to the complex aspects of texture. Recently, many
robust and scaling-invariant image features such as SIFT, SURF and
ORB have been successfully used in image retrieval and object
recognition. In this paper, we have tried to compare the performance
for texture classification using these feature descriptors with k-means
clustering. Different classifiers including K-NN, Naive Bayes, Back
Propagation Neural Network , Decision Tree and Kstar were applied in
three texture image sets - UIUCTex, KTH-TIPS and Brodatz,
respectively. Experimental results reveal SIFTS as the best average
accuracy rate holder in UIUCTex, KTH-TIPS and SURF is
advantaged in Brodatz texture set. BP neuro network works best in the
test set classification among all used classifiers
Evaluation of Robust Feature Descriptors for Texture Classification
Texture is an important characteristic in real and
synthetic scenes. Texture analysis plays a critical role in inspecting
surfaces and provides important techniques in a variety of
applications. Although several descriptors have been presented to
extract texture features, the development of object recognition is still a
difficult task due to the complex aspects of texture. Recently, many
robust and scaling-invariant image features such as SIFT, SURF and
ORB have been successfully used in image retrieval and object
recognition. In this paper, we have tried to compare the performance
for texture classification using these feature descriptors with k-means
clustering. Different classifiers including K-NN, Naive Bayes, Back
Propagation Neural Network , Decision Tree and Kstar were applied in
three texture image sets - UIUCTex, KTH-TIPS and Brodatz,
respectively. Experimental results reveal SIFTS as the best average
accuracy rate holder in UIUCTex, KTH-TIPS and SURF is
advantaged in Brodatz texture set. BP neuro network works best in the
test set classification among all used classifiers
Insights into high temperature pretreatment on cellulase processing of bamboo
Bamboo processing was performed with commercial cellulase. The properties of cellulase and the effect of high temperature pretreatment on cellulase hydrolysis of bamboo were investigated. Results indicated that cellulase hydrolysis performed fast and dramatically within 30 minutes, and then gradually reached its balance. It was found that pretreatment played an active role in cellulase processing, which enhanced the saccharification of bamboo and benefited high-molecular-weight lignin degradation and removal. Additionally, a better performance of bamboo processing was achieved under the cellulase concentration of 15IU in total reaction system of 100 ml at 50°C, pH 4.8, together with the high temperature pretreatment of 120°C for 15 minutes
Improving Code Generation by Dynamic Temperature Sampling
Recently, Large Language Models (LLMs) have shown impressive results in code
generation. However, existing decoding strategies are designed for Natural
Language (NL) generation, overlooking the differences between NL and
programming languages (PL). Due to this oversight, a better decoding strategy
for code generation remains an open question. In this paper, we conduct the
first systematic study to explore a decoding strategy specialized in code
generation. With an analysis of loss distributions of code tokens, we find that
code tokens can be divided into two categories: challenging tokens that are
difficult to predict and confident tokens that can be easily inferred. Among
them, the challenging tokens mainly appear at the beginning of a code block.
Inspired by the above findings, we propose a simple yet effective method:
Adaptive Temperature (AdapT) sampling, which dynamically adjusts the
temperature coefficient when decoding different tokens. We apply a larger
temperature when sampling for challenging tokens, allowing LLMs to explore
diverse choices. We employ a smaller temperature for confident tokens avoiding
the influence of tail randomness noises. We apply AdapT sampling to LLMs with
different sizes and conduct evaluations on two popular datasets. Results show
that AdapT sampling significantly outperforms state-of-the-art decoding
strategy
Ethyl 2-(3,3-dibutylthioureido)-4,5,6,7-tetrahydrobenzo[b]thiophene-3-carboxylate
In the title compound, C20H32N2O2S2, the cyclohexene ring is disordered over two half-boat conformations with occupancy factors of 0.71:0.29. One n-butyl chain is also disordered over two positions with occupancy factors of 0.83:0.17. The molecular conformation is stabilized by an intramolecular N—H⋯O hydrogen bond
Thiamine Deficiency Causes Long-Lasting Neurobehavioral Deficits in Mice
Thiamine deficiency (TD) has detrimental effects on brain health and neurobehavioral development, and it is associated with many aging-related neurological disorders. To facilitate TD-related neuropsychological studies, we generated a TD mouse model by feeding a thiamine-deficient diet for 30 days, followed by re-feeding the control diet for either one week or 16 weeks as recovery treatment. We then performed neurobehavioral tests in these two cohorts: cohort of one week post TD treatment (1 wk-PTDT) and 16 weeks post TD treatment (16 wks-PTDT). The TD mice showed no significant difference from control in any tests in the 1 wk-PTDT cohort at the age of 13–14 weeks. The tests for the 16 wks-PTDT cohort at the age of 28–29 weeks, however, demonstrated anxiety and reduced locomotion in TD animals in open field and elevated plus maze. In comparison, rotor rod and water maze revealed no differences between TD and control mice. The current findings of the differential effects of the same TD treatment on locomotion and anxiety at different ages may reflect the progressive and moderate change of TD-induced neurobehavioral effects. The study suggests that, even though the immediate neurobehavioral impact of TD is modest or negligible at a young age, the impact could develop and become severe during the aging process
Protecting Entanglement of Two V-type Atoms in Dissipative Cavity by Dipole-Dipole Interaction
In this work, we study a coupled system of two V-type atoms interacting with
a dissipative single-mode cavity, which couples with an external environment.
Firstly, in order to diagonalize Hamiltonian of dissipative cavity, we
introduce a set of new creation and annihilation operators according to theorem
Fano. Then, we obtain the analytical solution of this model by solving the time
dependent Schrodinger equation. We also discuss in detail the influences of the
cavity-environment coupling, the SGI parameter, the initial state and the
dipole-dipole interaction between the two atoms on entanglement dynamics. The
results show that, with the SGI parameter increasing, the entanglement will
decay quicker for the initially maximal entangled state but it will decay
slower for the initially partial entangled state. For the initially product
state, the larger the SGI parameter, the more entanglement will be generated.
The strong coupling can protect entanglement to some extent, but the
dipole-dipole interaction can significantly protect entanglement. Moreover, the
dipole-dipole interaction can not only generate entanglement very effectively,
but also enhance the regulation effect of {\theta} on entanglement for the
initially partial entangled and product states.Comment: 10 pages, 9 figure
Effects of Tai Chi on telomerase activity and gerotranscendence in middle aged and elderly adults in Chinese society
AbstractIntroductionTelomeres are DNA protein structures at the end of chromosomes and are linked to the physical aging process. The improvement of quality of life is closely associated with aerobic exercise, and the dynamic effects of exercise on physiology and psychology are evident with aging. Tai Chi is popularly practiced in China. However, findings on the effects of Tai Chi on telomerase activity (TA) in peripheral blood mononuclear cells, and gerotranscendence (GT), as well as the association of TA and GT with Tai Chi, have been inconsistent.PurposeThis study aims to assess TA in peripheral blood mononuclear cells, GT, and the associations between them. The associations among these variables are determined during six months of Tai Chi intervention among Chinese middle aged and elderly adults.MethodsTA assessment was obtained by TE-ELISA (human telomerase–enzyme linked immunosorbent assay), and GT was measured at the baseline level after six months of Tai Chi intervention.ResultsTA increased significantly in the Tai Chi group from 23.75 ± 3.78 u/mmol (pre-intervention) to 26.31 ± 2.93 u/mmol (after 6 months) (p < 0.05). Compared with the TA in the control group, the TA in the intervention group was statistically significant after six months (p < 0.05). Compared with the GT in the control group, the GT in the intervention group improved significantly after six months (p < 0.05). TA and GT had a positive correlation (r = 0.325, p < 0.01).ConclusionOur data illustrated that Tai Chi had a protective effect on TA and might improve the GT in Chinese middle aged and elderly adults. The TA increased with the increasing GT in Chinese middle aged and elderly adults
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