Wyniki wyszukiwania - BazTech

1

Bounds of the effective elastic moduli of nanoparticle-reinforced composites based on composite sphere assemblage and interface stress model

Tang Z., Ye W.

Archives of Mechanics

|

2022

|

Vol. 74, nr 4

283--317

EN

Three different approaches are formulated to obtain the bounds of the effective elastic moduli of nanoparticle-reinforced composites based on the CSA and the interface stress model. It is found that the effective bulk modulus can be obtained by all three different approaches but the effective shear modulus can be obtained only by the energy approach. The bounds of the effective bulk modulus coincide and depend only on the interface bulk modulus, while those of the effective shear modulus are distinct and depend on two interface elastic constants. Furthermore, limit analysis discloses that the bounds of the effective bulk modulus of nanoparticles coincide but deviate from the bulk modulus of particle in the classical case, and the bounds of the effective shear modulus are distinct in contrast to the effective bulk modulus of nanoparticles or both effective moduli of conventional composites.

2

Object detection based on deep learning for urine sediment examination

Liang Y., Tang Z., Yan M., Liu J.

Biocybernetics and Biomedical Engineering

|

2018

|

Vol. 38, no. 3

661--670

EN

Urine sediment examination (USE) is an important topic in kidney disease analysis and it is often the prerequisite for subsequent diagnostic procedures. We propose DFPN(Feature Pyramid Network with DenseNet) method to overcome the problem of class confusion in the USE images that it is hard to be solved by baseline model which is the state-of-the-art object detection model FPN with RoIAlign pooling. We explored the importance of two parts of baseline model for the USE cell detection. First, adding attention module in the network head, and the class-specific attention module has improved mAP by 0.7 points with pretrained ImageNet model and 1.4 points with pre-trained COCO model. Next, we introduced DenseNet to the baseline model(DFPN) for cell detection in USE, so that the input of the network's head own multiple levels of semantic information, compared to the baseline model only has high-level semantic information. DFPN achieves top result with a mAP of 86.9% on USE test set after balancing between the classification loss and bounding-box regression loss, which improve 5.6 points compared to baseline model, and especially erythrocyte's AP is greatly improved from 65.4% to 93.8%, indicating class confusion has been basically resolved. And we also explore the impacts of training schedule and pretrained model. Our method is promising for the development of automated USE.

3

Technologia wytwarzania i pomiary absorpcji szkieł chalkogenidkowych domieszkowanych jonami ziem rzadkich

Sójka Ł., Bereś-Pawlik E., Tang Z., Furniss D., Seddon A. B., Benson T. M., Sujecki S.

Elektronika : konstrukcje, technologie, zastosowania

|

2012

|

Vol. 53, nr 11

64-66

PL

Szkła chalkogenidkowe charakteryzują się niską energią fononów dlatego też są obiecującym materiałem dla realizacji światłowodów na zakres średniej podczerwieni. W pracy przedstawiono technologię wykonania szkieł chalkogenidkowych (Ge₁₆.₅ As₁₆Ga3Se₆.₅) domieszkowanych jonami ziem rzadkich (Dy³⁺, Tb³⁺, Pr³⁺). Wyniki eksperymentalne absorpcji otrzymano za pomocą spektroskopii furierowskiej w zakresie podczewieni (ang. FTIR). Podstawowe parametry domieszkowanych szkieł chalkogenidkowych takie jak: promieniste czasy życia poziomów energetycznych oraz współczynniki rozgałęzienia luminescencji beta obliczono metodą Judda- Ofelta. Na podstawie otrzymanych wyników omówiono wpływ linii bazowej na błędy metody pomiarowej. Na podstawie otrzymanych wyników zaprezentowano zastosowanie szkieł chalkogenidkowych do realizacji laserów światłowodowych na zakres średniej podczerwieni.

EN

One of the promising materials for the construction of mid-infrared fiber lasers is the chalcogenide glass. The chalcogenide glass has low phonon energy (below 400 cm⁻¹) when compared with standard materials used to produce fiber lasers, i.e. ZBLAN and silica glass.We present a comprehensive study of chalcogenide glass fiber lasers doped with Dy³⁺, Pr³⁺ or Tb³⁺ that operate in the mid-infrared wavelength range. A set of chalcogenide glass samples doped with different concentrations of rare earth ions was fabricated. The modeling parameters are directly extracted from FTIR absorption measurements performed on the fabricated bulk glass samples using Judd-Ofelt theory. Results show that, for all the dopants considered, an efficient mid-infrared laser action is possible if optical losses are kept at the level of 1dB/m or below.

4

Structural Feature-Based Image Hashing and Similarity Metric for Tampering Detection

Tang Z., Wang S., Zhang X., Wei W.

Fundamenta Informaticae

|

2011

|

Vol. 106, nr 1

75-91

EN

Structural image features are exploited to construct perceptual image hashes in this work. The image is first preprocessed and divided into overlapped blocks. Correlation between each image block and a reference pattern is calculated. The intermediate hash is obtained from the correlation coefficients. These coefficients are finally mapped to the interval [0, 100], and scrambled to generate the hash sequence. A key component of the hashingmethod is a specially defined similarity metric to measure the "distance" between hashes. This similarity metric is sensitive to visually unacceptable alterations in small regions of the image, enabling the detection of small area tampering in the image. The hash is robust against content-preserving processing such as JPEG compression, moderate noise contamination, watermark embedding, re-scaling, brightness and contrast adjustment, and low-pass filtering. It has very low collision probability. Experiments are conducted to show performance of the proposed method.