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Kuo-chin Fan

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Canadian University of Dubai

School of the Art Institute of Chicago

Aswani Kumar Cherukuri

VIT University

University of Oxford

Graduate Center of the City University of New York

Universidad Nacional de Educación a Distancia

Chien-Ming Yang

National Cheng Chi University

North Maharashtra University

Ferhat Ozgur Catak

TUBITAK

Istanbul Şehir University

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Papers by Kuo-chin Fan

Lossless Data Hiding of Color Images Using Pixel Decomposition and Phase Difference

Journal of Information Science and Engineering, Sep 1, 2007

Recently, the use of data hiding in hiding annotations, confidential data, or side information in... more Recently, the use of data hiding in hiding annotations, confidential data, or side information into multimedia attracts the attention of researchers in various fields, especially in digital library. One of the essential tasks in digital library is the digitization of arts together with the corresponding textural descriptions. Although there are some standard interleaving algorithms for hiding the relating textural description into an image or video, the textural information is still prone to be accessed and extracted by hackers. Most of the traditional data hiding schemes focus on the recovery of covert information. The common shortcoming is that the original image will be distorted due to the processing of bit-substitution, quantization and truncation. In this paper, three novel data hiding methods are proposed. The first two methods are implemented based on pair-wise logical computation (PWLC) and pixel decomposition by treating R, G, B bands and the intensity component as spatial domains and the third method is implemented by considering and utilizing the phase difference information in the hue and saturation components in the HSI color system. All of the three methods can achieve the goals of complete recovering of covert information and lossless reconstruction of original image simultaneously. In addition, it also obtains high data hiding capacity and good visual quality. Experimental results demonstrate the feasibility and validity of our proposed method in the data hiding of color images.

The Off-Design Performance Simulation of Marine Gas Turbine Based on Optimum Scheduling of Variable Stator Vanes

Mathematical Problems in Engineering, 2017

As one of the antisurge techniques, the adjusting scheme of VSV under off-design conditions has a... more As one of the antisurge techniques, the adjusting scheme of VSV under off-design conditions has a significant impact on the performance of gas turbines. In this paper, the one-dimensional characteristic of the compressor calculation program is embedded into the zero-dimensional overall gas turbine model, which replaces the original compressor characteristic module. Based on the assembling relationship of the actual components of the marine gas turbine, the architecture of the modular model library is designed, and an integrated simulation platform of marine gas turbine is developed by using MATLAB/GUI software. The influence of the first 3 rows of variable stator vanes of the 9-stage axial compressor working alone on the performance of the compressor at different speeds and different angles was analyzed by the HARIKA compressor characteristic calculation program. Taking the economics and stability of the gas turbine as the optimization objective, the optimization of the first three-stage stator vanes regulation schemes under different working conditions was carried out. The steady-state performance parameters under each working condition of gas turbine of power generation with or without variable stator vane mode were calculated. The study results can provide references for the adjusting scheme of VSV under gas turbine off-design conditions operating process.

Motion-embedded residual error for packet loss recovery of video transmission and encryption

Proceedings of SPIE, Jan 15, 2006

Traditional cryptographic encryption can achieve provable security but is unfortunately sensitive... more Traditional cryptographic encryption can achieve provable security but is unfortunately sensitive to a single bit error, which will cause an unreliable packet to be dropped to create packet loss. In order to achieve robust media encryption, error resilience in media encryption can be treated to be equivalent to error resilience in media transmission. This study proposes an embedded block hash searching scheme at the decoder side to achieve motion estimation and recover the lost packets, while maintaining format compliance and cryptographic provable security. It is important to note that the proposed framework is a kind of joint error-resilient video transmission/encryption and copyright protection.

Label Consistency Loss for Multi-label Decoding in Named Entity Recognition

Research Square (Research Square), May 8, 2023

Named entity recognition (NER) has beed studied well recent years. However, the diversity problem... more Named entity recognition (NER) has beed studied well recent years. However, the diversity problem that arises while multiple labels are decoded into entities has been ignored in most studies. Concretely, in the process of decoding labels into entities, the same label prediction accuracy may lead to different entity prediction accuracy. This paper propose label consistency loss (LCL) to address the multilabel decoding diversity problem while considering the global label prediction accuracy. Specifically, the proposed method consists of two loss functions: global loss function and entity loss function. The global loss function is dedicated to improve the global label prediction accuracy by calculating the global error between predicted labels and gold labels. Entity loss is dedicated to solve the diversity problem by achieving labels in same entity are in the same prediction score distribution. To verify the effectiveness of LCL, this paper propose L2E metric which denote the conversion rate of labels to entities. Apply LCL to baseline and conduct experiments on two datasets. The experiment results show the F1 performance of baseline is improved by 1.16% percent and 0.17% percent, the L2E is improved by 1.52% and 0.03% on two datasets.

Colour image segmentation in various illumination circumstances

International Conference on Circuits, systems, electronics, control & signal processing, Dec 29, 2010

We propose a novel colour segmentation algorithm can work in various illumination circumstances. ... more We propose a novel colour segmentation algorithm can work in various illumination circumstances. The proposed colour segmentation algorithm operates directly on RGB colour space without the need of colour space transformation and it is very robust to various illumination conditions. Our approach can be employed in various domains (e.g., human skin colour segmentation, the maturity of tomatoes). Furthermore, our approach has the benefits of being insensitive to rotation, scaling, and translation. In addition, the system can be applied to different applications, for example, colour segmentation for fruits (vegetables) quality control by merely changing the values of the parameters (α, β1, β2, γ1, γ2). Experimental results demonstrate the practicability of our proposed approach in colour segmentation.

Adaptive Shadow Compensation for Face Recognition Under Illumination Variations

Robust face recognition under variant illumination conditions is a challenging research problem. ... more Robust face recognition under variant illumination conditions is a challenging research problem. In this paper, a new shadow compensation method, called adaptive shadow compensation (ASC), will be proposed to eliminate shadows in the face image due to non-frontal lighting directions. ASC performs shadow compensation in each local region, based on Fourier analysis on each local image block, to remove as much shadows as possible. Null-space linear discriminant analysis is then employed to extract discriminant features from ASC compensated images. Experimental results on the Yale B face database show that the proposed ASC method can achieve high face recognition accuracy under illumination variations.

Investigation on Temperature Rise Characteristic and Load Capacity of Amorphous Alloy Vegetable Oil Distribution Transformers with 3D Coupled-Field Method

Machines, Jan 17, 2022

The large differences in the load peak and valley of rural distribution networks always bring sev... more The large differences in the load peak and valley of rural distribution networks always bring severe problems to system planners and operators. Given this issue, this paper deals with the hot-spot temperature (HST) of the transformer and its overload capability, and proposes a modeling method-based online monitoring of practical parameters. In the current work, a temperature-fluid coupling field of the 315 kVA vegetable oil distribution transformer is developed in both the twodimensional and three-dimensional geometry, by which the convection and heat dissipation process can be studied. The grid of the model is divided into regions to increase the calculation speed and ensure the accuracy of the calculation. Secondly, tests related to the temperature rise of the transformer are carried out. The accuracy of the three-dimensional model is later discussed in terms of temperature and fluid velocity distribution. Finally, the temperature distribution laws of the amorphous alloy vegetable oil distribution transformers (AVDT) are compared and analyzed under different load conditions. Findings reveal that the AVDT has low no-load loss and strong overload capacity, which is capable of reducing the internal overheating accidents of the transformer.

Fall Detection in Dusky Environment

Lecture notes in electrical engineering, Nov 13, 2013

Accidental fall is the most prominent factor that causes the accidental death of elder people due... more Accidental fall is the most prominent factor that causes the accidental death of elder people due to their slow body reaction. Automatic fall detection technology integrated in a health-care system can assist human monitoring the occurrence of fall, especially in dusky environments. In this paper, a novel fall detection system focusing mainly on dusky environments is proposed. In dusky environments, the silhouette images of human bodies extracted from conventional CCD cameras are usually imperfect due to the abrupt change of illumination. Thus, our work adopts a thermal imager to detect human bodies. The proposed approach adopts a coarse-to-fine strategy. Firstly, the downward optical flow features are extracted from the thermal images to identify fall-like actions in the coarse stage. The horizontal projection of motion history images (MHI) extracted from fall-like actions are then designed to verify the incident by the proposed nearest neighbor feature line embedding (NNFLE) in the fine stage. Experimental results demonstrate that the proposed method can distinguish the fall incidents with high accuracy even in dusky environments and overlapping situations.

A significant motion vector protection-based error-resilient scheme in H.264

This paper proposes a significant motion vector protection (SMVP) scheme for error-resilient tran... more This paper proposes a significant motion vector protection (SMVP) scheme for error-resilient transmission of videos. In terms of a rate-distortion optimization model, we show how to determine the significant motion vectors (SMVs) and how much rate space should be preserved to store SMVs. The idea behind our method is to give more protection to significant data. As a result, our method can be regarded as a kind of unequal error protection mechanisms. In comparison with the conventional forward error correction (FEC) and error concealment methods, experimental results demonstrate the effectiveness of the proposed method. In particularly, our method shows its superiority under the situation of higher packet loss rates.

A Novel Spectral Clustering Method Based on Pairwise Distance Matrix

Journal of Information Science and Engineering, Mar 1, 2010

In general, the similarity measure is indispensable for most traditional spectral clustering algo... more In general, the similarity measure is indispensable for most traditional spectral clustering algorithms since these algorithms typically begin with the pairwise similarity matrix of a given dataset. However, a general type of input for most clustering applications is the pairwise distance matrix. In this paper, we propose a distance-based spectral clustering method which makes no assumption on regarding both the suitable similarity measure and the prior-knowledge of cluster number. The kernel of distance-based spectral clustering is that the symmetric LoG weighted matrix constructed by applying the Laplace operator to the pairwise distance matrix. The main difference from the traditional spectral clustering is that the pairwise distance matrix can be directly employed without transformation as a similarity pairwise matrix in advance. Moreover, the inter-cluster structure is embedded and the intra-cluster pairwise relationships are maximized in the proposed method to increase the discrimination capability on extracting clusters. Experiments were conducted on different types of test datasets and the results demonstrate the correctness of the extracted clusters. Furthermore, the proposed method is also verified to be robust to noisy datasets.

Radar High-Resolution Range Profile Ship Recognition Using Two-Channel Convolutional Neural Networks Concatenated with Bidirectional Long Short-Term Memory

Remote Sensing, Mar 26, 2021

Radar automatic target recognition is a critical research topic in radar signal processing. Radar... more Radar automatic target recognition is a critical research topic in radar signal processing. Radar high-resolution range profiles (HRRPs) describe the radar characteristics of a target, that is, the characteristics of the target that is reflected by the microwave emitted by the radar are implicit in it. In conventional radar HRRP target recognition methods, prior knowledge of the radar is necessary for target recognition. The application of deep-learning methods in HRRPs began in recent years, and most of them are convolutional neural network (CNN) and its variants, and recurrent neural network (RNN) and the combination of RNN and CNN are relatively rarely used. The continuous pulses emitted by the radar hit the ship target, and the received HRRPs of the reflected wave seem to provide the geometric characteristics of the ship target structure. When the radar pulses are transmitted to the ship, different positions on the ship have different structures, so each range cell of the echo reflected in the HRRP will be different, and adjacent structures should also have continuous relational characteristics. This inspired the authors to propose a model to concatenate the features extracted by the two-channel CNN with bidirectional long short-term memory (BiLSTM). Various filters are used in two-channel CNN to extract deep features and fed into the following BiLSTM. The BiLSTM model can effectively capture long-distance dependence, because BiLSTM can be trained to retain critical information and achieve two-way timing dependence. Therefore, the two-way spatial relationship between adjacent range cells can be used to obtain excellent recognition performance. The experimental results revealed that the proposed method is robust and effective for ship recognition.

A Dimension Reduction Framework for HSI Classification Using Fuzzy and Kernel NFLE Transformation

Remote Sensing, Oct 29, 2015

In this paper, a general nearest feature line (NFL) embedding (NFLE) transformation called fuzzy-... more In this paper, a general nearest feature line (NFL) embedding (NFLE) transformation called fuzzy-kernel NFLE (FKNFLE) is proposed for hyperspectral image (HSI) classification in which kernelization and fuzzification are simultaneously considered. Though NFLE has successfully demonstrated its discriminative capability, the non-linear manifold structure cannot be structured more efficiently by linear scatters using the linear NFLE method. According to the proposed scheme, samples were projected into a kernel space and assigned larger weights based on that of their neighbors. The within-class and between-class scatters were calculated using the fuzzy weights, and the best transformation was obtained by maximizing the Fisher criterion in the kernel space. In that way, the kernelized manifold learning preserved the local manifold structure in a Hilbert space as well as the locality of the manifold structure in the reduced low-dimensional space. The proposed method was compared with various state-of-the-art methods to evaluate the performance using three benchmark data sets. Based on the experimental results: the proposed FKNFLE outperformed the other, more conventional methods.

Feature Line Embedding Based on Support Vector Machine for Hyperspectral Image Classification

Remote Sensing, 2021

In this paper, a novel feature line embedding (FLE) algorithm based on support vector machine (SV... more In this paper, a novel feature line embedding (FLE) algorithm based on support vector machine (SVM), referred to as SVMFLE, is proposed for dimension reduction (DR) and for improving the performance of the generative adversarial network (GAN) in hyperspectral image (HSI) classification. The GAN has successfully shown high discriminative capability in many applications. However, owing to the traditional linear-based principal component analysis (PCA) the pre-processing step in the GAN cannot effectively obtain nonlinear information; to overcome this problem, feature line embedding based on support vector machine (SVMFLE) was proposed. The proposed SVMFLE DR scheme is implemented through two stages. In the first scatter matrix calculation stage, FLE withinclass scatter matrix, FLE between-scatter matrix, and support vector-based FLE between-class scatter matrix are obtained. Then in the second weight determination stage, the training sample dispersion indices versus the weight of SVM-based FLE between-class matrix are calculated to determine the best weight between-scatter matrices and obtain the final transformation matrix. Since the reduced feature space obtained by the SVMFLE scheme is much more representative and discriminative than that obtained using conventional schemes, the performance of the GAN in HSI classification is higher. The effectiveness of the proposed SVMFLE scheme with GAN or nearest neighbor (NN) classifiers was evaluated by comparing them with state-of-the-art methods and using three benchmark datasets. According to the experimental results, the performance of the proposed SVMFLE scheme with GAN or NN classifiers was higher than that of the state-of-the-art schemes in three performance indices. Accuracies of 96.3%, 89.2%, and 87.0% were obtained for the Salinas, Pavia University, and Indian Pines Site datasets, respectively. Similarly, this scheme with the NN classifier also achieves 89.8%, 86.0%, and 76.2% accuracy rates for these three datasets.

Inhibitory Effect of Acer truncatum Bunge Seed Coat Extract on Fatty Acid Synthase, Differentiation and Lipid Accumulation in 3T3-L1 Adipocytes

Molecules, Feb 16, 2022

Acer truncatum Bunge is now widely cultivated throughout the world. Fatty acid synthase (FAS) is ... more Acer truncatum Bunge is now widely cultivated throughout the world. Fatty acid synthase (FAS) is a potential target in the treatment of both obesity and cancer. Only a few FAS inhibitors have been reported. In this study, the inhibitory effect of A. truncatum seed coat (ESA) on FAS and the inhibition mechanisms were investigated using a FAS activity assay and an enzyme kinetics study. The main chemicals of ESA were analyzed with UPLC-MS/MS. The effects of ESA on 3T3-L1 adipocyte differentiation and lipid accumulation were investigated using Oil red O staining. We first identified seven main compounds (quinic acid, malic acid, gentisic acid, procyanidin dimer, procyanidin trimer, catechin, and quercetin) from 50% ethanol extracts of seed coats of A. truncatum (ESAs), which were then found to inhibit 3T3-L1 adipocyte differentiation at the concentration of 50 µg/mL. ESA obviously reduced the visible triglyceride droplets accumulation, and dramatically decreased the number of the adipocytes at a comparatively high concentration. It is suggested that the effects are due to the inhibition of FAS by ESA; FAS activity is inhibited by ESA at a half inhibition concentration (IC 50 ) of 0.57 µg/mL, which is lower than that of classically known FAS inhibitors. Meanwhile, ESA displayed different inhibition kinetics and reacting sites for FAS. These results provide new clues for the development of novel products for obesity treatment and a scientific basis for the full use of byproducts for future industrial production of vegetable oil.

Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images

Sensors, Dec 12, 2015

In this paper, we present a reliable and robust biometric verification method based on bimodal ph... more In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods.

Ambient-pressure hydrogenation of CO2 into long-chain olefins

Nature Communications, May 3, 2022

The conversion of CO 2 by renewable power-generated hydrogen is a promising approach to a sustain... more The conversion of CO 2 by renewable power-generated hydrogen is a promising approach to a sustainable production of long-chain olefins (C 4+ = ) which are currently produced from petroleum resources. The decentralized small-scale electrolysis for hydrogen generation requires the operation of CO 2 hydrogenation in ambient-pressure units to match the manufacturing scales and flexible on-demand production. Herein, we report a Cu-Fe catalyst which is operated under ambient pressure with comparable C 4+ = selectivity (66.9%) to that of the state-of-the-art catalysts (66.8%) optimized under high pressure (35 bar). The catalyst is composed of copper, iron oxides, and iron carbides. Iron oxides enable reverse-watergas-shift to produce CO. The synergy of carbide path over iron carbides and CO insertion path over interfacial sites between copper and iron carbides leads to efficient C-C coupling into C 4+ = . This work contributes to the development of small-scale low-pressure devices for CO 2 hydrogenation compatible with sustainable hydrogen production.

High quantum oscillation frequencies and nontrivial topology in kagome superconductor KV3Sb5 probed by torque magnetometry up to 45 T

Physical Review B

Here, we present the Fermi surface properties of the kagome superconductor KV 3 Sb 5 using torque... more Here, we present the Fermi surface properties of the kagome superconductor KV 3 Sb 5 using torque magnetometry at applied fields up to 45 T and temperatures down to that of liquid 3 He (0.32 K). The torque signal shows clear de Haas-van Alphen (dHvA) oscillations with 14 major frequencies ranging from ∼33 to 2149 T, nine of which are higher frequencies (above 500 T) that have never been reported in KV 3 Sb 5 . Angular dependence measurements of the dHvA oscillations were carried out to investigate the dimensionality of the Fermi surface. Based on our analysis, several frequencies follow the 1/cos θ dependence, where θ is the tilt angle with respect to the applied field direction and oscillations disappear above θ = 60 • , which suggest that Fermi surfaces corresponding to these frequencies are quasitwo dimensional. The Berry phase ( B ), determined by constructing a Landau level fan diagram, was found to be B ∼ π , which strongly suggests the nontrivial topology of KV 3 Sb 5 . To explain the experimental results, we carried out band-structure and Fermi-surface calculations using density functional theory (DFT) for both pristine and charge-density wave (CDW) phases. We found that the Fermi surface undergoes severe reconstruction in the CDW phase and, more importantly, our calculation results are in reasonable agreement with the experimentally measured Fermi-surface frequencies. The observation in this paper of very high quantum oscillation frequencies in KV 3 Sb 5 and the determination of their detailed Fermi-surface properties, along with the analyses of corresponding DFT calculation results, are crucial for understanding CDW order, unconventional superconductivity, and nontrivial topology in AV 3 Sb 5 (A = K, Rb, and Cs), as well as the interplay among them.

Two new antimicrobial monoterpenoid indole alkaloids from the roots of Rauvolfia yunnanensis

Journal of Asian Natural Products Research

The Measurement of PSF Ellipticity of an Unobstructed Off-Axis Space Telescope: Error Analysis

IEEE Access, 2021

It is an effective method to detect weak gravitational lensing (WL) in the universe by measuring ... more It is an effective method to detect weak gravitational lensing (WL) in the universe by measuring ellipticities of galaxies via astronomical telescopes. Optical properties of telescopes are critical to WL detections. To ensure the used telescopes to be competent, it is necessary to measure point spread function (PSF) ellipticities of telescopes in labs. In this paper, a way based on simulated star target imaging is proposed to measure PSF ellipticity of an unobstructed off-axis space telescope. Related errors are identified and modeled carefully for the first time. Effects of detector noises, micro-vibration of optical platforms, defocusing of simulated star target, wavefront errors (WFEs) and central obstructions of collimators on PSF ellipticity measurements of the telescope are analyzed. Results show that the measurement error of PSF ellipticity decreases from 0.0105 to 0.0043 by adopting 10 iterations of the iterative weighted centroiding algorithm when SNRs are under 24 dB. To ensure PSF ellipticity measurement errors are not larger than 0.01, the micro-vibration angle of the optical platform should be less than 0.05 . When focal length of the collimator is twice that of the telescope, the measurement errors of PSF ellipticity are under 0.01 if the defocusing of simulated star target is controlled to be not larger than 0.1 mm. In addition, WFEs and central obstructions of collimators change PSF ellipticity measurement errors to different degrees at different fields of view (FOVs). Due to 20 nm RMS WFE of the collimator, the maximum value of PSF ellipticity measurement errors over full FOVs is 0.1 and the average value is 0.0269. If the radius of central obscuration of the collimator is 150 mm, the maximum measurement error of PSF ellipticity over full FOVs is 0.0091. According to the results shown in this paper, significant references for high accuracy measurements of PSF ellipticity of telescopes can be provided. INDEX TERMS Weak gravitational lensing, unobstructed off-axis space telescope, PSF ellipticity measurements, error analysis.

A feature point clustering approach to the segmentation of form documents

Proceedings of 3rd International Conference on Document Analysis and Recognition, 1995

Among various kinds of documents, forms are one of the important types. The prerequisite for form... more Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clustering based technique for extracting characters from form documents. In this method, they treat the character extraction process as a pattern clustering problem. The feasibility of the

Lossless Data Hiding of Color Images Using Pixel Decomposition and Phase Difference

Journal of Information Science and Engineering, Sep 1, 2007

Recently, the use of data hiding in hiding annotations, confidential data, or side information in... more Recently, the use of data hiding in hiding annotations, confidential data, or side information into multimedia attracts the attention of researchers in various fields, especially in digital library. One of the essential tasks in digital library is the digitization of arts together with the corresponding textural descriptions. Although there are some standard interleaving algorithms for hiding the relating textural description into an image or video, the textural information is still prone to be accessed and extracted by hackers. Most of the traditional data hiding schemes focus on the recovery of covert information. The common shortcoming is that the original image will be distorted due to the processing of bit-substitution, quantization and truncation. In this paper, three novel data hiding methods are proposed. The first two methods are implemented based on pair-wise logical computation (PWLC) and pixel decomposition by treating R, G, B bands and the intensity component as spatial domains and the third method is implemented by considering and utilizing the phase difference information in the hue and saturation components in the HSI color system. All of the three methods can achieve the goals of complete recovering of covert information and lossless reconstruction of original image simultaneously. In addition, it also obtains high data hiding capacity and good visual quality. Experimental results demonstrate the feasibility and validity of our proposed method in the data hiding of color images.

The Off-Design Performance Simulation of Marine Gas Turbine Based on Optimum Scheduling of Variable Stator Vanes

Mathematical Problems in Engineering, 2017

As one of the antisurge techniques, the adjusting scheme of VSV under off-design conditions has a... more As one of the antisurge techniques, the adjusting scheme of VSV under off-design conditions has a significant impact on the performance of gas turbines. In this paper, the one-dimensional characteristic of the compressor calculation program is embedded into the zero-dimensional overall gas turbine model, which replaces the original compressor characteristic module. Based on the assembling relationship of the actual components of the marine gas turbine, the architecture of the modular model library is designed, and an integrated simulation platform of marine gas turbine is developed by using MATLAB/GUI software. The influence of the first 3 rows of variable stator vanes of the 9-stage axial compressor working alone on the performance of the compressor at different speeds and different angles was analyzed by the HARIKA compressor characteristic calculation program. Taking the economics and stability of the gas turbine as the optimization objective, the optimization of the first three-stage stator vanes regulation schemes under different working conditions was carried out. The steady-state performance parameters under each working condition of gas turbine of power generation with or without variable stator vane mode were calculated. The study results can provide references for the adjusting scheme of VSV under gas turbine off-design conditions operating process.

Motion-embedded residual error for packet loss recovery of video transmission and encryption

Proceedings of SPIE, Jan 15, 2006

Traditional cryptographic encryption can achieve provable security but is unfortunately sensitive... more Traditional cryptographic encryption can achieve provable security but is unfortunately sensitive to a single bit error, which will cause an unreliable packet to be dropped to create packet loss. In order to achieve robust media encryption, error resilience in media encryption can be treated to be equivalent to error resilience in media transmission. This study proposes an embedded block hash searching scheme at the decoder side to achieve motion estimation and recover the lost packets, while maintaining format compliance and cryptographic provable security. It is important to note that the proposed framework is a kind of joint error-resilient video transmission/encryption and copyright protection.

Label Consistency Loss for Multi-label Decoding in Named Entity Recognition

Research Square (Research Square), May 8, 2023

Named entity recognition (NER) has beed studied well recent years. However, the diversity problem... more Named entity recognition (NER) has beed studied well recent years. However, the diversity problem that arises while multiple labels are decoded into entities has been ignored in most studies. Concretely, in the process of decoding labels into entities, the same label prediction accuracy may lead to different entity prediction accuracy. This paper propose label consistency loss (LCL) to address the multilabel decoding diversity problem while considering the global label prediction accuracy. Specifically, the proposed method consists of two loss functions: global loss function and entity loss function. The global loss function is dedicated to improve the global label prediction accuracy by calculating the global error between predicted labels and gold labels. Entity loss is dedicated to solve the diversity problem by achieving labels in same entity are in the same prediction score distribution. To verify the effectiveness of LCL, this paper propose L2E metric which denote the conversion rate of labels to entities. Apply LCL to baseline and conduct experiments on two datasets. The experiment results show the F1 performance of baseline is improved by 1.16% percent and 0.17% percent, the L2E is improved by 1.52% and 0.03% on two datasets.

Colour image segmentation in various illumination circumstances

International Conference on Circuits, systems, electronics, control & signal processing, Dec 29, 2010

We propose a novel colour segmentation algorithm can work in various illumination circumstances. ... more We propose a novel colour segmentation algorithm can work in various illumination circumstances. The proposed colour segmentation algorithm operates directly on RGB colour space without the need of colour space transformation and it is very robust to various illumination conditions. Our approach can be employed in various domains (e.g., human skin colour segmentation, the maturity of tomatoes). Furthermore, our approach has the benefits of being insensitive to rotation, scaling, and translation. In addition, the system can be applied to different applications, for example, colour segmentation for fruits (vegetables) quality control by merely changing the values of the parameters (α, β1, β2, γ1, γ2). Experimental results demonstrate the practicability of our proposed approach in colour segmentation.

Adaptive Shadow Compensation for Face Recognition Under Illumination Variations

Robust face recognition under variant illumination conditions is a challenging research problem. ... more Robust face recognition under variant illumination conditions is a challenging research problem. In this paper, a new shadow compensation method, called adaptive shadow compensation (ASC), will be proposed to eliminate shadows in the face image due to non-frontal lighting directions. ASC performs shadow compensation in each local region, based on Fourier analysis on each local image block, to remove as much shadows as possible. Null-space linear discriminant analysis is then employed to extract discriminant features from ASC compensated images. Experimental results on the Yale B face database show that the proposed ASC method can achieve high face recognition accuracy under illumination variations.

Investigation on Temperature Rise Characteristic and Load Capacity of Amorphous Alloy Vegetable Oil Distribution Transformers with 3D Coupled-Field Method

Machines, Jan 17, 2022

The large differences in the load peak and valley of rural distribution networks always bring sev... more The large differences in the load peak and valley of rural distribution networks always bring severe problems to system planners and operators. Given this issue, this paper deals with the hot-spot temperature (HST) of the transformer and its overload capability, and proposes a modeling method-based online monitoring of practical parameters. In the current work, a temperature-fluid coupling field of the 315 kVA vegetable oil distribution transformer is developed in both the twodimensional and three-dimensional geometry, by which the convection and heat dissipation process can be studied. The grid of the model is divided into regions to increase the calculation speed and ensure the accuracy of the calculation. Secondly, tests related to the temperature rise of the transformer are carried out. The accuracy of the three-dimensional model is later discussed in terms of temperature and fluid velocity distribution. Finally, the temperature distribution laws of the amorphous alloy vegetable oil distribution transformers (AVDT) are compared and analyzed under different load conditions. Findings reveal that the AVDT has low no-load loss and strong overload capacity, which is capable of reducing the internal overheating accidents of the transformer.

Fall Detection in Dusky Environment

Lecture notes in electrical engineering, Nov 13, 2013

Accidental fall is the most prominent factor that causes the accidental death of elder people due... more Accidental fall is the most prominent factor that causes the accidental death of elder people due to their slow body reaction. Automatic fall detection technology integrated in a health-care system can assist human monitoring the occurrence of fall, especially in dusky environments. In this paper, a novel fall detection system focusing mainly on dusky environments is proposed. In dusky environments, the silhouette images of human bodies extracted from conventional CCD cameras are usually imperfect due to the abrupt change of illumination. Thus, our work adopts a thermal imager to detect human bodies. The proposed approach adopts a coarse-to-fine strategy. Firstly, the downward optical flow features are extracted from the thermal images to identify fall-like actions in the coarse stage. The horizontal projection of motion history images (MHI) extracted from fall-like actions are then designed to verify the incident by the proposed nearest neighbor feature line embedding (NNFLE) in the fine stage. Experimental results demonstrate that the proposed method can distinguish the fall incidents with high accuracy even in dusky environments and overlapping situations.

A significant motion vector protection-based error-resilient scheme in H.264

This paper proposes a significant motion vector protection (SMVP) scheme for error-resilient tran... more This paper proposes a significant motion vector protection (SMVP) scheme for error-resilient transmission of videos. In terms of a rate-distortion optimization model, we show how to determine the significant motion vectors (SMVs) and how much rate space should be preserved to store SMVs. The idea behind our method is to give more protection to significant data. As a result, our method can be regarded as a kind of unequal error protection mechanisms. In comparison with the conventional forward error correction (FEC) and error concealment methods, experimental results demonstrate the effectiveness of the proposed method. In particularly, our method shows its superiority under the situation of higher packet loss rates.

A Novel Spectral Clustering Method Based on Pairwise Distance Matrix

Journal of Information Science and Engineering, Mar 1, 2010

In general, the similarity measure is indispensable for most traditional spectral clustering algo... more In general, the similarity measure is indispensable for most traditional spectral clustering algorithms since these algorithms typically begin with the pairwise similarity matrix of a given dataset. However, a general type of input for most clustering applications is the pairwise distance matrix. In this paper, we propose a distance-based spectral clustering method which makes no assumption on regarding both the suitable similarity measure and the prior-knowledge of cluster number. The kernel of distance-based spectral clustering is that the symmetric LoG weighted matrix constructed by applying the Laplace operator to the pairwise distance matrix. The main difference from the traditional spectral clustering is that the pairwise distance matrix can be directly employed without transformation as a similarity pairwise matrix in advance. Moreover, the inter-cluster structure is embedded and the intra-cluster pairwise relationships are maximized in the proposed method to increase the discrimination capability on extracting clusters. Experiments were conducted on different types of test datasets and the results demonstrate the correctness of the extracted clusters. Furthermore, the proposed method is also verified to be robust to noisy datasets.

Radar High-Resolution Range Profile Ship Recognition Using Two-Channel Convolutional Neural Networks Concatenated with Bidirectional Long Short-Term Memory

Remote Sensing, Mar 26, 2021

Radar automatic target recognition is a critical research topic in radar signal processing. Radar... more Radar automatic target recognition is a critical research topic in radar signal processing. Radar high-resolution range profiles (HRRPs) describe the radar characteristics of a target, that is, the characteristics of the target that is reflected by the microwave emitted by the radar are implicit in it. In conventional radar HRRP target recognition methods, prior knowledge of the radar is necessary for target recognition. The application of deep-learning methods in HRRPs began in recent years, and most of them are convolutional neural network (CNN) and its variants, and recurrent neural network (RNN) and the combination of RNN and CNN are relatively rarely used. The continuous pulses emitted by the radar hit the ship target, and the received HRRPs of the reflected wave seem to provide the geometric characteristics of the ship target structure. When the radar pulses are transmitted to the ship, different positions on the ship have different structures, so each range cell of the echo reflected in the HRRP will be different, and adjacent structures should also have continuous relational characteristics. This inspired the authors to propose a model to concatenate the features extracted by the two-channel CNN with bidirectional long short-term memory (BiLSTM). Various filters are used in two-channel CNN to extract deep features and fed into the following BiLSTM. The BiLSTM model can effectively capture long-distance dependence, because BiLSTM can be trained to retain critical information and achieve two-way timing dependence. Therefore, the two-way spatial relationship between adjacent range cells can be used to obtain excellent recognition performance. The experimental results revealed that the proposed method is robust and effective for ship recognition.

A Dimension Reduction Framework for HSI Classification Using Fuzzy and Kernel NFLE Transformation

Remote Sensing, Oct 29, 2015

In this paper, a general nearest feature line (NFL) embedding (NFLE) transformation called fuzzy-... more In this paper, a general nearest feature line (NFL) embedding (NFLE) transformation called fuzzy-kernel NFLE (FKNFLE) is proposed for hyperspectral image (HSI) classification in which kernelization and fuzzification are simultaneously considered. Though NFLE has successfully demonstrated its discriminative capability, the non-linear manifold structure cannot be structured more efficiently by linear scatters using the linear NFLE method. According to the proposed scheme, samples were projected into a kernel space and assigned larger weights based on that of their neighbors. The within-class and between-class scatters were calculated using the fuzzy weights, and the best transformation was obtained by maximizing the Fisher criterion in the kernel space. In that way, the kernelized manifold learning preserved the local manifold structure in a Hilbert space as well as the locality of the manifold structure in the reduced low-dimensional space. The proposed method was compared with various state-of-the-art methods to evaluate the performance using three benchmark data sets. Based on the experimental results: the proposed FKNFLE outperformed the other, more conventional methods.

Feature Line Embedding Based on Support Vector Machine for Hyperspectral Image Classification

Remote Sensing, 2021

In this paper, a novel feature line embedding (FLE) algorithm based on support vector machine (SV... more In this paper, a novel feature line embedding (FLE) algorithm based on support vector machine (SVM), referred to as SVMFLE, is proposed for dimension reduction (DR) and for improving the performance of the generative adversarial network (GAN) in hyperspectral image (HSI) classification. The GAN has successfully shown high discriminative capability in many applications. However, owing to the traditional linear-based principal component analysis (PCA) the pre-processing step in the GAN cannot effectively obtain nonlinear information; to overcome this problem, feature line embedding based on support vector machine (SVMFLE) was proposed. The proposed SVMFLE DR scheme is implemented through two stages. In the first scatter matrix calculation stage, FLE withinclass scatter matrix, FLE between-scatter matrix, and support vector-based FLE between-class scatter matrix are obtained. Then in the second weight determination stage, the training sample dispersion indices versus the weight of SVM-based FLE between-class matrix are calculated to determine the best weight between-scatter matrices and obtain the final transformation matrix. Since the reduced feature space obtained by the SVMFLE scheme is much more representative and discriminative than that obtained using conventional schemes, the performance of the GAN in HSI classification is higher. The effectiveness of the proposed SVMFLE scheme with GAN or nearest neighbor (NN) classifiers was evaluated by comparing them with state-of-the-art methods and using three benchmark datasets. According to the experimental results, the performance of the proposed SVMFLE scheme with GAN or NN classifiers was higher than that of the state-of-the-art schemes in three performance indices. Accuracies of 96.3%, 89.2%, and 87.0% were obtained for the Salinas, Pavia University, and Indian Pines Site datasets, respectively. Similarly, this scheme with the NN classifier also achieves 89.8%, 86.0%, and 76.2% accuracy rates for these three datasets.

Inhibitory Effect of Acer truncatum Bunge Seed Coat Extract on Fatty Acid Synthase, Differentiation and Lipid Accumulation in 3T3-L1 Adipocytes

Molecules, Feb 16, 2022

Acer truncatum Bunge is now widely cultivated throughout the world. Fatty acid synthase (FAS) is ... more Acer truncatum Bunge is now widely cultivated throughout the world. Fatty acid synthase (FAS) is a potential target in the treatment of both obesity and cancer. Only a few FAS inhibitors have been reported. In this study, the inhibitory effect of A. truncatum seed coat (ESA) on FAS and the inhibition mechanisms were investigated using a FAS activity assay and an enzyme kinetics study. The main chemicals of ESA were analyzed with UPLC-MS/MS. The effects of ESA on 3T3-L1 adipocyte differentiation and lipid accumulation were investigated using Oil red O staining. We first identified seven main compounds (quinic acid, malic acid, gentisic acid, procyanidin dimer, procyanidin trimer, catechin, and quercetin) from 50% ethanol extracts of seed coats of A. truncatum (ESAs), which were then found to inhibit 3T3-L1 adipocyte differentiation at the concentration of 50 µg/mL. ESA obviously reduced the visible triglyceride droplets accumulation, and dramatically decreased the number of the adipocytes at a comparatively high concentration. It is suggested that the effects are due to the inhibition of FAS by ESA; FAS activity is inhibited by ESA at a half inhibition concentration (IC 50 ) of 0.57 µg/mL, which is lower than that of classically known FAS inhibitors. Meanwhile, ESA displayed different inhibition kinetics and reacting sites for FAS. These results provide new clues for the development of novel products for obesity treatment and a scientific basis for the full use of byproducts for future industrial production of vegetable oil.

Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images

Sensors, Dec 12, 2015

In this paper, we present a reliable and robust biometric verification method based on bimodal ph... more In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods.

Ambient-pressure hydrogenation of CO2 into long-chain olefins

Nature Communications, May 3, 2022

The conversion of CO 2 by renewable power-generated hydrogen is a promising approach to a sustain... more The conversion of CO 2 by renewable power-generated hydrogen is a promising approach to a sustainable production of long-chain olefins (C 4+ = ) which are currently produced from petroleum resources. The decentralized small-scale electrolysis for hydrogen generation requires the operation of CO 2 hydrogenation in ambient-pressure units to match the manufacturing scales and flexible on-demand production. Herein, we report a Cu-Fe catalyst which is operated under ambient pressure with comparable C 4+ = selectivity (66.9%) to that of the state-of-the-art catalysts (66.8%) optimized under high pressure (35 bar). The catalyst is composed of copper, iron oxides, and iron carbides. Iron oxides enable reverse-watergas-shift to produce CO. The synergy of carbide path over iron carbides and CO insertion path over interfacial sites between copper and iron carbides leads to efficient C-C coupling into C 4+ = . This work contributes to the development of small-scale low-pressure devices for CO 2 hydrogenation compatible with sustainable hydrogen production.

High quantum oscillation frequencies and nontrivial topology in kagome superconductor KV3Sb5 probed by torque magnetometry up to 45 T

Physical Review B

Here, we present the Fermi surface properties of the kagome superconductor KV 3 Sb 5 using torque... more Here, we present the Fermi surface properties of the kagome superconductor KV 3 Sb 5 using torque magnetometry at applied fields up to 45 T and temperatures down to that of liquid 3 He (0.32 K). The torque signal shows clear de Haas-van Alphen (dHvA) oscillations with 14 major frequencies ranging from ∼33 to 2149 T, nine of which are higher frequencies (above 500 T) that have never been reported in KV 3 Sb 5 . Angular dependence measurements of the dHvA oscillations were carried out to investigate the dimensionality of the Fermi surface. Based on our analysis, several frequencies follow the 1/cos θ dependence, where θ is the tilt angle with respect to the applied field direction and oscillations disappear above θ = 60 • , which suggest that Fermi surfaces corresponding to these frequencies are quasitwo dimensional. The Berry phase ( B ), determined by constructing a Landau level fan diagram, was found to be B ∼ π , which strongly suggests the nontrivial topology of KV 3 Sb 5 . To explain the experimental results, we carried out band-structure and Fermi-surface calculations using density functional theory (DFT) for both pristine and charge-density wave (CDW) phases. We found that the Fermi surface undergoes severe reconstruction in the CDW phase and, more importantly, our calculation results are in reasonable agreement with the experimentally measured Fermi-surface frequencies. The observation in this paper of very high quantum oscillation frequencies in KV 3 Sb 5 and the determination of their detailed Fermi-surface properties, along with the analyses of corresponding DFT calculation results, are crucial for understanding CDW order, unconventional superconductivity, and nontrivial topology in AV 3 Sb 5 (A = K, Rb, and Cs), as well as the interplay among them.

Two new antimicrobial monoterpenoid indole alkaloids from the roots of Rauvolfia yunnanensis

Journal of Asian Natural Products Research

The Measurement of PSF Ellipticity of an Unobstructed Off-Axis Space Telescope: Error Analysis

IEEE Access, 2021

It is an effective method to detect weak gravitational lensing (WL) in the universe by measuring ... more It is an effective method to detect weak gravitational lensing (WL) in the universe by measuring ellipticities of galaxies via astronomical telescopes. Optical properties of telescopes are critical to WL detections. To ensure the used telescopes to be competent, it is necessary to measure point spread function (PSF) ellipticities of telescopes in labs. In this paper, a way based on simulated star target imaging is proposed to measure PSF ellipticity of an unobstructed off-axis space telescope. Related errors are identified and modeled carefully for the first time. Effects of detector noises, micro-vibration of optical platforms, defocusing of simulated star target, wavefront errors (WFEs) and central obstructions of collimators on PSF ellipticity measurements of the telescope are analyzed. Results show that the measurement error of PSF ellipticity decreases from 0.0105 to 0.0043 by adopting 10 iterations of the iterative weighted centroiding algorithm when SNRs are under 24 dB. To ensure PSF ellipticity measurement errors are not larger than 0.01, the micro-vibration angle of the optical platform should be less than 0.05 . When focal length of the collimator is twice that of the telescope, the measurement errors of PSF ellipticity are under 0.01 if the defocusing of simulated star target is controlled to be not larger than 0.1 mm. In addition, WFEs and central obstructions of collimators change PSF ellipticity measurement errors to different degrees at different fields of view (FOVs). Due to 20 nm RMS WFE of the collimator, the maximum value of PSF ellipticity measurement errors over full FOVs is 0.1 and the average value is 0.0269. If the radius of central obscuration of the collimator is 150 mm, the maximum measurement error of PSF ellipticity over full FOVs is 0.0091. According to the results shown in this paper, significant references for high accuracy measurements of PSF ellipticity of telescopes can be provided. INDEX TERMS Weak gravitational lensing, unobstructed off-axis space telescope, PSF ellipticity measurements, error analysis.

A feature point clustering approach to the segmentation of form documents

Proceedings of 3rd International Conference on Document Analysis and Recognition, 1995

Among various kinds of documents, forms are one of the important types. The prerequisite for form... more Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clustering based technique for extracting characters from form documents. In this method, they treat the character extraction process as a pattern clustering problem. The feasibility of the