A novel approach to design optimal 2-D digital differentiator using vortex search optimization algorithm

Multimedia Tools and Applications - The designing of 2-D digital differentiator is multimodal and high dimensional problem which requires large number of differentiator coefficients to be...     

Quote examiner: verifying quoted images using web-based text similarity

Over the last few years, there has been a rapid growth in digital data. Images with quotes are spreading virally through online social media platforms. Misquotes found online often spread like a forest fire through social media, which highlights the lack of responsibility of the web users when circulating poorly cited quotes. Thus, it is important to authenticate the content contained in the images being circulated online. So, there is a need to retrieve the information within such textual images to verify quotes before its usage in order to differentiate a fake or misquote from an authentic one. Optical Character Recognition (OCR) is used in this paper, for converting textual images into readable text format, but none of the OCR tools are perfect in extracting information from the images accurately. In this paper, a method of post-processing on the retrieved text to improve the accuracy of the detected text from images has been proposed. Google Cloud Vision has been used for recognizing text from images. It has also been observed that using post-processing on the extracted text improved the accuracy of text recognition by 3.5% approximately. A web-based text similarity approach (URLs and domain name) has been used to examine the authenticity of the content of the quoted images. Approximately, 96.26% accuracy has been achieved in classifying quoted images as verified or misquoted. Also, a ground truth dataset of authentic site names has been created. In this research, images with quotes by famous celebrities and global leaders have been used. A comparative analysis has been performed to show the effectiveness of our proposed algorithm.

     

Forensic image analysis using inconsistent noise pattern

With the advancement of image acquisition devices and social networking services, a huge volume of image data is generated. Using different image and video processing applications, these image data are manipulated, and thus, original images get tampered. These tampered images are the prime source of spreading fake news, defaming the personalities and in some cases (when used as evidence) misleading the law bodies. Hence before relying totally on the image data, the authenticity of the image must be verified. Works of the literature are reported for the verification of the authenticity of an image based on noise inconsistency. However, these works suffer from limitations of confusion between edges and noise, post-processing operation for localization and need of prior knowledge about an image. To handle these limitations, a noise inconsistency-based technique has been presented here to detect and localize a false region in an image. This work consists of three major steps of pre-processing, noise estimation and post-processing. For the experimental purpose two, publicly available datasets are used. The result is discussed in terms of precision, recall, accuracy and f1-score on the pixel level. The result of the presented work is also compared with the recent state-of-the-art techniques. The average accuracy of the proposed work on datasets is 91.70%, which is highest among state-of-the-art techniques.

     

HSIC-based affinity measure for learning on graphs

Pattern Analysis and Applications - The performance of graph-based learning techniques largely relies on the edges defined between the vertices of the graph. These edges that represent the affinity...     

Model reduction based on limited‐time interval impulse response Gramians

In this paper, three new Gramians are introduced namely ‐ limited‐time interval impulse response Gramians (LTIRG), generalized limited‐time Gramians (GLTG) and generalized limited‐time impulse response Gramians (GLTIRG). GLTG and GLTIRG are applicable to both unstable systems and also to systems which have eigenvalues of opposite polarities and equal magnitude. The concept of these Gramians is utilized to develop model reduction algorithms for linear time‐invariant continuous‐time single‐input single‐output (SISO) systems. In the cases of GLTIRG and GLTG based model reduction, the standard time‐limited Gramians are generalized to be applied to unstable systems by transforming the original system into a new system which requires the solution of two Riccati equations. Two numerical examples are included to illustrate the proposed methods. The results are also compared with standard techniques.     

A smart application to detect pupil for small dataset with low illumination

Biometric applications are very sensitive to the process because of its complexity in presenting unstructured input to the processing. The existing applications of image processing are based on the implementation of different programing segments such as image acquisition, segmentation, extraction, and final output. The proposed model is designed with 2 convolution layers and 3 dense layers. We examined the module with 5 datasets including 3 benchmark datasets, namely CASIA, UBIRIS, MMU, random dataset, and the live video. We calculated the FPR, FNR, Precision, Recall, and accuracy of each dataset. The calculated accuracy of CASIA using the proposed system is 82.8%, for UBIRIS is 86%, MMU is 84%, and the random dataset is 84%. On live video with low resolution, calculated accuracy is 72.4%. The proposed system achieved better accuracy compared to existing state-of-the-art systems.

     

高速公路施工区车辆强制换道耗时生存模型

为研究高速公路施工区车辆强制换道行为及其影响因素,采用生存分析中的半参数分析方法建立强制换道耗时的乘法风险率模型.通过无人机拍摄采集高速公路施工区的车辆换道耗时及其影响因素数据,最终确立换道耗时Cox比例风险模型,对换道耗时数据进行Cox回归建模分析.结果表明:近77%的换道车辆在10 s内完成换道;小型车和中型车经养护施工区的换道耗时未发现显著性差别;对于相同的换道耗时,平峰期的累积生存率明显低于高峰期和过渡时期,而高峰期的累积生存率最高.建立的强制换道耗时生存模型可有效的定量分析车型和交通时段对高速公路施工区车辆换道行为的影响,可为高速公路施工区交通管理控制及车辆换道行为建模及仿真奠定一定的理论基础.     

Enhancement of the hydrogen storage properties of Mg/C nanocomposites prepared by reactive milling with molybdenum

The effect of Mo on the morphology, crystal structure and hydrogen sorption properties of Mg/C composites prepared by reactive milling was studied. Transmission electron microscopic(TEM) observation shows that Mg/C composites prepared with the addition of Mo are of nanoscale with particle size about 20-120 nm after 3 h of milling under 1 MPaH_2. MgH_2 of tetrahedral crystal structure predominates in the materials with the geometric shape of oblique hexagonal prism. From X-ray diffraction(XRD) and hydrogen content studies, Mo and crystallitic carbon have a synergistic effect on promoting the hydrogenation rate in the reactive milling process. From differential scanning calorimetric(DSC) studies, the dehydrogenation peak temperature of the Mg/C materials with Mo is lowered to 299-340 ℃.     

Reaction mechanism and microstructure evolution of reaction sintered <Emphasis Type="Italic">h</Emphasis>-BN

Hexagonal boron nitride ceramic (h-BN) based on the nitridation of B powders was obtained by reaction sintering method. The effects of sintering temperature on the mechanical properties and microstructure of the resultant products were investigated and the reaction mechanism was discussed. Results showed that the reaction between B and N₂ occurred vigorously at temperatures ranging from 1 000 °C to 1 300 °C, which resulted in the generation of t-BN. When the temperature exceeded 1 450 °C, transformation from t-BN to h-BN began to occur. As the sintering temperature increased, the spherical particles of t-BN gradually transformed into fine sheet particles of h-BN. These particles subsequently displayed a compact arrangement to achieve a more uniform microstructure, thereby increasing the strength.     

Numerical simulation of the multicomponent mass transfer during Bridgman growth of CdZnTe crystal using Maxwell-Stefan diffusion model

To reveal the complicated mechanism of the multicomponent mass transfer during the growth of ternary compound semiconductors, a numerical model based on Maxwell-Stefan equations was developed to simulate the Bridgman growth of CdZnTe crystal. The Maxwell-Stefan diffusion coefficients in the melt were estimated. Distributions of Zn, Cd, and Te were calculated with variable ampoule traveling rate and diffusion coefficients. The experimental results show that Zn in melt near the growth interface decreases and diffuses from the bulk melt to the growth interface. For Cd, the situation is just the opposite. The coupling effects of Zn and Cd diffusions result in an uphill diffusion of Te at the beginning of the growth. Throughout the growth, the concentration of Te in the melt keeps low near the growth interface but high far from the growth interface. Increasing the ampoule traveling rate will aggravate the segregation of Zn and Cd, and hence deteriorate the uniformity of Te. We also find that not only the diffusion coefficients but also the ratios between them have significant influence on the species diffusions.