Image Copy-Move Forgery Detection via Deep Cross-Scale PatchMatch

The recently developed deep algorithms achieve promising progress in the field of image copy-move forgery detection (CMFD). However, they have limited generalizability in some practical scenarios, where the copy-move objects may not appear in the training images or cloned regions are from the background. To address the above issues, in this work, we propose a novel end-to-end CMFD framework by integrating merits from both conventional and deep methods. Specifically, we design a deep cross-scale patchmatch method tailored for CMFD to localize copy-move regions. In contrast to existing deep models, our scheme aims to seek explicit and reliable point-to-point matching between source and target regions using features extracted from high-resolution scales. Further, we develop a manipulation region location branch for source/target separation. The proposed CMFD framework is completely differentiable and can be trained in an end-to-end manner. Extensive experimental results demonstrate the high generalizability of our method to different copy-move contents, and the proposed scheme achieves significantly better performance than existing approaches.Comment: 6 pages, 4 figures, accepted by ICME202

A Randomized Phase I/II Trial to Compare Weekly Usage with Triple Weekly Usage of Paclitaxel in Concurrent Radiochemotherapy for Patients with Locally Advanced Non-small Cell Lung Cancer

Background and objective Although the guidelines of the National Comprehensive Cancer Network of USA recommend that the standard therapy for locally advanced non-small cell lung cancer (LANSCLC) is concurrent chemoradiotherapy. There is ongoing controversy about the treatment regimen which combines chemotherapy concurrently with radiotherapy. The aim of this study is to compare weekly usage with triple weekly usage of paclitaxel in concurrent radiochemotherapy for patients with LANSCLC, and to obtain the best paclitaxel regimen in the concurrent radiochemotherapy. Methods From April 2006 to April 2009, some LANSCLC patients in multicenter were randomly divided into weekly usage (45 mg/m2, 1 times/week, a total of 270 mg/m2 in six weeks) and triple weekly usage (15 mg/m2, 3 times/week, a total of 270 mg/m2 in six weeks) group of paclitaxel by a random number table. All patients were treated with 3D radiotherapy, and 95% planning target volume (PTV) received a prescription dose of (60-70) Gy/(30-35)times/(6-7)weeks, (1.8-2.0) Gy/fraction. Then the side effects, response and overall survival rate were compared between two groups of patients. Results Thirty-eight LANSCLC patients were enrolled. Weekly usage and triple weekly usage group were 20 and 18 patients, respectively. In the triple weekly usage group, the side effects were 12 patients had radiation esophagitis of I-II degree, 1 patient had radiation esophagitis of III degree, 2 patients had radiation pneumonitis of I degree, 1 patient had radiation pneumonitis of II degree, 1 patient had radiation pneumonitis of III degree and died of respiratory failure, 2 patients developed weight loss of I degree. In the weekly usage group, the side effects were 11 patients had radiation esophagitis of I-III degree, 6 patients had radiation pneumonitis of II-III degree, 2 patients developed weight loss of I degree, 6 patients developed leucopenia of III-IV degree. The response rate of two groups was 88.8% and 50.0%, respectively (P=0.026). 1-year survival rate of two groups was 79% and 67%, respectively (P=0.607). Conclusion Although the preliminary results did not show the merits of survival in triple weekly usage, but preliminary results show that triple weekly usage was more safe and effective than weekly usage of paclitaxel in concurrent radiochemotherapy for patients with LANSCLC

The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Open access article.The linear relationship of the original grey prediction model is too single, and the original grey prediction model does not consider the time delay of the effect of the current input parameters on the output parameters. In order to solve these problems, the interval grey number sequence is taken as the modelling sequence of the model, and the nonlinear parameter γ and the time-delay parameter τ are introduced into the multivariate grey prediction model, so as to construct the nonlinear time-delay multivariable grey prediction model for interval grey number. In view of the uncertain characteristics of the smog index data, this paper applies the improved model to the simulation and prediction of the smog index data. Compared with the original model, the results show that the prediction effect of the model proposed in this paper is superior to the original model in terms of its effectiveness and feasibility

A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends

As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity recognition (NER) serves as the core component in information extraction technology, while also playing a critical role in many other Natural Language Processing (NLP) systems, such as question answering and knowledge graph building. In this paper, we provide a comprehensive review of the development of Arabic NER, especially the recent advances in deep learning and pre-trained language model. Specifically, we first introduce the background of Arabic NER, including the characteristics of Arabic and existing resources for Arabic NER. Then, we systematically review the development of Arabic NER methods. Traditional Arabic NER systems focus on feature engineering and designing domain-specific rules. In recent years, deep learning methods achieve significant progress by representing texts via continuous vector representations. With the growth of pre-trained language model, Arabic NER yields better performance. Finally, we conclude the method gap between Arabic NER and NER methods from other languages, which helps outline future directions for Arabic NER.Comment: Accepted by IEEE TKD

Should chronic hepatitis B mothers breastfeed? a meta analysis

<p>Abstract</p> <p>Background</p> <p>Hepatitis B virus (HBV) exists in the breast milk of chronic hepatitis B (CHB) mothers. The authors use a meta-analytic technique to quantify the evidence of an association between breastfeeding and risk of CHB infection among the infants vaccinated against HBV.</p> <p>Methods</p> <p>Literature search is performed up to 2010 on the relationship between infantile CHB infection within one-year follow up after immunization with the third-dose hepatitis B vaccine and breastfeeding. Two reviewers independently extract the data and evaluate the methodological quality. A random-effects model is employed to systematically combine the results of all included studies.</p> <p>Results</p> <p>Based on data from 32 studies, 4.32% (244/5650) of infants born of CHB mothers develop CHB infection. The difference in risk of the infection between breastfed and formula-fed infants (RD) is -0.8%, (95% confidence interval [CI]: -1.6%, 0.1%). Analysis of the data from 16 of the studies finds that RD for mothers who are positive for the HBeAg and/or the HBV DNA, 0.7% (95%CI: -2.0%, 3.5%), is similar to that for those who are negative for these infectivity markers, -0.5% (95%CI: -1.7%, 0.6%).</p> <p>Conclusions</p> <p>Breast milk is infectious; yet, breastfeeding, even by mothers with high infectivity, is not associated with demonstrable risk of infantile CHB infection, provided that the infants have been vaccinated against HBV at birth.</p

Low-Profile Frequency-Scanned Antenna Based on Substrate Integrated Waveguide

A beam scanning flat antenna array with the frequency that covers about the whole X/Ku-band is proposed in this paper. The radiation element is the continuous transverse stub (CTS) constituted by the substrate integrated waveguide (SIW). The CTS array is fed by a linear source which is a SIW parabolic reflector, and good impedance matching characteristics within a broad bandwidth are obtained. The beam steering direction is tunable with the frequency increasing within the operation band. The design principles of the SIW based CTS array and the feed structure are explained in details. One 16-element array is simulated, designed and fabricated. The measurement results show a scanning angle range from 52.2° to -16.8° with the 3-dB gain decreasing within the operation band from 8.5 GHz to 14.1GHz. At the center frequency of 12 GHz, it achieves a maximum gain of 18.1 dBi with an array size of 11.7?0×1.28?0, the first sidelobe level is -11.4 dB and the 3-dB beamwidth is 6.5°

Perceptually Guided Photo Retargeting

We propose perceptually guided photo retargeting, which shrinks a photo by simulating a human's process of sequentially perceiving visually/semantically important regions in a photo. In particular, we first project the local features (graphlets in this paper) onto a semantic space, wherein visual cues such as global spatial layout and rough geometric context are exploited. Thereafter, a sparsity-constrained learning algorithm is derived to select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path which simulates how a human actively perceives semantics in a photo. Furthermore, we learn the prior distribution of such active graphlet paths (AGPs) from training photos that are marked as esthetically pleasing by multiple users. The learned priors enforce the corresponding AGP of a retargeted photo to be maximally similar to those from the training photos. On top of the retargeting model, we further design an online learning scheme to incrementally update the model with new photos that are esthetically pleasing. The online update module makes the algorithm less dependent on the number and contents of the initial training data. Experimental results show that: 1) the proposed AGP is over 90% consistent with human gaze shifting path, as verified by the eye-tracking data, and 2) the retargeting algorithm outperforms its competitors significantly, as AGP is more indicative of photo esthetics than conventional saliency maps