Immunization crisis may develop due to economic crisis during COVID-19 pandemic

COVID-19 pandemic is a global health crisis with 61, 149,391 confirmed cases and 370,478 deaths till 29May, 2020 [1]. This pandemic has shattered many economies with an estimated loss of $5.8 trillion to $8.8 trillion globally. This economic loss can result in reduction in funds to World Health Organization. Unfortunately, United States of America (USA) has announced termination of any further funding to WHO which can lead to another global health crisis[2]. As WHO is a voluntary funding based organization its main donor are America, China, Japan, Germany and United Kingdom. Among these USA is the main donor with a contribution of $115.8million alone followed by China $57.4 million, Japan $41million, Germany $29.1 million and UK $21.9 million [3].  America’s termination of funding can put WHO and child health programs in serious crisis. Among many programs run by WHO one of the most important program is immunization of children. Immunization coverage programs  save 2-3 million livesper year causing decline in measles related deaths, eradication of polio, surveillance of rotavirus, BCG and DTaP vaccination in children[4]. It is estimated that during MillenniumDevelopment Goal (MDG) there is overall decline in child related mortalities due to malaria, measles, diarrhea, AIDS and meningitis [5]. Remarkable results are achieved with measles are diarrhea immunization programs causing a decline in death rate by 73% and 80% respectively. According to a study with current success rate diarrhea related deaths can be virtually eliminated by 2030. Another successful program is “End Polio” program which eradicated polio from world except from Pakistan and Afghanistan [4][6]. This termination of funds to WHO can waste all previous efforts in developing countries. On the other hand despite of all efforts still 19.4 million children did not received prescribed dose of vaccines. Data analysis revealed among these  60% of children belong to 10 developing countries namelyAngola, Brazil, the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, the Philippines and Viet Nam [4]. These countries mainly rely on foreign funding and Non-Government Organization (NGOs) for child health care programs.

Digital Watermarking of Stereoscopic Images Using Depth Image Based Rendering and Machine Learning

Digital Watermarking of Stereoscopic Images Using Depth Image Based Rendering and Machine Learning The increasing acceptance of 3D-TV in recent years has attracted attention of the research community and industry towards the technology. Depth Image Based Rendering (DIBR) is the latest advancement in 3D-TV and free-view television. With the widespread of 3D content, copyright protection is becoming a serious concern for maximizing the profits and preventing illegitimate acquisition and distribution of the 3D media content. Digital watermarking is one such promising technique to tackle this problem. This thesis presents a comprehensive literature study of application of digital watermarking techniques, i.e., the three different paradigms for 3D images in particular and 3D-TV system in general. These paradigms include robust, fragile, and reversible watermarking for 3D system. In addition, this work also presents an improved reduced reference image quality assessment for 3D images along with a comprehensive literature survey of the field. Firstly, this thesis proposes a robust watermarking technique for 3D-TV. The proposed technique is based upon intelligent parameter selection using Genetic Algorithm (GA) in an improved spread spectrum based watermarking system. In order to enhance robustness, another layer of security of the watermark is added using Bose–Chadhuri–Hocquenghem (BCH) coding. Experimental results and comparison with state of the art technique demonstrate the effectiveness of the proposed technique to structure the watermark for high robustness in the presence of a number of hostile attacks. The second phase of this research proposes a fragile watermarking scheme for 3D-TV system for the purpose of content authentication. The proposed technique is based upon implicit watermarking of a number of other un-watermarked coefficient from a dependence neighborhood in a DCT based watermarking schemes. Such a scheme is robust against common counterfeiting attacks such as collage attack, cover up attack, transplantation, and vector quantization attack. In addition, the propose scheme is also capable of localizing the tempering of the cover work. x In the third phase of this research work, a reversible watermarking technique for DIBR 3D-TV is developed. The DIBR 3D-TV or free-view TV is one of the most promising technique in multimedia world. So, the protection of these valuable contents is an important concern in the world of digital processing. This study exploits the interpolation scheme by applying Genetic Programming (GP) based intelligent reversible watermarking technique. Previously, the empirical solutions are not that much effective and use hit and trial strategies for selecting optimal space for watermark embedding. The proposed scheme achieved considerable watermark capacity as well as Structure Similarity Index Metric (SSIM) and Peak Signal to Noise Ratio (PSNR), compared to existing state of the art contemporary schemes. The existing methods performed well against GA and Particle Swarm Optimizer (PSO), but show relatively less performance compared with Tian’s method. However, the PSNR value in the proposed method outperforms against Tian’s scheme. The proposed algorithm is tested on different standard publicly available 3D datasets. It is observed that the proposed scheme gives relatively better results compared with state of the art techniques. Last phase of this research work proposes an enhanced reduced reference image quality assessment technique. Reduced reference image quality assessment (RR-IQA) technique does not require the presence of the original image for assessing the quality of a degraded image. This work proposes an intelligent method for reduced reference image quality assessment based on Reorganized Discrete Cosine Transform (RDCT). The GA is used to compute optimized estimation of Generalized Gaussian Distribution (GGD), which then approximates the coefficient distribution in RDCT domain. Experimental results validate that such an intelligent estimation produces far superior results as compared to conventional empirical estimation methods as presented in literature. The comparative analysis of the proposed technique with a number of contemporary techniques present in the literature demonstrate the generalization capability and effectiveness of the proposed technique as compared to prior works.