On robustness against JPEG2000: a performance evaluation of wavelet-based watermarking techniques

With the emergence of new scalable coding standards, such as JPEG2000, multimedia is stored as scalable coded bit streams that may be adapted to cater network, device and usage preferences in multimedia usage chains providing universal multimedia access. These adaptations include quality, resolution, frame rate and region of interest scalability and achieved by discarding least significant parts of the bit stream according to the scalability criteria. Such content adaptations may also affect the content protection data, such as watermarks, hidden in the original content. Many wavelet-based robust watermarking techniques robust to such JPEG2000 compression attacks are proposed in the literature. In this paper, we have categorized and evaluated the robustness of such wavelet-based image watermarking techniques against JPEG2000 compression, in terms of algorithmic choices, wavelet kernel selection, subband selection, or watermark selection using a new modular framework. As most of the algorithms use a different set of parametric combination, this analysis is particularly useful to understand the effect of various parameters on the robustness under a common platform and helpful to design any such new algorithm. The analysis also considers the imperceptibility performance of the watermark embedding, as robustness and imperceptibility are two main watermarking properties, complementary to each other

Consequences of marine barriers for genetic diversity of the coral-specialist yellowbar angelfish from the Northwestern Indian Ocean

© 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Ocean circulation, geological history, geographic distance, and seascape heterogeneity play an important role in phylogeography of coral-dependent fishes. Here, we investigate potential genetic population structure within the yellowbar angelfish (Pomacanthus maculosus) across the Northwestern Indian Ocean (NIO). We then discuss our results with respect to the above abiotic features in order to understand the contemporary distribution of genetic diversity of the species. To do so, restriction site-associated DNA sequencing (RAD-seq) was utilized to carry out population genetic analyses on P. maculosus sampled throughout the species’ distributional range. First, genetic data were correlated to geographic and environmental distances, and tested for isolation-by-distance and isolation-by-environment, respectively, by applying the Mantel test. Secondly, we used distance-based and model-based methods for clustering genetic data. Our results suggest the presence of two putative barriers to dispersal; one off the southern coast of the Arabian Peninsula and the other off northern Somalia, which together create three genetic subdivisions of P. maculosus within the NIO. Around the Arabian Peninsula, one genetic cluster was associated with the Red Sea and the adjacent Gulf of Aden in the west, and another cluster was associated with the Arabian Gulf and the Sea of Oman in the east. Individuals sampled in Kenya represented a third genetic cluster. The geographic locations of genetic discontinuities observed between genetic subdivisions coincide with the presence of substantial upwelling systems, as well as habitat discontinuity. Our findings shed light on the origin and maintenance of genetic patterns in a common coral reef fish inhabiting the NIO, and reinforce the hypothesis that the evolution of marine fish species in this region has likely been shaped by multiple vicariance events

An efficient record linkage scheme using graphical analysis for identifier error detection

Integration of information on individuals (record linkage) is a key problem in healthcare delivery, epidemiology, and "business intelligence" applications. It is now common to be required to link very large numbers of records, often containing various combinations of theoretically unique identifiers, such as NHS numbers, which are both incomplete and error-prone

Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs

Connected components and spanning forest are fundamental graph algorithms due to their use in many important applications, such as graph clustering and image segmentation. GPUs are an ideal platform for graph algorithms due to their high peak performance and memory bandwidth. While there exist several GPU connectivity algorithms in the literature, many design choices have not yet been explored. In this paper, we explore various design choices in GPU connectivity algorithms, including sampling, linking, and tree compression, for both the static as well as the incremental setting. Our various design choices lead to over 300 new GPU implementations of connectivity, many of which outperform state-of-the-art. We present an experimental evaluation, and show that we achieve an average speedup of 2.47x speedup over existing static algorithms. In the incremental setting, we achieve a throughput of up to 48.23 billion edges per second. Compared to state-of-the-art CPU implementations on a 72-core machine, we achieve a speedup of 8.26--14.51x for static connectivity and 1.85--13.36x for incremental connectivity using a Tesla V100 GPU

Video Based Technology for Ambient Assisted Living: A review of the literature

Ambient assisted living (AAL) has the ambitious goal of improving the quality of life and maintaining independence of older and vulnerable people through the use of technology. Most of the western world will see a very large increase in the number of older people within the next 50 years with limited resources to care for them. AAL is seen as a promising alternative to the current care models and consequently has attracted lots of attention. Recently, a number of researchers have developed solutions based on video cameras and computer vision systems with promising results. However, for the domain to reach maturity, several challenges need to be faced, including the development of systems that are robust in the real-world and are accepted by users, carers and society. In this literature review paper we present a comprehensive survey of the scope of the domain, the existing technical solutions and the challenges to be faced

Prospects for sustainable intensification of soybean production in sub-Saharan Africa

There is a significant soybean yield gap in sub-Saharan African (SSA) countries. Sustainable intensification of the agricultural sector to reduce such a yield gap is important. Increasing soybean productivity can meet the growing demand for food and feed when complemented with higher soy meal demand by the local livestock industry. This study performs an ex-ante economic analysis to determine the effect of higher soybean production on trade and land use within SSA countries. We find that increasing soybean yield by 50% can increase the total returns from soybean production by 186 million LC (local currency) in Ethiopia and 36 billion LC in Nigeria. We show that soybean yield growth alone is enough to boost soy oil production, as the crushing of the beans produces 18% oil and 79% meal. While increasing productivity may lead to freeing land to produce high-valued cash crops, investors will be reluctant to invest in the crushing facilities in the absence of soy meal demand by the livestock industry. Therefore, policymakers need to establish collaboration between development organisations, private companies, farmers and researchers to achieve this transformation and thereby raise agricultural productivity.PRIFPRI3; CRP2; CRP4; 1 Fostering Climate-Resilient and Sustainable Food Supply; 2 Promoting Healthy Diets and Nutrition for all; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; Capacity Strengthening; ISIA4NH; AFR; DSGD; PIM; PHNDCGIAR Research Program on Agriculture for Nutrition and Health (A4NH); CGIAR Research Program on Policies, Institutions, and Markets (PIM

The impact of India’s food security policy on domestic and international rice market

PRIFPRI3; ISI; CRP2; A Ensuring Sustainable food production; C Improving markets and trade; F Strengthening institutions and governanceDGO; PIMCGIAR Research Programs on Policies, Institutions, and Markets (PIM

THEORY AND DESIGN OF A FLEXIBLE TWO-STAGE WIDEBAND WILKINSON POWER DIVIDER

This article presents the design scheme of a wideband Wilkinson Power Divider (WPD) with two-stage architecture utilizing quarter-wave transmission lines and short-circuit stubs. The bandwidth of the proposed WPD is flexible and can be controlled using the design parameters. The proposed design achieves excellent isolation between output ports in addition good in-band performance. The analysis of the proposed circuit results in a simplified transfer function which is then equated with a standard band-pass transfer function to determine the parameters of transmission lines, stub’s impedances, and the value of the isolation resistors. Furthermore, it is also demonstrated that a simple alteration in the proposed circuit enables the design of a wideband DC isolated WPD that maintains a good in-band and isolation performance. A number of case studies have been included to highlight the flexibility of the proposed design. Two distinct prototypes are developed on different boards to demonstrate the wideband performance of the proposed design. An excellent agreement between the experimental and measured results for both the designs over a wide band including very good isolation between ports validate the proposed design. Keywords: wideband; wilkinson power divider; band-pass filter; DC isolatio

Research Track Paper Fully Automatic Cross-Associations ∗

Large, sparse binary matrices arise in numerous data mining applications, such as the analysis of market baskets, web graphs, social networks, co-citations, as well as information retrieval, collaborative filtering, sparse matrix reordering, etc. Virtually all popular methods for the analysis of such matrices—e.g., k-means clustering, METIS graph partitioning, SVD/PCA and frequent itemset mining—require the user to specify various parameters, such as the number of clusters, number of principal components, number of partitions, and “support. ” Choosing suitable values for such parameters is a challenging problem. Cross-association is a joint decomposition of a binary matrix into disjoint row and column groups such that the rectangular intersections of groups are homogeneous. Starting from first principles, we furnish a clear, informationtheoretic criterion to choose a good cross-association as well as its parameters, namely, the number of row and column groups. We provide scalable algorithms to approach the optimal. Our algorithm is parameter-free, and requires no user intervention. In practice it scales linearly with the problem size, and is thus applicable to very large matrices. Finally, we present experiments on multiple synthetic and real-life datasets, where our method gives high-quality, intuitive results. This material is based upon work supported by the Nationa