The necessity of image fusion is growing in recently in image processing applications due to the tremendous amount of acquisition systems. Fusion of images is defined as an alignment of noteworthy Information from diverse sensors using various mathematical models to generate a single compound image. The fusion of images is used for integrating the complementary multi-temporal, multi-view and multi-sensor Information into a single image with improved image quality and by keeping the integrity of important features. It is considered as a vital pre-processing phase for several applications such as robot vision, aerial, satellite imaging, medical imaging, and a robot or vehicle guidance. In this paper, various state-of-art image fusion methods of diverse levels with their pros and cons, various spatial and transform based method with quality metrics and their applications in different domains have been discussed. Finally, this review has concluded various future directions for different applications of image fusion.

The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb−1, collected with the CMS detector at the CERN LHC, at $$ \sqrt{s} $$ s = 13 TeV. The hidden sector is hypothesized to couple to the standard model (SM) via a heavy leptophobic Z′ mediator produced as a resonance in proton-proton collisions. The mediator decay results in two “semivisible” jets, containing both visible matter and invisible dark matter. The final state therefore includes moderate missing energy aligned with one of the jets, a signature ignored by most dark matter searches. No structure in the dijet transverse mass spectra compatible with the signal is observed. Assuming the Z′ boson has a universal coupling of 0.25 to the SM quarks, an inclusive search, relevant to any model that exhibits this kinematic behavior, excludes mediator masses of 1.5–4.0 TeV at 95% confidence level, depending on the other signal model parameters. To enhance the sensitivity of the search for this particular class of hidden sector models, a boosted decision tree (BDT) is trained using jet substructure variables to distinguish between semivisible jets and SM jets from background processes. When the BDT is employed to identify each jet in the dijet system as semivisible, the mediator mass exclusion increases to 5.1 TeV, for wider ranges of the other signal model parameters. These limits exclude a wide range of strongly coupled hidden sector models for the first time.

No abstract

Workflow scheduling concerns the mapping of complex tasks to cloud resources by taking into account various Quality of Service requirements. In virtue of continuous proliferation in the exploration of cloud computing, it has become stringent to find the proper scheduling scheme for the execution of workflow under user specifications. Moreover, till date, there exists no systematic review of the existing numerous techniques for this NP-complete problem in the cloud. Taking this into account, the present study seeks to address this gap and spotlights the comprehensive taxonomy of various scheduling schemes as well as extensively compares them by illuminating their objectives, features, merits, and demerits. This paper also highlights the future research challenges with an aim to foster more research in the realm of workflow scheduling as an optimization task.

No abstract