Motion Recovery by Integrating over the Joint Image Manifold

Recovery of epipolar geometry is a fundamental problem in computer vision. The introduction of the “joint image manifold” (JIM) allows to treat the recovery of camera motion and epipolar geometry as the problem of fitting a manifold to the data measured in a stereo pair. The manifold has a singularity and boundary, therefore special care must be taken when fitting it. Four fitting methods are discussed—direct, algebraic, geometric, and the integrated maximum likelihood (IML) based method. The first three methods are the exact analogues of three common methods for recovering epipolar geometry. The more recently introduced IML method seeks the manifold which has the highest “support,” in the sense that the largest measure of its points are close to the data. While computationally more intensive than the other methods, its results are better in some scenarios. Both simulations and experiments suggest that the advantages of IML manifold fitting carry over to the task of recovering epipolar geometry, especially when the extent of the data and/or the motion are small.     

Direct recovery of planar-parallax from multiple frames

We present an algorithm that estimates dense planar-parallax motion from multiple uncalibrated views of a 3D scene. This generalizes the "plane+parallax" recovery methods to more than two frames. The parallax motion of pixels across multiple frames (relative to a planar surface) is related to the 3D scene structure and the camera epipoles. The parallax field, the epipoles, and the 3D scene structure are estimated directly from image brightness variations across multiple frames, without precomputing correspondences.     

Impact of planned water resource development on current and future water demand in the Koshi River basin,Nepal

The water resources of the Koshi Basin (87,311 km²) are largely untapped, and while proposals for their development exist, their impacts on current and future water demand are not quantified. The current study is the first to evaluate the impacts of 11 proposed development projects for hydropower generation and water storage. We find that 29,733 GWh of hydropower could be generated annually and 8382 million m³ of water could be stored. This could satisfy unmet demand in the current (660 million m³) basin situation and in future scenarios – i.e. population, agricultural and industrial growth – that are projected to have 920, 970 and 1003 million m³ of unmet demand, respectively, by 2050.     

An intelligent hybrid prairie dog optimization algorithm-based stable cluster reliable routing scheme for VANETs

Vehicular ad hoc network (VANET) is most significant for supporting intelligent transportation system (ITS)-based technologies, but it gets hurdled by sparse distribution of vehicles on highways, and dynamically challenging topology that arises due to increase in traffic. Hence, energy stable and optimized cluster construction maximizes the network lifetime. In this paper, Hybrid Prairie Dogs and Beluga Whale Optimization-based Node Clustering (HPDBWOA-NC) mechanism is proposed with the parameters of highway route, node velocity, number of vehicular nodes, and communication for achieving stable cluster construction in VANETs. It is proposed with the balanced exploration and exploitation potential of Prairie Dog Optimization Algorithm (PDOA) and Beluga Whale Optimization Algorithm (BWOA) for establishing optimal clusters that increase the network stability during the routing process. It integrated the exploration and exploitation capabilities of PDOA and BWOA and confirmed better optimized clusters which confirmed reliable data delivery by preventing the issue of premature convergence. It constructed clusters and selected cluster heads (CHs) depending on the fitness factors of energy, interdistance between vehicles, communication range, and vehicular density. The results of the proposed HPDBWOA-NC generated optimal number of CHs in the network which is comparatively 34.21% better than the benchmarked mechanisms. The mean throughput and packet delivery ratio (PDR) achieved by the proposed HPDBWOA-NC are identified to be significantly improved by 25.48% and 28.91% better than the investigated metaheuristic clustering protocols. The statistical study also guaranteed an increased factor of 81, during the processing of optimizing the clusters during the employment of ITS applications in VANETs.     

Hybrid Chameleon and Honey Badger Optimization Algorithm for QoS-Based Cloud Service Composition Problem

Cloud computing facilitates the great potentiality of storing and managing remote access to services in terms of software as a service (SaaS). Several organizations have moved towards outsourcing over the cloud to reduce the burden on local resources. In this context, the metaheuristic optimization method is determined to be highly suitable for selecting appropriate services that comply with the requirements of the client’s requests, as the services stored over the cloud are too complex and scalable. To achieve better service composition, the parameters of Quality of Service (QoS) related to each service considered to be the best resource need to be selected and optimized for attaining potential services over the cloud. Thus, the cloud service composition needs to concentrate on the selection and integration of services over the cloud to satisfy the client’s requests. In this paper, a Hybrid Chameleon and Honey Badger Optimization Algorithm (HCHBOA)-based cloud service composition scheme is presented for achieving efficient services with satisfying the requirements of QoS over the cloud. This proposed HCHBOA integrated the merits of the Chameleon Search Algorithm (CSA) and Honey Badger Optimization Algorithm (HBOA) for balancing the trade-off between the rate of exploration and exploitation. It specifically used HBOA for tuning the parameters of CSA automatically so that CSA could adapt its performance depending on its incorporated tuning factors. The experimental results of the proposed HCHBOA with experimental datasets exhibited its predominance by improving the response time by 21.38%, availability by 20.93% and reliability by 19.31% with a minimized execution time of 23.18%, compared to the baseline cloud service composition schemes used for investigation.     

Investigations on the mechanism of flame retardancy in HET acid containing unsaturated polyester resins

Unsaturated polyesters containing varying amounts of HET acid (1,4,5,6,7,7-hexachloro-5-norbornene-2,3-dicarboxylic acid) were synthesized and cured with styrene to give flame-retarding unsaturated polyester resins. The thermal properties were investigated by DTA (differential thermal analysis), TVA (thermal volatization analysis), SATVA (subambient thermal volatilization analysis), and weight loss measurements. The studies revealed that the reverse Diels–Alder reaction of the HET acid units present in the polyester backbone proceeds in the temperature range 300–350°C and yields hexachlorocyclopentadiene. The influence of the HET acid content on the mass distribution of the products of pyrolysis (450°C) was analyzed b means of a gas chromatograph coupled with a mass spectrometer. With increasing HET acid content, the total amount of aromatics evolved from the cured resins is decreased. Concurrently, the relative amount of styrene produced is decreased while the relative amounts of toluene and ethyl benzene are increased. This finding strongly suggests that the hexachlorocyclopentadiene interferes as a chain transfer agent with the unzipping reaction of the polystyrene chains. Further support for this interpretation is derived from the enhanced char formation with increasing HET acid content, as observed by the weight loss measurements.     

Effect of PostNitride Annealing on Wear and Corrosion Behavior of Titanium Alloy Ti-6Al-4V

Journal of Materials Engineering and Performance - Titanium alloy, Ti-6Al-4V, was plasma nitrided using RF plasma with 100% N at 800 °C and annealed at 850 °C in vacuum....     

Optimizing the functionalization process for nanopillar enhanced electrodes with GOx/PPY for glucose detection

In this study, the functionalization process for nanopillar enhanced electrodes (NEEs) using glucose oxidase (GOx) with polypyrrole (PPY) is optimized for the purpose of achieving enhanced sensing performances for these electrodes in glucose detection. Specifically, an optimal roughness factor for the NEEs and an optimal set of electro-polymerization/deposition parameters for their functionalization using GOx/PPY are identified. Results show that NEEs with a roughness factor of about 60 are optimal for enhancing the amperometric current responses and that for such electrodes an electro-functionalization/deposition process at a deposition current of 50?μA?cm(-2) and a total charge of 150?mC?cm(-2) will give rise to a high sensing performance with a sensitivity as high as 36?μA?cm(-2)?mM(-1).     

An efficient numerical analysis of starved thermohydrodynamically lubricated rolling line contacts

Effect of starvation in thermohydrodynamically lubricated high rolling speed line contacts has been investigated numerically by using an efficient numerical method in which temperature variations across the lubricant film is approximated by the second-order of Legendre polynomial. Mechanism of starvation at the contact has been set by creating gradual reduction in the length of the computational domain from the inlet side. In the solution, the lubricant has been assumed to be a Newtonian fluid. Minimum film thickness and rolling traction coefficient under fully flooded and starved conditions have been computed in this work. The rolling traction coefficient, minimum film thickness, and maximum mid film temperature rise in the starved line contact are found to be lesser than the fully flooded contact condition.