Simulation of Filament Heater for Uniform Emission from Dispenser Cathode

This paper presents the design study of toroid shape filament heater for dispenser cathode.The filament heater will be used in cathode assembly of 200 kW 42 GHz gyrotron. A 3 D model of cathode assembly is designed using electromagnetic and thermal simulation software, ANSYS. The simulations are performed for optimizing the input filament heater power with respect to cathode surface temperature. The parametric study shows that the input power and cathode surface temperature depends strongly on the potting material, diameter of filament, number of turns, position and height of the filament heater with respect to cathode pellet. The design analyses are also carried out for two different filament heater materials i.e. tungsten and molybdenum. Further, the thermal, structural and transient analyses are also carried out to study the mechanical strength of the filament heater. It is concluded that the input heater power should be greater than 200 W to achieve cathode surface temperature greater than 1,000°C.     

Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

Dynamic provisioning in multi-tenant service clouds

Cloud-based systems promise an on-demand service provisioning system along with a ??pay-as-you-use?? policy. In the case of multi-tenant systems this would mean dynamic creation of a tenant by integrating existing cloud-based services on the fly. Presently, dynamic creation of a tenant is handled by building the required components from scratch. Although multi-tenant systems help providers save cost by allocating multiple tenants to the same instance of an application, they incur huge reconfiguration costs. Cost and time spent on these reconfiguration activities can be reduced by re-constructing tenants from existing tenant configurations supported by service providers. Multi-tenant cloud-based systems also lack the facility of allowing clients to specify their requirements. Giving clients the flexibility to specify requirements helps them avoid spending an excessive amount of time and effort looking through a list of services, many of which might not be relevant to them. Moreover, dynamic provisioning in the cloud requires an integrated solution across the technology stack (software, platform and infrastructure) combining functional, non-functional and resource allocation requirements. Existing research works in the area of web service matching, although numerous, still fall short, since they usually consider each requirement type in isolation and cannot provide an integrated solution. To that end, in this paper we investigate the features needed for dynamic service provisioning on the cloud. We propose a novel User Interface-Tenant Selector-Customizer (UTC) model and approach, which enables cloud-based services to be systematically modeled and provisioned as variants of existing service tenants in the cloud. Our approach considers functional, non-functional and resource allocation requirements, which are explicitly specified by the client via the user interface component of the model. To the best of our knowledge, ours is the first such integrated approach. We illustrate our ideas using a realistic running example, and also present a proof-of-concept prototype built using IBM??s Rational Software Architect modeling tool. We also present experimental results demonstrating the applicability of our matching algorithm. Our results show significant reduction in matching time with the help of an elimination process that reduces the search space needed for performing matching.     

Region-Based Hierarchical Image Matching

This paper presents an approach to region-based hierarchical image matching, where, given two images, the goal is to identify the largest part in image 1 and its match in image 2 having the maximum similarity measure defined in terms of geometric and photometric properties of regions (e.g., area, boundary shape, and color), as well as region topology (e.g., recursive embedding of regions). To this end, each image is represented by a tree of recursively embedded regions, obtained by a multiscale segmentation algorithm. This allows us to pose image matching as the tree matching problem. To overcome imaging noise, one-to-one, many-to-one, and many-to-many node correspondences are allowed. The trees are first augmented with new nodes generated by merging adjacent sibling nodes, which produces directed acyclic graphs (DAGs). Then, transitive closures of the DAGs are constructed, and the tree matching problem reformulated as finding a bijection between the two transitive closures on DAGs, while preserving the connectivity and ancestor-descendant relationships of the original trees. The proposed approach is validated on real images showing similar objects, captured under different types of noise, including differences in lighting conditions, scales, or viewpoints, amidst limited occlusion and clutter.     

Mirror uncertainty and uniqueness conditions for determining shape and motion from orthographic projection

This paper presents new forms of necessary and sufficient conditions for determining shape and motion to within a mirror uncertainty from monocular orthographic projections of any number of point trajectories over any number of views. The new forms of conditions use image data only and can therefore be employed in any practical algorithms for shape and motion estimation. We prove that the mirror uncertainty for the three view problem also exists for a long sequence: if shapeS is a solution, so is its mirror imageS which is symmetric toS about the image plane. The necessary and sufficient conditions for determining the two sets of solutions are associated with the rank of the measurement matrixW.If the rank ofW is 3, then the original 3D scene points cannot be coplanar and the shape and motion can be determined to within a mirror uncertainty from the image data if and only if there are three distinct views. This condition is different from Ullman's theorem (which states thatthree distinct views of four noncoplanar points suffice to determine the shape and motion up to a reflection) in two aspects: (1) it is expressed in terms of image data; (2) it applies to a long image sequence in a homogeneous way.If the rank ofW is 2 and the image points in at least one view are not colinear in the image plane, then there are two possibilities: either the motion is around the optical axis, or the 3-D points all lie on the same plane. In the first case, the motion can be determined uniquely but the shape is not determined. In the second case, a necessary and sufficient condition is to be satisfied and at least 3 point trajectories over at least 3 distinct views are needed to determine the shape in each view to within a mirror uncertainty, and the number of motion solutions is equal to the combinatorial number of the possible positions of the plane in different views. The necessary and sufficient condition is associated with the rank of a matrixC: ifC has a rank of 1, the plane is undetermined; ifC has a rank of 2 (implying there are exactly 3 distinct views), then a necessary and sufficient condition, whose physical meaning is not completely clear, is to be satisfied to determine the plane to within 2 sets; ifC has a rank of 3 (implying there are 4 or more distinct views), then the plane can always be determined to within two sets.If the rank ofW is 2 or 1 and the image points in each view are colinear in the image plane, then the three dimensional motion problem reduces to a two dimensional motion problem. In this case, the uniqueness condition is associated with the rank of the reduced measurement matrix . If has a rank of 2, then the original 3D points cannot be colinear in the space and the shape and motion can be determined to within two sets if and only if three or more views are distinct. If has a rank of 1, there are two possibilities: if the rows of are identical, then either the original 3D points are not colinear and the motion is zero, or the points are colinear and possibly move between two mirror symmetric positions; if the rows of are not identical, then the motion is not determined.All proofs are constructive and thus define an algorithm for determining the uniqueness of solution as well as for estimating shape and motion from point trajectories.     

Robust Visual Tracking via Structured Multi-Task Sparse Learning

In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in Multi-Task Tracking (MTT). By employing popular sparsity-inducing $\ell _{p,q}$ mixed norms $(\text{ specifically} p\in \{2,\infty \}$ and $q=1),$ we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular $L_1$ tracker (Mei and Ling, IEEE Trans Pattern Anal Mach Intel 33(11):2259–2272, 2011) is a special case of our MTT formulation (denoted as the $L_{11}$ tracker) when $p=q=1.$ Under the MTT framework, some of the tasks (particle representations) are often more closely related and more likely to share common relevant covariates than other tasks. Therefore, we extend the MTT framework to take into account pairwise structural correlations between particles (e.g. spatial smoothness of representation) and denote the novel framework as S-MTT. The problem of learning the regularized sparse representation in MTT and S-MTT can be solved efficiently using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, S-MTT and MTT are computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that S-MTT is much better than MTT, and both methods consistently outperform state-of-the-art trackers.     

Notes on ensembles of IoT,network functions and clouds for service-oriented computing and applications

Many advances have been introduced recently for service-oriented computing and applications (SOCA). The Internet of Things (IoT) has been pervasive in various application domains. Fog/Edge computing models have shown techniques that move computational and analytics capabilities from centralized data centers where most enterprise business services have been located to the edge where most customer’s Things and their data and actions reside. Network functions between the edge and the cloud can be dynamically provisioned and managed through service APIs. Microservice architectures are increasingly used to simplify engineering, deployment and management of distributed services in not only cloud-based powerful machines but also in light-weighted devices. Therefore, a key question for the research in SOCA is how do we leverage existing techniques and develop new ones for coping with and supporting the changes of data and computation resources as well as customer interactions arising in the era of IoT and Fog/Edge computing. In this editorial paper, we attempt to address this question by focusing on the concept of ensembles for IoT, network functions and clouds.     

Solving a real-time allocation problem with constraint programming

In this paper, we present an original approach (CPRTA for “Constraint Programming for solving Real-Time Allocation”) based on constraint programming to solve a static allocation problem of hard real-time tasks. This problem consists in assigning periodic tasks to distributed processors in the context of fixed priority preemptive scheduling. CPRTA is built on dynamic constraint programming together with a learning method to find a feasible processor allocation under constraints. Two efficient new approaches are proposed and validated with experimental results. Moreover, CPRTA exhibits very interesting properties. It is complete (if a problem has no solution, the algorithm is able to prove it); it is non-parametric (it does not require specific tuning) thus allowing a large diversity of models to be easily considered. Finally, thanks to its capacity to explain failures, it offers attractive perspectives for guiding the architectural design process.     

Local search with constraint propagation and conflict-based heuristics

Search algorithms for solving csp (Constraint Satisfaction Problems) usually fall into one of two main families: local search algorithms and systematic algorithms. Both families have their advantages. Designing hybrid approaches seems promising since those advantages may be combined into a single approach. In this paper, we present a new hybrid technique. It performs a local search over partial assignments instead of complete assignments, and uses filtering techniques and conflict-based techniques to efficiently guide the search. This new technique benefits from both classical approaches: a priori pruning of the search space from filtering-based search and possible repair of early mistakes from local search. We focus on a specific version of this technique: tabu decision-repair. Experiments done on open-shop scheduling problems show that our approach competes well with the best highly specialized algorithms.