A Comprehensive Review of the State-of-the-Art of Secondary Control Strategies for Microgrids

The proliferation of distributed energy resources in distribution systems has given rise to a new concept known as Microgrids (MGs). The effective control of MGs is a crucial aspect that needs to be prioritized before undertaking any implementation procedure. This article provides a comprehensive overview of hierarchical control methods that ensure efficient and robust control for MGs. Specifically, it focuses on the secondary controller approaches (centralized, distributed, and decentralized control) and examines their primary strengths and weaknesses. The techniques are thoroughly discussed, deliberated, and compared to facilitate a better understanding. According to functionality, the hierarchical-based control scheme is allocated into three levels: primary, secondary, and tertiary. For secondary control level, the MG communication structures permit the usage of various control methods that provided the significance of the secondary controller for consistent and reliable MG performance and the deficiency of an inclusive recommendation for scholars. Also, it gives a review of the literature on present important matters related to MG secondary control approaches in relation to the challenges of communication systems. The problem of the secondary level control is deliberated with an emphasis on challenges like delays. Further, at the secondary layer, the distributed control techniques for reducing communication system utilization and then reducing communication system delays are conferred. Furthermore, the benefits and limitations of various control structures, such as centralized, decentralized, and distributed are also discusses in this study. Later a comparative analysis of entire control approaches, the best methods of control according to the author's perspective are also discussed

Computational pathology: Exploring the spatial dimension of tumor ecology.

Tumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment

Precise foreground detection algorithm using motion estimation, minima and maxima inside the foreground object

In this paper the precise foreground mask is obtained in a complex environment by applying simple and effective methods on a video sequence consisting of multi-colour and multiple foreground object environment. To detect moving objects we use a simple algorithm based on block-based motion estimation, which requires less computational time. To obtain a full and improved mask of the moving object, we use an opening-and-closing-by- reconstruction mechanism to identify the minima and maxima inside the foreground object by applying a set of morphological operations. This further enhances the outlines of foreground objects at various stages of image processing. Therefore, the algorithm does not require the knowledge of the background image. That is why it can be used in real world video sequences to detect the foreground in cases where we do not have a background model in advance. The comparative performance results demonstrate the effectiveness of the proposed algorithm.The Institute of Management Sciences Peshawar (http://imsciences.edu.pk/) through Higher Education Commission Islamabad, Pakistan (http://hec.gov.pk/)

How frequent are close supermassive binary black holes in powerful jet sources?

24 pages, 36 figures. © 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)Supermassive black hole binariesmay be detectable by an upcoming suite of gravitationalwave experiments. Their binary nature can also be revealed by radio jets via a short-period precession driven by the orbital motion as well as the geodetic precession at typically longer periods. We have investigated Karl G. Jansky Very Large Array and Multi-Element Radio Linked Interferometer Network (MERLIN) radio maps of powerful jet sources for morphological evidence of geodetic precession. For perhaps the best-studied source, Cygnus A, we find strong evidence for geodetic precession. Projection effects can enhance precession features, for which we find indications in strongly projected sources. For a complete sample of 33 3CR radio sources, we find strong evidence for jet precession in 24 cases (73 per cent). The morphology of the radio maps suggests that the precession periods are of the order of 10 6- 10 7 yr. We consider different explanations for the morphological features and conclude that geodetic precession is the best explanation. The frequently observed gradual jet angle changes in samples of powerful blazars can be explained by orbital motion. Both observations can be explained simultaneously by postulating that a high fraction of powerful radio sources have subparsec supermassive black hole binaries.We consider complementary evidence and discuss if any jetted supermassive black hole with some indication of precession could be detected as individual gravitational wave source in the near future. This appears unlikely, with the possible exception of M87.Peer reviewedFinal Published versio

Jet-intracluster medium interaction in hydra A - II. The effect of jet precession

We present three-dimensional relativistic hydrodynamical simulations of a precessing jet interacting with the intracluster medium and compare the simulated jet structure with the observed structure of the Hydra A northern jet. For the simulations, we use jet parameters obtained in the parameter space study of the first paper in this series and probe different values for the precession period and precession angle. We find that for a precession period P ≈ 1 Myr and a precession angle ψ ≈ 20°, the model reproduces (i) the curvature of the jet, (ii) the correct number of bright knots within 20 kpc at approximately correct locations and (iii) the turbulent transition of the jet to a plume. The Mach number of the advancing bow shock ≈1.85 is indicative of gentle cluster atmosphere heating during the early stages of the AGN's activity

Measuring the Accuracy of Object Detectors and Trackers

The accuracy of object detectors and trackers is most commonly evaluated by the Intersection over Union (IoU) criterion. To date, most approaches are restricted to axis-aligned or oriented boxes and, as a consequence, many datasets are only labeled with boxes. Nevertheless, axis-aligned or oriented boxes cannot accurately capture an object's shape. To address this, a number of densely segmented datasets has started to emerge in both the object detection and the object tracking communities. However, evaluating the accuracy of object detectors and trackers that are restricted to boxes on densely segmented data is not straightforward. To close this gap, we introduce the relative Intersection over Union (rIoU) accuracy measure. The measure normalizes the IoU with the optimal box for the segmentation to generate an accuracy measure that ranges between 0 and 1 and allows a more precise measurement of accuracies. Furthermore, it enables an efficient and easy way to understand scenes and the strengths and weaknesses of an object detection or tracking approach. We display how the new measure can be efficiently calculated and present an easy-to-use evaluation framework. The framework is tested on the DAVIS and the VOT2016 segmentations and has been made available to the community.Comment: 10 pages, 7 Figure

Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer.

BACKGROUND:Despite treatment advances, there remains a significant risk of recurrence in ovarian cancer, at which stage it is usually incurable. Consequently, there is a clear need for improved patient stratification. However, at present clinical prognosticators remain largely unchanged due to the lack of reproducible methods to identify high-risk patients. METHODS:In high-grade serous ovarian cancer patients with advanced disease, we spatially define a tumour ecological balance of stromal resource and immune hazard using high-throughput image and spatial analysis of routine histology slides. On this basis an EcoScore is developed to classify tumours by a shift in this balance towards cancer-favouring or inhibiting conditions. FINDINGS:The EcoScore provides prognostic value stronger than, and independent of, known risk factors. Crucially, the clinical relevance of mutational burden and genomic instability differ under different stromal resource conditions, suggesting that the selective advantage of these cancer hallmarks is dependent on the context of stromal spatial structure. Under a high resource condition defined by a high level of geographical intermixing of cancer and stromal cells, selection appears to be driven by point mutations; whereas, in low resource tumours featured with high hypoxia and low cancer-immune co-localization, selection is fuelled by aneuploidy. INTERPRETATION:Our study offers empirical evidence that cancer fitness depends on tumour spatial constraints, and presents a biological basis for developing better assessments of tumour adaptive strategies in overcoming ecological constraints including immune surveillance and hypoxia

Poster abstract: Bridge structural monitoring through a vibration energy harvesting wireless sensor network

Structural monitoring applications such as corrosion assessment, measurement of concrete temperature or moisture content of critical bridge structures can greatly benefit from the use of wireless sensor networks (WSNs), however energy harvesting for the operation of the network remains a challenge in this setting. We present a multihop vibration-based energy harvesting WSN system for bridge monitoring applications. Our preliminary simulation experiments show that the system is able to maintain energy neutral operation over time, preserving energy with careful management of sleep and communication times.Engineering and Physical Sciences Research Council Innovation and Knowledge Centre for Smart Infrastructure and Construction project (Grant ID: EP/K000314/1)This is the author accepted manuscript. The final version is available from the Association for Computing Machinery via https://doi.org/10.1145/2993422.299640

Energy neutral operation of vibration energy-harvesting sensor networks for bridge applications

greatly benefit from the use of wireless sensor networks (WSNs), however energy harvesting for the operation of the network remains a challenge in this setting. While solar and wind power are possible and credible solutions to energy generation, the need for positioning sensor nodes in shaded and sheltered locations, e.g., under a bridge deck, is also often precluding their adoption in real-world deployments. In some scenarios vibration energy harvesting has been shown as an effective solution, instead. This paper presents a multihop vibration energy-harvesting WSN system for bridge applications. The system relies on an ultra-low power wireless sensor node, driven by a novel vibration based energy-harvesting technology. We use a receiver-initiated routing protocol to enable energy-efficient and reliable connectivity between nodes with different energy charging capabilities. By combining real vibration data with an experimentally validated model of the vibration energy harvester, a hardware model, and the COOJA simulator, we develop a framework to conduct realistic and repeatable experiments to evaluate the system before on-site deployment. Simulation results show that the system is able to maintain energy neutral operation, preserving energy with careful management of sleep and communication times. We also validate the system through a laboratory experiment on real hardware against real vibration data collected from a bridge. Besides providing general guidelines and considerations for the development of vibration energy-harvesting systems for bridge applications, this work highlights the limitations of the energy budget made available by traffic-induced vibrations, which clearly shrink the applicability of vibration energy-harvesting technology for WSNs to applications that do not generate an overwhelming amounts of data

1-Phenyl-1H-naphtho­[1,2-e][1,3]oxazin-3(2H)-one

In the title compound, C18H13NO2, the naphthalene (r.m.s. deviation = 0.025 Å) and benzaldehyde (r.m.s. deviation = 0.006 Å) groups are oriented at a dihedral angle of 89.48 (4)°. The oxazine group is oriented at dihedral angles of 13.36 (4) and 85.08 (5)°, respectively, with respect to the naphthalene and benzaldehyde fragments. In the crystal, inversion dimers linked by pairs of C—H⋯O hydrogen bonds generate R 2 2(8) loops. The dimers are linked into [010] chains via N—H⋯O hydrogen bonds. Weak C—H⋯π links and aromatic π–π stacking between the centroids of the naphthalene phenyl rings [centroid–centroid separation = 3.5977 (8) Å] help to consolidate the packing