Scenarios for the Development of Smart Grids in the UK: Synthesis Report

Building on extensive expert feedback and input, this Research Report describes four smart grid scenarios which consider how the UK' electricity system might develop to 2050. The scenarios outline how political decisions, as well as those made in regulation, finance, technology, consumer and social behaviour, market design or response, might affect the decisions of other actors and limit or allow the availability of future options

Scenarios for the Development of Smart Grids in the UK: Literature Review

This Working Paper reviews the existing literature on the socio-technical aspects of smart grid development. This work was undertaken as part of the Scenarios for the Development of Smart Grids in the UK project

The effect of object perception on event integration and segregation

The perceptual system must integrate information from various points in time and space to interpret continuous sensory input into meaningful units, such as visual objects or events. To explore the relationship between the perception of spatial objects and temporal events, we modified the missing element task, a typical temporal integration task, by inserting a simple spatial object. The aim was to determine whether the perceptual processing of the object would have an impact on the frequency of temporal integration and segregation. Temporal integration was most successful when the missing element was located within the object, less successful when there was no object, and least successful when the missing element appeared outside the object. The advantage of the location of the missing element within the object was observed at display durations from 30 ms to 150 ms. Interestingly, the object provided the same benefit for integration and segregation despite their opposing perceptual demands. This study demonstrates the relationship that exists between the processing of temporal events and spatial objects, and shows how such spatial information can facilitate temporal integration.</p

Determination of a suitable low-dose abdominopelvic CT protocol using model-based iterative reconstruction through cadaveric study.

Introduction: Cadaveric studies provide a means of safely assessing new technologies and optimizing scanning prior to clinical validation. Reducing radiation exposure in a clinical setting can entail incremental dose reductions to avoid missing important clinical findings. The use of cadavers allows assessment of the impact of more substantial dose reductions on image quality. Our aim was to identify a suitable low‐dose abdominopelvic CT protocol for subsequent clinical validation. Methods: Five human cadavers were scanned at one conventional dose and three low‐dose settings. All scans were reconstructed using three different reconstruction algorithms: filtered back projection (FBP), hybrid iterative reconstruction (60% FBP and 40% adaptive statistical iterative reconstruction (ASIR40)), and model‐based iterative reconstruction (MBIR). Two readers rated the image quality both quantitatively and qualitatively. Results: Model‐based iterative reconstruction images had significantly better objective image noise and higher qualitative scores compared with both FBP and ASIR40 images at all dose levels. The greatest absolute noise reduction, between MBIR and FBP, of 34.3 HU (equating to a 68% reduction) was at the lowest dose level. MBIR reduced image noise and improved image quality even in CT images acquired with a mean radiation dose reduction of 62% compared with conventional dose studies reconstructed with ASIR40, with lower levels of objective image noise, superior diagnostic acceptability and contrast resolution, and comparable subjective image noise and streak artefact scores. Conclusion: This cadaveric study demonstrates that MBIR reduces image noise and improves image quality in abdominopelvic CT images acquired with dose reductions of up to 62%

Ethical approaches and their application in hotel manager's decision making

This study aims at evaluating the ethical approaches effective for managers working at hotel business when making decisions. Ethics, in the working place, refers to the rules of the workplace that an employee has to comply with, along with the rules of society. In the study, the concept of ethics has been examined within theories of ethics, followed by a conceptual framework of making ethical decisions. The scope of the study consists of interviews conducted with 60 managers working in a chain hotel. The interview consists of 5 different scenarios relating to ethical dilemmas. The scenarios are composed of three different ethics approaches (moral justice approach, subjective approach and contract -based theoretical approach). In the analysis of the data, the Manova Analysis was carried out. The results suggest that managers prefer the contract -based theoretical approach more frequently in decision making. It was also found that managers differ in their choice of ethical approaches in terms of the scenarios. This difference is caused by subjective approaches which are used when dealing with problems related to socio-cultural and institutional reputation and ecology

Semi-Automated 3D Registration for Heterogeneous Unmanned Robots Based on Scale Invariant Method

This paper addresses the problem of 3D registration of outdoor environments combining heterogeneous datasets acquired from unmanned aerial (UAV) and ground (UGV) vehicles. In order to solve this problem, we introduced a novel Scale Invariant Registration Method (SIRM) for semi-automated registration of 3D point clouds. The method is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, the SIRM does not require having a good initial overlap between two heterogeneous datasets. Our method strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous datasets and harsh outdoor environments) and fully manual registration approaches (which are labour-intensive). The experimental validation of the proposed 3D heterogeneous registration system was performed on large-scale datasets representing unstructured and harsh outdoor environments, demonstrating the potential and benefits of the proposed 3D registration system in real-world environments

3D registration and integrated segmentation framework for heterogeneous unmanned robotic systems

The paper proposes a novel framework for registering and segmenting 3D point clouds of large-scale natural terrain and complex environments coming from a multisensor heterogeneous robotics system, consisting of unmanned aerial and ground vehicles. This framework involves data acquisition and pre-processing, 3D heterogeneous registration and integrated multi-sensor based segmentation modules. The first module provides robust and accurate homogeneous registrations of 3D environmental models based on sensors' measurements acquired from the ground (UGV) and aerial (UAV) robots. For 3D UGV registration, we proposed a novel local minima escape ICP (LME-ICP) method, which is based on the well known iterative closest point (ICP) algorithm extending it by the introduction of our local minima estimation and local minima escape mechanisms. It did not require any prior known pose estimation information acquired from sensing systems like odometry, global positioning system (GPS), or inertial measurement units (IMU). The 3D UAV registration has been performed using the Structure from Motion (SfM) approach. In order to improve and speed up the process of outliers removal for large-scale outdoor environments, we introduced the Fast Cluster Statistical Outlier Removal (FCSOR) method. This method was used to filter out the noise and to downsample the input data, which will spare computational and memory resources for further processing steps. Then, we co-registered a point cloud acquired from a laser ranger (UGV) and a point cloud generated from images (UAV) generated by the SfM method. The 3D heterogeneous module consists of a semi-automated 3D scan registration system, developed with the aim to overcome the shortcomings of the existing fully automated 3D registration approaches. This semi-automated registration system is based on the novel Scale Invariant Registration Method (SIRM). The SIRM provides the initial scaling between two heterogenous point clouds and provides an adaptive mechanism for tuning the mean scale, based on the difference between two consecutive estimated point clouds' alignment error values. Once aligned, the resulting homogeneous ground-aerial point cloud is further processed by a segmentation module. For this purpose, we have proposed a system for integrated multi-sensor based segmentation of 3D point clouds. This system followed a two steps sequence: ground-object segmentation and color-based region-growing segmentation. The experimental validation of the proposed 3D heterogeneous registration and integrated segmentation framework was performed on large-scale datasets representing unstructured outdoor environments, demonstrating the potential and benefits of the proposed semi-automated 3D registration system in real-world environments

Tumors of the labial mucosa:a retrospective study of 1045 biopsies

To investigate the relative frequency of localized mucosal swellings of the upper and lower labial mucosa, the clinical-pathological diagnosis agreement and whether patient?s age and gender and tumor?s site and size may raise the suspicion of neoplasm. Retrospective analysis was performed on upper or lower labial mucosal tumors, histopathologically diagnosed between 2009-2018. The diagnostic categories developmental/reactive tumors, benign and malignant neoplasms were associated with patient?s age and gender and tumor?s site and size; clinical-pathological diagnosis agreement was, also, evaluated. Overall, 1000 (95.7%) developmental/reactive tumors, 35 (3.3%) benign and 10 (1%) malignant neoplasms were found. Upper/lower lip tumor ratio was 0.14:1. The diagnostic category was significantly associated with age (p1cm were independent predictors for neoplasms. Patients presenting 2 or 3 of these variables were 20.2 times (p?1cm in patients?60 years have significantly higher probability to be neoplasms