Ensemble Metropolis Light Transport

This article proposes a Markov Chain Monte Carlo ( MCMC ) rendering algorithm based on a family of guided transition kernels. The kernels exploit properties of ensembles of light transport paths, which are distributed according to the lighting in the scene, and utilize this information to make informed decisions for guiding local path sampling. Critically, our approach does not require caching distributions in world space, saving time and memory, yet it is able to make guided sampling decisions based on whole paths. We show how this can be implemented efficiently by organizing the paths in each ensemble and designing transition kernels for MCMC rendering based on a carefully chosen subset of paths from the ensemble. This algorithm is easy to parallelize and leads to improvements in variance when rendering a variety of scenes.

Screening of magnetic fields by superconducting and hybrid shields with circular cross-section

The use of superconducting (SC) materials is crucial for shielding quasi-static magnetic fields. However, the frequent requisite of space-saving solutions with high shielding performance requires the development of a 3D modelling procedure capable of predicting the screening properties for different orientations of the applied field. In this paper, we exploited a 3D numerical model based on a vector potential formulation to investigate the shielding ability of SC screens with cylindrical symmetry and a height/diameter aspect ratio close to unity, without and with the superimposition of a ferromagnetic (FM) circular shell. The chosen materials were MgB2 and soft iron. First, the calculation outcomes were compared with the experimental data obtained on different shielding arrangements, achieving a notable agreement in both axial-field (AF) and transverse-field (TF) orientations. Then, we used the thus validated modelling approach to investigate how the magnetic mitigation properties of a cup-shaped SC bulk can be improved by the superimposition of a coaxial FM cup. Calculations highlighted that the FM addition is very efficient in enhancing the shielding factors (SFs) in the TF orientation. Assuming a working temperature of 30 K and using a layout with the FM cup protruding over the SC one, shielding factors up to 8 times greater than those of the single SC cup were attained at low applied fields, reaching values equal or higher than 102 in the inner half of the shield. In the AF orientation, the same FM cup addition costs a modest worsening at low fields, but at the same time, it widens the applied field range, where SF ≥ 104 occurs near the close extremity of the shield, up over 1 T.

Optimal Compression of Remote Sensing Images Using Deep Learning during Transmission of Data

Industrial internet of things has grown quite popular in recent years and involves a large number of intelligent devices linked together to build a system that can investigate, communicate, gather and observe information. Due to this requirement, there is more demand for compression techniques which compresses data, leading to less usage of resources and low complexity. This is where Convolutional Neural Networks (CNN) play a large role in the field of computer vision, especially in places where high applications such as interpretation coupled with detection is required. Similarly, low-level applications such as image compression cannot be resolved using this methodology. In this paper, a compression technique for remote sensing images using CNN is proposed. This methodology incorporates CNN in a compact learning environment wherein the actual image that consists of structural data is coded using Lempel Ziv Markov chain algorithm. This process is followed by image reconstruction in order to obtain the actual image in high quality. Other methodologies such as optimized trunctiona, JPEG2000, JPEC and binary tree were compared using a large number of experiments in terms of space saving, reconstructed image quality and efficiency. The output obtained indicates that the proposed methodology shows effective improvement, attaining a 50 dB signal to noise ratio and space saving of 90%.

Comparative Study of Electric Machines for Stirling Generator Application

The choice of a machine for an application and a given specification remains a complex problem. This will involve, for example, bringing together criteria such as: performance, space saving, economical, reliable, little acoustic noise and others. The best machine selection to fulfill all constraints is an important step for the project to be realized. This work focus on Stirling Engine based Generator and study all types of rotating machines that can be employed for maximum electric power production. Analytical electromagnetic models where developed for all types of rotating machines that satisfied minimum requirement for the project by solving Maxwell equations. The purpose is to develop the design model and combine electromagnetic and thermal study of the machines. Finite Element Method is used to compare the performances of the generators for the best choice. Results show that for applications not requiring bigger output power, the major criteria for the selection is the optimal magnetic induction created by the inducer in the stationary part of the machine. For application such as Stirling generators, permanent magnet (PM) machine satisfy many comparison criteria such as maximum power at low speed, torque density, high efficiency. Beyond exposing a selection method for a project, this work lay down a step-by-step method for engineers and scientists for the crucial stage of design and conception work

Nonlinear soil-structure behavior of a deployable and compliant anchor system

This paper presents a novel compliant geo-structural systems bio-inspired by awns on grass seeds for increasing anchor capacity while minimizing material usage. A compliant deployable structure is here defined as a system that reacts to global displacements by continued elastic shape change and awns are slender flexible structures rigidly connected to the exterior of an anchor. When the anchor is loaded in tension, the awns react off the soil mass and deploy outwards from the pile shaft, enabling space-saving measures for transportation. This paper creates a structural pushover model to establish awn deformations and stress values, a scale model of the compliant system fabricated using additive manufacturing, geo-plasticity numerical models of soil awn interaction, and a finite element model of an example application. This research elucidates the soil displacement mechanisms around the awns, the structural deformation of individual awns, and the enhancement of overall anchor capacity due to awn deployment.

The Conceptualisation and Development of a Space-Saving Multipurpose Table for Enhanced Ergonomic Performance

Foldable furniture is a trend of the modern furniture industry. However, apart from limitations attributed to multifunctionality and space saving characteristics, a complete design process documentation of foldable furniture is uncommon in furniture research. This study aims to develop a space-saving multipurpose table for improved ergonomic performance. Features and functions are extracted from research articles and patents for concept generation. The final concept is modelled using Autodesk Inventor Professional 2019. Mechanical simulations are done to confirm the structural integrity of the invention before prototyping and testing. The tests accounted for usage efficiency, space and usability. Using Minitab 19, the experimental data are analysed with t-tests. The survey data are analysed using Spearman’s correlation test via IBM SPSS Statistics version 21. Participants were able to complete tasks around 1.1–1.5 times faster with the proposed invention than with single-function furniture items. The amount of space occupied with the proposed invention was approximately 25–80% lesser than with the single-function furniture items placed together. The survey analysis demonstrated that there was a strong, positive and significant correlation between space saving effectiveness and ergonomic performance. Further developments to transition this invention to its commercialisation phase should be done to facilitate daily living domestic activities of society at large.

The current state of research on energy communities

The introduction of the Clean energy for all Europeans package by the European Union (EU) led to a significant boost of public and research interest in energy communities. However, since neither their definition nor their goals are clearly defined, there is a very broad field of research on this topic. This paper aims to classify existing research on energy communities and to analyze what this umbrella term looks like in the literature. First, a literature review is conducted with regard to energy communities that have a local scope and are community-owned. The analysis of the results leads to the determination of the following categories for the existing literature on energy communities: the terminology used to refer to energy communities, components of energy communities, and their characteristics and structure. The review affirms that space-saving and easily constructible components are used the most, with photovoltaics (PV) and storage at the forefront. Our results also show that a third-party aggregator can be a vital part of an energy community with various functions, from managing the community’s energy flow and local market to trading energy with the grid. Taking this into consideration, we conclude that the use of aggregators is a good way to make the formation of energy communities easier, especially for people without an engineering background.

Compression for population genetic data through finite-state entropy

We improve the efficiency of population genetic file formats and GWAS computation by leveraging the distribution of samples in population-level genetic data. We identify conditional exchangeability of these data, recommending finite state entropy algorithms as an arithmetic code naturally suited for compression of population genetic data. We show between [Formula: see text] and [Formula: see text] speed and size improvements over modern dictionary compression methods that are often used for population genetic data such as Zstd and Zlib in computation and decompression tasks. We provide open source prototype software for multi-phenotype GWAS with finite state entropy compression demonstrating significant space saving and speed comparable to the state-of-the-art.

Effects of screen-responsive visualization on data comprehension

Visualization interfaces designed for heterogeneous devices such as wall displays and mobile screens must be responsive to varying display dimensions, resolution, and interaction capabilities. In this paper, we report on two user studies of visual representations for large versus small displays. The goal of our experiments was to investigate differences between a large vertical display and a mobile hand-held display in terms of the data comprehension and the quality of resulting insights. To this end, we developed a visual interface with a coordinated multiple view layout for the large display and two alternative designs of the same interface – a space-saving boundary visualization layout and an overview layout – for the mobile condition. The first experiment was a controlled laboratory study designed to evaluate the effect of display size on the perception of changes in a visual representation, and yielded significant correctness differences even while completion time remained similar. The second evaluation was a qualitative study in a practical setting and showed that participants were able to easily associate and work with the responsive visualizations. Based on the results, we conclude the paper by providing new guidelines for screen-responsive visualization interfaces.