5,602 research outputs found

    A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

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    In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

    Quadratic Projection Based Feature Extraction with Its Application to Biometric Recognition

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    This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes. We formulate quadratic matrix learning (QML) as a standard semidefinite programming (SDP) problem. However, the con- ventional interior-point SDP solvers do not scale well to the problem of QML for high-dimensional data. To solve the scalability of QML, we develop an efficient algorithm, termed DualQML, based on the Lagrange duality theory, to extract nonlinear features. To evaluate the feasibility and effectiveness of the proposed framework, we conduct extensive experiments on biometric recognition. Experimental results on three representative biometric recogni- tion tasks, including face, palmprint, and ear recognition, demonstrate the superiority of the DualQML-based feature extraction algorithm compared to the current state-of-the-art algorithm

    Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

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    Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal Systems Engineering (SE) practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the Value-Driven Design (VDD) methodology that has been developed for collaborative and iterative use in the Extended Enterprise (EE) within the aerospace industry, and that has been applied using the Concept Design Analysis (CODA) method to map captured Customer Needs (CNs) into Engineering Characteristics (ECs) and to model an overall ‘design merit’ metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace secto

    Shape from Shading through Shape Evolution

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    In this paper, we address the shape-from-shading problem by training deep networks with synthetic images. Unlike conventional approaches that combine deep learning and synthetic imagery, we propose an approach that does not need any external shape dataset to render synthetic images. Our approach consists of two synergistic processes: the evolution of complex shapes from simple primitives, and the training of a deep network for shape-from-shading. The evolution generates better shapes guided by the network training, while the training improves by using the evolved shapes. We show that our approach achieves state-of-the-art performance on a shape-from-shading benchmark

    Synthetic biology and microdevices : a powerful combination

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    Recent developments demonstrate that the combination of microbiology with micro-and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other technologies. In the last decade, there has been a shift from the optimization of the abiotic components, for example, the chip, to the improvement of the processing capabilities of cells through genetic engineering. The synthetic biology approach will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. To this end, the development of new genetic circuits has to be guided by computational design methods that enable to tune and optimize the circuit response. As the successful design of genetic circuits is highly dependent on the quality and reliability of its composing elements, intense characterization of standard biological parts will be crucial for an efficient rational design process in the development of new genetic circuits. Microengineered devices can thereby offer a new analytical approach for the study of complex biological parts and systems. By summarizing the recent techniques in creating new synthetic circuits and in integrating biology with microdevices, this review aims at emphasizing the power of combining synthetic biology with microfluidics and microelectronics

    Efficient global illumination calculation for inverse lighting problems

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    La luz es un elemento clave en la manera en que percibimos y experimentamos nuestro entorno. Como tal, es un objeto mas a modelar en el proceso de diseño, de forma similar a como ocurre con las formas y los materiales. Las intenciones de iluminacion (LI) son los objetivos y restricciones que el diseñador pretende alcanzar en el proceso del diseño de iluminaci´on: ¿qué superficies se deben iluminar con luz natural y cuales con luz artificial?, ¿qué zonas deben estar en sombra?, ¿cuales son las intensidades maximas y mínimas permitidas? Satisfacer las LI consiste en encontrar la ubicacion, forma e intensidad adecuada de las fuentes luminosas. Este tipo de problemas se define como un problema inverso de iluminacion (ILP) que se resuelve con tecnicas de optimizacion. En el contexto anterior, el objetivo de esta tesis consiste en proponer metodos eficientes para resolver ILP. Este objetivo es motivado por la brecha percibida entre los problemas habituales de diseño de iluminacion y las herramientas computacionales existentes para su resolucion. Las herramientas desarrolladas por la industria se especializan en evaluar configuraciones de iluminacion previamente diseñadas, y las desarrolladas por la academia resuelven problemas relativamente sencillos a costos elevados. Las propuestas cubren distintos aspectos del proceso de optimizacion, que van desde la formulacion del problema a su resolucion. Estan desarrolladas para el caso en que las superficies poseen reflexion e iluminacion difusas y se basan en el calculo de una aproximacion de rango bajo de la matriz de radiosidad. Algunos resultados obtenidos son: el calculo acelerado de la radiosidad de la escena en una unidad de procesamiento gr´afico (GPU); el uso de la heuristica \201Cvariable neighborhood search\201D (VNS) para la resolucion de ILP; el planteo de una estructura multinivel para tratar ILP de forma escalonada; y el uso de tecnicas para optimizar la configuracion de filtros de luz. Otros resultados obtenidos se basan en la formulacion de las LI en funcion de la media y desviacion estandar de las radiosidades halladas. Se propone un metodo para generar LI que contengan esos parametros estadisticos, y otro metodo para acelerar su evaluacion. Con estos resultados se logran tiempos de respuesta interactivos. Por último, las tecnicas anteriores adolecen de una etapa de pre-cómputo relativamente costosa, por tanto se propone acelerar el calculo de la inversa de la matriz de radiosidad a partir de una muestra de factores de forma. Los métodos aquí presentados fueron publicados en seis articulos, tres de ellos en congresos internacionales y tres en revistas arbitradas.Light is a key element that influences the way we perceive and experience our environment. As such, light is an object to be modeled in the design process, as happens with the forms and materials. The lighting intentions (LI) are the objectives and constraints that designers want to achieve in the process of lighting design: which surfaces should be illuminated with natural and which with artificial light?, which surfaces should be in shadow?, which are the maximum and minimum intensities allowed? The fulfillment of the LI consists in finding the location, shape and intensity appropriate for the light sources. This problem is defined as an inverse lighting problem (ILP), solved by optimization techniques. In the above context, the aim of this thesis is the proposal of efficient methods to solve ILP. This objective is motivated by the perceived gap between the usual problems of lighting design, and the computational tools developed for its resolution. The tools developed by the industry specialize in evaluating previously designed lighting configurations, and those developed by the academia solve relatively simple problems at a high computational cost. The proposals cover several aspects of the optimization process, ranging from the formulation of the problem to its resolution. They are developed for the case in which the surfaces have Lambertian reflection and illumination, and are based on the calculation of a low rank approximation to the radiosity matrix. Some results are: rapid calculation of radiosity of the scene in a graphics processing unit (GPU), the use of heuristics “variable neighborhood search” (VNS) for solving ILP, the proposition of a multilevel structure to solve ILP in a stepwise approach, and the use of these techniques to optimize the configuration of light filters. Other results are based on the formulation of LI that use the mean and standard deviation of the radiosity values found. A method is proposed for generating LI containing these parameters, and another method is developed to speed up their evaluations. With these results we achieve interactive response times. Finally, the above techniques suffer from a costly pre-computing stage and therefore, a method is proposed to accelerate the calculation of the radiosity inverse matrix based on a sample of the form factors. The methods presented here were published in six articles, three of them at international conferences and three in peer reviewed journals
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