Bayesian inference on group differences in multivariate categorical data

Multivariate categorical data are common in many fields. We are motivated by election polls studies assessing evidence of changes in voters opinions with their candidates preferences in the 2016 United States Presidential primaries or caucuses. Similar goals arise routinely in several applications, but current literature lacks a general methodology which combines flexibility, efficiency, and tractability in testing for group differences in multivariate categorical data at different---potentially complex---scales. We address this goal by leveraging a Bayesian representation which factorizes the joint probability mass function for the group variable and the multivariate categorical data as the product of the marginal probabilities for the groups, and the conditional probability mass function of the multivariate categorical data, given the group membership. To enhance flexibility, we define the conditional probability mass function of the multivariate categorical data via a group-dependent mixture of tensor factorizations, thus facilitating dimensionality reduction and borrowing of information, while providing tractable procedures for computation, and accurate tests assessing global and local group differences. We compare our methods with popular competitors, and discuss improved performance in simulations and in American election polls studies

Solar Control in Buidings with Large Glazed Surfaces : The Role of Internal Screens

A large part of new office buildings is characterized by extended external glazed surfaces, generally located without any care about orientation. Without a suitable solar control strategy, this fact implies a series of well-known problems: high-energy demand and consequent carbon dioxide emissions for HVAC, as well as thermal and luminous discomfort. Moreover, if the working room is large, the values of physical parameters influencing comfort are relevantly variable from point to point. The best way to control entering solar radiation is based on the use of external movable elements, such as slats or screens. However, in some winter periods, it would be appreciated to promote the collection of solar radiation in order to contribute to cover heating loads. In this case, the use of internal diffusing or redirecting elements (i.e., blinds or venetian curtains) is necessary to avoid glare phenomena. The physical properties of these elements influence the room thermal balance, and their temperatures influence indoor thermal comfort conditions, particularly for the nearest occupants. This work tries to identify, by means of computer simulations, optimal physical properties of some kinds of internal diffusing screens. A case study has been examined: it consists in a medium size office roo

natural ventilation level assessment in a school building by co2 concentration measures

Abstract This paper considers the topic of natural ventilation in school buildings that is faced not only for energy saving, but also for the fundamental exigency of the indoor comfort. This analysis is developed by measuring the concentration of carbon dioxide as a significant indicator of IAQ when pollution is mainly due to the presence of people. In this paper are presented the results of a monitoring campaign of the CO 2 levels carried on in classrooms. The measures show the criticality of IAQ with values often much higher than the limits specified by standard, but also the possibility to act effectively with the manual ventilation without excesses that could create comfort problems or waste of energy

Annual Performance Monitoring of a Demand Controlled Ventilation System in a University Library

Abstract Demand controlled ventilation (DCV) is an important opportunity to reduce energy requirement especially in presence of variable occupancy. An evaluation of the possible amount of the energy savings consequent this more flexible control strategy are here presented in a real application case. This refers to the case of an ancient building in Venice. A part of this building was recently transformed in a modern university library. By recording all the measured data from the supervisory system an analysis of the annual performance of the DCV system was carried on. The investigation has pointed out the possibility of remarkable energy savings without compromising internal comfort conditions

calculation procedure to improve the assessment of photovoltaic generation in solar maps

Abstract The Zero Energy Building (ZEB) target and the higher affordability of photovoltaic (PV) systems are pushing Governments and large Companies operating in electricity generation and distribution network management to develop tools able to better define the potential productivity of PV systems on a large scale, such as solar maps. However, solar maps mainly consider phenomena related to weather and geometry, with a low level of detail on second order effects. This research aims at the integration of additional technical aspects into solar maps, by means of diagrams able to increase the reliability in the assessment of potential electricity generation. For this purpose, more technical factors are taken into account, such as the variation of PV panel efficiency with cell temperature, the shadow cast by the preceding PV panel array, here including the action of by-pass diodes, and the ratio of active area over the area available for installation

Energy Retrofit in European Building Portfolios: A Review of Five Key Aspects

The research about energy efficiency in buildings has exponentially increased during the last few years. Nevertheless, both research and practice still cannot rely on complete methodologies tailored for building portfolios as a whole, because the attention has always been drawn to individual premises. Yet, energy efficiency analyses need to go beyond the single building perspective and incorporate strategic district approaches to optimize the retrofit investment. For this purpose, several aspects should be considered simultaneously, and new methodologies should also be promoted. Therefore, this paper aims to discuss energy retrofit campaigns in building portfolios, drawing an exhaustive and updated review about the challenge of jumping from the single-building perspective to a stock-based analysis. This research discusses the publications available on the topic from five key aspects that are all essential steps in achieving a complete and reliable study of energy efficiency at a portfolio level. They are energy modelling and assessment, energy retrofit design, decision-making criteria assessment, optimal allocation of (financial) resources and risk valuation. This review, therefore, advocates for joint consideration of the problem as a basis on which to structure further disciplinary developments. Research gaps are highlighted, and new directions for future research are suggested

A CNN-based fusion method for feature extraction from sentinel data

Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. A possible alternative is to benefit from weather-insensitive synthetic aperture radar (SAR) images. In many real-world applications, critical decisions are made based on some informative optical or radar features related to items such as water, vegetation or soil. Under cloudy conditions, however, optical-based features are not available, and they are commonly reconstructed through linear interpolation between data available at temporally-close time instants. In this work, we propose to estimate missing optical features through data fusion and deep-learning. Several sources of information are taken into account—optical sequences, SAR sequences, digital elevation model—so as to exploit both temporal and cross-sensor dependencies. Based on these data and a tiny cloud-free fraction of the target image, a compact convolutional neural network (CNN) is trained to perform the desired estimation. To validate the proposed approach, we focus on the estimation of the normalized difference vegetation index (NDVI), using coupled Sentinel-1 and Sentinel-2 time-series acquired over an agricultural region of Burkina Faso from May–November 2016. Several fusion schemes are considered, causal and non-causal, single-sensor or joint-sensor, corresponding to different operating conditions. Experimental results are very promising, showing a significant gain over baseline methods according to all performance indicators

development and testing of a platform aimed at pervasive monitoring of indoor environment and building energy

Abstract The interest of the building energy sector is leaning towards the measurement of building actual performance, as regards both indoor environment quality and energy consumption. Sensors and central elaboration units aimed at monitoring indoor environment and HVAC system parameters can also provide the basic infrastructure for further applications such as predictive and neuro-fuzzy controls. However, the cost of such systems is high, so they are mainly used in large buildings. This paper describes the main features and expected applications for a low-budget monitoring platform currently under development and tuning. In particular, the monitoring system was developed based on electronic prototyping platform Arduino and on sensors and devices usually available in the retail market of electronics. The monitoring platform has been designed with the following characteristics in mind: replicability, full remote control, portability, versatility, reliability and affordability

application of artificial neural networks to the simulation of a dedicated outdoor air system doas

Abstract Tables of performance of installed HVAC (Heating, Ventilation and Air Conditioning) devices are important in the development of consistent building energy audits and appropriate control strategies. However, given the possible complexity of HVAC devices and the need for the deployment to computational environments, tables of performance should be passed in a more complete and flexible format, compared with the current practices in the HVAC sector. In such a context, this paper describes the phases of development and application of Artificial Neural Networks (ANNs) aimed at the assessment of the performance of a Dedicated Outdoor Air System (DOAS). ANNs are well renowned because of their applications in many important fields such as autonomous driving systems, speech recognition, etc. However, they may be used also to calculate the output of complex phenomena (like the ones involved in HVAC components) and are characterized by a very flexible and comprehensive formulation which would be able to adapt to any HVAC component or system. In the frame of this study, three ANNs have been developed and tested, for the full description of the performance of a DOAS. The developed ANNs were trained by means of data coming from a proprietary software. The achieved ANNs showed robust and reliable behavior and ensure high accuracy (mean absolute errors usually below 0.1 K on temperatures and 0.3% on capacity and power) and flexibility. Moreover, in some cases, they may be used also for the identification of anomalous data present among the sets of training and validation data

Urban Covered Courtyards in Mediterranean Climates : a method for optimizing environmental control strategy

Covering urban courtyards allows you to create interesting public or semi-public spaces, sheltered from bad weather and possibly with a controlled climate. In addition, the use of a transparent or semi-transparent roof allows you to take advantage of natural lighting. The use of this type of roof is a common solution in the countries of central and northern Europe, but difficult to apply in Mediterranean temperate climates, because it would cause overheating for a good part of the year. This unless appropriate solar control strategies. In this work, a case study was taken into consideration. It is the courtyard of a former Venetian convent. With reference to it, some types of partially transparent roofing and some solar control strategies were compared by means of computer simulations. The various solutions were compared from the point of view of visual and thermal comfort, as well as from that of primary energy demand for supplementary artificial lighting and possible energy demand for heating, ventilation and air conditioning if the relative system is present. Given the diffusion of this type of courtyards in the Italian territory, its thermal and luminous behavior has also been simulated in the warmer climate of Palermo. Simulation’s results show that the better solutions are those based on the use of dynamic solar control devices