Energy efficiency and thermal comfort in historic buildings: A review

tThis is the author’s version of a work that was accepted for publication in . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable and Sustainable Energy Reviews Volume 61, August 2016, DOI 10.1016/j.rser.2016.03.018[EN] In recent years, energy efficiency and thermal comfort in historic buildings have become high-interest topics among scholars. Research has demonstrated that retrofitting buildings to current energy efficiency and thermal comfort standards is essential for improving sustainability and energy performance and for maintaining built heritage of historic structures. This study is an extensive overview of the literature surrounding this topic. This paper summarizes the different methods and techniques that have been used around the world to achieve performance refurbishments. Articles are organized based on the different building types used as case studies (residential, religious, academic and palace, museums, libraries and theaters, urban areas, and others). The results reveal that residential, religious and museum building types, especially from the last two centuries, have been most often used as case studies. Moreover, Europe, particularly Italy, is leading the research. The aim of this note is to demonstrate the feasibility of maintaining built heritage values of historic buildings while achieving significant improvements in their energy efficiency and thermal comfort.This paper has been developed as a result of a mobility stay funded by the Erasmus Mundus Programme of the European Commission under the Transatlantic Partnership for Excellence in Engineering - TEE Project.Martínez Molina, A.; Tort Ausina, I.; Cho, S.; Vivancos, J. (2016). Energy efficiency and thermal comfort in historic buildings: A review. Renewable and Sustainable Energy Reviews. 61:70-85. doi:10.1016/j.rser.2016.03.018S70856

Automatic Refactoring for Renamed Clones in Test Code

Unit testing plays an essential role in software development and maintenance, especially in Test-Driven Development. Conventional unit tests, which have no input parameters, often exercise similar scenarios with small variations to achieve acceptable coverage, which often results in duplicated code in test suites. Test code duplication hinders comprehension of test cases and maintenance of test suites. Test refactoring is a potential tool for developers to use to control technical debt arising due to test cloning. In this thesis, we present a novel tool, JTestParametrizer, for automatically refactoring method-scope renamed clones in test suites. We propose three levels of refactoring to parameterize type, data, and behaviour differences in clone pairs. Our technique works at the Abstract Syntax Tree level by extracting a parameterized template utility method and instantiating it with appropriate parameter values. We applied our technique to 5 open-source Java benchmark projects and conducted an empirical study on our results. Our technique examined 14,431 test methods in our benchmark projects and identified 415 renamed clone pairs as effective candidates for refactoring. On average, 65% of the effective candidates (268 clone pairs) in our test suites are refactorable using our technique. All of the refactored test methods are compilable, and 94% of them pass when executed as tests. We believe that our proposed refactorings generally improve code conciseness, reduce the amount of duplication, and make test suites easier to maintain and extend

Secure ADS-B: Towards Airborne Communications Security in the Federal Aviation Administration\u27s Next Generation Air Transportation System

The U.S. Congress has mandated that all aircraft operating within the National Airspace System, military or civilian, be equipped with ADS-B transponders by the year 2020. The ADS-B aircraft tracking system, part of the Federal Aviation Administration\u27s NextGen overhaul of the Air Transportation System, replaces Radar-based surveillance with a more accurate satellite-based surveillance system. However, the unencrypted nature of ADS-B communication poses an operational security risk to military and law enforcement aircraft conducting sensitive missions. The non-standard format of its message and the legacy communication channels used by its transponders make the ADS-B system unsuitable for traditional encryption mechanisms. FPE, a recent development in cryptography, provides the ability to encrypt arbitrarily formatted data without padding or truncation. Indeed, three new algorithms recommended by the NIST, may be suitable for encryption of ADS-B messages. This research assesses the security and hardware performance characteristics of the FF1, FF2, and FF3 algorithms, in terms of entropy of ciphertext, operational latency and resource utilization when implemented on a Field-Programmable Gate Array. While all of the algorithms inherit the security characteristics of the underlying AES block cipher, they exhibit differences in their performance profiles. Findings demonstrate that a Bump-in-the-Wire FPE cryptographic engine is a suitable solution for retrofitting encryption to ADS-B communication

Seismic retrofitting of substandard frame buildings using steel shear walls

The use of steel shear panels represents an effective strategy to enhance the seismic performance of substandard framed buildings not designed to resist earthquakes. The seismic response of framed structures equipped with steel walls can be predicted using finite element models with accurate shell elements for representing the steel panels. However, such a detailed numerical description requires significant computational resources, especially for nonlinear dynamic analysis of large retrofitted buildings with steel infill plates. Besides, the design of steel shear walls for seismic retrofitting has been addressed mainly by trial-and-error methods in previous research and practical applications. Therefore, there is a clear need for more simplified and efficient numerical models for accurate simulations of steel shear walls under earthquake loading and enhanced seismic retrofitting design procedures with automatic selection of the retrofitting components. In this research, an 8-noded macroelement formulation is first proposed incorporating six nonlinear springs with asymmetric constitutive relationships. To improve the macroelement performance, material parameters are calibrated via genetic algorithms (GAs) based on the numerical results from validated shell element models. Subsequently, simple functions for macroelement material parameters in terms of steel plate geometrical properties are determined using multiple linear regressions. Applications to numerical examples have confirmed the accuracy and computational efficiency of the proposed macroelement with calibrated material properties. An improved optimal seismic retrofitting design procedure utilising steel shear wall macroelements is developed based on the capacity spectrum method. The proposed approach regards the selection and design of infill plates as a multi-objective optimisation problem with constraints solved by GA procedures. Nonlinear regression for equivalent viscous damping of steel shear walls is also carried out to determine the hysteretic damping ratio as a function of plate dimensions and drift demand. Afterwards, the proposed optimal design strategy is applied to the seismic retrofitting of a deficient 4-storey RC frame building. Seismic assessment is finally conducted for the retrofitted structure, where a significant enhancement of the seismic performance is observed.Open Acces

From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The global population is aging; projections show that by 2050, more than 20% of the population will be aged over 64. This will lead to an increase in aging related illness, a decrease in informal support, and ultimately issues with providing care for these individuals. Assistive smart homes provide a promising solution to some of these issues. Nevertheless, they currently have issues hindering their adoption. To help address some of these issues, this study introduces a novel approach to implementing assistive smart homes. The devised approach is based upon an intention recognition mechanism incorporated into an intelligent agent architecture. This approach is detailed and evaluated. Evaluation was performed across three scenarios. Scenario 1 involved a web interface, focusing on testing the intention recognition mechanism. Scenarios 2 and 3 involved retrofitting a home with sensors and providing assistance with activities over a period of 3 months. The average accuracy for these three scenarios was 100%, 64.4%, and 83.3%, respectively. Future will extend and further evaluate this approach by implementing advanced sensor-filtering rules and evaluating more complex activities

CUP: Comprehensive User-Space Protection for C/C++

Memory corruption vulnerabilities in C/C++ applications enable attackers to execute code, change data, and leak information. Current memory sanitizers do no provide comprehensive coverage of a program's data. In particular, existing tools focus primarily on heap allocations with limited support for stack allocations and globals. Additionally, existing tools focus on the main executable with limited support for system libraries. Further, they suffer from both false positives and false negatives. We present Comprehensive User-Space Protection for C/C++, CUP, an LLVM sanitizer that provides complete spatial and probabilistic temporal memory safety for C/C++ program on 64-bit architectures (with a prototype implementation for x86_64). CUP uses a hybrid metadata scheme that supports all program data including globals, heap, or stack and maintains the ABI. Compared to existing approaches with the NIST Juliet test suite, CUP reduces false negatives by 10x (0.1%) compared to the state of the art LLVM sanitizers, and produces no false positives. CUP instruments all user-space code, including libc and other system libraries, removing them from the trusted code base

An overview of ciao and its design philosophy

We provide an overall description of the Ciao multiparadigm programming system emphasizing some of the novel aspects and motivations behind its design and implementation. An important aspect of Ciao is that, in addition to supporting logic programming (and, in particular, Prolog), it provides the programmer with a large number of useful features from different programming paradigms and styles and that the use of each of these features (including those of Prolog) can be turned on and off at will for each program module. Thus, a given module may be using, e.g., higher order functions and constraints, while another module may be using assignment, predicates, Prolog meta-programming, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of optimizations (including automatic parallelization). Such optimizations produce code that is highly competitive with other dynamic languages or, with the (experimental) optimizing compiler, even that of static languages, all while retaining the flexibility and interactive development of a dynamic language. This compilation architecture supports modularity and separate compilation throughout. The environment also includes a powerful autodocumenter and a unit testing framework, both closely integrated with the assertion system. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in a single journal paper, pointing instead to previous Ciao literature

Advancing the Cyberinfrastructure for Smart Water Metering and Water Demand Modeling

With rapid growth of urban populations and limited water resources, achieving an appropriate balance between water supply capacity and residential water demand poses a significant challenge to water supplying agencies. With the recent emergence of smart metering technology, where water use can be monitored and recorded at high resolution (e.g., observations of water use every 5 seconds), most existing research has been aimed at providing water managers with detailed information about the water use behavior of their consumers and the performance of water using fixtures. However, replacing existing meters with smart meters is expensive, and effectively using data produced by smart meters can be a roadblock for water utilities that lack sophisticated information technology expertise. The research in this dissertation presents low cost, open source cyberinfrastructure aimed at addressing these challenges. Components developed include an open source algorithm for identifying and classifying water end use events from smart meter data, a low cost datalogging and computational device that enables existing water meters to collect high resolution data and compute end use information, and a detailed water demand model that uses end use event information to simulate residential water use at a municipality level. Using this cyberinfrastructure, we conducted a case study application in the cities of Logan and Providence, Utah. We tested the applicability of the disaggregation algorithm in quantifying water end uses for different meter sizes and types. We tested the datalogging computational device at a residential household and demonstrated collection, disaggregation, and transfer of high resolution flow data and classified events into a secure server. Finally, we demonstrated a water demand model that simulates the detailed water end uses of Logan’s residents using a combination of a set of representative water end use events and monthly billing data. Using the data we collected and the outputs from the model, we demonstrated opportunities for conserving water through improving the efficiency of water using fixtures and promoting behavior changes