Advanced Occupancy Measurement Using Sensor Fusion

With roughly about half of the energy used in buildings attributed to Heating, Ventilation, and Air conditioning (HVAC) systems, there is clearly great potential for energy saving through improved building operations. Accurate knowledge of localised and real-time occupancy numbers can have compelling control applications for HVAC systems. However, existing technologies applied for building occupancy measurements are limited, such that a precise and reliable occupant count is difficult to obtain. For example, passive infrared (PIR) sensors commonly used for occupancy sensing in lighting control applications cannot differentiate between occupants grouped together, video sensing is often limited by privacy concerns, atmospheric gas sensors (such as CO2 sensors) may be affected by the presence of electromagnetic (EMI) interference, and may not show clear links between occupancy and sensor values. Past studies have indicated the need for a heterogeneous multi-sensory fusion approach for occupancy detection to address the short-comings of existing occupancy detection systems. The aim of this research is to develop an advanced instrumentation strategy to monitor occupancy levels in non-domestic buildings, whilst facilitating the lowering of energy use and also maintaining an acceptable indoor climate. Accordingly, a novel multi-sensor based approach for occupancy detection in open-plan office spaces is proposed. The approach combined information from various low-cost and non-intrusive indoor environmental sensors, with the aim to merge advantages of various sensors, whilst minimising their weaknesses. The proposed approach offered the potential for explicit information indicating occupancy levels to be captured. The proposed occupancy monitoring strategy has two main components; hardware system implementation and data processing. The hardware system implementation included a custom made sound sensor and refinement of CO2 sensors for EMI mitigation. Two test beds were designed and implemented for supporting the research studies, including proof-of-concept, and experimental studies. Data processing was carried out in several stages with the ultimate goal being to detect occupancy levels. Firstly, interested features were extracted from all sensory data collected, and then a symmetrical uncertainty analysis was applied to determine the predictive strength of individual sensor features. Thirdly, a candidate features subset was determined using a genetic based search. Finally, a back-propagation neural network model was adopted to fuse candidate multi-sensory features for estimation of occupancy levels. Several test cases were implemented to demonstrate and evaluate the effectiveness and feasibility of the proposed occupancy detection approach. Results have shown the potential of the proposed heterogeneous multi-sensor fusion based approach as an advanced strategy for the development of reliable occupancy detection systems in open-plan office buildings, which can be capable of facilitating improved control of building services. In summary, the proposed approach has the potential to: (1) Detect occupancy levels with an accuracy reaching 84.59% during occupied instances (2) capable of maintaining average occupancy detection accuracy of 61.01%, in the event of sensor failure or drop-off (such as CO2 sensors drop-off), (3) capable of utilising just sound and motion sensors for occupancy levels monitoring in a naturally ventilated space, (4) capable of facilitating potential daily energy savings reaching 53%, if implemented for occupancy-driven ventilation control

Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings

Static analysis for facilitating secure and reliable software

Software security and reliability are aspects of major concern for software development enterprises that wish to deliver dependable software to their customers. Several static analysis-based approaches for facilitating the development of secure and reliable software have been proposed over the years. The purpose of the present thesis is to investigate these approaches and to extend their state of the art by addressing existing open issues that have not been sufficiently addressed yet. To this end, an empirical study was initially conducted with the purpose to investigate the ability of software metrics (e.g., complexity metrics) to discriminate between different types of vulnerabilities, and to examine whether potential interdependencies exist between different vulnerability types. The results of the analysis revealed that software metrics can be used only as weak indicators of specific security issues, while important interdependencies may exist between different types of vulnerabilities. The study also verified the capacity of software metrics (including previously uninvestigated metrics) to indicate the existence of vulnerabilities in general. Subsequently, a hierarchical security assessment model able to quantify the internal security level of software products, based on static analysis alerts and software metrics is proposed. The model is practical, since it is fully-automated and operationalized in the form of individual tools, while it is also sufficiently reliable since it was built based on data and well-accepted sources of information. An extensive evaluation of the model on a large volume of empirical data revealed that it is able to reliably assess software security both at product- and at class-level of granularity, with sufficient discretion power, while it may be also used for vulnerability prediction. The experimental results also provide further support regarding the ability of static analysis alerts and software metrics to indicate the existence of software vulnerabilities. Finally, a mathematical model for calculating the optimum checkpoint interval, i.e., the checkpoint interval that minimizes the execution time of software programs that adopt the application-level checkpoint and restart (ALCR) mechanism was proposed. The optimum checkpoint interval was found to depend on the failure rate of the application, the execution cost for establishing a checkpoint, and the execution cost for restarting a program after failure. Emphasis was given on programs with loops, while the results were illustrated through several numerical examples.Open Acces

Bioinformatics applied to human genomics and proteomics: development of algorithms and methods for the discovery of molecular signatures derived from omic data and for the construction of co-expression and interaction networks

[EN] The present PhD dissertation develops and applies Bioinformatic methods and tools to address key current problems in the analysis of human omic data. This PhD has been organised by main objectives into four different chapters focused on: (i) development of an algorithm for the analysis of changes and heterogeneity in large-scale omic data; (ii) development of a method for non-parametric feature selection; (iii) integration and analysis of human protein-protein interaction networks and (iv) integration and analysis of human co-expression networks derived from tissue expression data and evolutionary profiles of proteins. In the first chapter, we developed and tested a new robust algorithm in R, called DECO, for the discovery of subgroups of features and samples within large-scale omic datasets, exploring all feature differences possible heterogeneity, through the integration of both data dispersion and predictor-response information in a new statistic parameter called h (heterogeneity score). In the second chapter, we present a simple non-parametric statistic to measure the cohesiveness of categorical variables along any quantitative variable, applicable to feature selection in all types of big data sets. In the third chapter, we describe an analysis of the human interactome integrating two global datasets from high-quality proteomics technologies: HuRI (a human protein-protein interaction network generated by a systematic experimental screening based on Yeast-Two-Hybrid technology) and Cell-Atlas (a comprehensive map of subcellular localization of human proteins generated by antibody imaging). This analysis aims to create a framework for the subcellular localization characterization supported by the human protein-protein interactome. In the fourth chapter, we developed a full integration of three high-quality proteome-wide resources (Human Protein Atlas, OMA and TimeTree) to generate a robust human co-expression network across tissues assigning each human protein along the evolutionary timeline. In this way, we investigate how old in evolution and how correlated are the different human proteins, and we place all them in a common interaction network. As main general comment, all the work presented in this PhD uses and develops a wide variety of bioinformatic and statistical tools for the analysis, integration and enlighten of molecular signatures and biological networks using human omic data. Most of this data corresponds to sample cohorts generated in recent biomedical studies on specific human diseases

The Economics of International Differences in Educational Achievement

An emerging economic literature over the past decade has made use of international tests of educational achievement to analyze the determinants and impacts of cognitive skills. The cross-country comparative approach provides a number of unique advantages over national studies: It can exploit institutional variation that does not exist within countries; draw on much larger variation than usually available within any country; reveal whether any result is country-specific or more general; test whether effects are systematically heterogeneous in different settings; circumvent selection issues that plague within-country identification by using system-level aggregated measures; and uncover general-equilibrium effects that often elude studies in a single country. The advantages come at the price of concerns about the limited number of country observations, the cross-sectional character of most available achievement data, and possible bias from unobserved country factors like culture. This chapter reviews the economic literature on international differences in educational achievement, restricting itself to comparative analyses that are not possible within single countries and placing particular emphasis on studies trying to address key issues of empirical identification. While quantitative input measures show little impact, several measures of institutional structures and of the quality of the teaching force can account for significant portions of the large international differences in the level and equity of student achievement. Variations in skills measured by the international tests are in turn strongly related to individual labor-market outcomes and, perhaps more importantly, to cross-country variations in economic growth.human capital, cognitive skills, international student achievement tests, education production function

QUALITY SORTING AND TRADE: FIRM-LEVEL EVIDENCE FOR FRENCH WINE

Quality sorting and trade: Firm-level evidence for French wine Investigations of the effect of quality differences on heterogeneous performance in exporting have been limited by lack of direct measures of quality. We examine exports of French wine, matching the exporting firms to producer ratings from two wine guides. We show that high quality producers export to more markets, charge higher prices, and sell more in each market. More attractive markets are served by exporters that, on average, make lower rated Champagne. Market attractiveness has a weakly negative effect on prices and a strongly positive effect on quantities, confirming the sign predictions of a simple quality sorting model. Methodologically, we make several contributions to the literature. First, we propose an estimation method for regressions of firm-level exports on ability measures and use Monte Carlo simulations to show that it corrects a severe selection bias present in OLS estimates. Second, we show how the means of quality, price, and quantity for exporters to a given market can be used to recover estimates of core parameters (which we compare with firm-level estimates) and discriminate between productivity and quality-sorting versions of the Melitz model. Our new method regresses country means on an index of each country's attractiveness and the fixed costs of entering it. We compare our method, which utilizes explanatory variables estimated in the firm-level regressions, to the conventional approach that relies on a reduced-form relationship with proxies for attractiveness and fixed costs.Industrial Organization, F12,

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Accounting for variance and hyperparameter optimization in machine learning benchmarks

La récente révolution de l'apprentissage automatique s'est fortement appuyée sur l'utilisation de bancs de test standardisés. Ces derniers sont au centre de la méthodologie scientifique en apprentissage automatique, fournissant des cibles et mesures indéniables des améliorations des algorithmes d'apprentissage. Ils ne garantissent cependant pas la validité des résultats ce qui implique que certaines conclusions scientifiques sur les avancées en intelligence artificielle peuvent s'avérer erronées. Nous abordons cette question dans cette thèse en soulevant d'abord la problématique (Chapitre 5), que nous étudions ensuite plus en profondeur pour apporter des solutions (Chapitre 6) et finalement developpons un nouvel outil afin d'amélioration la méthodologie des chercheurs (Chapitre 7). Dans le premier article, chapitre 5, nous démontrons la problématique de la reproductibilité pour des bancs de test stables et consensuels, impliquant que ces problèmes sont endémiques aussi à de grands ensembles d'applications en apprentissage automatique possiblement moins stable et moins consensuels. Dans cet article, nous mettons en évidence l'impact important de la stochasticité des bancs de test, et ce même pour les plus stables tels que la classification d'images. Nous soutenons d'après ces résultats que les solutions doivent tenir compte de cette stochasticité pour améliorer la reproductibilité des bancs de test. Dans le deuxième article, chapitre 6, nous étudions les différentes sources de variation typiques aux bancs de test en apprentissage automatique, mesurons l'effet de ces variations sur les méthodes de comparaison d'algorithmes et fournissons des recommandations sur la base de nos résultats. Une contribution importante de ce travail est la mesure de la fiabilité d'estimateurs peu coûteux à calculer mais biaisés servant à estimer la performance moyenne des algorithmes. Tel qu'expliqué dans l'article, un estimateur idéal implique plusieurs exécution d'optimisation d'hyperparamètres ce qui le rend trop coûteux à calculer. La plupart des chercheurs doivent donc recourir à l'alternative biaisée, mais nous ne savions pas jusqu'à présent la magnitude de la dégradation de cet estimateur. Sur la base de nos résultats, nous fournissons des recommandations pour la comparison d'algorithmes sur des bancs de test avec des budgets de calculs limités. Premièrement, les sources de variations devraient être randomisé autant que possible. Deuxièmement, la randomization devrait inclure le partitionnement aléatoire des données pour les ensembles d'entraînement, de validation et de test, qui s'avère être la plus importante des sources de variance. Troisièmement, des tests statistiques tel que la version du Mann-Withney U-test présenté dans notre article devrait être utilisé plutôt que des comparisons sur la simple base de moyennes afin de prendre en considération l'incertitude des mesures de performance. Dans le chapitre 7, nous présentons un cadriciel d'optimisation d'hyperparamètres développé avec principal objectif de favoriser les bonnes pratiques d'optimisation des hyperparamètres. Le cadriciel est conçu de façon à privilégier une interface simple et intuitive adaptée aux habitudes de travail des chercheurs en apprentissage automatique. Il inclut un nouveau système de versionnage d'expériences afin d'aider les chercheurs à organiser leurs itérations expérimentales et tirer profit des résultats antérieurs pour augmenter l'efficacité de l'optimisation des hyperparamètres. L'optimisation des hyperparamètres joue un rôle important dans les bancs de test, les hyperparamètres étant un facteur confondant significatif. Fournir aux chercheurs un instrument afin de bien contrôler ces facteurs confondants est complémentaire aux recommandations pour tenir compte des sources de variation dans le chapitre 6. Nos recommendations et l'outil pour l'optimisation d'hyperparametre offre une base solide pour une méthodologie robuste et fiable.The recent revolution in machine learning has been strongly based on the use of standardized benchmarks. Providing clear target metrics and undeniable measures of improvements of learning algorithms, they are at the center of the scientific methodology in machine learning. They do not ensure validity of results however, therefore some scientific conclusions based on flawed methodology may prove to be wrong. In this thesis we address this question by first raising the issue (Chapter 5), then we study it to find solutions and recommendations (Chapter 6) and build tools to help improve the methodology of researchers (Chapter 7). In first article, Chapter 5, we demonstrate the issue of reproducibility in stable and consensual benchmarks, implying that these issues are endemic to a large ensemble of machine learning applications that are possibly less stable or less consensual. We raise awareness of the important impact of stochasticity even in stable image classification tasks and contend that solutions for reproducible benchmarks should account for this stochasticity. In second article, Chapter 6, we study the different sources of variation that are typical in machine learning benchmarks, measure their effect on comparison methods to benchmark algorithms and provide recommendations based on our results. One important contribution of this work is that we measure the reliability of a cheaper but biased estimator for the average performance of algorithms. As explained in the article, an ideal estimator involving multiple rounds of hyperparameter optimization is too computationally expensive. Most researchers must resort to use the biased alternative, but it has been unknown until now how serious a degradation of the quality of estimation this leads to. Our investigations provides guidelines for benchmarks on practical budgets. First, as many sources of variations as possible should be randomized. Second, the partitioning of data in training, validation and test sets should be randomized as well, since this is the most important source of variation. Finally, statistical tests should be used instead of ad-hoc average comparisons so that the uncertainty of performance estimation can be accounted for when comparing machine learning algorithms. In Chapter 7, we present a framework for hyperparameter optimization that has been developed with the main goal of encouraging best practices for hyperparameter optimization. The framework is designed to favor a simple and intuitive interface adapted to the workflow of machine learning researchers. It includes a new version control system for experiments to help researchers organize their rounds of experimentations and leverage prior results for more efficient hyperparameter optimization. Hyperparameter optimization plays an important role in benchmarking, with the effect of hyperparameters being a serious confounding factor. Providing an instrument for researchers to properly control this confounding factor is complementary to our guidelines to account for sources of variation in Chapter 7. Our recommendations together with our tool for hyperparameter optimization provides a solid basis for a reliable methodology in machine learning benchmarks

Soccer : physical characteristics, physical demands of match-play and effective physical conditioning

The overall purpose of this thesis was to examine the physical aspects of high performance soccer. As such, four interrelated studies were designed to pursue this purpose. Each study was designed to overcome certain distinct methodological limitations of previous science and football (soccer) research and build upon existing research. The research designs for each of the four studies were methodologically different and progressed from previous research design incorporating data collected and analysed from text and internet sources, computerised video-analysis of interactive televised material and combined performance and laboratory assessments. In the following section the purpose of each study included in this thesis is provided and the rationale underpinning the selection of each research design is explained. Study 1: Analysis of Age, Stature, Body Mass, BNH and Quality of Elite Soccer Players from four European Leagues For many sports, there are specific physical characteristics that indicate suitability for, or potential to compete in that sport at the highest level. Various anthropometric characteristics of athletes have been shown to be reasonable predictors for participation at the highest level in sports such as swimming (Ackland et al., 1993), basketball, rugby league and American football (Norton and Olds, 2000). Surprisingly, there is no research available exploring these characteristics in soccer, particularly within the elite European soccer. It might well be that the recent changes in demands in soccer( Williams et al., 1999) PhD Thesis 6 Jonathan R- Bloomfield have been accompanied by physical characteristic changes in soccer players that have been of greater magnitude than that of the normal population. This is an important issue because even small changes in these physical characteristics of players could result in a large reduction in the pool of people to draw from in the general population who have the suitable physical characteristics to be successful in soccer (Olds, 2001). Furthermore, the comparison of players in different leagues and in different positions might provide some valuable information regarding the different demands placed on soccer players in different leagues (Reilly et al, 2000a; Rienzi et al, 2000; Strudwick et al., 2002). It is well documented that different positions in soccer constitute various different demands. Such findings suggest heterogeneity in physical characteristics that might be important for success in particular positions in soccer (Strudwick et al., 2002). The first aim of the present study was to investigate whether there are physical differences (age, stature, body mass, body mass index) between players in different positions in four European soccer leagues. This will also provide information into the diversity in playing style as well as the variation in what is being valued in soccer players in the various countries. This results in valuable information for the adaptation of different physical conditioning regimes as well as implications for talent identification (Fisher and Dean, 1998). The second aim of the present study was to assess the quality of the players of each of the four European leagues by surveying their international status, nationality and FIFA world ranking as well as participation in the FIFA World Cup 2002. This will offer information regarding the actual quality of international players within these leagues which, in turn, provides information about which league would be of the highest quality, differences in playing style and player selection. As the four leading European leagues were selected for analysis, the results provide beneficial information concerning the current status and possible future development of European soccer. Study 2: The 'Bloomfield Movement Classification': Motion Analysis of Individual Soccer Players In close relation with the investigation of the physical characteristics of elite level players, it was also aimed to identify the physical demands of performance. Computerised video-analysis was selected as the most appropriate platform to incorporate a study using the time-motion analysis methodology. This involves the notation of various subjectively or objectively chosen modes of motion which are digitally timed throughout the performance. To date, fewer than 8 modes of motion have often been chosen in time-motion investigation in soccer which arguably does not provide a sufficient degree of specificity to detail the physical demands. A high element of performance specificity must be established to elicit a high degree of transfer from competition into a training regime to optimise competitive performance (Henry, 1968; Barnett et al., 1973; Sale and MacDougall, 1981; Rosenbaum, 1987; Morrissey et al., 1995; Hill et al., 1998). The present study outlined a new approach to time-motion analysis through a method involving a greater depth of detail concerning modes of timed-motion, as well as other non-timed movements, directions, intensities, turning and 'On the Ball' categories. The aim of this study was to present a new methodology and establish reliability. The purpose was to provide a new method to perform a more detailed time-motion analysis study in soccer performance to be used in the third study of this thesis. PhD Thesis 8 Jonathan R. Bloomfield Study 3: Physical Demands of Outfield Positions in FA Premier League Soccer. To elicit an enhancement in soccer performance, it is considered important to analyse the physical demands of match-play (Reilly and Thomas, 1976; All and Farrally, 1991a; Hughes, 2003). Time-motion analysis has been used to investigate these demands. However, many limitations exist with previous research, one of which being the range of classifications used in the collection of data- A high degree of performance specificity is desired to improve coaching practices such as physical conditioning (Barnett et al., 1973). To this end, a new time-motion analysis methodology was designed (see Study 2) and aimed at providing a new level of specificity of performance into the physical demands of high level soccer. Also, the majority of soccer-related time-motion analyses have reported macroscopically with total frequency, total duration or total distance covered providing a summary of the overall physical requirements of soccer. As soccer match-play is essentially an intermittent exercise (Bangsbo, 1994e), it is important to progress the knowledge of the physical nature of the sport and further provide a higher level of specific detail. The aims of the present study were to provide detail regarding intermittent patterns of Purposeful Movement (PM) and Recovery (R), performed by players of three different positions (defender, midfielder and striker), to investigate the reoccurrence of bouts of PM and R within selected time phases and finally provide time-motion analysis of the PM using the BMC. PhD Study 4: Effective Conditioning for Soccer Match-Play The interaction of multiple dynamic physical activities often produces a hybrid of physiological and biomechanical stresses. Higher levels of soccer require increased levels of physical fitness through increased demands from high intensity activity (O'Donoghue et al., 2001; Strudwick and Reffly, 2001; Mohr et al., 2003). Therefore, increased ability to perform complex chains of movement skills (agility) in conjuncture with speed (both acceleration and deceleration) and quickness (overcoming inertia) are relative to high level performance (Withers et al., 1982; Bangsbo, 1992; Reilly, 1994a). This occurs through processes of motor learning and physical conditioning with the rules of specificity and overload as key underlying principles. In order to facilitate motor learning, practice should contain variability within each session in preference to the repeated rehearsal of a single skill (Fitts, 1964; Henry, 1968; Barnett et al., 1973; Carlson and Yaure, 1990; Vereijken, 1991; Whiting and Vereijken, 1993; Bangsbo, and Peitersen, 2000; WiHiams, 2002). This may take the form of programmed and controlled (e. g. SAQ0 conditioning) or random and semi-controlled (e. g. small-sided games) practice methods. Hoff et al., (2002) identified that both methods are credible for soccer conditioning. The main aim of this study was to investigate the efficacy of programmed and random motor learning and physical conditioning methods and investigate neurophysiological. and performance adaptations, A second aim was to investigate the necessity of the use of specialised SAQ8 equipment for the purposes of programmed conditioning

The Economics of Employment Testing

Greater use of employment tests for selecting workers will have important effects on the economy. First, the rewards for developing the competencies measured by the tests will rise and this will increase the supply of workers with these competencies. Employment tests predict job performance because they measure or are correlated with a large set of developed abilities which are causally related to productivity and not because they are correlated with an inherited ability to learn. Our economy currently under-rewards the achievements that are measured by these tests and the resulting weak incentives for hard study have contributed to the low levels of achievement in math and science. Greater use of tests to select workers will also change the sorting of workers across jobs. Its impacts on total output depends on the extent to which the developed abilities measured by employment tests--academic achievement, perceptual speed and psychomotor skills--have larger impacts on worker productivity in dollars in some occupations than in others. This question is examined by analyzing GATB revalidation data on 31,399 workers in 159 occupations and by reviewing the literature on how the standard deviation of worker productivity varies across occupations. The analysis finds that indeed such differentials exist and therefore that reassigning workers who do well on a test to occupations where the payoff to the talent is particularly high will increase aggregate output. The magnitude of the output effect was estimated by reweighting the GATB revalidation data to be representative of the 71 million workers in the non-professional and nonmanagerial occupations and then simulating various resorting scenarios. Selecting new hires randomly lowered aggregate output by at least $129 billion or 8 percent of the compensation received by these workers. An upper bound estimate of the productivity benefits of reassigning workers on the basis of three GATB composites is that it would raise output by$111 billion or 6.9 percent of compensation. Reassignment based on tests had an adverse impact on Blacks and Hispanics but greatly reduced gender segregation in the work place and substantially improved the average wage of the jobs held by women. These results are based on a maintained assumption--the models of job performance which were estimated in samples of job incumbents are after corrections for measurement error and selection on the dependent variable yield unbiased estimates of true population relationships--that is almost certainly wrong. The biases introduced into the calculation by this assumption lower the estimated costs of introducing random assignment of workers to jobs, exaggerate the benefits of greater test use and exaggerate the changes in demographic composition of occupational work forces. The paper concludes with a discussion of ways in which employment tests can simultaneously strengthen incentives to learn, improve sorting and minimize adverse impacts on minority groups