Quantifying evidence for forensic authorship analysis

The judicial interest in ‘scientific’ evidence has driven recent work to quantify results for forensic linguistic authorship analysis. Through a methodological discussion and a worked example this paper examines the issues which complicate attempts to quantify results in work. The solution suggested to some of the difficulties is a sampling and testing strategy which helps to identify potentially useful, valid and reliable markers of authorship. An important feature of the sampling strategy is that these markers identified as being generally valid and reliable are retested for use in specific authorship analysis cases. The suggested approach for drawing quantified conclusions combines discriminant function analysis and Bayesian likelihood measures. The worked example starts with twenty comparison texts for each of three potential authors and then uses a progressively smaller comparison corpus, reducing to fifteen, ten, five and finally three texts per author. This worked example demonstrates how reducing the amount of data affects the way conclusions can be drawn. With greater numbers of reference texts quantified and safe attributions are shown to be possible, but as the number of reference texts reduces the analysis shows how the conclusion which should be reached is that no attribution can be made. The testing process at no point results in instances of a misattribution.

Binary sparse nonnegative matrix factorization

This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

Semantic geographic information system

This thesis research describes the design and implementation of a Semantic Geographic Information System (GIS) and the creation of its spatial database. The database schema is designed and created, and all textual and spatial data are loaded into the database with the help of the Semantic DBMS's Binary Database Interface currently being developed at the FIU's High Performance Database Research Center (HPDRC). A friendly graphical user interface is created together with the other main system's areas: displaying process, data animation, and data retrieval. All these components are tightly integrated to form a novel and practical semantic GIS that has facilitated the interpretation, manipulation, analysis, and display of spatial data like: Ocean Temperature, Ozone(TOMS), and simulated SeaWiFS data. At the same time, this system has played a major role in the testing process of the HPDRC's high performance and efficient parallel Semantic DBMS.

Development of new vocational training modules on sustainable buildings maintenance and refurbishment

This article presents the methodology and main results obtained in Spain within the FORMAR project, a European-funded project under the Leonardo Da Vinci scheme (Lifelong Learning Programme), whose main goal is to jointly develop training resources and modules to improve the skills on sustainability issues of buildings maintenance and refurbishment workers, in three different European countries: Spain, Portugal (Project Coordinator) and France. The Units of Short-term Training (UST) developed within this project are focused on the VET of carpenters, painters, bricklayers, building technicians and installers of solar panels, and a transversal unit containing basic concepts on sustainable construction and nearly Zero Energy Buildings (n-ZEB) is also developed. In parallel, clients’ guides for the aforementioned professionals are also implemented to improve the information provided to clients and owners in order to support the procurement decisions regarding building products and materials. Therefore, the project provides an opportunity to exchange experiences between organizations of these three European countries, as the UST will be developed simultaneously in each of them, exploring opportunities for training, guidance and exchange of experience. Even though the UST will have a common structure and contents, they will be slightly different in each country to adapt them to the different specific training needs and regulations of Spain, Portugal and France. This paper details, as a case study, the development process of the UST for carpenters and building technicians in Spain, including the analysis of needs and existing training materials, the main contents developed and the evaluation and testing process of the UST, which involves the active participation of several stakeholders of this sector as well as a classroom testing to obtain the students’ feedback.

Controlled Vocabulary Enhancement through Crowdsourcing: Project Andvari, Micropasts, and Public Quality Assurance

Proceedings paper published by Society of American Archivists. Presented at conference in 2015 in Cleveland, OH (http://www2.archivists.org/proceedings/research-forum/2015/agenda#papers). Published by SAA in 2016.

Deep Learning Architectures for time of arrival detection in Acoustic Emissions Monitoring

Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine its location in Structural Health Monitoring (SHM) applications. Information on the time difference of the signal generated by the damage event arriving at different sensors is essential in performing localization. This makes the time of arrival (ToA) an important piece of information to retrieve from the AE signal. Generally, this is determined using statistical methods such as the Akaike Information Criterion (AIC) which is particularly prone to errors in the presence of noise. And given that the structures of interest are surrounded with harsh environments, a way to accurately estimate the arrival time in such noisy scenarios is of particular interest. In this work, two new methods are presented to estimate the arrival times of AE signals which are based on Machine Learning. Inspired by great results in the field, two models are presented which are Deep Learning models - a subset of machine learning. They are based on Convolutional Neural Network (CNN) and Capsule Neural Network (CapsNet). The primary advantage of such models is that they do not require the user to pre-define selected features but only require raw data to be given and the models establish non-linear relationships between the inputs and outputs. The performance of the models is evaluated using AE signals generated by a custom ray-tracing algorithm by propagating them on an aluminium plate and compared to AIC. It was found that the relative error in estimation on the test set was < 5% for the models compared to around 45% of AIC. The testing process was further continued by preparing an experimental setup and acquiring real AE signals to test on. Similar performances were observed where the two models not only outperform AIC by more than a magnitude in their average errors but also they were shown to be a lot more robust as compared to AIC which fails in the presence of noise.

Design and testing of a radiation hardened 13-bit 80 MS/s pipeline ADC implemented in a 90nm standard CMOS process

Second International Workshop on Analog and Mixed Signal Integrated Circuits for Space Applications (AMICSA 2008), Sintra, Portugal, Setembro de 2008

Process engineering of liver cells for drug testing applications

Dissertação para obtenção do Grau de Doutor em Bioengenharia

Development Process and Cognitive Testing of CARATkids - Control of Allergic Rhinitis and Asthma Test for Children

Background: Allergic rhinitis and asthma (ARA) are chronic inflammatory diseases of the airways that often coexist in children. The only tool to assess the ARA control, the Control of Allergic Rhinitis and Asthma Test (CARAT) is to be used by adults. We aimed to develop the Pediatric version of Control of Allergic Rhinitis and Asthma Test (CARATkids) and to test its comprehensibility in children with 4 to 12 years of age. Methods: The questionnaire development included a literature review of pediatric questionnaires on asthma and/or rhinitis control and two consensus meetings of a multidisciplinary group. Cognitive testing was carried out in a cross-sectional qualitative study using cognitive interviews. Results: Four questionnaires to assess asthma and none to assess rhinitis control in children were identified. The multidisciplinary group produced a questionnaire version for children with 17 questions with illustrations and dichotomous (yes/no) response format. The version for caregivers had 4-points and dichotomous scales. Twenty-nine children, 4 to 12 years old, and their caregivers were interviewed. Only children over 6 years old could adequately answer the questionnaire. A few words/expressions were not fully understood by children of 6 to 8 years old. The drawings illustrating the questions were considered helpful by children and caregivers. Caregivers considered the questionnaire complete and clear and preferred dichotomous over the 4-points scales. The proportion of agreement between children and their caregivers was 61%. The words/expressions that were difficult to understand were amended. Conclusion: CARATkids, the first questionnaire to assess a child’s asthma and rhinitis control was developed and its content validity was assured. Cognitive testing showed that CARATKids is well-understood by children 6 to 12 years old. The questionnaire’s measurement properties can now be assessed in a validation study.

Points to consider for prioritizing clinical genetic testing services: a European consensus process oriented at accountability for reasonableness.

Given the cost constraints of the European health-care systems, criteria are needed to decide which genetic services to fund from the public budgets, if not all can be covered. To ensure that high-priority services are available equitably within and across the European countries, a shared set of prioritization criteria would be desirable. A decision process following the accountability for reasonableness framework was undertaken, including a multidisciplinary EuroGentest/PPPC-ESHG workshop to develop shared prioritization criteria. Resources are currently too limited to fund all the beneficial genetic testing services available in the next decade. Ethically and economically reflected prioritization criteria are needed. Prioritization should be based on considerations of medical benefit, health need and costs. Medical benefit includes evidence of benefit in terms of clinical benefit, benefit of information for important life decisions, benefit for other people apart from the person tested and the patient-specific likelihood of being affected by the condition tested for. It may be subject to a finite time window. Health need includes the severity of the condition tested for and its progression at the time of testing. Further discussion and better evidence is needed before clearly defined recommendations can be made or a prioritization algorithm proposed. To our knowledge, this is the first time a clinical society has initiated a decision process about health-care prioritization on a European level, following the principles of accountability for reasonableness. We provide points to consider to stimulate this debate across the EU and to serve as a reference for improving patient management.

Testing for multigroup equivalence of a measuring instrument : a walk through the process

Resumen tomado de la publicaci??n

Testing for a unit root in a process exhibiting a structural break in the presence of GARCH errors

This paper considers the effect of GARCH errors on the tests proposed byPerron (1997) for a unit root in the presence of a structural break. We assessthe impact of degeneracy and integratedness of the conditional varianceindividually and find that, apart from in the limit, the testing procedure isinsensitive to the degree of degeneracy but does exhibit an increasingover-sizing as the process becomes more integrated. When we consider the GARCHspecifications that we are likely to encounter in empirical research, we findthat the Perron tests are reasonably robust to the presence of GARCH and donot suffer from severe over-or under-rejection of a correct null hypothesis.

Monitoring the process mean and variance using a synthetic control chart with two-stage testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mortgage Lending in Chicago and Los Angeles: A Paired Testing Study of the Pre-Application Process

This paper analyzes data from a recently completed study of discrimination against African-American and Hispanic homebuyers when they visit mortgage lending institutions in two major metropolitan markets to make pre-application inquiries. It represents the first application of paired testing to rigorously measure discrimination in the mortgage lending process. The paired tests isolated significant levels of differential treatment on the basis of race and ethnicity in Chicago with African Americans and Hispanics receiving less information and assistance than comparable whites. Adverse treatment of African-Americans and Hispanics is also observed in Los Angeles for specific treatments, but the overall pattern of treatment observed did not differ statistically from equal treatment. Multivariate analyses for Chicago indicate that large lenders treat minorities more favorably than small lenders and that lenders with substantial numbers of applications from African-Americans treat African Americans more favorably than lenders with predominantly white application pools.