Are the perspectives really different? Further experimentation on scenario-based reading of requirements

Perspective-Based Reading (PBR) is a scenario based inspection technique where several reviewers read a document from different perspectives (e.g. user, designer, tester). The reading is made according to a special scenario, specific for each perspective. The basic assumption behind PBR is that the perspectives find different defects and a combination of several perspectives detects more defects compared to the same amount of reading with a single perspective. The paper presents a study which analyses the differences in perspectives. The study is a partial replication of previous studies. It is conducted in an academic environment using graduate students as subjects. Each perspective applies a specific modelling technique: use case modelling for the user perspective, equivalence partitioning for the tester perspective and structured analysis for the design perspective. A total of 30 subjects were divided into 3 groups, giving 10 subjects per perspective. The analysis results show that: (1) there is no significant difference among the three perspectives in terms of defect detection rate and number of defects found per hour, (2) there is no significant difference in the defect coverage of the three perspectives, and (3) a simulation study shows that 30 subjects is enough to detect relatively small perspective differences with the chosen statistical test. The results suggest that a combination of multiple perspectives may not give higher coverage of the defects compared to single-perspective reading, but further studies are needed to increase the understanding of perspective differenc

Análise de propriedades intrínsecas e extrínsecas de amostras biométricas para detecção de ataques de apresentação

Orientadores: Anderson de Rezende Rocha, Hélio PedriniTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Os recentes avanços nas áreas de pesquisa em biometria, forense e segurança da informação trouxeram importantes melhorias na eficácia dos sistemas de reconhecimento biométricos. No entanto, um desafio ainda em aberto é a vulnerabilidade de tais sistemas contra ataques de apresentação, nos quais os usuários impostores criam amostras sintéticas, a partir das informações biométricas originais de um usuário legítimo, e as apresentam ao sensor de aquisição procurando se autenticar como um usuário válido. Dependendo da modalidade biométrica, os tipos de ataque variam de acordo com o tipo de material usado para construir as amostras sintéticas. Por exemplo, em biometria facial, uma tentativa de ataque é caracterizada quando um usuário impostor apresenta ao sensor de aquisição uma fotografia, um vídeo digital ou uma máscara 3D com as informações faciais de um usuário-alvo. Em sistemas de biometria baseados em íris, os ataques de apresentação podem ser realizados com fotografias impressas ou com lentes de contato contendo os padrões de íris de um usuário-alvo ou mesmo padrões de textura sintéticas. Nos sistemas biométricos de impressão digital, os usuários impostores podem enganar o sensor biométrico usando réplicas dos padrões de impressão digital construídas com materiais sintéticos, como látex, massa de modelar, silicone, entre outros. Esta pesquisa teve como objetivo o desenvolvimento de soluções para detecção de ataques de apresentação considerando os sistemas biométricos faciais, de íris e de impressão digital. As linhas de investigação apresentadas nesta tese incluem o desenvolvimento de representações baseadas nas informações espaciais, temporais e espectrais da assinatura de ruído; em propriedades intrínsecas das amostras biométricas (e.g., mapas de albedo, de reflectância e de profundidade) e em técnicas de aprendizagem supervisionada de características. Os principais resultados e contribuições apresentadas nesta tese incluem: a criação de um grande conjunto de dados publicamente disponível contendo aproximadamente 17K videos de simulações de ataques de apresentações e de acessos genuínos em um sistema biométrico facial, os quais foram coletados com a autorização do Comitê de Ética em Pesquisa da Unicamp; o desenvolvimento de novas abordagens para modelagem e análise de propriedades extrínsecas das amostras biométricas relacionadas aos artefatos que são adicionados durante a fabricação das amostras sintéticas e sua captura pelo sensor de aquisição, cujos resultados de desempenho foram superiores a diversos métodos propostos na literature que se utilizam de métodos tradicionais de análise de images (e.g., análise de textura); a investigação de uma abordagem baseada na análise de propriedades intrínsecas das faces, estimadas a partir da informação de sombras presentes em sua superfície; e, por fim, a investigação de diferentes abordagens baseadas em redes neurais convolucionais para o aprendizado automático de características relacionadas ao nosso problema, cujos resultados foram superiores ou competitivos aos métodos considerados estado da arte para as diferentes modalidades biométricas consideradas nesta tese. A pesquisa também considerou o projeto de eficientes redes neurais com arquiteturas rasas capazes de aprender características relacionadas ao nosso problema a partir de pequenos conjuntos de dados disponíveis para o desenvolvimento e a avaliação de soluções para a detecção de ataques de apresentaçãoAbstract: Recent advances in biometrics, information forensics, and security have improved the recognition effectiveness of biometric systems. However, an ever-growing challenge is the vulnerability of such systems against presentation attacks, in which impostor users create synthetic samples from the original biometric information of a legitimate user and show them to the acquisition sensor seeking to authenticate themselves as legitimate users. Depending on the trait used by the biometric authentication, the attack types vary with the type of material used to build the synthetic samples. For instance, in facial biometric systems, an attempted attack is characterized by the type of material the impostor uses such as a photograph, a digital video, or a 3D mask with the facial information of a target user. In iris-based biometrics, presentation attacks can be accomplished with printout photographs or with contact lenses containing the iris patterns of a target user or even synthetic texture patterns. In fingerprint biometric systems, impostor users can deceive the authentication process using replicas of the fingerprint patterns built with synthetic materials such as latex, play-doh, silicone, among others. This research aimed at developing presentation attack detection (PAD) solutions whose objective is to detect attempted attacks considering different attack types, in each modality. The lines of investigation presented in this thesis aimed at devising and developing representations based on spatial, temporal and spectral information from noise signature, intrinsic properties of the biometric data (e.g., albedo, reflectance, and depth maps), and supervised feature learning techniques, taking into account different testing scenarios including cross-sensor, intra-, and inter-dataset scenarios. The main findings and contributions presented in this thesis include: the creation of a large and publicly available benchmark containing 17K videos of presentation attacks and bona-fide presentations simulations in a facial biometric system, whose collect were formally authorized by the Research Ethics Committee at Unicamp; the development of novel approaches to modeling and analysis of extrinsic properties of biometric samples related to artifacts added during the manufacturing of the synthetic samples and their capture by the acquisition sensor, whose results were superior to several approaches published in the literature that use traditional methods for image analysis (e.g., texture-based analysis); the investigation of an approach based on the analysis of intrinsic properties of faces, estimated from the information of shadows present on their surface; and the investigation of different approaches to automatically learning representations related to our problem, whose results were superior or competitive to state-of-the-art methods for the biometric modalities considered in this thesis. We also considered in this research the design of efficient neural networks with shallow architectures capable of learning characteristics related to our problem from small sets of data available to develop and evaluate PAD solutionsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação140069/2016-0 CNPq, 142110/2017-5CAPESCNP

Proceedings of the Twenty-Third Annual Software Engineering Workshop

The Twenty-third Annual Software Engineering Workshop (SEW) provided 20 presentations designed to further the goals of the Software Engineering Laboratory (SEL) of the NASA-GSFC. The presentations were selected on their creativity. The sessions which were held on 2-3 of December 1998, centered on the SEL, Experimentation, Inspections, Fault Prediction, Verification and Validation, and Embedded Systems and Safety-Critical Systems

The Validation of Novel Ecological Survey Methods for Use in Describing Harvest Mouse Micromys minutus Autecology

According to much of the literature relating to Micromys minutus (harvest mouse) the species has historically presented many challenges to researchers, particularly when attempting to collect sufficient data to describe their ecology, life history and responses to the ever-increasing threat of habitat loss and fragmentation. Methodological improvements are needed which provide sufficient species-specific data to underpin conservation and which are of sufficient quality to allow their movement ecology to be quantified. Here two novel methods were developed and tested, which included remote scent surveys using a detection dog and Radio Frequency Identification (RFID) trapping. After validation, RFID trapping was then used to quantify M. minutus movement in fragmented habitats. A preliminary study was carried out which assessed the ability of a dog to be trained to indicate the scent of M. minutus. Here positive reinforcement training methods were used and the dog’s effectiveness was evaluated in a training environment using scent samples collected from controlled and uncontrolled situations. Secondly, RFID trap effectiveness was compared to the results of live trapping. Data were maximised by releasing individually tagged M. minutus into a suitable semi-natural enclosure on the Moulton College estate. After validation a further release was undertaken to investigate M. minutus movement ecology. Here gaps of differing widths were incorporated into the release enclosures and movements between the habitat patches were measured. Individuals included in each release cohort were exposed to an Open Field Test prior to release, and thus, their behaviour in relation to trapping and movement was also assessed. There is strong evidence that a dog can be trained to detect M. minutus and discriminate their scent from other sympatric nontarget species in a controlled training environment. When applied to uncontrolled field situations, the remote scent survey proved more effective than nest search surveys by volunteers during the autumn months, providing preliminary evidence that olfactory indicators could be more efficient than visual clues when establishing presence of M. minutus. Additional validation in uncontrolled settings is still required. Encouraging results were also seen during validation of the use of RFID trapping with better results in terms of raw trapping rates over live trapping being observed. Furthermore, findings indicate that M. minutus have sufficient navigational and motion capacity to successfully move over gaps ≤2m, but gaps greater than 2m could limit their movement with possible implications for population persistence. The findings also suggest that individuals that explore more slowly may have an advantage when inhabiting a fragmented habitat. Thus, movement propensity is likely to be an individual behavioural trait and may vary across situations; this provides a novel perspective on their conservation and may support conservation decisions being based on behaviour rather than density. The data collected for this thesis demonstrates that progress has been made in terms of monitoring M. minutus and the findings presented are entirely novel for this species. Nevertheless, they remain a challenging species and more questions have been asked than can be answered within the thesis. However, the sum of this work has provided a clear direction for future research on M. minutus

Institute of Ion Beam Physics and Materials Research: Annual Report 2001

Summary of the scientific activities of the institute in 2001 including selected highlight reports, short research contributions and an extended statistics overview

A framework for how logistics service providers should handle returns as a warehouse operation for e-commerce companies

Title: A framework for how logistics service providers should handle returns as a warehouse operation for pure e-commerce companies Authors: Louise Meurling and Matilda Sturesson Supervisor: Joakim Kembro, Division of Engineering Logistics at LTH Problem description: Managing the reverse logistics process in a warehouse is a central part of the activities for companies operating in e-commerce. Companies can outsource the return handling to a Logistics Service Provider (LSP) in order to focus on their core competences. The theory of today is based on the assumption that a physical point of contact is included in the chain. Therefore, there is a need to extend the theory into the context of e-commerce. Purpose: The purpose of this thesis is to create a framework for how LSPs should handle returns in the warehouse, from the point of receiving until put back in storage, for customers in the e-commerce business. Research questions: How should a LSP handle returns in the warehouse for customers of e-commerce? What are the barriers of the return handling in a warehouse and how can LSPs overcome these? How do the different characteristics of products and customers of a LSP change the handling of returns? How can the return handling in a warehouse of a LSP contribute to greater value for the customers acting in the e-commerce business? Methodology: A flexible design methodology has been used in this thesis together with a multiple case study based on two cases at PostNord TPL´s facility in Helsingborg. Interviews, observations, and historical data have been collected and analysed in an intra case analysis and a cross-case analysis in order to answer the research questions and modify the reverse logistics framework to the context of e-commerce. Conclusions: A framework for how LSPs should handle returns in a warehouse is extended based on theory to the context of e-commerce. Several barriers of the return handling for LSPs have been identified. These are: limited sharing of forecasts, limited visibility, customer requirements, heterogenous decision making, and the changing business of e-commerce. It can be concluded that the product and customer characteristics impact the handling of returns to a large extent. To be able to contribute to greater value for the customers, the LSP should offer a fast, efficient, and less costly reverse logistics process than if they would perform it in-house. Keywords: Warehouse activities, inbound logistics, reverse logistics process, returns, return handling, e-commerce, logistics service provide