Biometrics is a unique physical or behavioral characteristic of a person. This unique attribute, such as fingerprints or gait, can be used for identification or verification purposes. Gait is an emerging biometrics with great potential. Gait recognition is based on recognizing a person by the manner in which they walk. Its potential lays in that it can be captured at a distance and does not require the cooperation of the subject. This advantage makes it a very attractive tool for forensic cases and applications, where it can assist in identifying a suspect when other evidence such as DNA, fingerprints, or a face were not attainable. Gait can be used for recognition in a direct manner when the two samples are shot from similar camera resolution, position, and conditions. Yet in some cases, the only sample available is of an incomplete gait cycle, low resolution, low frame rate, a partially visible subject, or a single static image. Most of these conditions have one thing in common: static measurements. A gait signature is usually formed from a number of dynamic and static features. Static features are physical measurements of height, length, or build; while dynamic features are representations of joint rotations or trajectories. The aim of this thesis is to study the potential of predicting dynamic features from static features. In this thesis, we have created a database that utilizes a 3D laser scanner for capturing accurate shape and volumes of a person, and a motion capture system to accurately record motion data. The first analysis focused on analyzing the correlation between twenty-one 2D static features and eight dynamic features. Eleven pairs of features were regarded as significant with the criterion of a P-value less than 0.05. Other features also showed a strong correlation that indicated the potential of their predictive power. The second analysis focused on 3D static and dynamic features. Through the correlation analysis, 1196 pairs of features were found to be significantly correlated. Based on these results, a linear regression analysis was used to predict a dynamic gait signature. The predictors chosen were based on two adaptive methods that were developed in this thesis: "the top-x" method and the "mixed method". The predictions were assessed for both for their accuracy and their classification potential that would be used for gait recognition. The top results produced a 59.21% mean matching percentile. This result will act as baseline for future research in predicting a dynamic gait signature from static features. The results of this thesis bare potential for applications in biomechanics, biometrics, forensics, and 3D animation.

Yes / Aims: To create a gait database with optimum accuracy of joint rotational data and an accu-rate representation of 3D volume, and explore the potential of using the database in studying the relationship between static and dynamic features of a human’s gait. Study Design: The study collected gait samples from 38 subjects, in which they were asked to walk, run, walk to run transition, and walk with a bag. The motion capture, video, and 3d measurement data extracted was used to analyse and build a correlation between features. Place and Duration of Study: The study was conducted in the University of Bradford. With the ethical approval from the University, 38 subjects’ motion and body volumes were recorded at the motion capture studio from May 2011- February 2013. Methodology: To date, the database includes 38 subjects (5 females, 33 males) conducting walk cycles with speed and load as covariants. A correlation analysis was conducted to ex-plore the potential of using the database to study the relationship between static and dynamic features. The volumes and surface area of body segments were used as static features. Phased-weighted magnitudes extracted through a Fourier transform of the rotation temporal data of the joints from the motion capture were used as dynamic features. The Pearson correlation coefficient is used to evaluate the relationship between the two sets of data. Results: A new database was created with 38 subjects conducting four forms of gait (walk, run, walk to run, and walking with a hand bag). Each subject recording included a total of 8 samples of each form of gait, and a 3D point cloud (representing the 3D volume of the subject). Using a Pvalue (P<.05) as a criterion for statistical significance, 386 pairs of features displayed a strong relationship. Conclusion: A novel database available to the scientific community has been created. The database can be used as an ideal benchmark to apply gait recognition techniques, and based on the correlation analysis, can offer a detailed perspective of the dynamics of gait and its relationship to volume. Further research in the relationship between static and dynamic features can contribute to the field of biomechanical analysis, use of biometrics in forensic applications, and 3D virtual walk simulation.

Biometrics is a unique physical or behavioral characteristic of a person. This unique attribute, such as fingerprints or gait, can be used for identification or verification purposes. Gait is an emerging biometrics with great potential. Gait recognition is based on recognizing a person by the manner in which they walk. Its potential lays in that it can be captured at a distance and does not require the cooperation of the subject. This advantage makes it a very attractive tool for forensic cases and applications, where it can assist in identifying a suspect when other evidence such as DNA, fingerprints, or a face were not attainable. Gait can be used for recognition in a direct manner when the two samples are shot from similar camera resolution, position, and conditions. Yet in some cases, the only sample available is of an incomplete gait cycle, low resolution, low frame rate, a partially visible subject, or a single static image. Most of these conditions have one thing in common: static measurements. A gait signature is usually formed from a number of dynamic and static features. Static features are physical measurements of height, length, or build; while dynamic features are representations of joint rotations or trajectories. The aim of this thesis is to study the potential of predicting dynamic features from static features. In this thesis, we have created a database that utilizes a 3D laser scanner for capturing accurate shape and volumes of a person, and a motion capture system to accurately record motion data. The first analysis focused on analyzing the correlation between twenty-one 2D static features and eight dynamic features. Eleven pairs of features were regarded as significant with the criterion of a P-value less than 0.05. Other features also showed a strong correlation that indicated the potential of their predictive power. The second analysis focused on 3D static and dynamic features. Through the correlation analysis, 1196 pairs of features were found to be significantly correlated. Based on these results, a linear regression analysis was used to predict a dynamic gait signature. The predictors chosen were based on two adaptive methods that were developed in this thesis: "the top-x" method and the "mixed method". The predictions were assessed for both for their accuracy and their classification potential that would be used for gait recognition. The top results produced a 59.21% mean matching percentile. This result will act as baseline for future research in predicting a dynamic gait signature from static features. The results of this thesis bare potential for applications in biomechanics, biometrics, forensics, and 3D animation.

No description available.

An empirical investigation of the security flaws and features of an in-use modern electronic health record system is performed. The investigation was carried out using dynamic analysis, manual testing and interviews with developers. The results indicate that in-use electronic health record systems suffer from serious authentication flaws, arising from the interaction of many different proprietary systems. The authentication problems are so severe that gaining access to any user’s computer on the hospital intranet would compromise a large database of patient medical records, including radiological data regarding the patients. Common web vulnerabilities were also present, such as injections and incorrectly configured HTTP security headers. These vulnerabilities were heavily mitigated by the use of libraries for constructing web interfaces. / En empirisk undersökning av säkerheten inom ett modernt elektroniskt patientjournal-system har utförts. Undersökningen genomfördes med hjälp av dynamisk analys, manuell testning och intervjuer med utvecklarna. Resultatet indikerar att system för elektroniska patientjournaler har stora brister inom autentisering, vilka uppstår p.g.a. att flera olika kommersiella system måste samarbeta. Problemen är så allvarliga att med tillgång till en enda dator på intranätet kan en stor databas med patientdata äventyras, inklusive radiologisk data gällande patienterna. Vanliga websårbarheter fanns också, så som injektioner av skript och inkorrekt konfigurerade HTTP säkerhetsheaders. Dessa sårbarheter mitigerades starkt genom användandet av bibliotek för webinterface.

Over the last decade, the semiconductor industry has witnessed a steady increase in its complexity based on improvements in manufacturing processes and equipment. Progress in the technology used is no longer the key to success, however. In fact, the semiconductor technology has reached such a high level of complexity that improvements appear at a slow pace. Moreover, the diffusion of technology among competitors shows that traditional approaches based on technological advances and innovations are not sufficient to remain competitive. A recent crisis in the semiconductor field in the summer 2001 made it even clearer that optimizing the operational control of semiconductor wafer fabrication facilities is a vital key to success. Operating research-oriented studies have been carried out to this end for the last 5 years. None of them, however, suggest a comprehensive model and solution to the operational control problem of a semiconductor manufacturing facility. Two main approaches, namely mathematical programming and dispatching rules, have been explored in the literature so far, either partially or entirely dealing with this problem. Adapting the Shifting Bottleneck (SB) procedure is a third approach that has motivated many studies. Most research focuses on optimizing a certain objective function under idealized conditions and thus does not take into consideration system disruptions such as machine breakdown. While many papers address the adaptations of the SB procedure, the problem of re-scheduling jobs dynamically to take disruptions and local disturbances (machines breakdown, maintenance...) into consideration shows interesting perspectives for research. Dealing with local disturbances in a production environment and analyzing their impact on scheduling policies is a complex issue. It becomes even more complex in the semiconductor industry because of the numerous inherent constraints to take into account. The problem that is addressed in this thesis consists of studying dynamic scheduling in a job-shop environment where local disturbances occur. This research focuses on scheduling a large job shop and developing re-scheduling policies when local disturbances occur. The re-scheduling can be applied to the whole production horizon considered in the instance, or applied to a restricted period T that becomes a decision variable of the problem. The length of the restricted horizon T of re-scheduling can influence significantly the overall results. Its impact on the general performance is studied. Future extensions can be made to include constraints that arise in the semiconductors industry, such as the presence of parallel and batching machines, reentrant flows and the lot dedication problem. The theoretical results developed through this research will be applied to data sets to study their efficiency. We hope this methodology will bring useful insights to dealing effectively with local disturbances in production environments. / Master of Science

Importance of web services increases as the technology improves and the need for the challenging e-commerce strategies increases. This thesis focuses on web market analysis of web sites by evaluating from the perspectives of static, dynamic and content. Firstly, web site evaluation methods and web analytic tools are introduced. Then evaluation methodology is described from three perspectives. Finally, results obtained from the evaluation of 113 web sites are presented as well as their correlations.

This dissertation defines "modular-objective coupling", and shows that programming language designs which imply reduced modular-objective coupling reduce complexity of remodularizations--behaviour-preserving restructurings for which the only intended goals are to change program source code structure. We explicitly distinguish between two points of view on program structure: modular structure--the structure of a program as a set of static text documents, and objective structure--the structure of a program as a dynamic computational model during execution. We define modular-objective coupling as the degree to which changes in modular structure imply changes to objective structure, for a given programming language. We use the term remodularization to refer to any behaviour-preserving source code restructuring, for which the only intended goal is to change modular structure. We argue that programming languages with strong modular-objective coupling introduce accidental complexity into remodularizations, by requiring complex objective structure changes to achieve intended modular structure changes. Our claim is that a programming language design which implies reduced modular-objective coupling reduces remodularization complexity in the language. To validate this claim, we first present SubjectJ, a subject-oriented programming system that extends Java. The design of Java implies strong modular-objective coupling, while SubjectJ is designed for reduced modular-objective coupling. We then perform a series of remodularization case studies comparing Java and SubjectJ. Our results suggest that remodularizations are less complex in SubjectJ.

This dissertation defines "modular-objective coupling", and shows that programming language designs which imply reduced modular-objective coupling reduce complexity of remodularizations--behaviour-preserving restructurings for which the only intended goals are to change program source code structure. We explicitly distinguish between two points of view on program structure: modular structure--the structure of a program as a set of static text documents, and objective structure--the structure of a program as a dynamic computational model during execution. We define modular-objective coupling as the degree to which changes in modular structure imply changes to objective structure, for a given programming language. We use the term remodularization to refer to any behaviour-preserving source code restructuring, for which the only intended goal is to change modular structure. We argue that programming languages with strong modular-objective coupling introduce accidental complexity into remodularizations, by requiring complex objective structure changes to achieve intended modular structure changes. Our claim is that a programming language design which implies reduced modular-objective coupling reduces remodularization complexity in the language. To validate this claim, we first present SubjectJ, a subject-oriented programming system that extends Java. The design of Java implies strong modular-objective coupling, while SubjectJ is designed for reduced modular-objective coupling. We then perform a series of remodularization case studies comparing Java and SubjectJ. Our results suggest that remodularizations are less complex in SubjectJ.

This dissertation defines "modular-objective coupling", and shows that programming language designs which imply reduced modular-objective coupling reduce complexity of remodularizations--behaviour-preserving restructurings for which the only intended goals are to change program source code structure. We explicitly distinguish between two points of view on program structure: modular structure--the structure of a program as a set of static text documents, and objective structure--the structure of a program as a dynamic computational model during execution. We define modular-objective coupling as the degree to which changes in modular structure imply changes to objective structure, for a given programming language. We use the term remodularization to refer to any behaviour-preserving source code restructuring, for which the only intended goal is to change modular structure. We argue that programming languages with strong modular-objective coupling introduce accidental complexity into remodularizations, by requiring complex objective structure changes to achieve intended modular structure changes. Our claim is that a programming language design which implies reduced modular-objective coupling reduces remodularization complexity in the language. To validate this claim, we first present SubjectJ, a subject-oriented programming system that extends Java. The design of Java implies strong modular-objective coupling, while SubjectJ is designed for reduced modular-objective coupling. We then perform a series of remodularization case studies comparing Java and SubjectJ. Our results suggest that remodularizations are less complex in SubjectJ. / Science, Faculty of / Computer Science, Department of / Graduate