Multiscale principal component analysis

Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis.Comment: 24 pages, 22 figure

Diagnostics for categorical response models based on quantile residuals and distance measures

Polytomous categorical data are frequent in studies, that can be obtained with an individual or grouped structure. In both structures, the generalized logit model is commonly used to relate the covariates on the response variable. After fitting a model, one of the challenges is the definition of an appropriate residual and choosing diagnostic techniques. Since the polytomous variable is multivariate, raw, Pearson, or deviance residuals are vectors and their asymptotic distribution is generally unknown, which leads to difficulties in graphical visualization and interpretation. Therefore, the definition of appropriate residuals and the choice of the correct analysis in diagnostic tools is important, especially for nominal data, where a restriction of methods is observed. This paper proposes the use of randomized quantile residuals associated with individual and grouped nominal data, as well as Euclidean and Mahalanobis distance measures, as an alternative to reduce the dimension of the residuals. We developed simulation studies with both data structures associated. The half-normal plots with simulation envelopes were used to assess model performance. These studies demonstrated a good performance of the quantile residuals, and the distance measurements allowed a better interpretation of the graphical techniques. We illustrate the proposed procedures with two applications to real data.Comment: 20 page

Advancements in Designing, Producing, and Operating Off-Earth Infrastructure

Sending humans to the Moon and Mars in the near future requires appropriate infrastructure to support and subsequently sustain human activities. This includes infrastructure to shield from environmental conditions, generate energy, and facilitate mobility and communication. Construction of such infrastructure aims to use in-situ resources and reduce the use of supplies from Earth. The establishment and maintenance of the required infrastructure, equipment, and hardware involves the development of adequate manufacturing techniques, which can enable maximal use of the local resources. Those techniques can be based on processing of local materials into construction materials, extraction of useful elements from local materials or in combination with materials brought from Earth. The required manufacturing techniques address the range of needs for sustained human activities, from smaller scale manufactured items to large built structures. The design of such structures is associated with a number of space systems’ engineering challenges, ranging from the accurate definition of all resource budgets (mass, volume, power, data) to the design of the interfaces between all subsystems making use of these resources. The interplanetary spacecraft used to transport the required materials (and eventually, crew) from Earth to the final site would probably need to be designed ad-hoc for this specific application, given its peculiar mass and volume constraints, especially in case a reusable concept is adopted. Other engineering aspects involved in the design of the infrastructure systems include the selection of an appropriate power generation approach and the definition of the radiation environment in order to provide sufficient shielding to the habitats. This Spool CpA #4 issue investigates challenges of designing, engineering, constructing, operating, and maintaining off-Earth infrastructure

Cognitive load theory: limiting the gap between Academics and students in accounting and auditing

The objective of this paper is to investigate if academics and students share similar cognitive structures in relation to the True and Fair View (TFV) concept, a complex accounting principle, which has no official definition and is open to interpretation and professional judgement. A survey method was used to obtain data for this study. The survey allows us to explore academics and students cognitive structures in order to discover differences and the reasons for the variances if any. Our results show that academics and students do not share similar cognitive structures in three areas of interest: i) compliance with accounting rules and the fulfilment of True and Fair View, ii) the need to provide a written definition of True and Fair View, and iii) the interpretation of True and Fair View. The evidence can be interpreted due to the fact that academics and students tend to use different cognitive schemes in problem solving at least in complex concepts such as TFV. The evidence is supported by the cognitive load theory (CLT). We believe that useful financial information can be improved by understanding these differences and by subsequently implementing criteria in order to reduce the gap between academics and students in the area of information comprehension and presentation with the use of schemes, improvement in educational material and other assistance in the application and interpretation of written standards.info:eu-repo/semantics/publishedVersio

Flexural Buckling of Steel Cold-Formed Hollow Profiles in the Framework of Eurocodes

The use of cold-formed hollow structural (CFHS) steel has been growing in the past decade due to several advantages such as superior behavior towards lateral-torsional buckling, aesthetic structures, and feasibility of using internal volume to increase load-carrying capacity. The cold-forming process can change drastically the shape of the stress-strain curve and strength parameters of the base material. There are several investigations on buckling tests of hollow section columns; however, studies on cold-formed hollow sections are still lacking. This shortcoming of experimental data becomes more pronounced when the corner behavior of CFHS is under consideration. Only a limited number of corner coupon tests can be found in international literature. This Ph.D. thesis is developed in line with the progress of the European project INNOvative 3D JOINTS for Robust and Economic Hybrid Tubular Construction (INNO3DJOINTS). The primary objective is to advance, through analytical and experimental research, knowledge on the flexural buckling behavior of CFHS columns. An extensive experimental program ( 21 flexural buckling tests) on SHS and RHS columns has been carried out varying the steel grade (i.e. S275 and S355) and the overall slenderness ratio. This database serves as the basis for the assessment and improvement of the flexural buckling curve for CFHS. The stress-strain behavior of the sections was investigated by performing tensile coupon tests (81 tests) from both flat and corner areas. special effort was made to obtain the static stress-strain data by pausing the test for 60 seconds during the test. We also employed an innovative method to perform the coupon test on the corner area of CFHS. This procedure will reduce the secondary effect results from methods such as welding a plate or flattening the end grip, and therefore reduce the bias in the results of the corner area. A comprehensive discussion on the definition of safety and the adopted safety levels in EN1990 and EN1993-1-1 has been presented. The results show some potential criticisms of the application of current rules for plastic design and analysis of such a column and a further investigation is required on the matter. In addition, it is shown that the current material test procedures in BSI and ATM standards may lead to misevaluate the static strengths of material which is required for the design of structures

A Method for Mapping XML DTD to Relational Schemas In The Presence Of Functional Dependencies

The eXtensible Markup Language (XML) has recently emerged as a standard for data representation and interchange on the web. As a lot of XML data in the web, now the pressure is to manage the data efficiently. Given the fact that relational databases are the most widely used technology for managing and storing XML, therefore XML needs to map to relations and this process is one that occurs frequently. There are many different ways to map and many approaches exist in the literature especially considering the flexible nesting structures that XML allows. This gives rise to the following important problem: Are some mappings ‘better’ than the others? To approach this problem, the classical relational database design through normalization technique that based on known functional dependency concept is referred. This concept is used to specify the constraints that may exist in the relations and guide the design while removing semantic data redundancies. This approach leads to a good normalized relational schema without data redundancy. To achieve a good normalized relational schema for XML, there is a need to extend the concept of functional dependency in relations to XML and use this concept as guidance for the design. Even though there exist functional dependency definitions for XML, but these definitions are not standard yet and still having several limitation. Due to the limitations of the existing definitions, constraints in the presence of shared and local elements that exist in XML document cannot be specified. In this study a new definition of functional dependency constraints for XML is proposed that are general enough to specify constraints and to discover semantic redundancies in XML documents. The focus of this study is on how to produce an optimal mapping approach in the presence of XML functional dependencies (XFD), keys and Data Type Definition (DTD) constraints, as a guidance to generate a good relational schema. To approach the mapping problem, three different components are explored: the mapping algorithm, functional dependency for XML, and implication process. The study of XML implication is important to imply what other dependencies that are guaranteed to hold in a relational representation of XML, given that a set of functional dependencies holds in the XML document. This leads to the needs of deriving a set of inference rules for the implication process. In the presence of DTD and userdefined XFD, other set of XFDs that are guaranteed to hold in XML can be generated using the set of inference rules. This mapping algorithm has been developed within the tool called XtoR. The quality of the mapping approach has been analyzed, and the result shows that the mapping approach (XtoR) significantly improve in terms of generating a good relational schema for XML with respect to reduce data and relation redundancy, remove dangling relations and remove association problems. The findings suggest that if one wants to use RDBMS to manage XML data, the mapping from XML document to relations must based be on functional dependency constraints

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

A Logical Method for Policy Enforcement over Evolving Audit Logs

We present an iterative algorithm for enforcing policies represented in a first-order logic, which can, in particular, express all transmission-related clauses in the HIPAA Privacy Rule. The logic has three features that raise challenges for enforcement --- uninterpreted predicates (used to model subjective concepts in privacy policies), real-time temporal properties, and quantification over infinite domains (such as the set of messages containing personal information). The algorithm operates over audit logs that are inherently incomplete and evolve over time. In each iteration, the algorithm provably checks as much of the policy as possible over the current log and outputs a residual policy that can only be checked when the log is extended with additional information. We prove correctness and termination properties of the algorithm. While these results are developed in a general form, accounting for many different sources of incompleteness in audit logs, we also prove that for the special case of logs that maintain a complete record of all relevant actions, the algorithm effectively enforces all safety and co-safety properties. The algorithm can significantly help automate enforcement of policies derived from the HIPAA Privacy Rule.Comment: Carnegie Mellon University CyLab Technical Report. 51 page

Efficient Identification of Equivalences in Dynamic Graphs and Pedigree Structures

We propose a new framework for designing test and query functions for complex structures that vary across a given parameter such as genetic marker position. The operations we are interested in include equality testing, set operations, isolating unique states, duplication counting, or finding equivalence classes under identifiability constraints. A motivating application is locating equivalence classes in identity-by-descent (IBD) graphs, graph structures in pedigree analysis that change over genetic marker location. The nodes of these graphs are unlabeled and identified only by their connecting edges, a constraint easily handled by our approach. The general framework introduced is powerful enough to build a range of testing functions for IBD graphs, dynamic populations, and other structures using a minimal set of operations. The theoretical and algorithmic properties of our approach are analyzed and proved. Computational results on several simulations demonstrate the effectiveness of our approach.Comment: Code for paper available at http://www.stat.washington.edu/~hoytak/code/hashreduc