Data granulation by the principles of uncertainty

Researches in granular modeling produced a variety of mathematical models, such as intervals, (higher-order) fuzzy sets, rough sets, and shadowed sets, which are all suitable to characterize the so-called information granules. Modeling of the input data uncertainty is recognized as a crucial aspect in information granulation. Moreover, the uncertainty is a well-studied concept in many mathematical settings, such as those of probability theory, fuzzy set theory, and possibility theory. This fact suggests that an appropriate quantification of the uncertainty expressed by the information granule model could be used to define an invariant property, to be exploited in practical situations of information granulation. In this perspective, a procedure of information granulation is effective if the uncertainty conveyed by the synthesized information granule is in a monotonically increasing relation with the uncertainty of the input data. In this paper, we present a data granulation framework that elaborates over the principles of uncertainty introduced by Klir. Being the uncertainty a mesoscopic descriptor of systems and data, it is possible to apply such principles regardless of the input data type and the specific mathematical setting adopted for the information granules. The proposed framework is conceived (i) to offer a guideline for the synthesis of information granules and (ii) to build a groundwork to compare and quantitatively judge over different data granulation procedures. To provide a suitable case study, we introduce a new data granulation technique based on the minimum sum of distances, which is designed to generate type-2 fuzzy sets. We analyze the procedure by performing different experiments on two distinct data types: feature vectors and labeled graphs. Results show that the uncertainty of the input data is suitably conveyed by the generated type-2 fuzzy set models.Comment: 16 pages, 9 figures, 52 reference

Contours of Inclusion: Inclusive Arts Teaching and Learning

The purpose of this publication is to share models and case examples of the process of inclusive arts curriculum design and evaluation. The first section explains the conceptual and curriculum frameworks that were used in the analysis and generation of the featured case studies (i.e. Understanding by Design, Differentiated Instruction, and Universal Design for Learning). Data for the cases studies was collected from three urban sites (i.e. Los Angeles, San Francisco, and Boston) and included participant observations, student and teacher interviews, curriculum documentation, digital documentation of student learning, and transcripts from discussion forum and teleconference discussions from a professional learning community.The initial case studies by Glass and Barnum use the curricular frameworks to analyze and understand what inclusive practices look like in two case studies of arts-in-education programs that included students with disabilities. The second set of precedent case studies by Kronenberg and Blair, and Jenkins and Agois Hurel uses the frameworks to explain their process of including students by providing flexible arts learning options to support student learning of content standards. Both sets of case studies illuminate curricular design decisions and instructional strategies that supported the active engagement and learning of students with disabilities in educational settings shared with their peers. The second set of cases also illustrate the reflective process of using frameworks like Universal Design for Learning (UDL) to guide curricular design, responsive instructional differentiation, and the use of the arts as a rich, meaningful, and engaging option to support learning. Appended are curriculum design and evaluation tools. (Individual chapters contain references.

Modeling the object-oriented software process: OPEN and the unified process

A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed

Systematic evaluation of software product line architectures

The architecture of a software product line is one of its most important artifacts as it represents an abstraction of the products that can be generated. It is crucial to evaluate the quality attributes of a product line architecture in order to: increase the productivity of the product line process and the quality of the products; provide a means to understand the potential behavior of the products and, consequently, decrease their time to market; and, improve the handling of the product line variability. The evaluation of product line architecture can serve as a basis to analyze the managerial and economical values of a product line for software managers and architects. Most of the current research on the evaluation of product line architecture does not take into account metrics directly obtained from UML models and their variabilities; the metrics used instead are difficult to be applied in general and to be used for quantitative analysis. This paper presents a Systematic Evaluation Method for UML-based Software Product Line Architecture, the SystEM-PLA. SystEM-PLA differs from current research as it provides stakeholders with a means to: (i) estimate and analyze potential products; (ii) use predefined basic UML-based metrics to compose quality attribute metrics; (iii) perform feasibility and trade-off analysis of a product line architecture with respect to its quality attributes; and, (iv) make the evaluation of product line architecture more flexible. An example using the SEI’s Arcade Game Maker (AGM) product line is presented as a proof of concept, illustrating SystEM-PLA activities. Metrics for complexity and extensibility quality attributes are defined and used to perform a trade-off analysis

Modeling an ontology on accessible evacuation routes for emergencies

Providing alert communication in emergency situations is vital to reduce the number of victims. However, this is a challenging goal for researchers and professionals due to the diverse pool of prospective users, e.g. people with disabilities as well as other vulnerable groups. Moreover, in the event of an emergency situation, many people could become vulnerable because of exceptional circumstances such as stress, an unknown environment or even visual impairment (e.g. fire causing smoke). Within this scope, a crucial activity is to notify affected people about safe places and available evacuation routes. In order to address this need, we propose to extend an ontology, called SEMA4A (Simple EMergency Alert 4 [for] All), developed in a previous work for managing knowledge about accessibility guidelines, emergency situations and communication technologies. In this paper, we introduce a semi-automatic technique for knowledge acquisition and modeling on accessible evacuation routes. We introduce a use case to show applications of the ontology and conclude with an evaluation involving several experts in evacuation procedures. © 2014 Elsevier Ltd. All rights reserved

Ontology based Scene Creation for the Development of Automated Vehicles

The introduction of automated vehicles without permanent human supervision demands a functional system description, including functional system boundaries and a comprehensive safety analysis. These inputs to the technical development can be identified and analyzed by a scenario-based approach. Furthermore, to establish an economical test and release process, a large number of scenarios must be identified to obtain meaningful test results. Experts are doing well to identify scenarios that are difficult to handle or unlikely to happen. However, experts are unlikely to identify all scenarios possible based on the knowledge they have on hand. Expert knowledge modeled for computer aided processing may help for the purpose of providing a wide range of scenarios. This contribution reviews ontologies as knowledge-based systems in the field of automated vehicles, and proposes a generation of traffic scenes in natural language as a basis for a scenario creation.Comment: Accepted at the 2018 IEEE Intelligent Vehicles Symposium, 8 pages, 10 figure

On the Modeling of Correct Service Flows with BPEL4WS

Frameworks for composing Web Services offer a promising approach for realizing enterprise-wide and cross-organizational business applications. With BPEL4WS a powerful composition language exists. BPEL implementations allow orchestrating complex, stateful interactions among Web Services in a process-oriented way. One important task in this context is to ensure that respective flow specifications can be correctly processed, i.e., there will be no bad surprises (e.g., deadlocks, invocation of service operations with missing input data) at runtime. In this paper we subdivide BPEL schemes into different classes and discuss to which extent instances of these classes can be analyzed for the absence of control flow errors and inconsistencies. Altogether our work shall contribute to a more systematic evolution of the BPEL standard instead of overloading it with too many features

Retrospective on U.S. Health Risk Assessment: How Others Can Benefit

Dr. Paustenbach reviews the scientific underpinnings of about twenty years of health risk assessment practice and their implications for environmental policy. He observes that more than 600 peer-reviewed papers provide a wealth of information that can save other countries billions of dollars. He also briefly reviews risk-assessment practices outside the U.S