Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Continuous Rationale Management

Continuous Software Engineering (CSE) is a software life cycle model open to frequent changes in requirements or technology. During CSE, software developers continuously make decisions on the requirements and design of the software or the development process. They establish essential decision knowledge, which they need to document and share so that it supports the evolution and changes of the software. The management of decision knowledge is called rationale management. Rationale management provides an opportunity to support the change process during CSE. However, rationale management is not well integrated into CSE. The overall goal of this dissertation is to provide workflows and tool support for continuous rationale management. The dissertation contributes an interview study with practitioners from the industry, which investigates rationale management problems, current practices, and features to support continuous rationale management beneficial for practitioners. Problems of rationale management in practice are threefold: First, documenting decision knowledge is intrusive in the development process and an additional effort. Second, the high amount of distributed decision knowledge documentation is difficult to access and use. Third, the documented knowledge can be of low quality, e.g., outdated, which impedes its use. The dissertation contributes a systematic mapping study on recommendation and classification approaches to treat the rationale management problems. The major contribution of this dissertation is a validated approach for continuous rationale management consisting of the ConRat life cycle model extension and the comprehensive ConDec tool support. To reduce intrusiveness and additional effort, ConRat integrates rationale management activities into existing workflows, such as requirements elicitation, development, and meetings. ConDec integrates into standard development tools instead of providing a separate tool. ConDec enables lightweight capturing and use of decision knowledge from various artifacts and reduces the developers' effort through automatic text classification, recommendation, and nudging mechanisms for rationale management. To enable access and use of distributed decision knowledge documentation, ConRat defines a knowledge model of decision knowledge and other artifacts. ConDec instantiates the model as a knowledge graph and offers interactive knowledge views with useful tailoring, e.g., transitive linking. To operationalize high quality, ConRat introduces the rationale backlog, the definition of done for knowledge documentation, and metrics for intra-rationale completeness and decision coverage of requirements and code. ConDec implements these agile concepts for rationale management and a knowledge dashboard. ConDec also supports consistent changes through change impact analysis. The dissertation shows the feasibility, effectiveness, and user acceptance of ConRat and ConDec in six case study projects in an industrial setting. Besides, it comprehensively analyses the rationale documentation created in the projects. The validation indicates that ConRat and ConDec benefit CSE projects. Based on the dissertation, continuous rationale management should become a standard part of CSE, like automated testing or continuous integration

Role-Modeling in Round-Trip Engineering for Megamodels

Software is becoming more and more part of our daily life and makes it easier, e.g., in the areas of communication and infrastructure. Model-driven software development forms the basis for the development of software through the use and combination of different models, which serve as central artifacts in the software development process. In this respect, model-driven software development comprises the process from requirement analysis through design to software implementation. This set of models with their relationships to each other forms a so-called megamodel. Due to the overlapping of the models, inconsistencies occur between the models, which must be removed. Therefore, round-trip engineering is a mechanism for synchronizing models and is the foundation for ensuring consistency between models. Most of the current approaches in this area, however, work with outdated batch-oriented transformation mechanisms, which no longer meet the requirements of more complex, long-living, and ever-changing software. In addition, the creation of megamodels is time-consuming and complex, and they represent unmanageable constructs for a single user. The aim of this thesis is to create a megamodel by means of easy-to-learn mechanisms and to achieve its consistency by removing redundancy on the one hand and by incrementally managing consistency relationships on the other hand. In addition, views must be created on the parts of the megamodel to extract them across internal model boundaries. To achieve these goals, the role concept of Kühn in 2014 is used in the context of model-driven software development, which was developed in the Research Training Group 'Role-based Software Infrastructures for continuous-context-sensitive Systems.' A contribution of this work is a role-based single underlying model approach, which enables the generation of views on heterogeneous models. Besides, an approach for the synchronization of different models has been developed, which enables the role-based single underlying model approach to be extended by new models. The combination of these two approaches creates a runtime-adaptive megamodel approach that can be used in model-driven software development. The resulting approaches will be evaluated based on an example from the literature, which covers all areas of the work. In addition, the model synchronization approach will be evaluated in connection with the Transformation Tool Contest Case from 2019

Reason Maintenance - State of the Art

This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques

A model-based reasoning architecture for system-level fault diagnosis

This dissertation presents a model-based reasoning architecture with a two fold purpose: to detect and classify component faults from observable system behavior, and to generate fault propagation models so as to make a more accurate estimation of current operational risks. It incorporates a novel approach to system level diagnostics by addressing the need to reason about low-level inaccessible components from observable high-level system behavior. In the field of complex system maintenance it can be invaluable as an aid to human operators. The first step is the compilation of the database of functional descriptions and associated fault-specific features for each of the system components. The system is then analyzed to extract structural information, which, in addition to the functional database, is used to create the structural and functional models. A fault-symptom matrix is constructed from the functional model and the features database. The fault threshold levels for these symptoms are founded on the nominal baseline data. Based on the fault-symptom matrix and these thresholds, a diagnostic decision tree is formulated in order to intelligently query about the system health. For each faulty candidate, a fault propagation tree is generated from the structural model. Finally, the overall system health status report includes both the faulty components and the associated at risk components, as predicted by the fault propagation model.Ph.D.Committee Chair: Vachtsevanos, George; Committee Member: Liang, Steven; Committee Member: Michaels, Thomas; Committee Member: Vela, Patricio; Committee Member: Wardi, Yora

Building a pothole detection and tracking system

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, April 2019Building and maintaining infrastructure is often a key challenge in developing countries, and Ghana is no exception. Increasing population and car ownership rates coupled with poor maintenance cultures result in a corresponding increase in the rate of damage of roads, causing deformities such as cracks and potholes. These road deformities not only negatively impact a country’s road infrastructure and the cars which ply said roads, but also pose a threat to road users. In Ghana, only two mobile maintenance units are charged with monitoring the roads in all ten regions of the country. Thus, this project presents Pothole Tracker Ghana, a two-tiered application inspired by the idea of crowdsourcing. Consisting of a vision-based pothole classification system implemented on a Raspberry Pi and a map-based web application, this project aims to reduce the barriers to data collection on poor road infrastructure on the part of governments whilst allowing everyday road users to make informed decisions concerning their journeys. Three different algorithms are considered and compared for the classification task; logistic regression, support vector machines (SVM) and a hybrid algorithm incorporating a convolutional neural network (CNN) and SVM. The tuned SVM is chosen for the final system implementation. 
Ashesi Universit