Algebraic Models for Qualified Aggregation in General Rough Sets, and Reasoning Bias Discovery

In the context of general rough sets, the act of combining two things to form another is not straightforward. The situation is similar for other theories that concern uncertainty and vagueness. Such acts can be endowed with additional meaning that go beyond structural conjunction and disjunction as in the theory of $*$-norms and associated implications over $L$-fuzzy sets. In the present research, algebraic models of acts of combining things in generalized rough sets over lattices with approximation operators (called rough convenience lattices) is invented. The investigation is strongly motivated by the desire to model skeptical or pessimistic, and optimistic or possibilistic aggregation in human reasoning, and the choice of operations is constrained by the perspective. Fundamental results on the weak negations and implications afforded by the minimal models are proved. In addition, the model is suitable for the study of discriminatory/toxic behavior in human reasoning, and of ML algorithms learning such behavior.Comment: 15 Pages. Accepted. IJCRS-202

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Multi-signal Anomaly Detection for Real-Time Embedded Systems

This thesis presents MuSADET, an anomaly detection framework targeting timing anomalies found in event traces from real-time embedded systems. The method leverages stationary event generators, signal processing, and distance metrics to classify inter-arrival time sequences as normal/anomalous. Experimental evaluation of traces collected from two real-time embedded systems provides empirical evidence of MuSADET’s anomaly detection performance. MuSADET is appropriate for embedded systems, where many event generators are intrinsically recurrent and generate stationary sequences of timestamp. To find timinganomalies, MuSADET compares the frequency domain features of an unknown trace to a normal model trained from well-behaved executions of the system. Each signal in the analysis trace receives a normal/anomalous score, which can help engineers isolate the source of the anomaly. Empirical evidence of anomaly detection performed on traces collected from an industrygrade hexacopter and the Controller Area Network (CAN) bus deployed in a real vehicle demonstrates the feasibility of the proposed method. In all case studies, anomaly detection did not require an anomaly model while achieving high detection rates. For some of the studied scenarios, the true positive detection rate goes above 99 %, with false-positive rates below one %. The visualization of classification scores shows that some timing anomalies can propagate to multiple signals within the system. Comparison to the similar method, Signal Processing for Trace Analysis (SiPTA), indicates that MuSADET is superior in detection performance and provides complementary information that can help link anomalies to the process where they occurred

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B

Species boundaries in bats: a philosophical, morphometric, environmental, and phylogenetic analysis of the genera Anoura, Carollia and Sturnira

Thesis (Ph.D.)--Boston UniversitySpecies are central to evolutionary biology, systematics and taxonomy. However, their precise definition and diagnosis is not straightforward. Species may be purely nominal constructs of the human mind or they may be real entities. Part of the difficulty of defining and diagnosing species lies in the continuous nature of variation from the level of the individual to the population, subspecies and species. It is here where systematics and taxonomy become challenging and exciting tools for understanding life on the planet. For bats, most of the efforts to describe and differentiate species have been qualitative. This may have worked in earlier times, during the first efforts to describe and name species. But, more recently, our perspectives have become sharper and the shortcomings of the qualitative approach have become obvious. This thesis is a collection of published essays, submitted studies, and ongoing research into the boundaries of bat species. In each chapter, I stress that species are not ideas or categories in the mind, but are real entities, based on testable hypotheses about the distribution of character states within multiorganismal entities. Therefore, these hypotheses and distributions of character states should optimally be analyzed through the prism of statistical inference. The dynamics of size and shape in the genus Anoura are discussed in the context of the space occupied by the different species within the genus, with novel insights into the interpretation of the distribution of these species in morphospace. For boundaries in the genus Carollia, I reassess current taxonomical knowledge, analyze morphological variation in relation to the environment, and the statistical uncertainty of species discrimination. In the species-rich genus Sturnira, I analyze a large morphological dataset for several species from Ecuador, describe a new species (S. peria) synonymize an old one (S. luisi), and provide a new perspective on phylogenetic relationships and species boundaries