A Qualitative Analysis on Dynamical Systems : Sign Structure

This paper presents several qualitative properties of dynamical systems. These qualitative properties include structures which may have periodic solutions, structures which may have constant solutions, a generalized version of sign stalibity and structures which have solutions whose sign patterns are invariant. These qualitative properties are useful for qualitative analysis of large-scale dynamical systems. We also present a method for classifying a given dynamical system by these qualitative properties

Solving Dynamical Models Qualitatively : Causality Built in Dynamical Models : Topic : Common Sense Reasoning (simulation)

We define the “causality” which requires “time reference”. With this causality, causal reasoning is carried out by verifying that any change is made by the causality. The verification is done by the comsumption of dt = + for each step. In order to make such causal reasoning possible, we carefully choose the base model, i.e. the dynamical model, which describes causality from what makes the change to what is changed. We also developed the qualitative similation algorithm using the causality built in the dynamical model. The power of the causality and simulation algorithm is demonstrated on two examples of the pressure regulator and the mass-spring system

A Generalization of Diagnosability Analysis

A new concept of generalized diagnosability is proposed for a formal diagnosis model which incorporates most diagnosis models so far proposed. A self-diagnosis model consists of a set of units which can test other units and be tested by other units. Generalized diagnosability is a new measure of diagnosability in system diagnosis problems which is extensively studied with respect to self-diagnosis models. This diagnosability expresses explicitly such information as (1) the maximum number of units to be identified as faulty, (2) the maximum number of units to be identified as fault-free, and (3) the maximum number of units whose states are definitely identified when the upper bound on the number of faulty units is assumed. Conditions for generalized diagnosability are expressed by certain relations between the power sets of a set of faulty units. Since these conditions are of the form that they must be checked all over the possible syndrome, it is generally difficult to investigate generalized diagnosability. However, these conditions are meaningful in cases in which the graph of a diagnosis model has symmetricity, or a diagnosis model has a constrained structure about the relation between fault patterns and syndromes. Some examples of these cases are presented. Furthermore, we discuss the problem of finding the minimal fault pattern consistent with a given syndrome. This problem is formulated as a mathematical programming problem with the same relations both in constraints and objective functions as those used to express conditions for generalized diagnosability

A Note on Continuous Self-Identification as Self-Awareness: An Example of Robot Navigation

AbstractThis note reports on interdisciplinary approaches to model consciousness, an aspect of self-awareness in particular, aiming at artificial consciousness that can be mounted on an autonomous and mobile robot. For self-awareness to emerge, the self-identification process plays an important role. Self-awareness would emerge when self-locating in a self-created map in robot navigation; when solving self-related problems in (a self-related version of) the frame problem; and when a singularity arises in mapping the reference point in mathematical mappings

The function of the plant cell wall in plant–microbe interactions

The plant cell wall is an interface of plant–microbe interactions. The ability of microbes to decompose cell wall polysaccharides contributes to microbial pathogenicity. Plants have evolved mechanisms to prevent cell wall degradation. However, the role of the cell wall in plant–microbe interactions is not well understood. Here, we discuss four functions of the plant cell wall—physical defence, storage of antimicrobial compounds, production of cell wall-derived elicitors, and provision of carbon sources—in the context of plant–microbe interactions. In addition, we discuss the four families of cell surface receptors associated with plant cell walls (malectin-like receptor kinase family, wall-associated kinase family, leucine-rich repeat receptor-like kinase family, and lysin motif receptor-like kinase family) that have been the subject of several important studies in recent years. This review summarises the findings on both plant cell wall and plant immunity, improving our understanding and may provide impetus to various researchers

Adaptive Sensing Based on Profiles for Sensor Systems

This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission

Immunity-Based Diagnosis for a Motherboard

We have utilized immunity-based diagnosis to detect abnormal behavior of components on a motherboard. The immunity-based diagnostic model monitors voltages of some components, CPU temperatures, and fan speeds. We simulated abnormal behaviors of some components on the motherboard, and we utilized the immunity-based diagnostic model to evaluate motherboard sensors in two experiments. These experiments showed that the immunity-based diagnostic model was an effective method for detecting abnormal behavior of components on the motherboard

Normal-state properties of the antiperovskite oxide Sr3−x_{3-x}SnO revealed by 119^{119}Sn-NMR

We have performed $^{119}$Sn-NMR measurements on the antiperovskite oxide superconductor Sr$_{3-x}$SnO to investigate how its normal state changes with the Sr deficiency. A two-peak structure was observed in the NMR spectra of all the measured samples. This suggests that the phase separation tends to occur between the nearly stoichiometric and heavily Sr-deficient Sr$_{3-x}$SnO phases. The measurement of the nuclear spin-lattice relaxation rate $1/T_1$ indicates that the Sr-deficient phase shows a conventional metallic behavior due to the heavy hole doping. In contrast, the nearly stoichiometric phase exhibits unusual temperature dependence of $1/T_1$, attributable to the presence of a Dirac-electron band.Comment: 5 pages, 4 figure

A Cyber Attack-Resilient Server Using Hybrid Virtualization

AbstractThis paper describes a novel, cyber attack-resilient server using hybrid virtualization that can reduce the downtime of the server and enhance the diversity of operating systems by adding a Linux virtual machine. The hybrid virtualization consists of machine- and application-level virtualization. The prototype system virtualizes a machine using VMware ESXi, while the prototype system virtualizes a server application using Docker on a Linux virtual machine. Docker increases the speed at which a server application starts while requiring fewer resources such as memory and storage. Performance tests showed that the prototype system reduced the downtime of the DNS service by exploiting a vulnerability with no false positive detections compared with our previous work