Extra Connectivity of Strong Product of Graphs

The $g$-$extra$ $connectivity$ $\kappa_{g}(G)$ of a connected graph $G$ is the minimum cardinality of a set of vertices, if it exists, whose deletion makes $G$ disconnected and leaves each remaining component with more than $g$ vertices, where $g$ is a non-negative integer. The $strong$ $product$ $G_1 \boxtimes G_2$ of graphs $G_1$ and $G_2$ is the graph with vertex set $V(G_1 \boxtimes G_2)=V(G_1)\times V(G_2)$, where two distinct vertices $(x_{1}, y_{1}),(x_{2}, y_{2}) \in V(G_1)\times V(G_2)$ are adjacent in $G_1 \boxtimes G_2$ if and only if $x_{1}=x_{2}$ and $y_{1} y_{2} \in E(G_2)$ or $y_{1}=y_{2}$ and $x_{1} x_{2} \in E(G_1)$ or $x_{1} x_{2} \in E(G_1)$ and $y_{1} y_{2} \in E(G_2)$. In this paper, we give the $g\ (\leq 3)$-$extra$ $connectivity$ of $G_1\boxtimes G_2$, where $G_i$ is a maximally connected $k_i\ (\geq 2)$-regular graph for $i=1,2$. As a byproduct, we get $g\ (\leq 3)$-$extra$ conditional fault-diagnosability of $G_1\boxtimes G_2$ under $PMC$ model

Relating Extra Connectivity and Extra Conditional Diagnosability in Regular Networks

The h-extra node-connectivity of a graph G is the size of a minimal node-set, whose removal will disconnect G, but each remaining component has no fewer h + 1 nodes. Based on h-extra node-connectivity, the h-extra conditional fault-diagnosability of networks has been proposed for a better, more realistic measure of networks\u27 fault-tolerability. It is the maximal x such that G is h-extra conditionally x-fault-diagnosable. This paper will establish a relationship between the h-extra node-connectivity and h-extra conditional fault-diagnosability for a regular graph G, under the classic PMC diagnostic model. We will apply the newly found relationship to a variety of well-known regular networks, to directly obtain their h-extra conditional fault-diagnosability. The significance of the paper\u27s work is that it relates the notions of h-extra node-connectivity and h-extra conditional fault-diagnosability, so that a regular network\u27s h-extra conditional fault-diagnosability may be known once its h-extra node-connectivity is known

Evaluation of C# for a station controller in a reconfigurable manufacturing system

Thesis (MEng)--Stellenbosch University, 2016.ENGLISH ABSTRACT: Reconfigurable manufacturing systems (RMSs) are aimed at dynamic situations, such as varying products, variations in production volume requirements and changes in available resources. RMSs distinguish themselves from other types of manufacturing systems in that they can quickly adapt to a new product being introduced without the need for long reconfiguration times, and can therefore cost effectively produce smaller batch sizes. RMSs in research environments in most cases used Agent Based Control (ABC), but the main automation vendors in the industry do not support ABC. This inhibits the acceptance of RMSs by the industry. For this research, C# was investigated as an alternative to ABC, since C# can provide for many of the functionalities of agents, yet is a more widely known language than ABC. Furthermore, C# is an object-oriented programming (OOP) language and thus possesses characteristics aligned with the core characteristics of reconfigurable manufacturing systems. The focus of this thesis is to determine the suitability of C# for the development of the control software for RMSs. This thesis describes the design, implementation, testing and evaluation of a reconfigurable stacking and buffering station. The controller was implemented in C# and made use of the ADACOR architecture. The physical test-setup was built to evaluate the reconfigurability of the controller in a series of reconfiguration experiments. The thesis showed that the controller could handle all the hardware interfaces without problems, since C# generally simplifies the task of hardware interfacing. OOP characteristics helped making developing and maintaining the code an intuitive task. The stacking station handled all communication with the cell controller correctly, which proved that it could easily be integrated into a distributed control architecture.AFRIKAANSE OPSOMMING: "Reconfigurable manufacturing systems" (RMSs) is gemik op dinamiese situasies, soos veranderende produkte, veranderings in produksievolumes en veranderinge in beskikbare hulpbronne. RMSs onderskei hulself van ander tipes vervaardigingstelsels deurdat hulle vinnig kan aanpas by nuwe produkte wat bekendgestel word sonder dat dit nodig is om die stelsel eers lank te herkonfigureer, en kan sodoende kleiner lotgroottes koste-effektief produseer. RMSs maak in navorsingmilieus meestal gebruik van "Agent Based Control" (ABC), maar die hoof outomatisasie-verkopers in die industrie ondersteun nie ABC nie. Dit belemmer die aanvaarding van RMSs in die industrie. Vir hierdie navorsing is C# as 'n alternatief vir ABC ondersoek omdat C# baie van die funksionaliteite kan voorsien wat aangetref word in ABC, maar terselfdertyd 'n meer bekende taal is as ABC. Verder is C# 'n objek-georiënteerde programmerings- (OOP) taal en beskik dus oor karakteristieke wat in lyn is met die kernkarakteristieke van RMSs. Die fokus van hierdie tesis is die geskiktheid van C# vir die ontwikkeling van beheersagteware vir 'n RMS. Hierdie tesis beskryf die ontwerp, implementering, toetsing en evaluering van 'n herkonfigureerbare stapel- en bufferstasie. Die beheerder was in C# geïmplementeer en het van die ADACOR-argitektuur gebruik gemaak. Die fisiese toets-opstelling was gebou om die herkonfigureerbaarheid van die beheerder te kan evalueer aan hand van 'n reeks herkonfigureringseksperimente. Die tesis het gewys dat die beheerder sonder probleme alle hardeware-intervlakke kon hanteer, omdat C# dit oor die algemeen vergemaklik om met hardeware te kommunikeer. OOP karakteristieke was nuttig om die ontwikkeling en instandhouding van die program intuïtief te maak. Die stapelstasie het alle kommunikasie met die selbeheerder korrek hanteer, wat bewys het dat dit probleemloos in 'n verspreide beheerargitektuur opgeneem kon word

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Fault Detection and Identification in Computer Networks: A soft Computing Approach

Governmental and private institutions rely heavily on reliable computer networks for their everyday business transactions. The downtime of their infrastructure networks may result in millions of dollars in cost. Fault management systems are used to keep today’s complex networks running without significant downtime cost, either by using active techniques or passive techniques. Active techniques impose excessive management traffic, whereas passive techniques often ignore uncertainty inherent in network alarms,leading to unreliable fault identification performance. In this research work, new algorithms are proposed for both types of techniques so as address these handicaps. Active techniques use probing technology so that the managed network can be tested periodically and suspected malfunctioning nodes can be effectively identified and isolated. However, the diagnosing probes introduce extra management traffic and storage space. To address this issue, two new CSP (Constraint Satisfaction Problem)-based algorithms are proposed to minimize management traffic, while effectively maintain the same diagnostic power of the available probes. The first algorithm is based on the standard CSP formulation which aims at reducing the available dependency matrix significantly as means to reducing the number of probes. The obtained probe set is used for fault detection and fault identification. The second algorithm is a fuzzy CSP-based algorithm. This proposed algorithm is adaptive algorithm in the sense that an initial reduced fault detection probe set is utilized to determine the minimum set of probes used for fault identification. Based on the extensive experiments conducted in this research both algorithms have demonstrated advantages over existing methods in terms of the overall management traffic needed to successfully monitor the targeted network system. Passive techniques employ alarms emitted by network entities. However, the fault evidence provided by these alarms can be ambiguous, inconsistent, incomplete, and random. To address these limitations, alarms are correlated using a distributed Dempster-Shafer Evidence Theory (DSET) framework, in which the managed network is divided into a cluster of disjoint management domains. Each domain is assigned an Intelligent Agent for collecting and analyzing the alarms generated within that domain. These agents are coordinated by a single higher level entity, i.e., an agent manager that combines the partial views of these agents into a global one. Each agent employs DSET-based algorithm that utilizes the probabilistic knowledge encoded in the available fault propagation model to construct a local composite alarm. The Dempster‘s rule of combination is then used by the agent manager to correlate these local composite alarms. Furthermore, an adaptive fuzzy DSET-based algorithm is proposed to utilize the fuzzy information provided by the observed cluster of alarms so as to accurately identify the malfunctioning network entities. In this way, inconsistency among the alarms is removed by weighing each received alarm against the others, while randomness and ambiguity of the fault evidence are addressed within soft computing framework. The effectiveness of this framework has been investigated based on extensive experiments. The proposed fault management system is able to detect malfunctioning behavior in the managed network with considerably less management traffic. Moreover, it effectively manages the uncertainty property intrinsically contained in network alarms,thereby reducing its negative impact and significantly improving the overall performance of the fault management system

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations