A Conceptual Architecture of Ontology Based KM System for Failure Mode and Effects Analysis

Failure Mode and Effects Analysis (FMEA) is a systematic method forprocedure analyses and risk assessment. It is a structured way to identify potentialfailure modes of a product or process, probability of their occurrence, and their overalleffects. The basic purpose of this analysis is to mitigate the risk and the impactassociated to a failure by planning and prioritizing actions to make a product or aprocess robust to failure. Effective manufacturing and improved quality productsare the fruits of successful implementation of FMEA. During this activity valuableknowledge is generated which turns into product or process quality and efficiency. Ifthis knowledge can be shared and reused then it would be helpful in early identificationof failure points and their troubleshooting, and will also help the quality managementto get decision support in time. But integration and reuse of this knowledge is difficultbecause there are number of challenges e.g., unavailability of unified criteria of FMEAknowledge, lack of semantic organization, natural language text based description ofknowledge, most of the times FMEA is started from scratch instead of using existingknowledge that makes it incomplete for larger systems, and above all its successdepends on the knowledge which is stored in the brains of perfectionists in the formof experience which may or may not be available anytime anywhere. In this article weare proposing an Information and Communication Technology (ICT) based solutionto preserve, reuse, and share the valuable knowledge produced during FMEA. Inproposed system existing knowledge available in repositories and experts head will begathered and stored in a knowledge base using an ontology, and at the time of need thisknowledge base will be inferred to make decisions in order to mitigate the probablerisks. Ontology based approaches are best suited for the knowledge managementsystems, in which human experts are required to model and analyze their expertisein order to feed them in a conceptual knowledge base for its preservation and reuse

Adaptive and survivable trust management for Internet of Things systems

Abstract The Internet of Things (IoT) is characterized by the seamless integration of heterogeneous devices into information networks to enable collaborative environments, specifically those concerning the collection of data and exchange of information and services. Security and trustworthiness are among the critical requirements for the effective deployment of IoT systems. However, trust management in IoT is extremely challenging due to its open environment, where the quality of information is often unknown because entities may misbehave. A hybrid context‐aware trust and reputation management protocol is presented for fog‐based IoT that addresses adaptivity, survivability, and scalability requirements. Through simulation, the effectiveness of the proposed protocol is demonstrated

An Ontology to Support Semantic Management of FMEA Knowledge

Risk mitigation has always been a special concern for organization’s strategic management. Various tools and techniques have been developed to manage risk in an effective way. Failure Mode and Effects Analysis (FMEA) is one of the tools used for effective assessment of risk. It analyzes all potential failure modes, their causes, and effects on a product or process. Moreover it recommends actions to mitigate failures in order to enhance product reliability. Organizations spend their resources and domain experts make their efforts to complete this analysis. It further helps organizations identify the expected risks and plan strategies in advance to tackle them. But unfortunately the analysis produced after spending a lot of organizational assets and experts’ struggles, is not reusable due to its natural language text based description. Information and communication technology experts proposed some solutions but they are associated with some deficiencies. Authors in [13] proposed an ontology based solution to extract and reuse FMEA knowledge from the textual documents, and this article is the first step towards its implementation. In this article we proposed our ontology for Process Failure Mode and Effects Analysis (PFMEA) for automotive domain, along with its implementation, reasoning, and data retrieval through it

Context-aware pending interest table management scheme for NDN-based VANETs

In terms of delivery effectiveness, Vehicular Adhoc NETworks (VANETs) applications have multiple, possibly conflicting, and disparate needs (e.g., latency, reliability, and delivery priorities). Named Data Networking (NDN) has attracted the attention of the research community for effective content retrieval and dissemination in mobile environments such as VANETs. A vehicle in a VANET application is heavily reliant on information about the content, network, and application, which can be obtained from a variety of sources. The information gathered can be used as context to make better decisions. While it is difficult to obtain the necessary context information at the IP network layer, the emergence of NDN is changing the tide. The Pending Information Table (PIT) is an important player in NDN data retrieval. PIT size is the bottleneck due to the limited opportunities provided by current memory technologies. PIT overflow results in service disruptions as new Interest messages cannot be added to PIT. Adaptive, context-aware PIT entry management solutions must be introduced to NDN-based VANETs for effective content dissemination. In this context, our main contribution is a decentralised, context-aware PIT entry management (CPITEM) protocol. The simulation results show that the proposed CPITEM protocol achieves lower Interest Satisfaction Delay and effective PIT utilization based on context when compared to existing PIT entry replacement protocols

Policy analysis of girls’ primary school completion in rural Sindh: Root causes and policy recommendations using IIEP education policy toolbox

This report emerged from the policy analysis work produced as part of the course titled ‘Diagnostic tools for improving education policy planning’ by the IIEP-UNESCO with support from KIX. This course enabled us to explore diagnostic tools and their implications, specifically for developing countries, and helped the team unpack diagnostic tools and learn the history of their evolution. We further learned how the education management information system works and how data is essential for policy decisions. Finally, we engaged with real policy analysis using the IIEP Education Policy Toolbox. As a team, we chose to study the issue of girls’ completion of primary education in two districts of the Sindh province: Larkana and Dadu. Using the Policy Toolbox, we made a policy decision tree, gathered data that could help us understand each factor and then made policy decisions and forward policy recommendations

Numerical Approximation of Bounds of µ-Values for a Family of Pascal Matrices

In this article, we present numerical approximations to lower bounds of Structured Singular Values (SSV) for a family of Pascal matrices. In mathematics, particularly in matrix theory, Pascal matrix is an infinite matrix containing the binomial coefficients as its elements. The obtained lower bounds of SSV are then compared with the well-known MATLAB routine mussv available in MATLAB Control Toolbox

Context-Aware Naming and Forwarding in NDN-Based VANETs

Vehicular ad-hoc network (VANET) is a technology that allows ubiquitous mobility to mobile users. Inter-vehicle communication is an integral component of intelligent transportation systems that enables a wide variety of applications where vehicles interact and cooperate with each other, from safety applications to non-safety applications. VANETs applications have different needs (e.g., latency, reliability, delivery priorities, etc.) in terms of delivery effectiveness. In the last decade, named data networking (NDN) gained the attention of the research community for effective content retrieval and dissemination in mobile environments such as VANETs. In NDN, the content’s name has a vital role in storing and retrieving the content effectively and efficiently. In NDN-based VANETs, adaptive content dissemination solutions must be introduced that can make decisions related to forwarding, cache management, etc., based on context information represented by a content name. In this context, our main contributions are two-fold: (i) we present the hierarchical context-aware content-naming (CACN) scheme for NDN-based VANETs that enables naming the safety and non-safety applications, and (ii) we present a decentralized context-aware notification (DCN) protocol that broadcasts event notification information for awareness within the application-based geographical area. Simulation results show that the proposed DCN protocol succeeds in achieving reduced transmissions, bandwidth, and energy compared to existing critical contents dissemination protocols