Test analysis & fault simulation of microfluidic systems

This work presents a design, simulation and test methodology for microfluidic systems, with particular focus on simulation for test. A Microfluidic Fault Simulator (MFS) has been created based around COMSOL which allows a fault-free system model to undergo fault injection and provide test measurements. A post MFS test analysis procedure is also described.A range of fault-free system simulations have been cross-validated to experimental work to gauge the accuracy of the fundamental simulation approach prior to further investigation and development of the simulation and test procedure.A generic mechanism, termed a fault block, has been developed to provide fault injection and a method of describing a low abstraction behavioural fault model within the system. This technique has allowed the creation of a fault library containing a range of different microfluidic fault conditions. Each of the fault models has been cross-validated to experimental conditions or published results to determine their accuracy.Two test methods, namely, impedance spectroscopy and Levich electro-chemical sensors have been investigated as general methods of microfluidic test, each of which has been shown to be sensitive to a multitude of fault. Each method has successfully been implemented within the simulation environment and each cross-validated by first-hand experimentation or published work.A test analysis procedure based around the Neyman-Pearson criterion has been developed to allow a probabilistic metric for each test applied for a given fault condition, providing a quantitive assessment of each test. These metrics are used to analyse the sensitivity of each test method, useful when determining which tests to employ in the final system. Furthermore, these probabilistic metrics may be combined to provide a fault coverage metric for the complete system.The complete MFS method has been applied to two system cases studies; a hydrodynamic “Y” channel and a flow cytometry system for prognosing head and neck cancer.Decision trees are trained based on the test measurement data and fault conditions as a means of classifying the systems fault condition state. The classification rules created by the decision trees may be displayed graphically or as a set of rules which can be loaded into test instrumentation. During the course of this research a high voltage power supply instrument has been developed to aid electro-osmotic experimentation and an impedance spectrometer to provide embedded test

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Microfluidics for Biosensing

There are 12 papers published with 8 research articles, 3 review articles and 1 perspective. The topics cover: Biomedical microfluidics Lab-on-a-chip Miniaturized systems for chemistry and life science (MicroTAS) Biosensor development and characteristics Imaging and other detection technologies Imaging and signal processing Point-of-care testing microdevices Food and water quality testing and control We hope this collection could promote the development of microfluidics and point-of-care testing (POCT) devices for biosensing

A review of applications of fuzzy sets to safety and reliability engineering

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering

Multi-constrained mechanism for intra-body area network quality-of-service aware routing in wireless body sensor networks

Wireless Body Sensor Networks (WBSNs) have witnessed tremendous research interests in a wide range of medical and non-medical fields. In the delaysensitive application scenarios, the critical data packets are highly delay-sensitive which require some Quality-of-Service (QoS) to reach the intended destinations. The categorization of data packets and selection of poor links may have detrimental impacts on overall performance of the network. In WBSN, various biosensors transmit the sensed data towards a destination for further analysis. However, for an efficient data transmission, it is very important to transmit the sensed data towards the base station by satisfying the QoS multi-constrained requirements of the healthcare applications in terms of least end-to-end delay and high reliability, throughput, Packet Delivery Ratio (PDR), and route stability performance. Most of the existing WBSN routing schemes consider traffic prioritization to solve the slot allocation problem. Consequently, the data transmission may face high delays, packet losses, retransmissions, lack of bandwidth, and insufficient buffer space. On the other hand, an end-to-end route is discovered either using a single or composite metric for the data transmission. Thus, it affects the delivery of the critical data through a less privileged manner. Furthermore, a conventional route repair method is considered for the reporting of broken links which does not include surrounding interference. As such, this thesis presents the Multi-constrained mechanism for Intra- Body Area Network QoS aware routing (MIQoS) with Low Latency Traffic Prioritization (LLTP), Optimized Route Discovery (ORD), and Interference Adaptive Route Repair (IARR) schemes for the healthcare application of WBSN with an objective of improving performance in terms of end-to-end delay, route stability, and throughput. The proposed LLTP scheme considers various priority queues with an optimized scheduling mechanism that dynamically identifies and prioritizes the critical data traffic in an emergency situation to enhance the critical data transmission. Consequently, this will avoid unnecessary queuing delay. The ORD scheme incorporates an improved and multi-facet routing metric, Link Quality Metric (LQM) optimizes the route selection by considering link delay, link delivery ratio, and link interference ratio. The IARR scheme identifies the links experiencing transmission issues due to channel interference and makes a coherent decision about route breakage based on the long term link performance to avoid unnecessary route discovery notifications. The simulation results verified the improved performance in terms of reducing the end-to-end delay by 29%, increasing the throughput by 22% and route stability by 26% as compared to the existing routing schemes such as TTRP, PA-AODV and standard AODV. In conclusion, MIQoS proves to be a suitable routing mechanism for a wide range of interesting applications of WBSN that require fast, reliable and multi-hop communication in heavily loaded network traffic scenarios

Evolvable Smartphone-Based Point-of-Care Systems For In-Vitro Diagnostics

Recent developments in the life-science -omics disciplines, together with advances in micro and nanoscale technologies offer unprecedented opportunities to tackle some of the major healthcare challenges of our time. Lab-on-Chip technologies coupled with smart-devices in particular, constitute key enablers for the decentralization of many in-vitro medical diagnostics applications to the point-of-care, supporting the advent of a preventive and personalized medicine. Although the technical feasibility and the potential of Lab-on-Chip/smart-device systems is repeatedly demonstrated, direct-to-consumer applications remain scarce. This thesis addresses this limitation. System evolvability is a key enabler to the adoption and long-lasting success of next generation point-of-care systems by favoring the integration of new technologies, streamlining the reengineering efforts for system upgrades and limiting the risk of premature system obsolescence. Among possible implementation strategies, platform-based design stands as a particularly suitable entry point. One necessary condition, is for change-absorbing and change-enabling mechanisms to be incorporated in the platform architecture at initial design-time. Important considerations arise as to where in Lab-on-Chip/smart-device platforms can these mechanisms be integrated, and how to implement them. Our investigation revolves around the silicon-nanowire biological field effect transistor, a promising biosensing technology for the detection of biological analytes at ultra low concentrations. We discuss extensively the sensitivity and instrumentation requirements set by the technology before we present the design and implementation of an evolvable smartphone-based platform capable of interfacing lab-on-chips embedding such sensors. We elaborate on the implementation of various architectural patterns throughout the platform and present how these facilitated the evolution of the system towards one accommodating for electrochemical sensing. Model-based development was undertaken throughout the engineering process. A formal SysML system model fed our evolvability assessment process. We introduce, in particular, a model-based methodology enabling the evaluation of modular scalability: the ability of a system to scale the current value of one of its specification by successively reengineering targeted system modules. The research work presented in this thesis provides a roadmap for the development of evolvable point-of-care systems, including those targeting direct-to-consumer applications. It extends from the early identification of anticipated change, to the assessment of the ability of a system to accommodate for these changes. Our research should thus interest industrials eager not only to disrupt, but also to last in a shifting socio-technical paradigm