Framework for enterprise systems engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.

Bioinformatic analysis for exploring relationships between genes and gene products

To carry out their specific roles in the cell, genes and gene products often work together in groups, forming many relationships among themselves and with other molecules. Such relationships include physical protein-protein interaction relationships, regulatory relationships, metabolic relationships, genetic relationships, and much more. With advances in science and technology, some high throughput technologies have been developed to simultaneously detect tens of thousands of pairwise protein-protein interactions and protein-DNA interactions. However, the data generated by high throughput methods are prone to noise. Furthermore, the technology itself has its limitations, and cannot detect all kinds of relationships between genes and their products. Thus there is a pressing need to investigate all kinds of relationships and their roles in a living system using bioinformatic approaches, and is a central challenge in Computational Biology and Systems Biology. This dissertation focuses on exploring relationships between genes and gene products using bioinformatic approaches. Specifically, we consider problems related to regulatory relationships, protein-protein interactions, and semantic relationships between genes. A regulatory element is an important pattern or "signal", often located in the promoter of a gene, which is used in the process of turning a gene "on" or "off". Predicting regulatory elements is a key step in exploring the regulatory relationships between genes and gene products. In this dissertation, we consider the problem of improving the prediction of regulatory elements by using comparative genomics data. With regard to protein-protein interactions, we have developed bioinformatics techniques to estimate support for the data on these interactions. While protein-protein interactions and regulatory relationships can be detected by high throughput biological techniques, there is another type of relationship called semantic relationship that cannot be detected by a single technique, but can be inferred using multiple sources of biological data. The contributions of this thesis involved the development and application of a set of bioinformatic approaches that address the challenges mentioned above. These included (i) an EM-based algorithm that improves the prediction of regulatory elements using comparative genomics data, (ii) an approach for estimating the support of protein-protein interaction data, with application to functional annotation of genes, (iii) a novel method for inferring functional network of genes, and (iv) techniques for clustering genes using multi-source data.

Study of carbon nanotube film and shape memory alloys treatment for sensing and structural vibration control

Structural vibration control is of great importance. Current active and passive vibration control strategies usually employ individual elements to fulfill this task, such as viscoelastic patches for providing damping, transducers for picking up signals and actuators for inputting actuating forces. The goal of this dissertation work is to design, manufacture, investigate and apply a new type of multifunctional composite material for structural vibration control. This new composite, which is based on multi-walled carbon nanotube (MWCNT) film, is potentially to function as free layer damping treatment and strain sensor simultaneously. That is, the new material integrates the transducer and the damping patch into one element. The multifunctional composite was prepared by sandwiching the MWCNT film between two adhesive layers. Static sensing test indicated that the MWCNT film sensor resistance changes almost linearly with the applied load. Sensor sensitivity factors were comparable to those of the foil strain gauges. Dynamic test indicated that the MWCNT film sensor can outperform the foil strain gage in high frequency ranges. Temperature test indicated the MWCNT sensor had good temperature stability over the range of 237 K-363 K. The Young’s modulus and shear modulus of the MWCNT film composite were acquired by nanoindentation test and direct shear test, respectively. A free vibration damping test indicated that the MWCNT composite sensor can also provide good damping without adding excessive weight to the base structure. A new model for sandwich structural vibration control was then proposed. In this new configuration, a cantilever beam covered with MWCNT composite on top and one layer of shape memory alloy (SMA) on the bottom was used to illustrate this concept. The MWCNT composite simultaneously serves as free layer damping and strain sensor, and the SMA acts as actuator. Simple on-off controller was designed for controlling the temperature of the SMA so as to control the SMA recovery stress as input and the system stiffness. Both free and forced vibrations were analyzed. Simulation work showed that this new configuration for sandwich structural vibration control was successful especially for low frequency system.

Document understanding using data mining and machine learning techniques

With the explosive growth of the volume and complexity of document data (e.g., news, blogs, web pages), it has become a necessity to semantically understand documents and deliver meaningful information to users. Areas dealing with these problems are crossing data mining, information retrieval, and machine learning. For example, document clustering and summarization are two fundamental techniques for understanding document data and have attracted much attention in recent years. Given a collection of documents, document clustering aims to partition them into different groups to provide efficient document browsing and navigation mechanisms. One unrevealed area in document clustering is that how to generate meaningful interpretation for the each document cluster resulted from the clustering process. Document summarization is another effective technique for document understanding, which generates a summary by selecting sentences that deliver the major or topic-relevant information in the original documents. How to improve the automatic summarization performance and apply it to newly emerging problems are two valuable research directions. To assist people to capture the semantics of documents effectively and efficiently, the dissertation focuses on developing effective data mining and machine learning algorithms and systems for (1) integrating document clustering and summarization to obtain meaningful document clusters with summarized interpretation, (2) improving document summarization performance and building document understanding systems to solve real-world applications, and (3) summarizing the differences and evolution of multiple document sources.

Global Capitalism, Immigrant Labor, and the Struggle for Justice

Around the world borders are militarized, states are stepping up repressive anti-immigrant controls, and native publics are turning immigrants into scapegoats for the spiraling crisis of global capitalism. The massive displacement and primitive accumulation unleashed by free trade agreements and neo-liberal policies, as well as state and “private” violence has resulted in a virtually inexhaustible immigrant labor reserve for the global economy. State controls over immigration and immigrant labor have several functions for the system: 1) state repression and criminalization of undocumented immigration make immigrants vulnerable and deportable and therefore subject to conditions of super-exploitation, super-control and hyper-surveillance; 2) anti-immigrant repressive apparatuses are themselves ever more important sources of accumulation, ranging from private for-profit immigrant detention centers, to the militarization of borders, and the purchase by states of military hardware and systems of surveillance. Immigrant labor is extremely profitable for the transnational corporate economy; 3) the anti-immigrant policies associated with repressive state apparatuses help turn attention away from the crisis of global capitalism among more privileged sectors of the working class and convert immigrant workers into scapegoats for the crisis, thus deflecting attention from the root causes of the crisis and undermining working class unity. This article focuses on structural and historical underpinnings of the phenomenon of immigrant labor in the new global capitalist system and on how the rise of a globally integrated production and financial system, a transnational capitalist class, and transnational state apparatuses, have led to a reorganization of the world market in labor, including deeper reliance on a rapidly expanding reserve army of immigrant labor and a vicious new anti-immigrant politics. It looks at the United States as an illustration of the larger worldwide situation with regard to immigration and immigrant justice. Finally, it explores the rise of an immigrant justice movement around the world, observes the leading role that immigrant workers often play in worker’s struggles and that a mass immigrant rights movement is at the cutting edge of the struggle against transnational corporate exploitation. We call for replacing the whole concept of national citizenship with that of global citizenship as the only rallying cry that can assure justice and equality for all.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

Framework for Enterprise Systems Engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.

Design and Development of Geographical Information System (GIS) Map for Nuclear Waste Streams

A nuclear waste stream is the complete flow of waste material from origin to treatment facility to final disposal. The objective of this study was to design and develop a Geographic Information Systems (GIS) module using Google Application Programming Interface (API) for better visualization of nuclear waste streams that will identify and display various nuclear waste stream parameters. A proper display of parameters would enable managers at Department of Energy waste sites to visualize information for proper planning of waste transport. The study also developed an algorithm using quadratic Bézier curve to make the map more understandable and usable. Microsoft Visual Studio 2012 and Microsoft SQL Server 2012 were used for the implementation of the project. The study has shown that the combination of several technologies can successfully provide dynamic mapping functionality. Future work should explore various Google Maps API functionalities to further enhance the visualization of nuclear waste streams.

Paleomagnetic and beryllium isotope record of West Equatorial Pacific sediments

The reliability of paleomagnetic records as proxies of the geomagnetic field intensity is still a matter of controversy since volcanic materials hardly provide continuous records, and marine sediments are suspected to carry a remanence biased by post-depositional realignments and/or by overprints. Such long standing debate emphasizes the need for the development of methods independent from paleomagnetism to decipher geomagnetic intensity variations. High resolution measurements of authigenic 10Be/9Be along with a detailed sedimentary record of directional and relative paleointensity variations evidence, over the 0.6-1.3 Ma time interval, frequent and recurrent excursions or short events in the late Matuyama and the early Brunhes epochs, among which two Brunhes-Matuyama reversal precursors and an intra-Jaramillo excursion. The results of this study confirm the idea of a highly unstable geomagnetic field as suggested by paleomagnetic evidences.

Dynamic method of stiffness identification in impacting systems for percussive drilling applications

Peer reviewed

Simultaneous material and structural optimization by multiscale topology optimization

Acknowledgments The authors acknowledge the support from Engineering and Physical Sciences Research Council, grant number EP/M002322/1. The authors would also like to thank Numerical Analysis Group at the Rutherford Appleton Laboratory for their FORTRAN HSL packages (HSL, a collection of Fortran codes for large-scale scientific computation. See http://www.hsl.rl.ac.uk/).

Investigation of PHY, MAC and APP layers for adaptive and cross-layer optimization in IEEE802.11 WLAN

Due to huge popularity of portable terminals based on Wireless LANs and increasing demand for multimedia services from these terminals, the earlier structures and protocols are insufficient to cover the requirements of emerging networks and communications. Most research in this field is tailored to find more efficient ways to optimize the quality of wireless LAN regarding the requirements of multimedia services. Our work is to investigate the effects of modulation modes at the physical layer, retry limits at the MAC layer and packet sizes at the application layer over the quality of media packet transmission. Interrelation among these parameters to extract a cross-layer idea will be discussed as well. We will show how these parameters from different layers jointly contribute to the performance of service delivery by the network. The results obtained could form a basis to suggest independent optimization in each layer (an adaptive approach) or optimization of a set of parameters from different layers (a cross-layer approach). Our simulation model is implemented in the NS-2 simulator. Throughput and delay (latency) of packet transmission are the quantities of our assessments. © 2010 IEEE.

Robust H.264/AVC video transmission using data partitioning and unequal loss protection

In this work, we present an adaptive unequal loss protection (ULP) scheme for H264/AVC video transmission over lossy networks. This scheme combines erasure coding, H.264/AVC error resilience techniques and importance measures in video coding. The unequal importance of the video packets is identified in the group of pictures (GOP) and the H.264/AVC data partitioning levels. The presented method can adaptively assign unequal amount of forward error correction (FEC) parity across the video packets according to the network conditions, such as the available network bandwidth, packet loss rate and average packet burst loss length. A near optimal algorithm is developed to deal with the FEC assignment for optimization. The simulation results show that our scheme can effectively utilize network resources such as bandwidth, while improving the quality of the video transmission. In addition, the proposed ULP strategy ensures graceful degradation of the received video quality as the packet loss rate increases. © 2010 IEEE.

Impact of scatterer density on the performances of double-scattering MIMO channels

We investigate a MIMO double-scattering model with both local and remote scatterers, aiming to investigate the effect of scatterer density on channel performances, such as capacity, correlation, and the condition number of the channel matrix in flat and frequency-selective fading channels. The investigations are carried out in terms of scatterer density. It is shown that in flat fading channels the scatterer density has a marginal effect on channel performances when the area of the two scatterer zones is fixed, while a significant impact is observed when the area of the scatterer zones is allowed to change. In frequency-selective fading channels, no matter the area of the scatterer zones is fixed or not, scatterer density can affect the channel capacity to a certain degree that depends on the length of the coding block of the transmitted signals. © 2010 IEEE.

Sex offender risk assessment and management in Ireland

This research examined sex offender risk assessment and management in Ireland. It focused on the statutory agencies with primary responsibility (Garda Síochána and the Probation Service). The goal was to document the historical, contextual and current systems, in addition to identifying areas of concern/improvements. The research was a mixed-methods approach. Eight studies were conducted. This incorporated documentary reviews of four Commission to Inquire Reports, qualitative interviews/focus groups with Garda staff, Probation Service staff, statutory agencies, community stakeholders, various Non-Governmental Organisations (NGOs) and sex offenders. Quantitative questionnaires were also administered to Garda staff. In all over 70 interviews were conducted and questionnaires were forwarded to 270 Garda members. The overall findings are: •Sex offender management in Ireland has become formal only since 2001. Knowledge, skills and expertise is in its infancy and is still evolving. •Mixed reviews and questions regarding fitness for purpose of currently used risk assessments tools were noted. •The Sex Offender Act 2001 requires additional elements to ensure safe sex offender monitoring and public protection. A judicial review of the Sex Offender Act 2001 was recommended by many respondents. •Interagency working under SORAM was hugely welcomed. The sharing of information has been welcomed by managing agencies as the key benefit to improving sex offender management. •Respondents reported that in practice, sex offender management in Ireland is fragmented and unevenly implemented. The research concluded that an independent National Sex Offender Authority should be established as an oversight and regulatory body for policy, strategy and direction in sex offender management. Further areas of research were also highlighted: ongoing evaluation and audits of the joint agency process and systems in place; recidivism studies tracking the risk assessment ratings and subsequent offending; and an evaluation of the current status of sex offender housing in Ireland.