Signal processing using opto-electronic devices

All-optical signal processing is a powerful tool for the processing of communication signals and optical network applications have been routinely considered since the inception of optical communication. There are many successful optical devices deployed in today’s communication networks, including optical amplification, dispersion compensation, optical cross connects and reconfigurable add drop multiplexers. However, despite record breaking performance, all-optical signal processing devices have struggled to find a viable market niche. This has been mainly due to competition from electro-optic alternatives, either from detailed performance analysis or more usually due to the limited market opportunity for a mid-link device. For example a wavelength converter would compete with a reconfigured transponder which has an additional market as an actual transponder enabling significantly more economical development. Never-the-less, the potential performance of all-optical devices is enticing. Motivated by their prospects of eventual deployment, in this chapter we analyse the performance and energy consumption of digital coherent transponders, linear coherent repeaters and modulator based pulse shaping/frequency conversion, setting a benchmark for the proposed all-optical implementations.

Case-Based Reasoning Tools from Shells to Object-Oriented Frameworks

A Case-Based Reasoning (CBR) tool is software that can be used to develop several applications that require cased-based reasoning methodology. CBR shells are kind of application generators with graphical user interface. They can be used by non-programmer users but the extension or integration of new components in these tools is not possible. In this paper we analyzed three CBR object-oriented framework development environments CBR*Tools, CAT-CBR, and JColibri. These frameworks work as open software development environment and facilitate the reuse of their design as well as implementations.

Extension of the C-XSC Library with Scalar Products with Selectable Accuracy

The C++ class library C-XSC for scientific computing has been extended with the possibility to compute scalar products with selectable accuracy in version 2.3.0. In previous versions, scalar products have always been computed exactly with the help of the so-called long accumulator. Additionally, optimized floating point computation of matrix and vector operations using BLAS-routines are added in C-XSC version 2.4.0. In this article the algorithms used and their implementations, as well as some potential pitfalls in the compilation, are described in more detail. Additionally, the theoretical background of the employed DotK algorithm and the necessary modifications of the concrete implementation in C-XSC are briefly explained. Run-time tests and numerical examples are presented as well.

Detecting EPCIS exceptions in linked traceability streams across supply chain business processes

The EPCIS specification provides an event oriented mechanism to record product movement information across stakeholders in supply chain business processes. Besides enabling the sharing of event-based traceability datasets, track and trace implementations must also be equipped with the capabilities to validate integrity constraints and detect runtime exceptions without compromising the time-to-deliver schedule of the shipping and receiving parties. In this paper we present a methodology for detecting exceptions arising during the processing of EPCIS event datasets. We propose an extension to the EEM ontology for modelling EPCIS exceptions and show how runtime exceptions can be detected and reported. We exemplify and evaluate our approach on an abstraction of pharmaceutical supply chains.

Phase-conjugated pilots for fibre nonlinearity compensation in CO-OFDM transmission

In this paper, we demonstrate a novel fiber nonlinearity compensation technique for coherent optical orthogonal frequency-division multiplexing (CO-OFDM) systems based on the transmission of phase-conjugated pilots (PCPs). In this scheme, a portion of OFDM subcarriers (up to 50%) is transmitted with its phase conjugates, which is used at the receiver to estimate the nonlinear distortions in the respective subcarriers and other subcarriers, which are not accompanied by PCPs. Simulation and experimental results show that by varying the PCP overhead, a performance improvement up to 4 dB can be achieved. In addition, the proposed technique can be effectively applied in both single polarization and polarization-division multiplexed systems, in both single channel and wavelength-division multiplexing systems, thus, offering highest flexibility in implementations.

JSONYA/FN: Functional Computation in JSON

Functional programming has a lot to offer to the developers of global Internet-centric applications, but is often applicable only to a small part of the system or requires major architectural changes. The data model used for functional computation is often simply considered a consequence of the chosen programming style, although inappropriate choice of such model can make integration with imperative parts much harder. In this paper we do the opposite: we start from a data model based on JSON and then derive the functional approach from it. We outline the identified principles and present Jsonya/fn — a low-level functional language that is defined in and operates with the selected data model. We use several Jsonya/fn implementations and the architecture of a recently developed application to show that our approach can improve interoperability and can achieve additional reuse of representations and operations at relatively low cost. ACM Computing Classification System (1998): D.3.2, D.3.4.

Do manufacturing firms need informality in ERP post-implementation? A study of Chinese manufacturing sites

Purpose - Enterprise resource planning (ERP) systems are limited due to their operation around a fixed design production process and a fixed lead time to production plan and purchasing plan. The purpose of this paper is to define the concept of informality and to describe the notion of a system combining informality and ERP systems, based on empirical research from four manufacturing case studies. Design/methodology/approach - The case studies present a range of applications of ERP and are analysed in terms of the three characteristics of informality, namely, organisation structure, communication method and leadership approach. Findings - The findings suggest that systems consisting of informality in combination with ERP systems can elicit knowledge fromfrontlineworkers leading to timely improvements in the system. This is achieved by allowing users to modify work procedures or production orders, and to support collaborative working among all employees. However it was found that informality is not required for manufacturers with a relatively stable environment who can deal with uncertainty with a proactive strategy. Research limitations/implications - This study was carried out in China, with four companies as unit of analysis. Future work can help to extend this study across countries. Originality/value - The use of Four dimensions of informality that relate to manufacturers implementing ERP are defined as "technology in practice", "user flexibility", "trusted human networks" and "positive reaction to uncertainty". This is a new construct not applied before to ERP implementations.

Building the hybrid organisation through ERP and enterprise social software

This research traces the implementation of an information system in the form of ERP modules covering tenant and contract management in a Chinese service company. Misalignments between the ERP system specification and user needs led to the adoption of informal processes within the organisation. These processes are facilitated within an informal organisational structure and are based on human interactions undertaken within the formal organisation. Rather than to attempt to suppress the emergence of the informal organisation the company decided to channel the energies of staff involved in informal processes towards organisational goals. The company achieved this by harnessing the capabilities of what we term a hybrid ERP system, combining the functionality of a traditional (formal) ERP installation with the capabilities of Enterprise Social Software (ESS). However the company recognised that the successful operation of the hybrid ERP system would require a number of changes in organisational design in areas such as reporting structures and communication channels. A narrative provided by interviews with company personnel is thematised around the formal and informal characteristics of the organisation as defined in the literature. This leads to a definition of the characteristics of the hybrid organisation and strategies for enabling a hybrid organisation, facilitated by a hybrid ERP system, which directs formal and informal behaviour towards organisational goals and provides a template for future hybrid implementations.

Next generation high density three-dimensional magnetic recording systems

This work is the first work using patterned soft underlayers in multilevel three-dimensional vertical magnetic data storage systems. The motivation stems from an exponentially growing information stockpile, and a corresponding need for more efficient storage devices with higher density. The world information stockpile currently exceeds 150EB (ExaByte=1x1018Bytes); most of which is in analog form. Among the storage technologies (semiconductor, optical and magnetic), magnetic hard disk drives are posed to occupy a big role in personal, network as well as corporate storage. However; this mode suffers from a limit known as the Superparamagnetic limit; which limits achievable areal density due to fundamental quantum mechanical stability requirements. There are many viable techniques considered to defer superparamagnetism into the 100's of Gbit/in2 such as: patterned media, Heat-Assisted Magnetic Recording (HAMR), Self Organized Magnetic Arrays (SOMA), antiferromagnetically coupled structures (AFC), and perpendicular magnetic recording. Nonetheless, these techniques utilize a single magnetic layer; and can thusly be viewed as two-dimensional in nature. In this work a novel three-dimensional vertical magnetic recording approach is proposed. This approach utilizes the entire thickness of a magnetic multilayer structure to store information; with potential areal density well into the Tbit/in2 regime. ^ There are several possible implementations for 3D magnetic recording; each presenting its own set of requirements, merits and challenges. The issues and considerations pertaining to the development of such systems will be examined, and analyzed using empirical and numerical analysis techniques. Two novel key approaches are proposed and developed: (1) Patterned soft underlayer (SUL) which allows for enhanced recording of thicker media, (2) A combinatorial approach for 3D media development that facilitates concurrent investigation of various film parameters on a predefined performance metric. A case study is presented using combinatorial overcoats of Tantalum and Zirconium Oxides for corrosion protection in magnetic media. ^ Feasibility of 3D recording is demonstrated, and an emphasis on 3D media development is emphasized as a key prerequisite. Patterned SUL shows significant enhancement over conventional "un-patterned" SUL, and shows that geometry can be used as a design tool to achieve favorable field distribution where magnetic storage and magnetic phenomena are involved. ^

A framework for transforming, analyzing, and realizing software designs in unified modeling language

Unified Modeling Language (UML) is the most comprehensive and widely accepted object-oriented modeling language due to its multi-paradigm modeling capabilities and easy to use graphical notations, with strong international organizational support and industrial production quality tool support. However, there is a lack of precise definition of the semantics of individual UML notations as well as the relationships among multiple UML models, which often introduces incomplete and inconsistent problems for software designs in UML, especially for complex systems. Furthermore, there is a lack of methodologies to ensure a correct implementation from a given UML design. The purpose of this investigation is to verify and validate software designs in UML, and to provide dependability assurance for the realization of a UML design.^ In my research, an approach is proposed to transform UML diagrams into a semantic domain, which is a formal component-based framework. The framework I proposed consists of components and interactions through message passing, which are modeled by two-layer algebraic high-level nets and transformation rules respectively. In the transformation approach, class diagrams, state machine diagrams and activity diagrams are transformed into component models, and transformation rules are extracted from interaction diagrams. By applying transformation rules to component models, a (sub)system model of one or more scenarios can be constructed. Various techniques such as model checking, Petri net analysis techniques can be adopted to check if UML designs are complete or consistent. A new component called property parser was developed and merged into the tool SAM Parser, which realize (sub)system models automatically. The property parser generates and weaves runtime monitoring code into system implementations automatically for dependability assurance. The framework in the investigation is creative and flexible since it not only can be explored to verify and validate UML designs, but also provides an approach to build models for various scenarios. As a result of my research, several kinds of previous ignored behavioral inconsistencies can be detected.^

Efficient storage and domain-specific information discovery on semistructured documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. ^ Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. ^ This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model’s parsing mechanism. ^ The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents. ^

Knowledge creation in dynamic learning environments

Researchers have extensively discussed using knowledge management to achieve sustainable competitive advantages; however, the successful implementation of knowledge management programs in organizations remains challenging. Problems with knowledge management arise primarily from issues related to inter-subjective creation of meaning by diverse individuals in a dynamic learning environment. ^ The first part of this dissertation examined the concepts of shared interpretive resources referring to background assumptions, shared language, and symbolic resources upon which individuals draw in their interactions in the community. The discussion adopted an interpretive research approach to underscore how community members develop shared interpretive resources over time. The second part examined how learners' behaviors influence knowledge acquisition in the community, emphasizing the associations between learners' learning approaches and learning contexts. An empirical survey of learners provided significant evidence to demonstrate the influences of learners' learning approaches. The third part examined an instructor's strategy—namely, advance organizer—to enhance learners' knowledge assimilation process. Advance organizer is an instructor strategy that refers to a set of inclusive concepts that introduce and sum up new material, and refers to a method of bridging and linking old information with something new. In this part, I underscore the concepts of advance organizer, and the implementations of advance organizer in one learning environment. A study was conducted in one higher educational environment to show the implementation of advance organizer. Additionally, an advance organizer instrument was developed and tested, and results from learners' feedback were analyzed. The significant empirical evidence showed the association between learners' learning outcomes and the implementation of advance organizer strategy. ^

Large scale data processing using MapReduce

As massive data sets become increasingly available, people are facing the problem of how to effectively process and understand these data. Traditional sequential computing models are giving way to parallel and distributed computing models, such as MapReduce, both due to the large size of the data sets and their high dimensionality. This dissertation, as in the same direction of other researches that are based on MapReduce, tries to develop effective techniques and applications using MapReduce that can help people solve large-scale problems. Three different problems are tackled in the dissertation. The first one deals with processing terabytes of raster data in a spatial data management system. Aerial imagery files are broken into tiles to enable data parallel computation. The second and third problems deal with dimension reduction techniques that can be used to handle data sets of high dimensionality. Three variants of the nonnegative matrix factorization technique are scaled up to factorize matrices of dimensions in the order of millions in MapReduce based on different matrix multiplication implementations. Two algorithms, which compute CANDECOMP/PARAFAC and Tucker tensor decompositions respectively, are parallelized in MapReduce based on carefully partitioning the data and arranging the computation to maximize data locality and parallelism.

Wage matters & globalization: South Florida's low-wage immigrant plant nursery workers and business protectionism in the age of neoliberalism

Ornamental plant production in the State of Florida is an anomaly with respect to current theories of globalization and particularly their explanation of the employment of low-wage, immigrant labor. Those theories dictate that unskilled jobs that do not need to be performed within highly developed countries are outsourced to where labor is cheaper and more flexible. However, the State of Florida remains an important site of ornamental plant production in the US amidst a global economic environment of outsourcing and transnational corporate expansion. This dissertation relies on 50 semi-structured interviews with insiders of the Florida plant nursery industry, focus groups, and participant observation to explain how US trade, labor, and migration policy-making at local levels are not removed from larger global processes taking place in the world since the 1970s. In Florida, elite market players of the plant nursery industry have been able to resist global trends in free trade, operating instead in a protected market. They have done this by appealing to scientific justifications and through arbitrary implementations of neoliberal ideology that keeps small and middle range business alive, while maintaining a seemingly endless supply of marginalized and exploited low-wage, immigrant workers.^

What Google Maps can do for Biomedical Data Dissemination: Examples and a Design Study

Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.