Picosecond pulse source for OTDM/WDM applications based on arrayed waveguide grating

A novel technique for high quality femtosecond pulse generation from a gain-switched laser diode by means of pulse compression and transformation in a compact nonlinear fiber device, based on a dispersion-imbalanced fiber loop mirror (DILM) is demonstrated. This source allows the generation of extremely high quality pulses as short as 270 fs on demand with strong suppression of pulse pedestals. Spectral filtering in arrayed waveguide grating (AWG) converts the device into a compact multiwavelength source of high-quality picosecond pulses for optical time division multiplexing/wavelength division multiplexing applications.

The effects of corona treatment on impact and spreading of ink-jet drops on a polymeric film substrate

The effects of varying corona surface treatment on ink drop impact and spreading on a polymer substrate have been investigated. The surface energy of substrates treated with different levels of corona was determined from static contact angle measurement by the Owens and Wendt method. A drop-on-demand print-head was used to eject 38 μm diameter drops of UV-curable graphics ink travelling at 2.7 m/s on to a flat polymer substrate. The kinematic impact phase was imaged with a high speed camera at 500k frames per second, while the spreading phase was imaged at 20k frames per secoiui. The resultant images were analyzed to track the changes in the drop diameter during the different phases of drop spreading. Further experiments were carried out with white-light intetferometry to accurately measure the final diameter of drops which had been printed on different corona treated substrates and UV cured. The results are correlated to characterize the effects of corona treatment on drop impact behavior and final print quality.

The impact of government policy on technology transfer: An aircraft industry case study

This case study explores the interaction between domestic and foreign governmental policy on technology transfer with the goal of exploring the long-term impacts of technology transfer. Specifically, the impact of successive licensing of fighter aircraft manufacturing and design to Japan in the development of Japan's aircraft industry is reviewed. Results indicate Japan has built a domestic aircraft industry through sequential learning with foreign technology transfers from the United States, and design and production on domestic fighter aircraft. This process was facilitated by governmental policies in both Japan and the United States. Published by Elsevier B.V.

Future, opportunities and challenges of inkjet technologies

Inkjet printing relies on the formation of small liquid droplets to deliver precise amounts of material to a substrate under digital control. Inkjet technology is becoming relatively mature and is of great industrial interest thanks to its flexibility for graphical printing and its potential use in less conventional applications such as additive manufacturing and the production of printed electronics and other functional devices. Its advantages over traditional methods of printing include the following: it produces little or no waste, it is versatile because several different methods exist, it is noncontact, and it does not require a master template so that printed patterns can be readily modified on demand. However, the technology is in need of further development to become mainstream in emerging applications such as additive manufacturing (3D printing). This review contains a description of conventional and less common inkjet methods and surveys the current applications of inkjet in industry. This is followed by specific examples of the barriers, limitations, and challenges faced by inkjet technology in both graphical printing and manufacturing. © 2013 by Begell House, Inc.

Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions.

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions.

Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions. © 2014 Elsevier Ltd.

Research on micro-optical lenses fabrication technology

We present a detail investigation on the development of a series of gradient index (GRIN) optical glass microlens and polymer microlens and microlens arrays in our laboratory in recent years. The special glass material GRIN lenses have been fabricated mainly by using ion-exchange technology, which are applied to construct micro-optic devices and other applications. On one hand, we demonstrated the light propagation and imaging properties of GRIN lenses and the results analyzed. On the other hand, we have explored a drop-on-demand ink-jet printing method to produce microlens array using nano-scale polymer droplets involved with a uniform ultraviolet light and heat solidifying process. The experimental setup for manufacturing polymer microlens array and the performance of refractive microlens elements are also given in this paper. (C) 2006 Elsevier GmbH. All rights reserved.

The comparative estimation of phytoplanktonic, microphytobenthic and macrophytobenthic primary production in the oceans

The contributions of the planktonic unicellular algae [phytoplankton), the benthic unicellular algae [microphytobenthos) and the benthic multicellular algae (macrophytobenthos) to the primary production of the world ocean are evaluated, together with the respective limitations regarding data, concepts and methods. The use of “free-water” methods (e.g. in situ oxygen or CO2 budgets) is recommended in complement to the more specific measurements on enclosed organisms. For phytoplankton, a previous estimate of 30 . lo9 t C y-’ is retained as a minimal estimate. Earlier estimates of the world benthic production have been based on indirect calculations; revised estimates are suggested here which still lack precision but rely on the actual measurements available at present. Primary production of the micro- and macrobenthic algae amount to 50 and 375 g C m-? y-’ respectively as averages for the whole photic layer they can colonize, and total 2.9 . 10‘ t C y-’ for the world ocean. Thus, benthic algae contribute some 10% of the total marine primary production. On the continental shelf alone, the contributions of benthic and planktonib algae are commensurate and nearly equivalent.

SIZE STRUCTURES OF MICROPLANKTON BIOMASS AND PRODUCTION IN JIAOZHOU BAY, CHINA

Seasonal investigations of size-fractionated biomass and production were carried out from February 1992 to May 1993 in Jiaozhou Bay, China. Microplankton assemblages were separated into three fractions: pico-(0.7-2 mu m), nano- (2-20 mu m) and netplankton (20-200 mu m). The biomass was measured as chlorophyll a (Chl a), particulate organic carbon (POC) and particulate organic nitrogen (PON). The production was determined by C-14 and N-15 tracer techniques. The seasonal patterns in biomass, though variable, were characterized by higher values in spring and lower values in autumn and summer (for Chl a only). The seasonal patterns in production, on the other hand, were more clear with higher values occurring in summer and spring, and lower values occurring in autumn and winter. Averaged over the whole study period, the respective proportions of total biomass accounted for by net-, nano- and picoplankton were 26, 45 and 29% for Chl a, 32, 33 and 35% for POC, and 26, 32 and 42% for PON. The contributions to total primary production by net-, nano- and picoplankton were 31, 35 and 34%, respectively. The respective proportions of total NH4+-N uptake accounted for by net-, nano- and picoplankton were 28, 33 and 39% in the daytime, and 10, 29 and 61% at night. The respective contributions to total NO3--N uptake by net-, nano- and picoplankton were 37, 40 and 23% in the daytime, and 13, 23 and 64% at night. Some comprehensive ratios, including C/N biomass ratio, Chl a/C ratio, C uptake/Chl a ratio, C:N uptake ratio and the f-ratio, were also calculated size separately, and their biological and ecological meanings are discussed.

A Two-Tiered On-Line Server-Side Bandwidth Reservation Framework for the Real-Time Delivery of Multiple Video Streams

The advent of virtualization and cloud computing technologies necessitates the development of effective mechanisms for the estimation and reservation of resources needed by content providers to deliver large numbers of video-on-demand (VOD) streams through the cloud. Unfortunately, capacity planning for the QoS-constrained delivery of a large number of VOD streams is inherently difficult as VBR encoding schemes exhibit significant bandwidth variability. In this paper, we present a novel resource management scheme to make such allocation decisions using a mixture of per-stream reservations and an aggregate reservation, shared across all streams to accommodate peak demands. The shared reservation provides capacity slack that enables statistical multiplexing of peak rates, while assuring analytically bounded frame-drop probabilities, which can be adjusted by trading off buffer space (and consequently delay) and bandwidth. Our two-tiered bandwidth allocation scheme enables the delivery of any set of streams with less bandwidth (or equivalently with higher link utilization) than state-of-the-art deterministic smoothing approaches. The algorithm underlying our proposed frame-work uses three per-stream parameters and is linear in the number of servers, making it particularly well suited for use in an on-line setting. We present results from extensive trace-driven simulations, which confirm the efficiency of our scheme especially for small buffer sizes and delay bounds, and which underscore the significant realizable bandwidth savings, typically yielding losses that are an order of magnitude or more below our analytically derived bounds.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

A Scheme Design of Cloud + End Technology in Demand Side Management

Demand Side Management (DSM) plays an important role in Smart Grid. It has large scale access points, massive users, heterogeneous infrastructure and dispersive participants. Moreover, cloud computing which is a service model is characterized by resource on-demand, high reliability and large scale integration and so on and the game theory is a useful tool to the dynamic economic phenomena. In this study, a scheme design of cloud + end technology is proposed to solve technical and economic problems of the DSM. The architecture of cloud + end is designed to solve technical problems in the DSM. In particular, a construct model of cloud + end is presented to solve economic problems in the DSM based on game theories. The proposed method is tested on a DSM cloud + end public service system construction in a city of southern China. The results demonstrate the feasibility of these integrated solutions which can provide a reference for the popularization and application of the DSM in china.

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

How can GPU acceleration be obtained as a service in a cluster? This question has become increasingly significant due to the inefficiency of installing GPUs on all nodes of a cluster. The research reported in this paper is motivated to address the above question by employing rCUDA (remote CUDA), a framework that facilitates Acceleration-as-a-Service (AaaS), such that the nodes of a cluster can request the acceleration of a set of remote GPUs on demand. The rCUDA framework exploits virtualisation and ensures that multiple nodes can share the same GPU. In this paper we test the feasibility of the rCUDA framework on a real-world application employed in the financial risk industry that can benefit from AaaS in the production setting. The results confirm the feasibility of rCUDA and highlight that rCUDA achieves similar performance compared to CUDA, provides consistent results, and more importantly, allows for a single application to benefit from all the GPUs available in the cluster without loosing efficiency.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Les risques découlant de la diffusion sur les plateformes néomédiatiques du point de vue des producteurs audiovisuels

La diffusion sur les plateformes néomédiatiques d’œuvres audiovisuelles, comme les sites Internet des télédiffuseurs ou des webdiffuseurs, la vidéo sur demande, la télévision mobile ou la webdistribution, modifie les risques que les producteurs audiovisuels doivent gérer normalement sur les plateformes traditionnelles, comme la télévision. La mutation des risques découle de quatre sources en particulier, soit du marché, des pratiques d’affaires, des lois et règlements et des techniques elles-mêmes. Ces sources peuvent également induire des normes pouvant constituer un cadre juridique afin de moduler ou éliminer les risques. Le présent mémoire analyse les risques encourus lors de la diffusion sur les plateformes néomédiatiques d’œuvres audiovisuelles du point de vue des producteurs par l’entremise du processus de gestion de risques. Il identifie et recense ainsi les risques en mutation et les nouveaux risques auxquels les producteurs sont confrontés. Puis, les risques identifiés y sont définis et le cadre juridique est abordé dans le contexte de la mise en œuvre d’une stratégie de gestion de risques et des mesures afin d’atténuer ou d’éviter les risques encourus par les activités de production et d’exploitation des producteurs.