Demonstrating effective all-optical processing in ultrafast data networks using semiconductor optical amplifiers

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references.The demand for bandwidth in worldwide data networks continues to increase due to growing Internet use and high-bandwidth applications such as video. All-optical signal processing is one promising technique for providing the necessary capacity and offers payload transparency, power consumption which scales efficiently with increasing bit rates, reduced processing latency, and ultrafast performance. In this thesis, we focus on using semiconductor optical amplifier-based logic gates to address both routing and regeneration needs in ultrafast data networks. To address routing needs, we demonstrate a scalable, multi-packet all-optical header processing unit operating at a line rate of 40 Gb/s. For this experiment, we used the ultrafast nonlinear interferometer (UNI) gate, a discrete optical logic gate which has been demonstrated at speeds of 100 Gb/s for bit-wise switching. However, for all-optical switching to become a reality, integration is necessary to significantly reduce the cost of manufacturing, installation, and operation. One promising integrated all-optical logic gate is the semiconductor optical amplifier Mach-Zehnder interferometer (SOA-MZI). This gate has previously been demonstrated capable of up to 80 Gb/s bit-wise switching operation. To enable simple installation and operation of this gate, we developed a performance optimization method which can quickly and accurately pinpoint the optimal operating point of the switch. This eliminates the need for a time-intensive search over a large parameter space and significantly simplifies the operation of the switch. With this method, we demonstrate the ability of a single SOA-MZI logic gate to regenerate ultrafast pulses over 100 passes and 10,000 km in a regenerative loop. Ultimately, all-optical logic gates must be integrated on a single low-cost platform and demonstrated in cascaded, multi-gate operation for increased functionality.(cont.) This requires low-loss monolithic integration. Our approach to this involves an asymmetric twin waveguide (ATG) design. This design also has the potential for high-yields as a result of a high tolerance for fabrication errors. We present our characterization results of ATG waveguides and proposals for future improvements.by Jade P. Wang.Ph.D

Can an online scenario-based learning intervention influence preservice teachers’ self-efficacy, career intentions, and perceived fit with the profession?

The purpose of this article is to explore how a brief, scalable, online scenario-based learning (SBL) intervention influences preservice teachers’ self-efficacy, career intentions, and perceived fit with the profession. A sample of 1,513 preservice teachers from a large undergraduate teacher education programme in Australia was recruited over two years to complete three SBL sessions (with four measurement points) over the course of three weeks. We conducted a series of latent change analyses to explore the patterns of change over time, with covariates including year in ITE programme, prospective teaching level, and sex. Results showed that self-efficacy, teaching commitment, and perceived fit with the profession increased after the initial SBL session, and the effect was maintained for self-efficacy and perceived fit, but not for teaching commitment. Implications for practice and further research are discussed

Reproducible and Portable Big Data Analytics in the Cloud

Cloud computing has become a major approach to help reproduce computational experiments because it supports on-demand hardware and software resource provisioning. Yet there are still two main difficulties in reproducing big data applications in the cloud. The first is how to automate end-to-end execution of analytics including environment provisioning, analytics pipeline description, pipeline execution, and resource termination. The second is that an application developed for one cloud is difficult to be reproduced in another cloud, a.k.a. vendor lock-in problem. To tackle these problems, we leverage serverless computing and containerization techniques for automated scalable execution and reproducibility, and utilize the adapter design pattern to enable application portability and reproducibility across different clouds. We propose and develop an open-source toolkit that supports 1) fully automated end-to-end execution and reproduction via a single command, 2) automated data and configuration storage for each execution, 3) flexible client modes based on user preferences, 4) execution history query, and 5) simple reproduction of existing executions in the same environment or a different environment. We did extensive experiments on both AWS and Azure using four big data analytics applications that run on virtual CPU/GPU clusters. The experiments show our toolkit can achieve good execution performance, scalability, and efficient reproducibility for cloud-based big data analytics

Can an online scenario-based learning intervention influence preservice teachers’ self-efficacy, career intentions, and perceived fit with the profession?

Abstract The purpose of this article is to explore how a brief, scalable, online scenario-based learning (SBL) intervention influences preservice teachers’ self-efficacy, career intentions, and perceived fit with the profession. A sample of 1,513 preservice teachers from a large undergraduate teacher education programme in Australia was recruited over two years to complete three SBL sessions (with four measurement points) over the course of three weeks. We conducted a series of latent change analyses to explore the patterns of change over time, with covariates including year in ITE programme, prospective teaching level, and sex. Results showed that self-efficacy, teaching commitment, and perceived fit with the profession increased after the initial SBL session, and the effect was maintained for self-efficacy and perceived fit, but not for teaching commitment. Implications for practice and further research are discussed

Report on the results of the large-scale pilot and guidelines for improvement

200SMEchallenge -- H2020-INNOSUP-2018-2020 -- Grant Agreement number: 824212 -- D4.3 Report on the results of the large-scale pilot and guidelines for improvementThis deliverable includes the report of the 7 UX Challenges that were held in the seven partnering countries. Along with the reports, the main results and outcomes are reports, along with feedback from the partners piloting the UX Challenges. This deliverable is designed to provide comprehensive information about how each of the seven UX Challenge was executed

Imaging Spectrometer Implementation on a Small Satellite Platform for Aquatic Ecosystems Science

The implementation of Imaging spectrometers with state-of-the-art performance on small satellites is challenging due to the size, weight, and power (SWaP) limitations. We have recently developed a compact form, the Chrisp Compact VNIR/SWIR Imaging Spectrometer (CCVIS), that facilitates their usage without sacrificing performance. The CCVIS enables a modular implementation that, combined with a freeform telescope, produces a wide field of view with high signal to noise ratio (SNR) performance. The targeted scientific application is the study of aquatic ecosystems. The imaging spectrometer is designed to address carbon sequestration in coastal margins and wetlands, kelp and seagrass studies, coral reefs, harmful algal blooms and hypoxia, and carbon cycling in this dynamic environment. The requirements are challenging since the high SNR, which is necessary in order to produce quality data products over water, is coupled with sufficient dynamic range in order to simultaneously record spectra from the shore area, which has elevated spectral radiance in comparison to the water. To meet these requirements, the small satellite will execute a pitchback maneuver where the imaging of the slit projected onto the surface is slowly scanned while recording focal plane array (FPA) readouts at a higher rate. The effective frame rate is determined by the time it takes to scan the projected slit one ground sample distance (GSD). This concept of operation avoids saturation over the land surface while obtaining high SNR over the water. This approach has the added benefit of measuring a range of angles during a single GSD acquisition, providing insight into the bidirectional reflectance distribution function (BRDF). One consequence of this approach is extremely large data volumes requiring a high bandwidth downlink system. Laser communications is a critical technology that enables the transfer of these large data volumes. We present a preliminary design of the imaging spectrometer based on the aquatic ecosystem requirements including the modular implementation of the CCVIS, the laser communications system, and the implementation on a ESPA-grande satellite

Association between neighbourhood composition, kindergarten educator-reported distance learning barriers, and return to school concerns during the first wave of the COVID-19 pandemic in Ontario, Canada

Introduction Research to date has established that the COVID-19 pandemic has not impacted everyone equitably. Whether this unequitable impact was seen educationally with regards to educator reported barriers to distance learning, concerns and mental health is less clear. Objective The objective of this study was to explore the association between the neighbourhood composition of the school and kindergarten educator-reported barriers and concerns regarding children's learning during the first wave of COVID-19 related school closures in Ontario, Canada. Methods In the spring of 2020, we collected data from Ontario kindergarten educators (n = 2569; 74.2% kindergarten teachers, 25.8% early childhood educators; 97.6% female) using an online survey asking them about their experiences and challenges with online learning during the first round of school closures. We linked the educator responses to 2016 Canadian Census variables based on schools' postal codes. Bivariate correlations and Poisson regression analyses were used to determine if there was an association between neighbourhood composition and educator mental health, and the number of barriers and concerns reported by kindergarten educators. Results There were no significant findings with educator mental health and school neighbourhood characteristics. Educators who taught at schools in neighbourhoods with lower median income reported a greater number of barriers to online learning (e.g., parents/guardians not submitting assignments/providing updates on their child's learning) and concerns regarding the return to school in the fall of 2020 (e.g., students' readjustment to routines). There were no significant associations with educator reported barriers or concerns and any of the other Census neighbourhood variables (proportion of lone parent families, average household size, proportion of population that do no speak official language, proportion of population that are recent immigrants, or proportion of population ages 0-4). Conclusions Overall, our study suggests that the neighbourhood composition of the children's school location did not exacerbate the potential negative learning experiences of kindergarten students and educators during the COVID-19 pandemic, although we did find that educators teaching in schools in lower-SES neighbourhoods reported more barriers to online learning during this time. Taken together, our study suggests that remediation efforts should be focused on individual kindergarten children and their families as opposed to school location

Noise exposure and distortion product otoacoustic emission suprathreshold amplitudes : a genome-wide association study

Background: Although several candidate-gene association studies have been conducted to investigate noise-induced hearing loss (NIHL) in humans, most are underpowered, unreplicated, and account for only a fraction of the genetic risk. Mouse genome-wide association studies (GWASs) have revolutionized the field of genetics and have led to the discovery of hundreds of genes involved in complex traits. The hybrid mouse diversity panel (HMDP) is a collection of classic inbred and recombinant inbred strains whose genomes have been either genotyped at high resolution or sequenced. To further investigate the genetics of NIHL, we report the first GWAS based on distortion product otoacoustic emission (DPOAE) measurements and the HMDP. Methods: A total of 102 strains (n = 635) from the HMDP were evaluated based on DPOAE suprathreshold amplitudes before and after noise exposure. DPOAE amplitude variation was set at 60 and 70 dB SPL of the primary tones for each frequency separately (8, 11.3, 16, 22.6, and 32 kHz). These values provided an indirect assessment of outer hair cell integrity. Six-week-old mice were exposed for 2 h to 10 kHz octave-band noise at 108 dB SPL. To perform local expression quantitative trait locus (eQTL) analysis, gene expression microarray profiles were generated using cochlear RNA from 64 hybrid mouse strains (n = 3 arrays per strain). Results: Several new loci were identified and positional candidate-genes associated with NIHL were prioritized, especially after noise exposure (1 locus at baseline and 5 loci after exposure). A total of 35 candidate genes in these 6 loci were identified with at least 1 probe whose expression was regulated by a significant cis-eQTL in the cochlea. After careful analysis of the candidate genes based on cochlear gene expression, 2 candidate genes were prioritized: Eya1 (baseline) and Efr3a (post-exposure). Discussion and Conclusion: For the first time, an association analysis with correction for population structure was used to map several loci for hearing traits in inbred strains of mice based on DPOAE suprathreshold amplitudes before and after noise exposure. Our results identified a number of novel loci and candidate genes for susceptibility to NIHL, especially the Eya1 and Efr3a genes. Our findings validate the power of the HMDP for detecting NIHL susceptibility genes