Boston, Massachusetts, 2-Dimensional Building Footprints with Height Data (from LIDAR data), 2002

This dataset consists of 2D footprints of the buildings in the metropolitan Boston area, based on tiles in the orthoimage index (orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 237890, 237894, 237898, 237902, 241890, 241894, 241898, 241902, 245898, 245902). This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). Roof height and footprint elevation attributes (derived from 1-meter resolution LIDAR (LIght Detection And Ranging) data) are included as part of each building feature. This data can be combined with other datasets to create 3D representations of buildings and the surrounding environment.

The European Narcolepsy Network (EU-NN) database.

Narcolepsy with cataplexy is a rare disease with an estimated prevalence of 0.02% in European populations. Narcolepsy shares many features of rare disorders, in particular the lack of awareness of the disease with serious consequences for healthcare supply. Similar to other rare diseases, only a few European countries have registered narcolepsy cases in databases of the International Classification of Diseases or in registries of the European health authorities. A promising approach to identify disease-specific adverse health effects and needs in healthcare delivery in the field of rare diseases is to establish a distributed expert network. A first and important step is to create a database that allows collection, storage and dissemination of data on narcolepsy in a comprehensive and systematic way. Here, the first prospective web-based European narcolepsy database hosted by the European Narcolepsy Network is introduced. The database structure, standardization of data acquisition and quality control procedures are described, and an overview provided of the first 1079 patients from 18 European specialized centres. Due to its standardization this continuously increasing data pool is most promising to provide a better insight into many unsolved aspects of narcolepsy and related disorders, including clear phenotype characterization of subtypes of narcolepsy, more precise epidemiological data and knowledge on the natural history of narcolepsy, expectations about treatment effects, identification of post-marketing medication side-effects, and will contribute to improve clinical trial designs and provide facilities to further develop phase III trials.

Standardized reporting using CODES (Crash Outcome Data Evaluation System).

National Highway Traffic Safety Administration, Washington, D.C.

Expert systems for crash data collection.

Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

Beach changes at Holden Beach, North Carolina, 1970-74 /

Beach profile lines at 21 near-evenly spaced intervals along Holden Beach, North Carolina, between Lockwoods Folly and Shallotte Inlets, were measured from November 1970 to December 1974. These have been analyzed to determine the spatial and temporal variabilities on long-term, seasonal, and short-term scales. Profile lines near the inlets showed the greatest variability in mean sea level (MSL) position, above MSL volume, foreshore slope, and profile envelope. This variability near Lockwoods Folly Inlet was partly enhanced by artificial nourishment at profile line 2. Temporary, low-cost shore protection devices (e.g., sandbag groins) were constructed near that inlet during part of the study. No other modifications or activities that affected beach processes were known to occur during the study period. The central part of Holden Beach was studied separately because of the high variability of the inlet sections at either end of the island. Foreshore slopes along this reach increased from an average of 1:30 at the east end to 1:17 at the west. A seasonal change in above MSL volume indicates loss of sand during autumn and winter, and gain during spring and summer. Changes in MSL shoreline intercept and above MSL volume were highly variable during the study.

The crash outcome data evaluation system (CODES).

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Heavy truck data in Virginia: collection, uses, and needs. Final report.

Virginia Department of Transportation, Richmond

Development of roadside safety data collection plan. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

National Governors' Association Truck Accident Data Collection Program - officer's manual. Final report.

Federal Highway Administration, Washington, D.C.

National Institute on Drug Abuse statistical series.

Discontinued

Distributed routing algorithms for interconnected FDDI LANS

The Fibre Distributed Data Interface (FDDI) represents the new generation of local area networks (LANs). These high speed LANs are capable of supporting up to 500 users over a 100 km distance. User traffic is expected to be as diverse as file transfers, packet voice and video. As the proliferation of FDDI LANs continues, the need to interconnect these LANs arises. FDDI LAN interconnection can be achieved in a variety of different ways. Some of the most commonly used today are public data networks, dial up lines and private circuits. For applications that can potentially generate large quantities of traffic, such as an FDDI LAN, it is cost effective to use a private circuit leased from the public carrier. In order to send traffic from one LAN to another across the leased line, a routing algorithm is required. Much research has been done on the Bellman-Ford algorithm and many implementations of it exist in computer networks. However, due to its instability and problems with routing table loops it is an unsatisfactory algorithm for interconnected FDDI LANs. A new algorithm, termed ISIS which is being standardized by the ISO provides a far better solution. ISIS will be implemented in many manufacturers routing devices. In order to make the work as practical as possible, this algorithm will be used as the basis for all the new algorithms presented. The ISIS algorithm can be improved by exploiting information that is dropped by that algorithm during the calculation process. A new algorithm, called Down Stream Path Splits (DSPS), uses this information and requires only minor modification to some of the ISIS routing procedures. DSPS provides a higher network performance, with very little additional processing and storage requirements. A second algorithm, also based on the ISIS algorithm, generates a massive increase in network performance. This is achieved by selecting alternative paths through the network in times of heavy congestion. This algorithm may select the alternative path at either the originating node, or any node along the path. It requires more processing and memory storage than DSPS, but generates a higher network power. The final algorithm combines the DSPS algorithm with the alternative path algorithm. This is the most flexible and powerful of the algorithms developed. However, it is somewhat complex and requires a fairly large storage area at each node. The performance of the new routing algorithms is tested in a comprehensive model of interconnected LANs. This model incorporates the transport through physical layers and generates random topologies for routing algorithm performance comparisons. Using this model it is possible to determine which algorithm provides the best performance without introducing significant complexity and storage requirements.

Quantum dot-based terahertz photoconductive antennas

We present novel Terahertz (THz) emitting optically pumped Quantum Dot (QD) photoconductive (PC) materials and antenna structures on their basis both for pulsed and CW pumping regimes. Full text Quantum dot and microantenna design - Presented here are design considerations for the semiconductor materials in our novel QD-based photoconductive antenna (PCA) structures, metallic microantenna designs, and their implementation as part of a complete THz source or transceiver system. Layers of implanted QDs can be used for the photocarrier lifetime shortening mechanism[1,2]. In our research we use InAs:GaAs QD structures of varying dot layer number and distributed Bragg reflector(DBR)reflectivity range. According to the observed dependence of carrier lifetimes on QD layer periodicity [3], it is reasonable to assume that electron lifetimes can be potentially reduced down to 0.45ps in such structures. Both of these features; long excitation wavelength and short carriers lifetime predict possible feasibility of QD antennas for THz generation and detection. In general, relatively simple antenna configurations were used here, including: coplanar stripline (CPS); Hertzian-type dipoles; bow-ties for broadband and log-spiral(LS)or log-periodic(LP)‘toothed’ geometriesfor a CW operation regime. Experimental results - Several lasers are used for antenna pumping: Ti:Sapphire femtosecond laser, as well as single-[4], double-[5] wavelength, and pulsed [6] QD lasers. For detection of the THz signal different schemes and devices were used, e.g. helium-cooled bolometer, Golay cell and a second PCA for coherent THz detection in a traditional time-domain measurement scheme.Fig.1shows the typical THz output power trend from a 5 um-gap LPQD PCA pumped using a tunable QD LD with optical pump spectrum shown in (b). Summary - QD-based THz systems have been demonstrated as a feasible and highly versatile solution. The implementation of QD LDs as pump sources could be a major step towards ultra-compact, electrically controllable transceiver system that would increase the scope of data analysis due to the high pulse repetition rates of such LDs [3], allowing real-time THz TDS and data acquisition. Future steps in development of such systems now lie in the further investigation of QD-based THz PCA structures and devices, particularly with regards to their compatibilitywith QD LDs as pump sources. [1]E. U. Rafailov et al., “Fast quantum-dot saturable absorber for passive mode-locking of solid-State lasers,”Photon.Tech.Lett., IEEE, vol. 16 pp. 2439-2441(2004) [2]E. Estacio, “Strong enhancement of terahertz emission from GaAs in InAs/GaAs quantum dot structures. Appl.Phys.Lett., vol. 94 pp. 232104 (2009) [3]C. Kadow et al., “Self-assembled ErAs islands in GaAs: Growth and subpicosecond carrier dynamics,” Appl. Phys. Lett., vol. 75 pp. 3548-3550 (1999) [4]T. Kruczek, R. Leyman, D. Carnegie, N. Bazieva, G. Erbert, S. Schulz, C. Reardon, and E. U. Rafailov, “Continuous wave terahertz radiation from an InAs/GaAs quantum-dot photomixer device,” Appl. Phys. Lett., vol. 101(2012) [5]R. Leyman, D. I. Nikitichev, N. Bazieva, and E. U. Rafailov, “Multimodal spectral control of a quantum-dot diode laser for THz difference frequency generation,” Appl. Phys. Lett., vol. 99 (2011) [6]K.G. Wilcox, M. Butkus, I. Farrer, D.A. Ritchie, A. Tropper, E.U. Rafailov, “Subpicosecond quantum dot saturable absorber mode-locked semiconductor disk laser, ” Appl. Phys. Lett. Vol 94, 2511 © 2014 IEEE.

Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.

Design and Implementation of a Cloud Infrastructure for Distributed Scientific Calculation

Cloud computing enables independent end users and applications to share data and pooled resources, possibly located in geographically distributed Data Centers, in a fully transparent way. This need is particularly felt by scientific applications to exploit distributed resources in efficient and scalable way for the processing of big amount of data. This paper proposes an open so- lution to deploy a Platform as a service (PaaS) over a set of multi- site data centers by applying open source virtualization tools to facilitate operation among virtual machines while optimizing the usage of distributed resources. An experimental testbed is set up in Openstack environment to obtain evaluations with different types of TCP sample connections to demonstrate the functionality of the proposed solution and to obtain throughput measurements in relation to relevant design parameters.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.