State of the art in continuous speech recognition.

In the past decade, tremendous advances in the state of the art of automatic speech recognition by machine have taken place. A reduction in the word error rate by more than a factor of 5 and an increase in recognition speeds by several orders of magnitude (brought about by a combination of faster recognition search algorithms and more powerful computers), have combined to make high-accuracy, speaker-independent, continuous speech recognition for large vocabularies possible in real time, on off-the-shelf workstations, without the aid of special hardware. These advances promise to make speech recognition technology readily available to the general public. This paper focuses on the speech recognition advances made through better speech modeling techniques, chiefly through more accurate mathematical modeling of speech sounds.

New multivalent calixarene-based ligands for protein recognition and inhibition

One of the challenges that concerns chemistry is the design of molecules able to modulate protein-protein and protein-ligand interactions, since these are involved in many physiological and pathological processes. The interactions occurring between proteins and their natural counterparts can take place through reciprocal recognition of rather large surface areas, through recognition of single contact points and single residues, through inclusion of the substrates in specific, more or less deep binding sites. In many cases, the design of synthetic molecules able to interfere with the processes involving proteins can benefit from the possibility of exploiting the multivalent effect. Multivalency, widely spread in Nature, consists in the simultaneous formation between two entities (cell-cell, cell-protein, protein-protein) of multiple equivalent ligand-recognition site complexes. In this way the whole interaction results particularly strong and specific. Calixarenes furnish a very interesting scaffold for the preparation of multivalent ligands and in the last years calixarene-based ligands demonstrated their remarkable capability to recognize and inhibit or restore the activity of different proteins, with a high efficiency and selectivity in several recognition phenomena. The relevance and versatility of these ligands is due to the different exposition geometries of the binding units that can be explored exploiting the conformational properties of these macrocycles, the wide variety of functionalities that can be linked to their structure at different distances from the aromatic units and to their intrinsic multivalent nature. With the aim of creating new multivalent systems for protein targeting, the work reported in this thesis regards the synthesis and properties of glycocalix[n]arenes and guanidino calix[4]arenes for different purposes. Firstly, a new bolaamphiphile glycocalix[4]arene in 1,3-alternate geometry, bearing cellobiose, was synthesized for the preparation of targeted drug delivery systems based on liposomes. The formed stable mixed liposomes obtained by mixing the macrocycle with DOPC were shown to be able of exploiting the sugar units emerging from the lipid bilayer to agglutinate Concanavalin A, a lectin specific for glucose. Moreover, always thanks to the presence of the glycocalixarene in the layer, the same liposomes demonstrated through preliminary experiments to be uptaken by cancer cells overexpressing glucose receptors on their exterior surface more efficiently respect to simple DOPC liposomes lacking glucose units in their structure. Then a small library of glycocalix[n]arenes having different valency and geometry was prepared, for the creation of potentially active immunostimulants against Streptococcus pneumoniae, particularly the 19F serotype, one of the most virulent. These synthesized glycocalixarenes bearing β-N-acetylmannosamine as antigenic unit were compared with the natural polysaccharide on the binding to the specific anti-19F human polyclonal antibody, to verify their inhibition potency. Among all, the glycocalixarene based on the conformationally mobile calix[4]arene resulted the more efficient ligand, probably due its major possibility to explore the antibody surface and dispose the antigenic units in a proper arrangement for the interaction process. These results pointed out the importance of how the different multivalent presentation in space of the glycosyl units can influence the recognition phenomena. At last, NMR studies, using particularly 1H-15N HSQC experiments, were performed on selected glycocalix[6]arenes and guanidino calix[4]arenes blocked in the cone geometry, in order to better understand protein-ligand interactions. The glycosylated compounds were studied with Ralstonia solanacearum lectin, in order to better understand the nature of the carbohydrate‐lectin interactions in solution. The series of cationic calixarene was employed with three different acidic proteins: GB1, Fld and alpha synuclein. Particularly GB1 and Fld were observed to interact with all five cationic calix[4]arenes but showing different behaviours and affinities.

Large-scale clustering measurements with photometric redshifts: comparing the dark matter haloes of X-ray AGN, star-forming and passive galaxies at z ≈ 1

We combine multi-wavelength data in the AEGIS-XD and C-COSMOS surveys to measure the typical dark matter halo mass of X-ray selected active galactic nuclei (AGN) [L_X(2–10 keV) > 10^42 erg s^− 1] in comparison with far-infrared selected star-forming galaxies detected in the Herschel/PEP survey (PACS Evolutionary Probe; L_IR > 10^11 L_⊙) and quiescent systems at z ≈ 1. We develop a novel method to measure the clustering of extragalactic populations that uses photometric redshift probability distribution functions in addition to any spectroscopy. This is advantageous in that all sources in the sample are used in the clustering analysis, not just the subset with secure spectroscopy. The method works best for large samples. The loss of accuracy because of the lack of spectroscopy is balanced by increasing the number of sources used to measure the clustering. We find that X-ray AGN, far-infrared selected star-forming galaxies and passive systems in the redshift interval 0.6 < z < 1.4 are found in haloes of similar mass, log M_DMH/(M_⊙ h^−1) ≈ 13.0. We argue that this is because the galaxies in all three samples (AGN, star-forming, passive) have similar stellar mass distributions, approximated by the J-band luminosity. Therefore, all galaxies that can potentially host X-ray AGN, because they have stellar masses in the appropriate range, live in dark matter haloes of log M_DMH/(M_⊙ h^−1) ≈ 13.0 independent of their star formation rates. This suggests that the stellar mass of X-ray AGN hosts is driving the observed clustering properties of this population. We also speculate that trends between AGN properties (e.g. luminosity, level of obscuration) and large-scale environment may be related to differences in the stellar mass of the host galaxies.

Enhancing Conservation Options: An Argument for Statutory Recognition of Options to Purchase Conservation Easements (OPCEs)

The most dynamic component of the conservation movement in the United States for the past three decades has been land conservation transactions. In the United States, land conservation organizations have protected roughly 40 million acres of land through transactions. Most of these acres have been protected using conservation easements. Climate change threatens the vast conservation edifice created by land conservation transactions. The tools of land conservation transactions are, traditionally, stationary. Climate change means that the resources that land conservation transactions were intended to protect may no longer remain on the land protected. Options to purchase conservation easements (OPCEs) have long played a modest but important role in conservation law practice. In the world climate change is creating, with its substantial uncertainties and shifting windows of opportunity, OPCEs can serve more complicated and strategic purposes. The ability of OPCEs to serve important roles in protecting land in the context of uncertainty would be significantly increased if state legislatures amend current conservation easement statutes to (1) specifically recognize OPCEs, (2) immunize OPCEs from a range of potential common law challenges, (3) guarantee the durability and transferability of OPCEs, and (4) integrate OPCEs into the burgeoning body of conservation easement law. These statutory amendments would do for OPCEs what conservation easement statutes have done for conservation easements: transform them into an essential multi-purpose tool for conservation in a changing world.

Agriculture and sustainable development: The role of small scale agriculture in obtaining food security

The international community has expressed a renewed interest in small scale agriculture and the role it plays in long-term food security in the face of climate change and population growth. This interest has led to a new development paradigm in which small scale producers are being brought into the global market. Undoubtedly, small scale agriculture should be pursued as a sustainable form of development which can contribute to poverty alleviation, environmental stewardship, and the preservation of genetic diversity. These unique contributions are inherently threatened by a system captured in the idea of the neoliberal food regime. The ability of small scale agriculture to uphold the goals of food security are dependent on recognition and preservation of these contributions.

A multimodal genre recognition prototype

In this paper, a multimodal and interactive prototype to perform music genre classification is presented. The system is oriented to multi-part files in symbolic format but it can be adapted using a transcription system to transform audio content in music scores. This prototype uses different sources of information to give a possible answer to the user. It has been developed to allow a human expert to interact with the system to improve its results. In its current implementation, it offers a limited range of interaction and multimodality. Further development aimed at full interactivity and multimodal interactions is discussed.

A formal framework for modelling complex network management systems

Society today is completely dependent on computer networks, the Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Subconsciously, we rely increasingly on network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect, and enhance the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we do not consider network management systems during the development stage of distributed systems, then there could be serious consequences or even total failures in the development of the distributed system. It is necessary, therefore, to consider the management of the systems within the design of the distributed systems and to systematise their design to minimise the impact of network management in distributed systems projects. In this paper, we present a framework that allows the design of network management systems systematically. To accomplish this goal, formal modelling tools are used for modelling different views sequentially proposed of the same problem. These views cover all the aspects that are involved in the system; based on process definitions for identifying responsible and defining the involved agents to propose the deployment in a distributed architecture that is both feasible and appropriate.

Improving kNN multi-label classification in Prototype Selection scenarios using class proposals

Prototype Selection (PS) algorithms allow a faster Nearest Neighbor classification by keeping only the most profitable prototypes of the training set. In turn, these schemes typically lower the performance accuracy. In this work a new strategy for multi-label classifications tasks is proposed to solve this accuracy drop without the need of using all the training set. For that, given a new instance, the PS algorithm is used as a fast recommender system which retrieves the most likely classes. Then, the actual classification is performed only considering the prototypes from the initial training set belonging to the suggested classes. Results show that this strategy provides a large set of trade-off solutions which fills the gap between PS-based classification efficiency and conventional kNN accuracy. Furthermore, this scheme is not only able to, at best, reach the performance of conventional kNN with barely a third of distances computed, but it does also outperform the latter in noisy scenarios, proving to be a much more robust approach.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Gazetteer to maps of Hokkaidō and Karafuto. Map series AMS L764, L761 and L762 (1st ed.) Scale 1:50,000. January 1945.

"Conversion tables of Romaji equivalents (Goju-on Order)" [katakana]: p. x-xv.

The knowledge of the heavens and the earth made easy, or, The first principles of astronomy and geography explain'd by the use of globes and maps : with a solution of the common problems by a plain scale and compasses, as well as by the globe /

With privilege leaf (A₁).

Topographic map of the property of Mr. William H. Roberts on N. side of W. 105th Place.

Red, black ink on tracing paper; topo. lines; unsigned; 75 x 37 cm.; Scale: 1" = 20' [from photographic copy by Lance Burgharrdt]

Multi-year Trends in MODIS and MISR Observed Cloud Fraction over the Extratropical Oceans

Thesis (Master's)--University of Washington, 2016-06

Air pollution exposure and novel biomarkers of inflammation and cardiac stress in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Thesis (Master's)--University of Washington, 2016-06

Dynamic multi-resolution spatial object derivation for mobile and WWW applications

Online geographic information systems provide the means to extract a subset of desired spatial information from a larger remote repository. Data retrieved representing real-world geographic phenomena are then manipulated to suit the specific needs of an end-user. Often this extraction requires the derivation of representations of objects specific to a particular resolution or scale from a single original stored version. Currently standard spatial data handling techniques cannot support the multi-resolution representation of such features in a database. In this paper a methodology to store and retrieve versions of spatial objects at, different resolutions with respect to scale using standard database primitives and SQL is presented. The technique involves heavy fragmentation of spatial features that allows dynamic simplification into scale-specific object representations customised to the display resolution of the end-user's device. Experimental results comparing the new approach to traditional R-Tree indexing and external object simplification reveal the former performs notably better for mobile and WWW applications where client-side resources are limited and retrieved data loads are kept relatively small.