Study and analysis of the Leap Motion sensor and the Software Development Kit (SDK) for the implementation of visual Human Computer Interfaces

En este proyecto, se presenta un informe técnico sobre la cámara Leap Motion y el Software Development Kit correspondiente, el cual es un dispositivo con una cámara de profundidad orientada a interfaces hombre-máquina. Esto es realizado con el propósito de desarrollar una interfaz hombre-máquina basada en un sistema de reconocimiento de gestos de manos. Después de un exhaustivo estudio de la cámara Leap Motion, se han realizado diversos programas de ejemplo con la intención de verificar las capacidades descritas en el informe técnico, poniendo a prueba la Application Programming Interface y evaluando la precisión de las diferentes medidas obtenidas sobre los datos de la cámara. Finalmente, se desarrolla un prototipo de un sistema de reconocimiento de gestos. Los datos sobre la posición y orientación de la punta de los dedos obtenidos de la Leap Motion son usados para describir un gesto mediante un vector descriptor, el cual es enviado a una Máquina Vectores Soporte, utilizada como clasificador multi-clase.

Context modelling for natural Human Computer Interaction applications in e-health

The conception of IoT (Internet of Things) is accepted as the future tendency of Internet among academia and industry. It will enable people and things to be connected at anytime and anyplace, with anything and anyone. IoT has been proposed to be applied into many areas such as Healthcare, Transportation，Logistics, and Smart environment etc. However, this thesis emphasizes on the home healthcare area as it is the potential healthcare model to solve many problems such as the limited medical resources, the increasing demands for healthcare from elderly and chronic patients which the traditional model is not capable of. A remarkable change in IoT in semantic oriented vision is that vast sensors or devices are involved which could generate enormous data. Methods to manage the data including acquiring, interpreting, processing and storing data need to be implemented. Apart from this, other abilities that IoT is not capable of are concluded, namely, interoperation, context awareness and security & privacy. Context awareness is an emerging technology to manage and take advantage of context to enable any type of system to provide personalized services. The aim of this thesis is to explore ways to facilitate context awareness in IoT. In order to realize this objective, a preliminary research is carried out in this thesis. The most basic premise to realize context awareness is to collect, model, understand, reason and make use of context. A complete literature review for the existing context modelling and context reasoning techniques is conducted. The conclusion is that the ontology-based context modelling and ontology-based context reasoning are the most promising and efficient techniques to manage context. In order to fuse ontology into IoT, a specific ontology-based context awareness framework is proposed for IoT applications. In general, the framework is composed of eight components which are hardware, UI (User Interface), Context modelling, Context fusion, Context reasoning, Context repository, Security unit and Context dissemination. Moreover, on the basis of TOVE (Toronto Virtual Enterprise), a formal ontology developing methodology is proposed and illustrated which consists of four stages: Specification & Conceptualization, Competency Formulation, Implementation and Validation & Documentation. In addition, a home healthcare scenario is elaborated by listing its well-defined functionalities. Aiming at representing this specific scenario, the proposed ontology developing methodology is applied and the ontology-based model is developed in a free and open-source ontology editor called Protégé. Finally, the accuracy and completeness of the proposed ontology are validated to show that this proposed ontology is able to accurately represent the scenario of interest.

An antagonistic vascular endothelial growth factor (VEGF) variant inhibits VEGF-stimulated receptor autophosphorylation and proliferation of human endothelial cells

Vascular endothelial growth factor (VEGF) is a potent mitogen with a unique specificity for endothelial cells and a key mediator of aberrant endothelial cell proliferation and vascular permeability in a variety of human pathological situations, such as tumor angiogenesis, diabetic retinopathy, rheumatoid arthritis, or psoriasis. VEGF is a symmetric homodimeric molecule with two receptor binding interfaces lying on each pole of the molecule. Herein we report on the construction and recombinant expression of an asymmetric heterodimeric VEGF variant with an intact receptor binding interface at one pole and a mutant receptor binding interface at the second pole of the dimer. This VEGF variant binds to VEGF receptors but fails to induce receptor activation. In competition experiments, the heterodimeric VEGF variant antagonizes VEGF-stimulated receptor autophosphorylation and proliferation of endothelial cells. A 15-fold excess of the heterodimer was sufficient to inhibit VEGF-stimulated endothelial cell proliferation by 50%, and a 100-fold excess resulted in an almost complete inhibition. By using a rational approach that is based on the structure of VEGF, we have shown the feasibility to construct a VEGF variant that acts as an VEGF antagonist.

The crystal structure of human interferon β at 2.2-Å resolution

Type I interferons (IFNs) are helical cytokines that have diverse biological activities despite the fact that they appear to interact with the same receptor system. To achieve a better understanding of the structural basis for the different activities of α and β IFNs, we have determined the crystal structure of glycosylated human IFN-β at 2.2-Å resolution by molecular replacement. The molecule adopts a fold similar to that of the previously determined structures of murine IFN-β and human IFN-α2b but displays several distinct structural features. Like human IFN-α2b, human IFN-β contains a zinc-binding site at the interface of the two molecules in the asymmetric unit, raising the question of functional relevance for IFN-β dimers. However, unlike the human IFN-α2b dimer, in which homologous surfaces form the interface, human IFN-β dimerizes with contact surfaces from opposite sides of the molecule. The relevance of the structure to the effects of point mutations in IFN-β at specific exposed residues is discussed. A potential role of ligand–ligand interactions in the conformational assembly of IFN receptor components is discussed.

Novel dimeric interface and electrostatic recognition in bacterial Cu,Zn superoxide dismutase

Eukaryotic Cu,Zn superoxide dismutases (CuZnSODs) are antioxidant enzymes remarkable for their unusually stable β-barrel fold and dimer assembly, diffusion-limited catalysis, and electrostatic guidance of their free radical substrate. Point mutations of CuZnSOD cause the fatal human neurodegenerative disease amyotrophic lateral sclerosis. We determined and analyzed the first crystallographic structure (to our knowledge) for CuZnSOD from a prokaryote, Photobacterium leiognathi, a luminescent symbiont of Leiognathid fish. This structure, exemplifying prokaryotic CuZnSODs, shares the active-site ligand geometry and the topology of the Greek key β-barrel common to the eukaryotic CuZnSODs. However, the β-barrel elements recruited to form the dimer interface, the strategy used to forge the channel for electrostatic recognition of superoxide radical, and the connectivity of the intrasubunit disulfide bond in P. leiognathi CuZnSOD are discrete and strikingly dissimilar from those highly conserved in eukaryotic CuZnSODs. This new CuZnSOD structure broadens our understanding of structural features necessary and sufficient for CuZnSOD activity, highlights a hitherto unrecognized adaptability of the Greek key β-barrel building block in evolution, and reveals that prokaryotic and eukaryotic enzymes diverged from one primordial CuZnSOD and then converged to distinct dimeric enzymes with electrostatic substrate guidance.

Free energy of burying hydrophobic residues in the interface between protein subunits

We have obtained an experimental estimate of the free energy change associated with variations at the interface between protein subunits, a subject that has raised considerable interest since the concept of accessible surface area was introduced by Lee and Richards [Lee, B. & Richards, F. M. (1971) J. Mol. Biol. 55, 379–400]. We determined by analytical ultracentrifugation the dimer–tetramer equilibrium constant of five single and three double mutants of human Hb. One mutation is at the stationary α1β1 interface, and all of the others are at the sliding α1β2 interface where cleavage of the tetramer into dimers and ligand-linked allosteric changes are known to occur. A surprisingly good linear correlation between the change in the free energy of association of the mutants and the change in buried hydrophobic surface area was obtained, after corrections for the energetic cost of losing steric complementarity at the αβ dimer interface. The slope yields an interface stabilization free energy of −15 ± 1.2 cal/mol upon burial of 1 Å2 of hydrophobic surface, in very good agreement with the theoretical estimate given by Eisenberg and McLachlan [Eisenberg, D. & McLachlan, A. D. (1986) Nature (London) 319, 199–203].

Engineering actin-resistant human DNase I for treatment of cystic fibrosis.

Human deoxyribonuclease I (DNase I), an enzyme recently approved for treatment of cystic fibrosis (CF), has been engineered to create two classes of mutants: actin-resistant variants, which still catalyze DNA hydrolysis but are no longer inhibited by globular actin (G-actin) and active site variants, which no longer catalyze DNA hydrolysis but still bind G-actin. Actin-resistant variants with the least affinity for actin, as measured by an actin binding ELISA and actin inhibition of [33P] DNA hydrolysis, resulted from the introduction of charged, aliphatic, or aromatic residues at Ala-114 or charged residues on the central hydrophobic actin binding interface at Tyr-65 or Val-67. In CF sputum, the actin-resistant variants D53R, Y65A, Y65R, or V67K were 10-to 50-fold more potent than wild type in reducing viscoelasticity as determined in sputum compaction assays. The reduced viscoelasticity correlated with reduced DNA length as measured by pulsed-field gel electrophoresis. In contrast, the active site variants H252A or H134A had no effect on altering either viscoelasticity or DNA length in CF sputum. The data from both the active site and actin-resistant variants demonstrate that the reduction of viscoelasticity by DNase I results from DNA hydrolysis and not from depolymerization of filamentous actin (F-actin). The increased potency of the actin-resistant variants indicates that G-actin is a significant inhibitor of DNase I in CF sputum. These results further suggest that actin-resistant DNase I variants may have improved efficacy in CF patients.

Crystal structure at 2.6-A resolution of human macrophage migration inhibitory factor.

Macrophage migration inhibitory factor (MIF) was the first cytokine to be described, but for 30 years its role in the immune response remained enigmatic. In recent studies, MIF has been found to be a novel pituitary hormone and the first protein identified to be released from immune cells on glucocorticoid stimulation. Once secreted, MIF counterregulates the immunosuppressive effects of steroids and thus acts as a critical component of the immune system to control both local and systemic immune responses. We report herein the x-ray crystal structure of human MIF to 2.6 angstrom resolution. The protein is a trimer of identical subunits. Each monomer contains two antiparallel alpha-helices that pack against a four-stranded beta-sheet. The monomer has an additional two beta-strands that interact with the beta-sheets of adjacent subunits to form the interface between monomers. The three beta-sheets are arranged to form a barrel containing a solvent-accessible channel that runs through the center of the protein along a molecular 3-fold axis. Electrostatic potential maps reveal that the channel has a positive potential, suggesting that it binds negatively charged molecules. The elucidated structure for MIF is unique among cytokines or hormonal mediators, and suggests that this counterregulator of glucocorticoid action participates in novel ligand-receptor interactions.

Mutagenesis in the C-terminal region of human interleukin 5 reveals a central patch for receptor alpha chain recognition.

Cassette mutagenesis was used to identify side chains in human interleukin 5 (hIL-5) that mediate binding to hIL-5 receptor alpha chain (hIL-5R alpha). A series of single alanine substitutions was introduced into a stretch of residues in the C-terminal region, including helix D, which previously had been implicated in receptor alpha chain recognition and which is aligned on the IL-5 surface so as to allow the topography of receptor binding residues to be examined. hIL-5 and single site mutants were expressed in COS cells, their interactions with hIL-5R alpha were measured by a sandwich surface plasmon resonance biosensor method, and their biological activities were measured by an IL-5-dependent cell proliferation assay. A pattern of mutagenesis effects was observed, with greatest impact near the interface between the two four-helix bundles of IL-5, in particular at residues Glu-110 and Trp-111, and least at the distal ends of the D helices. This pattern suggests the possibility that residues near the interface of the two four-helix bundles in hIL-5 comprise a central patch or hot spot, which constitutes an energetically important alpha chain recognition site. This hypothesis suggests a structural explanation for the 1:1 stoichiometry observed for the complex of hIL-5 with hIL-5R alpha.

Towards Closed-loop Deep Brain Stimulation: Behavior Recognition from Human STN

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. This thesis proposes novel detection and classification techniques for behavior recognition based on deep brain LFP. Behavior detection from such signals is the vital step in developing the next generation of closed-loop DBS devices. LFP recordings from 13 subjects are utilized in this study to design and evaluate our method. Recordings were performed during the surgery and the subjects were asked to perform various behavioral tasks. Various techniques are used understand how the behaviors modulate the STN. One method studies the time-frequency patterns in the STN LFP during the tasks. Another method measures the temporal inter-hemispheric connectivity of the STN as well as the connectivity between STN and Pre-frontal Cortex (PFC). Experimental results demonstrate that different behaviors create different m odulation patterns in STN and it’s connectivity. We use these patterns as features to classify behaviors. A method for single trial recognition of the patient’s current task is proposed. This method uses wavelet coefficients as features and support vector machine (SVM) as the classifier for recognition of a selection of behaviors: speech, motor, and random. The proposed method is 82.4% accurate for the binary classification and 73.2% for classifying three tasks. As the next step, a practical behavior detection method which asynchronously detects behaviors is proposed. This method does not use any priori knowledge of behavior onsets and is capable of asynchronously detect the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity and to detect the finger movements. Our experimental results using STN LFP recorded from eight patients with PD demonstrate this is a promising approach for behavior detection and developing novel closed-loop DBS systems.

Machine learning techniques for automatic opinion detection in non-traditional textual genres

This paper presents a preliminary study in which Machine Learning experiments applied to Opinion Mining in blogs have been carried out. We created and annotated a blog corpus in Spanish using EmotiBlog. We evaluated the utility of the features labelled firstly carrying out experiments with combinations of them and secondly using the feature selection techniques, we also deal with several problems, such as the noisy character of the input texts, the small size of the training set, the granularity of the annotation scheme and the language object of our study, Spanish, with less resource than English. We obtained promising results considering that it is a preliminary study.

Human-computer interaction for optical music recognition tasks

The need to digitise music scores has led to the development of Optical Music Recognition (OMR) tools. Unfortunately, the performance of these systems is still far from providing acceptable results. This situation forces the user to be involved in the process due to the need of correcting the mistakes made during recognition. However, this correction is performed over the output of the system, so these interventions are not exploited to improve the performance of the recognition. This work sets the scenario in which human and machine interact to accurately complete the OMR task with the least possible effort for the user.

Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).

Quantifying epistemic actions in human-computer interaction

As digital systems move away from traditional desktop setups, new interaction paradigms are emerging that better integrate with users’ realworld surroundings, and better support users’ individual needs. While promising, these modern interaction paradigms also present new challenges, such as a lack of paradigm-specific tools to systematically evaluate and fully understand their use. This dissertation tackles this issue by framing empirical studies of three novel digital systems in embodied cognition – an exciting new perspective in cognitive science where the body and its interactions with the physical world take a central role in human cognition. This is achieved by first, focusing the design of all these systems on a contemporary interaction paradigm that emphasizes physical interaction on tangible interaction, a contemporary interaction paradigm; and second, by comprehensively studying user performance in these systems through a set of novel performance metrics grounded on epistemic actions, a relatively well established and studied construct in the literature on embodied cognition. The first system presented in this dissertation is an augmented Four-in-a-row board game. Three different versions of the game were developed, based on three different interaction paradigms (tangible, touch and mouse), and a repeated measures study involving 36 participants measured the occurrence of three simple epistemic actions across these three interfaces. The results highlight the relevance of epistemic actions in such a task and suggest that the different interaction paradigms afford instantiation of these actions in different ways. Additionally, the tangible version of the system supports the most rapid execution of these actions, providing novel quantitative insights into the real benefits of tangible systems. The second system presented in this dissertation is a tangible tabletop scheduling application. Two studies with single and paired users provide several insights into the impact of epistemic actions on the user experience when these are performed outside of a system’s sensing boundaries. These insights are clustered by the form, size and location of ideal interface areas for such offline epistemic actions to occur, as well as how can physical tokens be designed to better support them. Finally, and based on the results obtained to this point, the last study presented in this dissertation directly addresses the lack of empirical tools to formally evaluate tangible interaction. It presents a video-coding framework grounded on a systematic literature review of 78 papers, and evaluates its value as metric through a 60 participant study performed across three different research laboratories. The results highlight the usefulness and power of epistemic actions as a performance metric for tangible systems. In sum, through the use of such novel metrics in each of the three studies presented, this dissertation provides a better understanding of the real impact and benefits of designing and developing systems that feature tangible interaction.

Institute for Human Adjustment; Dr. Wilma Donahue, March 1948

On negative sleeve: DIAGRAMS WHICH BLIND CAN 'READ'--Diagrams embossed on aluminum foil by the Faximile visograph, now being used for experimental study at the University of Michigan, as they appear before the foil is removed from the machine. these diagrams have been enlarged four times over the size of the sheet of "copy" inserted in the visagraph. They are embossed so that the blind can follow them by touch rather than sight