956 resultados para Human Machine Interface
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Mode of access: Internet.
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Mode of access: Internet.
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Includes bibliographies and indexes.
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The paper introduces a method for dependencies discovery during human-machine interaction. It is based on an analysis of numerical data sets in knowledge-poor environments. The driven procedures are independent and they interact on a competitive principle. The research focuses on seven of them. The application is in Number Theory.
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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016
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Starting with a description of the software and hardware used for corpus linguistics in the late 1980s to early 1990s, this contribution discusses difficulties faced by the software designer when attempting to allow users to study text. Future human-machine interfaces may develop to be much more sophisticated, and certainly the aspects of text which can be studied will progress beyond plain text without images. Another area which will develop further is the study of patternings involving not just single words but word-relations across large stretches of text.
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Effective interaction with personal computers is a basic requirement for many of the functions that are performed in our daily lives. With the rapid emergence of the Internet and the World Wide Web, computers have become one of the premier means of communication in our society. Unfortunately, these advances have not become equally accessible to physically handicapped individuals. In reality, a significant number of individuals with severe motor disabilities, due to a variety of causes such as Spinal Cord Injury (SCI), Amyothrophic Lateral Sclerosis (ALS), etc., may not be able to utilize the computer mouse as a vital input device for computer interaction. The purpose of this research was to further develop and improve an existing alternative input device for computer cursor control to be used by individuals with severe motor disabilities. This thesis describes the development and the underlying principle for a practical hands-off human-computer interface based on Electromyogram (EMG) signals and Eye Gaze Tracking (EGT) technology compatible with the Microsoft Windows operating system (OS). Results of the software developed in this thesis show a significant improvement in the performance and usability of the EMG/EGT cursor control HCI.
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The astonishing development of diverse and different hardware platforms is twofold: on one side, the challenge for the exascale performance for big data processing and management; on the other side, the mobile and embedded devices for data collection and human machine interaction. This drove to a highly hierarchical evolution of programming models. GVirtuS is the general virtualization system developed in 2009 and firstly introduced in 2010 enabling a completely transparent layer among GPUs and VMs. This paper shows the latest achievements and developments of GVirtuS, now supporting CUDA 6.5, memory management and scheduling. Thanks to the new and improved remoting capabilities, GVirtus now enables GPU sharing among physical and virtual machines based on x86 and ARM CPUs on local workstations,computing clusters and distributed cloud appliances.
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Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.
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La ricerca si focalizza sul rapporto tra tecnologie abilitanti e corpo umano. La miniaturizzazione delle tecnologie, unita alla loro maggiore diffusione negli ambienti, porta ad interrogarsi sull’efficacia dell’integrazione di esse con corpo e attività ad esso connesse. Il contesto problematico della ricerca riguarda i dispositivi indossabili e il progetto di soluzioni destinate a risolvere inediti bisogni o potenziare i sensi umani. La letteratura scientifica e i casi studio circoscrivono il piede come efficace piattaforma per la sperimentazione di interfacce aptiche di comunicazione uomo/macchina, atte a connettere il corpo con informazioni referenziate all’ambiente. Il piede, elemento motorio duplice e simmetrico, ha un’elevata qualità percettiva ed è morfologicamente adeguato all’applicazione di tecnologie emergenti. La posizione di soglia, tra spazio e corpo, consente la raccolta di stimoli da entrambe le aree. La bibliografia evidenzia quanto la pressione, rispetto alla vibrazione, sia preferibile nella comunicazione aptica in quanto componente naturale dei linguaggi relazionali del corpo. Dall’analisi multidisciplinare emerge infine l’opportunità di sviluppo del ritmo come componente strutturale dei messaggi. I legami relazionali tra ritmo, corpo e comportamenti umani sono evidenti in molteplici meccanismi: trascinamento ritmico, mimesi ritmica, sincronia. La messa in relazione di piede, pressione e ritmo diventa affordance dello spazio, capace di suggerire, enfatizzare o attivare determinati comportamenti. L’unione di questi elementi è qui definita ritmica podotattile ed esplicitata nella tesi della descrizione delle sue caratteristiche, dalla circoscrizione di campi e azioni applicative e dalla raccolta dati sui test effettuati con i prototipi costruiti. Le analisi quantitative e qualitative dei dati di lettura del movimento e delle emozioni dimostrano quanto l’utilizzo di un linguaggio ritmico aptico nel piede esprima elevate potenzialità di integrazione con il corpo nel rispetto del comfort e dell’equilibrio attentivo nei flussi di azione preesistenti. I risultati aprono riflessioni su nuove applicazioni progettuali nel campo museale, lavorativo e urbano.
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Advancements in technology have enabled increasingly sophisticated automation to be introduced into the flight decks of modern aircraft. Generally, this automation was added to accomplish worthy objectives such as reducing flight crew workload, adding additional capability, or increasing fuel economy. Automation is necessary due to the fact that not all of the functions required for mission accomplishment in today’s complex aircraft are within the capabilities of the unaided human operator, who lacks the sensory capacity to detect much of the information required for flight. To a large extent, these objectives have been achieved. Nevertheless, despite all the benefits from the increasing amounts of highly reliable automation, vulnerabilities do exist in flight crew management of automation and Situation Awareness (SA). Issues associated with flight crew management of automation include: • Pilot understanding of automation’s capabilities, limitations, modes, and operating principles and techniques. • Differing pilot decisions about the appropriate automation level to use or whether to turn automation on or off when they get into unusual or emergency situations. • Human-Machine Interfaces (HMIs) are not always easy to use, and this aspect could be problematic when pilots experience high workload situations. • Complex automation interfaces, large differences in automation philosophy and implementation among different aircraft types, and inadequate training also contribute to deficiencies in flight crew understanding of automation.
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Intelligent systems are currently inherent to the society, supporting a synergistic human-machine collaboration. Beyond economical and climate factors, energy consumption is strongly affected by the performance of computing systems. The quality of software functioning may invalidate any improvement attempt. In addition, data-driven machine learning algorithms are the basis for human-centered applications, being their interpretability one of the most important features of computational systems. Software maintenance is a critical discipline to support automatic and life-long system operation. As most software registers its inner events by means of logs, log analysis is an approach to keep system operation. Logs are characterized as Big data assembled in large-flow streams, being unstructured, heterogeneous, imprecise, and uncertain. This thesis addresses fuzzy and neuro-granular methods to provide maintenance solutions applied to anomaly detection (AD) and log parsing (LP), dealing with data uncertainty, identifying ideal time periods for detailed software analyses. LP provides deeper semantics interpretation of the anomalous occurrences. The solutions evolve over time and are general-purpose, being highly applicable, scalable, and maintainable. Granular classification models, namely, Fuzzy set-Based evolving Model (FBeM), evolving Granular Neural Network (eGNN), and evolving Gaussian Fuzzy Classifier (eGFC), are compared considering the AD problem. The evolving Log Parsing (eLP) method is proposed to approach the automatic parsing applied to system logs. All the methods perform recursive mechanisms to create, update, merge, and delete information granules according with the data behavior. For the first time in the evolving intelligent systems literature, the proposed method, eLP, is able to process streams of words and sentences. Essentially, regarding to AD accuracy, FBeM achieved (85.64+-3.69)%; eGNN reached (96.17+-0.78)%; eGFC obtained (92.48+-1.21)%; and eLP reached (96.05+-1.04)%. Besides being competitive, eLP particularly generates a log grammar, and presents a higher level of model interpretability.
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Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.
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Tarkastelen tutkielmassani Dan Simmonsin kaksiosaista tieteisfiktioteosta, joka koostuu romaaneista Hyperion ja The Fall of Hyperion. Keskityn teoksissa esiintyvään Shrike-hirviöön, joka edustaa ihmiskunnan pelkäämää potentiaalista konfliktia ihmisten ja koneiden välillä. Pelko ja konflikti ovat keskeisiä teemoja paitsi tieteisfiktiossa, myös hirviöteoksissa yleensä, ja näiden kahden käyttö samassa kertomuksessa luo otolliset edellytykset nyky-yhteiskunnan ahdistusten kuvaamiseen. Hirviöitä ja tieteisfiktiota on tätä nykyä tutkittu melko laajalti, mutta Shrike on aiemmin jäänyt vähälle huomiolle. Lähtökohtaisen teoreettisen viitekehyksen tutkimukselleni ovat luoneet Jeffrey Cohenin Monster Theory: Reading Culture, Stephen Asman On Monsters: An Unnatural History of Our Worst Fears sekä Holly Lynn Baumgartnerin ja Roger Davisin At the Interface: Hosting the Monster. Teoksista kokoamani hirviöteorian kautta tarkastelen sitä, miten Shriken puoliksi orgaaninen ja puoliksi keinotekoinen keho heijastaa niitä romaaneissa esiintyviä osa-alueita, joista tulevaisuudenpelko ja ihmisten ja koneiden väliseen konfliktin uhka koostuu. Koska Shrike on puoliksi orgaaninen ja puoliksi keinotekoinen, se on näiden ominaisuuksien kynnyksellä; tässä risteytyneessä kehossa yhdistyvät molemmat ääripäät, jolloin tämä keho myös symboloi osapuolten välistä konfliktia. Konfliktin lisäksi Shrike ilmentää niitä vastakkaisuuksia, joista ihmisten ja koneiden välisen konfliktin pelko rakentuu: itseyttä ja toiseutta, houkuttelevuutta ja luotaantyöntävyyttä, menneisyyttä ja tulevaisuutta sekä utopiaa ja dystopiaa.
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In this paper a look is taken at how the use of implant technology can be used to either increase the range of the abilities of a human and/or diminish the effects of a neural illness, such as Parkinson's Disease. The key element is the need for a clear interface linking the human brain directly with a computer. The area of interest here is the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Pilot tests and experimentation are invariably carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed here. The paper goes on to describe human experimentation, in particular that carried out by the author himself, which led to him receiving a neural implant which linked his nervous system bi-directionally with the internet. With this in place neural signals were transmitted to various technological devices to directly control them. In particular, feedback to the brain was obtained from the fingertips of a robot hand and ultrasonic (extra) sensory input. A view is taken as to the prospects for the future, both in the near term as a therapeutic device and in the long term as a form of enhancement.