409 research outputs found
Human Machine Interaction
In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction
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Multi-electrode array recording and data analysis methods for molluscan central nervous systems
In this work the use of the central nervous system (CNS) of the aquatic
snail Lymnaea stagnalis on planar multi-electrode arrays (MEAs) was
developed and analysis methods for the data generated were created.
A variety of different combinations of configurations of tissue from the
Lymnaea CNS were explored to determine the signal characteristics
that could be recorded by sixty channel MEAs. In particular, the
suitability of the semi-intact system consisting of the lips, oesophagus,
CNS, and associated nerve connectives was developed for use on
the planar MEA. The recording target area of the dorsal surface of
the buccal ganglia was selected as being the most promising for study
and recordings of its component cells during fictive feeding behaviour
stimulated by sucrose were made. The data produced by this type of
experimentation is very high volume and so its analysis required the
development of a custom set of software tools. The goal of this tool
set is to find the signal from individual neurons in the data streams of
the electrodes of a planar MEA, to estimate their position, and then
to predict their causal connectivity. To produce such an analysis techniques
for noise filtration, neural spike detection, and group detection
of bursts of spikes were created to pre-process electrode data streams.
The Kohonen self-organising map (SOM) algorithm was adapted for
the purpose of separating detected spikes into data streams representing
the spike output of individual cells found in the target system. A
significant addition to SOM algorithm was developed by the concurrent
use of triangulation methods based on current source density
analysis to predict the position of individual cells based on their spike
output on more than one electrode. The likely functional connectivity
of individual neurons identified by the SOM technique were analysed
through the use of a statistical causality method known as Granger
causality/causal connectivity. This technique was used to produce a
map of the likely connectivity between neural sources
Easy Uncertainty Quantification (EasyUQ): Generating Predictive Distributions from Single-valued Model Output
How can we quantify uncertainty if our favorite computational tool - be it a
numerical, a statistical, or a machine learning approach, or just any computer
model - provides single-valued output only? In this article, we introduce the
Easy Uncertainty Quantification (EasyUQ) technique, which transforms
real-valued model output into calibrated statistical distributions, based
solely on training data of model output-outcome pairs, without any need to
access model input. In its basic form, EasyUQ is a special case of the recently
introduced Isotonic Distributional Regression (IDR) technique that leverages
the pool-adjacent-violators algorithm for nonparametric isotonic regression.
EasyUQ yields discrete predictive distributions that are calibrated and optimal
in finite samples, subject to stochastic monotonicity. The workflow is fully
automated, without any need for tuning. The Smooth EasyUQ approach supplements
IDR with kernel smoothing, to yield continuous predictive distributions that
preserve key properties of the basic form, including both, stochastic
monotonicity with respect to the original model output, and asymptotic
consistency. For the selection of kernel parameters, we introduce multiple
one-fit grid search, a computationally much less demanding approximation to
leave-one-out cross-validation. We use simulation examples and forecast data
from weather prediction to illustrate the techniques. In a study of benchmark
problems from machine learning, we show how EasyUQ and Smooth EasyUQ can be
integrated into the workflow of neural network learning and hyperparameter
tuning, and find EasyUQ to be competitive with conformal prediction, as well as
more elaborate input-based approaches
Modular Neural Networks for Low-Power Image Classification on Embedded Devices
Embedded devices are generally small, battery-powered computers with limited hardware resources. It is difficult to run deep neural networks (DNNs) on these devices, because DNNs perform millions of operations and consume significant amounts of energy. Prior research has shown that a considerable number of a DNN’s memory accesses and computation are redundant when performing tasks like image classification. To reduce this redundancy and thereby reduce the energy consumption of DNNs, we introduce the Modular Neural Network Tree architecture. Instead of using one large DNN for the classifier, this architecture uses multiple smaller DNNs (called modules) to progressively classify images into groups of categories based on a novel visual similarity metric. Once a group of categories is selected by a module, another module then continues to distinguish among the similar categories within the selected group. This process is repeated over multiple modules until we are left with a single category. The computation needed to distinguish dissimilar groups is avoided, thus reducing redundant operations, memory accesses, and energy. Experimental results using several image datasets reveal the effectiveness of our proposed solution to reduce memory requirements by 50% to 99%, inference time by 55% to 95%, energy consumption by 52% to 94%, and the number of operations by 15% to 99% when compared with existing DNN architectures, running on two different embedded systems: Raspberry Pi 3 and Raspberry Pi Zero
Automatic Dispenser for Kitchen Robots
In the last years we have seen technology and human-machine-interaction exponentially evolve and having great developments. With these developments and the integration of technology in every day life, a natural change in quotidian life is expected, and a place where we can see these changes is in the kitchen.
One of technology’s objectives is to ease a task or do it completely on its own, with the rising pace at which the society lives it became a necessity to reduce the wasted time in every way we can. This dissertation objective was to reduce the wasted time, by being integrated in the kitchen it will reduce the time the user needs to be present and therefore use the free time as he wishes. There are already some implemented solutions, however, those solutions still have some problems that end up limiting the possibility of user absence, the ones that permit total absence don’t permit any user input as to change any
recipe information during its execution.
As a solution for this, an automatic dispenser was developed as the objective of this dissertation, the goal of this dispenser is to deliver the required ingredients for a given recipe, this recipe will be given by the main machine where this dispenser is to connect and be a module of. The development of this work started with looking into some existing solutions and identify their major issues, and with those in mind define software and
hardware architectures, to better answer the problems at hand and get to an improved solution which the user can rely on.Nos últimos anos a tecnologia e as interações humano-máquina têm sofrido uma evolução exponencial e com grandes desenvolvimentos. Com estes desenvolvimentos e integração dessas tecnologias no dia a dia vem uma mudança natural na vida quotidiana, uma zona onde podemos observar estas mudanças é na cozinha.
Um dos objetivos da tecnologia é o de facilitar tarefas ou fazê-las por completo, com o ritmo cada vez mais acelerado com que a sociedade vive, tornou-se numa necessidade reduzir o tempo desperdiçado nas mais diversas áreas. Esta dissertação surge com o objetivo de reduzir esse tempo desperdiçado a cozinhar, sendo esta uma tarefa que necessita de algum tempo, tempo esse que poderia ser utilizado para lazer. Apesar de existirem já algumas soluções implementadas, existem ainda alguns problemas que acabam por limitar a possibilidade de uma ausência total do utilizador, as que permitem esta ausência, não permitem qualquer alteração por parte do utilizador na receita, após iniciar o processo.
De forma a solucionar estas questões, foi desenvolvido um dispensador automático nesta dissertação, o objetivo deste dispensador é o de dispensar ingredientes para uma dada receita, esta receita é dada pela máquina principal à qual este dispensador deve ser conectado, e da qual deve ser um modulo. O desenvolvimento desta dissertação começou por analizar as soluções já existentes e identificar os seus maiores problemas, e a partindo destes, definir arquiteturas de software e hardware que respondem da melhor forma aos mesmos, de modo a obter uma melhor solução final em que o utilizador possa confiar
Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review
Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years.
On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance.
Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones
Web-based language production experiments: Semantic interference assessment is robust for spoken and typed response modalities
For experimental research on language production, temporal precision and high quality of the recorded audio files are imperative. These requirements are a considerable challenge if language production is to be investigated online. However, online research has huge potential in terms of efficiency, ecological validity and diversity of study populations in psycholinguistic and related research, also beyond the current situation. Here, we supply confirmatory evidence that language production can be investigated online and that reaction time (RT) distributions and error rates are similar in written naming responses (using the keyboard) and typical overt spoken responses. To assess semantic interference effects in both modalities, we performed two pre-registered experiments (n = 30 each) in online settings using the participants' web browsers. A cumulative semantic interference (CSI) paradigm was employed that required naming several exemplars of semantic categories within a seemingly unrelated sequence of objects. RT is expected to increase linearly for each additional exemplar of a category. In Experiment 1, CSI effects in naming times described in lab-based studies were replicated. In Experiment 2, the responses were typed on participants' computer keyboards, and the first correct key press was used for RT analysis. This novel response assessment yielded a qualitatively similar, very robust CSI effect. Besides technical ease of application, collecting typewritten responses and automatic data preprocessing substantially reduce the work load for language production research. Results of both experiments open new perspectives for research on RT effects in language experiments across a wide range of contexts. JavaScript- and R-based implementations for data collection and processing are available for download
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