Modern optoelectronic devices use the advantage of digital systems for data processing aimed at delivering reliable information. However, since commonly used DACs have limited accuracy, some ...artefacts can be observed in data streams, especially in systems designed for continuous, long-term process monitoring. In this paper, the authors' experience with data enhancement using a fibre-optic rotational seismograph (FORS) operating in a closed-loop mode is presented and discussed. Generally, two kinds of enhancement are described. The first one uses suitable filtering techniques adequate for FORS noise investigation, as well as a suitable data resampling method for transmitted data file size reduction. The second one relates to the artefacts observed during data recording in real time. The recording starting point is triggered when the detected signal exceeds a middle signal level and, therefore, the existence of artefacts generally disturbs the recording process. Although the artefacts are easily recognised by human eyes even at first sight, their automatic elimination is not so easy. In this paper, the authors propose a new concept of signal filtering to solve the above problem.
The article presents simple modeling and experimental verification of the power required for thermal comfort in electrically heated clothing. The clothing consists of a jumpsuit with embedded heating ...insets, controlled by a dedicated microprocessor system. The user is able to set heating power using a smartphone app. The experiments, conducted in a mobile freezing chamber, aimed at verification of the model of theoretical power (according to ISO 11079) required to maintain thermal comfort in ambient temperatures below 0 °C. Three participants were asked to adjust heating power to reach thermal comfort. The experiment revealed the required power to be only 40–60% of the theoretical one, meaning that the design of the electrically heating clothing relying solely on the theoretical models and standards would lead to oversizing of the heating system power. Further study indicated that the mean skin temperature by itself is not sufficient as an input to the algorithm for automatic maintaining of thermal comfort, even in stationary conditions.
Despite its recent growth in popularity, actively heated clothing still lacks the ability to cope with demanding user scenarios. As many of these deficiencies stem from an absence of automatic ...control, the authors propose a novel approach using a set of sensors embedded in the clothing to provide data about thermal comfort. Available sensors suffer from a lack of accuracy, as for practical reasons, they cannot be attached to the skin, whose temperature is usually used as a comfort indicator. To determine the magnitude of the problem, the authors conducted experiments, and a thermal model was proposed based on experimental findings; the output from the model was compared with the experimental reference data for three different upper body undergarments. The overall accuracy was found to be good: in most cases, the difference between the computed and reference skin temperatures did not exceed 0.5 °C. Furthermore, the model does not rely on unrealistic assumptions regarding the availability of parameters or measurement data. Our findings demonstrate that it is possible to create a thermal model that, when used for input data processing, allows undergarment temperature to be converted to skin temperature, allowing for automatic control of heating insets.
Vestibular impairments affect patients' movements and can result in difficulties with daily life activities. The main aim of this study is to answer the question whether a simple and short test such ...as rotation about a vertical axis can be an objective method of assessing balance dysfunction in patients with unilateral vestibular impairments. A 360˚ rotation test was performed using six MediPost devices. The analysis was performed in three ways: (1) the analytical approach based only on data from one sensor; (2) the analytical approach based on data from six sensors; (3) the artificial neural network (ANN) approach based on data from six sensors. For approaches 1 and 2 best results were obtained using maximum angular velocities (MAV) of rotation and rotation duration (RD), while approach 3 used 11 different features. The following sensitivities and specificities were achieved: for approach 1: MAV-80% and 60%, RD-69% and 74%; for approach 2: 61% and 85% and RD-74% and 56%; for approach 3: 88% and 84%. The ANN-based six-sensor approach revealed the best sensitivity and specificity among parameters studied, however one-sensor approach might be a simple screening test used e.g. for rehabilitation purposes.
This paper presents a fall risk assessment approach based on a fast mobility test, automatically evaluated using a low-cost, scalable system for the recording and analysis of body movement. This ...mobility test has never before been investigated as a sole source of data for fall risk assessment. It can be performed in a very limited space and needs only minimal additional equipment, yet provides large amounts of information, as the presented system can obtain much more data than traditional observation by capturing minute details regarding body movement. The readings are provided wirelessly by one to seven low-cost micro-electro-mechanical inertial measurement units attached to the subject's body segments. Combined with a body model, these allow segment rotations and translations to be computed and for body movements to be recreated in software. The subject can then be automatically classified by an artificial neural network based on selected values in the test, and those with an elevated risk of falls can be identified. Results obtained from a group of 40 subjects of various ages, both healthy volunteers and patients with vestibular system impairment, are presented to demonstrate the combined capabilities of the test and system. Labelling of subjects as fallers and non-fallers was performed using an objective and precise sensory organization test; it is an important novelty as this approach to subject labelling has never before been used in the design and evaluation of fall risk assessment systems. The findings show a true-positive ratio of 85% and true-negative ratio of 63% for classifying subjects as fallers or non-fallers using the introduced fast mobility test, which are noticeably better than those obtained for the long-established Timed Up and Go test.
BACKWARD INDUCTION: MERITS AND FLAWS Kamiński, Marek M.
Studies in logic, grammar and rhetoric : the Journal of University of Bialystok,
6/2017, Letnik:
50, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Backward induction (BI) was one of the earliest methods developed for solving finite sequential games with perfect information. It proved to be especially useful in the context of Tom Schelling’s ...ideas of credible versus incredible threats. BI can be also extended to solve complex games that include an infinite number of actions or an infinite number of periods. However, some more complex empirical or experimental predictions remain dramatically at odds with theoretical predictions obtained by BI. The primary example of such a troublesome game is Centipede. The problems appear in other long games with sufficiently complex structure. BI also shares the problems of subgame perfect equilibrium and fails to eliminate certain unreasonable Nash equilibria.
Abstract This paper presents a decision support system that aims to estimate a patient׳s general condition and detect situations which pose an immediate danger to the patient׳s health or life. The ...use of this system might be especially important in places such as accident and emergency departments or admission wards, where a small medical team has to take care of many patients in various general conditions. Particular stress is laid on cardiovascular and pulmonary conditions, including those leading to sudden cardiac arrest. The proposed system is a stand-alone microprocessor-based device that works in conjunction with a standard vital signs monitor, which provides input signals such as temperature, blood pressure, pulseoxymetry, ECG, and ICG. The signals are preprocessed and analysed by a set of artificial intelligence algorithms, the core of which is based on Bayesian networks. The paper focuses on the construction and evaluation of the Bayesian network, both its structure and numerical specification.
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