Dialog Based on Graphical Static Scenes Managed by an Ontology

A new method to implementation of dialog based on graphical static scenes using an ontology-based approach to user interface development is proposed. The main idea of the approach is to form necessary to the user interface development and implementation information using ontologies and then based on this high-level specification to generate the user interface.

Static and Dynamic Integrated Expert Systems: State of the Art, Problems and Trends

Systemized analysis of trends towards integration and hybridization in contemporary expert systems is conducted, and a particular class of applied expert systems, integrated expert systems, is considered. For this purpose, terminology, classification, and models, proposed by the author, are employed. As examples of integrated expert systems, Russian systems designed in this field and available to the majority of specialists are analyzed.

Neural Approach in Multi-Agent Routing for Static Telecommunication Networks

The problem of multi-agent routing in static telecommunication networks with fixed configuration is considered. The problem is formulated in two ways: for centralized routing schema with the coordinator-agent (global routing) and for distributed routing schema with independent agents (local routing). For both schemas appropriate Hopfield neural networks (HNN) are constructed.

Smart Portable Tester for Bird Flue Express-Diagnostics: Principles of Design

In the V.M. Glushov Institute of Cybernetics of National Academy of Sciences of Ukraine in collaboration with O.V. Palladin’s Institute of Biochemistry of National Academy of Sciences of Ukraine the smart portable device for express-diagnostics of acute viral infections, including bird flu, is designed. The device is based on the effect of surface plasmon resonance. The principles of device are described in the article.

Static, dynamic, and adaptive heterogeneity in distributed smart camera networks

We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

The effect of whole body vibration on oxygen uptake and electromyographic signal of the rectus femoris muscle during static and dynamic squat

Whole Body Vibrations consist of a vibration stimulus mechanically transferred to the body. The impact of vibration treatment on specific muscular activity, neuromuscular, and postural control has been widely studied. We investigated whole body vibration (WBV) effect on oxygen uptake and electromyographic signal of the rectus femoris muscle during static and dynamic squat. Fourteen healthy subjects performed a static and dynamic squat with and without vibration. During the vibration exercises, a significant increase was found in oxygen uptake (P=0.05), which increased by 44% during the static squat and 29.4% during the dynamic squat. Vibration increased heart rate by 11.1 ± 9.1 beats.min-1 during the static squat and 7.9 ± 8.3 beats.min-1 during the dynamic squat. No significant changes were observed in rate of perceived exertion between the exercises with and without vibration. The results indicate that the static squat with WBV produced higher neuromuscular and cardiorespiratory system activation for exercise duration ?60 sec. Otherwise, if the single bout duration was higher than 60 sec, the greater cardiorespiratory system activation was achieved during the dynamic squat with WBV while higher neuromuscular activation was still obtained with the static exercise.

Neuromuscular response to whole body vibration treatment during static and dynamic squat exercises

The impact of whole body vibrations (vibration stimulus mechanically transferred to the body) on muscular activity and neuromuscular response has been widely studied but without standard protocol and by using different kinds of exercises and parameters. In this study, we investigated how whole body vibration treatments affect electromyographic signal of rectus femoris during static and dynamic squat exercises. The aim was the identification of squat exercise characteristics useful to maximize neuromuscular activation and hence progress in training efficacy. Fourteen healthy volunteers performed both static and dynamic squat exercises without and with vibration treatments. Surface electromyographic signals of rectus femoris were recorded during the whole exercise and processed to reduce artifacts and to extract root mean square values. Paired t-test results demonstrated an increase of the root mean square values (p<0.05) in both static and dynamic squat exercises with vibrations respectively of 63% and 108%. For each exercise, subjects gave a rating of the perceived exertion according to the Borg's scale but there were no significant changes in the perceived exertion rate between exercises with and without vibration. Finally, results from analysis of electromyographic signals identified the static squat with WBV treatment as the exercise with higher neuromuscular system response. © 2012 IEEE.

Measuring the flow properties of small powder samples using an avalanche tester

The feasibility of using a small-scale avalanche tester to measure the flow properties of pharmaceutical lactose powders was examined. The modes of behaviour observed in larger systems were displayed and showed a clear distinction between angular, free-flowing particles and more spherical particles of similar flow characteristics. Angular Lactohale LH100 particles showed slumping behaviour at a rotational frequency of 0.33Hz which disappeared at higher frequencies. Spherical lactose powder with a similar flow function to LH100 only showed rolling behaviour under the same conditions, as did more cohesive powders LH200 and LH300. Further investigation of the LH100 data using Fast Fourier analysis showed that the slumping frequency was 1/10th of the rotational frequency.

Extracting Business Rules through Static Analysis of the Source Code

Красимир Манев, Нели Манева, Хараламби Хараламбиев - Подходът с използване на бизнес правила (БП) беше въведен в края на миналия век, за да се улесни специфицирането на фирмен софтуер и да може той да задоволи по-добре нуждите на съответния бизнес. Днес повечето от целите на подхода са постигнати. Но усилията, в научно-изследователски и практически аспект, за постигане на „’формална основа за обратно извличане на БП от съществуващи системи “продължават. В статията е представен подход за извличане на БП от програмен код, базиран на методи за статичен анализ на кода. Посочени са някои предимства и недостатъци на такъв подход.

The value of tablets as reading aids for individuals with central visual field loss:an evaluation of eccentric reading with static and scrolling text

Purpose: Technological devices such as smartphones and tablets are widely available and increasingly used as visual aids. This study evaluated the use of a novel app for tablets (MD_evReader) developed as a reading aid for individuals with a central field loss resulting from macular degeneration. The MD_evReader app scrolls text as single lines (similar to a news ticker) and is intended to enhance reading performance using the eccentric viewing technique by both reducing the demands on the eye movement system and minimising the deleterious effects of perceptual crowding. Reading performance with scrolling text was compared with reading static sentences, also presented on a tablet computer. Methods: Twenty-six people with low vision (diagnosis of macular degeneration) read static or dynamic text (scrolled from right to left), presented as a single line at high contrast on a tablet device. Reading error rates and comprehension were recorded for both text formats, and the participant’s subjective experience of reading with the app was assessed using a simple questionnaire. Results: The average reading speed for static and dynamic text was not significantly different and equal to or greater than 85 words per minute. The comprehension scores for both text formats were also similar, equal to approximately 95% correct. However, reading error rates were significantly (p=0.02) less for dynamic text than for static text. The participants’ questionnaire ratings of their reading experience with the MD_evReader were highly positive and indicated a preference for reading with this app compared with their usual method. Conclusions: Our data show that reading performance with scrolling text is at least equal to that achieved with static text and in some respects (reading error rate) is better than static text. Bespoke apps informed by an understanding of the underlying sensorimotor processes involved in a cognitive task such as reading have excellent potential as aids for people with visual impairments.

A static traffic assignment model combined with an artificial neural network delay model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

A Static Traffic Assignment Model Combined with an Artificial Neural Network Delay Model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Static and dynamic mechanical testing of a polymer with potential use as heart valve material

Synthetic tri-leaflet heart valves generally fail in the long-term use (more than 10 years). Tearing and calcification of the leaflets usually cause failure of these valves as a consequence of high tensile and bending stresses borne on the material. The primary purpose of this study was to explore the possibilities of a new polymer composite to be used as synthetic tri-leaflet heart valve material. This composite was comprised of polystyrene-polyisobutylene-polystyrene (Quatromer), a proprietary polymer, embedded with continuous polypropylene (PP) fibers. Quatromer had been found to be less likely to degrade in vivo than polyurethane. Moreover, it was postulated that a decrease in tears and perforations might result from fiber-reinforced leaflets reducing high stresses on the leaflets. The static and dynamic mechanical properties of the Quatromer/PP composite were compared with those of an implant-approved polyurethane (PU) for cardiovascular applications. Results show that the reinforcement of Quatromer with PP fibers improves both its static and dynamic properties as compared to the PU. Hence, this composite has the potential to be a more suitable material for synthetic tri-leaflet heart valves.

(Table 1) Comparisons of dynamic and static Young's moduli of basalt at DSDP Holes 69-504B, 70-504B and 83-504B

Compressional- and shear-wave velocity logs (Vp and Vs, respectively) that were run to a sub-basement depth of 1013 m (1287.5 m sub-bottom) in Hole 504B suggest the presence of Layer 2A and document the presence of layers 2B and 2C on the Costa Rica Rift. Layer 2A extends from the mudline to 225 m sub-basement and is characterized by compressional-wave velocities of 4.0 km/s or less. Layer 2B extends from 225 to 900 m and may be divided into two intervals: an upper level from 225 to 600 m in which Vp decreases slowly from 5.0 to 4.8 km/s and a lower level from 600 to about 900 m in which Vp increases slowly to 6.0 km/s. In Layer 2C, which was logged for about 100 m to a depth of 1 km, Vp and Vs appear to be constant at 6.0 and 3.2 km/s, respectively. This velocity structure is consistent with, but more detailed than the structure determined by the oblique seismic experiment in the same hole. Since laboratory measurements of the compressional- and shear-wave velocity of samples from Hole 504B at Pconfining = Pdifferential average 6.0 and 3.2 km/s respectively, and show only slight increases with depth, we conclude that the velocity structure of Layer 2 is controlled almost entirely by variations in porosity and that the crack porosity of Layer 2C approaches zero. A comparison between the compressional-wave velocities determined by logging and the formation porosities calculated from the results of the large-scale resistivity experiment using Archie's Law suggest that the velocity- porosity relation derived by Hyndman et al. (1984) for laboratory samples serves as an upper bound for Vp, and the noninteractive relation derived by Toksöz et al. (1976) for cracks with an aspect ratio a = 1/32 serves as a lower bound.