Modeling of the relative humidity via functional networks and control of the temperature via classic controls for a bird incubator

The control of the relative humidity and the temperature is important for the birds to be born. It is not easy to control the relative humidity, but it is possible to obtain the measure of the relative humidity as a consequence of the control of the temperature in a bird incubator. In this article, (1) the mathematical model for the control of temperature in the bird incubator is presented, (2) a functional network to approximate the relative humidity behavior in the bird incubator is proposed, (3) a control for the temperature in the bird incubator is proposed, the error of the proportional control applied to the mathematical model of the temperature of the bird incubator is assured to be uniformly stable, (4) the comparison results of four classic control laws for the control of the temperature considering the proposed mathematical model of the temperature and the functional network to approximate the relative humidity behavior in the bird incubator are presented.     

How to take into account general and contextual knowledge for interactive aiding design: Towards the coupling of CSP and CBR approaches

The goal of this paper is to show how it is possible to support design decisions with two different tools relying on two kinds of knowledge: case-based reasoning operating with contextual knowledge embodied in past cases and constraint filtering that operates with general knowledge formalized using constraints. Our goals are, firstly to make an overview of existing works that analyses the various ways to associate these two kinds of aiding tools essentially in a sequential way. Secondly, we propose an approach that allows us to use them simultaneously in order to assist design decisions with these two kinds of knowledge. The paper is organized as follows. In the first section, we define the goal of the paper and recall the background of case-based reasoning and constraint filtering. In the second section, the industrial problem which led us to consider these two kinds of knowledge is presented. In the third section, an overview of the various possibilities of using these two aiding decision tools in a sequential way is drawn up. In the fourth section, we propose an approach that allows us to use both aiding decision tools in a simultaneous and iterative way according to the availability of knowledge. An example dealing with helicopter maintenance illustrates our proposals.     

Office task effects on comfort and body dynamics in five dynamic office chairs

In the present study, we investigated the effect of office tasks on posture and movements in field settings, and the comfort rating for chair characteristics and correlation with type of task. The tasks studied were: computer work, telephoning, desk work and conversation. Postures, movements, chair part inclinations and comfort rating data were collected from 12 subjects. Computer work showed the lowest physical activity, together with upright trunk and head position and low backrest inclination. Conversation shows the highest activity of head legs and low back together with the highest cervical spine extension. In contrast, desk work provoked the most cervical spine flexion and showed the second lowest activity. The telephoning tasks showed medium activity and the highest kyphosis. Conversation showed the highest backrest inclination. Positive comfort relations were found for computer work and a "swing system" chair, for telephoning and an active longitudinal seat rotation, and for desk work and a chair with a three-dimensionally moveable seat.     

Numerical simulation of the N-dimensional sine-Gordon equation via operational matrices

In this paper, we develop a numerical method for the N-dimensional sine-Gordon equation using differentiation matrices, in the theoretical frame of matrix differential equations.Our method avoids calculating exponential matrices, is very intuitive and easy to express, and can be implemented without toil in any number of spatial dimensions. Although there is currently a vast literature on the numerical treatment of the one-dimensional sine-Gordon equation, the references for the two-dimensional case are much sparser, and virtually nonexistent for higher dimensions.We apply it to a battery of two-dimensional problems taken from the literature, showing that it largely outperforms the previously existing algorithms; while for three-dimensional problems, the results seem very promising.     

Light on! Real world evaluation of a P300-based brain-computer interface (BCI) for environment control in a smart home

Brain-computer interface (BCI) systems aim to enable interaction with other people and the environment without muscular activation by the exploitation of changes in brain signals due to the execution of cognitive tasks. In this context, the visual P300 potential appears suited to control smart homes through BCI spellers. The aim of this work is to evaluate whether the widely used character-speller is more sustainable than an icon-based one, designed to operate smart home environment or to communicate moods and needs. Nine subjects with neurodegenerative diseases and no BCI experience used both speller types in a real smart home environment. User experience during BCI tasks was evaluated recording concurrent physiological signals. Usability was assessed for each speller type immediately after use. Classification accuracy was lower for the icon-speller, which was also more attention demanding. However, in subjective evaluations, the effect of a real feedback partially counterbalanced the difficulty in BCI use. PRACTITIONER SUMMARY: Since inclusive BCIs require to consider interface sustainability, we evaluated different ergonomic aspects of the interaction of disabled users with a character-speller (goal: word spelling) and an icon-speller (goal: operating a real smart home). We found the first one as more sustainable in terms of accuracy and cognitive effort.     

The influence of music on mood and performance while driving

Mood can influence our everyday behaviour and people often seek to reinforce, or to alter their mood, for example by turning on music. Music listening while driving is a popular activity. However, little is known about the impact of music listening while driving on physiological state and driving performance. In the present experiment, it was investigated whether individually selected music can induce mood and maintain moods during a simulated drive. In addition, effects of positive, negative, and no music on driving behaviour and physiological measures were assessed for normal and high cognitive demanding rides. Subjective mood ratings indicated that music successfully maintained mood while driving. Narrow lane width drives increased task demand as shown in effort ratings and increased swerving. Furthermore, respiration rate was lower during music listening compared to rides without music, while no effects of music were found on heart rate. Overall, the current study demonstrates that music listening in car influences the experienced mood while driving, which in turn can impact driving behaviour. PRACTITIONERS SUMMARY: Even though it is a popular activity, little is known about the impact of music while driving on physiological state and performance. We examined whether music can induce moods during high and low simulated drives. The current study demonstrates that in car music listening influences mood which in turn can impact driving behaviour. The current study shows that listening to music can positively impact mood while driving, which can be used to affect state and safe behaviour. Additionally, driving performance in high demand situations is not negatively affected by music.     

Compact yet efficient hardware implementation of artificial neural networks with customized topology

There are several neural network implementations using either software, hardware-based or a hardware/software co-design. This work proposes a hardware architecture to implement an artificial neural network (ANN), whose topology is the multilayer perceptron (MLP). In this paper, we explore the parallelism of neural networks and allow on-the-fly changes of the number of inputs, number of layers and number of neurons per layer of the net. This reconfigurability characteristic permits that any application of ANNs may be implemented using the proposed hardware. In order to reduce the processing time that is spent in arithmetic computation, a real number is represented using a fraction of integers. In this way, the arithmetic is limited to integer operations, performed by fast combinational circuits. A simple state machine is required to control sums and products of fractions. Sigmoid is used as the activation function in the proposed implementation. It is approximated by polynomials, whose underlying computation requires only sums and products. A theorem is introduced and proven so as to cover the arithmetic strategy of the computation of the activation function. Thus, the arithmetic circuitry used to implement the neuron weighted sum is reused for computing the sigmoid. This resource sharing decreased drastically the total area of the system. After modeling and simulation for functionality validation, the proposed architecture synthesized using reconfigurable hardware. The results are promising.     

SME Network Characteristics vs. Product Innovativeness: How to Achieve High Innovation Performance

Small‐ and medium‐sized enterprises (SMEs) must on the one hand innovate for company survival with the appropriate degree of product innovativeness, and on the other they need to collaborate and focus on core competences for efficiency matters. This research examines the relation of network characteristics and product innovativeness on innovation performance in SMEs. We tested hypotheses on the relationship between these three variables via data gathered from 60 SMEs, active in the medical devices sector. In this context we aim to offer consensus on the theoretical and empirical question of whether or not network characteristics and product innovativeness have a direct effect on innovation performance of SMEs. Results show no significant direct effect of product innovativeness on innovation performance. A positive interaction effect of multiple network characteristics on innovation performance was found, which confirms the significant importance of network configuration on innovation performance for SMEs. It indicates that, for SMEs in a highly regulated sector like the medical devices sector, the interaction of network characteristics is of crucial importance for high innovation performance. It is the combination of network characteristics that counts.     

Preference-based multi-objective evolutionary algorithms for power-aware application mapping on NoC platforms

Network-on-chip (NoC) are considered the next generation of communication infrastructure in embedded systems. In the platform-based design methodology, an application is implemented by a set of collaborative intellectual property (IP) blocks. The selection of the most suited set of IPs as well as their physical mapping onto the NoC infrastructure to implement efficiently the application at hand are two hard combinatorial problems that occur during the synthesis process of Noc-based embedded system implementation. In this paper, we propose an innovative preference-based multi-objective evolutionary methodology to perform the assignment and mapping stages. We use one of the well-known and efficient multi-objective evolutionary algorithms NSGA-II and microGA as a kernel. The optimization processes of assignment and mapping are both driven by the minimization of the required silicon area and imposed execution time of the application, considering that the decision maker’s preference is a pre-specified value of the overall power consumption of the implementation.