In above operational scenario, following agents 1 have been identified: Aircraft, Air Traffic Control (ATC), Meteorological Service Provider (MPS), Airspace Resources Provider (ASP) and Airline Operational Control (AOC). In addition several ATC agents could be defined in order to coordinate arrival ATC activities with en-route or departure ATC. However it is not essential when the study is focused on an airborne viewpoint. MSP, ASP and AOC agents’ functionalities have been used to identify information requirements of ATC and Aircraft as well as their associated protocols to obtain referred information. In addition, human user and systems have been jointly modeled as an autonomous agent whose inner automatic processes are transparent to the human operator (crew or air-traffic controller).
cases, the comparison of MIFs computed in diverse compounds requires that these structures must be first superimposed in the space, in such way that the energies computed at the same position of the space could be directly comparable. This structural superimposition or alignment is not an easy task. When the compounds share common scaffold or evident pharmacophoric elements, it is feasible, but when they are structurally diverse or such common features are not that clear, the procedure is difficult and the results are often arbitrary. Moreover, the procedure is difficult to perform in an automatic way and usually requires intensive human intervention that limits the applicability of the method and also the size of the series to be investigated. For these reasons, GRID INdependent Descriptors (GRIND) were suggested as a new generation of MIF-based alignment-independent molecular descriptors, specifically designed to characterize ligand-receptor interactions. 121,122 The GRIND method does not aim to capture all the
In order to efficiently annotate actions in large collections of video or mocap data, some researchers have focused on unsupervised segmentation and clustering of human actions. Barbic et al. [BSP + 04] propose a change detection algorithm for mocap data. They provide accurate results, but their method is not able to cluster the temporal segments into the different behaviors. Ozay et al. [OSC08] overcome the clustering problem by modeling the first three principal components of the data as an autoregressive model. The coefficients of the model are then clustered with k-means. Similarly, the Aligned Cluster Analysis (ACA) proposed by Zhou et al. [ZDH08] extends the k-means concept to cluster time series. They show that ACA can accurately find different behaviors in sequences of mocap data. However, [OSC08] [ZDH08] are limited by having to manually set the number of clusters (actions) k. In [RWS10], this limitation is tackled by using a spike-train driven dynamical model that can detect motion transitions and clusters them into different behaviors, without having to manually set the number of clusters k. As far as video data is concerned, approaches such as [KOSS11][KBvGF10] have proposed variants and extensions of hierarchical Dirichlet processes (HDP) [TJBB06] in order to find activities using optical flow features mainly. In [FSJW08], HDPs are used as a prior for HMM parameters in order to cluster time series data into distinct behaviors. This latter approach is applied to synthetic data, stock indices and dancing honeybee data.
This paper proposes the application of a Bluetooth detection technique (Eagle & Pentland, 2005; Kostakos, O’Neill, Penn, Roussos & Panadongonas, 2010; Delafontaine, Versichele, Neutens & van de Weghe, 2012; Nicolai, Yoneki, Behrens & Kenn, 2006; O’Neill, Kostakos, Kindberg, Sciek, Penn, Fraser & Jones, 2006; Paulos & Goodman, 2004; Versichele, Neutens, Delafontaine, van de Weghe, 2011; Yoshimura, Sobolevsky, Ratti, Girardin, Carrascal, Blat & Sinatra, 2014) to monitor pedestrians’ sequential movements through the shopping area. This technique enables us to generate a large-scale dataset of human mobility at the district scale, because unannounced tracking methodologies makes it possible to collect them during a longer period (i.e., one month) including weekends and special events, which are not included in most of the previous studies. Thus, we try to examine “real and large-scale empirical data” to uncover the pedestrians’ behavioral differences during both sales periods and normal shopping days, in terms of the special trajectory, visited places, and their temporal length of stay in the determined district. This specific application of pedestrian analysis during discount sales makes our research different from the above-mentioned previous studies using a Bluetooth technique. Additionally, this proposed method is different from estimating variables in a model or from validating existing constructed models, based on the collected small-scale samples. Rather, our methodology compensates the modeling approach with different perspectives, shedding light on the significant information about pedestrians’ impulsive behaviors, which the modeling approach cannot disclose.
The second layer in the framework pyramid in can be divided in two. The right side relates to processes that incorporate expert knowledge, namely context analysisand expert system, whereas the left side deals with characterization . Context analysis identifies patterns or structures in the symbolic data (e. g., in/out of bed). Symbolic data relates context analysis with time dimension and routines of the patient (e.g., they get out of bed after 9 AM). Having identified patterns of the patient, their meaning may be determined by including expert knowledge. The expert system is the process that makes the connection between patterns in the symbolic data and expert knowledge (including information about caregivers and persons related to the patient). At this level of abstraction the data conveys information about the daily activities of the patient. The left side of the second layer of the framework pyramid converts symbols for information through characterization. This process typically quantifies certain aspects of the symbolic data. This characterization of activities of the patient can be used to compare the well-being state before and after treatment, or determine the rate of recovery of the patient. The third layer in the information pyramid is concerned with converting information into knowledge. One common way to achieve this is through classification. In this example, one possibility would be to determine whether or not the patient is in good health based on their daily activities. The last layer in the information pyramid transforms knowledge into expertise. One possible way to achieve this is through Data Mining. We have found this work really relevant for our solution, but we believe a higher level platform including other clinical aspects such as specific scales or treatment should also be included in the model in order to provide a full perspective to health professionals in order to perform a proper evaluation of the patient.
One advantage of the work done is that we were able to cope with time by connecting our Bio OntoCAPE with MatLab platform using the java application developed, we were able to simulate patients evolution over time. This is an important issue since we need to know how to construct this kind of biological models but through their computer implementations we are able to predict in certain time horizon the dynamic behavior of the most criti- cal variables. In this context, we have in mind as future work to analyze if it could be necessary to develop a new ontology based on the ideas of  who presented an ontology-based framework to support intelligent data analysis of recorded temporal data. They have shown how a process condition can be inferred when qualita- tive temporal patterns are available. These skills are very useful for doing recommendations each time the patient is out of the healthy range of glycemia. Another possibility is to take into account the work of  who proposed a fuzzy framework for encoding un- certainty in clinical decision-making to analyze insulin dosage and meals and recommend corrections to both.
In the research literature there is a wide variety of task models with different approaches, it is difficult to consider all in order to elaborate a comparative anal- ysis. To generate our meta-model, we consider those that are supported by theoretical studies, accepted within the Human-Computer Interaction community, and are integrated in a development methodology. Task models analyzed in previous sections show a variety of concepts and relationships. Differences between concepts are both syntactic and semantic. Syntactic differences cover differences of vocabulary used for a same concept across models. Semantic differences are related to the conceptual variations across models. Semantic differences can be of major or of minor importance. A major difference consists in the variation of entities or relationships definitions and coverage; for instance, a same concept does not preserve a consistent definition across models. A mi- nor difference consists in the variation of expressing an entity or a relationship. For example, constructors in GTA or TKS express temporal relationship between a task and its subtasks, although the set of construc- tors is not identical in all models, while operators in CTT are used between sibling tasks. After the analysis of those task models, a multi-users interaction meta- model was generated in order to cover the principal characteristics required to work with multiplicity enti- ties playing a role. The meta-model applies to identify how tasks are structured, who perform them, what their relative order is, how they are offered or as- signed, and how tasks are being tracked. Moreover, an editor was developed to put in practice the afore- mentioned model.
Wood is commonly used as building and engineering material. Unprotected wood exposed to outdoor conditions undergoes a variety of degradation reactions induced by diverse factors such as light, moisture, heat, oxygen, pollutants (Evans et al. 1992). Moisture contain promotes the fungal attack and leads to sever destruction of wood. In the past, wood preservation has been carried out by chemical treatments, some of them including components that are poisonous for environment andhuman health. Nowadays, heat treatment of the wood by mild pyrolysis is used as an alternative to chemically impregnated wood materials. It is an effective method to improve biological durability of wood (Finnish Thermowood Association 2003, Momohara et al. 2003, Shi et al. 2007). Wood heat treatment induces chemical modification of main wood constituents. Lignin polymer structure is modified (Zammen et al. 2000, Tjeerdsma and Militz 2005, Nguila et al. 2006, Nguila et al. 2007a, Esteves et al. 2008), the ratio between amorphous and crystalline cellulose is also changed (Fengel and Wegener 1989, Sivonen et al. 2002, Yildiz et al. 2006), hemicelluloses are strongly decomposed (Sivonen et al. 2002, Nuopponen et al. 2004, Gérardin et al. 2007), some products precursors of charcoal appear (Nguila et al. 2007b). These chemical
The flow of gastric contents induced by the propagation of a series of peristaltic antral contractive waves (ACWs) in the distal stomach plays a vital role in the human digestive process. It not only facilitates the mechanical disintegration of food parti- cles, but also enhances their e ffi cient mixing with digestive juices secreted from the stomach wall. Our previous work has shown that computational fluid dynamics (CFD) techniques can be successfully applied to model and simulate ACW-induced flows, and to provide detailed insights into the flow behavior of gastric fluids and pressure distributions developed within a 3D model of a human stomach. In this study, the flow dynamics that develops within the stomach in the case of a mixture of food particles and digestive juices was numerically investigated using the multiphase Euler-Euler model- ing approach provided by ANSYS Fluent.The e ff ects of liquid / solid density di ff erence and particle loading ratio on gastric flow were investigated. Our simulation results show that slight di ff erence in liquid / solid density(5%) and increase in particle loading ratio (10% to 30%) have significant e ff ects on the flow behavior of gastric contents in the stomach. Results from this study illustrates the unique capability of CFD tools to analyze and further advance our understanding of the mechanisms that promotes the digestive process of complex food systems within the stomach.
4. The idea comes from the fact that in editing a survey, we need as much information as possible about the phenomenon that we try to measure. On the other hand, different subsets of data often show a very different variability and behaviour. For example, when editing the Spanish monthly indices of industrial production, we can find extremely small (even zero) production data values for August, because summer holidays are usually taken in this month in Spain. Of course, these data must not be considered as outliers (i.e. suspicious data items) if we have information about this seasonal pattern. But an additional problem is that, this seasonal behaviour in August is very different from one branch to another (even there are branches which production does not decrease but strongly grows in August, as in beer production). For this reason, it is important to acquire information about the different dynamic characteristics of each of the branches to improve editing rules and strategies.
An acoustic signal representation based on sinusoidal and envelope-modulation modeling is described. Such studies are crucial to acoustic events modeling for structured audio-signal representation and rendering through interactive networks. This paper confirmed that; (1) sinusoidal modeling is useful for constructing an intelligible speech using only a few dominant components, (2) envelope modulation modeling enables modification of a talker’s pitch and speech rate without sacrificing intelligibility through use of the simple carriers, and (3) the narrow-band envelope could be also estimated by clustered line- spectrum modeling (CLSM) based on the least square error criterion in the frequency domain.
ABSTRACT. Cavitation noise represents a useful source of information on physical processes accompanying bubble oscillations in liquids. However, to be able to extract this information from measured data, both a suitable mathematical model of cavitation noise and an appropriate method for signal analysis are necessary. In presentation these problems are discussed in detail in view of recent results obtained by the author. Cavitation noise is modeled under assumption that certain parameters controlling the bubble oscillations are random and hence radiated pressure waves, perceived as cavitation noise, may be described as a superposition of nonrandom functions governed by a finite set of random parameters. The mean values of these parameters are obtained from a numerical computation using the Gilmore's model of an oscillating bubble. Cavitation noise model is then used to generate a time series which can be analyzed. The computed autospectral densities are compared with corresponding experimentally determined autospectral densities and inferences on cavitation noise are drawn.
In order to capture the voltage deviation, ac measurement was used. It can be observed that the 7V output is not affected by the load step as predicted by the simulations. The measured voltage deviation in 10.5V module is compared to the simu- lated value as shown in Figure 14. The dashed line shows the simulation result and subsequent to the comparison between measured values, it can be observed that the modeled dc-dc converter predicts well the behavior of the actual converter in a load change situations.
The recording of physiological signals has provided researchers with insight into the relationships between cognition, behavior and physiology. In the neurophysiology area, signals acquired from the scalp are used to identify diseases such as seizure disorders, strokes, brain tumors, head trauma and other physiological problems related to the brain . These signals are called electroencephalographic signals and the complete recording is named Electroencephalogram (EEG). The EEG senses electrical impulses within the brain through electrodes placed on the scalp and records them on paper using an electroencephalograph. Nowadays the technology has replaced the use of paper by digital memories, permitting the storage of the EEG in electronic devices as a data file . This evolution allowed the use of computational tools, such as digital signal processing, to extract information from the EEG data and perform quantitative analysis [3, 4].
Many authors have explored how to control a virtual environment with hands (i.e. PC desktop, 3D model). Such applications involve, in most of the cases, dynamic hand gesturing. In this direction, Soutschek et al. [SPHK08] propose a user interface for the navigation through 3D datasets using a Time-of-Flight (TOF) camera. They perform a polar crop of the hand over a distance threshold to the centroid, and a subsequent NN classification into five hand gestures. With a similar objective, Van den Berg and Van Gool [VV11] improve their work in [VKMBV09] by combining RGB and depth to construct classification vectors. Their alphabet consists of four gestures that enable selecting, rotating, panning and zooming of a 3D model on a screen. Hackenberg et al. [HMB11] estimate hand pose by identifying palm and finger candidates, after a pixel-wise classification into tips and pipes. The final hand structure is obtained with optical flow techniques. Ren et al. [RYZ11] segment the hand under some restrictive assumptions and adapt the Earth Movers Distance to a finger signature, finding the NN according to this metric. Malassiotis and Strintzis [MS08] extract PCA features from depth images of synthetic 3D hand models for training.
environmentally friendly alternatives, providing easy access to major urban joints and alleviating the user from parking worries. On top of that, policymakers are working hard to achieve car-free cities ,  through subsidies and aware- ness campaigns. In spite of these, the shift in the commuting mode is sluggish – and the transportation sector is in desperate need of a game changer. A large section of stakeholders believe that equipping public vehicles with on-board gigabit wireless networks can accelerate the shift considerably. The idea is illustrated in Fig. 1, where the access network forms a two-hop system: base stations (BSs) or road side units (RSUs) serve the vehicular access point (AP) over vehicle-to-infrastructure (V2I) mobile channels, and the vehicular AP connects to the passengers inside over static intravehicular channels. 1 The network architecture helps in avoiding the penetration loss caused by metallic bodies and signaling overhead due to group handovers  experienced in direct outdoor channels. There are many other potential appli- cations of intravehicular wireless signaling beyond user con- nectivity, which include counting the number of passengers in a public vehicle  or establishing a small-scale social networking platform between co-passengers . However, wireless communication infrastructures inside public vehi- cles should be able to provide such on-demand real-time high- data-rate diverse services.
Since the establishment of Participatory Design it has tried to expand in order to try to benefit as many people as possible. And, as a way to reach the most number of people, the business world is ideal as it produces the majority of software out there. The interfusion of these two fields touches a fundamental issue for the future of Participatory Design and its community. Participatory Design positions itself as a relevant aspect for a business as it is a tool to produce better and innovative products for businesses to commercialize. Software development business are told that they need user involvement because they are told by the market that they need to produce better software products. So these two fields seem like they form an obvious benefitting partnership. Yet the reality is that Participatory Design is not being fully adopted by software development companies. They prefer to improve their products through other means or innovate through other aspects. So to be able to see if Participatory Design can become a common tool in today´s modern software development sector we must research this area of study. We must see what shared interest are common to both Business modeling in the software developing sector and Participatory Design, as there is sure to be some common interests parting from the fact that they both wish to produce better products/software. As well as the shared interest we must research the opposing interests and what hinders the total adoption of Participatory Design by business companies. This issue has largely arisen by researchers, such as (Kyng, 2010), pointing out at a gap in Participatory Design study where the politics of a design project are largely ignored. And in this gap lies the adoption of Participatory Design by businesses. In this project we will study this largely unexplored gap pointed out by Kyng, to know how these two fields of study, Participatory Design and business modeling, overlap, as Participatory Design tries to reach towards a business environment. I will find out how PD interacts with the project reality in a business environment. To see if they clash or they cooperate in favor of joint interests.
The contrast of perspectives can be brought out with many different types of illustrations; let me choose a rather harsh example. It is, by now, fairly well established that, given symmetric care, women tend to live longer than men. If one were concerned only with capabilities (and nothing else), and in particular with equality of the capability to live long, it would have been possible to construct an argument for giving men more medical attention than women to counteract the natural masculine handicap. But giving women less medical attention than men for the same health problems would clearly violate an important requirement of process equity, and it seems reasonable to argue, in cases of this kind, that demands of equity in process freedom could sensibly override a single- minded concentration on the opportunity aspect of freedom (and on the requirements of capability equality in particular). While it is important to emphasise the relevance of the capability perspective in judging people’s substantive opportunities (particularly in comparison with alternative approaches that focus on incomes, or primary goods, or resources), that point does not, in any way, go against seeing the relevance also of the process aspect of freedom in a theory of human rights — or, for that matter, in a theory of justice.
For centuries, wood has been widely used as a building material due to its superior properties. When compared with other competitive materials, it offers following advantages: it is a versatile material; it is a naturally renewable resource; it exhibits highly good thermal insulation; it provides a high strength and elasticity despite its low weight; it presents an aesthetic appearance and it is environmentally friendly. Such many factors have made the wood more suitable and more usable as a building material. However, it is worthy to mention that wood suffers from an unfavorable property. It is a highly hygroscopic material, and hence it undergoes shape changes with the fluctuations in relative humidity of the surrounding air (Camille and Kmaid 2005, Gryc et al. 2007).
According to their phylogenetic associations, all putative HPV types identified in the genera Alphapapillomavirus (Fig. 1a) and Betapapillomavirus (Fig. 1b) were segregated inside the defined species. In contrast, only 98 out of the 159 putative types found in the genus Gammapapillomavirus were segregated in the defined species (c-1–c-17) (Fig. 1c, Table 1) (de Villiers, 2013). Moreover, two putative HPV types belonged to a recently identified species (c-18) (Chouhy et al., 2013), and 59 were segregated in 21 unidentified putative species (named c-X1–c-X21) (Fig. 1c, Table 1). In addition, the strain GC03 (Fig. 1) may pro- bably define a new putative species within the genus Mupapillomavirus (69.8 and 68.2 % nucleotide identities with HPV-1a and HPV-63, respectively). Comparative analysis of trees generated by the maximum-likelihood method (RaxML program, evolutionary substitution model set as rtREV+ C +I with fast bootstrap of 1000 replicates) revealed almost the same phylogenetic associations as those obtained by Bayesian analysis (data not shown), further supporting the overall relationships found and the existence of additional undefined putative species within the genera c- PV and m-PV as well. Interestingly, those species of the genera Betapapillomavirus and Gammapapillomavirus con- taining viruses that showed incongruences in the phylogen- etic analysis of the FAP/CUT and MY regions (Fig. S1: b-1, b-2, c-7, c-8, c-10, c-11, c-12) had the greatest number of putative HPV types within both subgenomic regions (FAP/ Fig. 1. Phylogenetic trees of 190 putative HPV types identified in the FAP/CUT region and 33 putative HPV types found in the MY region, and 166 characterized PV types. (a) Genus Alphapapillomavirus. (b) Genus Betapapillomavirus. (c) Genus Gammapapillomavirus: the left part of the tree is indicated as ‘c-Collapsed’ in the right part of the figure and vice versa. Protein sequence-derived nucleotide multiple alignments were performed with MEGA 5 (Tamura et al., 2011), and phylogenetic