Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

The terrestrial Gastropoda Megalobulimus abbreviatus as a useful model for nociceptive experiments: effects of morphine and naloxone on thermal avoidance behavior

We describe the behavior of the snail Megalobulimus abbreviatus upon receiving thermal stimuli and the effects of pretreatment with morphine and naloxone on behavior after a thermal stimulus, in order to establish a useful model for nociceptive experiments. Snails submitted to non-functional (22ºC) and non-thermal hot-plate stress (30ºC) only displayed exploratory behavior. However, the animals submitted to a thermal stimulus (50ºC) displayed biphasic avoidance behavior. Latency was measured from the time the animal was placed on the hot plate to the time when the animal lifted the head-foot complex 1 cm from the substrate, indicating aversive thermal behavior. Other animals were pretreated with morphine (5, 10, 20 mg/kg) or naloxone (2.5, 5.0, 7.5 mg/kg) 15 min prior to receiving a thermal stimulus (50ºC; N = 9 in each group). The results (means ± SD) showed an extremely significant difference in response latency between the group treated with 20 mg/kg morphine (63.18 ± 14.47 s) and the other experimental groups (P < 0.001). With 2.5 mg/kg (16.26 ± 3.19 s), 5.0 mg/kg (11.53 ± 1.64 s) and 7.5 mg/kg naloxone (7.38 ± 1.6 s), there was a significant, not dose-dependent decrease in latency compared to the control (33.44 ± 8.53 s) and saline groups (29.1 ± 9.91 s). No statistically significant difference was found between the naloxone-treated groups. With naloxone plus morphine, there was a significant decrease in latency when compared to all other groups (minimum 64% in the saline group and maximum 83.2% decrease in the morphine group). These results provide evidence of the involvement of endogenous opioid peptides in the control of thermal withdrawal behavior in this snail, and reveal a stereotyped and reproducible avoidance behavior for this snail species, which could be studied in other pharmacological and neurophysiological studies.

Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.

Modelling Cutting States in Rough Turning of 34CrNiMo6 Steel

Rough turning is an important form of manufacturing cylinder-symmetric parts. Thus far, increasing the level of automation in rough turning has included process monitoring methods or adaptive turning control methods that aim to keep the process conditions constant. However, in order to improve process safety, quality and efficiency, an adaptive turning control should be transformed into an intelligent machining system optimizing cutting values to match process conditions or to actively seek to improve process conditions. In this study, primary and secondary chatter and chip formation are studied to understand how to measure the effect of these phenomena to the process conditions and how to avoid undesired cutting conditions. The concept of cutting state is used to address the combination of these phenomena and the current use of the power capacity of the lathe. The measures to the phenomena are not developed based on physical measures, but instead, the severity of the measures is modelled against expert opinion. Based on the concept of cutting state, an expert system style fuzzy control system capable of optimizing the cutting process was created. Important aspects of the system include the capability to adapt to several cutting phenomena appearing at once, even if the said phenomena would potentially require conflicting control action.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

Analysis of heart rate control to assess thermal sensitivity responses in Brazilian toads

In anurans, changes in ambient temperature influence body temperature and, therefore, energy consumption. These changes ultimately affect energy supply and, consequently, heart rate (HR). Typically, anurans living in different thermal environments have different thermal sensitivities, and these cannot be distinguished by changes in HR. We hypothesized that Rhinella jimi (a toad from a xeric environment that lives in a wide range of temperatures) would have a lower thermal sensitivity regarding cardiac control than R. icterica (originally from a tropical forest environment with a more restricted range of ambient temperatures). Thermal sensitivity was assessed by comparing animals housed at 15° and 25°C. Cardiac control was estimated by heart rate variability (HRV) and heart rate complexity (HRC). Differences in HRV between the two temperatures were not significant (P=0.214 for R. icterica and P=0.328 for R. jimi), whereas HRC differences were. All specimens but one R. jimi had a lower HRC at 15°C (all P<0.01). These results indicate that R. jimi has a lower thermal sensitivity and that cardiac control is not completely dependent on the thermal environment because HRC was not consistently different between temperatures in all R. jimi specimens. This result indicates a lack of evolutive trade-offs among temperatures given that heart rate control at 25°C is potentially not a constraint to heart rate control at 15°C.

Antioxidant activity of rosemary and oregano ethanol extracts in soybean oil under thermal oxidation

Four experiments were conducted to measure the antioxidant activity of ethanol extracts of rosemary and oregano compared with synthetic antioxidants such as TBHQ and BHA/BHT. The antioxidant activity was determined and results differed from those of the Oven test at 63º C. Peroxide values and absorptivities at 232 nm of soybean oil under Oven test were lower in treatments with 25, 50, 75, 100 and 200 mg.Kg-1 TBHQ than in treatments with 1000 mg.Kg-1 oregano extract (O), 500 mg.Kg-1 rosemary extract (R) and their mixture R+O. All the treatments were effective in controlling the thermal oxidation of oils; the natural extracts were as effective as BHA+BHT and less effective than TBHQ. The natural extracts were mixed with 25, 50, 75 and 100 mg.Kg-1 TBHQ and then added to the oil. No improvement in antioxidative properties was observed. The best antioxidant concentration could be determined from polynomial regression and quadratic equation from the experimental data.

Mathematical modelling of the osmotic dehydration of cherry tomato (Lycopersicon esculentum var. cerasiforme)

Osmotic dehydration of cherry tomato as influenced by osmotic agent (sodium chloride and a mixed sodium chloride and sucrose solutions) and solution concentration (10 and 25% w/w) at room temperature (25°C) was studied. Kinetics of water loss and solids uptake were determined by a two parameter model, based on Fick's second law and applied to spherical geometry. The water apparent diffusivity coefficients obtained ranged from 2.17x10-10 to 11.69x10-10 m²/s.

Modelling Energy Consumption of a Switch using Fuzzy-Rule Classifier

The energy consumption of IT equipments is becoming an issue of increasing importance. In particular, network equipments such as routers and switches are major contributors to the energy consumption of internet. Therefore it is important to understand how the relationship between input parameters such as bandwidth, number of active ports, traffic-load, hibernation-mode and their impact on energy consumption of a switch. In this paper, the energy consumption of a switch is analyzed in extensive experiments. A fuzzy rule-based model of energy consumption of a switch is proposed based on the result of experiments. The model can be used to predict the energy saving when deploying new switches by controlling the parameters to achieve desired energy consumption and subsequent performance. Furthermore, the model can also be used for further researches on energy saving techniques such as energy-efficient routing protocol, dynamic link shutdown, etc.

Permanent magnet synchronous generator design solution for large directdrive wind turbines: Thermal behavior of the LC DD-PMSG

Wind is one of the most compelling forms of indirect solar energy. Available now, the conversion of wind power into electricity is and will continue to be an important element of energy self-sufficiency planning. This paper is one in a series intended to report on the development of a new type of generator for wind energy; a compact, high-power, direct-drive permanent magnet synchronous generator (DD-PMSG) that uses direct liquid cooling (LC) of the stator windings to manage Joule heating losses. The main param-eters of the subject LC DD-PMSG are 8 MW, 3.3 kV, and 11 Hz. The stator winding is cooled directly by deionized water, which flows through the continuous hollow conductor of each stator tooth-coil winding. The design of the machine is to a large degree subordinate to the use of these solid-copper tooth-coils. Both steady-state and timedependent temperature distributions for LC DD-PMSG were examined with calculations based on a lumpedparameter thermal model, which makes it possible to account for uneven heat loss distribution in the stator conductors and the conductor cooling system. Transient calculations reveal the copper winding temperature distribution for an example duty cycle during variable-speed wind turbine operation. The cooling performance of the liquid cooled tooth-coil design was predicted via finite element analysis. An instrumented cooling loop featuring a pair of LC tooth-coils embedded in a lamination stack was built and laboratory tested to verify the analytical model. Predicted and measured results were in agreement, confirming the predicted satisfactory operation of the LC DD-PMSG cooling technology approach as a whole.

Theoretical modelling of Staphylococcus aureus growth in a cooked meat product kept at ambient temperature using temperature profiles of selected Mexican cities

A theoretical model is used to predict the growth of Staphylococcus aureus in a pasteurized meat product kept at ambient temperatures for several hours. For this purpose, the temperature profiles of some cities of Mexico were combined with literature data on the kinetics of S. aureus growth. As shown by theoretical predictions, if the food is kept at ambient temperature, the average daily temperature may not give accurate predictions.

The effect of irradiation and thermal process on beef heme iron concentration and color properties

The aim of this study was to evaluate the influence of irradiation and thermal process on the heme iron (heme-Fe) concentration and color properties of Brazilian cattle beef. Beef samples (patties and steaks) were irradiated at 0-10 kGy and cooked in a combination oven at 250 ºC for 9 minutes with 70% humidity. Total iron and heme iron (heme-Fe) concentrations were determined. The data were compared by multiple comparisons and fixed- effects ANOVA. Irradiation at doses higher than 5 kGy significantly altered the heme-Fe concentration. However, the sample preparation conditions interfered more in the heme-Fe content than did the irradiation. Depending on the animal species, meat heme iron levels between 35 and 52% of the total iron are used for dietetic calculations. In this study the percentage of heme-iron was, on average, 70% of the total iron showing that humidity is an important factor for its preservation. The samples were analyzed instrumentally for CIE L*, a*, and b* values.

Changes in guava (Psidium guajava L. var. Paluma) nectar volatile compounds concentration due to thermal processing and storage

Guava nectars were formulated for approximately 10, 12, or 14 ºBrix, with 40% guava pulp. Sodium benzoate, 500 mg.kg-1 was used as preservative. The Brix value was adjusted with saturated sucrose syrup. The guava nectar was pasteurized (85 ºC/42 seconds) in tubular heat exchanger and then hot filled in 500 mL white glass bottles. The products were stored either at room temperature (25 ± 5 ºC) or refrigerated (5 ± 2 ºC) under fluorescent light exposure and analyzed on the day after processing (time zero) and also 40, 80, and 120 days of storage. Eight compounds were identified and quantified by Gas Chromatography (GC) -Mass Spectrometry (MS): hexanal, (E)-hex-2-enal, 1-hexenol, (Z)-hex-3-enol, (Z)-hex-3-enyl acetate, phenyl-3-propyl acetate, cinnamyl acetate, and acetic acid. There was no significant effect of thermal treatment on the volatile compound concentrations, except for a significant decrease (p = 0.0001) in hexanal and (Z)-hex-3-enyl acetate (p = 0.0029). As for the storage time, there was a much greater decrease in the esters contents, such as (Z)-hex-3-enyl and phenyl-3-propyl acetates. Cinnamyl acetate had the greatest decrease over storage time. Refrigeration was better than room temperature for guava nectar volatile compounds stability over storage time, mainly for esters compounds, which are important for the product aroma and flavor

Processing of Brazil-nut flour: characterization, thermal and morphological analysis

The Brazil nut (Bertholletia excelsea H. B. K.) is noteworthy for its high content of lipids and proteins of elevated biological value and these factors justify the need for further research and incentives for the manufacturing of new trade products. In the present study we sought new forms of technological use of these nuts by the food industry, through their processing as flour, with no alteration in its energy content. The results after its elaboration showed a product with high energy value (431.48 kcal.100 g-1), protein content of 45.92 g.100 g-1, and fiber of 17.14%. The thermal analyses indicate that the introduction of another protein component, such as soy protein isolate, does not alter the reactions or thermal behavior. On the other hand, morphological analyses revealed granular structures similar to the structure of globular proteins. It was observed that after processing to obtain the flour, the product maintains its protein-energy content, as well as its characteristics when subjected to high temperatures.