Um estudo das modalidades deôntica e volitiva nos discursos do presidente Lula

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An exploration of feature detector performance in the thermal-infrared modality

Thermal-infrared images have superior statistical properties compared with visible-spectrum images in many low-light or no-light scenarios. However, a detailed understanding of feature detector performance in the thermal modality lags behind that of the visible modality. To address this, the first comprehensive study on feature detector performance on thermal-infrared images is conducted. A dataset is presented which explores a total of ten different environments with a range of statistical properties. An investigation is conducted into the effects of several digital and physical image transformations on detector repeatability in these environments. The effect of non-uniformity noise, unique to the thermal modality, is analyzed. The accumulation of sensor non-uniformities beyond the minimum possible level was found to have only a small negative effect. A limiting of feature counts was found to improve the repeatability performance of several detectors. Most other image transformations had predictable effects on feature stability. The best-performing detector varied considerably depending on the nature of the scene and the test.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

The impact of interface modality on police officers' visual behaviour when using an in-vehicle system

Background Standard operating procedures state that police officers should not drive while interacting with their mobile data terminal (MDT) which provides in-vehicle information essential to police work. Such interactions do however occur in practice and represent a potential source of driver distraction. The MDT comprises visual output with manual input via touch screen and keyboard. This study investigated the potential for alternative input and output methods to mitigate driver distraction with specific focus on eye movements. Method Nineteen experienced drivers of police vehicles (one female) from the NSW Police Force completed four simulated urban drives. Three drives included a concurrent secondary task: imitation licence plate search using an emulated MDT. Three different interface methods were examined: Visual-Manual, Visual-Voice, and Audio-Voice (“Visual” and “Audio” = output modality; “Manual” and “Voice” = input modality). During each drive, eye movements were recorded using FaceLAB™ (Seeing Machines Ltd, Canberra, ACT). Gaze direction and glances on the MDT were assessed. Results The Visual-Voice and Visual-Manual interfaces resulted in a significantly greater number of glances towards the MDT than Audio-Voice or Baseline. The Visual-Manual and Visual-Voice interfaces resulted in significantly more glances to the display than Audio-Voice or Baseline. For longer duration glances (>2s and 1-2s) the Visual-Manual interface resulted in significantly more fixations than Baseline or Audio-Voice. The short duration glances (<1s) were significantly greater for both Visual-Voice and Visual-Manual compared with Baseline and Audio-Voice. There were no significant differences between Baseline and Audio-Voice. Conclusion An Audio-Voice interface has the greatest potential to decrease visual distraction to police drivers. However, it is acknowledged that an audio output may have limitations for information presentation compared with visual output. The Visual-Voice interface offers an environment where the capacity to present information is sustained, whilst distraction to the driver is reduced (compared to Visual-Manual) by enabling adaptation of fixation behaviour.

Effect of recovery modality on 4-hour repeated treadmill running performance and changes in physiological variables

The purpose of this study was to compare the effectiveness of three different recovery modalities - active (ACT), passive (PAS) and contrast temperature water immersion (CTW) - on the performance of repeated treadmill running, lactate concentration and pH. Fourteen males performed two pairs of treadmill runs to exhaustion at 120% and 90% of peak running speed (PRS) over a 4-hour period. ACT, PAS or CTW was performed for 15-min after the first pair of treadmill runs. ACT consisted of running at 40% PRS, PAS consisted of standing stationary and CTW consisted of alternating between 60-s cold (10°C) and 120-s hot (42°C) water immersion. Run times were converted to time to cover set distance using critical power. Type of recovery modality did not have a significant effect on change in time to cover 400 m (Mean±SD; ACT 2.7±3.6 s, PAS 2.9±4.2 s, CTW 4.2±6.9 s), 1000 m (ACT 2.2±4.0 s, PAS 4.8±8.6 s, CTW 2.1±7.2 s) or 5000 m (ACT 1.4±29.0 s, PAS 16.7±58.5 s, CTW 11.7±33.0 s). Post exercise blood lactate concentration was lower in ACT and CTW compared with PAS. Participants reported an increased perception of recovery in the CTW compared with ACT and PAS. Blood pH was not significantly influenced by recovery modality. Data suggest both ACT and CTW reduce lactate accumulation after high intensity running, but high intensity treadmill running performance is returned to baseline 4-hours after the initial exercise bout regardless of the recovery strategy employed.

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

Efficiency of lexical access in children with autism spectrum disorders : does modality matter?

The provision of visual support to individuals with an autism spectrum disorder (ASD) is widely recommended. We explored one mechanism underlying the use of visual supports: efficiency of language processing. Two groups of children, one with and one without an ASD, participated. The groups had comparable oral and written language skills and nonverbal cognitive abilities. In two semantic priming experiments, prime modality and prime–target relatedness were manipulated. Response time and accuracy of lexical decisions on the spoken word targets were measured. In the first uni-modal experiment, both groups demonstrated significant priming effects. In the second experiment which was cross-modal, no effect for relatedness or group was found. This result is considered in the light of the attentional capacity required for access to the lexicon via written stimuli within the developing semantic system. These preliminary findings are also considered with respect to the use of visual support for children with ASD.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

Non-parametric consistency test for multiple-sensing-modality data fusion

Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

Modality as portrayed in upper secondary school textbooks : A corpus-based approach

Tämän pro gradu -lopputyön aiheena on englannin kielen modaalisten apuverbien ns. ydinjoukko: will, would, can, could, shall, should, may, might ja must. Semantiikan kannalta nämä apuverbit ovat erityisen kompleksisia: niiden tulkinnassa on usein huomattavaa monivivahteisuutta, vaikka perinteiset kieliopit antavat ymmärtää niillä olevan kaksi tai kolme toisistaan selkeästi erillään olevaa merkitystä. Ne asettavatkin vieraan kielen oppimisympäristössä erityisiä haasteita. Viimeaikainen kehitys korpuslingvistiikan metodeissa on tuottanut entistä tarkempia kuvauksia siitä, miten modaalisia apuverbejä nykyenglannissa käytetään ja mihin suuntaan niiden kehitys on lyhyenkin ajan sisällä kulkenut. Tämän tutkielman tavoitteena on ollut verrata näiden uusien tutkimusten tuloksia siihen todellisuuteen, jonka englannin kielen lukiotasoinen oppimateriaali Suomessa opiskelijalle tarjoaa. Lähdin siitä, että opetussuunnitelman vaatima autenttisuus ja kommunikaativisuus kieltenopetuksessa tulisi näkyä tasapuolisena modaalisten apuverbien kohteluna. Alkuperäinen hypoteesini kuitenkin oli, että siinä miten modaalisuus ilmenee autenttisessa ympäristössä ja siinä miten se esitetään oppikirjoissa, on poikkeavuuksia. Lähestymistapani tähän tutkielmaan oli korpuslähtöinen. Valitsin kahdesta lukion kirjasarjasta ne kirjat, joissa modaaliset apuverbit mainittiin eksplisiittisesti. Skannasin jokaisen neljästä eri kirjasta löytyvän (kokonaisen) tekstin ja rakensin näistä aineksista pienen korpuksen. Tästä korpuksesta hain korpusanalyyseihin tarkoitetulla ohjelmalla kaikki lauseet, joissa esiintyi modaalisia apuverbejä. Tämän jälkeen analysoin jokaisen modaalisen apuverbin semanttisesti lauseyhteydessään. Tämän analyysin tuloksena pystyin rakentamaan taulukoita ja vertailemaan tuloksia uusimpien tutkimusten tuloksiin. Tämän tutkielman perusteella poikkeavuuksia on olemassa. Yleisesti ottaen modaalisten apuverbien keskinäinen frekvenssi oli oikean suuntainen: mitään apuverbiä ei ollut käytetty merkittävästi enemmän tai vähemmän kuin mitä viimeaikaisen tutkimuksen valossa olisi suotavaa. Sen sijaan apuverbien semanttisessa jakaumassa oli paikoin suuriakin eroja siinä, mitkä merkitykset oppikirjoissa painottuivat ja mitkä taas nykyenglannissa vaikuttaisivat olevan frekvensseiltään suurempia. Erityisesti can ja must erottuivat joukosta siinä, että oppikirjojen tarjoama kuva niiden käytöstä on päinvastainen kuin mitä voisi odottaa: can-verbin käyttö painottui selvästi tarkoittamaan ’kykyä’ eikä ’mahdollisuutta’, joka nykytutkimuksen valossa on sen pääasiallinen käyttötapa. Toisaalta must tarkoitti aineistossa ylikorostuneesti ’pakkoa’, kun se useimmiten nykyään tarkoittaa yhtä usein ’johtopäätöstä’ kuin ’pakkoa’. Lisäksi ’lupaa’ pyydettiin aineistossa merkillisen harvoin. Tulosten perusteella esitän, että oppikirjojen tekijät yleisellä tasolla luopuisivat kielioppikirjojen luutuneista käsityksistä ja uskaltaisivat altistaa opiskelijat koko modaalisten apuverbien merkityskirjolle.

Which patients with chronic kidney disease have the greatest symptom burden? A comparative study of advanced CKD stage and dialysis modality

Background Chronic kidney disease (CKD) leads to a range of symptoms, which are often under-recognised and little is known about the multidimensional symptom experience in advanced CKD. Objectives To examine (1) symptom burden at CKD stages 4 and 5, and dialysis modalities, and (2) demographic and renal history correlates of symptom burden. Methods Using a cross-sectional design, a convenience sample of 436 people with CKD was recruited from three hospitals. The CKD Symptom Burden Index (CKD-SBI) was used to measure the prevalence, severity, distress and frequency of 32 symptoms. Demographic and renal history data were also collected. Results Of the sample, 75.5 % were receiving dialysis (haemodialysis, n = 287; peritoneal dialysis, n = 42) and 24.5 % were not undergoing dialysis (stage 4, n = 69; stage 5, n = 38). Participants reported an average of 13.01 ± 7.67 symptoms. Fatigue and pain were common and burdensome across all symptom dimensions. While approximately one-third experienced sexual symptoms, when reported these symptoms were frequent, severe and distressing. Haemodialysis, older age and being female were independently associated with greater symptom burden. Conclusions In CKD, symptom burden is better understood when capturing the multidimensional aspects of a range of physical and psychological symptoms. Fatigue, pain and sexual dysfunction are key contributors to symptom burden, and these symptoms are often under-recognised and warrant routine assessment. The CKD-SBI offers a valuable tool for renal clinicians to assess symptom burden, leading to the commencement of timely and appropriate interventions.

Unconstrained monocular 3D human pose estimation by action detection and cross-modality regression forest

This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.