Temporal Information Extraction

Comparison of the spatial and temporal information retrieved from near-infrared phase and average intensity (DC) data reveals that these data types can play a complementary role in the study of the temporal and spatial features of the optical response associated with brain activation during a finger-tapping test. The optical data have been collected with a frequency-domain tissue imager at two wavelengths (690 and 830 nm) and have been analyzed using standard filtering and folding-average procedures. DC and phase data show different temporal and spatial features. A plausible explanation of the different behavior of DC and phase data has been attempted by using Monte Carlo simulations.

While the presence of uncertainty in the geometric and attribute aspects of geographic information is well known, it is also present in temporal information. In spatiotemporal GIS databases and other formal representations, uncertainty in all three aspects of geography (space, time, and theme) must often be modeled, but a good data model must first be based on a sound theoretical understanding of spatiotemporal uncertainty. The nature of both uncertainty inherent in a phenomenon (often termed indeterminacy) and uncertainty in assertions of that phenomenon can be better understood through the Uncertain Temporal Entity Model, which characterizes the cause, type, and form of uncertainties in the spatial, temporal, and attribute aspects of geographic information. These uncertainties are the result of complexities and problems in two processes: the process of conceptualization, by which humans make sense of an infinitely complex reality, and measurement, by which we create formal representations (e.g. GIS) of those conceptual models of reality. Based on this framework, the nature and form of uncertainty is remarkably consistent across various situations, and is approximately equivalent in the three aspects, which will enable consistent solutions for representation and processing of spatiotemporal data. of applications, especially in education and research in history, geography, and other disciplines.

We present two different change detection techniques to monitor surface changes that occurred at the Rocky Flats nuclear weapons facility located immediately to the North West of the city of Denver, Colorado, USA. The site started being cleaned up and dismantled in 1998 and was completed in 2005.

The fast update rate and good performance of new generation electronic sector scanning sonars is now allowing practicable use of temporal information for signal processing tasks such as object classification and motion estimation. Problems remain, however, as objects change appearance, merge, maneuver, move in and out of the field of view, and split due to poor segmentation. This paper presents an approach to the segmentation, two-dimensional motion estimation, and subsequent tracking of multiple objects in sequences of sector scan sonar images. Applications such as ROV obstacle avoidance, visual servoing, and underwater surveillance are relevant. Initially, static and moving objects are distinguished in the sonar image sequence using frequency-domain filtering. Optical flow calculations are then performed on moving objects with significant size to obtain magnitude and direction motion estimates. Matches of these motion estimates, and the future positions they predict, are then used as a basis for identifying corresponding objects in adjacent scans. To enhance robustness, a tracking tree is constructed storing multiple possible correspondences and cumulative confidence values obtained from successive compatibility measures. Deferred decision making is then employed to enable best estimates of object tracks to be updated as subsequent scans produce new information. The method is shown to work well, with good tracking performance when objects merge, split, and change shape. The optical flow is demonstrated to give position prediction errors of between 10 and 50 cm (1%-5% of scan range), with no violation of smoothness assumptions using sample rates between 4 and 1 frames/s.

We propose a novel solution to the email classification problem: the integration of temporal information with the traditional content-based classification approaches. We discover temporal relations in an email sequence in the form of temporal sequential patterns and embed the discovered information into contentbased learning methods. The new heterogeneous classification system shows a good performance reducing the classification error by up to 22%.

lnIbrmation on various agricultural resource parameters at various levels is essential for proper management and efficient resource allocation for sustainable agricultural development. Limitations in ground-based method have encouraged the use of satellite data coupled with geographical information system (GIS) in providing spatial as well as temporal information over large and inaccessible areas. In the present study, an attempt has been made to generate raster maps using remote sensing and GIS techniques to characterize the agroecosystem of South 24 Paraganas district of West Bengal, based on land utilization indices. Information on multi-season landcover derived from the analysis of the multi-temporal RADARSAT-1 SAR and 1RS-ID LISS III data as well as other ancillary information in GIS environment are the basic inputs used in the study. The present analysis shows that northern and northwestern parts are more diverse in terms of agricultural intensification as compared to the southern and northeastern pans whereas the central parts show moderate density. In terms of carrying capacity, the high carrying capacity has been observed in the southern to northeastern parts whereas the northwestern and central parts show moderate and northern parts show low carrying capacity. Overall, the characterization of agroecosystem using land utilization indices can be identified as major input to formulate a management plan for sustainable agriculture with concerns for the environment.

Super-resolution enhancement techniques may be used sequence move with subpixel increments. A Bayesian multito estimate a high-resolution still from several low-resoluframe enhancement algorithm is presented to compute an tion video frames, provided that objects within the image HRVS using the spatial information present within each frame sequence move with subpixel increments . To properly as well as the temporal information present due to object motion incorporate temporal correlations into the multiframe obbetween frames. However, the required subpixel-resolution moservation model, high-quality subpixel motion vectors must tion vectors must be estimated from low-resolution and noisy be estimated between video frames . Methods for video frames, resulting in an inaccurate motion field which can adversely impact the quality of the enhanced image. Several attaining subpixel accuracy generally employ an interpolasubpixel motion estimation techniques are incorporated into tion of the image sequence frames, followed by the applicathe Bayesian multiframe enhancement algorithm to determine tion of a parametric or nonparametric motion estimation their efficacy in the presence of global data transformations scheme. The accuracy of the estimated motion fields has between frames (i.e., camera pan, rotation, tilt, and zoom) and a direct influence on the quality of the high-resolution independent object motion. Visual and quantitative comparivideo still (HRVS) image.

The widespread proliferation of wireless networks (WLAN) has opened up new paradigms of security policy management in enterprise networks. To enforce the organizational security policies in wireless local area networks (WLANs), it is required to protect the network resources from unauthorized access. In WLAN security policy management, the standard IP based access control mechanisms are not sufficient to meet the organizational requirements due to its dynamic topology characteristics. In such dynamic network environments, the role-based access control (RBAC) mechanisms can be deployed to strengthen the security perimeter over the network resources. Further, there is a need to incorporate time and location dependent constraints in the access control models. In this paper, we propose a WLAN security management system which supports a spatio-temporal RBAC (STRBAC) model. The system stems from logical partitioning of the WLAN topology into various security policy zones. It includes a Global Policy Server (GPS) that formalizes the organizational access policies and determines the high level policy configurations for different policy zones; a Central Authentication & Role Server (CARS) which authenticates the users (or nodes) and the access points (AP) in various zones and also assigns appropriate roles to the users. Each policy zone consists of an Wireless Policy Zone Controller (WPZCon) that co-ordinates with a dedicated Local Role Server (LRS) to extract the low level access configurations corresponding to the zone access points. We also propose a formal spatio-temporal RBAC (STRBAC) model to represent the security policies formally.

... sucessful, it has two main drawbacks: heavy computational load and warping of forgeries. ... of the dynamical system at time , the function represents the state change of dynamical ... generated from input handwriting time series (test sample) and enrollment handwriting time series ...

We investigated whether the effect of covert attention on information accrual varies with eccentricity (4°vs 9°) and the complexity of the visual search task (feature vs conjunction). We used speed-accuracy tradeoff procedures to derive conjoint measures of the speed of information processing and accuracy in each search task. Information processing was slower with more complex conjunction searches than with simpler feature searches, and overall it was faster at peripheral (9°) than parafoveal (4°) locations in both search types. Covert attention increased discriminability and accelerated information accrual at both eccentricities, and the magnitude of this attentional effect was the same for both feature (simple) and conjunction (complex) searches. Interestingly, in contrast to the compensatory effect of covert attention on information processing at iso-eccentric locations (temporal performance fields), covert attention did not eliminate speed differences across eccentricity.

Metadata interoperability is crucial for various kinds of surveillance applications and systems, e.g. metadata mining in multi-sensor environments, metadata exchange in networked camera systems or information fusion in multi-sensor and multi-detector environments. Different metadata formats have been proposed to foster metadata interoperability, but they show significant limitations. ViPER, CVML and MPEG Visual Surveillance MAF support only the visual modality, CVML's

In the present study, Karso watershed of Hazaribagh, Jharkhand State, India was divided into 200 × 200 grid cells and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion prone areas of watershed for prioritization purpose. Average annual sediment yield data on grid basis was estimated using Universal Soil Loss Equation (USLE). In general, a major limitation in the use of hydrological models has been their inability to handle the large amounts of input data that describe the heterogeneity of the natural system. Remote sensing (RS) technology provides the vital spatial and temporal information on some of these parameters. A recent and emerging technology represented by Geographic Information System (GIS) was used as the tool to generate, manipulate and spatially organize disparate data for sediment yield modeling. Thus, the Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data to the erosion model, while the USLE was used to predict the spatial distribution of the sediment yield on grid basis. The deviation of estimated sediment yield from the observed values in the range of 1.37 to 13.85 percent indicates accurate estimation of sediment yield from the watershed.

—This paper deals with a video content classification based on spatial and temporal information. The main goal of the paper is to find out whether the non-expert test subjects are able to correctly recognize the spatial and temporal information and how precise is the corresponding parameterization of video content based on these two attributes. Moreover, how well do the objective values provided by the tool deployed in this experiment correlate with the subjective ones. The subjective measurement has shown that the non-expert test subjects are able to correctly recognize the spatial and temporal information only for the extreme scenes in terms of the spatial and temporal information but have experienced some problems when it comes to a more granular classification. When it comes to the objective assessment, the SI and TI values provided by the tool used in this experiment correlate quite well with the subjective data obtained from the basic test for the spatial information.

Although Geographic Information Systems (GIS) have been recognised as the most advanced technology for the management of geospatial information, they are still unable to efficiently manage the temporal dimension. Originally this problem affected only the study and analysis of highly dynamic phenomena. Today's expansion of GIS technology, the ease to acquire and store geospatial data and the increased capacity of computing technologies to manage large amount of data have contributed to the propagation of this problem across the whole geospatial sector. The extended use of GIS in decision-making processes is increasing the demand for tools able to manage and to analyse dynamic geospatial phenomena where the temporal dimension is crucial. The only temporal model available in commercial GIS packages is based on discretisation of temporal data. Changes are represented as a succession of snapshots. The dynamics and what happens between those stages are not registered. In addition, this approach presents severe problems due to unavoidable multiplication of data volume, abundant redundancies, loss in query efficiency and the impossibility of knowing when the exact timing of changes occurs. Since the late 1980s and particularly in the 1990s, researching the temporal changes and the conceptual and technological options available has been undertaken by the GIS and DBMS sectors. The primary objective of the research presented in this paper is the development of a model for the integration of temporal data with GIS. The method adopted to achieve this objective is based on the combination of Time Geography principles, its graphic language and dynamic segmentation techniques used in GIS. Past research has demonstrated that the difficulty to integrate time with GIS has its origin in the continuous nature of time. Dynamic segmentation in GIS network analysis has the potential to provide the means for a time-GIS integration in a continuous manner. Lifelines, one of the main Time geography's graphic language elements, has been modelled as a set of network segments where the dynamics in attribute information has been attached to different time segments rather than distance segments (for example Euclidean or cost-based) as normally occurs in dynamic segmentation. This paper summarises initial findings of the project. These outcomes have the potential to improve the way the geospatial sector currently handles temporal information. However, the static nature of current GIS technology impedes an appropriate visualisation of dynamic temporal phenomena. To this effect, the paper also explores the possibilities offered by multimedia techniques as a complement to GIS capabilities.

This article tries to explain our rule-based Arabic Named Entity recognition (NER) and classification system. It is based on lists of classified proper names (PN) and particularly on syntactico-semantic
patterns resulting in fine classification of Arabic NE. These patterns use syntactico-semantic combination of morpho-syntactic and syntactic entities. It also uses lexical classification of trigger words and NE
extensions. These linguistic data are essential not only to name entity extraction but also to the taxonomic classification and to determining the NE frontiers. Our method is also based on the contextualisation and
on the notion of NE class attributes and values. Inspired from X-bar theory and immediate constituents, we built a rule-based NER system composed of five levels of syntactico-semantic combination. We also show how the fine NE annotations in our system output (XML database) is exploited in information retrieval and information extraction.

Behavioral studies have provided evidence that the processing of a musical target is faster and more accurate when it is harmonically related to the preceding prime context. We investigated the neural correlates of processing related and unrelated musical targets that were presented at the end of musical sequences. Participants were scanned with functional magnetic resonance imaging (fMRI) while performing speeded intonation judgments (consonant versus dissonant) on the target chords. Behavioral results acquired in the scanner replicated the facilitation effect of related over unrelated consonant targets. The overall activation pattern associated with target processing showed commonalities with networks previously described for target detection and novelty processing. The blood oxygen level-dependent (BOLD) signal linked to target processing revealed activation of bilateral inferior frontal regions (i.e. inferior frontal gyrus, frontal operculum, insula) that was stronger for unrelated than for related targets. We discuss our results with regard to the role of these areas in the processing and integration of temporal information.  (B. Tillmann).

The global environmental change research community requires improved and up-to-date land use/land cover (LULC) datasets at regional to global scales to support a variety of science and policy applications. Considerable strides have been made to improve large-area LULC datasets, but little emphasis has been placed on thematically detailed crop mapping, despite the considerable influence of management activities in the cropland sector on various environmental processes and the economy. Time-series MODIS 250 m Vegetation Index (VI) datasets hold considerable promise for large-area crop mapping in an agriculturally intensive region such as the U.S. Central Great Plains, given their global coverage, intermediate spatial resolution, high temporal resolution (16-day composite period), and cost-free status. However, the specific spectraltemporal information contained in these data has yet to be thoroughly explored and their applicability for large-area crop-related LULC classification is relatively unknown. The objective of this research was to investigate the general applicability of the time-series MODIS 250 m Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) datasets for crop-related LULC classification in this region. A combination of graphical and statistical analyses were performed on a 12-month time-series of MODIS EVI and NDVI data from more than 2000 cropped field sites across the U.S. state of Kansas. Both MODIS VI datasets were found to have sufficient spatial, spectral, and temporal resolutions to detect unique multi-temporal signatures for each of the region's major crop types (alfalfa, corn, sorghum, soybeans, and winter wheat) and management practices (double crop, fallow, and irrigation). Each crop's multi-temporal VI signature was consistent with its general phenological characteristics and most crop classes were spectrally separable at some point during the growing season. Regional intra-class VI signature variations were found for some crops across Kansas that reflected the state's climate and planting time differences. The multi-temporal EVI and NDVI data tracked similar seasonal responses for all crops and were highly correlated across the growing season. However, differences between EVI and NDVI responses were most pronounced during the senescence phase of the growing season.

This article describes a general framework for detecting sleepiness states on the basis of prosody, articulation, and speech-quality-related speech characteristics. The advantages of this automatic real-time approach are that obtaining speech data is nonobstrusive and is free from sensor application and calibration efforts. Different types of acoustic features derived from speech, speaker, and emotion recognition were employed (frame-level-based speech features). Combing these features with high-level contour descriptors, which capture the temporal information of frame-level descriptor contours, results in 45,088 features per speech sample. In general, the measurement proceß follows the speech-adapted steps of pattern recognition: (1) recording speech, (2) preproceßing, (3) feature computation (using perceptual and signal-proceßing-related features such as, e.g., fundamental frequency, intensity, pause patterns, formants, and cepstral coefficients), (4) dimensionality reduction, (5) claßification, and (6) evaluation. After a correlation-filter-based feature subset selection employed on the feature space in order to find most relevant features, different claßification models were trained. The best model—namely, the support-vector machine—achieved 86.1% claßification accuracy in predicting sleepineß in a sleep deprivation study (two-claß problem, N 5 12; 01.00-08.00 a.m.).

Expression profiles of developmental genes in Dictyostelium were determined on microarrays during development of wild type cells and mutant cells lacking either the DNA binding protein GBF or the signaling protein LagC. We found that the mutant strains developed in suspension with added cAMP expressed the pulse-induced and early adenylyl cyclase (ACA)-dependent genes, but not the later ACA-dependent, post-aggregation genes. Since expression of lagC itself is dependent on GBF, expression of the post-aggregation genes might be controlled only by signaling from LagC. However, expression of lagC in a GBF-independent manner in a gbfA− null strain did not result in expression of the post-aggregation genes. Since GBF is necessary for accumulation of LagC and both the DNA binding protein and the LagC signal transduction pathway are necessary for expression of post-aggregation genes, GBF and LagC form a feed-forward loop. Such network architecture is a common motif in diverse organisms and can act as a filter for noisy inputs. Breaking the feed-forward loop by expressing lagC in a GBF-independent manner in a gbfA+ strain does not significantly affect the patterns of gene expression for cells developed in suspension with added cAMP, but results in a significant delay at the mound stage and asynchronous development on solid supports. This feed-forward loop can integrate temporal information with morphological signals to ensure that post-aggregation genes are only expressed after cell contacts have been made.

The Ethiopian Rift System consists of basins that are in different stages of evolution. Some of the rift-related basins in southwestern Ethiopia are half-grabens that have not evolved to symmetrical rifts since the initiation of rifting here in the middle Miocene. These basins contain fossiliferous Pliocene-Pleistocene volcaniclastic sediments and volcanic rocks and have been occupied by early hominid populations. The Afar and the Main Ethiopian Rifts are symmetrical, with both margins fully developed. Several paleoanthropological localities, ranging in age from the Quaternary to the Pliocene, were discovered within these rift basins. The discovery of Australopithecus afarensis (the "Lucy" species) at Hadar and Ardipithecus ramidus and Australopithecus garhi in the Middle Awash makes the region the most prolific early hominid area in the world.

This paper presents a geo-temporal gazetteer Web service that provides access to names of places and historical periods, together with the associated geo-temporal information. Within the DIGMAP project, this gazetteer serves as the unified repository of geographic and temporal information, assisting in the mining of geo-temporal expressions over text, as well as in resource searching and indexing. We describe the data integration methodology and some of the applications that use the gazetteer. Initial evaluation results ...

The Geosciences and Geography are not just yet another application area for semantic technologies. The vast heterogeneity of the involved disciplines ranging from the natural sciences to the social sciences introduces new challenges in terms of interoperability. Moreover, the inherent spatial and temporal information components also require distinct semantic approaches. For these reasons, geospatial semantics, geo-ontologies, and semantic interoperability have

The present paper reports on an end-to-end application using a deep processing grammar to extract spatial and temporal information of prepositional and adverbial expressions from running text. The extraction process is based on the full understanding of the input text. It is represented in a formalism standard for unification-based grammars and with a language-independent vocabulary as far as spatiotemporal information is concerned. The latter feature in principle allows portability of the extraction algorithm across ...

The purpose of the study is to demonstrate that correlation and spectral analyses can contribute to the regional study of a large karst aquifer. An example is presented for the La Rochefoucauld karst aquifer (Charente, France). Different types of spatially distributed time series provide valuable spatio-temporal information for the karst aquifer. The available time series consist of the spring flow rates, the flow rates at different locations in sinking streams, the piezometric levels, the electrical conductivity and temperature of the water, the atmospheric pressure and the precipitation, The analysis of the flow rates at the springs shows that the aquifer empties very slowly and has a large storage capacity. Hydrodynamic links were established between three of the four rivers flowing on the aquifer and the springs. The results also demonstrate the important spatial heterogeneity of the aquifer and indicate that the most rapid flow occurs in the northern part of the aquifer. Hourly piezometric and electrical conductivity time series indicate that the transmissivity of the aquifer varies when some conductive channels become desaturated during the low water period. The delays between the distributed recharge and the piezometric level, between the localized river input and the flow rates at the springs and between the electrical conductivities in rivers and the main spring provide information on the travel times in the aquifer. The observation of earth tides and barometric effects indicate that this apparently unconfined aquifer has a confined behaviour.

The Geosciences and Geography are not just yet another application area for semantic technologies. The vast heterogeneity of the involved disciplines ranging from the natural sciences to the social sciences introduces new challenges in terms of interoperability. Moreover, the inherent spatial and temporal information components also require distinct semantic approaches. For these reasons, geospatial semantics, geo-ontologies, and semantic interoperability have been active research areas over the last 20 years. The geospatial semantics community has been among the early adopters of the Semantic Web, contributing methods, ontologies, use cases, and datasets. Today, geographic information is a crucial part of many central hubs on the Linked Data Web. In this editorial, we outline the research field of geospatial semantics, highlight major research directions and trends, and glance at future challenges. We hope that this text will be valuable for geoscientists interested in semantics research as well as knowledge engineers interested in spatiotemporal data.

In this research, community level spatial models were developed for determining mosquito abundance and environmental factors that could aid in the risk prediction of West Nile virus (WNv) outbreaks. Adult Culex pipiens and Culex restuan mosquitoes and multiple habitat covariates were collected from nine sites within Cook County, Illinois, USA, to provide spatio-temporal information on the abundance of WNv vectors from 2002 to 2005. Regression analyses of the sampled covariates revealed that the adult Culex population was positively associated with temperature throughout the sampling frame. The model output also indicated that precipitation was negatively associated to mosquito abundance in 2002, 2003 and 2005 (P <0.05), but positively associated in 2004 (P <0.05). A land use land cover classification, based on QuickBird visible and near infra-red data, acquired at 0.61 m resolution, was used to investigate possible associations between geographical features and the abundance of sampled Culex oviposition surveillance sites. A maximum likelihood unsupervised classification in ArcInfo 9.2 ® revealed that the highest overall mosquito abundance was found in sites having a low-to-moderate range of built environment (40%) and high forest composition. A set of propagation equations were then designed to model the calibration uncertainties, which revealed that normalized difference vegetation index (NDVI), and two NDVI variants, were informative markers for the sampled mosquito data. Spatial dependence of the covariates of Cx. restuans and Cx. pipiens oviposition sites were indexed using semivariograms, which suggested that all main effects of the explanatory variables were statistically significant in the model. Additionally, a multispectral classification and digital elevation model-based geographical information system method were able to evaluate stream flow direction and accumulation for identification of terrain covariates associated with the sampled habitat data. These results demonstrate that remotely sensed operational indices can be used to identify parameters associated with field-sampled Cx. pipiens and Cx. restuans aquatic habitats.

The NLMeans filter, originally proposed by Buades et al., is a very popular filter for the removal of white Gaussian noise, due to its simplicity and excellent performance. The strength of this filter lies in exploiting the repetitive character of structures in images. However, to fully take advantage of the repetitivity a computationally extensive search for similar candidate blocks is indispensable. In previous work, we presented a number of algorithmic acceleration techniques for the NLMeans filter for still grayscale images. In this paper, we go one step further and incorporate both temporal information and color information into the NLMeans algorithm, in order to restore video sequences. Starting from our algorithmic acceleration techniques, we investigate how the NLMeans algorithm can be easily mapped onto recent parallel computing architectures. In particular, we consider the graphical processing unit (GPU), which is available on most recent computers. Our developments lead to a high-quality denoising filter that can process DVD-resolution video sequences in real-time on a mid-range GPU.

Most theorists propose that when a person is aware that a duration judgment must be made (prospective paradigm), experienced duration depends on attention to temporal information, which competes with attention to nontemporal information. When a person is not aware that a duration judgment must be made until later (retrospective paradigm), remembered duration depends on incidental memory for temporal information. In the present article we describe two experiments in which durations involved with high-level, executive-control functions were judged either prospectively or retrospectively. In one experiment, the executive function involved resolving syntactic ambiguity in reading. In another experiment, it involved controlling the switching between tasks. In both experiments, there was a unique cost to the operation of control high-level, executive functions which was manifested by prospective reproductions shortening a finding that supports an attentional model of prospective timing. In addition, activation of executive functions produced contextual changes that were encoded in memory and resulted in longer retrospective reproductions, a finding that supports a contextual-change model of retrospective timing. Thus, different cognitive processes underlie prospective and retrospective timing. Recent findings obtained by some brain researchers also support these conclusions.

We investigate the problem of efficient panoramic video construction based on time-synchronized input video streams. No additional constraints are imposed regarding the motion of the capturing video cameras. The presented work is, to the best of our knowledge, the first attempt to construct in real-time a panoramic video stream from input video streams captured by freely moving cameras. The main contribution is in proposing an efficient panoramic video construction algorithm that exploits temporal information to avoid solving the stitching problem fully on a frame by frame basis. We provide detailed experimental evaluation of different methodologies that employ previous frames stitching results such as tracking interest points using optical flow and using areas of overlap to limit the search space for interest points. Our results clearly indicate that making use of temporal information in video stitching can achieve a significant reduction in execution time while providing a comparable effectiveness.

The Ethiopian Rift System consists of basins that are in different stages of evolution. Some of the rift-related basins in southwestern Ethiopia are half-grabens that have not evolved to symmetrical rifts since the initiation of rifting here in the middle Miocene. These basins contain fossiliferous Pliocene-Pleistocene volcaniclastic sediments and volcanic rocks and have been occupied by early hominid populations. The Afar and the Main Ethiopian Rifts are symmetrical, with both margins fully developed. Several paleoanthropological localities, ranging in age from the Quaternary to the Pliocene, were discovered within these rift basins. The discovery of Australopithecus afarensis (the "Lucy" species) at Hadar and Ardipithecus ramidus and Australopithecus garhi in the Middle Awash makes the region the most prolific early hominid area in the world.

This article reviews some of our investigations concerning individual differences in temporal information processing. Two different levels of temporal information processing are discussed, namely the low-frequency (i.e., a few seconds time range) and the high-frequency processing level (i.e., some tens of milliseconds range) of temporal information with respect to various experimental paradigms. Evidence has been obtained indicating that the processing of temporal information on these two levels can be influenced by various subject-related factors, out of which age, gender, developmental disorders, auditory experience and localisation of damage in the brain seem to be the most significant.

The cone-beam computed tomography (CBCT) imaging modality is an integral component of image-guided adaptive radiation therapy (IGART), which uses patient-specific dynamic/temporal information for potential treatment plan modification. In this study, an offline process for the integral component IGART framework has been implemented that consists of deformable image registration (DIR) and its validation, dose reconstruction, dose accumulation and dose verification. This study compares the differences between planned and estimated delivered doses under an IGART framework of five patients undergoing prostate cancer radiation therapy. The dose calculation accuracy on CBCT was verified by measurements made in a Rando pelvic phantom. The accuracy of DIR on patient image sets was evaluated in three ways: landmark matching with fiducial markers, visual image evaluation and unbalanced energy (UE); UE has been previously demonstrated to be a feasible method for the validation of DIR accuracy at a voxel level. The dose calculated on each CBCT image set was reconstructed and accumulated over all fractions to reflect the 'actual dose' delivered to the patient. The deformably accumulated (delivered) plans were then compared to the original (static) plans to evaluate tumor and normal tissue dose discrepancies. The results support the utility of adaptive planning, which can be used to fully elucidate the dosimetric impact based on the simulated delivered dose to achieve the desired tumor control and normal tissue sparing, which may be of particular importance in the context of hypofractionated radiotherapy regimens.

Expressions carry vital information in sign language. In this study, we have implemented a multi-resolution Active Shape Model (MR-ASM) tracker, which tracks 116 facial landmarks on videos. Since the expressions involve significant amount of head rotation, we employ multiple ASM models to deal with different poses. The tracked landmark points are used to extract motion features which are used by a Support Vector Machine (SVM) based classifier. We obtained above 90% classification accuracy in a data set containing 7 expressions.

The objective of this study is to determine the effects of environmental factors on physician situation awareness (SA) in an emergency department (ED) setting. An objective method of level 1 (i.e., perception) SA measurement and evaluation was developed and applied. Resident physician level 1 SA was measured using the Situational Awareness Global Assessment Technique (SAGAT). SAGAT question probes (i.e., sets of 10 questions) were generated randomly from a pool of questions and administered hourly. Questions were answered at a 7.4% false response rate. Environmental measures (i.e., patient information, physician information, temporal information, and workload) were collected concurrently. Mixed-effects modeling was used to determine the relationship between physician SA and environmental factors adjusting for potential correlation within physician observed, patients managed, and questions asked. Significant factors associated with decreases in SA include: patient hand-offs (Odds Ratio (OR): 1.67), resident physician in final year of training (OR: 0.49), and number of patients managed (OR: 1.17). Significant correlation within question was observed and adjusted for. Overall, this study demonstrates a novel approach toward diagnosing factors contributing to physician SA during patient care. SA studies in healthcare may provide evidence for interventions aimed at improving healthcare work environments and patient safety.