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Diabetic kidney disease is a significant complication of type 2 diabetes mellitus and has a significant impact on quality of life and patient survival, both due to progression towards endstage kidney disease and associated atherosclerosis. Identification of the risk factors, especially in incipient kidney disease, is an important focus of research. The aim of our study was to rank the risk factors...
Given a remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets emotion...
Eye contact provides a communicative link between humans, prompting joint attention. As spontaneous brain activity might have an important role in the coordination of neuronal processing within the brain, their inter-subject synchronization might occur during eye contact. To test this, we conducted simultaneous functional MRI in pairs of adults. Eye contact was maintained at baseline while the subjects...
In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations...
The main objective of this work is to study the degree of engagement levels of human subjects in completing a series of tasks based on their physiological signals. The tasks are in the form of tracking a set of trajectories on the computer screen by using a mouse… The subjects are chosen randomly based on both sexes, aged from 20 to 40 years old. After completing the required tasks in a series of...
This paper presents a new method on generating realistic human animation of various styles with given step constraints and a specific skeleton. Given a set of normal walking data captured from different subjects, a hierarchical geostatistical model is automatically learned to encode variety of walking styles by representing human body as a hierarchy of joint groups. For each child hierarchy level,...
This paper deals a novel pseudonoise sequence with imperceptibility in conceptually significant region of human auditory system. The proposed sequence was generated from a typical pseudonoise sequence by the canonical signed digit coding and ordered pair transition. Frequency and auto- and cross-correlation analysis were tested for security, randomness and imperceptibility. The proposed sequence is...
The objective of this research is to explore the relationship between training transfer determinants and small businesswomen's goal setting. The instrument for this research is adapted and modified from the Training Transfer Model and Model for Excellence (American Society of Training and Development Competency Research). Training transfer determinants: training design (training content, training...
Investigations of the biomechanical parameters of robotic walker assisted gait are needed to allow modern rehabilitation strategies and to improve further technological developments. In this study, spatio-temporal gait parameters were assessed during normal and assisted ambulation with the Simbiosis walker model, a robotic walker with forearm supports. Six infra-red video cameras, integrated in a...
Given the remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets...
We explore recently proposed Bayesian nonparametric models of image partitions, based on spatially dependent Pitman-Yor processes. These models are attractive because they adapt to images of varying complexity, successfully modeling uncertainty in the structure and scale of human segmentations of natural scenes. By developing substantially improved inference and learning algorithms, we achieve performance...
Activity recognition in video is dominated by low- and mid-level features, and while demonstrably capable, by nature, these features carry little semantic meaning. Inspired by the recent object bank approach to image representation, we present Action Bank, a new high-level representation of video. Action bank is comprised of many individual action detectors sampled broadly in semantic space as well...
Human action recognition in videos draws strong research interest in computer vision because of its promising applications for video surveillance, video annotation, interactive gaming, etc. However, the amount of video data containing human actions is increasing exponentially, which makes the management of these resources a challenging task. Given a database with huge volumes of unlabeled videos,...
Gross motor skills is one of the precursors for successful involvement in any sports and physical activities performance. This study investigated the gross motor skills development among Down syndrome children in Klang Valley. 30 children (16 boys and 14 girls) participated in this study with the age range from 3–10 years old. They were assessed on locomotor and object control skills. It includes...
The ground penetrating radar (GPR) are widely used in recent years due to its potential applications and unique capabilities, especially in the earthquake search or rescue. In this paper, a novel adaptive line enhancer (ALE) algorithm for human respiration monitoring through obstacle with low-power GPR is presented. The results of through wall experiments show that it is feasible to use this algorithm...
In service-oriented enterprise architecture, provisioning business services is made on top of IT processes, which should be elastic amid the availability of computing resources and the variation of user demand. In addition, the provisioning depends on human resources utilized and is constrained by the business objectives (e.g. a goal) plus coarse-grained constraints (e.g. an order in which business...
One of the major subjects of study in computational biology is finding the similarity between DNA sequences. Several techniques exist that are either based on alignment between sequences or are alignment-free. This paper demonstrates two techniques that are alignment-free. The first one is based on a graphical representation of the difference between DNA sequences, while the other one is based on...
Biometry is a wide-used and pervasive approach to verify people identity, based on the presence of some unique characteristics, having precise properties (i.e. biometric characteristics). On the other hand, optical detection of random features is widely used for recognizing object authenticity. In this paper we explain how these two approaches are similar; random features can be seen as "fingerprint"...
One of the most recent trends in surveillance research is the application of socially aware approaches, i.e. approaches that integrate human sciences findings in order to better understand, model and predict the behaviour of people under observation. One of the key requirements for the development of such approaches is the collection of corpora that provide sufficient and reliable information about...
Fiber tracking techniques are essential for representing and visualizing the cardiac fiber architecture information encoded in diffusion-tensor imaging (DTI) data. We propose a neighborhood-based probabilistic fiber tracking method for cardiac DTI which accounts for spatial correlation and data uncertainty. The method consists in tracking fiber paths by sampling step directions from a normalized weighted...
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