Information acquisition using eye-gaze tracking for person-following with mobile robots

In the effort of developing natural means for human-robot interaction (HRI), signifcant amount of research has been focusing on Person-Following (PF) for mobile robots. PF, which generally consists of detecting, recognizing and following people, is believed to be one of the required functionalities for most future robots that share their environments with their human companions. Research in this field is mostly directed towards fully automating this functionality, which makes the challenge even more tedious. Focusing on this challenge leads research to divert from other challenges that coexist in any PF system. A natural PF functionality consists of a number of tasks that are required to be implemented in the system. However, in more realistic life scenarios, not all the tasks required for PF need to be automated. Instead, some of these tasks can be operated by human operators and therefore require natural means of interaction and information acquisition. In order to highlight all the tasks that are believed to exist in any PF system, this paper introduces a novel taxonomy for PF. Also, in order to provide a natural means for HRI, TeleGaze is used for information acquisition in the implementation of the taxonomy. TeleGaze was previously developed by the authors as a means of natural HRI for teleoperation through eye-gaze tracking. Using TeleGaze in the aid of developing PF systems is believed to show the feasibility of achieving a realistic information acquisition in a natural way

Single-occupancy simulator for ambient intelligent environment

In this paper, the simulation of an occupant’s behaviour in a single-occupant ambient intelligent environment is addressed. The algorithm of the simulator is designed flexible enough to accept different environmental profiles including the number of areas and the connections between them along with different occupant’s profiles including expected daily occupancy pattern of him/her and the uncertainty of his/her behaviour to follow this occupancy pattern. The generated occupancy signal by the simulator represents the occupancy of areas by assuming a signal level for the occupancy of each area in a single-occupant environment with the resolution of one minute in a whole day activity of the occupant in the environment. The validity of the simulator will be verified by tuning the simulator’s parameters to occupancy data collected by sensory agents from a real equivalent environment. By applying the generated data from this simulator to the data mining techniques, the ability of different techniques will be investigated

Echo state network for occupancy prediction and pattern mining in intelligent environment

Pattern analysis and prediction of sensory data is becoming an increasing scientific challenge and a massive economical interest supports the need for better pattern mining techniques. The aim of this paper is to investigate efficient mining of useful information from a sensor network representing an ambient intelligence environment. The goal is to extract and predict behavioral patterns of a person in his/her daily activities by analyzing the time series data representing the behaviour of the occupant, generated using occupancy sensors. There are various techniques available for analysis and prediction of a continuous time series signal. However, the occupancy signal is represented by a binary time series where only discrete values of a signal are available. To build the prediction model, recurrent neural networks are investigated. They are proven to be useful tools to solve the difficulties of the temporal relationships of inputs between observations at different time steps, by maintaining internal states that have memory. In this paper, a special form of recurrent neural network, the so-called Echo State Network (ESN) is used in which discrete values of time series can be well processed. Then, a model developed based on ESN is compared with the most popular recurrent neural net-works; namely Back Propagation Through Time (BPTT) and Real Time Recurrent Learning (RTRL). The results showed that ESN provides better prediction results compared with BPTT and RTRL. Using ESN, large datasets are learnt in only few minutes or even seconds. It can be concluded that ESN are efficient and valuable tools in binary time series prediction. The results presented in this paper are based on simulated data generated from a simulator representing a person in a 1 bedroom flat

Modeling of Power Losses Caused by Hidden Tree-Related High Impedance Faults

The great majority of overhead distribution systems in urban and rural areas of countries such as Australia, Iran and etc., are in interfering with vegetation. This phenomena leads to high impedance faults (HIFs) which not produce enough fault current to be detectable and consequently causes electrical energy losses. In this paper, according to experimental data obtained from measurements, the effective factors in power losses caused by trees are studied and a new numerical model of power loss is presented so as to reflect the effects of environmental conditions and biological classification. The base of this method is according to Samuelson theory. In proposed algorithm, the impacts of species, short-term environmental conditions (temperature and humidity) and long-term environmental conditions (Seasonal variations in physiology) on the power loss estimation are fully considered. Experimental investigations on a real low voltage (380 V) and medium voltage (20 kV) distribution network verify the algorithm\u27s operation

Experimental And Theoretical Study Of The Substitution Mechanism In The W6+: Litao3 Correlated With The Ferroelectric Properties

The purpose of the present work is to report the latest results of our experimental and theoretical non-stoichiometry investigations of solid solutions isolated close to LiTaO3 inside the ternary system Li2O-Ta2O5-(WO3)2 correlated with the ferroelectrics transitions. Dielectric measurements performed on ceramic samples have shown that ferro-paraelectric temperatures transitions TC varied along the solids solutions, as the stoichiometry deviates from LiTaO3. A Safaryan’s theory of ferroelectric transition and the various vacancy models in this work reproduce well the experimental results by explaining the substitution nature of Tungsten hexavalent (W6+) in LiTaO3.The purpose of the present work is to report the latest results of our experimental and theoretical non-stoichiometry investigations of solid solutions isolated close to LiTaO3 inside the ternary system Li2O-Ta2O5-(WO3)2 correlated with the ferroelectrics transitions. Dielectric measurements performed on ceramic samples have shown that ferro-paraelectric temperatures transitions TC varied along the solids solutions, as the stoichiometry deviates from LiTaO3. A Safaryan’s theory of ferroelectric transition and the various vacancy models in this work reproduce well the experimental results by explaining the substitution nature of Tungsten hexavalent (W6+) in LiTaO3

On the Wang-Landau Method for Off-Lattice Simulations in the "Uniform" Ensemble

We present a rigorous derivation for off-lattice implementations of the so-called "random-walk" algorithm recently introduced by Wang and Landau [PRL 86, 2050 (2001)]. Originally developed for discrete systems, the algorithm samples configurations according to their inverse density of states using Monte-Carlo moves; the estimate for the density of states is refined at each simulation step and is ultimately used to calculate thermodynamic properties. We present an implementation for atomic systems based on a rigorous separation of kinetic and configurational contributions to the density of states. By constructing a "uniform" ensemble for configurational degrees of freedom--in which all potential energies, volumes, and numbers of particles are equally probable--we establish a framework for the correct implementation of simulation acceptance criteria and calculation of thermodynamic averages in the continuum case. To demonstrate the generality of our approach, we perform sample calculations for the Lennard-Jones fluid using two implementation variants and in both cases find good agreement with established literature values for the vapor-liquid coexistence locus.Comment: 21 pages, 4 figure

The impact of variability and distribution of practice on student’s learning of basketball throw skill

Purpose: The practice organization is an important factor in sports environment and education. This study aimed to investigate the impact of variability and distribution of practice on basketball throw skill learning among female elementary school students. Material: Based on the pre-test scores of 15 attempts (5 throw from any distances of 3, 3.5, and 4 meters), 90 volunteer participants were distributed in 6 homogeneous groups of 15 participants (three massed practice groups and three distributed practice groups with blocked, increasing, and decreasing practice arrangements). In acquisition stage, the participants practiced for 9 sessions. After 72 hours, all participants conducted the retention test. Changing the angle at a distance of 3.5 meters, the transfer test was conducted at the same day. Results: The findings showed that the variability and distribution of practice did not impact on participants’ performance in acquisition, retention, and transfer stages. Conclusions: For development of contextual interference effect, the variability in parameters of a motor program is not enough

Serum level of interleukin-6 in patients with oral tongue squamous cell carcinoma

Introduction: The clinical outcome of patients with squamous cell carcinoma (SCC) located in the head and neck has remained poor despite ongoing advances in diagnosis and management. Interleukin-6(IL-6) is a multi-functional cytokine that plays an important role in the process of cell differentiation and is increased in several malignancies. The aim of this study was to investigate the serum levels of interleukin-6 in patients with oral tongue SCC. Materials and Methods: In a cross-sectional study, 17 patients with oral tongue SCC were compared with the same number of age- and gender-matched healthy subjects. Serum IL-6 level fluctuation was determined using an immunological technique, before detecting its possible association with the subjects' age, gender, drinking and smoking history, cancer site, and disease severity. Results: The intensity of serum IL-6 in patients with oral tongue SCC was statistically significantly higher than that in healthy subjects (P<0.001). Serum IL-6 level was independent of the patients' age, gender, smoking and drinking history as well as cancer stage. Conclusion: IL-6 is a valuable biomarker in the diagnosis of oral tongue SCC. Its high sensitivity makes prediction of this condition possible, while this biomarker can also be used to screen high-risk patients