Evaluation of in-air hand gestures interaction for older people

Universal Access in the Information Society - In-air gestural interfaces are gaining popularity due to the increasing availability and low cost of gesture recognition hardware. However, the current...     

Designing erosion management plans in Lebanon using remote sensing, GIS and decision-tree modeling

Soil erosion by water represents a serious threat to the natural and human environment in Mediterranean countries, including Lebanon, which represents a good case study. This research deals with how to use Geographic Information Systems (GIS), remote sensing, and, more specifically, structural classification techniques and decision-tree modeling to map erosion risks and design priority management planning over a representative region of Lebanon. The structural classification organization and analysis of spatial structures (OASIS) of Landsat TM satellite imagery (30 m) was used to define landscapes that prevail in this area and their boundaries, depending on their spectral appearance. The landscape map produced was overlaid sequentially with thematic erosion factorial maps (i.e., slope gradient, drainage density, rainfall quantity, vegetal cover, soil infiltration, soil erodibility, rock infiltration and rock movement). The overlay was visual and conditional using three visual interpretation rules (dominance, unimodality and scarcity conservation), and landscape properties were produced. Rills and gullies were measured in the field, and a decision-tree regression model was developed on the landscapes to statistically explain gully occurrence. This model explained 88% of the variability in field gully measurements. The erosion risk map produced corresponds well to field observations (accuracy of 82%). The landscapes were prioritized according to anti-erosive remedial measures: preventive (Pre), protective (Pro), and restorative (Res). This approach seems useful in Lebanon, but can also serve in other countries with similar geo-environmental conditions or those lacking detailed geospatial data.     

Introducing the fractional-order Darwinian PSO

One of the most well-known bio-inspired algorithms used in optimization problems is the particle swarm optimization (PSO), which basically consists on a machine-learning technique loosely inspired by birds flocking in search of food. More specifically, it consists of a number of particles that collectively move on the search space in search of the global optimum. The Darwinian particle swarm optimization (DPSO) is an evolutionary algorithm that extends the PSO using natural selection, or survival of the fittest, to enhance the ability to escape from local optima. This paper firstly presents a survey on PSO algorithms mainly focusing on the DPSO. Afterward, a method for controlling the convergence rate of the DPSO using fractional calculus (FC) concepts is proposed. The fractional-order optimization algorithm, denoted as FO-DPSO, is tested using several well-known functions, and the relationship between the fractional-order velocity and the convergence of the algorithm is observed. Moreover, experimental results show that the FO-DPSO significantly outperforms the previously presented FO-PSO.     

Enhancing typing performance of older adults on tablets

Touch screen interfaces are increasingly more popular. However, they lack haptic feedback, making it harder to perform certain tasks, such as text entry, where users have to constantly select one of many small targets. This problem particularly affects older users, whose deteriorating physical and cognitive conditions, combined with their unfamiliarity with technology, can discourage them from using touch devices. The goal of this work was to thoroughly understand older adults touch typing behavior, in order to develop text-entry solutions more appropriate to their needs, which will enhance their typing performance. On a first phase, a baseline QWERTY keyboard and five different variants were developed that mostly used a text prediction algorithm to suggest the most probable keys or words. These keyboards were evaluated on a baseline study with 20 younger adults in order to find the most promising ones, which were then used in a study with 20 older adults. The older adults study revealed more about their typing behavior and therefore created four new variants to be used in a simulation study. Results show that visual changes should be kept to a minimum; touch points should be shifted upward and to the opposite side of the hand used to type; single touch keyboards perform better than multi-touch; and omitting keys below a certain time threshold minimizes accidental insertions.     

Mechanism and Convergence Analysis of a Multi-Robot Swarm Approach Based on Natural Selection

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization (PSO) using natural selection, or survival-of-the-fittest, to enhance the ability to escape from local optima. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots. Therefore, the RDPSO decreases the amount of required information exchange among robots, and is scalable to large populations of robots. This paper presents a stability analysis of the RDPSO to better understand the relationship between the algorithm parameters and the robot’s convergence. Moreover, the analysis of the RDPSO is further extended for real robot constraints (e.g., robot dynamics, obstacles and communication constraints) and experimental assessment with physical robots. The optimal parameters are evaluated in groups of physical robots and a larger population of simulated mobile robots for different target distributions within larger scenarios. Experimental results show that robots are able to converge regardless of the RDPSO parameters within the defined attraction domain. However, a more conservative parametrization presents a significant influence on the convergence time. To further evaluate the herein proposed approach, the RDPSO is further compared with four state-of-the-art swarm robotic alternatives under simulation. It is observed that the RDPSO algorithm provably converges to the optimal solution faster and more accurately than the other approaches.     

CFD modeling of heat transfer and flow field in a bakery pilot oven

A bakery pilot oven is modeled using computational fluid dynamics software. This approach relies on integration of an instrument into modeled geometry. The instrument is a heat flux measuring device that can be used in the industrial baking process. All three heat transfer mechanisms are considered and coupled with turbulent flow. Turbulence is taken into account via the k–ε realizable model whereas the surface-to-surface model simulates the radiation. Additionally, buoyancy forces are introduced by means of a weakly compressible formulation. The model predictions show a good qualitative agreement with the experimental measurements. A quantitative agreement was obtained to some extent. Limitations came from the difficulty to measure the temperature of the radiant surfaces of the oven. Operating conditions used are typical of bakery products and, as expected, radiation was the dominant mode of heat transfer. The integration of the instrument was useful for assessing the model. Since it is designed for industrial use, it may be a valuable tool for future challenges in the field, such as simulation of an industrial scale oven.     

A fractional calculus approach for the evaluation of the golf lip-out

Golf is a sport in which competing players need to introduce the ball into the hole using the fewest number of strikes. However, this goal can sometimes be compromised when the ball suffers from lip-out phenomenon, that is, when the ball surrounds the hole??s edge without dropping in. Although some techniques may be presented in the literature to assess golfers?? performance (e.g., evaluation of the ball??s final position to the hole), none takes in consideration the putting lip-out. With this in mind, this article proposes a correction metric based on fractional calculus that considers past events in ball??s trajectory, thus slightly increasing player??s performance when putting lip-out occurs. On the opposite of integer derivatives which are considered as ??local?? operators, fractional derivatives implicitly have ??memory?? of all past events being well suited to describe the dynamic phenomena of ball??s trajectory. Therefore, this novel correction metric will provide a new virtual position of the ball based on its trajectory induced by the putting lip-out. This metric was evaluated analyzing the performance of 10 expert subjects who performed a total of 30 trials, with the lip-out occurring in 29 out of the 300 considered. Experimental results show an average improvement of 19.6?% in trials where the lip-out occurred and an average overall improvement of 1.82?% in player??s performances, when applying the correction metric.     

A PSO multi-robot exploration approach over unreliable MANETs

This paper proposes two extensions of Particle Swarm Optimization (PSO) and Darwinian Particle Swarm Optimization (DPSO), respectively denoted as RPSO (Robotic PSO) and RDPSO (Robotic DPSO), so as to adapt these promising biologically inspired techniques to the multi-robot systems domain, by considering obstacle avoidance and communication constraints. The concepts of social exclusion and social inclusion are used in the RDPSO algorithm as a ‘punish–reward’ mechanism, thus enhancing the ability to escape from local optima. Experimental results obtained in a simulated environment shows the superiority of the RDPSO evidencing that sociobiological inspiration can be useful to meet the challenges of robotic applications that can be described as optimization problems (e.g. search and rescue). Moreover, the performance of the RDPSO is further evaluated within a population of up to 12 physical robots under communication constraints. Experimental results with real platforms show that only 4 robots are needed to accomplish the herein proposed mission and, independently on the number of robots and maximum communication distance, the global optimum is achieved in approximately 90% of the experiments.     

Generating relativistic pseudo-potentials with explicit incorporation of semi-core states using APE, the Atomic Pseudo-potentials Engine

We present a computer package designed to generate and test norm-conserving pseudo-potentials within Density Functional Theory. The generated pseudo-potentials can be either non-relativistic, scalar relativistic or fully relativistic and can explicitly include semi-core states. A wide range of exchange-correlation functionals is included.

Program summary

Program title: Atomic Pseudo-potentials Engine (APE)Catalogue identifier: AEAC_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAC_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 88 287No. of bytes in distributed program, including test data, etc.: 649 959Distribution format: tar.gzProgramming language: Fortran 90, CComputer: any computer architecture, running any flavor of UNIXOperating system: GNU/LinuxRAM: <5 MbClassification: 7.3External routines: GSL (http://www.gnu.org/software/gsl/)Nature of problem: Determination of atomic eigenvalues and wave-functions using relativistic and nonrelativistic Density-Functional Theory. Construction of pseudo-potentials for use in ab-initio simulations.Solution method: Grid-based integration of the Kohn-Sham equations.Restrictions: Relativistic spin-polarized calculations are not possible. The set of exchange-correlation functionals implemented in the code does not include orbital-dependent functionals.Unusual features: The program creates pseudo-potential files suitable for the most widely used ab-initio packages and, besides the standard non-relativistic Hamann and Troullier-Martins potentials, it can generate pseudo-potentials using the relativistic and semi-core extensions to the Troullier-Martins scheme. APE also has a very sophisticated and user-friendly input system.Running time: The example given in this paper (Si) takes 10 s to run on a Pentium IV machine clocked at 2 GHz.