Distributed attitude synchronization using backstepping and sliding mode control

We consider the problem of attitude synchronization for systems of rigid body agents with directed topologies. Two different scenarios for the rotation matrices of the agents are considered. In the first scenario, the rotations are contained in a convex subset of SO(3), which is a ball of radius less than π/2, whereas in the second scenario the agents are contained in a subset of SO(3), which is a ball of radius less than π. Using a control law based on backstepping and sliding mode control, we provide distributed, semi-global, torque control laws for the agents so that the rotations asymptotically synchronize. The control laws for the agents in the first scenario only depend on the relative rotations between neighboring agents, whereas the control laws in the second scenario depend on rotations defined in a global coordinate frame. Illustrative examples are provided where the synchronization is shown for both scenarios.     

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...     

Detection of thermophilic Campylobacter spp. in blood-free enriched samples of inoculated foods by the polymerase chain reaction

The detection of thermophilic Campylobacter spp., as represented by Campylobacter jejuni, by the polymerase chain reaction (PCR) was investigated and compared with the selective agar isolation (SAI) method. Stationary-phase cultures of C. jejuni were inoculated into either blood-free enrichment broth (BFEB) or BFEB that contained 10% broccoli, crabmeat, mushroom, raw milk, and raw oyster rinses. Following a 48-h enrichment period, aliquots of food test portions were removed for simultaneous analysis by PCR and SAI. It was determined that the presence of charcoal and iron in the enrichment broth interfered with the PCR assay. Therefore, three DNA extraction techniques were developed and evaluated using a 16S rRNA primer pair in the PCR assay. The 50% end point (DL50) values (determined upon six initial C. jejuni spiking levels) were used to assess the frequency of isolation utilizing PCR versus SAI for the detection of this organism in the enrichment matrices. There were virtually no differences in detection of C. jejuni among enriched samples analyzed by PCR and SAI. Mean DL50 values (n = 3) for plain BFEB, broccoli, crabmeat, mushroom, raw milk, and raw oyster were, respectively, 0.02 (PCR) versus 0.01 (SAI), 0.01 versus 0.06, 0.07 versus 0.04, 0.03 versus 0.08, 0.01 versus 0.01, and 0.01 versus 0.01 CFU/5 g food. Significant variability in the detection limit of C. jejuni by PCR in the food enrichments was observed among DNA extraction techniques. Using 48-h enrichment cultures followed by PCR analysis could save 1 day of the time required for the presumptive identification of C. jejuni in suspected foods.     

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.