Simulation of undular bores evolution with damping

Propagation of undular bores with damping is considered in the framework of perturbed extended Korteweg-de Vries (peKdV) equation. Two types of damping terms for the peKdV equation, namely linear and Chezy frictional terms, which describe the turbulent boundary layers in the fluid flow are considered. Solving the peKdV equation numerically using the method of lines shows that under the influence of damping, the lead-ing solitary wave of the undular bores will split from the nonlinear wavetrain, propagates and behaves like an isolated solitary wave. The amplitude of the leading wave will remain the same for some times before it starts to decay again at a larger time. In general the amplitude of the leading wave and the mean level across the undular bore decreases due to the effect of damping

Strength, water absorption and thermal comfort of mortar bricks containing crushed ceramic waste

This present study investigated the crushed ceramic waste utilisation as sand replacement in solid mortar bricks. The percentage of crushed ceramic waste used were 0% (CW0), 10% (CW10), 20% (CW20) and 30% (CW30) from the total weight of sand. The dimension prescribed of mortar bricks are 215 mm x 102.5 mm x 65 mm as followed accordance to MS 2281:2010 and BS EN 771-1:2011+A1:2015. Four (4) tests were conducted on mortar bricks namely crushing strength, water absorption, compressive strength of masonry units and thermal comfort. The incorporation of ceramic waste in all designated mortar bricks showed the increment of crushing strength between 23% and 46% at 28 days of curing and decrement water absorption between 34% and 44% was recorded corresponding to control mortar bricks. The prism test of masonry units consists of mortar bricks containing ceramic waste indicated the high increment of compressive strength at about 200% as compared to mortar brick without ceramic waste. The thermal comfort test of ceramic mortar bricks were also showed the good insulation with low interior temperature. Therefore, the ceramic waste can be utilised as a material replacement to fine aggregate in mortar brick productions due to significant outcomes performed

The level of Marzano higher-order thinking skills among polytechnic students

This study aims to identify polytechnic students' level of Marzano Higher-Order Thinking Skills (HOTS) based on two dimensions, 'Extension and Refinement of Knowledge' and 'Meaningful Use of Knowledge,' and to analyze the difference in the students' level of Marzano HOTS based on these two dimensions depending on the students' demographic factors. This study design was a survey using quantitative methods. A total of 313 students were randomly selected as the survey sample. A questionnaire in the form of closed-ended questions was used as the research instrument. Data were analyzed using frequency percentage and MANOVA test. The findings showed no significant differences in the eight HOTS in the dimension of 'Extension and Refinement of Knowledge' with the gender and socio-economic status (SES) factors. However, there were significant differences in the eight HOTS with the academic achievement factor. Meanwhile, based on the dimension of 'Meaningful Use of Knowledge,' the findings showed no significant differences in the five HOTS in this dimension with the gender and academic achievement factors. The paper includes implications of the Higher-Order Thinking Skills (HOTS) for students to improve their academic performance. In future research, the authors can further identify university students' HOTS levels in the technical area

Robust modeling and planning of radio-frequency identification network in logistics under uncertainties

To realize higher coverage rate, lower reading interference, and cost efficiency of radio-frequency identification networkin logistics under uncertainties, a novel robust radio-frequency identification network planning model is built and arobust particle swarm optimization is proposed. In radio-frequency identification network planning model, coverage isestablished by referring the probabilistic sensing model of sensor with uncertain sensing range; reading interference iscalculated by concentric map–based Monte Carlo method; cost efficiency is described with the quantity of readers. Inrobust particle swarm optimization, a sampling method, the sampling size of which varies with iterations, is put forwardto improve the robustness of robust particle swarm optimization within limited sampling size. In particular, the exploita-tion speed in the prophase of robust particle swarm optimization is quickened by smaller expected sampling size; theexploitation precision in the anaphase of robust particle swarm optimization is ensured by larger expected sampling size.Simulation results show that, compared with the other three methods, the planning solution obtained by this work ismore conducive to enhance the coverage rate and reduce interference and cost.info:eu-repo/semantics/publishedVersio

Modeling and Optimization of Radio Frequency Identification Networks for Inventory Management

Stock loss and out-of-stocks are outcomes of poorly designed inventory management systems and can lead to significant revenue losses. Inventory management systems (IMSs) based on radio frequency identification (RFID) have the potential to minimize these losses if they are properly designed and deployed. However, the placement of RFID readers to support IMSs is often done on a trial and error basis which is time consuming and results in less than optimal coverage. A methodology to find the optimal location and number of RFID readers in a warehouse facility to ensure a desired level of radio frequency signal coverage was developed in this research. The results show that the proposed methodology works very well when applied to small rectangular facilities and small inverted-T facilities. However, some limitations exist when the method is applied to large facilities

Path Optimization and Object Localization Using Hybrid Particle Swarm and Ant Colony Optimization for Mobile RFID Reader

This paper proposes a hybrid approach of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for the mobile Radio Frequency Identification System (RFID) reader to get the shortest path for object localization. In this approach, we have adopted the ACO global pheromone updating information of ants to guide the update velocities and position for PSO based on nearest neighbor constraints. The pheromone information is used efficiently to guide the selection of each particle in a search space of its visits. The best path will be used for mobile RFID reader for objects localization in search space. Simulation results show that the method is effective, minimizing the number of visited nodes for a mobile RFID reader

A new algorithm based CSP framework for RFID network planning

International audienceThe huge growth of industrial society requires the deployment of radio frequency identification networks on a large scale. This necessitates the installation of a large number of radio frequency identification components (readers, tags, middleware and others). As a consequence, the cost and complexity of networks are increasing due to the large number of readers to be installed. Finding the optimal number, placement and parameters of readers to provide a high quality of service for radio frequency identification systems is a critical problem. A good planning affords a basic need for radio frequency identification networks, such as coverage, load balance and interference between readers. This problem is famous in the literature as a radio frequency identification network planning problem. All the proposed approaches in the literature have been based on meta-heuristics. In this paper, we design a new algorithm, called the RNP-CSP algorithm based on the constraint satisfaction problem framework to solve the radio frequency identification network planning problem. The performance evaluation shows that the RNP-CSP algorithm is more efficient than PS 2 O , GPSO and VNPSO-RNP

Efficient multi-objective optimization of wireless network problems on wireless testbeds

A large amount of research focuses on experimentally optimizing performance of wireless solutions. Finding the optimal performance settings typically requires investigating all possible combinations of design parameters, while the number of required experiments increases exponentially for each considered design parameter. The aim of this paper is to analyze the applicability of global optimization techniques to reduce the optimization time of wireless experimentation. In particular, the paper applies the Efficient Global Optimization (EGO) algorithm implemented in the SUrrogate MOdeling (SUMO) toolbox inside a wireless testbed. The proposed techniques are implemented and evaluated in a wireless testbed using a realistic wireless conference network problem. The performance accuracy and experimentation time of an exhaustively searched experiment is compared against a SUMO optimized experiment. In our proof of concept, the proposed SUMO optimizer reaches 99.51% of the global optimum performance while requiring 10 times less experiments compared to the exhaustive search experiment