98 research outputs found
The usability dimension in the development of Web applications
No full textUsability dimensions for the usability evaluation of the web application
Optimal E-Field Vector Combination for a Highly Focused Antenna-Array
No full textA near-field highly focused circular phased-array antenna for 5.8-GHz radio frequency identification (RFID) applications is presented. The electric field (E-field) at the focus is enhanced by a constructive vector combination in a three-dimensional (3-D) coordinate system. The array dipoles of the antenna are oriented to enhance the energy confinement at the focus, and the radii of the circular array is optimized for lower sidelobe levels. As a result, the proposed design achieves an enhanced focalization of ~4 dB with reduced sidelobe levels of ~12dB compared to earlier designs
Influence of substrate types and reflector proximities over a NDTC antenna
No full textThe influence of dissimilar substrates and reflector proximities over a newly developed Non-uniformly Distributed-Turns Coil (NDTC) antenna for High-Frequency (HF) Radio Frequency IDentification (RFID) applications is presented. In the study, the performance of the HF-RFID NDTC antenna over various substrates with deposited conductor thicknesses is conducted. In addition, the effect over a conceivably encountered reflector in the proximity of the antenna is considered. Insensitive reflection coefficient (S11) responses for different substrate permittivities were experienced and the diverse conductor types and thicknesses contributed to a compromised magnetic-field (H-field) and recalculated matching network. The matching network additionally preserves resonance when the antennas is in close proximity to the reflector and a predictable H-field response for the separation range is shown
A Comparative Study on the Performance of Evolutionary Fuzzy and Crisp Rule Based Classification Methods in Congestion Prediction
No full textAbstractAccurate estimation of the future state of the traffic is an attracting area for researchers in the field of Intelligent Transportation Systems (ITS). This kind of predictions can lead to traffic managers and drivers to act in consequence, reducing the economic and social impact of a possible congestion. Due to the inter-urban traffic information nature, the task of predicting the future state of the traffic requires, in most cases, a non-linear patterns search in the input data. In recent years, a wide variety of models has been used to solve this problem in the most accurate way. Due to that, models generated to provide information about the future state of the road are, usually, incomprehensible to a human operator, making impossible to give him/her an explanation about the causes of the prediction. Given the capacity of rule based systems to explain the reasoning followed to classify a new pattern, the advantages and disadvantages of such approaches are explored in this work.To conduct such task, datasets recorded from the California Department of Transportation are created. A 9-kilometer section of the I5 highway of Sacramento is used for this research. Two different types of datasets are built for the experimentation. One of them contains the entire information recorded. The other one contains with a simplified version of the information, considering only the first, middle and last monitored points of the road. Twelve prediction horizons, from 5 to 60minutes, were considered for prediction. An experimental comparative study involving 16 state of the art techniques is performed. Techniques tested include those that fall within the categories of Evolutionary Crisp Rule Learning (ECRL) and Evolutionary Fuzzy Rule Learning (EFRL). These methods were selected since they offer to the final user, not only a prediction, but also a legible model about the way in which the decision was taken. Techniques are compared in terms of accuracy and complexity of the models generated
A High Throughput Anticollision Protocol to Decrease the Energy Consumption in a Passive RFID System
No full textOne of the main existing problems in Radio Frequency Identification (RFID) technology is the tag collision problem. When several tags try to respond to the reader under the coverage of the same reader antenna their messages collide, degrading bandwidth and increasing the number of transmitted bits. An anticollision protocol, based on the classical Binary Tree (BT) protocol, with the ability to decrease the number of bits transmitted by the reader and the tags, is proposed here. Simulations results show that the proposed protocol increases the throughput with respect to other recent state-of-the-art protocols while keeping a low energy consumption of a passive RFID system
Focusing on the Golden Ball Metaheuristic: An Extended Study on a Wider Set of Problems
No full textNowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results
Simultation Tool based on a Memetic Algorithm to Solve a Real Instance of a Dynamic TSP
No full textNowadays, public transportation has become an essential area which affects our quality of life. Therefore, the design of new roads, new vehicles or new stations is a complicated process that requires a preliminary study to analyze its impact. This paper shows the algorithm of a simulation tool that allows the definition of transport routes, in regular and on-demand transportation systems. The resulting application allows adjustment and modification of routes, depending on passenger demand. All this is achieved through the use of a memetic algorithm that combines a genetic algorithm and tabu search. The result of the work done is a simulation tool and a memetic algorithm used for solving a particular instance of the Dynamic TSP.Peer reviewe
On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP
No full textPublisher Copyright: © 2014 IEEE.Combinatorial optimization is a widely studied field within artificial intelligence. There are many problems of this type, and many techniques applied to them can be found in the literature. Especially, population techniques have received much attention in this area, being genetic algorithms (GA) the most famous ones. Although throughout history many studies on GAs have been performed, there is still no study like the presented in this work. In this paper, a study on the influence of using heuristic initialization functions in genetic algorithms (GA) applied to combinatorial optimization problems is performed. Being the first phase of this research, the study is conducted using one of the best known problems in combinatorial optimization: the traveling salesman problem. Three different experimentations are carried out, using three different heuristic initialization functions. Additionally, for each experiment four versions of a GA have been developed for the comparison. Each of these variant differs in the initialization phase. The results obtained by each GA are compared to determine the influence of the use of heuristic functions for the initialization of the population.Peer reviewe
Programa práctico de una asignatura de Ingeniería del Software Distribuido
No full textEn esta contribución describimos de manera detallada el programa práctico de la asignatura Ingeniería del Software III, del plan de estudios implantado en 1996 en ESIDE (Universidad de Deusto). Esta asignatura es troncal y se impartirá por primera vez a los alumnos de 5° durante el primer cuatrimestre del curso 2000-2001. Mediante su docencia, nuestra intención es acercar a los alumnos los conceptos involucrados en el desarrollo de software distribuido, así como afianzar algunos de ellos mediante las clases de laboratorio que describimos
Comments on "albayrak, M., & Allahverdy N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms. Expert Systems with Applications, 38(3), 1313-1320": A proposal of good practice
No full textThis short note presents a discussion arisen after reading "Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms", by Murat Albayrak and Novruz Allahverdi, (2011). Expert System with Applications (38) (pp. 1313-1320). The discussed paper presents a new greedy mutation operator to solve the well-known Traveling Salesman Problem. To prove the quality of their new operator, the authors compare different versions of a classical genetic algorithm, each of one with a different mutation operator. The experimentation shown by the authors can generate some controversy. In this short note, we explain the origin of this controversy and we bring a solution to prevent it in future publications.Peer reviewe
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