A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened Steel turning

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Design of in-building wireless networks deployments using evolutionary algorithms

In this article, a novel approach to deal with the design of in-building wireless networks deployments is proposed. This approach known as MOQZEA (Multiobjective Quality Zone Based Evolutionary Algorithm) is a hybr id evolutionary algorithm adapted to use a novel fitness function, based on the definition of quality zones for the different objective functions considered. This approach is conceived to solve wireless network design problems without previous information of the required number of transmitters, considering simultaneously a high number of objective functions and optimizing multiple configuration parameters of the transmitters.

Ypres rally network

Along of this document the reader could find a suitable network design and solution for the Rally Championship of Ypres meeting all the requirements set by the organization of the rally. These requirements have brought many problems in accordance with the network standards, because the area where the boxes are located is pretty large nevertheless technologies to solve those problems are detailed in the project. It has been included different designs in the project, each one of them based on distinct characteristic as they could be efficient, performance… , and the most important, since the organization of the rally is non-profit , the budget. Nevertheless we didn’t dismiss the use of long-lasting devices, as CISCO devices, despite their price. Furthermore a configuration of routing/switching devices has been explained for those who will be commanded to implement this solution. This solution is design to supply internet access as well as video streaming to all boxes for what teams can follow the championship in live time. The maximum connection of internet service provider (ISP) is 160Mbps, this bandwidth has to be distributed for the boxes dynamically. Finally to ensure the network works out it has to be monitored, this is reachable by using network analysis tools which in this project Wireshark has been chosen. RESUMEN. A lo largo de este documento, el lector encontrara un posible diseño y una posible solución para la red local del circuito de Rally celebrado en Ypres, cumpliendo con todos los requisitos y especificaciones establecidos por la organización. Estos requisitos han causado problemas de conformidad con los estándares de la red, debido a que la zona donde se encuentran los Boxes de los equipos es bastante larga, sin embargo las tecnologías para resolver esos problemas se detallan en este proyecto. Se han incluido diferentes diseños, cada uno de ellos centrado en aspectos diferentes así como la eficacia, el rendimiento, el presupuesto, etc... Esta solución está diseñada para suministrar acceso a Internet, así como la transmisión dinámica de video a todos los equipos para que puedan seguir la competición en tiempo real. Finalmente para controlar y asegurar que la red funciona, será monitorizada mediante herramientas de análisis de redes (Wireshark).

Independent modulation of engagement and connectivity of the facial network during affect processing by CACNA1C and ANK3 risk genes for bipolar disorder

IMPORTANCE Genome-wide association studies (GWASs) indicate that single-nucleotide polymorphisms in the CACNA1C and ANK3 genes increase the risk for bipolar disorder (BD). The genes influence neuronal firing by modulating calcium and sodium channel functions, respectively. Both genes modulate ?-aminobutyric acid-transmitting interneuron function and can thus affect brain regional activation and interregional connectivity. OBJECTIVE To determine whether the genetic risk for BD associated with 2 GWAS-supported risk single-nucleotide polymorphisms at CACNA1C rs1006737 and ANK3 rs10994336 is mediated through changes in regional activation and interregional connectivity of the facial affect-processing network. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional functional magnetic resonance imaging study at a research institute of 41 euthymic patients with BD and 46 healthy participants, all of British white descent. MAIN OUTCOMES AND MEASURES Blood oxygen level-dependent signal and effective connectivity measures during the facial affect-processing task. RESULTS In healthy carriers, both genetic risk variants were independently associated with increased regional engagement throughout the facial affect-processing network and increased effective connectivity between the visual and ventral prefrontal cortical regions. In contrast, BD carriers of either genetic risk variant exhibited pronounced reduction in ventral prefrontal cortical activation and visual-prefrontal effective connectivity. CONCLUSIONS AND RELEVANCE Our data demonstrate that the effect of CACNA1C rs1006737 and ANK3 rs10994336 (or genetic variants in linkage disequilibrium) on the brain converges on the neural circuitry involved in affect processing and provides a mechanism linking BD to genome-wide genetic risk variants.

Reconfiguration of supply chain network:an ISM-based roadmap to performance

Purpose: Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network. Design/methodology/approach: The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network. Findings: The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC. Practical implications: ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings. Originality/value: The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM. © Emerald Group Publishing Limited.

Neural network based off-line handwritten text recognition system

This dissertation introduces a new system for handwritten text recognition based on an improved neural network design. Most of the existing neural networks treat mean square error function as the standard error function. The system as proposed in this dissertation utilizes the mean quartic error function, where the third and fourth derivatives are non-zero. Consequently, many improvements on the training methods were achieved. The training results are carefully assessed before and after the update. To evaluate the performance of a training system, there are three essential factors to be considered, and they are from high to low importance priority: (1) error rate on testing set, (2) processing time needed to recognize a segmented character and (3) the total training time and subsequently the total testing time. It is observed that bounded training methods accelerate the training process, while semi-third order training methods, next-minimal training methods, and preprocessing operations reduce the error rate on the testing set. Empirical observations suggest that two combinations of training methods are needed for different case character recognition. Since character segmentation is required for word and sentence recognition, this dissertation provides also an effective rule-based segmentation method, which is different from the conventional adaptive segmentation methods. Dictionary-based correction is utilized to correct mistakes resulting from the recognition and segmentation phases. The integration of the segmentation methods with the handwritten character recognition algorithm yielded an accuracy of 92% for lower case characters and 97% for upper case characters. In the testing phase, the database consists of 20,000 handwritten characters, with 10,000 for each case. The testing phase on the recognition 10,000 handwritten characters required 8.5 seconds in processing time.

Robust infraestructure design in rapid transit rail systems

Incidents and rolling stock breakdowns are commonplace in rapid transit rail systems and may disrupt the system performance imposing deviations from planned operations. A network design model is proposed for reducing the effect of disruptions less likely to occur. Failure probabilities are considered functions of the amount of services and the rolling stock’s routing on the designed network so that they cannot be calculated a priori but result from the design process itself. A two recourse stochastic programming model is formulated where the failure probabilities are an implicit function of the number of services and routing of the transit lines.

Complex network theoretical analysis on information dissemination over vehicular networks

How to enhance the communication efficiency and quality on vehicular networks is one critical important issue. While with the larger and larger scale of vehicular networks in dense cities, the real-world datasets show that the vehicular networks essentially belong to the complex network model. Meanwhile, the extensive research on complex networks has shown that the complex network theory can both provide an accurate network illustration model and further make great contributions to the network design, optimization and management. In this paper, we start with analyzing characteristics of a taxi GPS dataset and then establishing the vehicular-to-infrastructure, vehicle-to-vehicle and the hybrid communication model, respectively. Moreover, we propose a clustering algorithm for station selection, a traffic allocation optimization model and an information source selection model based on the communication performances and complex network theory.

Cipher cities

Cipher Cities was a practice-led research project developed in 3 stages between 2005 and 2007 resulting in the creation of a unique online community, ‘Cipher Cities’, that provides simple authoring tools and processes for individuals and groups to create their own mobile events and event journals, build community profile and participate in other online community activities. Cipher Cities was created to revitalise peoples relationship to everyday places by giving them the opportunity and motivation to create and share complex digital stories in simple and engaging ways. To do so we developed new design processes and methods for both the research team and the end user to appropriate web and mobile technologies. To do so we collaborated with ethnographers, designers and ICT researchers and developers. In teams we ran a series of workshops in a wide variety of cities in Australia to refine an engagement process and to test a series of iteratively developed prototypes to refine the systems that supported community motivation and collaboration. The result of the research is 2 fold: 1. a sophisticated prototype for researchers and designers to further experiment with community engagement methodologies using existing and emerging communications technologies. 2. A ‘human dimensions matrix’. This matrix assists in the identification and modification of place based interventions in the social, technical, spatial, cultural, pedagogical conditions of any given community. This matrix has now become an essential part of a number of subsequent projects and assists design collaborators to successfully conceptualise, generate and evaluate interactive experiences. the research team employed practice-led action research methodologies that involved a collaborative effort across the fields of interaction design and social science, in particular ethnography, in order to: 1. seek, contest, refine a design methodology that would maximise the successful application of a dynamic system to create new kinds of interactions between people, places and artefacts’. 2. To design and deploy an application that intervenes in place-based and mobile technologies and offers people simple interfaces to create and share digital stories. Cipher Cities was awarded 3 separate CRC competitive grants (over $270,000 in total) to assist 3 stages of research covering the development of the Ethnographic Design Methodologies, the development of the tools, and the testing and refinement of both the engagement models and technologies. The resulting methodologies and tools are in the process of being commercialised by the Australasian CRC for Interaction Design.

Performance analysis of IEEE 802.11 DCF based WNCS networks

Wireless network technologies, such as IEEE 802.11 based wireless local area networks (WLANs), have been adopted in wireless networked control systems (WNCS) for real-time applications. Distributed real-time control requires satisfaction of (soft) real-time performance from the underlying networks for delivery of real-time traffic. However, IEEE 802.11 networks are not designed for WNCS applications. They neither inherently provide quality-of-service (QoS) support, nor explicitly consider the characteristics of the real-time traffic on networked control systems (NCS), i.e., periodic round-trip traffic. Therefore, the adoption of 802.11 networks in real-time WNCSs causes challenging problems for network design and performance analysis. Theoretical methodologies are yet to be developed for computing the best achievable WNCS network performance under the constraints of real-time control requirements. Focusing on IEEE 802.11 distributed coordination function (DCF) based WNCSs, this paper analyses several important NCS network performance indices, such as throughput capacity, round trip time and packet loss ratio under the periodic round trip traffic pattern, a unique feature of typical NCSs. Considering periodic round trip traffic, an analytical model based on Markov chain theory is developed for deriving these performance indices under a critical real-time traffic condition, at which the real-time performance constraints are marginally satisfied. Case studies are also carried out to validate the theoretical development.

Microstrip decoupling networks for low-order multi-port arrays with reduced element spacing

An array of monopole elements with reduced element spacing of λ/6 to λ/20 is considered for application in digital beam-forming and direction-finding. The small element spacing introduces strong mutual coupling between the array elements. This paper discusses that decoupling can be achieved analytically for arrays with three elements and describes Kuroda’s identities to realize the lumped elements of the derived decoupling network. Design procedures and equations are proposed. Experimental results are presented. The decoupled array has a bandwidth of 1% and a superdirective radiation pattern.

Structural optimization approach for specially shaped composite tank in spacecrafts

This study proposes an optimized approach of designing in which a model specially shaped composite tank for spacecrafts is built by applying finite element analysis. The composite layers are preliminarily designed by combining quasi-network design method with numerical simulation, which determines the ratio between the angle and the thickness of layers as the initial value of the optimized design. By adopting an adaptive simulated annealing algorithm, the angles and the numbers of layers at each angle are optimized to minimize the weight of structure. Based on this, the stacking sequence of composite layers is formulated according to the number of layers in the optimized structure by applying the enumeration method and combining the general design parameters. Numerical simulation is finally adopted to calculate the buckling limit of tanks in different designing methods. This study takes a composite tank with a cone-shaped cylinder body as example, in which ellipsoid head section and outer wall plate are selected as the object to validate this method. The result shows that the quasi-network design method can improve the design quality of composite material layer in tanks with complex preliminarily loading conditions. The adaptive simulated annealing algorithm can reduce the initial design weight by 30%, which effectively probes the global optimal solution and optimizes the weight of structure. It can be therefore proved that, this optimization method is capable of designing and optimizing specially shaped composite tanks with complex loading conditions.

E-learning intervention for STEM education: Developing country case study

This paper reports an innovative and systemic approach to implementing ICT intervention to support enhancement of teaching and learning of STEM subjects in developing countries. The need for adopting ICT was 2 fold: a lack of availability of qualified STEM secondary teachers and a lack of quality teaching and learning resources to assist teachers and students. ICT was seen as being able to impact on both issues. The intervention involved developing sustainable network design including equipment choices, providing high quality e-learning resources and human resource development including teacher training. The intervention has gradually been accepted by teachers, students, and parents and institutionalized as a key feature of the secondary STEM education in the case study country.