Intelligent ABS Fuzzy Controller for Diverse RoadSurfaces

Fuzzy controllers are potential candidates for the control of nonlinear, time variant and also complicated systems. Anti lock brake system (ABS) which is a nonlinear system, may not be easily controlled by classical control methods. An intelligent Fuzzy control method is very useful for this kind of nonlinear system. A typical antilock brake system (ABS) by sensing the wheel lockup, releases the brakes for a short period of time, and then reapplies again the brakes when the wheel spins up. In this paper, an intelligent fuzzy ABS controller is designed to adjust slipping performance for variety of roads. There are tow major sections in the proposing control system. First section consists of tow Fuzzy-Logic Controllers (FLC) providing optimal brake torque for both front and rear wheels. Second section which is also a FLC provides required amount of slip and torque references properties for different kind of roads. Simulation results of our proposed intelligent ABS for three different kinds of road show more reliable and better performance in compare with two other break systems.

Simulation of the Performance of Novel Nonlinear Optimal Control Technique on Two Cart-inverted Pendulum System

The two cart inverted pendulum system is a good bench mark for testing the performance of system dynamics and control engineering principles. Devasia introduced this system to study the asymptotic tracking problem for nonlinear systems. In this paper the problem of asymptotic tracking of the two-cart with an inverted-pendulum system to a sinusoidal reference inputs via introducing a novel method for solving finite-horizon nonlinear optimal control problems is presented. In this method, an iterative method applied to state dependent Riccati equation (SDRE) to obtain a reliable algorithm. The superiority of this technique has been shown by simulation and comparison with the nonlinear approach.

A Logic Approach to Database Dynamic Updating

We introduce a logic-based framework for database updating under constraints. In our framework, the constraints are represented as an instantiated extended logic program. When performing an update, database consistency may be violated. We provide an approach of maintaining database consistency, and study the conditions under which the maintenance process is deterministic. We show that the complexity of the computations and decision problems presented in our framework is in each case polynomial time.

Modeling User Behaviour by Planning

A model of user behaviour based automated planning is introduced in this work. The behaviour of users of web interactive systems can be described in term of a planning domain encapsulating the timed actions patterns representing the intended user profile. The user behaviour recognition is then posed as a planning problem where the goal is to parse a given sequence of user logs of the observed activities while reaching a final state. A general technique for transforming a timed finite state automata description of the behaviour into a numerical parameter planning model is introduced. Experimental results show that the performance of a planning based behaviour model is effective and scalable for real world applications. A major advantage of the planning based approach is to represent in a single automated reasoning framework problems of plan recognitions, plan synthesis and plan optimisation.

Contact Drying Simulation of Particulate Materials: A Comprehensive Approach

In this work, simulation algorithms for contact drying of agitated particulate materials under vacuum and at atmospheric pressure were developed. The implementation of algorithms gives a predictive estimation of drying rate curves and bulk bed temperature during contact drying. The calculations are based on the penetration model to describe the drying process, where all process parameters such as heat and mass transfer coefficients, effective bed properties, gas and liquid phase properties are estimated with proper correlations. Simulation results were compared with experimental data from the literature. In both cases, simulation results were in good agreement with experimental data. Few deviations were identified and the limitations of the predictive capabilities of the models are discussed. The programs give a good insight of the drying behaviour of the analysed powders.

Corporate Culture and Innovation: Implications for Reward Systems

Continuous innovation is becoming a necessity if firms want to stay competitive. Different factors influence the rate of innovation in a firm, among which corporate culture has often been recognized among the most important factors. In this paper we argue that the development of corporate culture that will support and foster innovation must be accompanied with an appropriate reward system. A research conducted among Croatian firms showed that a statistically significant relationship exists among corporate culture that supports innovations and reward system features.

The Measurement of Endogenous Higher-Order Formative Composite Variables in PLS-SEM: An Empirical Application from CRM System Development

In recent methodological articles related to structural equation modeling (SEM), the question of how to measure endogenous formative variables has been raised as an urgent, unresolved issue. This research presents an empirical application from the CRM system development context to test a recently developed technique, which makes it possible to measure endogenous formative constructs in structural models. PLS path modeling is used to demonstrate the feasibility of measuring antecedent relationships at the formative indicator level, not the formative construct level. Empirical results show that this technique is a promising approach to measure antecedent relationships of formative constructs in SEM.

A Probability based Pair Extension Method in Protein 2-DE Gel Image Analysis

The two-dimensional gel electrophoresis method (2-DE) is widely used in Proteomics to separate thousands of proteins in a sample. By comparing the protein expression levels of proteins in a normal sample with those in a diseased one, it is possible to identify a meaningful set of marker proteins for the targeted disease. The major shortcomings of this approach involve inherent noises and irregular geometric distortions of spots observed in 2-DE images. Various experimental conditions can be the major causes of these problems. In the protein analysis of samples, these problems eventually lead to incorrect conclusions. In order to minimize the influence of these problems, this paper proposes a partition based pair extension method that performs spot-matching on a set of gel images multiple times and segregates more reliable mapping results which can improve the accuracy of gel image analysis. The improved accuracy of the proposed method is analyzed through various experiments on real 2-DE images of human liver tissues.

A User - Requirements Approach in Medical Devices Maintenance System Development: A Case Study from an Industry Perspective

This paper is a part of research, in which the way the biomedical engineers follow in their work is analyzed. The goal of this paper is to present a method for specification of user requirements in the medical devices maintenance process. Data Gathering Methods, Research Model Phases and Descriptive Analysis is presented. These technology and verification rules can be implemented in Medical devices maintenance management process to the maintenance process.

Development of Maximum Entropy Method for Prediction of Droplet-size Distribution in Primary Breakup Region of Spray

Droplet size distributions in the cold spray of a fuel are important in observed combustion behavior. Specification of droplet size and velocity distributions in the immediate downstream of injectors is also essential as boundary conditions for advanced computational fluid dynamics (CFD) and two-phase spray transport calculations. This paper describes the development of a new model to be incorporated into maximum entropy principle (MEP) formalism for prediction of droplet size distribution in droplet formation region. The MEP approach can predict the most likely droplet size and velocity distributions under a set of constraints expressing the available information related to the distribution. In this article, by considering the mechanisms of turbulence generation inside the nozzle and wave growth on jet surface, it is attempted to provide a logical framework coupling the flow inside the nozzle to the resulting atomization process. The purpose of this paper is to describe the formulation of this new model and to incorporate it into the maximum entropy principle (MEP) by coupling sub-models together using source terms of momentum and energy. Comparison between the model prediction and experimental data for a gas turbine swirling nozzle and an annular spray indicate good agreement between model and experiment.

Detecting Older Drivers- Stress Level during Real-World Driving Tasks

This paper presents the effect of driving a motor vehicle on the stress levels of older drivers, indicated by monitoring their hear rate increase whilst completing various everyday driving tasks. Results suggest that whilst older female drivers heart rate varied more significantly than males, the actual age of a participant did not result in a significant change in heart rate due to stress, within the age group tested. The analysis of the results indicates the most stressful manoeuvres undertaken by the older drivers and highlights the tasks which were found difficult with a view to implementing technologies to aid the more senior driver in automotive travel.

Modeling and Simulation of a Hybrid Scooter

This paper presents a hybrid electric scooter model developed and simulated using Matlab/Simulink. This hybrid scooter modeled has a parallel hybrid structure. The main propulsion units consist of a two stroke internal combustion engine and a hub motor attached to the front wheel of the scooter. The methodology used to optimize the energy and fuel consumption of the hybrid electric scooter is the multi-mode approach. Various case studies were presented to check the model and were compared to the literatures. Results shown that the model developed was feasible and valuable.

Assessment of Sediment Quality in the West Port Based On the Index Analysis Approach

The coastal sediments of West Port of Malaysia was monitored from Nov. 2009 to Oct. 2010 to assess spatial distribution of heavy metals As, Cu, Cd, Cr, Hg, Ni, Zn and Pb. Sediment samples were collected from 10 stations in dry and rainy season in West Port. The range concentrations measured (Mg/g dry weight ) were from 23.4 to 98.3 for Zn, 22.3 to 80 for Pb, 7.4 to 27.6 Cu, 0.244 to 3.53 for Cd, 7.2 to 22.2 for Ni, 20.2 to 162 for As, 0.11 to 0.409 for Hg and 11.5 to 61.5 for Cr. The geochemical indexes used in this study were Geoaccumulation (Igeo), Contamination Factor (CF) and Pollution Load Index (PLI); these indexes were used to evaluate the levels of sediment contaminations. The results of these indexes show that, the status of West Port sediment quality are moderately polluted by heavy metals except in arsenic which shows the high level of pollution.

Application of Wireless Visual Sensor for Semi- Autonomous Mine Navigation System

The present paper represent the efforts undertaken for the development of an semi-automatic robot that may be used for various post-disaster rescue operation planning and their subsequent execution using one-way communication of video and data from the robot to the controller and controller to the robot respectively. Wireless communication has been used for the purpose so that the robot may access the unapproachable places easily without any difficulties. It is expected that the information obtained from the robot would be of definite help to the rescue team for better planning and execution of their operations.

Dynamic Bayesian Networks Modeling for Inferring Genetic Regulatory Networks by Search Strategy: Comparison between Greedy Hill Climbing and MCMC Methods

Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data is one of the major paradigms for inferring the interactions among genes. Averaging a collection of models for predicting network is desired, rather than relying on a single high scoring model. In this paper, two kinds of model searching approaches are compared, which are Greedy hill-climbing Search with Restarts (GSR) and Markov Chain Monte Carlo (MCMC) methods. The GSR is preferred in many papers, but there is no such comparison study about which one is better for DBN models. Different types of experiments have been carried out to try to give a benchmark test to these approaches. Our experimental results demonstrated that on average the MCMC methods outperform the GSR in accuracy of predicted network, and having the comparable performance in time efficiency. By proposing the different variations of MCMC and employing simulated annealing strategy, the MCMC methods become more efficient and stable. Apart from comparisons between these approaches, another objective of this study is to investigate the feasibility of using DBN modeling approaches for inferring gene networks from few snapshots of high dimensional gene profiles. Through synthetic data experiments as well as systematic data experiments, the experimental results revealed how the performances of these approaches can be influenced as the target gene network varies in the network size, data size, as well as system complexity.

Influence of Combined Drill Coulters on Seedbed Compaction under Conservation Tillage Technologies

All over the world, including the Middle and East European countries, sustainable tillage and sowing technologies are applied increasingly broadly with a view to optimising soil resources, mitigating soil degradation processes, saving energy resources, preserving biological diversity, etc. As a result, altered conditions of tillage and sowing technological processes are faced inevitably. The purpose of this study is to determine the seedbed topsoil hardness when using a combined sowing coulter in different sustainable tillage technologies. The research involved a combined coulter consisting of two dissected blade discs and a shoe coulter. In order to determine soil hardness at the seedbed area, a multipenetrometer was used. It was found by experimental studies that in loosened soil, a combined sowing coulter equally suppresses the furrow bottom, walls and soil near the furrow; therefore, here, soil hardness was similar at all researched depths and no significant differences were established. In loosened and compacted (double-rolled) soil, the impact of a combined coulter on the hardness of seedbed soil surface was more considerable at a depth of 2 mm. Soil hardness at the furrow bottom and walls to a distance of up to 26 mm was 1.1 MPa. At a depth of 10 mm, the greatest hardness was established at the furrow bottom. In loosened and heavily compacted (rolled for 6 times) soil, at a depth of 2 and 10 mm a combined coulter most of all compacted the furrow bottom, which has a hardness of 1.8 MPa. At a depth of 20 mm, soil hardness within the whole investigated area varied insignificantly and fluctuated by around 2.0 MPa. The hardness of furrow walls and soil near the furrow was by approximately 1.0 MPa lower than that at the furrow bottom

The Content of Acrylamide in Deep-fat Fried, Shallow Fried and Roasted Potatoes

Potato is one of the main components of warm meals in Latvia. Consumption of fried potatoes in Latvia is the highest comparing to Nordic and other Baltic countries. Therefore acrylamide (AA) intake coming from fried potatoes in population might be high as well. The aim of the research was to determine AA content in traditionally cooked potatoes bred and cultivated in Latvia. Five common Latvian potato varieties were selected: Lenora, Brasla, Imanta, Zile and Madara. A two-year research was conducted during two periods: just after harvesting and after six months of storage. The following cooking methods were used: shallow frying (150 ± 5 °C); deep-fat frying (180 ± 5 °C) and roasting (210 ± 5 °C). Time and temperature was recorded during frying. AA was extracted from potatoes by solid phase extraction and AA content was determined by LC-MS/MS. AA content significantly differs (p

Data Mining on the Router Logs for Statistical Application Classification

With the advance of information technology in the new era the applications of Internet to access data resources has steadily increased and huge amount of data have become accessible in various forms. Obviously, the network providers and agencies, look after to prevent electronic attacks that may be harmful or may be related to terrorist applications. Thus, these have facilitated the authorities to under take a variety of methods to protect the special regions from harmful data. One of the most important approaches is to use firewall in the network facilities. The main objectives of firewalls are to stop the transfer of suspicious packets in several ways. However because of its blind packet stopping, high process power requirements and expensive prices some of the providers are reluctant to use the firewall. In this paper we proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. By discriminating these data, an administrator may take an approach action against the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Covering-based Rough sets Based on the Refinement of Covering-element

Covering-based rough sets is an extension of rough sets and it is based on a covering instead of a partition of the universe. Therefore it is more powerful in describing some practical problems than rough sets. However, by extending the rough sets, covering-based rough sets can increase the roughness of each model in recognizing objects. How to obtain better approximations from the models of a covering-based rough sets is an important issue. In this paper, two concepts, determinate elements and indeterminate elements in a universe, are proposed and given precise definitions respectively. This research makes a reasonable refinement of the covering-element from a new viewpoint. And the refinement may generate better approximations of covering-based rough sets models. To prove the theory above, it is applied to eight major coveringbased rough sets models which are adapted from other literature. The result is, in all these models, the lower approximation increases effectively. Correspondingly, in all models, the upper approximation decreases with exceptions of two models in some special situations. Therefore, the roughness of recognizing objects is reduced. This research provides a new approach to the study and application of covering-based rough sets.

A Pairing-based Blind Signature Scheme with Message Recovery

Blind signatures enable users to obtain valid signatures for a message without revealing its content to the signer. This paper presents a new blind signature scheme, i.e. identity-based blind signature scheme with message recovery. Due to the message recovery property, the new scheme requires less bandwidth than the identitybased blind signatures with similar constructions. The scheme is based on modified Weil/Tate pairings over elliptic curves, and thus requires smaller key sizes for the same level of security compared to previous approaches not utilizing bilinear pairings. Security and efficiency analysis for the scheme is provided in this paper.