Learning Classifier Systems Approach for Automated Discovery of Censored Production Rules

In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Error Correction Codes in Wireless Sensor Network: An Energy Aware Approach

Link reliability and transmitted power are two important design constraints in wireless network design. Error control coding (ECC) is a classic approach used to increase link reliability and to lower the required transmitted power. It provides coding gain, resulting in transmitter energy savings at the cost of added decoder power consumption. But the choice of ECC is very critical in the case of wireless sensor network (WSN). Since the WSNs are energy constraint in nature, both the BER and power consumption has to be taken into count. This paper develops a step by step approach in finding suitable error control codes for WSNs. Several simulations are taken considering different error control codes and the result shows that the RS(31,21) fits both in BER and power consumption criteria.

Performance Analysis of a Free-Space Optical Code Division Multiple Access through Atmospheric Turbulence Channel

In this paper, the effect of atmospheric turbulence on bit error probability in free-space optical CDMA scheme with Sequence Inverse Keyed (SIK) optical correlator receiver is analyzed. Here Intensity Modulation scheme is considered for transmission. The turbulence induced fading is described by the newly introduced gamma-gamma pdf[1] as a tractable mathematical model for atmospheric turbulence. Results are evaluated with Gold and Kasami code & it is shown that Gold sequence can be used for more efficient transmission than Kasami sequence in an atmospheric turbulence channel.

Multi-View Neural Network Based Gait Recognition

Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.

A Combined Practical Approach to Condition Monitoring of Reciprocating Compressors using IAS and Dynamic Pressure

A Comparison and evaluation of the different condition monitoring (CM) techniques was applied experimentally on RC e.g. Dynamic cylinder pressure and crankshaft Instantaneous Angular Speed (IAS), for the detection and diagnosis of valve faults in a two - stage reciprocating compressor for a programme of condition monitoring which can successfully detect and diagnose a fault in machine. Leakage in the valve plate was introduced experimentally into a two-stage reciprocating compressor. The effect of the faults on compressor performance was monitored and the differences with the normal, healthy performance noted as a fault signature been used for the detection and diagnosis of faults. The paper concludes with what is considered to be a unique approach to condition monitoring. First, each of the two most useful techniques is used to produce a Truth Table which details the circumstances in which each method can be used to detect and diagnose a fault. The two Truth Tables are then combined into a single Decision Table to provide a unique and reliable method of detection and diagnosis of each of the individual faults introduced into the compressor. This gives accurate diagnosis of compressor faults.

Effect of Real Wastewater on Biotransformation of 17α-ethynylestradiol by Ammonia-Oxidizing Bacteria in Nitrifying Activated Sludge

17α-ethynylestradiol (EE2) is a synthetic estrogen used as a key ingredient in an oral contraceptives pill. EE2 is an endocrine disrupting compound, high in estrogenic potency. Although EE2 exhibits low degree of biodegradability with common microorganisms in wastewater treatment plants (WWTPs), this compound can be biotransformed by ammonia-oxidizing bacteria (AOB) via a co-metabolism mechanism in WWTPs. This study aimed to investigate the effect of real wastewater on biotransformation of EE2 by AOB. A preliminary experiment on the effect of nitrite and pH levels on abiotic transformation of EE2 suggested that the abiotic transformation occurred at only pH

Targeting the Pulmonary Delivery via Optimizing Physicochemical Characteristics of Instilled Liquid and Exploring Distribution of Produced Liquids by Bench-Top Models and Scintigraphy of Rabbits- Lungs

We aimed to investigate how can target and optimize pulmonary delivery distribution by changing physicochemical characteristics of instilled liquid.Therefore, we created a new liquids group: a. eligible for desired distribution within lung because of assorted physicochemical characteristics b. capable of being augmented with a broad range of chemicals inertly c. no interference on respiratory function d. compatible with airway surface liquid We developed forty types of new liquid,were composed of Carboxymethylcellulose sodium,Glycerin and different types of Polysorbates.Viscosity was measured using a Programmable Rheometer and surface tension by KRUSS Tensiometer.We subsequently examined the liquids and delivery protocols by simple and branched glass capillary tube models of airways.Eventually,we explored pulmonary distribution of liquids being augmented with technetium-99m in mechanically ventilated rabbits.We used a single head large field of view gamma camera.Kinematic viscosity between 0.265Stokes and 0.289Stokes,density between 1g/cm3 and 1.5g/cm3 and surface tension between 25dyn/cm and 35dyn/cm were the most acceptable.

Fast and Accurate Reservoir Modeling: Genetic Algorithm versus DIRECT Method

In this paper, two very different optimization algorithms, Genetic and DIRECT algorithms, are used to history match a bottomhole pressure response for a reservoir with wellbore storage and skin with the best possible analytical model. No initial guesses are available for reservoir parameters. The results show that the matching process is much faster and more accurate for DIRECT method in comparison with Genetic algorithm. It is furthermore concluded that the DIRECT algorithm does not need any initial guesses, whereas Genetic algorithm needs to be tuned according to initial guesses.

M-Learning the Next Generation of Education in Cyberspace

The technology usages of high speed Internet leads to establish and start new era of online education. With the advancement of the information technology and communication systems new opportunities have been created. This leads universities to have various online education channels to meet the demand of different learners- needs. One of these channels is M-learning, which can be used to improve the online education environment. With using such mobile technology in learning both students and instructors can easily access educational courses anytime from anywhere. The paper first presents literature about mobile learning and to what extent this approach can be utilized to enhance the overall learning system. It provides a comparison between mobile learning and traditional elearning showing the wide array of benefits of the new generation of technology. The possible challenges and potential advantages of Mlearning in the online education system are also discussed.

Tidal Flow Patterns Near A Coastal Headland

Experimental investigations were carried out in the Manchester Tidal flow Facility (MTF) to study the flow patterns in the region around and adjacent to a hypothetical headland in tidal (oscillatory) ambient flow. The Planar laser-induced fluorescence (PLIF) technique was used for visualization, with fluorescent dye released at specific points around the headland perimeter and in its adjacent recirculation zone. The flow patterns can be generalized into the acceleration, stable flow and deceleration stages for each halfcycle, with small variations according to location, which are more distinct for low Keulegan-Carpenter number (KC) cases. Flow patterns in the mixing region are unstable and complex, especially in the recirculation zone. The flow patterns are in agreement with previous visualizations, and support previous results in steady ambient flow. It is suggested that the headland lee could be a viable location for siting of pollutant outfalls.

Application of Phase Change Materials (PCMs) in Maintaining Comfort Temperature inside an Automobile

This paper presents the modeling results of an innovative system for the temperature control in the interior compartment of a stationary automobile facing the solar energy from the sun. A very thin layer of PCM inside a pouch placed in the ceiling of the car in which the heating energy is absorbed and release with melting and solidification of phase change materials. As a result the temperature of the car interior is maintained in the comfort condition. The amount of required PCM has been calculated to be about 755 g. The PCM-temperature controlling system is simple and has a potential to be implemented as a practical solution to prevent undesirable heating of the automobile-s cabin.

Atomic Force Microscopy (AFM)Topographical Surface Characterization of Multilayer-Coated and Uncoated Carbide Inserts

In recent years, scanning probe atomic force microscopy SPM AFM has gained acceptance over a wide spectrum of research and science applications. Most fields focuses on physical, chemical, biological while less attention is devoted to manufacturing and machining aspects. The purpose of the current study is to assess the possible implementation of the SPM AFM features and its NanoScope software in general machining applications with special attention to the tribological aspects of cutting tool. The surface morphology of coated and uncoated as-received carbide inserts is examined, analyzed, and characterized through the determination of the appropriate scanning setting, the suitable data type imaging techniques and the most representative data analysis parameters using the MultiMode SPM AFM in contact mode. The NanoScope operating software is used to capture realtime three data types images: “Height", “Deflection" and “Friction". Three scan sizes are independently performed: 2, 6, and 12 μm with a 2.5 μm vertical range (Z). Offline mode analysis includes the determination of three functional topographical parameters: surface “Roughness", power spectral density “PSD" and “Section". The 12 μm scan size in association with “Height" imaging is found efficient to capture every tiny features and tribological aspects of the examined surface. Also, “Friction" analysis is found to produce a comprehensive explanation about the lateral characteristics of the scanned surface. Configuration of many surface defects and drawbacks has been precisely detected and analyzed.

Behavioral Analysis of Team Members in Virtual Organization based on Trust Dimension and Learning

Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

A Fast Handover Scheme for Proxy Mobile IPv6 using IEEE 802.21 Media Independent Handover

In this paper, to resolve the problem of existing schemes, an alternative fast handover Proxy Mobile IPv6 (PMIPv6) scheme using the IEEE 802.21 Media Independent Handover (MIH) function is proposed for heterogeneous wireless networks. The proposed scheme comes to support fast handover for the mobile node (MN) irrespective of the presence or absence of MIH functionality as well as L3 mobility functionality, whereas the MN in existing schemes has to implement MIH functionality. That is, the proposed scheme does not require the MN to be involved in MIH related signaling required for handover procedure. The base station (BS) with MIH functionality performs handover on behalf of the MN. Therefore, the proposed scheme can reduce burden and power consumption of MNs with limited resource and battery power since MNs are not required to be involved for the handover procedure. In addition, the proposed scheme can reduce considerably traffic overhead over wireless links between MN and BS since signaling messages are reduced.

Quadratic Pulse Inversion Ultrasonic Imaging(QPI): A Two-Step Procedure for Optimization of Contrast Sensitivity and Specificity

We have previously introduced an ultrasonic imaging approach that combines harmonic-sensitive pulse sequences with a post-beamforming quadratic kernel derived from a second-order Volterra filter (SOVF). This approach is designed to produce images with high sensitivity to nonlinear oscillations from microbubble ultrasound contrast agents (UCA) while maintaining high levels of noise rejection. In this paper, a two-step algorithm for computing the coefficients of the quadratic kernel leading to reduction of tissue component introduced by motion, maximizing the noise rejection and increases the specificity while optimizing the sensitivity to the UCA is presented. In the first step, quadratic kernels from individual singular modes of the PI data matrix are compared in terms of their ability of maximize the contrast to tissue ratio (CTR). In the second step, quadratic kernels resulting in the highest CTR values are convolved. The imaging results indicate that a signal processing approach to this clinical challenge is feasible.

Design, Fabrication and Performance Evaluation of Mobile Engine-Driven Pneumatic Paddy Collector

A simple mobile engine-driven pneumatic paddy collector made of locally available materials using local manufacturing technology was designed, fabricated, and tested for collecting and bagging of paddy dried on concrete pavement. The pneumatic paddy collector had the following major components: radial flat bladed type centrifugal fan, power transmission system, bagging area, frame and the conveyance system. Results showed significant differences on the collecting capacity, noise level, and fuel consumption when rotational speed of the air mover shaft was varied. Other parameters such as collecting efficiency, air velocity, augmented cracked grain percentage, and germination rate were not significantly affected by varying rotational speed of the air mover shaft. The pneumatic paddy collector had a collecting efficiency of 99.33 % with a collecting capacity of 2685.00 kg/h at maximum rotational speed of centrifugal fan shaft of about 4200 rpm. The machine entailed an investment cost of P 62,829.25. The break-even weight of paddy was 510,606.75 kg/yr at a collecting cost of 0.11 P/kg of paddy. Utilizing the machine for 400 hours per year generated an income of P 23,887.73. The projected time needed to recover cost of the machine based on 2685 kg/h collecting capacity was 2.63 year.

Possibilistic Clustering Technique-Based Traffic Light Control for Handling Emergency Vehicle

A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good managementof the crossroad. In this paper, we develop a new approach based onthe technique of clustering and the graphical possibilistic fusionmodeling. So, the proposed model is elaborated in three phases. Thefirst one consists to decompose the environment into clusters,following by the fusion intra and inter clusters processes. Finally, wewill show some experimental results by simulation that proves theefficiency of our proposed approach.KeywordsTraffic light, Wireless sensor network, Controller,Possibilistic network/Bayesain network.

The Contribution of Growth Rate to the Pathogenicity of Candida spp.

Fungal infections are becoming more common and the range of susceptible individuals has expanded. While Candida albicans remains the most common infective species, other Candida spp. are becoming increasingly significant. In a range of large-scale studies of candidaemia between 1999 and 2006, about 52% of 9717 cases involved C. albicans, about 30% involved either C. glabrata or C. parapsilosis and less than 15% involved C. tropicalis, C. krusei or C. guilliermondii. However, the probability of mortality within 30 days of infection with a particular species was at least 40% for C. tropicalis, C. albicans, C. glabrata and C. krusei and only 22% for C. parapsilopsis. Clinical isolates of Candida spp. grew at rates ranging from 1.65 h-1 to 4.9 h-1. Three species (C. krusei, C. albicans and C. glabrata) had relatively high growth rates (μm > 4 h-1), C. tropicalis and C. dubliniensis grew moderately quickly (Ôëê 3 h-1) and C. parapsilosis and C. guilliermondii grew slowly (< 2 h-1). Based on these data, the log of the odds of mortality within 30 days of diagnosis was linearly related to μm. From this the underlying probability of mortality is 0.13 (95% CI: 0.10-0.17) and it increases by about 0.09 ± 0.02 for each unit increase in μm. Given that the overall crude mortality is about 0.36, the growth of Candida spp. approximately doubles the rate, consistent with the results of larger case-matched studies of candidaemia.

An Efficient MIPv6 Return Routability Scheme Based on Geometric Computing

IETF defines mobility support in IPv6, i.e. MIPv6, to allow nodes to remain reachable while moving around in the IPv6 internet. When a node moves and visits a foreign network, it is still reachable through the indirect packet forwarding from its home network. This triangular routing feature provides node mobility but increases the communication latency between nodes. This deficiency can be overcome by using a Binding Update (BU) scheme, which let nodes keep up-to-date IP addresses and communicate with each other through direct IP routing. To further protect the security of BU, a Return Routability (RR) procedure was developed. However, it has been found that RR procedure is vulnerable to many attacks. In this paper, we will propose a lightweight RR procedure based on geometric computing. In consideration of the inherent limitation of computing resources in mobile node, the proposed scheme is developed to minimize the cost of computations and to eliminate the overhead of state maintenance during binding updates. Compared with other CGA-based BU schemes, our scheme is more efficient and doesn-t need nonce tables in nodes.

Binary Classification Tree with Tuned Observation-based Clustering

There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.