Locating Center Points for Radial Basis Function Networks Using Instance Reduction Techniques

The behavior of Radial Basis Function (RBF) Networks greatly depends on how the center points of the basis functions are selected. In this work we investigate the use of instance reduction techniques, originally developed to reduce the storage requirements of instance based learners, for this purpose. Five Instance-Based Reduction Techniques were used to determine the set of center points, and RBF networks were trained using these sets of centers. The performance of the RBF networks is studied in terms of classification accuracy and training time. The results obtained were compared with two Radial Basis Function Networks: RBF networks that use all instances of the training set as center points (RBF-ALL) and Probabilistic Neural Networks (PNN). The former achieves high classification accuracies and the latter requires smaller training time. Results showed that RBF networks trained using sets of centers located by noise-filtering techniques (ALLKNN and ENN) rather than pure reduction techniques produce the best results in terms of classification accuracy. The results show that these networks require smaller training time than that of RBF-ALL and higher classification accuracy than that of PNN. Thus, using ALLKNN and ENN to select center points gives better combination of classification accuracy and training time. Our experiments also show that using the reduced sets to train the networks is beneficial especially in the presence of noise in the original training sets.

Fabrication and Characterization of Al/Methyl Orange/n-Si Heterojunction Diode

Herein, the organic semiconductor methyl orange (MO), is investigated for the first time for its electronic applications. For this purpose, Al/MO/n-Si heterojunction is fabricated through economical cheap and simple “drop casting” technique. The currentvoltage (I-V) measurements of the device are made at room temperature under dark conditions. The I-V characteristics of Al/MO/n-Si junction exhibits asymmetrical and rectifying behavior that confirms the formation of diode. The diode parameters such as rectification ratio (RR), turn on voltage (Vturn on), reverse saturation current (I0), ideality factor (n), barrier height ( b f ), series resistance (Rs) and shunt resistance (Rsh) are determined from I-V curves using Schottky equations. These values of these parameters are also extracted and verified by applying Cheung’s functions. The conduction mechanisms are explained from the forward bias I-V characteristics using the power law.

Performance Improvement of a Supersonic External Compression Inlet by Heat Source Addition

Heat source addition to the axisymmetric supersonic inlet may improve the performance parameters, which will increase the inlet efficiency. In this investigation the heat has been added to the flow field at some distance ahead of an axisymmetric inlet by adding an imaginary thermal source upstream of cowl lip. The effect of heat addition on the drag coefficient, mass flow rate and the overall efficiency of the inlet have been investigated. The results show that heat addition causes flow separation, hence to prevent this phenomena, roughness has been added on the spike surface. However, heat addition reduces the drag coefficient and the inlet mass flow rate considerably. Furthermore, the effects of position, size, and shape on the inlet performance were studied. It is found that the thermal source deflects the flow streamlines. By improper location of the thermal source, the optimum condition has been obtained. For the optimum condition, the drag coefficient is considerably reduced and the inlet mass flow rate and its efficiency have been increased slightly. The optimum shape of the heat source is obtained too.

Design of High Gain, High Bandwidth Op-Amp for Reduction of Mismatch Currents in Charge Pump PLL in 180 nm CMOS Technology

The designing of charge pump with high gain Op- Amp is a challenging task for getting faithful response .Design of high performance phase locked loop require ,a design of high performance charge pump .We have designed a operational amplifier for reducing the error caused by high speed glitch in a transistor and mismatch currents . A separate Op-Amp has designed in 180 nm CMOS technology by CADENCE VIRTUOSO tool. This paper describes the design of high performance charge pump for GHz CMOS PLL targeting orthogonal frequency division multiplexing (OFDM) application. A high speed low power consumption Op-Amp with more than 500 MHz bandwidth has designed for increasing the speed of charge pump in Phase locked loop.

Effects of Human Capital and Openness on Economic Growth of Developed and Developing Countries: A Panel Data Analysis

Technology transfer by international trade and foreign direct investment is the most important positive outcome of open economy. It is widely accepted that new technology and knowledge have an important role in enhancing economic growth. Human capital is the other important factor assisting economic growth. In this study, the role of human capital in the growth process is examined in a view of new endogenous growth theory emphasizing on the technology transfer resulting from international trade. Using the panel data of 10 developed and 10 developing countries, impact of human capital and openness on the rate of economic growth of different countries is analysed. Evidence suggests the view that human capital and openness contribute to the economic growth in both developing and developed countries, but with different rates.

Microbubbles Enhanced Synthetic Phorbol Ester Degradation by Ozonolysis

A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil might also be used as a foodstuff due to its significant nutrition content. The limitations for utilizing the oil as a foodstuff are mainly due to a toxicity of PE. Currently, a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence. Ozone is considered as a strong oxidative agent. It reacts with PE by attacking the carbon-carbon double bond of PE. This modification of PE molecular structure yields a non toxic ester with high lipid content. This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is an application for a new microscale plasma unit to ozone production and the technology permits ozone injection to the water-TPA mixture in form of microbubbles. The efficacy of a heterogeneous process depends on the diffusion coefficient which can be controlled by contact time and interfacial area. The low velocity of rising microbubbles and high surface to volume ratio allow efficient mass transfer to be achieved during the process. Direct injection of ozone is the most efficient way to process with such highly reactive and short lived chemical. Data on the plasma unit behavior are presented and the influence of gas oscillation technology on the microbubble production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.

Heuristic Search Algorithms for Tuning PUMA 560 Fuzzy PID Controller

This paper compares the heuristic Global Search Techniques; Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Generalized Pattern Search, genetic algorithm hybridized with Nelder–Mead and Generalized pattern search technique for tuning of fuzzy PID controller for Puma 560. Since the actual control is in joint space ,inverse kinematics is used to generate various joint angles correspoding to desired cartesian space trajectory. Efficient dynamics and kinematics are modeled on Matlab which takes very less simulation time. Performances of all the tuning methods with and without disturbance are compared in terms of ITSE in joint space and ISE in cartesian space for spiral trajectory tracking. Genetic Algorithm hybridized with Generalized Pattern Search is showing best performance.

Optimising Business Rules in the Services Sector

Business rules are widely used within the services sector. They provide consistency and allow relatively unskilled staff to process complex transactions correctly. But there are many examples where the rules themselves have an impact on the costs and profits of an organisation. Financial services, transport and human services are areas where the rules themselves can impact the bottom line in a predictable way. If this is the case, how can we find that set of rules that maximise profit, performance or customer service, or any other key performance indicators? The manufacturing, energy and process industries have embraced mathematical optimisation techniques to improve efficiency, increase production and so on. This paper explores several real world (but simplified) problems in the services sector and shows how business rules can be optimised. It also examines the similarities and differences between the service and other sectors, and how optimisation techniques could be used to deliver similar benefits.

A Low Cost Knowledge Base System Framework for Design of Deep Drawing Die

In this paper a low cost knowledge base system (KBS) framework is proposed for design of deep drawing die and procedure for developing system modules. The task of building the system is structured into different modules for major activities of design of deep drawing die. A manufacturability assessment module of the proposed framework is developed to check the manufacturability of deep drawn parts. The technological knowledge is represented by using IF- THEN rules and it is coded in AutoLISP language. The module is designed to be loaded into the prompt area of AutoCAD. The cost of implementation of proposed system makes it affordable for small and medium scale sheet metal industries.

Sweethearting: The Complicity Relatives Theft CRT in Saudi Arabia

The study will search the level of existence of the sweethearting in Saudi Arabia's Supermarkets in Riyadh. Sweethearting occurs when frontline workers give unauthorized free or uncounted goods and services to customer-s conspirators. The store managers and /or security managers were asked about the sweethearting that occurs in the supermarkets. The characteristics of sweethearting in Riyadh stores were investigated. Two independent variables were related to the report of sweethearting. These independent variables are: The effect of store environment on sweethearting and the security techniques and loss prevention electronics techniques used. This study expected to shed the light about the level of sweethearting in Saudi Arabia and the factors behind it. This study will serve as an exploratory study for such phenomenon in Saudi Arabia as well as both descriptive for the characteristics of sweethearting and explanatory study to link between the environmental and security systems factors to sweethearting.

Optimal Solution of Constraint Satisfaction Problems

An optimal solution for a large number of constraint satisfaction problems can be found using the technique of substitution and elimination of variables analogous to the technique that is used to solve systems of equations. A decision function f(A)=max(A2) is used to determine which variables to eliminate. The algorithm can be expressed in six lines and is remarkable in both its simplicity and its ability to find an optimal solution. However it is inefficient in that it needs to square the updated A matrix after each variable elimination. To overcome this inefficiency the algorithm is analyzed and it is shown that the A matrix only needs to be squared once at the first step of the algorithm and then incrementally updated for subsequent steps, resulting in significant improvement and an algorithm complexity of O(n3).

UWB Bowtie Slot Antenna for Breast Cancer Detection

UWB is a very attractive technology for many applications. It provides many advantages such as fine resolution and high power efficiency. Our interest in the current study is the use of UWB radar technique in microwave medical imaging systems, especially for early breast cancer detection. The Federal Communications Commission FCC allowed frequency bandwidth of 3.1 to 10.6 GHz for this purpose. In this paper we suggest an UWB Bowtie slot antenna with enhanced bandwidth. Effects of varying the geometry of the antenna on its performance and bandwidth are studied. The proposed antenna is simulated in CST Microwave Studio. Details of antenna design and simulation results such as return loss and radiation patterns are discussed in this paper. The final antenna structure exhibits good UWB characteristics and has surpassed the bandwidth requirements.

Textile Technology: Application in Sport and Medicine

Sport is one of the sectors in which the largest technical projections regarding the functions of textiles can be found. He is a large consumer of high performance composite materials and new fibers. It is one of the sectors where the innovation is the most important when the greatest numbers of spectacular developments are aimed at increasing performance. In medicine, textile innovation is used and contributes in the amelioration of different materials such as dressing, orthosis, bandages, etc. The hygienic textiles in non-woven materials record a strong growth. The objective of this study is to show the different advances of development we obtained in the both ways (sport and medicine). Polyamide fibers where developed tacking into account the specification of the high level athlete’s performance like swimming and triathlon (Olympic Games, Brazil 2016). The first textile utilization was for skiing (Olympic Games, Sotchi 2014). The different textiles technologies where adapted for medicine.

Identification of Most Frequently Occurring Lexis in Winnings-announcing Unsolicited Bulke-mails

e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of nearly 3000 winnings-announcing UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the winnings-announcing UBE documents. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexisset in the given UBE and the probability that the given UBE will be the one announcing fake winnings. To the best of our knowledge and survey of related literature, this is the first formal attempt for identification of most frequently occurring lexis in winningsannouncing UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.

ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance

Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material resources. We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. This framework is attended to be able to achieve real-time alarming, reducing the lags in traditional monitoring systems. This architecture proposal addresses four main challenges: behaviour understanding in crowded scenes, hard lighting conditions, multiple input kinds of sensors and contextual-based adaptability to recognize the active context of the scene.

Accurate Time Domain Method for Simulation of Microstructured Electromagnetic and Photonic Structures

A time-domain numerical model within the framework of transmission line modeling (TLM) is developed to simulate electromagnetic pulse propagation inside multiple microcavities forming photonic crystal (PhC) structures. The model developed is quite general and is capable of simulating complex electromagnetic problems accurately. The field quantities can be mapped onto a passive electrical circuit equivalent what ensures that TLM is provably stable and conservative at a local level. Furthermore, the circuit representation allows a high level of hybridization of TLM with other techniques and lumped circuit models of components and devices. A photonic crystal structure formed by rods (or blocks) of high-permittivity dieletric material embedded in a low-dielectric background medium is simulated as an example. The model developed gives vital spatio-temporal information about the signal, and also gives spectral information over a wide frequency range in a single run. The model has wide applications in microwave communication systems, optical waveguides and electromagnetic materials simulations.

Application of Data Mining Tools to Predicate Completion Time of a Project

Estimation time and cost of work completion in a project and follow up them during execution are contributors to success or fail of a project, and is very important for project management team. Delivering on time and within budgeted cost needs to well managing and controlling the projects. To dealing with complex task of controlling and modifying the baseline project schedule during execution, earned value management systems have been set up and widely used to measure and communicate the real physical progress of a project. But it often fails to predict the total duration of the project. In this paper data mining techniques is used predicting the total project duration in term of Time Estimate At Completion-EAC (t). For this purpose, we have used a project with 90 activities, it has updated day by day. Then, it is used regular indexes in literature and applied Earned Duration Method to calculate time estimate at completion and set these as input data for prediction and specifying the major parameters among them using Clem software. By using data mining, the effective parameters on EAC and the relationship between them could be extracted and it is very useful to manage a project with minimum delay risks. As we state, this could be a simple, safe and applicable method in prediction the completion time of a project during execution.

Oscillation Theorems for Second-order Nonlinear Neutral Dynamic Equations with Variable Delays and Damping

In this paper, we study the oscillation of a class of second-order nonlinear neutral damped variable delay dynamic equations on time scales. By using a generalized Riccati transformation technique, we obtain some sufficient conditions for the oscillation of the equations. The results of this paper improve and extend some known results. We also illustrate our main results with some examples.

Optimal Based Damping Controllers of Unified Power Flow Controller Using Adaptive Tabu Search

This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.

Use of Radial Basis Function Neural Network for Bearing Pressure Prediction of Strip Footing on Reinforced Granular Bed Overlying Weak Soil

Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.