Dynamic Threshold Adjustment Approach For Neural Networks

The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

Phase Error Accumulation Methodology for On-Chip Cell Characterization

This paper describes the design of new method of propagation delay measurement in micro and nanostructures during characterization of ASIC standard library cell. Providing more accuracy timing information about library cell to the design team we can improve a quality of timing analysis inside of ASIC design flow process. Also, this information could be very useful for semiconductor foundry team to make correction in technology process. By comparison of the propagation delay in the CMOS element and result of analog SPICE simulation. It was implemented as digital IP core for semiconductor manufacturing process. Specialized method helps to observe the propagation time delay in one element of the standard-cell library with up-to picoseconds accuracy and less. Thus, the special useful solutions for VLSI schematic to parameters extraction, basic cell layout verification, design simulation and verification are announced.

Contact Stress on the Surface of Gear Teeth with Different Profile

Contact stress is an important problem in industry. This is a problem that in the first attention may be don-t appears, but disregard of these stresses cause a lot of damages in machines. These stresses occur at locations such as gear teeth, bearings, cams and between a locomotive wheel and the railroad rail. These stresses cause failure by excessive elastic deformation, yielding and fracture. In this paper we intend show the effective parameters in contact stress and ponder effect of curvature. In this paper we study contact stresses on the surface of gear teeth and compare these stresses for four popular profiles of gear teeth (involute, cycloid, epicycloids, and hypocycloid). We study this problem with mathematical and finite element methods and compare these two methods on different profile surfaces.

Speech Data Compression using Vector Quantization

Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.

Water Quality from a Mixed Land-Use Catchment in Miri, Sarawak

Urbanization has been found to impact stormwater runoff quantity and quality. A study catchment with mixed land use, residential and industrial were investigated and the water quality discharged from the catchment were sampled and tested for four basic water quality parameters; BOD5, NH3-N, NO3-N and P. One dry weather flow and several stormwater runoff were sampled. Results were compared to the USEPA stormwater quality benchmark values and the Interim National Water Quality Standards for Malaysia (INWQS). The concentration of the parameters was found to vary significantly between storms and the pollutant of concern was found to be NO3-N.

A Simple Adaptive Algorithm for Norm-Constrained Optimization

In this paper we propose a simple adaptive algorithm iteratively solving the unit-norm constrained optimization problem. Instead of conventional parameter norm based normalization, the proposed algorithm incorporates scalar normalization which is computationally much simpler. The analysis of stationary point is presented to show that the proposed algorithm indeed solves the constrained optimization problem. The simulation results illustrate that the proposed algorithm performs as good as conventional ones while being computationally simpler.

Recurrent Neural Network Based Fuzzy Inference System for Identification and Control of Dynamic Plants

This paper presents the development of recurrent neural network based fuzzy inference system for identification and control of dynamic nonlinear plant. The structure and algorithms of fuzzy system based on recurrent neural network are described. To train unknown parameters of the system the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The neuro-fuzzy system is used for the identification and control of nonlinear dynamic plant. The simulation results of identification and control systems based on recurrent neuro-fuzzy network are compared with the simulation results of other neural systems. It is found that the recurrent neuro-fuzzy based system has better performance than the others.

In Vivo Evaluation of Stable Cream Containing Flavonoids on Hydration and TEWL of Human Skin

Antioxidants contribute to endogenous photoprotection and are important for the maintenance of skin health. The study was carried out to compare the skin hydration and transepidermal water loss (TEWL) effects of a stable cosmetic preparation containing flavonoids, following two applications a day over a period of tenth week. The skin trans-epidermal water loss and skin hydration effect was measured at the beginning and up to the end of study period of ten weeks. Any effect produced was measured by Corneometer and TEWA meter (Non-invasive probe). Two formulations were developed for this study design. Formulation one the control formulation in which no apple juice extract( Flavonoids) was incorporated while second one was the active formulation in which the apple juice extract (3%) containing flavonoids was incorporated into water in oil emulsion using Abil EM 90 as an emulsifier. Stable formulations (control and Active) were applied on human cheeks (n = 12) for a study period of 10 weeks. Result of each volunteer of skin hydration and TEWL was measured by corneometer and TEWA meter. By using ANOVA and Paired sample t test as a statistical evaluation, result of both base and formulation were compared. Statistical significant results (p≤0.05) were observed regarding skin hydration and TEWL when two creams, control and Formulation were compared. It showed that desired formulation (Active) may have interesting application as an active moisturizing cream on healthy skin.

Optimal Location of Multi Type Facts Devices for Multiple Contingencies Using Particle Swarm Optimization

In deregulated operating regime power system security is an issue that needs due thoughtfulness from researchers in the horizon of unbundling of generation and transmission. Electric power systems are exposed to various contingencies. Network contingencies often contribute to overloading of branches, violation of voltages and also leading to problems of security/stability. To maintain the security of the systems, it is desirable to estimate the effect of contingencies and pertinent control measurement can be taken on to improve the system security. This paper presents the application of particle swarm optimization algorithm to find the optimal location of multi type FACTS devices in a power system in order to eliminate or alleviate the line over loads. The optimizations are performed on the parameters, namely the location of the devices, their types, their settings and installation cost of FACTS devices for single and multiple contingencies. TCSC, SVC and UPFC are considered and modeled for steady state analysis. The selection of UPFC and TCSC suitable location uses the criteria on the basis of improved system security. The effectiveness of the proposed method is tested for IEEE 6 bus and IEEE 30 bus test systems.

Design of a Low Cost Motion Data Acquisition Setup for Mechatronic Systems

Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

A Dynamic Model of Air Pollution, Health,and Population Growth Using System Dynamics: A Study on Tehran-Iran (With Computer Simulation by the Software Vensim)

The significance of environmental protection is wellknown in today's world. The execution of any program depends on sufficient knowledge and required familiarity with environment and its pollutants. Taking advantage of a systematic method, as a new science, in environmental planning can solve many problems. In this article, air pollution in Tehran and its relationship with health and population growth have been analyzed using dynamic systems. Firstly, by using casual loops, the relationship between the parameters effective on air pollution in Tehran were taken into consideration, then these casual loops were turned into flow diagrams [6], and finally, they were simulated using the software Vensim [16]in order to conclude what the effect of each parameter will be on air pollution in Tehran in the next 10 years, how changing of one or more parameters influences other parameters, and which parameter among all other parameters requires to be controlled more.

Optimization of Microwave-Assisted Extraction of Cherry Laurel (Prunus laurocerasus L.) Fruit Using Response Surface Methodology

Optimization of a microwave-assisted extraction of cherry laurel (Prunus laurocerasus) fruit using methanol was studied. The influence of process parameters (microwave power, plant material-to-solvent ratio and the extraction time) on the extraction efficiency were optimized by using response surface methodology. The predicted maximum yield of extractive substances (41.85 g/100 g fresh plant material) was obtained at microwave power of 600 W and plant material to solvent ratio of 0.2 g/cm3 after 26 minutes of extraction, while a mean value of 40.80±0.41 g/100 g fresh plant material was obtained from laboratory experiments. This proves applicability of the model in predicting optimal extraction conditions with minimal laborious and time consuming. The results indicated that all process parameters were effective on the extraction efficiency, while the most important factor was extraction time. In order to rationalize production the optimal economical condition which gave a large total extract yield with minimal energy and solvent consumption was found.

Analyzing of Temperature-Dependent Thermal Conductivity Effect in the Numerical Modeling of Fin-Tube Radiators: Introduction of a New Method

In all industries which are related to heat, suitable thermal ranges are defined for each device to operate well. Consideration of these limits requires a thermal control unit beside the main system. The Satellite Thermal Control Unit exploits from different methods and facilities individually or mixed. For enhancing heat transfer between primary surface and the environment, utilization of radiating extended surfaces are common. Especially for large temperature differences; variable thermal conductivity has a strong effect on performance of such a surface .In most literatures, thermo-physical properties, such as thermal conductivity, are assumed as constant. However, in some recent researches the variation of these parameters is considered. This may be helpful for the evaluation of fin-s temperature distribution in relatively large temperature differences. A new method is introduced to evaluate temperature-dependent thermal conductivity values. The finite volume method is employed to simulate numerically the temperature distribution in a space radiating fin. The present modeling is carried out for Aluminum as fin material and compared with previous method. The present results are also compared with those of two other analytical methods and good agreement is shown.

Effect of Thermal Radiation on Temperature Variation in 2-D Stagnation-Point flow

Non-isothermal stagnation-point flow with consideration of thermal radiation is studied numerically. A set of partial differential equations that governing the fluid flow and energy is converted into a set of ordinary differential equations which is solved by Runge-Kutta method with shooting algorithm. Dimensionless wall temperature gradient and temperature boundary layer thickness for different combinaton of values of Prandtl number Pr and radiation parameter NR are presented graphically. Analyses of results show that the presence of thermal radiation in the stagnation-point flow is to increase the temperature boundary layer thickness and decrease the dimensionless wall temperature gradient.

Sorption of Nickel by Hypnea Valentiae: Application of Response Surface Methodology

In this work, sorption of nickel from aqueous solution on hypnea valentiae, red macro algae, was investigated. Batch experiments have been carried out to find the effect of various parameters such as pH, temperature, sorbent dosage, metal concentration and contact time on the sorption of nickel using hypnea valentiae. Response surface methodology (RSM) is employed to optimize the process parameters. Based on the central composite design, quadratic model was developed to correlate the process variables to the response. The most influential factor on each experimental design response was identified from the analysis of variance (ANOVA). The optimum conditions for the sorption of nickel were found to be: pH – 5.1, temperature – 36.8oC, sorbent dosage – 5.1 g/L, metal concentration – 100 mg/L and contact time – 30 min. At these optimized conditions the maximum removal of nickel was found to be 91.97%. A coefficient of determination R2 value 0.9548 shows the fitness of response surface methodology in this work.

Study of the Cryogenically Cooled Electrode Shape in Electric Discharge Machining Process

Electrical discharge machining (EDM) is well established machining technique mainly used to machine complex geometries on difficult-to-machine materials and high strength temperature resistant alloys. In the present research, the objective is to study the shape of the electrode and establish the application of liquid nitrogen in reducing distortion of the electrode during electrical discharge machining of M2 grade high speed steel using copper electrodes. Study of roundness was performed on the electrode to observe the shape of the electrode for both conventional EDM and EDM with cryogenically cooled electrode. Scanning Electron Microscope (SEM) has been used to study the shape of electrode tip. The effect of various parameters such as discharge current and pulse on time has been studied to understand the behavior of distortion of electrode. It has been concluded that the shape retention is better in case of liquid nitrogen cooled electrode.

CART Method for Modeling the Output Power of Copper Bromide Laser

This paper examines the available experiment data for a copper bromide vapor laser (CuBr laser), emitting at two wavelengths - 510.6 and 578.2nm. Laser output power is estimated based on 10 independent input physical parameters. A classification and regression tree (CART) model is obtained which describes 97% of data. The resulting binary CART tree specifies which input parameters influence considerably each of the classification groups. This allows for a technical assessment that indicates which of these are the most significant for the manufacture and operation of the type of laser under consideration. The predicted values of the laser output power are also obtained depending on classification. This aids the design and development processes considerably.

An Augmented Automatic Choosing Control Designed by Extremizing a Combination of Hamiltonian and Lyapunov Functions for Nonlinear Systems with Constrained Input

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

New Simultaneous High Performance Liquid Chromatographic Method for Determination of NSAIDs and Opioid Analgesics in Advanced Drug Delivery Systems and Human Plasma

A new and cost effective RP-HPLC method was developed and validated for simultaneous analysis of non steroidal anti inflammatory dugs Diclofenac sodium (DFS), Flurbiprofen (FLP) and an opioid analgesic Tramadol (TMD) in advanced drug delivery systems (Liposome and Microcapsules), marketed brands and human plasma. Isocratic system was employed for the flow of mobile phase consisting of 10 mM sodium dihydrogen phosphate buffer and acetonitrile in molar ratio of 67: 33 with adjusted pH of 3.2. The stationary phase was hypersil ODS column (C18, 250×4.6 mm i.d., 5 μm) with controlled temperature of 30 C°. DFS in liposomes, microcapsules and marketed drug products was determined in range of 99.76-99.84%. FLP and TMD in microcapsules and brands formulation were 99.78 - 99.94 % and 99.80 - 99.82 %, respectively. Single step liquid-liquid extraction procedure using combination of acetonitrile and trichloroacetic acid (TCA) as protein precipitating agent was employed. The detection limits (at S/N ratio 3) of quality control solutions and plasma samples were 10, 20, and 20 ng/ml for DFS, FLP and TMD, respectively. The Assay was acceptable in linear dynamic range. All other validation parameters were found in limits of FDA and ICH method validation guidelines. The proposed method is sensitive, accurate and precise and could be applicable for routine analysis in pharmaceutical industry as well as in human plasma samples for bioequivalence and pharmacokinetics studies.

Design of Adaptive Sliding Mode Controller for Robotic Manipulators Tracking Control

This paper proposes an adaptive sliding mode controller which combines adaptive control and sliding mode control to control a nonlinear robotic manipulator with uncertain parameters. We use an adaptive algorithm based on the concept of sliding mode control to alleviate the chattering phenomenon of control input. Adaptive laws are developed to obtain the gain of switching input and the boundary layer parameters. The stability and convergence of the robotic manipulator control system are guaranteed by applying the Lyapunov theorem. Simulation results demonstrate that the chattering of control input can be alleviated effectively. The proposed controller scheme can assure robustness against a large class of uncertainties and achieve good trajectory tracking performance.