Simulation of Tracking Time Delay Algorithm using Mathcad Package

This paper deals with tracking and estimating time delay between two signals. The simulation of this algorithm accomplished by using Mathcad package is carried out. The algorithm we will present adaptively controls and tracking the delay, so as to minimize the mean square of this error. Thus the algorithm in this case has task not only of seeking the minimum point of error but also of tracking the change of position, leading to a significant improving of performance. The flowchart of the algorithm is presented as well as several tests of different cases are carried out.

Error Factors in Vertical Positioning System

Machine tools are improved capacity remarkably during the 20th century. Improving the precision of machine tools are related with precision of products and accurate processing is always associated with the subject of interest. There are a lot of the elements that determine the precision of the machine, as guides, motors, structure, control, etc. In this paper we focused on the phenomenon that vertical movement system has worse precision than horizontal movement system even they were made up with same components. The vertical movement system needs to be studied differently from the horizontal movement system to develop its precision. The vertical movement system has load on its transfer direction and it makes the movement system weak in precision than the horizontal one. Some machines have mechanical counter balance, hydraulic or pneumatic counter balance to compensate the weight of the machine head. And there is several type of compensating the weight. It can push the machine head and also can use chain or wire lope to transfer the compensating force from counter balance to machine head. According to the type of compensating, there could be error from friction, pressure error of hydraulic or pressure control error. Also according to what to use for transferring the compensating force, transfer error of compensating force could be occur.

A Fuzzy Dynamic Load Balancing Algorithm for Homogenous Distributed Systems

Load balancing in distributed computer systems is the process of redistributing the work load among processors in the system to improve system performance. Most of previous research in using fuzzy logic for the purpose of load balancing has only concentrated in utilizing fuzzy logic concepts in describing processors load and tasks execution length. The responsibility of the fuzzy-based load balancing process itself, however, has not been discussed and in most reported work is assumed to be performed in a distributed fashion by all nodes in the network. This paper proposes a new fuzzy dynamic load balancing algorithm for homogenous distributed systems. The proposed algorithm utilizes fuzzy logic in dealing with inaccurate load information, making load distribution decisions, and maintaining overall system stability. In terms of control, we propose a new approach that specifies how, when, and by which node the load balancing is implemented. Our approach is called Centralized-But-Distributed (CBD).

Automatic Classification of Initial Categories of Alzheimer's Disease from Structural MRI Phase Images: A Comparison of PSVM, KNN and ANN Methods

An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Electrical Characteristics of SCR - based ESD Device for I/O and Power Rail Clamp in 0.35um Process

This paper presents a SCR-based ESD protection devices for I/O clamp and power rail clamp, respectably. These devices have a low trigger voltage and high holding voltage characteristics than conventional SCR device. These devices are fabricated by using 0.35um BCD (Bipolar-CMOS-DMOS) processes. These devices were validated using a TLP system. From the experimental results, the device for I/O ESD clamp has a trigger voltage of 5.8V. Also, the device for power rail ESD clamp has a holding voltage of 7.7V.

Navigation of Multiple Mobile Robots using Rule-based-Neuro-Fuzzy Technique

This paper deals with motion planning of multiple mobile robots. Mobile robots working together to achieve several objectives have many advantages over single robot system. However, the planning and coordination between the mobile robots is extremely difficult. In the present investigation rule-based and rulebased- neuro-fuzzy techniques are analyzed for multiple mobile robots navigation in an unknown or partially known environment. The final aims of the robots are to reach some pre-defined goals. Based upon a reference motion, direction; distances between the robots and obstacles; and distances between the robots and targets; different types of rules are taken heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and with an attracting influence between the robots and targets. Then a hybrid rule-based-neuro-fuzzy technique is analysed to find the steering angle of the robots. Simulation results show that the proposed rulebased- neuro-fuzzy technique can improve navigation performance in complex and unknown environments compared to this simple rulebased technique.

The Innovative Information System for Systemic Approach of the Sustainability in the Enterprise

This paper presents an innovative computer system that contributes to sustainable development of the enterprise. The research refers to a rethinking of traditional systems of collaboration and risk assessment, present in any organization, leading to a sustainable enterprise. This concept integrates emerging tools that allow the implementation and exploitation of the collective intelligence of the enterprise, allowing the exchange of contextual, agile and simplified information, and collaboration with networks of customers and partners in an environment where risks are controlled. Risk assessment is done in a systemic way: the enterprise as the system compared to the contained departments and the enterprise as a subsystem compared to: families of international standards and sustainability-s responsibilities. The enterprise, in this systemic vision, responds to the requirements that any existing system to operate continuously in an indefinite future without reaching key resource depletion. The research is done by integrating collaborative science, engineering, management, psychology, obtaining thus a cornerstone of sustainable development of the enterprise.

Heat-treated or Raw Sunflower Seeds in Lactating Dairy Cows Diets: Effects on Milk Fatty Acids Profile and Milk Production

The objective of this study was to investigate the effects of dietary supplementation with raw or heat-treated sunflower oil seed with two levels of 7.5% or 15% on unsaturated fatty acids in milk fat and performances of high-yielding lactating cows. Twenty early lactating Holstein cows were used in a complete randomized design. Treatments included: 1) CON, control (without sunflower oil seed). 2) LS-UT, 7.5% raw sunflower oil seed. 3) LS-HT, 7.5% heat-treated sunflower oil seed. 4) HS-UT, 15% raw sunflower oil seed. 5) HS-HT, 15% heat-treated sunflower oil seed. Experimental period lasted for 4 wk, with first 2 wk used for adaptation to the diets. Supplementation with 7.5% raw sunflower seed (LS-UT) tended to decrease milk yield, with 28.37 kg/d compared with the control (34.75 kg/d). Milk fat percentage was increased with the HS-UT treatment that obtained 3.71% compared with CON that was 3.39% and without significant different. Milk protein percent was decreased high level sunflower oil seed treatments (15%) with 3.18% whereas CON treatment is caused 3.40% protein. The cows fed added low sunflower heat-treated (LS-HT) produced milk with the highest content of total unsaturated fatty acid with 32.59 g/100g of milk fat compared with the HS-UT with 23.59 g/100g of milk fat. Content of C18 unsaturated fatty acids in milk fat increased from 21.68 g/100g of fat in the HS-UT to 22.50, 23.98, 27.39 and 30.30 g/100g of fat from the cow fed HS-HT, CON, LS-UT and LS-HT treatments, respectively. C18:2 isomers of fatty acid in milk were greater by LSHT supplementation with significant effect (P < 0.05). Total of C18 unsaturated fatty acids content was significantly higher in milk of animal fed added low heat-treated sunflower (7.5%) than those fed with high sunflower. In all, results of this study showed that diet cow's supplementation with sunflower oil seed tended to reduce milk production of lactating cows but can improve C18 UFA (Unsaturated Fatty Acid) content in milk fat. 7.5% level of sunflower oil seed that heated seemed to be the optimal source to increase UFA production.

Fuzzy Processing of Uncertain Data

In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity measure with of the requirements of the selection with stored data, where both the select query and the data itself may contain vague terms, for example in the form of linguistic qualifiers. In this paper, we focus on the processing of uncertain data in databases and demonstrate it on the example multi-criteria decision making in the selection of variants, specified by higher number of technical parameters.

Real-Coded Genetic Algorithm for Robust Power System Stabilizer Design

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.

Surface Defects Detection for Ceramic Tiles UsingImage Processing and Morphological Techniques

Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.

Effects of Drought on Microbial Activity in Rhizosphere, Soil Hydrophobicity and Leaching of Mineral Nitrogen from Arable Soil Depending on Method of Fertilization

This work presents the first results from the long-term laboratory experiment dealing with impact of drought on soil properties. Three groups of the treatment (A, B and C) with different regime of irrigation were prepared. The soil water content was maintained at 70 % of soil water holding capacity in group A, at 40 % in group B. In group C, soil water regime was maintained in the range of wilting point. Each group of the experiment was divided into three variants (A1 = B1, C1; A2 = B2, C2 etc.) with three repetitions: Variants A1 (B1, C1) were a controls without addition of another fertilizer. Variants A2 (B2, C2) were fertilized with mineral nitrogen fertilizer DAM 390 (0.140 Mg of N per ha) and variants A3 (B3, C3) contained 45 g of Cp per a pot. The significant differences (ANOVA, P

Optimal Supplementary Damping Controller Design for TCSC Employing RCGA

Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.

The Control of a Highly Nonlinear Two-wheels Balancing Robot: A Comparative Assessment between LQR and PID-PID Control Schemes

The research on two-wheels balancing robot has gained momentum due to their functionality and reliability when completing certain tasks. This paper presents investigations into the performance comparison of Linear Quadratic Regulator (LQR) and PID-PID controllers for a highly nonlinear 2–wheels balancing robot. The mathematical model of 2-wheels balancing robot that is highly nonlinear is derived. The final model is then represented in statespace form and the system suffers from mismatched condition. Two system responses namely the robot position and robot angular position are obtained. The performances of the LQR and PID-PID controllers are examined in terms of input tracking and disturbances rejection capability. Simulation results of the responses of the nonlinear 2–wheels balancing robot are presented in time domain. A comparative assessment of both control schemes to the system performance is presented and discussed.

Uniform Distribution of Ductility Demand in Irregular Bridges using Shape Memory Alloy

Excessive ductility demand on shorter piers is a common problem for irregular bridges subjected to strong ground motion. Various techniques have been developed to reduce the likelihood of collapse of bridge due to failure of shorter piers. This paper presents the new approach to improve the seismic behavior of such bridges using Nitinol shape memory alloys (SMAs). Superelastic SMAs have the ability to remain elastic under very large deformation due to martensitic transformation. This unique property leads to enhanced performance of controlled bridge compared with the performance of the reference bridge. To evaluate the effectiveness of the devices, nonlinear time history analysis is performed on a RC single column bent highway bridge using a suite of representative ground motions. The results show that this method is very effective in limiting the ductility demand of shorter pier.

A Cross-Layer Approach for Cooperative MIMO Multi-hop Wireless Sensor Networks

In this work, we study the problem of determining the minimum scheduling length that can satisfy end-to-end (ETE) traffic demand in scheduling-based multihop WSNs with cooperative multiple-input multiple-output (MIMO) transmission scheme. Specifically, we present a cross-layer formulation for the joint routing, scheduling and stream control problem by incorporating various power and rate adaptation schemes, and taking into account an antenna beam pattern model and the signal-to-interference-and-noise (SINR) constraint at the receiver. In the context, we also propose column generation (CG) solutions to get rid of the complexity requiring the enumeration of all possible sets of scheduling links.

Neural Network Implementation Using FPGA: Issues and Application

.Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation of a multi-input neuron with linear/nonlinear excitation functions using FPGA. Implementation method with resource/speed tradeoff is proposed to handle signed decimal numbers. The VHDL coding developed is tested using Xilinx XC V50hq240 Chip. To improve the speed of operation a lookup table method is used. The problems involved in using a lookup table (LUT) for a nonlinear function is discussed. The percentage saving in resource and the improvement in speed with an LUT for a neuron is reported. An attempt is also made to derive a generalized formula for a multi-input neuron that facilitates to estimate approximately the total resource requirement and speed achievable for a given multilayer neural network. This facilitates the designer to choose the FPGA capacity for a given application. Using the proposed method of implementation a neural network based application, namely, a Space vector modulator for a vector-controlled drive is presented

20 GHz Fractional Phased Locked Loop Circuit for the Gbps Wireless Communication

This paper presents the 20-GHz fractional PLL (Phase Locked Loop) circuit for the next generation Wi-Fi by using 90 nm TSMC process. The newly suggested millimeter wave 16/17 pre-scalar is designed and verified by measurement to make the fractional PLL having a low quantization noise. The operational bandwidth of the 60 GHz system is 15 % of the carrier frequency which requires large value of Kv (VCO control gain) resulting in degradation of phase noise. To solve this problem, this paper adopts AFC (Automatic Frequency Controller) controlled 4-bit millimeter wave VCO with small value of Kv. Also constant Kv is implemented using 4-bit varactor bank. The measured operational bandwidth is 18.2 ~ 23.2 GHz which is 25 % of the carrier frequency. The phase noise of -58 and -96.2 dBc/Hz at 100 KHz and 1 MHz offset is measured respectively. The total power consumption of the PLL is only 30 mW.

Measuring Business and Information Technology Value in BPR: An Empirical Study in the Japanese Enterprises

This paper presents an analysis result of relationship between business and information technology (IT) in business process reengineering (BPR). 258 Japanese firm-level data collected have been analyzed using structural equation modeling. This analysis was aimed to illuminating success factors of achieve effective BPR. Analysis was focused on management factors (including organizational factors) and implementing management method (e.g. balanced score card, internal control, etc.).These results would contribute for achieving effective BPR by showing effective tasks and environment to be focused.

Controller Design for Euler-Bernoulli Smart Structures Using Robust Decentralized FOS via Reduced Order Modeling

This paper features the modeling and design of a Robust Decentralized Fast Output Sampling (RDFOS) Feedback control technique for the active vibration control of a smart flexible multimodel Euler-Bernoulli cantilever beams for a multivariable (MIMO) case by retaining the first 6 vibratory modes. The beam structure is modeled in state space form using the concept of piezoelectric theory, the Euler-Bernoulli beam theory and the Finite Element Method (FEM) technique by dividing the beam into 4 finite elements and placing the piezoelectric sensor / actuator at two finite element locations (positions 2 and 4) as collocated pairs, i.e., as surface mounted sensor / actuator, thus giving rise to a multivariable model of the smart structure plant with two inputs and two outputs. Five such multivariable models are obtained by varying the dimensions (aspect ratios) of the aluminium beam. Using model order reduction technique, the reduced order model of the higher order system is obtained based on dominant Eigen value retention and the Davison technique. RDFOS feedback controllers are designed for the above 5 multivariable-multimodel plant. The closed loop responses with the RDFOS feedback gain and the magnitudes of the control input are obtained and the performance of the proposed multimodel smart structure system is evaluated for vibration control.