Design a Low Voltage- Low Offset Class AB Op-Amp

A new design approach for three-stage operational amplifiers (op-amps) is proposed. It allows to actually implement a symmetrical push-pull class-AB amplifier output stage for wellestablished three-stage amplifiers using a feedforward transconductance stage. Compared with the conventional design practice, the proposed approach leads to a significant improvement of the symmetry between the positive and the negative op-amp step response, resulting in similar values of the positive/negative settling time. The new approach proves to be very useful in order to fully exploit the potentiality allowed by the op-amp in terms of speed performances. Design examples in a commercial 0.35-μm CMOS prove the effectiveness of theproposed strategy.

An Efficient Algorithm for Computing all Program Forward Static Slices

Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program backward slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. The existing algorithms for computing program slices are introduced to compute a slice at a program point. In these algorithms, the program, or the model that represents the program, is traversed completely or partially once. To compute more than one slice, the same algorithm is applied for every point of interest in the program. Thus, the same program, or program representation, is traversed several times. In this paper, an algorithm is introduced to compute all forward static slices of a computer program by traversing the program representation graph once. Therefore, the introduced algorithm is useful for software engineering applications that require computing program slices at different points of a program. The program representation graph used in this paper is called Program Dependence Graph (PDG).

A Numerical Investigation on the Dynamic Stall of a Wind Turbine Section Using Different Turbulent Models

In this article, the flow behavior around a NACA 0012 airfoil which is oscillating with different Reynolds numbers and in various amplitudes has been investigated numerically. Numerical simulations have been performed with ANSYS software. First, the 2- D geometry has been studied in different Reynolds numbers and angles of attack with various numerical methods in its static condition. This analysis was to choose the best turbulent model and comparing the grids to have the optimum one for dynamic simulations. Because the analysis was to study the blades of wind turbines, the Reynolds numbers were not arbitrary. They were in the range of 9.71e5 to 22.65e5. The angle of attack was in the range of -41.81° to 41.81°. By choosing the forward wind speed as the independent parameter, the others like Reynolds and the amplitude of the oscillation would be known automatically. The results show that the SST turbulent model is the best choice that leads the least numerical error with respect the experimental ones. Also, a dynamic stall phenomenon is more probable at lower wind speeds in which the lift force is less.

Feeder Reconfiguration for Loss Reduction in Unbalanced Distribution System Using Genetic Algorithm

This paper presents an efficient approach to feeder reconfiguration for power loss reduction and voltage profile imprvement in unbalanced radial distribution systems (URDS). In this paper Genetic Algorithm (GA) is used to obtain solution for reconfiguration of radial distribution systems to minimize the losses. A forward and backward algorithm is used to calculate load flows in unbalanced distribution systems. By simulating the survival of the fittest among the strings, the optimum string is searched by randomized information exchange between strings by performing crossover and mutation. Results have shown that proposed algorithm has advantages over previous algorithms The proposed method is effectively tested on 19 node and 25 node unbalanced radial distribution systems.

Rapid Finite-Element Based Airport Pavement Moduli Solutions using Neural Networks

This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data. The HWD test is one of the most widely used tests for routinely assessing the structural integrity of airport pavements in a non-destructive manner. The elastic moduli of the individual pavement layers backcalculated from the HWD deflection profiles are effective indicators of layer condition and are used for estimating the pavement remaining life. HWD tests were periodically conducted at the Federal Aviation Administration-s (FAA-s) National Airport Pavement Test Facility (NAPTF) to monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test gear trafficking on the structural condition of flexible pavement sections. In this study, a multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD backcalculation function. The synthetic database generated using an advanced non-linear pavement finite-element program was used to train the ANN to overcome the limitations associated with conventional pavement moduli backcalculation. The changes in ANN-based backcalculated pavement moduli with trafficking were used to compare the relative severity effects of the aircraft landing gears on the NAPTF test pavements.

On the Central Limit Theorems for Forward and Backward Martingales

Let {Xi}i≥1 be a martingale difference sequence with Xi = Si - Si-1. Under some regularity conditions, we show that (X2 1+· · ·+X2N n)-1/2SNn is asymptotically normal, where {Ni}i≥1 is a sequence of positive integer-valued random variables tending to infinity. In a similar manner, a backward (or reverse) martingale central limit theorem with random indices is provided.

Operational Analysis of Urban Intelligent Transportation System and Strategies for Future Development - Taking Calling Service of Taxi in Wuhan as an Example

Intelligent Transportation System integrates various modern advanced technologies into the ground transportation system, and it will be the goal of urban transport system in the future because of its comprehensive effects. However, it also brings some problems, such as project performance assessment, fairness of benefiting groups, fund management, which are directly related to its operation and implementation. Wuhan has difficulties in organizing transportation because of its nature feature (river and lake), therefore, calling Service of Taxi plays an important role in transportation. This paper researches on calling Service of Taxi in Wuhan, based on quantitative and qualitative analysis. It analyzes its operations management systematically, including business model, finance, usage analysis and users evaluation. As for business model, it is that the government leads the operation at the initial stage, and the third part dominates the operation at the mature stage, which not only eases the pressure of the third part and benefits the spread of the calling service at the initial stage, but also alleviates financial pressure of government and improve the efficiency of the operation at the mature stage. As for finance, it draws that this service will bring heavy financial burden of equipments, but it will be alleviated in the future because of its spread. As for usage analysis, through data comparison, this service can bring some benefits for taxi drivers, and time and spatial distribution of usage have certain features. As for user evaluation, it analyzes using group and the reason why choosing it. At last, according to the analysis above, the paper puts forward the potentials, limitations, and future development strategies for it.

Semantic Markup for Web Applications

In this paper we would like to introduce some of the best practices of using semantic markup and its significance in the success of web applications. Search engines are one of the best ways to reach potential customers and are some of the main indicators of web sites' fruitfulness. We will introduce the most important semantic vocabularies which are used by Google and Yahoo. Afterwards, we will explain the process of semantic markup implementation and its significance for search engines and other semantic markup consumers. We will describe techniques for slow conceiving RDFa markup to our web application for collecting Call for papers (CFP) announcements.

Landowers' Participation Behavior on the Payment for Environmental Service (PES): Evidences from Taiwan

To respond to the Kyoto Protocol, the policy of Payment for Environmental Service (PES), which was entitled “Plain Landscape Afforestation Program (PLAP)", was certified by Executive Yuan in Taiwan on 31 August 2001 and has been implementing for six years since 1 January 2002. Although the PLAP has received a lot of positive comments, there are still many difficulties during the process of implementation, such as insufficient technology for afforestation, private landowners- low interests in participating in PLAP, insufficient subsidies, and so on, which are potential threats that hinder the PLAP from moving forward in future. In this paper, selecting Ping-Tung County in Taiwan as a sample region and targeting those private landowners with and without intention to participate in the PLAP, respectively, we conduct an empirical analysis based on the Logit model to investigate the factors that determine whether those private landowners join the PLAP, so as to realize the incentive effects of the PLAP upon the personal decision on afforestation. The possible factors that might determine private landowner-s participation in the PLAP include landowner-s characteristics, cropland characteristics, as well as policy factors. Among them, the policy factors include afforestation subsidy amount (+), duration of afforestation subsidy (+), the rules on adjoining and adjacent areas (+), and so on, which do not reach the remarkable level in statistics though, but the directions of variable signs are consistent with the intuition behind the policy. As for the landowners- characteristics, each of age (+), education level (–), and annual household income (+) variables reaches 10% of the remarkable level in statistics; as for the cropland characteristics, each of cropland area (+), cropland price (–), and the number of cropland parcels (–) reaches 1% of the remarkable level in statistics. In light of the above, the cropland characteristics are the dominate factor that determines the probability of landowner-s participation in the PLAP. In the Logit model established by this paper, the probability of correctly estimating nonparticipants is 98%, the probability of correctly estimating the participants is 71.8%, and the probability for the overall estimation is 95%. In addition, Hosmer-Lemeshow test and omnibus test also revealed that the Logit model in this paper may provide fine goodness of fit and good predictive power in forecasting private landowners- participation in this program. The empirical result of this paper expects to help the implementation of the afforestation programs in Taiwan.

FWM Wavelength Conversion Analysis in a 3-Integrated Portion SOA and DFB Laser using Coupled Wave Approach and FD-BPM Method

In this paper we have numerically analyzed terahertzrange wavelength conversion using nondegenerate four wave mixing (NDFWM) in a SOA integrated DFB laser (experiments reported both in MIT electronics and Fujitsu research laboratories). For analyzing semiconductor optical amplifier (SOA), we use finitedifference beam propagation method (FDBPM) based on modified nonlinear SchrÖdinger equation and for distributed feedback (DFB) laser we use coupled wave approach. We investigated wavelength conversion up to 4THz probe-pump detuning with conversion efficiency -5dB in 1THz probe-pump detuning for a SOA integrated quantum-well

An Enhanced Situational Awareness of AUV's Mission by Multirate Neural Control

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.

An Index based Forward Backward Multiple Pattern Matching Algorithm

Pattern matching is one of the fundamental applications in molecular biology. Searching DNA related data is a common activity for molecular biologists. In this paper we explore the applicability of a new pattern matching technique called Index based Forward Backward Multiple Pattern Matching algorithm(IFBMPM), for DNA Sequences. Our approach avoids unnecessary comparisons in the DNA Sequence due to this; the number of comparisons of the proposed algorithm is very less compared to other existing popular methods. The number of comparisons rapidly decreases and execution time decreases accordingly and shows better performance.

Agent Decision using Granular Computing in Traffic System

In recent years multi-agent systems have emerged as one of the interesting architectures facilitating distributed collaboration and distributed problem solving. Each node (agent) of the network might pursue its own agenda, exploit its environment, develop its own problem solving strategy and establish required communication strategies. Within each node of the network, one could encounter a diversity of problem-solving approaches. Quite commonly the agents can realize their processing at the level of information granules that is the most suitable from their local points of view. Information granules can come at various levels of granularity. Each agent could exploit a certain formalism of information granulation engaging a machinery of fuzzy sets, interval analysis, rough sets, just to name a few dominant technologies of granular computing. Having this in mind, arises a fundamental issue of forming effective interaction linkages between the agents so that they fully broadcast their findings and benefit from interacting with others.

MIMO Antenna Selections using CSI from Reciprocal Channel

It is well known that the channel capacity of Multiple- Input-Multiple-Output (MIMO) system increases as the number of antenna pairs between transmitter and receiver increases but it suffers from multiple expensive RF chains. To reduce the cost of RF chains, Antenna Selection (AS) method can offer a good tradeoff between expense and performance. In a transmitting AS system, Channel State Information (CSI) feedback is necessarily required to choose the best subset of antennas in which the effects of delays and errors occurred in feedback channels are the most dominant factors degrading the performance of the AS method. This paper presents the concept of AS method using CSI from channel reciprocity instead of feedback method. Reciprocity technique can easily archive CSI by utilizing a reverse channel where the forward and reverse channels are symmetrically considered in time, frequency and location. In this work, the capacity performance of MIMO system when using AS method at transmitter with reciprocity channels is investigated by own developing Testbed. The obtained results show that reciprocity technique offers capacity close to a system with a perfect CSI and gains a higher capacity than a system without AS method from 0.9 to 2.2 bps/Hz at SNR 10 dB.

Cross-Industry Innovations–Systematic Identification of Ideas for Radical Problem Solving

Creativity is often based on an unorthodox recombination of knowledge; in fact: 80% of all innovations use given knowledge and put it into a new combination. Cross-industry innovations follow this way of thinking and bring together problems and solution ideas from different industries. Therefore analogies and search strategies have to be developed. Taking this path, the questions where to search, what to search and how to search have to be answered. Afterwards, the gathered information can be used within a planned search process. Identified solution ideas have to be assessed and analyzed in detail for the success promising adaption planning.

Analytical Investigation of Sediment Formation and Transport in the Vicinity of the Water Intake Structures - A Case Study of the Dez Diversion Weir in Greater Dezful

Sedimentation process resulting from soil erosion in the water basin especially in arid and semi-arid where poor vegetation cover in the slope of the mountains upstream could contribute to sediment formation. The consequence of sedimentation not only makes considerable change in the morphology of the river and the hydraulic characteristics but would also have a major challenge for the operation and maintenance of the canal network which depend on water flow to meet the stakeholder-s requirements. For this reason mathematical modeling can be used to simulate the effective factors on scouring, sediment transport and their settling along the waterways. This is particularly important behind the reservoirs which enable the operators to estimate the useful life of these hydraulic structures. The aim of this paper is to simulate the sedimentation and erosion in the eastern and western water intake structures of the Dez Diversion weir using GSTARS-3 software. This is done to estimate the sedimentation and investigate the ways in which to optimize the process and minimize the operational problems. Results indicated that the at the furthest point upstream of the diversion weir, the coarser sediment grains tended to settle. The reason for this is the construction of the phantom bridge and the outstanding rocks just upstream of the structure. The construction of these along the river course has reduced the momentum energy require to push the sediment loads and make it possible for them to settle wherever the river regime allows it. Results further indicated a trend for the sediment size in such a way that as the focus of study shifts downstream the size of grains get smaller and vice versa. It was also found that the finding of the GSTARS-3 had a close proximity with the sets of the observed data. This suggests that the software is a powerful analytical tool which can be applied in the river engineering project with a minimum of costs and relatively accurate results.

STLF Based on Optimized Neural Network Using PSO

The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Consumer Insolvency in the Czech Republic

The Czech Republic is a country whose economy has undergone a transformation since 1989. Since joining the EU it has been striving to reduce the differences in its economic standard and the quality of its institutional environment in comparison with developed countries. According to an assessment carried out by the World Bank, the Czech Republic was long classed as a country whose institutional development was seen as problematic. For many years one of the things it was rated most poorly on was its bankruptcy law. The new Insolvency Act, which is a modern law in terms of its treatment of bankruptcy, was first adopted in the Czech Republic in 2006. This law, together with other regulatory measures, offers debtridden Czech economic subjects legal instruments which are well established and in common practice in developed market economies. Since then, analyses performed by the World Bank and the London EBRD have shown that there have been significant steps forward in the quality of Czech bankruptcy law. The Czech Republic still lacks an analytical apparatus which can offer a structured characterisation of the general and specific conditions of Czech company and household debt which is subject to current changes in the global economy. This area has so far not been given the attention it deserves. The lack of research is particularly clear as regards analysis of household debt and householders- ability to settle their debts in a reasonable manner using legal and other state means of regulation. We assume that Czech households have recourse to a modern insolvency law, yet the effective application of this law is hampered by the inconsistencies in the formal and informal institutions involved in resolving debt. This in turn is based on the assumption that this lack of consistency is more marked in cases of personal bankruptcy. Our aim is to identify the symptoms which indicate that for some time the effective application of bankruptcy law in the Czech Republic will be hindered by factors originating in householders- relative inability to identify the risks of falling into debt.

Performance Analysis of Multiuser Diversity in Multiuser Two-Hop Decode-and-Forward Cooperative Multi-Relay Wireless Networks

Cooperative diversity (CD) has been adopted in many communication systems because it helps in improving performance of the wireless communication systems with the help of the relays that emulate the multiple antenna terminals. This work aims to provide the derivation of the performance analysis expressions of the multiuser diversity (MUD) in the two-hop cooperative multi-relay wireless networks (TCMRNs). Considering the work analysis, we provide analytically the derivation of a closed form expression of the two most commonly used performance metrics namely, the outage probability and the symbol error probability (SEP) for the fixed decode-and-forward (FDF) protocol with MUD.

Application of Association Rule Mining in Supplier Selection Criteria

In this paper the application of rule mining in order to review the effective factors on supplier selection is reviewed in the following three sections 1) criteria selecting and information gathering 2) performing association rule mining 3) validation and constituting rule base. Afterwards a few of applications of rule base is explained. Then, a numerical example is presented and analyzed by Clementine software. Some of extracted rules as well as the results are presented at the end.