Analysis and suppression of spurious modes of the ring shape anchored RF MEMS contour mode disk resonator

One of the most encumbering issues in RF MEMS resonators is spurious modes. The problem of spurious modes becomes more critical, when the ring type resonators are used. In the ring shape anchored contour mode disk resonator, for achieving a low serial resistance, the inner radius of the disk must be increased. This causes the spurious modes to become too close to the desired mode and degrade the operation of the resonator. In this work, spurious modes of before-mentioned device are introduced and their characteristics are evaluated by exact analytical approach. Based on those analytical approaches, we introduce two techniques for spurious mode suppression. The first technique is based on exciting the desired mode by proper electrode engineering and hence is an electrical approach. The second technique is reconfiguring of the anchor from a continuous ring to crossed ring segments and locating the segments on the phase discriminating lines to increase the insertion loss for spurious modes and decrease the losses for the fundamental mode. The final harmonic analysis verifies that the proposed techniques result a resonator with a pure frequency spectrum and spurious modes excluded over a very wide frequency range.     

Genetic-based minimum classification error mapping for accurate identifying Peer-to-Peer applications in the internet traffic

In this paper, we propose a hybrid approach using genetic algorithm and neural networks to classify Peer-to-Peer (P2P) traffic in IP networks. We first compute the minimum classification error (MCE) matrix using genetic algorithm. The MCE matrix is then used during the pre-processing step to map the original dataset into a new space. The mapped data set is then fed to three different classifiers: distance-based, K-Nearest Neighbors, and neural networks classifiers. We measure three different indexes, namely mutual information, Dunn, and SD to evaluate the extent of separation of the data points before and after mapping is performed. The experimental results demonstrate that with the proposed mapping scheme we achieve, on average, 8% higher accuracy in classification of the P2P traffic compare to the previous solutions. Moreover, the genetic-based MCE matrix increases the classification accuracy more than what the basic MCE does.     

Adaptive enhancement and binarization techniques for degraded plate images

Multimedia Tools and Applications - Vehicle License Plate Recognition (VLPR) is one of the most important aspects of applying computer techniques in Intelligent Transport Systems (ITS). They face...     

Multi expression programming: a new approach to formulation of soil classification

This paper presents an alternative approach to formulation of soil classification by means of a promising variant of genetic programming (GP), namely multi expression programming (MEP). Properties of soil, namely plastic limit, liquid limit, color of soil, percentages of gravel, sand, and fine-grained particles are used as input variables to predict the classification of soils. The models are developed using a reliable database obtained from the previously published literature. The results demonstrate that the MEP-based formulas are able to predict the target values to high degree of accuracy. The MEP-based formulation results are found to be more accurate compared with numerical and analytical results obtained by other researchers.     

Multi agent architecture for dynamic incremental process planning in the flexible manufacturing system

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer’s needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.     

Role of laser sensor systems in automation and flexible manufacturing

New industries and production plants require a flexible system, which is capable of picking up objects of various shapes, weights, and colors with arbitrary position and orientation. Such a system also needs recognition and guiding sub-systems. The recognition system includes target function for the recognition sub-system and relation between object characteristics and recognition target. The laser sensor system can be used for such object recognition. Wire-based telemetry and control systems can cause many problems in shop floors and factories, and so there has been a strong growth of interest in wireless guidance like vehicles equipped with laser guiding and navigation systems. For the continuous measurements of parameters such as temperature, etc. optical laser sensor technology seems to become more applicable at this stage. This article describes the operational principles and the use of the most advanced laser sensor systems for quantity measurements, guiding, navigation, pattern recognition, and vision systems for inspection purposes. A variety of laser-based sensors, which can be used as sensing devices in manufacturing, and production technology, are described in this study. Adaptive cruise control systems that can be used in automobile industry to monitor distance and speed are described in this report. As a typical example, the principal operation of a laser guided mobile robot using a laser navigation system is also described.     

Static and dynamic wind turbine simulator using a converter controlled dc motor

This paper describes a new wind turbine simulator for dynamic conditions. The authors have developed an experimental platform to simulate the static and dynamic characteristics of real wind energy conversion system. This system consists of a 3 kW dc motor, which drives a synchronous generator. The converter is a 3 kW single-phase half-controlled converter. MATLAB/Simulink real time control software interfaced to I/O board and a converter controlled dc motor are used instead of a real wind turbine. A MATLAB/Simulink model is developed that obtains wind profiles and, by applying real wind turbine characteristics in dynamics and rotational speed of dc motor, calculates the command shaft torque of a real wind turbine. Based on the comparison between calculated torques with command one, the shaft torque of dc motor is regulated accordingly by controlling armature current demand of a single-phase half-controlled ac–dc converter. Simulation and experimental results confirm the effectiveness of proposed wind turbine simulator in emulating and therefore evaluating various turbines under a wide variety of wind conditions.     

Growing Innovative Calcium Carbonate Morphologies by Utilizing the Colloidal Gas Aphron System as a Surfactant-Based Template Method

Many studies have been conducted to study the various polymorphs and morphologies of calcium carbonate crystals in nature and living organisms. In this experimental work, a novel method has been employed to crystallize calcium carbonate by using colloidal gas aphron dispersion. The polymorph and morphology of prepared particles were investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectrometry techniques. SEM and XRD analyses demonstrated that the morphology of synthesized CaCO₃ can be changed from spherical (vaterite phase) to novel rod and plate-like shapes (mixture of vaterite and calcite phases) with changes in the surfactant concentration. The quantitative examination results of different calcium carbonate polymorph orientations showed that the precursor concentrations had no significant effect on the orientation of calcite phase, but rather they affected the orientation development of vaterite phase at a higher surfactant concentration.     

Direct and Residual Effects of Water Deficit Stress,Different Sources of Silicon and Plant-Growth Promoting Bacteria on Silicon Fractions in the Soil

Silicon - Silicon (Si) and plant growth promoting bacteria (PGPB) can effectively reduce the negative effects of water deficit stress and augment plant growth. Few studies have simultaneously...     

IsomiR-eQTL: A Cancer-Specific Expression Quantitative Trait Loci Database of miRNAs and Their Isoforms

The identification of expression quantitative trait loci (eQTL) is an important component in efforts to understand how genetic variants influence disease risk. MicroRNAs (miRNAs) are short noncoding RNA molecules capable of regulating the expression of several genes simultaneously. Recently, several novel isomers of miRNAs (isomiRs) that differ slightly in length and sequence composition compared to their canonical miRNAs have been reported. Here we present isomiR-eQTL, a user-friendly database designed to help researchers find single nucleotide polymorphisms (SNPs) that can impact miRNA (miR-eQTL) and isomiR expression (isomiR-eQTL) in 30 cancer types. The isomiR-eQTL includes a total of 152,671 miR-eQTLs and 2,390,805 isomiR-eQTLs at a false discovery rate (FDR) of 0.05. It also includes 65,733 miR-eQTLs overlapping known cancer-associated loci identified through genome-wide association studies (GWAS). To the best of our knowledge, this is the first study investigating the impact of SNPs on isomiR expression at the genome-wide level. This database may pave the way for researchers toward finding a model for personalised medicine in which miRNAs, isomiRs, and genotypes are utilised.