Fuzzy logic controller and cascade inverter for direct torque control of IM

In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.     

Optical properties of high-temperature heat-treated vitrinites

Three vitrinites (C = 80.0, 87.9 wt%, daf and 94.2 wt%, dmmf) have been heat-treated over the temperature range 1000–2400 °C in the presence of argon. The variation of morphological and optical properties of the heat-treated samples is studied systematically using reflected-light microscopy. An optically isotropic, highly reflecting material is formed on the surface of anisotropic particles of two of the vitrinites (C, 80 and 94.2 wt%) during semi-graphitization (1000–1400 °C), which decreases in extent with increasing temperature and is absent at the end of this stage. The development and subsequent disappearance of the isotropic material is probably due to the evolution of volatile matter and subsequent deposition of pyrolytic carbon during semi-graphitization. The continuous increase of bireflectance of these two vitrinite residues, with heat-treatment temperature, indicates progressive improvement in the ordering of the molecular structure. The reflectance of the heat-treated anthracitic vitrinite (C, 94.2 wt%), increases continuously whereas the reflectance of the heat-treated low-rank vitrinite (C, 80 wt% decreases slightly from a maximum during semi-graphitization. The third vitrinite (C, 87.9 wt%) does not develop an optically isotropic highly reflecting material on particle surfaces during semi-graphitization. However, this vitrinite softens during carbonization (25–1000 °C) producing a residue with a mosaictype anisotropic microstructure. The condition of polished surfaces prepared from residues of this vitrinite from the semi-graphitization to crystallization stages (1000–2300 °C) deteriorates, values of bireflectance and reflectance decrease continuously with increasing temperature. This appears to result from a reduction in the surface hardness of particles of this vitrinite residue resulting on transformation from two-dimensional ordering to three-dimensional graphitic ordering.     

Trace element geochemistry of the Obed Mountain deposit coals, Alberta, Canada

This study reports on the elemental concentrations and vertical variation of coal seams from the Obed Mountain deposit, Alberta Foothills, Canada. Results from two sections of Seam 1 show that the major elements (i.e. Al, Fe, Mg, K, Na, Ti, and Si) have high concentrations in intervals having high ash content, with the only exception of Ca. Similarities are apparent, in both sections, in the vertical variations of Th, U, Se, and Zn; Rb, Cs, and K; Sb, Mo, and W; Mn and Sr; and Ba, Cr, Co, Hf, and Sc. These similarities are also evident among the REEs, notably between Ce and La; also between Dy, Eu, and Sm. Most elements, with the exception of Ba and Sr are slightly more concentrated in Section 2 of Seam 1, located approximately 1.5Fig. km away from Section 1. Compared to Seam 1, Seam 2 has lower mean concentrations of elements. Boron in the coal ranges from 27 to 100 ppmw, though most values are less than 50 ppmw. Boron concentrations suggest a freshwater depositional environment. The element is depleted in the sedimentary partings (12–29 ppmw only) and is enriched in the coal interval near the roof and immediately beneath the partings. This enrichment shows possible downward mobilization of boron. Vertical variations of elements are helpful in delineating the boundaries between coal and sedimentary partings in the succession. The Obed Mountain coals are “clean” by world standards and their elemental concentrations are comparable with those in coals of a lower rank from the same coal formation used for power generation in Alberta. All sedimentary partings have low concentrations of Ba, Hf, Sc, Sr, Ta, Th, U, and REEs; this, along with the absence of an Eu negative anomaly suggests a non-volcanic origin for the partings.     

Mechanical characterization and modeling stress relaxation behavior of acrylic–polyurethane-based graft-interpenetrating polymer networks

The stress relaxation behavior of acrylic–polyurethane (PU)-based graft-interpenetrating polymer networks (IPNs) was characterized via dynamic mechanical analysis (DMA) and modeled using finite element method (FEM) analysis. Stress relaxation of glassy IPN specimens was experimentally studied under flexural testing, while rubbery IPN specimens were tested in tension. The effects of varying the styrene content in the acrylic copolymer phase, compatibility of the two phases in IPNs, and changing the concentration of acrylic copolymer and PU were studied. A higher percentage of styrene content resulted in higher homogeneity of IPN specimens, and decrease in initial modulus for acrylic copolymer specimens. Additionally, glassy IPN specimens with 90% styrene shows resistance to relaxation as high as acrylic copolymer samples. Experimental results were used to develop a numerical model to study stress relaxation response of specimens. While polymer systems have been studied computationally, numerical modeling of IPN systems is still in its infancy. A three-dimensional FEM model was developed using the Generalized Maxwell model and four-term Prony series constants, which were extracted from the stress relaxation experiments. With four terms in the Prony series, a good match was observed between experimental observations and results from the FEM model.     

A GMM/HMM model for reconstruction of missing speech spectral components for continuous speech recognition

This paper presents a method for reconstructing unreliable spectral components of speech signals using the statistical distributions of the clean components. Our goal is to model the temporal patterns in speech signal and take advantage of correlations between speech features in both time and frequency domain simultaneously. In this approach, a hidden Markov model (HMM) is first trained on clean speech data to model the temporal patterns which appear in the sequences of the spectral components. Using this model and according to the probabilities of occurring noisy spectral component at each states, a probability distributions for noisy components are estimated. Then, by applying maximum a posteriori (MAP) estimation on the mentioned distributions, the final estimations of the unreliable spectral components are obtained. The proposed method is compared to a common missing feature method which is based on the probabilistic clustering of the feature vectors and also to a state of the art method based on sparse reconstruction. The experimental results exhibits significant improvement in recognition accuracy over a noise polluted Persian corpus.     

Concept learning games

In this paper, we intend to have a game theoretic study on the concept learning problem in a multi-agent system. Concept learning is a very essential and well-studied domain of machine learning when it is studied under the characteristics of a multi-agent system. The most important reasons are the partiality of the environment perception for any agent and also the communication holdbacks, resulting into a deep need for a collaborative protocol in favor of multi-agent transactions. Here we wish to investigate multi-agent concept learning with the help of its components, thoroughly with a game theoretic taste, esp. on the pre-learning processes. Based on two standard notations, we address the non-unanimity of concepts, classification of objects, voting and communicating protocol, and also the learning itself. In such a game of concept learning, we consider a group of agents, communicating and consulting to upgrade their ontologies based on their conceptualizations of the environment. For this purpose, we investigate the problem in two separate and standard distinctions of game theory study, cooperation and competition. Several solution concepts and innovative ideas from the multi-agent realm are used to produce an approach that contains the reasoning process of the agents in this system. Some experimentations come at the end to show the functionality of our approach. These experimentations come distinctly for both cooperative and competitive views.     

A Fuzzy Logic-Based Method for Replica Placement in the Peer to Peer Cloud Using an Optimization Algorithm

The Peer to Peer-Cloud (P2P-Cloud) is a suitable alternative to distributed cloud-based or peer-to-peer (P2P)-based content on a large scale. The P2P-Cloud is used in many applications such as IPTV, Video-On-Demand, and so on. In the P2P-Cloud network, overload is a common problem during overcrowds. If a node receives many requests simultaneously, the node may not be able to respond quickly to user requests, and this access latency in P2P-Cloud networks is a major problem for their users. The replication method in P2P-Cloud environments reduces the time to access and uses network bandwidth by making multiple data copies in diverse locations. The replication improves access to the information and increases the reliability of the system. The data replication's main problem is identifying the best possible placement of replica data nodes based on user requests for data access time and an NP-hard optimization problem. This paper proposes a new replica replacement to improve average access time and replica cost using fuzzy logic and Ant Colony Optimization algorithm. Ants can find the shortest path to discover the optimal node to place the duplicate file with the least access time latency. The fuzzy module evaluates the historical information of each node to analyze the pheromone value per iteration. The fuzzy membership function is also used to determine each node's degree based on the four characteristics. The simulation results showed that the access time and replica cost are improved compared to other replica replacement algorithms.

     

Fullerene: biomedical engineers get to revisit an old friend

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Colloidal Quantum Dot Infrared Lasers Featuring Sub-Single-Exciton Threshold and Very High Gain

The use of colloidal quantum dots (CQDs) as a gain medium in infrared laser devices has been underpinned by the need for high pumping intensities, very short gain lifetimes, and low gain coefficients. Here, PbS/PbSSe core/alloyed-shell CQDs are employed as an infrared gain medium that results in highly suppressed Auger recombination with a lifetime of 485 ps, lowering the amplified spontaneous emission (ASE) threshold down to 300 µJ cm⁻², and showing a record high net modal gain coefficient of 2180 cm⁻¹. By doping these engineered core/shell CQDs up to nearly filling the first excited state, a significant reduction of optical gain threshold is demonstrated, measured by transient absorption, to an average-exciton population-per-dot 〈N^th〉_g of 0.45 due to bleaching of the ground state absorption. This in turn have led to a fivefold reduction in ASE threshold at 〈N^th〉_ASE = 0.70 excitons-per-dot, associated with a gain lifetime of 280 ps. Finally, these heterostructured QDs are used to achieve near-infrared lasing at 1670 nm at a pump fluences corresponding to sub-single-exciton-per-dot threshold (〈N^th〉_Las = 0.87). This work brings infrared CQD lasing thresholds on par to their visible counterparts, and paves the way toward solution-processed infrared laser diodes.     

Analysis and forecasting of IPO underpricing

Probability of withdrawal is a feature of initial public offering (IPOs), which can be an important parameter in decisions of investors and issuers. Considering the probability of offering withdrawal facilitates more precise estimation of underpricing. In this paper, the effective factors on probability of IPO withdrawal and underpricing in Tehran Stock Exchange have been characterized using regression, and then neural network is applied to estimate the probability of IPO withdrawal and underpricing. To evaluate the performance of our applied method, fuzzy regression is employed and compared with neural network. According to the obtained empirical results, neural network demonstrates better accuracy than fuzzy regression. The results indicate that there is a meaningful relationship between underpricing and probability of withdrawal, and the probability of IPO withdrawal plays an important role in precise evaluation of underpricing.