Semigroups on Frechet spaces and equations with infinite delays

In this paper, we show existence and uniqueness of a solution to a functional differential equation with infinite delay. We choose an appropriate Frechet space so as to cover a large class of functions to be used as initial functions to obtain existence and uniqueness of solutions.

Support vector machine approach for the switching transient peak overvoltages during line energization

At the time of restoration transmission line switching is one of the major causes, which creates transient overvoltages. Though detailed Electro Magnetic Transient studies are carried out extensively for the planning and design of transmission systems, such studies are not common in a day-today operation of power systems. However it is important for the operator to ensure during restoration of supply that peak overvoltages resulting from the switching operations are well within safe limits. This paper presents a support vector machine approach to classify the various cases of line energization in the category of safe or unsafe based upon the peak value of overvoltage at the receiving end of line. Operator can define the threshold value of voltage to assign the data pattern in either of the class. For illustration of proposed approach the power system used for switching transient peak overvoltages tests is a 400 kV equivalent system of an Indian southern gri

Improved switching frequency variation control of hysteresis controlled voltage source inverter-fed IM drives using current error space vector

A constant switching frequency current error space vector-based hysteresis controller for two-level voltage source inverter-fed induction motor (IM) drives is proposed in this study. The proposed controller is capable of driving the IM in the entire speed range extending to the six-step mode. The proposed controller uses the parabolic boundary, reported earlier, for vector selection in a sector, but uses simple, fast and self-adaptive sector identification logic for sector change detection in the entire modulation range. This new scheme detects the sector change using the change in direction of current error along the axes jA, jB and jC. Most of the previous schemes use an outer boundary for sector change detection. So the current error goes outside the boundary six times during sector change, in one cycle,, introducing additional fifth and seventh harmonic components in phase current. This may cause sixth harmonic torque pulsations in the motor and spread in the harmonic spectrum of phase voltage. The proposed new scheme detects the sector change fast and accurately eliminating the chance of introducing additional fifth and seventh harmonic components in phase current and provides harmonic spectrum of phase voltage, which exactly matches with that of constant switching frequency voltage-controlled space vector pulse width modulation (VC-SVPWM)-based two-level inverter-fed drives.

Stimulation by adenosine 3′,5′-cyclic monophosphate of protein synthesis by adenohypophyseal polyribosomes

Addition of dibutyryl 3′,5′-cyclic AMP to slices of bovine pituitary stimulated incorporation of [3H]leucine into protein, whether or not actinomycin D was present; therefore the influence of 3′,5′-cyclic AMP on protein synthesis by bovine pituitary polysomes was studied. If the cyclic nucleotide was added to the complete protein-synthesizing system (including pH 5.0 enzyme), stimulation of [3H]leucine incorporation occurred only with pH 5.0 enzyme from rat liver; there was no stimulation when homologous enzyme, i.e., from bovine pituitary, was used. Addition of 3′,5′-cyclic AMP to the polysomes, before addition of pH 5.0 enzyme, resulted in stimulation of protein synthesis with either source of enzyme, but stimulation was facilitated to a greater degree, over the range 0.5-2 mM 3′,5′-cyclic AMP, when rat liver was the source. The stimulation of protein synthesis was prevented by the addition of cycloheximide. With rat liver pH 5.0 enzyme the product of hydrolysis of 3′,5′-cyclic AMP was mainly 5′-AMP whereas with pituitary pH 5.0 enzyme there was also dephosphorylation and deamination resulting in production of hypoxanthine and other bases. However, using either source of pH 5.0 enzyme and the complete protein-synthesizing system (i.e., including an ATP-regenerating mechanism) most of the 3H from hydrolysis of [3H]3′,5′-cyclic AMP was incorporated into ATP. The data are seen as compatible with a stimulation by 3′,5′-cyclic AMP of translation by pituitary polysomes; the significance of the importance of the source of pH 5.0 enzyme used in the system is obscure.

Reaction of benzisoxazolium cations with cyclic β-diketones

Reaction of 2-ethylbenzisoxazolium fluoborate (III) with dimedone, dihydroresorcinol, 2-methyldihydroresorcinol and 2-methylcyclopentane-1,3-dione in the presence of base leads to the formation of amides VIII, XI, X and XIII respectively, via the benzoketoketenimine intermediate (IX) and an intramolecular migration. The 7-hydroxy-2-ethylbenzisoxazolium salt (IV) gives the amide (XIV) by double migration. Amides VIII, XI, X and XIII undergo intramolecular Michael reaction to furnish the benzoxazinones (XVI, XVIII, XVII and XXVI). Stereochemistry of this addition is discussed and the conformation in which the CN bond at C-1′ is attached equatorially to the cyclohexanone ring is assigned to the Spirans (XX, XXX and XXVIII). Effect of acids and bases on the amide (VIII) and the spiran (XVI) is described.

Synthesis, structure, transformation studies and catalytic properties of open-framework cadmium thiosulfate compounds

Five new thiosulfate based inorganic-organic hybrid open-framework compounds have been synthesized employing mild reaction conditions. Of the five compounds, [Na-2(H2O)(8)][Cd(C10H8N2)( S2O3)(2)]center dot 2H(2)O, I and [Cd-2(C10H8N2)(2)(HS2O3)(2)(S2O3)(2)][(C10H9N2)(2)(C10H8N2)(2)]center dot 8H(2)O, II have one-dimensional (1D) structures and [Cd(C10H8N2)(H2O)(2)(S2O3)]center dot 2H(2)O, III, [Cd-2(C10H8N2)(3)(S2O3)(2)], IV and [Cd-2(C10H8N2)(2.5)(S2O3)(2)], V have three- dimensional (3D) structures. The 1D structures are somewhat related, formed by the bonding between tetrahedral Cd centers (CdN2S2) and 4,4'-bipyridine (bpy) units. The inter-chain spaces are occupied by the hanging thiosulfate units in both the cases along with Na(H2O)(6) chains in I and free bpy units in II. The three 3D structures have one-dimensional cadmium thiosulfate chains linked by bpy units. Interpenetration has been observed in all the 3D structures. The 3D structures appear to be related and can be derived from fgs net. Transformation studies on the 1D compound, [Na-2(H2O)(8)][Cd(C10H8N2)(S2O3)(2)]center dot 2H(2)O, I, indicated a facile formation of [Cd(C10H8N2)(H2O)(2)(S2O3)]center dot 2H(2)O, III. Prolonged heating of I gave rise to a 3D cadmium sulfate phase, [Cd-2(C10H8N2)(2)(H2O)(3)(SO4)(2)]center dot 2H(2)O, VI. Compound VI has one-dimensional cadmium sulfate chains formed by six-membered rings connected by bpy units to form a 3D structure, which appears to resemble the topological arrangement of III. Transformation studies of III indicates the formation of IV and V, and at a higher temperature a new 3D cadmium sulfate, [Cd(C10H8N2)(SO4)], VII. Compound VII has a 4 x 4 grid cadmium sulfate layers pillared by bpy units. All the compounds were characterized by PXRD, TGA, IR and UV-visible studies. Preliminary studies on the possible use of the 3D compounds (III-VII) in heterogeneous cyanosilylation of imines appear to be promising.

Comparison of Multiclass SVM Classification Methods to Use in a Supportive System for Distance Relay Coordination

This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.

Electron diffraction patterns from the Al-Mn decagonal phase

The variety of electron diffraction patterns arising from the decagonal phase has been explored using a stereographic analysis for generating the important zone axes as intersection points corresponding to important relvectors. An indexing scheme employing a set of five vectors and an orthogonal vector has been followed. A systematic tilting from the decagonal axis to one of the twofold axes has been adopted to generate a set of experimental diffraction patterns corresponding to the expected patterns from the stereographic analysis with excellent agreement.

Switching frequency variation control in hysteresis PWM controller for IM drives using variable parabolic bands for current error space phasor

Variation of switching frequency over the entire operating speed range of an induction motor (M drive is the major problem associated with conventional two-level three-phase hysteresis controller as well as the space phasor based PWM hysteresis controller. This paper describes a simple hysteresis current controller for controlling the switching frequency variation in the two-level PWM inverter fed IM drives for various operating speeds. A novel concept of continuously variable hysteresis boundary of current error space phasor with the varying speed of the IM drive is proposed in the present work. The variable parabolic boundary for the current error space phasor is suggested for the first time in this paper for getting the switching frequency pattern with the hysteresis controller, similar to that of the constant switching frequency voltage-controlled space vector PWM (VC-SVPWM) based inverter fed IM drive. A generalized algorithm is also developed to determine parabolic boundary for controlling the switching frequency variation, for any IM load. Only the adjacent inverter voltage vectors forming a triangular sector, in which tip of the machine voltage vector ties, are switched to keep current error space vector within the parabolic boundary. The controller uses a self-adaptive sector identification logic, which provides smooth transition between the sectors and is capable of taldng the inverter up to six-step mode of operation, if demanded by drive system. The proposed scheme is simulated and experimentally verified on a 3.7 kW IM drive.

Stability of scheduled message communication over degraded broadcast channels

We develop a multi-class discrete-time processor-sharing queueing model for scheduled message communication over a discrete memoryless degraded broadcast channel. The framework we consider here models both the random message arrivals and the subsequent reliable communication by suitably combining techniques from queueing theory and information theory. Requests for message transmissions are assumed to arrive according to i.i.d. arrival processes. Then, (i) we derive an outer bound to the stability region of message arrival rate vectors achievable by the class of stationary scheduling policies, (ii) we show for any message arrival rate vector that satisfies the outer bound, that there exists a stationary "state-independent" policy that results in a stable system for the corresponding message arrival processes, and (iii) under an asymptotic regime, we show that the stability region of information arrival rate vectors is the information-theoretic capacity region of a degraded broadcast channel.

An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Cluster based core vector machine

Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.

Minimum enclosing spheres formulations for support vector ordinal regression

We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. Both approaches guarantee that the radii of the spheres are properly ordered at the optimal solution. The size of the optimization problem is linear in the number of training samples. The popular SMO algorithm is adapted to solve the resulting optimization problem. Numerical experiments on some real-world data sets verify the usefulness of our approaches for data mining.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.