Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Real-Time Simulation of Electrical Machines on FPGA Platform

This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software

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.

Bacteria colonizing paper machines

Bacteria growing in paper machines can cause several problems. Biofilms detaching from paper machine surfaces may lead to holes and spots in the end product or even break the paper web leading to expensive delays in production. Heat stable endospores will remain viable through the drying section of paper machine, increasing the microbial contamination of paper and board. Of the bacterial species regularly found in the end products, Bacillus cereus is the only one classified as a pathogen. Certain B. cereus strains produce cereulide, the toxin that causes vomiting disease in food poisonings connected to B. cereus. The first aim of this thesis was to identify harmful bacterial species colonizing paper machines and to assess the role of bacteria in the formation of end product defects. We developed quantitative PCR methods for detecting Meiothermus spp. and Pseudoxanthomonas taiwanensis. Using these methods I showed that Meiothermus spp. and Psx. taiwanensis are major biofoulers in paper machines. I was the first to be able to show the connection between end product defects and biofilms in the wet-end of paper machines. I isolated 48 strains of primary-biofilm forming bacteria from paper machines. Based on one of them, strain K4.1T, I described a novel bacterial genus Deinobacterium with Deinobacterium chartae as the type species. I measured the transfer of Bacillus cereus spores from packaging paper into food. To do this, we constructed a green fluorescent protein (GFP) labelled derivative of Bacillus thuringiensis and prepared paper containing spores of this strain. Chocolate and rice were the recipient foods when transfer of the labelled spores from the packaging paper to food was examined. I showed that only minority of the Bacillus cereus spores transferred into food from packaging paper and that this amount is very low compared to the amount of B. cereus naturally occurring in foods. Thus the microbiological risk caused by packaging papers is very low. Until now, the biological function of cereulide for the producer cell has remained unknown. I showed that B. cereus can use cereulide to take up K+ from environment where K+ is scarce: cereulide binds K+ ions outside the cell with high affinity and transports these ions across cell membrane into the cytoplasm. Externally added cereulide increased the growth rate of cereulide producing strains in medium where potassium was growth limiting. In addition, cereulide producing strains outcompeted cereulide non-producing B. cereus in potassium deficient environment, but not when the potassium concentration was high. I also showed that cereulide enhances biofilm formation of B. cereus.

Easily Diagnosable Sequential Machines

This correspondence throws some light into the area of easily diagnosable machines. Given the behavior of a sequential machine in terms of a state table it explores the possibilities of designing a structure, that facilitates easy diagnosis of faults. The objective is achieved through structural decomposition which has already claimed to produce simpler physical realization.

A new approach to the kinetics of size reduction in ball milling

The rate of breakage of feed in ball milling is usually represented in the form of a first-order rate equation. The equation was developed by treating a simple batch test mill as a well mixed reactor. Several case of deviation from the rule have been reported in the literature. This is attributed to the fact that accumulated fines interfere with the feed material and breaking events are masked by these fines. In the present paper, a new rate equation is proposed which takes into account the retarding effect of fines during milling. For this purpose the analogy of diffusion of ions through permeable membranes is adopted, with suitable modifications. The validity of the model is cross checked with the data obtained in batch grinding of ?850/+600 ?m size quartz. The proposed equation enables calculation of the rate of breakage of the feed at any instant of time.

Minimizing total completion time on batch processing machines

We study the problem of minimizing total completion time on single and parallel batch processing machines. A batch processing machine is one which can process up to B jobs simultaneously. The processing time of a batch is equal to the largest processing time among all jobs in the batch. This problem is motivated by burn-in operations in the final testing stage of semiconductor manufacturing and is expected to occur in other production environments. We provide an exact solution procedure for the single-machine problem and heuristic algorithms for both single and parallel machine problems. While the exact algorithms have limited applicability due to high computational requirements, extensive experiments show that the heuristics are capable of consistently obtaining near-optimal solutions in very reasonable CPU times.

Combined Cryo and Room-Temperature Ball Milling to Produce Ultrafine Halide Crystallites

The combined milling at cryogenic temperature as well as room temperature (RT) has been carried out to prepare ultrafine NaCl crystallites. The milling has been done in evacuated tungsten carbide vials backfilled with high-purity Ar. The results indicate the effect duration of cryomilling prior to RT milling has a strong effect on the final crystallite size. The deformation aided sintering of NaCl crystallites during RT milling and leads to the formation of bimodal distribution of crystallites. The cuboidal-shaped NaCl crystallite undergoes a roughening transition due to plastic deformation. The experimental results are explained using the temperature-dependent mechanical properties of NaCl single crystals and plastic-deformation-induced roughening.

Milling maps and amorphization during mechanical alloying

The effect of various milling parameters such as, milling intensity, ball:powder weight ratio and number of balls on the glass forming ability of an elemental blend of composition Ti50Ni50 has been studied by mechanical alloying. In order to understand the results, all the milling parameters have been converted into two energy parameters, namely, impact energy of the ball and the total energy of milling. In a milling map of these two parameters, the conditions for amorphous phase formation have been isolated. A similar exercise has been carried out for Ti50Cu50 as a function of milling time at two milling intensities. The results indicate that a minimum impact energy of the ball and a minimum total energy are essential for amorphization by mechanical alloying.

Novel materials synthesis by mechanical alloying/milling

An account is given of the research that has been carried out on mechanical alloying/milling (MA/MM) during the past 25 years. Mechanical alloying, a high energy ball milling process, has established itself as a viable solid state processing route for the synthesis of a variety of equilibrium and non-equilibrium phases and phase mixtures. The process was initially invented for the production of oxide dispersion strengthened (ODS) Ni-base superalloys and later extended to other ODS alloys. The success of MA in producing ODS alloys with better high temperature capabilities in comparison with other processing routes is highlighted. Mechanical alloying has also been successfully used for extending terminal solid solubilities in many commercially important metallic systems. Many high melting intermetallics that are difficult to prepare by conventional processing techniques could be easily synthesised with homogeneous structure and composition by MA. It has also, over the years, proved itself to be superior to rapid solidification processing as a non-equilibrium processing tool. The considerable literature on the synthesis of amorphous, quasicrystalline, and nanocrystalline materials by MA is critically reviewed. The possibility of achieving solid solubility in liquid immiscible systems has made MA a unique process. Reactive milling has opened new avenues for the solid state metallothermic reduction and for the synthesis of nanocrystalline intermetallics and intermetallic matrix composites. Despite numerous efforts, understanding of the process of MA, being far from equilibrium, is far from complete, leaving large scope for further research in this exciting field.

An Approach for Distance Relay Co-ordination using Support Vector Machines

In this paper, an approach to enhance the Extra High Voltage (EHV) Transmission system distance protection is presented. The scheme depends on the apparent impedance seen by the distance relay during the disturbance. In a distance relay,the impedance seen at the relay location is calculated from the fundamental frequency component of the voltage and current signals. Support Vector Machines (SVMs) are a new learning-byexample are employed in discriminating zone settings (Zone-1,Zone-2 and Zone-3) using the signals to be used by the relay.Studies on 265-bus system, an equivalent of practical Indian Western grid are presented for illustrating the proposed scheme.