A fast algorithm for finding frequent episodes in event streams

Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the frequency of an episode is some suitable measure of how often the episode occurs in the data sequence. Recently,we proposed a new frequency measure for episodes based on the notion of non-overlapped occurrences of episodes in the event sequence, and showed that, such a definition, in addition to yielding computationally efficient algorithms, has some important theoretical properties in connecting frequent episode discovery with HMM learning. This paper presents some new algorithms for frequent episode discovery under this non-overlapped occurrences-based frequency definition. The algorithms presented here are better (by a factor of N, where N denotes the size of episodes being discovered) in terms of both time and space complexities when compared to existing methods for frequent episode discovery. We show through some simulation experiments, that our algorithms are very efficient. The new algorithms presented here have arguably the least possible orders of spaceand time complexities for the task of frequent episode discovery.

Discovering compressing serial episodes from event sequences

Most pattern mining methods yield a large number of frequent patterns, and isolating a small relevant subset of patterns is a challenging problem of current interest. In this paper, we address this problem in the context of discovering frequent episodes from symbolic time-series data. Motivated by the Minimum Description Length principle, we formulate the problem of selecting relevant subset of patterns as one of searching for a subset of patterns that achieves best data compression. We present algorithms for discovering small sets of relevant non-redundant episodes that achieve good data compression. The algorithms employ a novel encoding scheme and use serial episodes with inter-event constraints as the patterns. We present extensive simulation studies with both synthetic and real data, comparing our method with the existing schemes such as GoKrimp and SQS. We also demonstrate the effectiveness of these algorithms on event sequences from a composable conveyor system; this system represents a new application area where use of frequent patterns for compressing the event sequence is likely to be important for decision support and control.

Generation of H2O2 in biomembranes

Knowledge of the generation of H202 in cellular oxidations has existed for many years. It has been assumed that H202 is tOxiC tO cells and the presence of catalase is indicative of a detoxication mechanism. Other radicals of oxygen were recently recognized to be more potent destructive agents of biological material than H202. Also catalase and other peroxidases utilize H202 in some cellular oxidation processes leading to several important metabolites. Thus, the generation of H202 in cellular processes seems to be purposeful and H202 can not be dismissed as a mere undesirable byproduct. Biological formation of H202 is not limited to the previously known flavoproteins and some copper enzymes, but other redox systems, particularly heme and non-heme iron proteins, are now found to undergo auto-oxidation yielding H202. The capacity for generation of H202 is now found to be widespread in a variety of organisms and in the organdies of the cells. The reduction of oxygen to H20 by mitochondrial cytochrome oxidase being the predominant oxygen-utilizing reaction had over-shadowed the importance of the quantitatively minor pathways. Under aerobic conditions generation of H202 by a Variety of biomembranes has now been found to be a physiological event interlinked with phenomena such as phagocytosis, transport processes and thermogenesis in some as yet unidentified way. The underlying mechanisms of these processes seem to involve generation and utilization of H202 in mitochondria, microsomes, peroxisomes or plasma membranes. This review gives an account of the potential of biomembranes to generate H202 and its implication in the cellular processes.

A knowledge-based clustering scheme

In this paper the notion of conceptual cohesiveness is precised and used to group objects semantically, based on a knowledge structure called ‘cohesion forest’. A set of axioms is proposed which should be satisfied to make the generated clusters meaningful.

Studies on characteristics of lightning generated currents in an interconnected lightning protection system

An in-depth knowledge about the characteristics of lightning generated currents will facilitate evaluation of the interception efficacy of lightning protection systems. In addition, it would aid in extraction of valuable statistics (from measured current data) on local lightning parameters. Incidentally, present day knowledge on characteristics of lightning induced current in typical lightning protection systems is rather limited. This is particularly true with closely interconnected protection systems, like the one employed in Indian Satellite Launch Pad-II. This system is taken as a specific example in the present study. Various aspects suggest that theoretical modelling would be the best possible approach for the intended work. From the survey of pertinent literature, it is concluded that electromagnetic modelling of lightning return-stroke with current source at the channel base is best suited for this study. Numerical electromagnetic code was used for the required electromagnetic field solution and Fourier transform techniques were employed for computing time-domain results. A validation for the numerical modelling is provided by laborator experiments on a reduced scale model of the system. Apart from ascertaining the influence of various parameters, salient characteristics of tower base currents for different kinds of events are deduced. This knowledge can be used in identifying the type of event, as well as its approximate location. A method for estimation of injected stroke current has also been proposed.

Microprocessor-based event sequence recorder

An event sequence recorder is a specialized piece of equipment that accepts inputs from switches and contactors, and prints the sequence in which they operate. This paper describes an event sequence recorder based on an Intel 8085 microprocessor. It scans the inputs every millisecond and prints in a compact form the channel number, type of event (normal or abnormal) and time of occurrence. It also communicates these events over an RS232C link to a remote computer. A realtime calendar/clock is included. The system described has been designed for continuous operation in process plants, power stations etc. The system has been tested and found to be working satisfactorily.

K-Ar ages of biotite and muscovite from Pangong metamorphic complex, Shyok suture zone, India: Implications for the youngest post-collision metamorphic event in Ladakh Himalaya

The garnet-kyanite-staurolite and garnet-biotite-staurolite gneisses were collected from a locality within Lukung area that belongs to the Pangong metamorphic complex in Shyok valley, Ladakh Himalaya. The kyanite-free samples have garnet and staurolite in equilibrium, where garnets show euhedral texture and have flat compositional profile. On the other hand, the kyanite-bearing sample shows equilibrium assemblage of garnet-kyanite-staurolite along with muscovite and biotite. In this case, garnet has an inclusion rich core with a distinct grain boundary, which was later overgrown by inclusion free euhedral garnet. Garnet cores are rich in Mn and Ca, while the rims are poor in Mn and rich in Fe and Mg, suggesting two distinct generations of growth. However, the compositional profiles and textural signature of garnets suggests the same stage of P -T evolution for the formation of the inclusion free euhedral garnets in the kyanite-free gneisses and the inclusion free euhedral garnet rims in the kyanite-bearing gneiss. Muscovites from the four samples have consistent K-Ar ages, suggesting the cooling age (∼ 10 Ma) of the gneisses. These ages make a constraint on the timing of the youngest post-collision metamorphic event that may be closely related to an activation of the Karakoram fault in Pangong metamorphic complex.

Understanding the Knowledge Needs of Designers During Design Process in Industry

Product success is substantially influenced by satisfaction of knowledge needs of designers, and many tools and methods have been proposed to support these needs. However, adoption of these methods in industry is minimal. This may be due to an inadequate understanding of the knowledge needs of designers in industry. This research attempts to develop a better understanding of these needs by undertaking descriptive studies in an industry. We propose a taxonomy of knowledge, and evaluate this by analyzing the questions asked by the designers involved in the study during their interactions. Using the taxonomy, we converted the questions asked into a generic form. The generic questions provide an understanding about what knowledge must be captured during design, and what its structure should be.