Real-time data mining of massive data streams from synoptic sky surveys

The nature of scientific and technological data collection is evolving rapidly: data volumes and rates grow exponentially, with increasing complexity and information content, and there has been a transition from static data sets to data streams that must be analyzed in real time. Interesting or anomalous phenomena must be quickly characterized and followed up with additional measurements via optimal deployment of limited assets. Modern astronomy presents a variety of such phenomena in the form of transient events in digital synoptic sky surveys, including cosmic explosions (supernovae, gamma ray bursts), relativistic phenomena (black hole formation, jets), potentially hazardous asteroids, etc. We have been developing a set of machine learning tools to detect, classify and plan a response to transient events for astronomy applications, using the Catalina Real-time Transient Survey (CRTS) as a scientific and methodological testbed. The ability to respond rapidly to the potentially most interesting events is a key bottleneck that limits the scientific returns from the current and anticipated synoptic sky surveys. Similar challenge arises in other contexts, from environmental monitoring using sensor networks to autonomous spacecraft systems. Given the exponential growth of data rates, and the time-critical response, we need a fully automated and robust approach. We describe the results obtained to date, and the possible future developments.     

OCPAD: One class Naive Bayes classifier for payload based anomaly detection

Application specific attack detection requires packet payload analysis. Current payload analysis techniques suffer from failed detection as they use only the presence or absence of short sequences of a packet in a knowledge-base created out of non-malicious packets. In this paper, we describe OCPAD a content anomaly detection method to identify network packets with suspicious payload content. Proposed method combines the benefits of one class classification and frequency information of short sequences.We adapt one class Multinomial Naive Bayes classifier as anomaly detector for detecting HTTP attacks. OCPAD uses likelihood of each short sequence’s occurrence in a payload of known non-malicious packets as a measure to derive the degree of maliciousness of a packet. In the training phase, OCPAD generates the likelihood range of each sequence’s occurrence from every packet. In order to store the likelihood range of these sequences, we propose a novel and efficient data structure called Probability Tree. In the testing phase, it treats a short sequence as anomalous if it is not found in the database or its likelihood of occurrence in a packet is not in the range found in training phase. Using the likelihood of anomalous short sequences, it generates a class label for a test packet. Our experiments with a large dataset of 1 million HTTP packets collected from an academic network revealed OCPAD has a high Detection Rate (up to 100%) compared to previous methods and acceptable rate of False Positives (less than 0.6%).     

Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach

Genetic algorithm is well-known of its best heuristic search method. Fuzzy logic unveils the advantage of interpretability. Genetic fuzzy system exploits potential of optimization with ease of understanding that facilitates rules optimization. This paper presents the optimization of fourteen fuzzy rules for semi expert judgment automation of early activity based duration estimation in software project management. The goal of the optimization is to reduce linguistic terms complexity and improve estimation accuracy of the fuzzy rule set while at the same time maintaining a similar degree of interpretability. The optimized numbers of linguistic terms in fuzzy rules by 27.76% using simplistic binary encoding mechanism managed to improve accuracy by 14.29% and reduce optimization execution time by 6.95% without compromising on interpretability in addition to promote improvement of knowledge base in fuzzy rule based systems.     

Anorexic contribution to increased linoleate mobilization and oxidation in lymphoma-bearing mice

To test for a regulatory defect in adipose triacylglycerol (essential) fatty acid mobilization in lymphoma-bearing mice, free [1-¹⁴C]linoleic acid/mouse serum albumin was injectediv into lymphoma-bearing and control mice, adapted to a reversed light cycle, and studied in three dietary states in the dark period. Mean daily food intake decreased in mice with small and large tumor burdens. Plasma free fatty acid (FFA) oxidation rates, which approximate FFA mobilization rates, were estimated by multicompartmental analysis (CONSAM). Oxidation of linoleate to CO₂ was reduced significantly (85%) inad libitum fed as compared to briefly fasted control mice but not in fedvs. fasted mice with large or small tumor burdens. However, plasma FFA oxidation rates to CO₂ did not differ in briefly fasted tumor-bearing and pairfed control mice. When re-fed a 250-mg test meal, briefly fasted mice with small tumors suppressed plasma free linoleic acid oxidation, as did controls. During simulated night, mildly anorexic, tumor-bearing mice with small tumor burdens mobilized essential fatty acids much faster than controls. This could explain body fat loss. The abnormally rapid rates of FFA (free linoleic acid) mobilization at night probably result from anorexia rather than from inability of food to suppress fat mobilization.     

Transmission of an explosion between linked vessels

Small scale experiments on explosion transmission through a narrow cylindrical tube (diameter: 3.0–8.3 mm) between two cylindrical vessels were performed, using a stoichiometric C₃H₆/air mixture at various initial pressures within the range 20–120 kPa. The successful explosion transmission between the linked vessels occurred above a critical initial pressure, which increases when the tube diameter decreases. The critical pressure of transmission measured for upward flame propagation is lower than the one for downward propagation, at each value of the tube diameter. Different patterns of pressure evolution were observed for upward and downward flame propagation. The influence of the tube diameter and initial pressure on the characteristic features of explosion evolution in each vessel (the peak pressures, the maximum rates of pressure rise and the time delay between ignition in the primary and secondary vessel) are discussed.     

Light scattering for particle characterization

Light scattering has proved to be one of the most powerful techniques for probing the properties of particulate systems. The purpose of this paper is to review the status of elastic light scattering. The emphasis is on recent developments, rather than being over-repetitive of earlier reviews, but considerable background is included with the aim of making the paper self-contained. There is an extensive summary of theoretical treatments, including both historical work and new. On the experimental side, while there is some discussion of well-tried methods, the emphasis is on recent techniques for measuring other properties as well as size. This includes, among others, the fractal treatment of agglomerates, determination of particle shape and measurement of refractive index. The discussion is broad rather than deep to provide a wide-ranging review of an extremely active field.