Advances in Data Mining Knowledge Discovery and Applications

Advances in Data Mining Knowledge Discovery and Applications aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining. It seems to be same things are repeated again. But in general, same approach and techniques may help us in different fields and expertise areas. This book presents knowledge discovery and data mining applications in two different sections. As known that, data mining covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, and other areas. In this book, most of the areas are covered with different data mining applications. The eighteen chapters have been classified in two parts: Knowledge Discovery and Data Mining Applications

A Framework for Discovery and Diagnosis of Behavioral Transitions in Event-streams

Date stream mining techniques can be used in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models identify potential changes in user goal attainment. When the quality of some data mined models varies significantly from nearby models—as defined by quality metrics—then the user’s behavior is automatically flagged as a potentially significant behavioral change. Decision tree, sequence pattern and Hidden Markov modeling being used in this study. These three types of modeling can expose different aspect of user’s behavior. In case of decision tree modeling, the specific changes in user behavior can automatically characterized by differencing the data-mined decision-tree models. The sequence pattern modeling can shed light on how the user changes his sequence of actions and Hidden Markov modeling can identifies the learning transition points. This research describes how model-quality monitoring and these three types of modeling as a generic framework can aid recognition and diagnoses of behavioral changes in a case study of cognitive rehabilitation via emailing. The date stream mining techniques mentioned are used to monitor patient goals as part of a clinical plan to aid cognitive rehabilitation. In this context, real time data mining aids clinicians in tracking user behaviors as they attempt to achieve their goals. This generic framework can be widely applicable to other real-time data-intensive analysis problems. In order to illustrate this fact, the similar Hidden Markov modeling is being used for analyzing the transactional behavior of a telecommunication company for fraud detection. Fraud similarly can be considered as a potentially significant transaction behavioral change

Systemic Iron Regulation and Adipose Tissue Inflammation in Health and Disease.

Iron dysregulation can lead to serious health concerns resulting from either too much or too little iron storage and availability. For example, iron deficiency anemia results in a reduced exercise tolerance, while chronic conditions such as obesity and type 2 diabetes may predispose individuals to tissue iron overload. The relatively recent discovery of hepcidin, the major iron-regulating hormone, has led to new hypotheses regarding conditions of iron dysregulation, including exercise-induced iron deficiency. A series of recent studies have suggested that exercise-induced iron deficiency might result from a transient increase in circulating hepcidin following acute exercise. However, it is unclear whether there is a cumulative effect of multiple acute excursions of hepcidin in response to everyday training. On the opposite end of the iron dysregulation spectrum, excess iron deposition is a potential contributor to the pathology of obesity-related metabolic complications. However, the underlying mechanisms are still unclear. The major findings from my dissertation studies include: in STUDY#1, the iron-regulating hormone, hepcidin, is not chronically elevated with sustained training in competitive collegiate runners, who have a high risk of iron deficiency (p>0.05); In STUDY#2, a high level of iron in the epididymal adipose tissue was accompanied by a robust adipose tissue remodeling, characterized by increased macrophages, fibrosis, cell death and elevated inflammation; In Study#3, five weeks voluntary exercise reduced weight, improved glucose intolerance and altered adipose tissue inflammatory gene expression in female polygenic obese KK mice. Contrary to our hypothesis, in STUDY#3, exercise did not improve the serum iron levels in KK mice and in STUDY#2 we observed no relationship between adipose tissue iron deposition and glucose homeostasis. Together the three projects enhanced our understanding of the underlying cause of exercise-induced iron deficiency anemia in female athletes as well as the relationship among the risks of diabetes, iron overload and exercise.PhDKinesiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111483/1/xiaoyama_1.pd

African traditional medicine-antiretroviral interactions : effects of Sutherlandia frutescens on the pharmacokinetics of Atazanavir

In response to the urgent call for investigations into antiretroviral (ARV)-African traditional medicine (ATM) interactions, this research was undertaken to ascertain whether chronic administration of the ATM, Sutherlandia frutescens (SF) may alter the bioavailability of the protease inhibitor (PI), atazanavir (ATV), which may impact on the safety or efficacy of the ARV. Prior to investigating a potential interaction between ATV and SF in vitro and in vivo, a high performance liquid chromatography method with ultraviolet detection (HPLC-UV) was developed and validated for the bioanalysis of ATV in human plasma and liver microsomes. An improved and efficient analytical method with minimal use of solvents and short run time was achieved in comparison to methods published in the literature. In addition, the method was selective, linear, accurate and precise for quantitative analysis of ATV in these studies. Molecular docking studies were conducted to compare the binding modes and affinities of ATV and two major SF constituents, Sutherlandioside B and Sutherlandin C, with the efflux transporter, P-glycoprotein (P-gp) and the CYP450 isoenzyme, CYP3A4 to determine the potential for these phytochemicals to competitively inhibit the binding of ATV to these two proteins, which are mediators of absorption and metabolism. These studies revealed that modulation of P-gp transport of ATV by Sutherlandioside B and Sutherlandin C was not likely to occur via competitive inhibition. The results further indicated that weak competitive inhibition of CYP3A4 may possibly occur in the presence of either of these two SF constituents. The Caco-2 cell line was used as an in vitro model of human intestinal absorption. Accumulation studies in these cells were conducted to ascertain whether extracts and constituents of SF have the ability to alter the absorption of ATV. The results showed that the aqueous extract of SF significantly reduced ATV accumulation, suggesting decreased ATV absorption, whilst a triterpenoid glycoside fraction isolated from SF exhibited an opposing effect. Analogous responses were elicited by the aqueous extract and a triterpenoid glycoside fraction in similar accumulation studies in P-gp overexpressing Madin–Darby Canine Kidney Strain II cells (MDCKII-MDR1), which signified that the effects of this extract and component on ATV transport in the Caco-2 cells were P-gp-mediated. The quantitative analysis of ATV in human liver microsomes after co-incubation with extracts and components of SF was conducted to determine the effects of SF on the metabolism of ATV. The aqueous and methanolic extracts of SF inhibited ATV metabolism, whilst the triterpenoid glycoside fraction had a converse effect. Analogous effects by the extracts were demonstrated in experiments conducted in CYP3A4-transfected microsomes, suggesting that the inhibition of ATV metabolism in the liver microsomes by these SF extracts was CYP3A4-mediated. A combination of Sutherlandiosides C and D also inhibited CYP3A4-mediated ATV metabolism, which was in contrast to the response elicited by the triterpenoid fraction in the liver microsomes, where other unidentified compounds, shown to be present therein, may have contributed to the activation of ATV metabolism. The in vitro studies revealed the potential for SF to alter the bioavailability of ATV, therefore a clinical study in which the effect of a multiple dose regimen of SF on the pharmacokinetics (PK) of a single dose of ATV was conducted in healthy male volunteers. The statistical analysis showed that the 90 % confidence intervals around the geometric mean ratios (ATV + SF/ATV alone) for both Cmax and AUC0-24 hours, fell well below the lower limit of the "no-effect" boundary of 0.8 – 1.25, implying that the bioavailability of ATV was significantly reduced in this cohort of subjects. It may thus be concluded that if the reduction in bioavailability observed in this clinical study is found to be clinically relevant, co-administration of SF commercial dosage forms and ATV in HIV/AIDS patients may potentially result in subtherapeutic ATV levels, which may in turn contribute to ATV resistance and/or treatment failure. This research has therefore highlighted the potential risk for toxicity or lack of efficacy of ARV regimens which may result when ATMs and PIs are used concurrently and that patients and health care practitioners alike should be aware of these perils

Proceedings. 25. Workshop Computational Intelligence, Dortmund, 26. - 27. November 2015

Dieser Tagungsband enthält die Beiträge des 25. Workshops „Computational Intelligence“ des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) , der vom 26. – 27. November 2015 in Dortmund stattfindet

Modélisation formelle des systèmes de détection d'intrusions

L’écosystème de la cybersécurité évolue en permanence en termes du nombre, de la diversité, et de la complexité des attaques. De ce fait, les outils de détection deviennent inefficaces face à certaines attaques. On distingue généralement trois types de systèmes de détection d’intrusions : détection par anomalies, détection par signatures et détection hybride. La détection par anomalies est fondée sur la caractérisation du comportement habituel du système, typiquement de manière statistique. Elle permet de détecter des attaques connues ou inconnues, mais génère aussi un très grand nombre de faux positifs. La détection par signatures permet de détecter des attaques connues en définissant des règles qui décrivent le comportement connu d’un attaquant. Cela demande une bonne connaissance du comportement de l’attaquant. La détection hybride repose sur plusieurs méthodes de détection incluant celles sus-citées. Elle présente l’avantage d’être plus précise pendant la détection. Des outils tels que Snort et Zeek offrent des langages de bas niveau pour l’expression de règles de reconnaissance d’attaques. Le nombre d’attaques potentielles étant très grand, ces bases de règles deviennent rapidement difficiles à gérer et à maintenir. De plus, l’expression de règles avec état dit stateful est particulièrement ardue pour reconnaître une séquence d’événements. Dans cette thèse, nous proposons une approche stateful basée sur les diagrammes d’état-transition algébriques (ASTDs) afin d’identifier des attaques complexes. Les ASTDs permettent de représenter de façon graphique et modulaire une spécification, ce qui facilite la maintenance et la compréhension des règles. Nous étendons la notation ASTD avec de nouvelles fonctionnalités pour représenter des attaques complexes. Ensuite, nous spécifions plusieurs attaques avec la notation étendue et exécutons les spécifications obtenues sur des flots d’événements à l’aide d’un interpréteur pour identifier des attaques. Nous évaluons aussi les performances de l’interpréteur avec des outils industriels tels que Snort et Zeek. Puis, nous réalisons un compilateur afin de générer du code exécutable à partir d’une spécification ASTD, capable d’identifier de façon efficiente les séquences d’événements.Abstract : The cybersecurity ecosystem continuously evolves with the number, the diversity, and the complexity of cyber attacks. Generally, we have three types of Intrusion Detection System (IDS) : anomaly-based detection, signature-based detection, and hybrid detection. Anomaly detection is based on the usual behavior description of the system, typically in a static manner. It enables detecting known or unknown attacks but also generating a large number of false positives. Signature based detection enables detecting known attacks by defining rules that describe known attacker’s behavior. It needs a good knowledge of attacker behavior. Hybrid detection relies on several detection methods including the previous ones. It has the advantage of being more precise during detection. Tools like Snort and Zeek offer low level languages to represent rules for detecting attacks. The number of potential attacks being large, these rule bases become quickly hard to manage and maintain. Moreover, the representation of stateful rules to recognize a sequence of events is particularly arduous. In this thesis, we propose a stateful approach based on algebraic state-transition diagrams (ASTDs) to identify complex attacks. ASTDs allow a graphical and modular representation of a specification, that facilitates maintenance and understanding of rules. We extend the ASTD notation with new features to represent complex attacks. Next, we specify several attacks with the extended notation and run the resulting specifications on event streams using an interpreter to identify attacks. We also evaluate the performance of the interpreter with industrial tools such as Snort and Zeek. Then, we build a compiler in order to generate executable code from an ASTD specification, able to efficiently identify sequences of events

Third International Symposium on Space Mission Operations and Ground Data Systems, part 2

Under the theme of 'Opportunities in Ground Data Systems for High Efficiency Operations of Space Missions,' the SpaceOps '94 symposium included presentations of more than 150 technical papers spanning five topic areas: Mission Management, Operations, Data Management, System Development, and Systems Engineering. The symposium papers focus on improvements in the efficiency, effectiveness, and quality of data acquisition, ground systems, and mission operations. New technology, methods, and human systems are discussed. Accomplishments are also reported in the application of information systems to improve data retrieval, reporting, and archiving; the management of human factors; the use of telescience and teleoperations; and the design and implementation of logistics support for mission operations. This volume covers expert systems, systems development tools and approaches, and systems engineering issues

The role and regulation of nuclear myosins in DNA damage

Unconventional myosins have often been characterised within the cytoplasm of the cell, however little work has been done to characterise their role within the nucleus. The first nuclear myosin was identified within the 1990s and since then eight types of myosin have been found within the nucleus. The first to be found and the one myosin that has been heavily characterised is nuclear myosin 1. This myosin has a role in transcription, as well as chromatin movement after DNA damage. Myosin VI another myosin recently found in the nucleus has also been attributed to stable transcription, and, like nuclear myosin 1 can also bind to the RNA polymerase II complex. So far, a full length structure of nuclear myosin I is yet to be defined, here in this thesis, using typical biochemical techniques, an interaction between the N-terminus of the protein and the nuclear localisation sequence has been identified, along with disassociation constants, that finally show a direct interaction between DNA and the myosin. As well as this, MVI has had another role in the nucleus, which is observed after the induction of double strand breaks within DNA. This thesis discusses why MVI is vital for double strand break signalling, as cellular biology techniques have shown the lack of γH2AX signalling the motor domain of MVI is inhibited. Not only is a working MVI necessary for when signalling DNA damage, this thesis has also found direct interactions with histones and their modifiers. As both nuclear myosins are involved in transcription, this thesis has looked at how these two myosins interact, and looks further into their nuclear import, roles in the DNA damage response, and how they are regulated within these roles