Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

Noise Reduction Using Low Weight and Constant Weight Coding Techniques

Signalling off-chip requires significant current. As a result, a chip's power-supply current changes drastically during certain output-bus transitions. These current fluctuations cause a voltage drop between the chip and circuit board due to the parasitic inductance of the power-supply package leads. Digital designers often go to great lengths to reduce this "transmitted" noise. Cray, for instance, carefully balances output signals using a technique called differential signalling to guarantee a chip has constant output current. Transmitted-noise reduction costs Cray a factor of two in output pins and wires. Coding achieves similar results at smaller costs.

Admission Control for TCP Flows Using Packet Classes and Edge-to-edge Measurements of Aggregates

TCP flows from applications such as the web or ftp are well supported by a Guaranteed Minimum Throughput Service (GMTS), which provides a minimum network throughput to the flow and, if possible, an extra throughput. We propose a scheme for a GMTS using Admission Control (AC) that is able to provide different minimum throughput to different users and that is suitable for "standard" TCP flows. Moreover, we consider a multidomain scenario where the scheme is used in one of the domains, and we propose some mechanisms for the interconnection with neighbor domains. The whole scheme uses a small set of packet classes in a core-stateless network where each class has a different discarding priority in queues assigned to it. The AC method involves only edge nodes and uses a special probing packet flow (marked as the highest discarding priority class) that is sent continuously from ingress to egress through a path. The available throughput in the path is obtained at the egress using measurements of flow aggregates, and then it is sent back to the ingress. At the ingress each flow is detected using an implicit way and then it is admission controlled. If it is accepted, it receives the GMTS and its packets are marked as the lowest discarding priority classes; otherwise, it receives a best-effort service. The scheme is evaluated through simulation in a simple "bottleneck" topology using different traffic loads consisting of "standard" TCP flows that carry files of varying sizes

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

Part 1 - talk on using Creative Commons and opensource software to make Open Content (what is creative commons ?, what is open content ?)

This is the first part of a 2 part video from my talk in May 2008 on open source content creation.

Part 2 - talk on using Creative Commons and opensource software to make Open Content. (Making of Doljer)

This is the second part of a 2 part video from my talk in May 2008 on open source content creation. Here I am talking about the Making of Doljer

Using the Normal and Quotation styles in the University's thesis template for MS Word 2010

The Normal style is used for all your standard paragraphs of text in the thesis and also provides the underlying formatting attributes for other styles. Learn how to use this style. For best viewing Download the video. The Quotation style is used to indicate text that it being quoted in your thesis, see how to use this style.

Using the Normal and Quotation styles in the University's thesis template in MS Word 2011 (for Apple computers)

The Normal style is used for all your standard paragraphs of text in the thesis and also provides the underlying formatting attributes for other styles. Learn how to use this style. The Quotation style is used to indicate text that it being quoted in your thesis, see how to use this style. For best viewing Download the video.

Using the Contents and Appendix styles in the University's thesis template for MS Word 2011

This video shows you when and how to use the styles Contents and Appendix styles in the University's thesis template in Word 2011. For best viewing Download the video.

Reaching and teaching the child with autism spectrum disorder : using learning preferences and strengths.

Manual que ofrece un enfoque positivo a la comprensión y la educación de los niños con autismo. Ofrece una mayor comprensión de la perspectiva y el comportamiento de un niño con autismo y explora cómo pueden utilizarse sus preferencias de aprendizaje, fortalezas e intereses para facilitar el aprendizaje y aumentar la motivación. La autora ha utilizado una mezcla de teorías de la personalidad, inteligencias múltiples y aprendizaje para crear un método de trabajo, Aprendizaje Preferencias y Fortalezas (LPS), para el desarrollo de habilidades de aprendizaje para la vida independiente en niños con autismo entre dos y doce años. Describe los principios básicos, preferencias de aprendizaje y los puntos fuertes típicos de los niños con autismo y ofrece una estructura de programa detallado, pero flexible, basada en estos conceptos. Fácil de seguir, se describen en cada capítulo actividades y orientaciones junto con ejemplos e ilustraciones.

Using crises, feedback, and fading for online task design

Resumen basado en el de la publicaci??n

Phoneme analysis of cochlear implant recipients' responses to CNC words using the MPEAK and SPEAK speech coding strategies of the Nucleus cochlear implant system

This paper discusses a study done to determine how cochlear implant users perceive speech sounds using MPEAK or SPEAK speech coding strategy.

Monitoring changes in precipitation and radiative energy using satellite data and climate models

Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

Glacier shrinkage and climatic change in the Russian Altai from the mid-20th century: An assessment using remote sensing and PRECIS regional climate model

This paper examines changes in the surface area of glaciers in the North and South Chuya Ridges, Altai Mountains in 1952-2004 and their links with regional climatic variations. The glacier surface areas for 2004 were derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Data from the World Glacier Inventory (WGI)dating to 1952 and aerial photographs from 1952 were used to estimate the changes. 256 glaciers with a combined area of 253±5.1 km2 have been identified in the region in 2004. Estimation of changes in extent of 126 glaciers with the individual areas not less than 0.5 km2 in 1952 revealed a 19.7±5.8% reduction. The observed glacier retreat is primarily driven by an increase in summer temperatures since the 1980s when air temperatures were increasing at a rate of 0.10 - 0.13oC a-1 at the glacier tongue elevation. The regional climate projections for A2 and B2 CO2 emission scenarios developed using PRECIS regional climate model indicate that summer temperatures will increase in the Altai in 2071-2100 by 6-7oC and 3-5oC respectively in comparison with 1961-1990 while annual precipitation will increase by 15% and 5%. The length of the ablation season will extend from June-August to the late April – early October. The projected increases in precipitation will not compensate for the projected warming and glaciers will continue to retreat in the 21st century under both B2 and A2 scenarios.