The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.

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.

Optimal Unsupervised Learning in Feedforward Neural Networks

We investigate the properties of feedforward neural networks trained with Hebbian learning algorithms. A new unsupervised algorithm is proposed which produces statistically uncorrelated outputs. The algorithm causes the weights of the network to converge to the eigenvectors of the input correlation with largest eigenvalues. The algorithm is closely related to the technique of Self-supervised Backpropagation, as well as other algorithms for unsupervised learning. Applications of the algorithm to texture processing, image coding, and stereo depth edge detection are given. We show that the algorithm can lead to the development of filters qualitatively similar to those found in primate visual cortex.

Explorations of the Practical Issues of Learning Prediction-Control Tasks Using Temporal Difference Learning Methods

There has been recent interest in using temporal difference learning methods to attack problems of prediction and control. While these algorithms have been brought to bear on many problems, they remain poorly understood. It is the purpose of this thesis to further explore these algorithms, presenting a framework for viewing them and raising a number of practical issues and exploring those issues in the context of several case studies. This includes applying the TD(lambda) algorithm to: 1) learning to play tic-tac-toe from the outcome of self-play and of play against a perfectly-playing opponent and 2) learning simple one-dimensional segmentation tasks.

Embodiment and Manipulation Learning Process for a Humanoid Hand

Babies are born with simple manipulation capabilities such as reflexes to perceived stimuli. Initial discoveries by babies are accidental until they become coordinated and curious enough to actively investigate their surroundings. This thesis explores the development of such primitive learning systems using an embodied light-weight hand with three fingers and a thumb. It is self-contained having four motors and 36 exteroceptor and proprioceptor sensors controlled by an on-palm microcontroller. Primitive manipulation is learned from sensory inputs using competitive learning, back-propagation algorithm and reinforcement learning strategies. This hand will be used for a humanoid being developed at the MIT Artificial Intelligence Laboratory.

Student self-assessment a feedback seeking strategy through competence evaluation

There is a body of literature that suggests that student self-assessment is a main goal in higher education (Boud et al., 1995; Tan, 2008); moreover new forms of work organization require a high level of skills and competences. The efforts to deal with competence gaps could be developed at many levels, such as employers, educational institutions, individuals and public agents. Employers could put into practice competence development programs to moderate these gaps. Educational institutions can restructure the curriculum to support students in attaining the competences that are essential in the labour market. Individuals themselves may deploy their resources (time and money) in general or specific competence training. Further, government agencies could fund competence promotion programs. Such challenges for education drive change in learning curricula and method, to properly include the competences required for developing global workers who can move beyond basic competence, to enhanced flexibility and adaptability. In performance assessment methods, there is a shift from the traditional exam-based assessments to more innovative task assessment, which considers performance in multiple different tasks carry out by students. ICTs make it technologically feasible to carry out a complete and complex selfassessment of competences, which provides immediate results to students or other recipients. In the case of students, the evaluation of competences is relevant as developing competences is part - if not all - of the objectives of education. Therefore, it is an important element of the quality of educational organizations (e.g., universities), and of their organizational success. Further, educational organizations may put special emphasis on some differentiating competences, which can be a means of positioning and differentiation from competitors. Competence assessment is an instrument to make students conscious of their strengths and weaknesses, leading to higher motivation to develop their own learning career

A Self-Scoring Exercise On APA Style, Research Language, and Referencing for Undergraduate Students

Based on examples provided by 27 graduate psychology faculty, this self-test incorporates many of the more common errors in style, language, and referencing found in student papers. Taking this self-test helps students to recognize common errors and encourages them to refer the APA Publication Manual on a regular basis. In addition, students begin to think about how to use correctly the language of psychological research. This self-test should take about 30 minutes to complete and score. It is composed of three parts: a) a mock Discussion section, where students are asked to act as editors and find the errors, p. 2 (10 minutes). b) a corrected Discussion section, where students find the errors they missed, p. 3 (5 minutes) and, c) a full description of each error with illustrations of correct usage, pp. 4-7 (15 minutes). This exercise assumes some knowledge of APA style. Thus, it is best-suited for advanced undergraduates who need to write research reports and all levels of graduate students. It may be taken at home or in class. Although the self-test is designed to be fully self-directed, instructors may wish to use it at the beginning or end of a classroom discussion on APA style. It could also be used in a pre-test-post-test fashion to evaluate students learning over the course of a term.

Introduction to Matlab - a self-study tutorial

Matlab is a high level language that is very easy to use and very powerful. It comes with a wealth of libraries and toolboxes, that you can use directly, so that you don't need to program low level functions. It enables you to display results very easily on graphs and images. To get started with it, you need to understand how to manipulate and represent data, and how to find information about the available functions. During this self-study tutorial, you will learn: 1- How to start Matlab. 2- How you can find out all the information you need. 3- How to create simple vectors and matrices. 4- What functions are available and how to find them. 5- How to plot graphs of functions. 6- How to write a script. After this (should take about an hour), you will know most of what you need to know about Matlab and should definitely know how to go on learning about it on your own…

Self-study Language Modules Using Blackboard - Julie Watson

This is one of a series of short case studies describing how academic tutors at the University of Southampton have made use of learning technologies to support their students.

Using video markschemes to support self-assessment in Chemistry

A video markscheme was created using a combination of Camtasia screen capture (on a Tablet PC) and 'live action' video taken with a camcorder. The resulting video supported students in the self-assessment of an organic chemistry exercise which had been set over the Easter vacation break. Feedback was collected from the students after the exercise and was overwhelmingly positive. The video won the 2010 award for 'Most Effective Use of Video in an Educational Context' from the Assocation for Learning Technology. DOWNLOAD THE ZIP FOLDER AND EXTRACT THE FILES TO ACCESS THEM.

Actitudes de los directivos en torno a la adopción del e-learning como herramienta de trabajo en las empresas

El desarrollo del presente documento constituye una investigación sobre las actitudes de los directivos frente a la adopción del e-learning como herramienta de trabajo en las organizaciones de Bogotá. Para ello se realizó una encuesta a 101 directivos, tomando como base el tipo de muestreo de conveniencia; esto con el objetivo de identificar sus actitudes frente al uso del e-learning y su influencia dentro de la organización. Como resultado se obtuvo que las actitudes de los directivos influencian en el uso de herramientas e-learning, así como también en las acciones que promueven su uso y en las actitudes de los empleados; por otro lado se identificó que las creencias relacionadas con la apropiación de herramientas e-learning y los factores facilitadores del uso de estas, influencian en las actitudes de los directivos. Lo anterior, corresponde a los análisis llevados a cabo a partir de los resultados contrastados con los estudios empíricos hallados y el marco teórico desarrollado.

Análisis de los componentes de la cadena de suministro y su relación con el desempeño superior de la organización en el sector manufacturero

En este documento se evidencia como el desempeño organizacional de una empresa, entendido como el rendimiento superior de la misma, se ve modificado por las prácticas o metodologías utilizadas, aplicadas e integradas a cada uno de los componentes de la Cadena de suministros. Es así que el propósito principal es demostrar cual es la relación entre los componentes de la Cadena de Suministros y su gestión sobre los rendimientos económicos de la empresa. De esa manera se encontraron múltiples actividades que toman lugar en los procesos característicos de cada uno de los componentes de la cadena de suministros y que al final nos presentan una variabilidad sobre los rendimientos de la empresa. Cabe recalcar que la investigación se realizó con respecto a empresas pertenecientes al sector manufacturero y abarca una buena parte de este. La importancia que tiene la investigación, es el haber entregado como resultado, el conocimiento sobre algunas de las practicas más utilizadas en el sector en cada uno de sus componentes, lo cual hace de la Cadena de suministros, un factor por excelencia para ser tratado e implementado con el fin de alcanzar mayores rendimientos económicos a nivel de empresa. En la investigación se utilizaron los casos de empresas reales tanto nacionales como internacionales y se encontraron situaciones claves que evidenciaban la hipótesis de la relación entre la cadena de suministros y el desempeño organizacional. Es por ello, que si bien es ahora cierto, que las actividades desarrolladas en los componentes de la Cadena de Suministros de las empresas influyen en el incremento de los rendimientos, es importante que las empresas conozcan de esta información para tener una idea de cómo desarrollar ventajas competitivas que los posicionen como empresa y les genere entonces mayores rendimientos, o por el contrario, les genere ahorros en costos y por ende altos beneficios y nuevas inversiones en prácticas que a la larga volverá a la empresa en un organismo eficientes y próspero.

Las tecnologías de la información y la comunicación en los procesos de orientación para el estudio a distancia. 'Ict in the orientation processes for distance learning'.

Resumen tomado de la publicación. Con el apoyo económico del departamento MIDE de la UNED. Incluye anexos

Assessment and learning : is it time to rethink student activities and academic roles?

Resumen basado en el de la publicación

Museu inspirador: exercício de aplicação da ferramenta de auto-avaliação - Inspiring learning for all em quatro serviços educativos de museus portugueses

Esta dissertação tem como objectivo principal procurar contribuir para a discussão em torno das valências das ferramentas da Qualidade aplicadas ao campo museal. O seu enfoque particular desenvolve-se ao nível dos serviços educativos, procurando avaliar os seus processos e resultados. Partindo da premissa de que os museus que aplicam os princípios da Qualidade nas suas práticas museais estão mais aptos a inspirarem e apoiarem as necessidades de aprendizagem dos seus utilizadores, esta dissertação defenderá as instituições museológicas enquanto organizações de conhecimento, sendo a aprendizagem o âmago da sua acção. A sua questão orientadora centra-se em torno da pertinência da aplicação da ferramenta de auto-avaliação Inspiring Learning for All em museus portugueses.