Bad Medicine: Homework or Headache? Responsibility and Accountability for Middle Level Mathematics Students

In this action research study of my 5th grade mathematics class, I investigated the issue of homework and its relationship with students and parents. I made some interesting observations and discovered that the majority of students and parents felt that the math homework that was given was fairly easy, yet issues of incomplete assignments and failing homework quizzes were notorious for some individuals. Comments were also made to make homework even easier and have shortened assignments despite the already indicated ease of the work. As a result of this research, I plan to look more closely at the history and development of homework, as well as the psychological implications and “hereditary” issues involving homework, which I believe are passed from one generation of learners to the next. My intent is to continue to study this phenomenon in future school years, trying to develop methods of instilling successful, intrinsic motivational skills to aid students in their homework endeavors. Finally, I will take a close inventory of my own beliefs and understandings toward homework: What is the purpose of having students do work away from the classroom, and how can homework serve as a proactive service for all who are involved?

Design the support for granting required sla in public cloud environments based on cloud foundry

Through the use of Cloud Foundry "stack" concept, a new isolation is provided to the application running on the PaaS. A new deployment feature that can easily scale on distributed system, both public and private clouds.

Building an Academic Cloud for 500,000 Users

Under the brand name “sciebo – the Campuscloud” (derived from “science box”) a consortium of more than 20 research and applied science universities started a large scale cloud service for about 500,000 students and researchers in North Rhine-Westphalia, Germany’s most populous state. Starting with the much anticipated data privacy compliant sync & share functionality, sciebo offers the potential to become a more general cloud platform for collaboration and research data management which will be actively pursued in upcoming scientific and infrastructural projects. This project report describes the formation of the venture, its targets and the technical and the legal solution as well as the current status and the next steps.

One size fits all? Managing trust and privacy on social networking sites in Russia and Germany

When it comes to platform sustainability, mitigating user privacy concerns and enhancing trust represent two major tasks providers of Social Networking Sites (SNSs) are facing today. State-of-the-art research advocates reliance on the justice-based measures as possible means to address these challenges. However, as providers are increasingly expanding into foreign markets, the effectiveness of these measures in a cross-cultural setting is questioned. In an attempt to address this set of issues, in this study we build on the existing model to examine the impact of culture on the robustness of four justice-based means in mitigating privacy concerns and ensuring trust. Survey responses from German and Russian SNS members are used to evaluate the two structural equation models, which are then compared. We find that perceptions regarding Procedural and Informational Justice are universally important and hence should be addressed as part of the basic strategy by the SNS provider. When expanding to collectivistic countries like Russia, measures enhancing perceptions of Distributive and Interpersonal Justice can be additionally applied. Beyond practical implications, our study makes a significant contribution to the theoretical discourse on the role of culture in determining individual perceptions and behavior.

Leveraging Trust and Privacy Concerns in Online Social Networks: an Empirical Study

Unprecedented success of Online Social Networks, such as Facebook, has been recently overshadowed by the privacy risks they imply. Weary of privacy concerns and unable to construct their identity in the desired way, users may restrict or even terminate their platform activities. Even though this means a considerable business risk for these platforms, so far there have been no studies on how to enable social network providers to address these problems. This study fills this gap by adopting a fairness perspective to analyze related measures at the disposal of the provider. In a Structural Equation Model with 237 subjects we find that ensuring interactional and procedural justice are two important strategies to support user participation on the platform.

Effectiveness of Justice-Based Measures in Managing Trust and Privacy Concerns on Social Networking Sites: Intercultural Perspective

The unprecedented success of social networking sites (SNSs) has been recently overshadowed by concerns about privacy risks. As SNS users grow weary of privacy breaches and thus develop distrust, they may restrict or even terminate their platform activities. In the long run, these developments endanger SNS platforms’ financial viability and undermine their ability to create individual and social value. By applying a justice perspective, this study aims to understand the means at the disposal of SNS providers to leverage the privacy concerns and trusting beliefs of their users—two important determinants of user participation on SNSs. Considering that SNSs have a global appeal, empirical tests assess the effectiveness of justice measures for three culturally distinct countries: Germany, Russia and Morocco. The results indicate that these measures are particularly suited to address trusting beliefs of SNS audience. Specifically, in all examined countries, procedural justice and the awareness dimension of informational justice improve perceptions of trust in the SNS provider. Privacy concerns, however, are not as easy to manage, because the impact of justice-based measures on privacy concerns is not universal. Beyond theoretical value, this research offers valuable practical insights into the use of justice-based measures to promote trust and mitigate privacy concerns in a cross-cultural setting.

Privacy Policies and Users’ Trust: Does Readability Matter?

Over the years, a drastic increase in online information disclosure spurs a wave of concerns from multiple stakeholders. Among others, users resent the “behind the closed doors” processing of their personal data by companies. Privacy policies are supposed to inform users how their personal information is handled by a website. However, several studies have shown that users rarely read privacy policies for various reasons, not least because limitedly readable policy texts are difficult to understand. Based on our online survey with over 440 responses, we examine the objective and subjective readability of privacy policies and investigate their impact on users’ trust in five big Internet services. Our findings show the stronger a user believes in having understood the privacy policy, the higher he or she trusts a web site across all companies we studied. Our results call for making readability of privacy policies more accessible to an average reader.

Privacy-preserving genomic testing in the clinic: a model using HIV treatment

PURPOSE The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. METHODS We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. RESULTS A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. CONCLUSIONS The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.Genet Med advance online publication 14 January 2016Genetics in Medicine (2016); doi:10.1038/gim.2015.167.

Assessing user bias in affect detection within context-based spoken dialog systems

This paper presents an empirical evidence of user bias within a laboratory-oriented evaluation of a Spoken Dialog System. Specifically, we addressed user bias in their satisfaction judgements. We question the reliability of this data for modeling user emotion, focusing on contentment and frustration in a spoken dialog system. This bias is detected through machine learning experiments that were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. The target used was the satisfaction rating and the predictors were conversational/dialog features. Our results indicated that standard classifiers were significantly more successful in discriminating frustration and contentment and the intensities of these emotions (reflected by user satisfaction ratings) from annotator data than from user data. Indirectly, the results showed that conversational features are reliable predictors of the two abovementioned emotions.

Analysis of service-oriented computing systems

La computación basada en servicios (Service-Oriented Computing, SOC) se estableció como un paradigma ampliamente aceptado para el desarollo de sistemas de software flexibles, distribuidos y adaptables, donde las composiciones de los servicios realizan las tareas más complejas o de nivel más alto, frecuentemente tareas inter-organizativas usando los servicios atómicos u otras composiciones de servicios. En tales sistemas, las propriedades de la calidad de servicio (Quality of Service, QoS), como la rapídez de procesamiento, coste, disponibilidad o seguridad, son críticas para la usabilidad de los servicios o sus composiciones en cualquier aplicación concreta. El análisis de estas propriedades se puede realizarse de una forma más precisa y rica en información si se utilizan las técnicas de análisis de programas, como el análisis de complejidad o de compartición de datos, que son capables de analizar simultáneamente tanto las estructuras de control como las de datos, dependencias y operaciones en una composición. El análisis de coste computacional para la composicion de servicios puede ayudar a una monitorización predictiva así como a una adaptación proactiva a través de una inferencia automática de coste computacional, usando los limites altos y bajos como funciones del valor o del tamaño de los mensajes de entrada. Tales funciones de coste se pueden usar para adaptación en la forma de selección de los candidatos entre los servicios que minimizan el coste total de la composición, basado en los datos reales que se pasan al servicio. Las funciones de coste también pueden ser combinadas con los parámetros extraídos empíricamente desde la infraestructura, para producir las funciones de los límites de QoS sobre los datos de entrada, cuales se pueden usar para previsar, en el momento de invocación, las violaciones de los compromisos al nivel de servicios (Service Level Agreements, SLA) potenciales or inminentes. En las composiciones críticas, una previsión continua de QoS bastante eficaz y precisa se puede basar en el modelado con restricciones de QoS desde la estructura de la composition, datos empiricos en tiempo de ejecución y (cuando estén disponibles) los resultados del análisis de complejidad. Este enfoque se puede aplicar a las orquestaciones de servicios con un control centralizado del flujo, así como a las coreografías con participantes multiples, siguiendo unas interacciones complejas que modifican su estado. El análisis del compartición de datos puede servir de apoyo para acciones de adaptación, como la paralelización, fragmentación y selección de los componentes, las cuales son basadas en dependencias funcionales y en el contenido de información en los mensajes, datos internos y las actividades de la composición, cuando se usan construcciones de control complejas, como bucles, bifurcaciones y flujos anidados. Tanto las dependencias funcionales como el contenido de información (descrito a través de algunos atributos definidos por el usuario) se pueden expresar usando una representación basada en la lógica de primer orden (claúsulas de Horn), y los resultados del análisis se pueden interpretar como modelos conceptuales basados en retículos. ABSTRACT Service-Oriented Computing (SOC) is a widely accepted paradigm for development of flexible, distributed and adaptable software systems, in which service compositions perform more complex, higher-level, often cross-organizational tasks using atomic services or other service compositions. In such systems, Quality of Service (QoS) properties, such as the performance, cost, availability or security, are critical for the usability of services and their compositions in concrete applications. Analysis of these properties can become more precise and richer in information, if it employs program analysis techniques, such as the complexity and sharing analyses, which are able to simultaneously take into account both the control and the data structures, dependencies, and operations in a composition. Computation cost analysis for service composition can support predictive monitoring and proactive adaptation by automatically inferring computation cost using the upper and lower bound functions of value or size of input messages. These cost functions can be used for adaptation by selecting service candidates that minimize total cost of the composition, based on the actual data that is passed to them. The cost functions can also be combined with the empirically collected infrastructural parameters to produce QoS bounds functions of input data that can be used to predict potential or imminent Service Level Agreement (SLA) violations at the moment of invocation. In mission-critical applications, an effective and accurate continuous QoS prediction, based on continuations, can be achieved by constraint modeling of composition QoS based on its structure, known data at runtime, and (when available) the results of complexity analysis. This approach can be applied to service orchestrations with centralized flow control, and choreographies with multiple participants with complex stateful interactions. Sharing analysis can support adaptation actions, such as parallelization, fragmentation, and component selection, which are based on functional dependencies and information content of the composition messages, internal data, and activities, in presence of complex control constructs, such as loops, branches, and sub-workflows. Both the functional dependencies and the information content (described using user-defined attributes) can be expressed using a first-order logic (Horn clause) representation, and the analysis results can be interpreted as a lattice-based conceptual models.

A framework for implementing outsourcing schemes

En esta tesis se aborda el problema de la externalización segura de servicios de datos y computación. El escenario de interés es aquel en el que el usuario posee datos y quiere subcontratar un servidor en la nube (“Cloud”). Además, el usuario puede querer también delegar el cálculo de un subconjunto de sus datos al servidor. Se presentan dos aspectos de seguridad relacionados con este escenario, en concreto, la integridad y la privacidad y se analizan las posibles soluciones a dichas cuestiones, aprovechando herramientas criptográficas avanzadas, como el Autentificador de Mensajes Homomórfico (“Homomorphic Message Authenticators”) y el Cifrado Totalmente Homomórfico (“Fully Homomorphic Encryption”). La contribución de este trabajo es tanto teórica como práctica. Desde el punto de vista de la contribución teórica, se define un nuevo esquema de externalización (en lo siguiente, denominado con su término inglés Outsourcing), usando como punto de partida los artículos de [3] y [12], con el objetivo de realizar un modelo muy genérico y flexible que podría emplearse para representar varios esquemas de ”outsourcing” seguro. Dicho modelo puede utilizarse para representar esquemas de “outsourcing” seguro proporcionando únicamente integridad, únicamente privacidad o, curiosamente, integridad con privacidad. Utilizando este nuevo modelo también se redefine un esquema altamente eficiente, construido en [12] y que se ha denominado Outsourcinglin. Este esquema permite calcular polinomios multivariados de grado 1 sobre el anillo Z2k . Desde el punto de vista de la contribución práctica, se ha construido una infraestructura marco (“Framework”) para aplicar el esquema de “outsourcing”. Seguidamente, se ha testado dicho “Framework” con varias implementaciones, en concreto la implementación del criptosistema Joye-Libert ([18]) y la implementación del esquema propio Outsourcinglin. En el contexto de este trabajo práctico, la tesis también ha dado lugar a algunas contribuciones innovadoras: el diseño y la implementación de un nuevo algoritmo de descifrado para el esquema de cifrado Joye-Libert, en colaboración con Darío Fiore. Presenta un mejor comportamiento frente a los algoritmos propuestos por los autores de [18];la implementación de la función eficiente pseudo-aleatoria de forma amortizada cerrada (“amortized-closed-form efficient pseudorandom function”) de [12]. Esta función no se había implementado con anterioridad y no supone un problema trivial, por lo que este trabajo puede llegar a ser útil en otros contextos. Finalmente se han usado las implementaciones durante varias pruebas para medir tiempos de ejecución de los principales algoritmos.---ABSTRACT---In this thesis we tackle the problem of secure outsourcing of data and computation. The scenario we are interested in is that in which a user owns some data and wants to “outsource” it to a Cloud server. Furthermore, the user may want also to delegate the computation over a subset of its data to the server. We present the security issues related to this scenario, namely integrity and privacy and we analyse some possible solutions to these two issues, exploiting advanced cryptographic tools, such as Homomorphic Message Authenticators and Fully Homomorphic Encryption. Our contribution is both theoretical and practical. Considering our theoretical contribution, using as starting points the articles of [3] and [12], we introduce a new cryptographic primitive, called Outsourcing with the aim of realizing a very generic and flexible model that might be employed to represent several secure outsourcing schemes. Such model can be used to represent secure outsourcing schemes that provide only integrity, only privacy or, interestingly, integrity with privacy. Using our new model we also re-define an highly efficient scheme constructed in [12], that we called Outsourcinglin and that is a scheme for computing multi-variate polynomials of degree 1 over the ring Z2k. Considering our practical contribution, we build a Framework to implement the Outsourcing scheme. Then, we test such Framework to realize several implementations, specifically the implementation of the Joye-Libert cryptosystem ([18]) and the implementation of our Outsourcinglin scheme. In the context of this practical work, the thesis also led to some novel contributions: the design and the implementation, in collaboration with Dario Fiore, of a new decryption algorithm for the Joye-Libert encryption scheme, that performs better than the algorithms proposed by the authors in [18]; the implementation of the amortized-closed-form efficient pseudorandom function of [12]. There was no prior implementation of this function and it represented a non trivial work, which can become useful in other contexts. Finally we test the implementations to execute several experiments for measuring the timing performances of the main algorithms.