Considérations sur les enfans trouvés dans les principaux états de l'Europe /

Goldsmiths'-Kress no. 24290.1.

Huchown of the Awle Ryale and his poems, examined in the light of recent criticism.

Read to the Royal Philosophical Society, Glasgow (Historical and Philological Section), on 21st April, 1902.

Transactions of the Wordsworth Society.

"List of members," April 1883 (8 p.) is prefixed to no. 1; "List of members ... who have joined since April 1883" (1 l.) and "Constitution" (3 p.) are appended to no. 5 (with list of "Papers ... either read to the society, or published in its Transactions")

Towards Automation in Digital Investigations : Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments

Cybercrime and related malicious activity in our increasingly digital world has become more prevalent and sophisticated, evading traditional security mechanisms. Digital forensics has been proposed to help investigate, understand and eventually mitigate such attacks. The practice of digital forensics, however, is still fraught with various challenges. Some of the most prominent of these challenges include the increasing amounts of data and the diversity of digital evidence sources appearing in digital investigations. Mobile devices and cloud infrastructures are an interesting specimen, as they inherently exhibit these challenging circumstances and are becoming more prevalent in digital investigations today. Additionally they embody further characteristics such as large volumes of data from multiple sources, dynamic sharing of resources, limited individual device capabilities and the presence of sensitive data. These combined set of circumstances make digital investigations in mobile and cloud environments particularly challenging. This is not aided by the fact that digital forensics today still involves manual, time consuming tasks within the processes of identifying evidence, performing evidence acquisition and correlating multiple diverse sources of evidence in the analysis phase. Furthermore, industry standard tools developed are largely evidence-oriented, have limited support for evidence integration and only automate certain precursory tasks, such as indexing and text searching. In this study, efficiency, in the form of reducing the time and human labour effort expended, is sought after in digital investigations in highly networked environments through the automation of certain activities in the digital forensic process. To this end requirements are outlined and an architecture designed for an automated system that performs digital forensics in highly networked mobile and cloud environments. Part of the remote evidence acquisition activity of this architecture is built and tested on several mobile devices in terms of speed and reliability. A method for integrating multiple diverse evidence sources in an automated manner, supporting correlation and automated reasoning is developed and tested. Finally the proposed architecture is reviewed and enhancements proposed in order to further automate the architecture by introducing decentralization particularly within the storage and processing functionality. This decentralization also improves machine to machine communication supporting several digital investigation processes enabled by the architecture through harnessing the properties of various peer-to-peer overlays. Remote evidence acquisition helps to improve the efficiency (time and effort involved) in digital investigations by removing the need for proximity to the evidence. Experiments show that a single TCP connection client-server paradigm does not offer the required scalability and reliability for remote evidence acquisition and that a multi-TCP connection paradigm is required. The automated integration, correlation and reasoning on multiple diverse evidence sources demonstrated in the experiments improves speed and reduces the human effort needed in the analysis phase by removing the need for time-consuming manual correlation. Finally, informed by published scientific literature, the proposed enhancements for further decentralizing the Live Evidence Information Aggregator (LEIA) architecture offer a platform for increased machine-to-machine communication thereby enabling automation and reducing the need for manual human intervention.

Effects of Temporal Self-Comparisons on the Pursuit of Improvement

Thesis (Ph.D.)--University of Washington, 2016-06

The skin of the Burqa: Recent life narratives from Afghanistan

The "war on terror" has been associated with an extraordinary proliferation of Afghan autoethnographies in the Western marketplace. In this article, various implications and connotations of this are read to explore the ethical engagements of life narrative in these times.

Superstring: A scalable service discovery protocol for the wide-area pervasive environment

Arguably, the world has become one large pervasive computing environment. Our planet is growing a digital skin of a wide array of sensors, hand-held computers, mobile phones, laptops, web services and publicly accessible web-cams. Often, these devices and services are deployed in groups, forming small communities of interacting devices. Service discovery protocols allow processes executing on each device to discover services offered by other devices within the community. These communities can be linked together to form a wide-area pervasive environment, allowing processes in one p u p tu interact with services in another. However, the costs of communication and the protocols by which this communication is mediated in the wide-area differ from those of intra-group, or local-area, communication. Communication is an expensive operation for small, battery powered devices, but it is less expensive for servem and workstations, which have a constant power supply and 81'e connected to high bandwidth networks. This paper introduces Superstring, a peer to-peer service discovery protocol optimised fur use in the wide-area. Its goals are to minimise computation and memory overhead in the face of large numbers of resources. It achieves this memory and computation scalability by distributing the storage cost of service descriptions and the computation cost of queries over multiple resolvers.

An Autonomic Framework for Mobile Cloud Computing

This thesis presents the formal definition of a novel Mobile Cloud Computing (MCC) extension of the Networked Autonomic Machine (NAM) framework, a general-purpose conceptual tool which describes large-scale distributed autonomic systems. The introduction of autonomic policies in the MCC paradigm has proved to be an effective technique to increase the robustness and flexibility of MCC systems. In particular, autonomic policies based on continuous resource and connectivity monitoring help automate context-aware decisions for computation offloading. We have also provided NAM with a formalization in terms of a transformational operational semantics in order to fill the gap between its existing Java implementation NAM4J and its conceptual definition. Moreover, we have extended NAM4J by adding several components with the purpose of managing large scale autonomic distributed environments. In particular, the middleware allows for the implementation of peer-to-peer (P2P) networks of NAM nodes. Moreover, NAM mobility actions have been implemented to enable the migration of code, execution state and data. Within NAM4J, we have designed and developed a component, denoted as context bus, which is particularly useful in collaborative applications in that, if replicated on each peer, it instantiates a virtual shared channel allowing nodes to notify and get notified about context events. Regarding the autonomic policies management, we have provided NAM4J with a rule engine, whose purpose is to allow a system to autonomously determine when offloading is convenient. We have also provided NAM4J with trust and reputation management mechanisms to make the middleware suitable for applications in which such aspects are of great interest. To this purpose, we have designed and implemented a distributed framework, denoted as DARTSense, where no central server is required, as reputation values are stored and updated by participants in a subjective fashion. We have also investigated the literature regarding MCC systems. The analysis pointed out that all MCC models focus on mobile devices, and consider the Cloud as a system with unlimited resources. To contribute in filling this gap, we defined a modeling and simulation framework for the design and analysis of MCC systems, encompassing both their sides. We have also implemented a modular and reusable simulator of the model. We have applied the NAM principles to two different application scenarios. First, we have defined a hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. Merging P2P and cloud paradigms brings together the advantages of both: high availability, provided by the Cloud presence, and low cost, by exploiting inexpensive peers resources. As an example, we have shown how the proposed approach can be used to design NAM-based collaborative storage systems based on an autonomic policy to decide how to distribute data chunks among peers and Cloud, according to cost minimization and data availability goals. As a second application, we have defined an autonomic architecture for decentralized urban participatory sensing (UPS) which bridges sensor networks and mobile systems to improve effectiveness and efficiency. The developed application allows users to retrieve and publish different types of sensed information by using the features provided by NAM4J's context bus. Trust and reputation is managed through the application of DARTSense mechanisms. Also, the application includes an autonomic policy that detects areas characterized by few contributors, and tries to recruit new providers by migrating code necessary to sensing, through NAM mobility actions.

Similarities between eating attitudes among friendship groups in childhood:the moderating role of child anxiety

Objective: This study explores the similarities between individual and group eating and weight concerns in 8-11-year-old children. It also evaluates whether child anxiety moderates the relationships between individual and group eating and weight concerns. Methods: One hundred and fifty four children aged 8-11 completed questionnaires concerning their friendship groups, their eating and weight concerns, and their levels of anxiety. Results: Children's own scores on dietary restraint, body dissatisfaction, and external eating were significantly correlated with their friendship groups' scores on dietary restraint. Child anxiety moderated the relationships between group dietary restraint and individual scores on external eating. Group levels of dietary restraint predicted higher levels of external eating in children with moderate or high anxiety. Conclusions: In pre-adolescent children, peer group levels of dietary restraint are related to individual eating and weight concerns. More anxious children may be more susceptible to peer influences on their eating behaviors. © The Author 2011. Published by Oxford University Press.

Pushing the Quality Level in Networked News Business: Semantic-Based Content Retrieval and Composition in International News Publishing

Electronic publishing exploits numerous possibilities to present or exchange information and to communicate via most current media like the Internet. By utilizing modern Web technologies like Web Services, loosely coupled services, and peer-to-peer networks we describe the integration of an intelligent business news presentation and distribution network. Employing semantics technologies enables the coupling of multinational and multilingual business news data on a scalable international level and thus introduce a service quality that is not achieved by alternative technologies in the news distribution area so far. Architecturally, we identified the loose coupling of existing services as the most feasible way to address multinational and multilingual news presentation and distribution networks. Furthermore we semantically enrich multinational news contents by relating them using AI techniques like the Vector Space Model. Summarizing our experiences we describe the technical integration of semantics and communication technologies in order to create a modern international news network.

Open Access Strategy of UNESCO

One of UNESCO’s overarching goals is to build inclusive knowledge societies by harnessing information and communication technologies to maintain, increase and diffuse knowledge in the fields of education, the sciences, culture, and communication and information, including through open access. Open Access (OA) is the provision of free access to peer-reviewed, scholarly, research information (both scientific papers and research data) to all. It envisages that the rights-holder grants worldwide irrevocable right of access to copy, use, distribute, transmit, and make derivative works in any format for any lawful activities with proper attribution to the original author. Through Open Access, researchers and students from around the world gain increased access to knowledge, publications have greater visibility and readership, and the potential impact of research is heightened.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Characterizing Internet worm spatial-temporal infection structures

Since the Morris worm was released in 1988, Internet worms continue to be one of top security threats. For example, the Conficker worm infected 9 to 15 million machines in early 2009 and shut down the service of some critical government and medical networks. Moreover, it constructed a massive peer-to-peer (P2P) botnet. Botnets are zombie networks controlled by attackers setting out coordinated attacks. In recent years, botnets have become the number one threat to the Internet. The objective of this research is to characterize spatial-temporal infection structures of Internet worms, and apply the observations to study P2P-based botnets formed by worm infection. First, we infer temporal characteristics of the Internet worm infection structure, i.e., the host infection time and the worm infection sequence, and thus pinpoint patient zero or initially infected hosts. Specifically, we apply statistical estimation techniques on Darknet observations. We show analytically and empirically that our proposed estimators can significantly improve the inference accuracy. Second, we reveal two key spatial characteristics of the Internet worm infection structure, i.e., the number of children and the generation of the underlying tree topology formed by worm infection. Specifically, we apply probabilistic modeling methods and a sequential growth model. We show analytically and empirically that the number of children has asymptotically a geometric distribution with parameter 0.5, and the generation follows closely a Poisson distribution. Finally, we evaluate bot detection strategies and effects of user defenses in P2P-based botnets formed by worm infection. Specifically, we apply the observations of the number of children and demonstrate analytically and empirically that targeted detection that focuses on the nodes with the largest number of children is an efficient way to expose bots. However, we also point out that future botnets may self-stop scanning to weaken targeted detection, without greatly slowing down the speed of worm infection. We then extend the worm spatial infection structure and show empirically that user defenses, e.g. , patching or cleaning, can significantly mitigate the robustness and the effectiveness of P2P-based botnets. To counterattack, we evaluate a simple measure by future botnets that enhances topology robustness through worm re-infection.

An examination of the effects of a summer book-reading program on the language and early literacy outcomes of toddlers from high risk environments

The current study examined the impact of an early summer literacy program and the mediating effects of the home literacy environment on the language and literacy outcomes of a group of children at-risk for long-term developmental and academic delays. Participating children (n=54) were exposed to an intensive book-reading intervention each summer (June through mid August) over a 3-year period. The current study implemented an ex post facto, quasi-experimental design. This nonequivalent group design involved a pretest and posttest over three time points for a non-randomized treatment group and a matched non-treatment comparison group. Results indicated that literacy scores did improve for the children over the 3-year period; however, language scores did not experience the same rate of change over time. Receptive language was significantly impacted by attendance, and race/ethnicity. Expressive language was impacted significantly by gestational age and attendance. Results also indicated that language outcomes for young children who are exposed to a literacy program were higher than those who did not participate; however, only receptive language yielded significance at the p<.05 level. These study results also found that activities in the home that support literacy and learning do indeed impact language and literacy outcomes for these children, specifically, the age at which a child is read to, the number of books in the home, a child’s enjoyment of reading, and whether a child looks at books on his or her own impact language scores. This study concluded that at-risk young children do benefit from center-based literacy intervention. This literacy experience, however, is also driven by the children's home environment, their attendance to the program, whether they were premature or not and the type of caregiver.

Foundational Forensic Techniques for Cellular and Ad Hoc Multi-hop Networks

The Internet has become an integral part of our nation's critical socio-economic infrastructure. With its heightened use and growing complexity however, organizations are at greater risk of cyber crimes. To aid in the investigation of crimes committed on or via the Internet, a network forensics analysis tool pulls together needed digital evidence. It provides a platform for performing deep network analysis by capturing, recording and analyzing network events to find out the source of a security attack or other information security incidents. Existing network forensics work has been mostly focused on the Internet and fixed networks. But the exponential growth and use of wireless technologies, coupled with their unprecedented characteristics, necessitates the development of new network forensic analysis tools. This dissertation fostered the emergence of a new research field in cellular and ad-hoc network forensics. It was one of the first works to identify this problem and offer fundamental techniques and tools that laid the groundwork for future research. In particular, it introduced novel methods to record network incidents and report logged incidents. For recording incidents, location is considered essential to documenting network incidents. However, in network topology spaces, location cannot be measured due to absence of a 'distance metric'. Therefore, a novel solution was proposed to label locations of nodes within network topology spaces, and then to authenticate the identity of nodes in ad hoc environments. For reporting logged incidents, a novel technique based on Distributed Hash Tables (DHT) was adopted. Although the direct use of DHTs for reporting logged incidents would result in an uncontrollably recursive traffic, a new mechanism was introduced that overcome this recursive process. These logging and reporting techniques aided forensics over cellular and ad-hoc networks, which in turn increased their ability to track and trace attacks to their source. These techniques were a starting point for further research and development that would result in equipping future ad hoc networks with forensic components to complement existing security mechanisms.