Web Archive Services Framework for Tighter Integration Between the Past and Present Web

Web archives have contained the cultural history of the web for many years, but they still have a limited capability for access. Most of the web archiving research has focused on crawling and preservation activities, with little focus on the delivery methods. The current access methods are tightly coupled with web archive infrastructure, hard to replicate or integrate with other web archives, and do not cover all the users\u27 needs. In this dissertation, we focus on the access methods for archived web data to enable users, third-party developers, researchers, and others to gain knowledge from the web archives. We build ArcSys, a new service framework that extracts, preserves, and exposes APIs for the web archive corpus. The dissertation introduces a novel categorization technique to divide the archived corpus into four levels. For each level, we will propose suitable services and APIs that enable both users and third-party developers to build new interfaces. The first level is the content level that extracts the content from the archived web data. We develop ArcContent to expose the web archive content processed through various filters. The second level is the metadata level; we extract the metadata from the archived web data and make it available to users. We implement two services, ArcLink for temporal web graph and ArcThumb for optimizing the thumbnail creation in the web archives. The third level is the URI level that focuses on using the URI HTTP redirection status to enhance the user query. Finally, the highest level in the web archiving service framework pyramid is the archive level. In this level, we define the web archive by the characteristics of its corpus and building Web Archive Profiles. The profiles are used by the Memento Aggregator for query optimization

ASCR/HEP Exascale Requirements Review Report

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio

Pattern to process: methodological investigations into the formation and interpretation of spatial patterns in archaeological landscapes

My research has shown that the type of regional archaeological data analysis required by landscape archaeological approaches is an area where both theory and method are still in their infancy. High-level theories about the occurrence, scope, and effects of processes such as centralization, urbanization, and Hellenization/Romanization cannot yet be supported by middle range theory, which itself cannot be developed until the basic business of generating information of sufficient quality about the archaeological record has been tackled. Currently, archaeological data can be made to fit almost any interpretation generated, ultimately, on the basis of the ancient written sources. If we are to escape from this selfreinforcing cycle, research should perhaps no longer be focused on the classical themes generated by culture-historical approaches, but should seek its own proper field of operation. In the area of methods and methodology, I have demonstrated the pervasive influence of systematic research and visibility biases on the patterns that are present in the archaeological data generated over the past 50 years or so. There are mechanisms at work, both in the traditional archaeological interpretation of limited numbers of excavated sites and historical sources, and in the landscape archaeological approach, that cause the systematic undervaluation of unobtrusive remains. The significance of systematic biases in both the coarse site-based data sets resulting from desktop and ‘topographic’ studies and the more detailed site-based or ‘continuous’ data resulting from intensive field surveys has become much clearer as a result of the studies reported here. This should have practical consequences for the ways in which we study the existing archaeological record, plan future landscape archaeological research, and conduct field surveys. Site databases, the traditional starting point for regional archaeological studies, can no longer be taken at face value; rather, they require careful source criticism before being used to support specific arguments and hypotheses about settlement and land use dynamics. My studies have also shown that future data collection, whether through field survey, excavation or other methods, has to take place in a much more methodical manner if we are to produce data that are sufficiently standardized to be successfully exchanged, compared, and interpreted by others – guidelines for which should become embodied in an international standard defining ‘best practice in landscape archaeology’.

Towards Expressive and Versatile Visualization-as-a-Service (VaaS)

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization services with multi-device support and hypothesis-driven explorations. By incorporating stateful information and enabling dynamic computation, VaaS\u27 performance and flexibility for various real-world applications is improved. This dissertation explores the history of monolithic and VaaS architectures, the design and implementations of 3 new VaaS applications, and a final exploration of the future of VaaS. This research contributes to the advancement of interactive scientific visualization, addressing the challenges posed by large datasets and remote collaboration scenarios

Redesigning the Structure and Access Paths of Databases for Effective and Efficient Query Processing

Many database users are not familiar with formal query languages, the concept of schema, or the exact content of their database. Thus, it is challenging for these users to formulate their information needs over semi-structured and structured databases. To address this problem, researchers have proposed usable query interfaces over which users can formulate their information needs without knowing about formal query languages, schema or the exact content of the database. Although the mentioned interfaces increase the us-ability of the databases, they inherently suffer from low effectiveness and efficiency. The recent growth in databases’ content size and schema complexity only exacerbates this problem. In this dissertation, we present a set of approaches to redesign the components of database management systems to improve the effectiveness and efficiency of query processing. We present theoretical and empirical results on the impact of database size and schema complexity on the effectiveness of keyword query search. Based on these results, we propose a system that answers keyword queries more effectively. Further-more, we present an online learning method that improves the response time of query processing over large databases

Artificial Intelligence based multi-agent control system

Le metodologie di Intelligenza Artificiale (AI) si occupano della possibilità di rendere le macchine in grado di compiere azioni intelligenti con lo scopo di aiutare l’essere umano; quindi è possibile affermare che l’Intelligenza Artificiale consente di portare all’interno delle macchine, caratteristiche tipiche considerate come caratteristiche umane. Nello spazio dell’Intelligenza Artificiale ci sono molti compiti che potrebbero essere richiesti alla macchina come la percezione dell’ambiente, la percezione visiva, decisioni complesse. La recente evoluzione in questo campo ha prodotto notevoli scoperte, princi- palmente in sistemi ingegneristici come sistemi multi-agente, sistemi in rete, impianti, sistemi veicolari, sistemi sanitari; infatti una parte dei suddetti sistemi di ingegneria è presente in questa tesi di dottorato. Lo scopo principale di questo lavoro è presentare le mie recenti attività di ricerca nel campo di sistemi complessi che portano le metodologie di intelligenza artifi- ciale ad essere applicati in diversi ambienti, come nelle reti di telecomunicazione, nei sistemi di trasporto e nei sistemi sanitari per la Medicina Personalizzata. Gli approcci progettati e sviluppati nel campo delle reti di telecomunicazione sono presentati nel Capitolo 2, dove un algoritmo di Multi Agent Reinforcement Learning è stato progettato per implementare un approccio model-free al fine di controllare e aumentare il livello di soddisfazione degli utenti; le attività di ricerca nel campo dei sistemi di trasporto sono presentate alla fine del capitolo 2 e nel capitolo 3, in cui i due approcci riguardanti un algoritmo di Reinforcement Learning e un algoritmo di Deep Learning sono stati progettati e sviluppati per far fronte a soluzioni di viaggio personalizzate e all’identificazione automatica dei mezzi trasporto; le ricerche svolte nel campo della Medicina Personalizzata sono state presentate nel Capitolo 4 dove è stato presentato un approccio basato sul controllo Deep Learning e Model Predictive Control per affrontare il problema del controllo dei fattori biologici nei pazienti diabetici.Artificial Intelligence (AI) is a science that deals with the problem of having machines perform intelligent, complex, actions with the aim of helping the human being. It is then possible to assert that Artificial Intelligence permits to bring into machines, typical characteristics and abilities that were once limited to human intervention. In the field of AI there are several tasks that ideally could be delegated to machines, such as environment aware perception, visual perception and complex decisions in the various field. The recent research trends in this field have produced remarkable upgrades mainly on complex engineering systems such as multi-agent systems, networked systems, manufacturing, vehicular and transportation systems, health care; in fact, a portion of the mentioned engineering system is discussed in this PhD thesis, as most of them are typical field of application for traditional control systems. The main purpose if this work is to present my recent research activities in the field of complex systems, bringing artificial intelligent methodologies in different environments such as in telecommunication networks, transportation systems and health care for Personalized Medicine. The designed and developed approaches in the field of telecommunication net- works is presented in Chapter 2, where a multi-agent reinforcement learning algorithm was designed to implement a model-free control approach in order to regulate and improve the level of satisfaction of the users, while the research activities in the field of transportation systems are presented at the end of Chapter 2 and in Chapter 3, where two approaches regarding a Reinforcement Learning algorithm and a Deep Learning algorithm were designed and developed to cope with tailored travels and automatic identification of transportation moralities. Finally, the research activities performed in the field of Personalized Medicine have been presented in Chapter 4 where a Deep Learning and Model Predictive control based approach are presented to address the problem of controlling biological factors in diabetic patients

Recommendations concerning satellite-acquired earth resource data: 1982 report of the Data Management Subcommittee of the GEOSAT Committee, Incorporated

End user concerns about the content and accessibility of libraries of remote sensing data in general are addressed. Recommendations pertaining to the United States' satellite remote sensing programs urge: (1) the continuation of the NASA/EROS Data Center program to convert pre-1979 scenes to computer readable tapes and create a historical archive of this valuable data; (2) improving the EROS archive by adding geologically interesting scenes, data from other agencies (including previously classified data), and by adopting a policy to retire data from the archive; (3) establishing a computer data base inquiry system that includes remote sensing data from all publically available sources; (4) capability for prepurchase review and evaluation; (5) a flexible price structure; and (6) adoption of standard digital data products format. Information about LANDSAT 4, the status of worldwide LANDSAT receiving stations, future non-U.S. remote sensing satellites, a list of sources for LANDSAT data, and the results of a survey of GEOSAT members' remote sensing data processing systems are also considered

Transforming participation?: a comparative study of state and civil society agency within national development processes in Malawi and Ireland

In the context of growing economic, social and political polarisation between and within countries both North and South, this study addresses the question as to whether new forms of participatory governance, in the form of the Poverty Reduction Strategy Programme (PRSP) process in Malawi, and Social Partnership in Ireland, have the potential to engage multiple development discourses, and if so, under what conditions. Developing a theoretical framework to uncover the structures and dynamics underpinning both processes over time, the study highlights the interaction of domestic and global political cultures within both processes. It is argued that state actors, focused on ‘spinning’ participation to attract foreign investment, while simultaneously contracting civil society ‘partners’ in managing the fallout of the state’s economic globalisation project, are not seeking to engage multiple development discourses. The potential for such transformative participation within both processes therefore rests with civil society actors responding to the mandates of their constituents. The study identifies a key enabler in this regard as being ‘communication without’ or public awareness raising, with this enhancing visibility and public debate on both the developmental outcomes of the respective processes and the agency and actions of actors therein. While both processes are characterised by many similarities, a key difference in the area of communication is identified. While in Ireland, where domestic legacies of a hierarchical, authoritarian political culture facilitate state and civil society actors in disciplining participants within the Irish process and stifling public debate, in Malawi, these national disciplining legacies have been challenged. The study demonstrates how, in Malawi, global influences, in particular as mediated through global informational networks, have played a significant part in stimulating critical public debate, thereby transforming cultural legacies. These influences have resulted in the dominant organisation within the Malawian process tapping into the diversity of Malawian civic life, thereby raising challenges to its own form of leadership, and potentially transforming participation within its national development process