What is the contribution of personal information management systems (PIMS) to the Working Model and personal work system of knowledge workers?

The thesis reports research into a phenomenon which it calls the personal working model of an individual knowledge worker. The principal conjecture addressed in this thesis is that each of us has a personal working model which is supported by a personal work system enabled by a personal information management system. For some people, these are well defined; for most they are not even explicit. By means of structured self-reflection aided by conceptual knowledge modelling within the context of a process of action learning they can be improved. That personal working model is predicted by Ashby's law of requisite variety and by the good regulator theorem of Conant and Ashby. The latter theorem states that the only good regulator of a system is a model of that system. The thesis and the work it reports result from a systemic approach to identifying the personal information management system and personal work system which together contribute to the personal working model. Starting with abductive conjecture, the author has sought to understand what models are and to explore ways in which those models can themselves be expressed. The thesis shows how a new approach to the conceptual modelling of aspects of the personal knowledge of knowledge worker was designed, built and then used. Similarly, the actual data used by a knowledge worker had to be stored, and for this purpose a personal information management system was also designed. Both these artefacts are evaluated in accordance with principles drawn from the literature of design science research. The research methodology adopted in the first phase of the research now ending also included a relatively novel approach in which the PhD student attempted to observe himself over the last five years of his PhD research – this approach is sometimes called autoethnography. This autoethnographic element is one of a number of methods used within an overall framework grounded by the philosophical approach called critical realism. The work reported in the thesis is initial exploratory research which, it is planned, will continue in empirical action research involving mentored action learning undertaken by professional knowledge workers

Predictable Shared Memory Resources for Multi-Core Real-Time Systems

A major challenge in multi-core real-time systems is the interference problem on the shared hardware components amongst cores. Examples of these shared components include buses, on-chip caches, and off-chip dynamic random access memories (DRAMs). The problem arises because different cores in the system interfere with each other, while competing to access the shared hardware components. It is a challenging problem for real-time systems because operations of one core affect the temporal behaviour of other cores, which complicates the timing analysis of the system. We address this problem by making the following contributions. 1) For shared buses, we propose CArb, a predictable and criticality-aware arbiter, which provides guaranteed and differential service to tasks based on their requirements. In addition, we utilize CArb to mitigate overheads resulting from system switching among different modes. 2) For the cache hierarchy, we address the problem of maintaining cache coherence in multi-core real-time systems by modifying current coherence protocols such that data sharing is viable for real-time systems in a manner amenable for timing analysis. The proposed solution provides performance improvements, does not impose any scheduling restrictions, and does not require any source-code modifications. 3) At the shared DRAM level, we propose PMC, a programmable memory controller that provides latency guarantees for running tasks upon accessing the off-chip DRAM, while assigning differential memory services to tasks based on their bandwidth and latency requirements. In addition to PMC, we conduct a latency-based analysis on DRAM memory controllers (MCs). Our analysis provides both best-case and worst-case bounds on the latency that any request suffers upon accessing the DRAM. The analysis comprehensively covers all possible interactions of successive requests considering all possible DRAM states. Finally, we formally model request interrelations and DRAM command interactions. We use these models to develop an automated validation framework along with benchmark suites to validate and evaluate PMC and any other MC, which we release as an open-source tool

Geodetic Sciences

Space geodetic techniques, e.g., global navigation satellite systems (GNSS), Very Long Baseline Interferometry (VLBI), satellite gravimetry and altimetry, and GNSS Reflectometry & Radio Occultation, are capable of measuring small changes of the Earth�s shape, rotation, and gravity field, as well as mass changes in the Earth system with an unprecedented accuracy. This book is devoted to presenting recent results and development in space geodetic techniques and sciences, including GNSS, VLBI, gravimetry, geoid, geodetic atmosphere, geodetic geophysics and geodetic mass transport associated with the ocean, hydrology, cryosphere and solid-Earth. This book provides a good reference for geodetic techniques, engineers, scientists as well as user community

A scalable analysis framework for large-scale RDF data

With the growth of the Semantic Web, the availability of RDF datasets from multiple domains as Linked Data has taken the corpora of this web to a terabyte-scale, and challenges modern knowledge storage and discovery techniques. Research and engineering on RDF data management systems is a very active area with many standalone systems being introduced. However, as the size of RDF data increases, such single-machine approaches meet performance bottlenecks, in terms of both data loading and querying, due to the limited parallelism inherent to symmetric multi-threaded systems and the limited available system I/O and system memory. Although several approaches for distributed RDF data processing have been proposed, along with clustered versions of more traditional approaches, their techniques are limited by the trade-off they exploit between loading complexity and query efficiency in the presence of big RDF data. This thesis then, introduces a scalable analysis framework for processing large-scale RDF data, which focuses on various techniques to reduce inter-machine communication, computation and load-imbalancing so as to achieve fast data loading and querying on distributed infrastructures. The first part of this thesis focuses on the study of RDF store implementation and parallel hashing on big data processing. (1) A system-level investigation of RDF store implementation has been conducted on the basis of a comparative analysis of runtime characteristics of a representative set of RDF stores. The detailed time cost and system consumption is measured for data loading and querying so as to provide insight into different triple store implementation as well as an understanding of performance differences between different platforms. (2) A high-level structured parallel hashing approach over distributed memory is proposed and theoretically analyzed. The detailed performance of hashing implementations using different lock-free strategies has been characterized through extensive experiments, thereby allowing system developers to make a more informed choice for the implementation of their high-performance analytical data processing systems. The second part of this thesis proposes three main techniques for fast processing of large RDF data within the proposed framework. (1) A very efficient parallel dictionary encoding algorithm, to avoid unnecessary disk-space consumption and reduce computational complexity of query execution. The presented implementation has achieved notable speedups compared to the state-of-art method and also has achieved excellent scalability. (2) Several novel parallel join algorithms, to efficiently handle skew over large data during query processing. The approaches have achieved good load balancing and have been demonstrated to be faster than the state-of-art techniques in both theoretical and experimental comparisons. (3) A two-tier dynamic indexing approach for processing SPARQL queries has been devised which keeps loading times low and decreases or in some instances removes intermachine data movement for subsequent queries that contain the same graph patterns. The results demonstrate that this design can load data at least an order of magnitude faster than a clustered store operating in RAM while remaining within an interactive range for query processing and even outperforms current systems for various queries

Large Space Antenna Systems Technology, 1984

Mission applications for large space antenna systems; large space antenna structural systems; materials and structures technology; structural dynamics and control technology, electromagnetics technology, large space antenna systems and the Space Station; and flight test and evaluation were examined

The Effect Of Visual Representations Of Large Qualitative Data Sets On Decision-Making Processes

This study investigated the influence of visual representation of qualitative data at progressively greater levels of abstraction on decision-making processes in order to address a gap in research that currently focuses predominantly on the final choice phase of decision-making and representation of quantitative information. Specifically, this research investigated how four forms of data representation, varying progressively in their use of visualization and data abstraction, compare in the effort required to arrive at a decision, the ease with which themes are identified, satisfaction with the level of detail obtained, the confidence in decisions made, and the intuitiveness of representations. The experimental design closely simulated a real world decision-making scenario with a decision-making task developed in consultation with industry experts and a large qualitative dataset obtained from a survey on workplace environmental design conducted by a large global company. Qualitative data can be open to interpretation and final decisions or conclusions can be difficult to evaluate for accuracy. Therefore, decisions were compared across the four conditions to see how varying the level of visual abstraction of data representation encouraged participants to focus on certain themes versus others and to arrive at their decisions. The results indicate that in a matter of an hour, most participants identified key themes in the data regardless of the level of abstraction of the visual representation. However, there were significant differences in operational effort required, the intuitiveness of representations, and a marginaly significant difference in the ease with which themes were identified. Participants reported satisfaction with the level of detail reached and ratings of confidence in decisions-made were low or neutral and at odds with their objective performance. Insights into the effect of the visual representations and the subjective experience of the decision-maker are discussed

LINGUISTIC DIVERSITY AND CHANGING TECHNOLOGY IN INDIA'S REGIONAL FILM MARKETS

Thesis (Ph.D.) - Indiana University, Mass Communications/Telecommunications, 2009The Indian film market is unique compared to other major film producing countries. India is the most prolific producer of films and Indian films command a dominant share of the domestic market. However, these films earn meager export revenues. This pattern contradicts findings from research which show that media products produced by larger markets tend to dominate their domestic markets and are also popular when exported. This dissertation shows that when the linguistic diversity of Indian film production is taken into consideration, the patterns observed in the Indian film market conform to theoretical predictions. This dissertation applies the theoretical frameworks of the home market model, and market size theories from the economics literature, to examine the effect of market size on product quality and variety in Indian language film markets. Time series data relating to the number of films produced, linguistic population size and gross domestic state product was assembled from multiple Indian language film markets from the coming of sound in 1931 to 2005. Cross sectional and panel estimation methods were used to analyze the relationships between market size and film production. As predicted by theory both cross sectional and panel models found that market size had a significant positive effect on the number of films produced in a language market. Anecdotal evidence also shows that films produced in larger Indian language markets have higher film production investment, greater variety of genre elements, and are exported more. These patterns provide further supplemental evidence for the predictions of the home market model. In the second part of the dissertation, the contrary trend of persistent film admissions in the face of growing television penetration in India was examined. Research has shown that competing technologies such as television can have a positive or negative effect on film industry revenues depending on the types of services that are offered. For instance, premium services such as pay-cable and DBS along with home video have added revenues to the US film industry which have supported the production of expensive films that in turn have stimulated theatrical admissions. On the other hand, broadcast television has generally had a negative effect on theatrical admissions. This dissertation empirically examines the effect of television penetration in India, in the context of five major film producing countries such as US, UK, France, Germany and Japan. Time series data from the introduction of television in each of these markets till 2005 relating to two measures of the annual number of theatrical admissions ─ aggregate admissions, and admissions per capita ─ and two additional measures, i.e., the annual number of films produced, and the number of screens was assembled. Regression models at the individual country level as well as at the group level were estimated. The empirical analysis reveals that statistically, India fits the international pattern when it comes to the significant negative effect of television penetration on aggregate and per capita admissions. As in other countries, as more Indian households acquired television sets, per capita admissions declined. Individual country regressions showed India was similar to the US and France where television penetration did not have a statistically significant effect on the number of films produced. This is different from the UK and Japan where television penetration had a significant negative effect on films produced. However television penetration had a negative but statistically non- significant effect on the number of screens in India unlike in the US where television penetration had a statistically significant negative effect on the number of screens. These results assume significance for policy because the major share of Indian film industry revenues (78%) comes from theatrical admissions. Television penetration thus poses a serious threat to Indian film industry revenues unless premium services can be used to add revenues

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Nimbus-B solar-conversion power supply subsystem Quarterly technical report no. 2, Dec. 1965 - Feb. 1966

Nimbus B solar conversion power supply subsyste

Scheduling with Time Lags

Scheduling is essential when activities need to be allocated to scarce resources over time. Motivated by the problem of scheduling barges along container terminals in the Port of Rotterdam, this thesis designs and analyzes algorithms for various on-line and off-line scheduling problems with time lags. A time lag specifies a minimum time delay required between the execution of two consecutive operations of the same job. Time lags may be the result of transportation delays (like the time required for barges to sail from one terminal to the next), the duration of activities that do not require resources (like drying or cooling down), or intermediate processes on non-bottleneck machines between two bottleneck machines. For the on-line flow shop, job shop and open shop problems of minimizing the makespan, we analyze the competitive ratio of a class of greedy algorithms. For the off-line parallel flow shop scheduling problem with time lags of minimizing the makespan, we design algorithms with fixed worst-case performance guarantees. For two special subsets of scheduling problems with time lags, we show that Polynomial-Time Approximation Schemes (PTAS) can be constructed under certain mild conditions. For the fixed interval scheduling problem, we show that the flow shop problem is solvable in polynomial time in the case of equal time lags but that it is NP-hard in the strong sense for general time lags. The fixed interval two-machine job shop and open shop problems are shown to be solvable in polynomial time if the time lags are smaller than the processing time of any operation