Dynamic Dependency Collapsing

In this dissertation, we explore the concept of dynamic dependency collapsing. Performance increases in computer architecture are always introduced by exploiting additional parallelism when the clock speed is fixed. We show that further improvements are possible even when the available parallelism in programs are exhausted. This performance improvement is possible due to executing instructions in parallel that would ordinarily have been serialized. We call this concept dependency collapsing. We explore existing techniques that exploit parallelism and show which of them fall under the umbrella of dependency collapsing. We then introduce two dependency collapsing techniques of our own. The first technique collapses data dependencies by executing two normally dependent instructions together by fusing them. We show that exploiting the additional parallelism generated by collapsing these dependencies results in a performance increase. Our second technique collapses resource dependencies to execute instructions that would normally have been serialized due to resource constraints in the processor. We show that it is possible to take advantage of larger in-processor structures while avoiding the power and area penalty this often implies

Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace

The symposium Vision-21: Interdisciplinary Science and Engineering in the Era of Cyberspace was held at the NASA Lewis Research Center on March 30-31, 1993. The purpose of the symposium was to simulate interdisciplinary thinking in the sciences and technologies which will be required for exploration and development of space over the next thousand years. The keynote speakers were Hans Moravec, Vernor Vinge, Carol Stoker, and Myron Krueger. The proceedings consist of transcripts of the invited talks and the panel discussion by the invited speakers, summaries of workshop sessions, and contributed papers by the attendees

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Management: A continuing literature survey with indexes, March 1975

A special bibliography listing 1,064 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in 1974 is presented

The Shadows of Immobility: Low-Wage Work, Single Mothers' Lives and Workplace Culture.

Contemporary American public policies targeted towards low-income single mothers reflect a presumption that steady employment in and of itself, even in the low-wage labor market, is the key to mobility. The experiences recounted in this dissertation challenge that presumption. Based on fifteen months of ethnographic research among single mothers working as nursing assistants at a care facility in southeastern Michigan, this dissertation reveals lives characterized by considerable economic hardships and social strains. Even long-term job tenure does little to diminish these struggles as the job’s structure (a structure typical of less-skilled service-sector jobs), combined with conditions in single mothers’ home lives, militates against significant wage or occupational mobility. This immobility creates economic and social tensions that permeate these mothers’ home and work lives. In this ethnography of the social experience of immobility, I explore how the immobility of these nursing assistant jobs joins together the economic and social world of the workplace with the economic and social worlds of the single mothers in both predictable and unexpected ways. I document, for example, the quandaries the wages pose for women’s home lives and how women handle these. But, uniquely, I also show how tensions engendered by low wages and immobility feedback into and are managed within the workplace. I demonstrate that workers’ economic and social struggles are not only recognized by management but are incorporated into workplace practices in ways that help contain and depoliticize their disruptive potential. I also highlight ways in which neo-liberalism and speculative capitalism (and the market-based, individualized orientations they promote) encourage both the mothers and management to embrace remedies to the immobility of these jobs that depend on individual effort and market opportunities. Within the workplace this can be seen in management’s endorsement of extra-work, postsecondary educational endeavors. The improbability of such endeavors for most mothers, however, leads some to devise “alternative” strategies for transforming their circumstances involving on-line dating, membership in a multi-level marketing sales organization, and participation in the subprime mortgage market; strategies that can expose mothers to significant risk. This dissertation suggests the limits of individualized, market-based remedies in ameliorating larger inequalities.Ph.D.Social Work and AnthropologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60819/1/kimclum_1.pd

Data quality issues in electronic health records for large-scale databases

Data Quality (DQ) in Electronic Health Records (EHRs) is one of the core functions that play a decisive role to improve the healthcare service quality. The DQ issues in EHRs are a noticeable trend to improve the introduction of an adaptive framework for interoperability and standards in Large-Scale Databases (LSDB) management systems. Therefore, large data communications are challenging in the traditional approaches to satisfy the needs of the consumers, as data is often not capture directly into the Database Management Systems (DBMS) in a seasonably enough fashion to enable their subsequent uses. In addition, large data plays a vital role in containing plenty of treasures for all the fields in the DBMS. EHRs technology provides portfolio management systems that allow HealthCare Organisations (HCOs) to deliver a higher quality of care to their patients than that which is possible with paper-based records. EHRs are in high demand for HCOs to run their daily services as increasing numbers of huge datasets occur every day. Efficient EHR systems reduce the data redundancy as well as the system application failure and increase the possibility to draw all necessary reports. However, one of the main challenges in developing efficient EHR systems is the inherent difficulty to coherently manage data from diverse heterogeneous sources. It is practically challenging to integrate diverse data into a global schema, which satisfies the need of users. The efficient management of EHR systems using an existing DBMS present challenges because of incompatibility and sometimes inconsistency of data structures. As a result, no common methodological approach is currently in existence to effectively solve every data integration problem. The challenges of the DQ issue raised the need to find an efficient way to integrate large EHRs from diverse heterogeneous sources. To handle and align a large dataset efficiently, the hybrid algorithm method with the logical combination of Fuzzy-Ontology along with a large-scale EHRs analysis platform has shown the results in term of improved accuracy. This study investigated and addressed the raised DQ issues to interventions to overcome these barriers and challenges, including the provision of EHRs as they pertain to DQ and has combined features to search, extract, filter, clean and integrate data to ensure that users can coherently create new consistent data sets. The study researched the design of a hybrid method based on Fuzzy-Ontology with performed mathematical simulations based on the Markov Chain Probability Model. The similarity measurement based on dynamic Hungarian algorithm was followed by the Design Science Research (DSR) methodology, which will increase the quality of service over HCOs in adaptive frameworks