1,203 research outputs found
A cost effective solar powered led street light
A cost effective solar powered LED street light was designed based on the current solar
powered street light installed at Masjid Nurul Huda, Kampung Gentisan, Sepanggar,
Sabah, Malaysia. A new load profile is obtained based on a thirty day data collection at
site utilizing motion sensor to record movement at the area. A proposed algorithm to
control the LED light intensity was presented. The new load profile was processed based
on the proposed algorithm. Simulation to design a new solar powered LED street light
was done using the new load profile. The design uses 180W Solar Panel, with 8 x 6V
(10Ah) batteries. The system has the design capability to last for 38.6 hours. Results are
compared with existing solar powered LED street light and also existing mercury vapor
street light. An economic analysis for 25 years is also performed to determine the cost
effectiveness of the new system where the Life Cycle Cost is found to be RM 11,143.00
compared to the existing conventional design of RM 13,626.00 which is equivalent to
18.22% of cost savings
Interview of Frederick Van Fleteren, Ph.D.
Frederick Van Fleteren was born in St. Clair Shores, Michigan in 1941. He was raised by two devout Catholic parents who valued his education. He went to Catholic grade schools and colleges in the United States, as well as two Irish universities when he was getting his PhD. in philosophy. His interest in philosophy would guide his academic and professional career from his undergraduate years to the present day where he is a Philosophy professor at La Salle University. From 1967 until 1978, he was an ordained priest with the Augustinians. He received his B.A. and M.A. from Villanova in 1964 and 1968 respectively, and his PhD in ancient philosophy with a specialty in St. Augustine from the National University of Ireland and University College, Dublin in 1971. After leaving the priesthood in 1978, he worked as an assistant administrator at Crozer-Chester Medical Center at Crozer Pennsylvania in 1978, an executive director of the hospice program at Lourdes Hospital in Bingham New York from 1979 until 1981, and director of a hospice at Quakertown Pennsylvania from 1989 until 1995. He has been a professor at La Salle University since 1987, and has edited and published numerous academic articles and books since the 1970s
Combining the Performance Strengths of the Logistic Regression and Neural Network Models: A Medical Outcomes Approach
The assessment of medical outcomes is important in the effort to contain costs, streamline patient management, and codify medical practices. As such, it is necessary to develop predictive models that will make accurate predictions of these outcomes. The neural network methodology has often been shown to perform as well, if not better, than the logistic regression methodology in terms of sample predictive performance. However, the logistic regression method is capable of providing an explanation regarding the relationship(s) between variables. This explanation is often crucial to understanding the clinical underpinnings of the disease process. Given the respective strengths of the methodologies in question, the combined use of a statistical (i.e., logistic regression) and machine learning (i.e., neural network) technology in the classification of medical outcomes is warranted under appropriate conditions. The study discusses these conditions and describes an approach for combining the strengths of the models
Towards Semantic Interoperability for IT Governance: An Ontological Approach
In today's IT-centric environment, businesses rely more heavily on IT technologies. Organizations are often obliged to satisfy different requirements demanded and imposed by customers, business partners and legal entities. With increasing regulatory requirements, various best practices and standards are phenomenally employed to benchmark organizational adherence to different regulations. In a heterogeneous, multi-regulated, multi-disciplined and global environment, corporations are often required to consult with multiple standards. Interoperability between the standards for heterogeneous compliance management in the forms of semantic data translation and data integration is subsequently required. Semantic translation between standards allows compliance efforts established on a standard to be based on another standard. On the other hand, semantic data integration enables an integrated view of multiple standards. We present in this paper an ontology-based approach to the semantic interoperability problem in the domain of IT governance
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The unfolding body plan of primate embryos in culture.
Improved culture of non-human primate embryos reveals the establishment of the crucial framework for subsequent development of bodily tissues and the germline in fetuses, bringing us closer to comprehending the elusive development of early human embryos
Information developer-user system linking roles of education assistants in the Missouri small farm family program
"August 1982."Includes bibliographical references (pages 34-35)
Recent Developments in Nonregular Fractional Factorial Designs
Nonregular fractional factorial designs such as Plackett-Burman designs and
other orthogonal arrays are widely used in various screening experiments for
their run size economy and flexibility. The traditional analysis focuses on
main effects only. Hamada and Wu (1992) went beyond the traditional approach
and proposed an analysis strategy to demonstrate that some interactions could
be entertained and estimated beyond a few significant main effects. Their
groundbreaking work stimulated much of the recent developments in design
criterion creation, construction and analysis of nonregular designs. This paper
reviews important developments in optimality criteria and comparison, including
projection properties, generalized resolution, various generalized minimum
aberration criteria, optimality results, construction methods and analysis
strategies for nonregular designs.Comment: Submitted to the Statistics Surveys (http://www.i-journals.org/ss/)
by the Institute of Mathematical Statistics (http://www.imstat.org
Birds in peatswamp at Klias Forest Reserve and Environs, Sabah, Malaysian Borneo
Periodically from 1998-2004, we surveyed birds in the Klias Forest Reserve, which is one of the last remaining pockets of peatswamp in western Sabah. We report here on those surveys. We also review prior work on birds in peatswamp and swamp forest in the Klias-Sipitang region of Sabah as it relates to the conservation of habitat and birds specialized on peatswamp. Peatswamp forest is in jeopardy from development and fires throughout Borneo, and particularly in the Malaysian State of Sabah, which had very little to start. Peatswamp in the Klias area is of particular importance for conservation and bird watching because Klias is close to the main tourist center of Borneo, Kota Kinabalu, and is the only easily accessible site for reliable sightings of Hook-billed Bulbul (Setornis criniger), Grey-breasted Babbler, (Malacopteron albogulare), and Scarlet-breasted Flowerpecker (Prionochilus thoracicus) in Sabah
Predicting co-complexed protein pairs using genomic and proteomic data integration
BACKGROUND: Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H) and affinity purification coupled with mass spectrometry (APMS) have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. RESULTS: Using a supervised machine learning approach – probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP) of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue), a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database), and the remaining predictions may potentially represent unknown CCPs. CONCLUSIONS: We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP) pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation
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