Reel notes

https://orc.library.atu.edu/atu_reel160/1003/thumbnail.jp

Two Pattern Test Cubes for Transition Path Delay Faults Test for ISCAS-85 C432

ABSTRACT: Considering full-scan circuits, incompletely-specified tests, or test cubes, are used for test data compression. When considering path delay faults, certain specified input values in a test cube are needed only for determining the lengths of the paths associated with detected faults. Path delay faults, and therefore, small delay defects, would still be detected if such values are unspecified. The goal of this paper is to explore the possibility of increasing the number of unspecified input values in a test set for path delay faults by un specifying such values in order to make the test set more amenable to test data compression. Experimental results indicate that significant numbers of such values exist. The proposed procedure unspecified them gradually to obtain a series of test sets with increasing numbers of unspecified values and decreasing path lengths. Experimental results also indicate that filling the unspecified values randomly (as with some test data compression methods) recovers some or all of the path lengths associated with detected path delay faults. The procedure uses a matching of the sets of detected faults for the comparison of path lengths

Report of the 2005 Snowmass Top/QCD Working Group

This report discusses several topics in both top quark physics and QCD at an International Linear Collider (ILC). Issues such as measurements at the $t\bar{t}$ threshold, including both theoretical and machine requirements, and the determination of electroweak top quark couplings, are reviewed. New results concerning the potential of a 500 GeV $e^+e^-$ collider for measuring $Wtb$ couplings and the top quark Yukawa coupling are presented. The status of higher order QCD corrections to jet production cross sections, heavy quark form factors, and longitudinal gauge boson scattering, needed for percent-level studies at the ILC, are reviewed. A new study of the measurement of the hadronic structure of the photon at a $\gamma\gamma$ collider is presented. The effects on top quark properties from several models of new physics, including composite models, Little Higgs theories, and CPT violation, are studied.Comment: 39 pages, many figs; typos fixed and refs added. Contributed to the 2005 International Linear Collider Physics and Detector Workshop and 2nd ILC Accelerator Workshop, Snowmass, Colorado, 14-27 Aug 200

Feeding of different levels of metabolite combinations produced by Lactobacillus plantarum on growth performance, fecal microflora, volatile fatty acids and villi height in broilers

The effects of feeding different dosages of metabolite combination of L. plantarum RS5, RI11, RG14 and RG11 strains (Com3456) on the performance of broiler chickens was studied. A total of 504 male Ross broilers were grouped into 7 treatments and offered different diets: (i) standard corn-soybean based diet (negative control); (ii) standard corn-soybean based diet +100 ppm neomycin and oxytetracycline (positive control); (iii) standard corn-soybean based diet+0.1% metabolite combination of L. plantarum RS5, RI11, RG14 and RG11 strains (Com3456); (iv) standard corn-soybean based diet+0.2% of Com3456; (v) standard corn-soybean based diet+0.3% of Com3456 (vi) standard corn-soybean based diet+0.4% of Com3456 and (vii) standard corn-soybean based diet+0.5% of Com3456. Supplementation of Com3456 with different dosages improved growth performance, reduced Enterobacteriaceae and increased lactic acid bacteria count, and increased villi height of small intestine and fecal volatile fatty acid concentration. Treatment with 0.4% and 0.2% Com3456 had the best results, especially in terms of growth performance, feed conversion ratio and villi height among other dosages. However, the dosage of 0.2% was recommended due to its lower concentration yielding a similar effect as 0.4% supplementation. These results indicate that 0.2% is an optimum level to be included in the diets of broiler in order to replace antibiotic growth promoters

Multiple - pion production by 200-GeV/c muons

The main objectives of this experiment are to study the multiple-pion production, especially fire ball-like behavior at the known muon energy, and to compare with the cosmic ray data by means of cloud chambers containing lead plates and with emulsion stack data in the lower energy region (5GeV/c). The cloud chamber data by cosmic ray muons has been investigated by means of the One Fire Ball Model (the mesons are emitted from excited centers) in the energy range of 10 to 100 GeV, while the emulsion data at 5 GeV/c have indicated dominant contributions from isobars (the excited baryon of 1238 MeV). In the cosmic ray data we can not discuss more details of 'the fire ball', such as its mass or temperature, because those incident muon energies can not be estimated directly

Authentication of Secret Information in Image Stenography

Abstract : In recent years, Steganography and Steganalysis are two important areas of research that involve a number of applications. These two areas of research are important especially when reliable and secure information exchange is required. Steganography is an art of embedding information in a cover image without causing statistically significant variations to the cover image. Steganalysis is the technology that attempts to defeat Steganography by detecting the hidden information and extracting. In this paper we propose an image Steganography that can verify the reliability of the information being transmitted to the receiver. The method can verify whether the attacker has tried to edit, delete or forge the secret information in the stegoimage. The technique embeds the hidden information in the spatial domain of the cover image and uses two special AC coefficients of the Discrete Wavelet Transform domain to verify the veracity (integrity) of the secret information from the stego image. The analysis shows that the BER and PSNR are improved in the case of DWT than DCT

Gene prediction in metagenomic fragments: A large scale machine learning approach

<p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p

Increasing health worker capacity through distance learning: a comprehensive review of programmes in Tanzania

<p>Abstract</p> <p>Background</p> <p>Tanzania, like many developing countries, faces a crisis in human resources for health. The government has looked for ways to increase the number and skills of health workers, including using distance learning in their training. In 2008, the authors reviewed and assessed the country's current distance learning programmes for health care workers, as well as those in countries with similar human resource challenges, to determine the feasibility of distance learning to meet the need of an increased and more skilled health workforce.</p> <p>Methods</p> <p>Data were collected from 25 distance learning programmes at health training institutions, universities, and non-governmental organizations throughout the country from May to August 2008. Methods included internet research; desk review; telephone, email and mail-in surveys; on-site observations; interviews with programme managers, instructors, students, information technology specialists, preceptors, health care workers and Ministry of Health and Social Welfare representatives; and a focus group with national HIV/AIDS care and treatment organizations.</p> <p>Results</p> <p>Challenges include lack of guidelines for administrators, instructors and preceptors of distance learning programmes regarding roles and responsibilities; absence of competencies for clinical components of curricula; and technological constraints such as lack of access to computers and to the internet. Insufficient funding resulted in personnel shortages, lack of appropriate training for personnel, and lack of materials for students.</p> <p>Nonetheless, current and prospective students expressed overwhelming enthusiasm for scale-up of distance learning because of the unique financial and social benefits offered by these programs. Participants were retained as employees in their health care facilities, and remained in their communities and supported their families while advancing their careers. Space in health training institutions was freed up for new students entering in-residence pre-service training.</p> <p>Conclusions</p> <p>A blended print-based distance learning model is most feasible at the national level due to current resource and infrastructure constraints. With an increase in staffing; improvement of infrastructure, coordination and curricula; and decentralization to the zonal or district level, distance learning can be an effective method to increase both the skills and the numbers of qualified health care workers capable of meeting the health care needs of the Tanzanian population.</p