Prediction of turning stability using receptance coupling

NASA Astrophysics Data System (ADS)

Jasiewicz, Marcin; Powałka, Bartosz

2018-01-01

This paper presents an issue of machining stability prediction of dynamic "lathe - workpiece" system evaluated using receptance coupling method. Dynamic properties of the lathe components (the spindle and the tailstock) are assumed to be constant and can be determined experimentally based on the results of the impact test. Hence, the variable of the system "machine tool - holder - workpiece" is the machined part, which can be easily modelled analytically. The method of receptance coupling enables a synthesis of experimental (spindle, tailstock) and analytical (machined part) models, so impact testing of the entire system becomes unnecessary. The paper presents methodology of analytical and experimental models synthesis, evaluation of the stability lobes and experimental validation procedure involving both the determination of the dynamic properties of the system and cutting tests. In the summary the experimental verification results would be presented and discussed.

Machinability of IPS Empress 2 framework ceramic.

PubMed

Schmidt, C; Weigl, P

2000-01-01

Using ceramic materials for an automatic production of ceramic dentures by CAD/CAM is a challenge, because many technological, medical, and optical demands must be considered. The IPS Empress 2 framework ceramic meets most of them. This study shows the possibilities for machining this ceramic with economical parameters. The long life-time requirement for ceramic dentures requires a ductile machined surface to avoid the well-known subsurface damages of brittle materials caused by machining. Slow and rapid damage propagation begins at break outs and cracks, and limits life-time significantly. Therefore, ductile machined surfaces are an important demand for machine dental ceramics. The machining tests were performed with various parameters such as tool grain size and feed speed. Denture ceramics were machined by jig grinding on a 5-axis CNC milling machine (Maho HGF 500) with a high-speed spindle up to 120,000 rpm. The results of the wear test indicate low tool wear. With one tool, you can machine eight occlusal surfaces including roughing and finishing. One occlusal surface takes about 60 min machining time. Recommended parameters for roughing are middle diamond grain size (D107), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 1000 mm/min, depth of cut a(e) = 0.06 mm, width of contact a(p) = 0.8 mm, and for finishing ultra fine diamond grain size (D46), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 100 mm/min, depth of cut a(e) = 0.02 mm, width of contact a(p) = 0.8 mm. The results of the machining tests give a reference for using IPS Empress(R) 2 framework ceramic in CAD/CAM systems. Copyright 2000 John Wiley & Sons, Inc.

Stirling cryocooler test results and design model verification

NASA Astrophysics Data System (ADS)

Shimko, Martin A.; Stacy, W. D.; McCormick, John A.

A long-life Stirling cycle cryocooler being developed for spaceborne applications is described. The results from tests on a preliminary breadboard version of the cryocooler used to demonstrate the feasibility of the technology and to validate the generator design code used in its development are presented. This machine achieved a cold-end temperature of 65 K while carrying a 1/2-W cooling load. The basic machine is a double-acting, flexure-bearing, split Stirling design with linear electromagnetic drives for the expander and compressors. Flat metal diaphragms replace pistons for sweeping and sealing the machine working volumes. The double-acting expander couples to a laminar-channel counterflow recuperative heat exchanger for regeneration. The PC-compatible design code developed for this design approach calculates regenerator loss, including heat transfer irreversibilities, pressure drop, and axial conduction in the regenerator walls. The code accurately predicted cooler performance and assisted in diagnosing breadboard machine flaws during shakedown and development testing.

Machinability of cast commercial titanium alloys.

PubMed

Watanabe, I; Kiyosue, S; Ohkubo, C; Aoki, T; Okabe, T

2002-01-01

This study investigated the machinability of cast orthopedic titanium (metastable beta) alloys for possible application to dentistry and compared the results with those of cast CP Ti, Ti-6Al-4V, and Ti-6Al-7Nb, which are currently used in dentistry. Machinability was determined as the amount of metal removed with the use of an electric handpiece and a SiC abrasive wheel turning at four different rotational wheel speeds. The ratios of the amount of metal removed and the wheel volume loss (machining ratio) were also evaluated. Based on these two criteria, the two alpha + beta alloys tested generally exhibited better results for most of the wheel speeds compared to all the other metals tested. The machinability of the three beta alloys employed was similar or worse, depending on the speed of the wheel, compared to CP Ti. Copyright 2002 Wiley Periodicals, Inc.

The production of calibration specimens for impact testing of subsize Charpy specimens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexander, D.J.; Corwin, W.R.; Owings, T.D.

1994-09-01

Calibration specimens have been manufactured for checking the performance of a pendulum impact testing machine that has been configured for testing subsize specimens, both half-size (5.0 {times} 5.0 {times} 25.4 mm) and third-size (3.33 {times} 3.33 {times} 25.4 mm). Specimens were fabricated from quenched-and-tempered 4340 steel heat treated to produce different microstructures that would result in either high or low absorbed energy levels on testing. A large group of both half- and third-size specimens were tested at {minus}40{degrees}C. The results of the tests were analyzed for average value and standard deviation, and these values were used to establish calibration limitsmore » for the Charpy impact machine when testing subsize specimens. These average values plus or minus two standard deviations were set as the acceptable limits for the average of five tests for calibration of the impact testing machine.« less

Machining of Aircraft Titanium with Abrasive-Waterjets for Fatigue Critical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, H. T.; Hovanski, Yuri; Dahl, Michael E.

2010-10-04

Laboratory tests were conducted to determine the fatigue performance of AWJ-machined aircraft titanium. Dog-bone specimens machined with AWJs were prepared and tested with and without sanding and dry-grit blasting with Al2O3 as secondary processes. The secondary processes were applied to remove the visual appearance of AWJ-generated striations and to clean up the garnet embedment. The fatigue performance of AWJ-machined specimens was compared with baseline specimens machined with CNC milling. Fatigue test results not only confirmed the findings of the aluminum dog-bone specimens but also further enhance the fatigue performance. In addition, titanium is known to be notoriously difficult to cutmore » with contact tools while AWJs cut it 34% faster than stainless steel. AWJ cutting and dry-grit blasting are shown to be a preferred combination for processing aircraft titanium that is fatigue critical.« less

A comparison of muscle activation between a Smith machine and free weight bench press.

PubMed

Schick, Evan E; Coburn, Jared W; Brown, Lee E; Judelson, Daniel A; Khamoui, Andy V; Tran, Tai T; Uribe, Brandon P

2010-03-01

The bench press exercise exists in multiple forms including the machine and free weight bench press. It is not clear though how each mode differs in its effect on muscle activation. The purpose of this study was to compare muscle activation of the anterior deltoid, medial deltoid, and pectoralis major during a Smith machine and free weight bench press at lower (70% 1 repetition maximum [1RM]) and higher (90% 1RM) intensities. Normalized electromyography amplitude values were used during the concentric phase of the bench press to compare muscle activity between a free weight and Smith machine bench press. Participants were classified as either experienced or inexperienced bench pressers. Two testing sessions were used, each of which entailed either all free weight or all Smith machine testing. In each testing session, each participant's 1RM was established followed by 2 repetitions at 70% of 1RM and 2 repetitions at 90% of 1RM. Results indicated greater activation of the medial deltoid on the free weight bench press than on the Smith machine bench press. Also, there was greater muscle activation at the 90% 1RM load than at the 70% 1RM load. The results of this study suggest that strength coaches should consider choosing the free weight bench press over the Smith machine bench press because of its potential for greater upper-body muscular development.

Taking the fifth amendment in Turing's imitation game

NASA Astrophysics Data System (ADS)

Warwick, Kevin; Shah, Huma

2017-03-01

In this paper, we look at a specific issue with practical Turing tests, namely the right of the machine to remain silent during interrogation. In particular, we consider the possibility of a machine passing the Turing test simply by not saying anything. We include a number of transcripts from practical Turing tests in which silence has actually occurred on the part of a hidden entity. Each of the transcripts considered here resulted in a judge being unable to make the 'right identification', i.e., they could not say for certain which hidden entity was the machine.

Hydraulic Fatigue-Testing Machine

NASA Technical Reports Server (NTRS)

Hodo, James D.; Moore, Dennis R.; Morris, Thomas F.; Tiller, Newton G.

1987-01-01

Fatigue-testing machine applies fluctuating tension to number of specimens at same time. When sample breaks, machine continues to test remaining specimens. Series of tensile tests needed to determine fatigue properties of materials performed more rapidly than in conventional fatigue-testing machine.

Propagation mode of Portevin-Le Chatelier plastic instabilities in an aluminium-magnesium alloy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeghloul, A.; Mliha-Touati, M.; Bakir, S.

1996-11-01

The Portevin-Le Chatelier (PLC) effect is characterized by the appearance of serrations in load (hard tensile machine for constant strain rate tests) or by steps (soft tensile machine for constant stress rate tests) or by steps (soft tensile machine for constant stress rate tests) on the stress-strain curves. It is now widely accepted that the PLC propagative instability stems from the dynamic interaction between diffusing solute atoms and mobile dislocations in the temperature and strain rate ranges where dynamic strain ageing (DSA) takes place. This competition results in a negative strain-rate sensitivity. However, in some alloys, like concentrated solid solutions,more » shearing of precipitates accompanied by their dissolution and subsequent reprecipitation during tensile test may also lead to a negative strain rate sensitivity. In view of the renewed theoretical interest in propagative instabilities, it is important that the experimental features of band propagation be well characterized. In this work the authors present experimental results that are obtained from the investigation of the PLC bands associated with discontinuous yielding. These results show that the band strain, the band velocity and the propagation mode of the bands depend on the stress rate when the test is carried out on a soft tensile machine.« less

[A new machinability test machine and the machinability of composite resins for core built-up].

PubMed

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

Application of Abrasive-Waterjets for Machining Fatigue-Critical Aircraft Aluminum Parts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, H T; Hovanski, Yuri; Dahl, Michael E

2010-08-19

Current specifications require AWJ-cut aluminum parts for fatigue critical aerospace structures to go through subsequent processing due to concerns of degradation in fatigue performance. The requirement of secondary process for AWJ-machined parts greatly negates the cost effectiveness of waterjet technology. Some cost savings are envisioned if it can be shown that AWJ net cut parts have comparable durability properties as those conventionally machined. To revisit and upgrade the specifications for AWJ machining of aircraft aluminum, “Dog-bone” specimens, with and without secondary processes, were prepared for independent fatigue tests at Boeing and Pacific Northwest National Laboratory (PNNL). Test results show thatmore » the fatigue life is proportional to quality levels of machined edges or inversely proportional to the surface roughness Ra . Even at highest quality level, the average fatigue life of AWJ-machined parts is about 30% shorter than those of conventionally machined counterparts. Between two secondary processes, dry-grit blasting with aluminum oxide abrasives until the striation is removed visually yields excellent result. It actually prolongs the fatigue life of parts at least three times higher than that achievable with conventional machining. Dry-grit blasting is relatively simple and inexpensive to administrate and, equally important, alleviates the concerns of garnet embedment.« less

THE ROLE OF REVIEW MATERIAL IN CONTINUOUS PROGRAMMING WITH TEACHING MACHINES.

ERIC Educational Resources Information Center

FERSTER, C.B.

STUDENTS WERE PRESENTED 61 LESSONS BY MEANS OF SEMIAUTOMATIC TEACHING MACHINES. LESSONS WERE ARRANGED SO THAT EACH PARTICIPATING STUDENT STUDIED PART OF THE COURSE MATERIAL WITH A SINGLE REPETITION AND PART WITHOUT REPETITION. DATA WERE OBTAINED FROM TWO TESTS SHOWING TEACHING-MACHINE RESULTS AND ONE FINAL COURSE EXAMINATION. NO SIGNIFICANT…

Acceptability of Using Electronic Vending Machines to Deliver Oral Rapid HIV Self-Testing Kits: A Qualitative Study

PubMed Central

Young, Sean D.; Daniels, Joseph; Chiu, ChingChe J.; Bolan, Robert K.; Flynn, Risa P.; Kwok, Justin; Klausner, Jeffrey D.

2014-01-01

Introduction Rates of unrecognized HIV infection are significantly higher among Latino and Black men who have sex with men (MSM). Policy makers have proposed that HIV self-testing kits and new methods for delivering self-testing could improve testing uptake among minority MSM. This study sought to conduct qualitative assessments with MSM of color to determine the acceptability of using electronic vending machines to dispense HIV self-testing kits. Materials and Methods African American and Latino MSM were recruited using a participant pool from an existing HIV prevention trial on Facebook. If participants expressed interest in using a vending machine to receive an HIV self-testing kit, they were emailed a 4-digit personal identification number (PIN) code to retrieve the test from the machine. We followed up with those who had tested to assess their willingness to participate in an interview about their experience. Results Twelve kits were dispensed and 8 interviews were conducted. In general, participants expressed that the vending machine was an acceptable HIV test delivery method due to its novelty and convenience. Discussion Acceptability of this delivery model for HIV testing kits was closely associated with three main factors: credibility, confidentiality, and convenience. Future research is needed to address issues, such as user-induced errors and costs, before scaling up the dispensing method. PMID:25076208

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

NASA Astrophysics Data System (ADS)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Results of Investigative Tests of Gas Turbine Engine Compressor Blades Obtained by Electrochemical Machining

NASA Astrophysics Data System (ADS)

Kozhina, T. D.; Kurochkin, A. V.

2016-04-01

The paper highlights results of the investigative tests of GTE compressor Ti-alloy blades obtained by the method of electrochemical machining with oscillating tool-electrodes, carried out in order to define the optimal parameters of the ECM process providing attainment of specified blade quality parameters given in the design documentation, while providing maximal performance. The new technological methods suggested based on the results of the tests; in particular application of vibrating tool-electrodes and employment of locating elements made of high-strength materials, significantly extend the capabilities of this method.

Young’s modulus and Poisson’s ratio changes due to machining in porous microcracked cordierite

DOE PAGES

Cooper, R. C.; Bruno, Giovanni; Onel, Yener; ...

2016-07-25

Microstructural changes in porous cordierite caused by machining were characterized using microtensile testing, X-ray computed tomography and scanning electron microscopy. Young s moduli and Poisson s ratios were determined on ~215-380 um thick machined samples by combining digital image correlation and microtensile loading. The results provide evidence for an increase in microcrack density due to machining of the thin samples extracted from diesel particulate filter honeycombs.

Impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Michael

2016-01-01

Background: Elementary Science Education is struggling with multiple challenges. National and State test results confirm the need for deeper understanding in elementary science education. Moreover, national policy statements and researchers call for increased exposure to engineering and technology in elementary science education. The basic motivation of this study is to suggest a solution to both improving elementary science education and increasing exposure to engineering and technology in it. Purpose/Hypothesis: This mixed-method study examined the impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. We hypothesize that the LEGO-engineering design unit is as successful as the inquiry-based unit in terms of students' science content learning of simple machines. Design/Method: We used a mixed-methods approach to investigate our research questions; we compared the control and the experimental groups' scores from the tests and interviews by using Analysis of Covariance (ANCOVA) and compared each group's pre- and post-scores by using paired t-tests. Results: Our findings from the paired t-tests show that both the experimental and comparison groups significantly improved their scores from the pre-test to post-test on the multiple-choice, open-ended, and interview items. Moreover, ANCOVA results show that students in the experimental group, who learned simple machines with the design-based unit, performed significantly better on the interview questions. Conclusions: Our analyses revealed that the design-based Design a people mover: Simple machines unit was, if not better, as successful as the inquiry-based FOSS Levers and pulleys unit in terms of students' science content learning.

The study on the nanomachining property and cutting model of single-crystal sapphire by atomic force microscopy.

PubMed

Huang, Jen-Ching; Weng, Yung-Jin

2014-01-01

This study focused on the nanomachining property and cutting model of single-crystal sapphire during nanomachining. The coated diamond probe is used to as a tool, and the atomic force microscopy (AFM) is as an experimental platform for nanomachining. To understand the effect of normal force on single-crystal sapphire machining, this study tested nano-line machining and nano-rectangular pattern machining at different normal force. In nano-line machining test, the experimental results showed that the normal force increased, the groove depth from nano-line machining also increased. And the trend is logarithmic type. In nano-rectangular pattern machining test, it is found when the normal force increases, the groove depth also increased, but rather the accumulation of small chips. This paper combined the blew by air blower, the cleaning by ultrasonic cleaning machine and using contact mode probe to scan the surface topology after nanomaching, and proposed the "criterion of nanomachining cutting model," in order to determine the cutting model of single-crystal sapphire in the nanomachining is ductile regime cutting model or brittle regime cutting model. After analysis, the single-crystal sapphire substrate is processed in small normal force during nano-linear machining; its cutting modes are ductile regime cutting model. In the nano-rectangular pattern machining, due to the impact of machined zones overlap, the cutting mode is converted into a brittle regime cutting model. © 2014 Wiley Periodicals, Inc.

Certification of highly complex safety-related systems.

PubMed

Reinert, D; Schaefer, M

1999-01-01

The BIA has now 15 years of experience with the certification of complex electronic systems for safety-related applications in the machinery sector. Using the example of machining centres this presentation will show the systematic procedure for verifying and validating control systems using Application Specific Integrated Circuits (ASICs) and microcomputers for safety functions. One section will describe the control structure of machining centres with control systems using "integrated safety." A diverse redundant architecture combined with crossmonitoring and forced dynamization is explained. In the main section the steps of the systematic certification procedure are explained showing some results of the certification of drilling machines. Specification reviews, design reviews with test case specification, statistical analysis, and walk-throughs are the analytical measures in the testing process. Systematic tests based on the test case specification, Electro Magnetic Interference (EMI), and environmental testing, and site acceptance tests on the machines are the testing measures for validation. A complex software driven system is always undergoing modification. Most of the changes are not safety-relevant but this has to be proven. A systematic procedure for certifying software modifications is presented in the last section of the paper.

Testing and Validating Machine Learning Classifiers by Metamorphic Testing☆

PubMed Central

Xie, Xiaoyuan; Ho, Joshua W. K.; Murphy, Christian; Kaiser, Gail; Xu, Baowen; Chen, Tsong Yueh

2011-01-01

Machine Learning algorithms have provided core functionality to many application domains - such as bioinformatics, computational linguistics, etc. However, it is difficult to detect faults in such applications because often there is no “test oracle” to verify the correctness of the computed outputs. To help address the software quality, in this paper we present a technique for testing the implementations of machine learning classification algorithms which support such applications. Our approach is based on the technique “metamorphic testing”, which has been shown to be effective to alleviate the oracle problem. Also presented include a case study on a real-world machine learning application framework, and a discussion of how programmers implementing machine learning algorithms can avoid the common pitfalls discovered in our study. We also conduct mutation analysis and cross-validation, which reveal that our method has high effectiveness in killing mutants, and that observing expected cross-validation result alone is not sufficiently effective to detect faults in a supervised classification program. The effectiveness of metamorphic testing is further confirmed by the detection of real faults in a popular open-source classification program. PMID:21532969

Differences in liver stiffness values obtained with new ultrasound elastography machines and Fibroscan: A comparative study.

PubMed

Piscaglia, Fabio; Salvatore, Veronica; Mulazzani, Lorenzo; Cantisani, Vito; Colecchia, Antonio; Di Donato, Roberto; Felicani, Cristina; Ferrarini, Alessia; Gamal, Nesrine; Grasso, Valentina; Marasco, Giovanni; Mazzotta, Elena; Ravaioli, Federico; Ruggieri, Giacomo; Serio, Ilaria; Sitouok Nkamgho, Joules Fabrice; Serra, Carla; Festi, Davide; Schiavone, Cosima; Bolondi, Luigi

2017-07-01

Whether Fibroscan thresholds can be immediately adopted for none, some or all other shear wave elastography techniques has not been tested. The aim of the present study was to test the concordance of the findings obtained from 7 of the most recent ultrasound elastography machines with respect to Fibroscan. Sixteen hepatitis C virus-related patients with fibrosis ≥2 and having reliable results at Fibroscan were investigated in two intercostal spaces using 7 different elastography machines. Coefficients of both precision (an index of data dispersion) and accuracy (an index of bias correction factors expressing different magnitudes of changes in comparison to the reference) were calculated. Median stiffness values differed among the different machines as did coefficients of both precision (range 0.54-0.72) and accuracy (range 0.28-0.87). When the average of the measurements of two intercostal spaces was considered, coefficients of precision significantly increased with all machines (range 0.72-0.90) whereas of accuracy improved more scatteredly and by a smaller degree (range 0.40-0.99). The present results showed only moderate concordance of the majority of elastography machines with the Fibroscan results, preventing the possibility of the immediate universal adoption of Fibroscan thresholds for defining liver fibrosis staging for all new machines. Copyright © 2017 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Machining process influence on the chip form and surface roughness by neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Anicic, Obrad; Jović, Srđan; Aksić, Danilo; Skulić, Aleksandar; Nedić, Bogdan

2017-04-01

The main aim of the study was to analyze the influence of six machining parameters on the chip shape formation and surface roughness as well during turning of Steel 30CrNiMo8. Three components of cutting forces were used as inputs together with cutting speed, feed rate, and depth of cut. It is crucial for the engineers to use optimal machining parameters to get the best results or to high control of the machining process. Therefore, there is need to find the machining parameters for the optimal procedure of the machining process. Adaptive neuro-fuzzy inference system (ANFIS) was used to estimate the inputs influence on the chip shape formation and surface roughness. According to the results, the cutting force in direction of the depth of cut has the highest influence on the chip form. The testing error for the cutting force in direction of the depth of cut has testing error 0.2562. This cutting force determines the depth of cut. According to the results, the depth of cut has the highest influence on the surface roughness. Also the depth of cut has the highest influence on the surface roughness. The testing error for the cutting force in direction of the depth of cut has testing error 5.2753. Generally the depth of cut and the cutting force which provides the depth of cut are the most dominant factors for chip forms and surface roughness. Any small changes in depth of cut or in cutting force which provide the depth of cut could drastically affect the chip form or surface roughness of the working material.

Effect of focusing flow on stationary spot machining properties in elastic emission machining

PubMed Central

2013-01-01

Ultraprecise optical elements are applied in advanced optical apparatus. Elastic emission machining (EEM) is one of the ultraprecision machining methods used to fabricate shapes with 0.1-nm accuracy. In this study, we proposed and experimentally tested the control of the shape of a stationary spot profile by introducing a focusing-flow state between the nozzle outlet and the workpiece surface in EEM. The simulation results indicate that the focusing-flow nozzle sharpens the distribution of the velocity on the workpiece surface. The results of machining experiments verified those of the simulation. The obtained stationary spot conditions will be useful for surface processing with a high spatial resolution. PMID:23680043

Machine compliance in compression tests

NASA Astrophysics Data System (ADS)

Sousa, Pedro; Ivens, Jan; Lomov, Stepan V.

2018-05-01

The compression behavior of a material cannot be accurately determined if the machine compliance is not accounted prior to the measurements. This work discusses the machine compliance during a compressibility test with fiberglass fabrics. The thickness variation was measured during loading and unloading cycles with a relaxation stage of 30 minutes between them. The measurements were performed using an indirect technique based on the comparison between the displacement at a free compression cycle and the displacement with a sample. Relating to the free test, it has been noticed the nonexistence of machine relaxation during relaxation stage. Considering relaxation or not, the characteristic curves for a free compression cycle can be overlapped precisely in the majority of the points. For the compression test with sample, it was noticed a non-physical decrease of about 30 µm during the relaxation stage, what can be explained by the greater fabric relaxation in relation to the machine relaxation. Beyond the technique normally used, another technique was used which allows a constant thickness during relaxation. Within this second method, machine displacement with sample is simply subtracted to the machine displacement without sample being imposed as constant. If imposed as a constant it will remain constant during relaxation stage and it will suddenly decrease after relaxation. If constantly calculated it will decrease gradually during relaxation stage. Independently of the technique used the final result will remain unchanged. The uncertainty introduced by this imprecision is about ±15 µm.

Extracting laboratory test information from biomedical text

PubMed Central

Kang, Yanna Shen; Kayaalp, Mehmet

2013-01-01

Background: No previous study reported the efficacy of current natural language processing (NLP) methods for extracting laboratory test information from narrative documents. This study investigates the pathology informatics question of how accurately such information can be extracted from text with the current tools and techniques, especially machine learning and symbolic NLP methods. The study data came from a text corpus maintained by the U.S. Food and Drug Administration, containing a rich set of information on laboratory tests and test devices. Methods: The authors developed a symbolic information extraction (SIE) system to extract device and test specific information about four types of laboratory test entities: Specimens, analytes, units of measures and detection limits. They compared the performance of SIE and three prominent machine learning based NLP systems, LingPipe, GATE and BANNER, each implementing a distinct supervised machine learning method, hidden Markov models, support vector machines and conditional random fields, respectively. Results: Machine learning systems recognized laboratory test entities with moderately high recall, but low precision rates. Their recall rates were relatively higher when the number of distinct entity values (e.g., the spectrum of specimens) was very limited or when lexical morphology of the entity was distinctive (as in units of measures), yet SIE outperformed them with statistically significant margins on extracting specimen, analyte and detection limit information in both precision and F-measure. Its high recall performance was statistically significant on analyte information extraction. Conclusions: Despite its shortcomings against machine learning methods, a well-tailored symbolic system may better discern relevancy among a pile of information of the same type and may outperform a machine learning system by tapping into lexically non-local contextual information such as the document structure. PMID:24083058

Machining of Aircraft Titanium with Abrasive-Waterjets for Fatigue Critical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, H. T.; Hovanski, Yuri; Dahl, Michael E.

2012-02-01

Laboratory tests were conducted to determine the fatigue performance of abrasive-waterjet- (AWJ-) machined aircraft titanium. Dog-bone specimens machined with AWJs were prepared and tested with and without sanding and dry-grit blasting with Al2O3 as secondary processes. The secondary processes were applied to remove the visual appearance of AWJ-generated striations and to clean up the garnet embedment. The fatigue performance of AWJ-machined specimens was compared with baseline specimens machined with CNC milling. Fatigue test results of the titanium specimens not only confirmed our previous findings in aluminum dog-bone specimens but in comparison also further enhanced the fatigue performance of the titanium.more » In addition, titanium is known to be difficult to cut, particularly for thick parts, however AWJs cut the material 34% faster han stainless steel. AWJ cutting and dry-grit blasting are shown to be a preferred ombination for processing aircraft titanium that is fatigue critical.« less

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

The cleaning and disinfection by heat of bedpans in automatic and semi-automatic machines.

PubMed Central

Mostafa, A. B.; Chackett, K. F.

1976-01-01

This work is concerned with the cleaning and disinfection by heat of stainless-steel and polypropylene bedpans, which had been soiled with either a biological contaminant, human serum albumin (HSA) labelled with technetium-99m 99m(Tc), or a bacteriological contaminant, streptococcus faecalis mixed with Tc-labelled HSA. Results of cleaning and disinfection achieved with a Test Machine and those achieved by procedures adopted in eight different wards of a general hospital are reported. Bedpan washers installed in wards were found to be less efficient than the Test Machine, at least partly because of inadequate maintenance. Stainless-steel and polypropylene bedpans gave essentially the same results. PMID:6591

A Novel Application of Machine Learning Methods to Model Microcontroller Upset Due to Intentional Electromagnetic Interference

NASA Astrophysics Data System (ADS)

Bilalic, Rusmir

A novel application of support vector machines (SVMs), artificial neural networks (ANNs), and Gaussian processes (GPs) for machine learning (GPML) to model microcontroller unit (MCU) upset due to intentional electromagnetic interference (IEMI) is presented. In this approach, an MCU performs a counting operation (0-7) while electromagnetic interference in the form of a radio frequency (RF) pulse is direct-injected into the MCU clock line. Injection times with respect to the clock signal are the clock low, clock rising edge, clock high, and the clock falling edge periods in the clock window during which the MCU is performing initialization and executing the counting procedure. The intent is to cause disruption in the counting operation and model the probability of effect (PoE) using machine learning tools. Five experiments were executed as part of this research, each of which contained a set of 38,300 training points and 38,300 test points, for a total of 383,000 total points with the following experiment variables: injection times with respect to the clock signal, injected RF power, injected RF pulse width, and injected RF frequency. For the 191,500 training points, the average training error was 12.47%, while for the 191,500 test points the average test error was 14.85%, meaning that on average, the machine was able to predict MCU upset with an 85.15% accuracy. Leaving out the results for the worst-performing model (SVM with a linear kernel), the test prediction accuracy for the remaining machines is almost 89%. All three machine learning methods (ANNs, SVMs, and GPML) showed excellent and consistent results in their ability to model and predict the PoE on an MCU due to IEMI. The GP approach performed best during training with a 7.43% average training error, while the ANN technique was most accurate during the test with a 10.80% error.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooper, R. C.; Bruno, Giovanni; Onel, Yener

Microstructural changes in porous cordierite caused by machining were characterized using microtensile testing, X-ray computed tomography and scanning electron microscopy. Young s moduli and Poisson s ratios were determined on ~215-380 um thick machined samples by combining digital image correlation and microtensile loading. The results provide evidence for an increase in microcrack density due to machining of the thin samples extracted from diesel particulate filter honeycombs.

Theoretical and experimental research on machine tool servo system for ultra-precision position compensation on CNC lathe

NASA Astrophysics Data System (ADS)

Ma, Zhichao; Hu, Leilei; Zhao, Hongwei; Wu, Boda; Peng, Zhenxing; Zhou, Xiaoqin; Zhang, Hongguo; Zhu, Shuai; Xing, Lifeng; Hu, Huang

2010-08-01

The theories and techniques for improving machining accuracy via position control of diamond tool's tip and raising resolution of cutting depth on precise CNC lathes have been extremely focused on. A new piezo-driven ultra-precision machine tool servo system is designed and tested to improve manufacturing accuracy of workpiece. The mathematical model of machine tool servo system is established and the finite element analysis is carried out on parallel plate flexure hinges. The output position of diamond tool's tip driven by the machine tool servo system is tested via a contact capacitive displacement sensor. Proportional, integral, derivative (PID) feedback is also implemented to accommodate and compensate dynamical change owing cutting forces as well as the inherent non-linearity factors of the piezoelectric stack during cutting process. By closed loop feedback controlling strategy, the tracking error is limited to 0.8 μm. Experimental results have shown the proposed machine tool servo system could provide a tool positioning resolution of 12 nm, which is much accurate than the inherent CNC resolution magnitude. The stepped shaft of aluminum specimen with a step increment of cutting depth of 1 μm is tested, and the obtained contour illustrates the displacement command output from controller is accurately and real-time reflected on the machined part.

Tribological performance of Zinc soft metal coatings in solid lubrication

NASA Astrophysics Data System (ADS)

Regalla, Srinivasa Prakash; Krishnan Anirudh, V.; Reddy Narala, Suresh Kumar

2018-04-01

Solid lubrication by soft coatings is an important technique for superior tribological performance in machine contacts involving high pressures. Coating with soft materials ensures that the subsurface machine component wear decreases, ensuring longer life. Several soft metal coatings have been studied but zinc coatings have not been studied much. This paper essentially deals with the soft coating by zinc through electroplating on hard surfaces, which are subsequently tested in sliding experiments for tribological performance. The hardness and film thickness values have been found out, the coefficient of friction of the zinc coating has been tested using a pin on disc wear testing machine and the results of the same have been presented.

Dynamic analysis and vibration testing of CFRP drive-line system used in heavy-duty machine tool

NASA Astrophysics Data System (ADS)

Yang, Mo; Gui, Lin; Hu, Yefa; Ding, Guoping; Song, Chunsheng

2018-03-01

Low critical rotary speed and large vibration in the metal drive-line system of heavy-duty machine tool affect the machining precision seriously. Replacing metal drive-line with the CFRP drive-line can effectively solve this problem. Based on the composite laminated theory and the transfer matrix method (TMM), this paper puts forward a modified TMM to analyze dynamic characteristics of CFRP drive-line system. With this modified TMM, the CFRP drive-line of a heavy vertical miller is analyzed. And the finite element modal analysis model of the shafting is established. The results of the modified TMM and finite element analysis (FEA) show that the modified TMM can effectively predict the critical rotary speed of CFRP drive-line. And the critical rotary speed of CFRP drive-line is 20% higher than that of the original metal drive-line. Then, the vibration of the CFRP and the metal drive-line were tested. The test results show that application of the CFRP drive shaft in the drive-line can effectively reduce the vibration of the heavy-duty machine tool.

Testing Machine for Biaxial Loading

NASA Technical Reports Server (NTRS)

Demonet, R. J.; Reeves, R. D.

1985-01-01

Standard tensile-testing machine applies bending and tension simultaneously. Biaxial-loading test machine created by adding two test fixtures to commercial tensile-testing machine. Bending moment applied by substrate-deformation fixture comprising yoke and anvil block. Pneumatic tension-load fixture pulls up on bracket attached to top surface of specimen. Tension and deflection measured with transducers. Modified test apparatus originally developed to load-test Space Shuttle surface-insulation tiles and particuarly important for composite structures.

Lawrence Livermore National Laboratory ULTRA-350 Test Bed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hopkins, D J; Wulff, T A; Carlisle, K

2001-04-10

LLNL has many in-house designed high precision machine tools. Some of these tools include the Large Optics Diamond Turning Machine (LODTM) [1], Diamond Turning Machine No.3 (DTM-3) and two Precision Engineering Research Lathes (PERL-1 and PERL-11). These machines have accuracy in the sub-micron range and in most cases position resolution in the couple of nanometers range. All of these machines are built with similar underlying technologies. The machines use capstan drive technology, laser interferometer position feedback, tachometer velocity feedback, permanent magnet (PM) brush motors and analog velocity and position loop servo compensation [2]. The machine controller does not perform anymore » servo compensation it simply computes the differences between the commanded position and the actual position (the following error) and sends this to a D/A for the analog servo position loop. LLNL is designing a new high precision diamond turning machine. The machine is called the ULTRA 350 [3]. In contrast to many of the proven technologies discussed above, the plan for the new machine is to use brushless linear motors, high precision linear scales, machine controller motor commutation and digital servo compensation for the velocity and position loops. Although none of these technologies are new and have been in use in industry, applications of these technologies to high precision diamond turning is limited. To minimize the risks of these technologies in the new machine design, LLNL has established a test bed to evaluate these technologies for application in high precision diamond turning. The test bed is primarily composed of commercially available components. This includes the slide with opposed hydrostatic bearings, the oil system, the brushless PM linear motor, the two-phase input three-phase output linear motor amplifier and the system controller. The linear scales are not yet commercially available but use a common electronic output format. As of this writing, the final verdict for the use of these technologies is still out but the first part of the work has been completed with promising results. The goal of this part of the work was to close a servo position loop around a slide incorporating these technologies and to measure the performance. This paper discusses the tests that were setup for system evaluation and the results of the measurements made. Some very promising results include; slide positioning to nanometer level and slow speed slide direction reversal at less than 100nm/min with no observed discontinuities. This is very important for machine contouring in diamond turning. As a point of reference, at 100 nm/min it would take the slide almost 7 years to complete the full designed travel of 350 mm. This speed has been demonstrated without the use of a velocity sensor. The velocity is derived from the position sensor. With what has been learned on the test bed, the paper finishes with a brief comparison of the old and new technologies. The emphasis of this comparison will be on the servo performance as illustrated with bode plot diagrams.« less

Lawrence Livermore National Laboratory ULTRA-350 Test Bed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hopkins, D J; Wulff, T A; Carlisle, K

2001-04-10

LLNL has many in-house designed high precision machine tools. Some of these tools include the Large Optics Diamond Turning Machine (LODTM) [1], Diamond Turning Machine No.3 (DTM-3) and two Precision Engineering Research Lathes (PERL-I and PERL-II). These machines have accuracy in the sub-micron range and in most cases position resolution in the couple of nanometers range. All of these machines are built with similar underlying technologies. The machines use capstan drive technology, laser interferometer position feedback, tachometer velocity feedback, permanent magnet (PM) brush motors and analog velocity and position loop servo compensation [2]. The machine controller does not perform anymore » servo compensation it simply computes the differences between the commanded position and the actual position (the following error) and sends this to a D/A for the analog servo position loop. LLNL is designing a new high precision diamond turning machine. The machine is called the ULTRA 350 [3]. In contrast to many of the proven technologies discussed above, the plan for the new machine is to use brushless linear motors, high precision linear scales, machine controller motor commutation and digital servo compensation for the velocity and position loops. Although none of these technologies are new and have been in use in industry, applications of these technologies to high precision diamond turning is limited. To minimize the risks of these technologies in the new machine design, LLNL has established a test bed to evaluate these technologies for application in high precision diamond turning. The test bed is primarily composed of commercially available components. This includes the slide with opposed hydrostatic bearings, the oil system, the brushless PM linear motor, the two-phase input three-phase output linear motor amplifier and the system controller. The linear scales are not yet commercially available but use a common electronic output format. As of this writing, the final verdict for the use of these technologies is still out but the first part of the work has been completed with promising results. The goal of this part of the work was to close a servo position loop around a slide incorporating these technologies and to measure the performance. This paper discusses the tests that were setup for system evaluation and the results of the measurements made. Some very promising results include; slide positioning to nanometer level and slow speed slide direction reversal at less than 100nm/min with no observed discontinuities. This is very important for machine contouring in diamond turning. As a point of reference, at 100 nm/min it would take the slide almost 7 years to complete the full designed travel of 350 mm. This speed has been demonstrated without the use of a velocity sensor. The velocity is derived from the position sensor. With what has been learned on the test bed, the paper finishes with a brief comparison of the old and new technologies. The emphasis of this comparison will be on the servo performance as illustrated with bode plot diagrams.« less

Bridging Realty to Virtual Reality: Investigating Gender Effect and Student Engagement on Learning through Video Game Play in an Elementary School Classroom

ERIC Educational Resources Information Center

Annetta, Leonard; Mangrum, Jennifer; Holmes, Shawn; Collazo, Kimberly; Cheng, Meng-Tzu

2009-01-01

The purpose of this study was to examine students' learning of simple machines, a fifth-grade (ages 10-11) forces and motion unit, and student engagement using a teacher-created Multiplayer Educational Gaming Application. This mixed-method study collected pre-test/post-test results to determine student knowledge about simple machines. A survey…

Development of a New Utm (universal Testing Machine) System for the Nano/micro In-Process Measurement

NASA Astrophysics Data System (ADS)

Kweon, Hyunkyu; Choi, Sungdae; Kim, Youngsik; Nam, Kiho

Micro UTM (Universal Testing Machines) are becoming increasingly popular for testing the mechanical properties of MEMS materials, metal thin films, and micro-molecule materials1-2. And, new miniature testing machines that can perform in-process measurement in SEM, TEM, and SPM are also needed. In this paper, a new micro UTM with a precision positioning system that can be fine positioning stage. Coarse positioning is implemented by step motor. The size, load output and used in SEM, TEM, and SPM have been proposed. Bimorph type PZT precision actuator is used in displacement output of bimorph type UTM are 109×64×22(mm), about 35g, and 0.4 mm, respectively. And the displacement output is controlled in the block digital form. The results of the analysis and basic properties of positioning system and the UTM system are presented. In addition, the experiment results of in-process measurement during tensile load in SEM and AFM are showed.

Development of a small specimen test machine to evaluate irradiation embrittlement of fusion reactor materials

NASA Astrophysics Data System (ADS)

Ishii, T.; Ohmi, M.; Saito, J.; Hoshiya, T.; Ooka, N.; Jitsukawa, S.; Eto, M.

2000-12-01

Small specimen test techniques (SSTT) are essential to use an accelerator-driven deuterium-lithium stripping reaction neutron source for the study of fusion reactor materials because of the limitation of the available irradiation volume. A remote-controlled small punch (SP) test machine was developed at the hot laboratory of the Japan Materials Testing Reactor (JMTR) in the Japan Atomic Energy Research Institute (JAERI). This report describes the SP test method and machine for use in a hot cell, and test results on irradiated ferritic steels. The specimen was either a coupon 10×10×0.25 mm 3 or a TEM disk 3 mm in diameter by 0.25 mm in thickness. Tests can be performed at temperatures ranging from 93 to 1123 K in a vacuum or in an inert gas environment. The ductile to brittle transition temperature of the irradiated ferritic steel as determined by the SP test is also evaluated.

Felling and bunching small timber on steep slopes.

Treesearch

Rodger A. Arola; Edwin S. Miyata; John A. Sturos; Helmuth M. Steinhilb

1981-01-01

Discusses the results of a field test of the unique Menzi Muck machine for felling and bunching small trees on steep slopes. Includes the analysis of a detailed time study to determine the productivity, costs, and economic feasibility of this unusual machine.

Predicting hydrofacies and hydraulic conductivity from direct-push data using a data-driven relevance vector machine approach: Motivations, algorithms, and application

NASA Astrophysics Data System (ADS)

Paradis, Daniel; Lefebvre, René; Gloaguen, Erwan; Rivera, Alfonso

2015-01-01

The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a nonparametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12 km2 subwatershed, where relations between K and multiparameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training data set representative of the study area that includes K data from slug tests and CPT/SMR data up-scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross validation with data withheld from the training data set and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM-based learning machine proved to be powerful and efficient for the characterization of high-resolution K heterogeneity for unconsolidated aquifers.

Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

PubMed

Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

2016-01-01

The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and incomplete genome assembly confounded the rules-based algorithm, resulting in predictions based on gene family, rather than on knowledge of the specific variant found. Low-frequency resistance caused errors in the machine-learning algorithm because those genes were not seen or seen infrequently in the test set. We also identified an example of variability in the phenotype-based results that led to disagreement with both genotype-based methods. Genotype-based antimicrobial susceptibility testing shows great promise as a diagnostic tool, and we outline specific research goals to further refine this methodology.

Fracture Tests of Etched Components Using a Focused Ion Beam Machine

NASA Technical Reports Server (NTRS)

Kuhn, Jonathan, L.; Fettig, Rainer K.; Moseley, S. Harvey; Kutyrev, Alexander S.; Orloff, Jon; Powers, Edward I. (Technical Monitor)

2000-01-01

Many optical MEMS device designs involve large arrays of thin (0.5 to 1 micron components subjected to high stresses due to cyclic loading. These devices are fabricated from a variety of materials, and the properties strongly depend on size and processing. Our objective is to develop standard and convenient test methods that can be used to measure the properties of large numbers of witness samples, for every device we build. In this work we explore a variety of fracture test configurations for 0.5 micron thick silicon nitride membranes machined using the Reactive Ion Etching (RIE) process. Testing was completed using an FEI 620 dual focused ion beam milling machine. Static loads were applied using a probe. and dynamic loads were applied through a piezo-electric stack mounted at the base of the probe. Results from the tests are presented and compared, and application for predicting fracture probability of large arrays of devices are considered.

Hybrid test on building structures using electrodynamic fatigue test machine

NASA Astrophysics Data System (ADS)

Xu, Zhao-Dong; Wang, Kai-Yang; Guo, Ying-Qing; Wu, Min-Dong; Xu, Meng

2017-01-01

Hybrid simulation is an advanced structural dynamic experimental method that combines experimental physical models with analytical numerical models. It has increasingly been recognised as a powerful methodology to evaluate structural nonlinear components and systems under realistic operating conditions. One of the barriers for this advanced testing is the lack of flexible software for hybrid simulation using heterogeneous experimental equipment. In this study, an electrodynamic fatigue test machine is made and a MATLAB program is developed for hybrid simulation. Compared with the servo-hydraulic system, electrodynamic fatigue test machine has the advantages of small volume, easy operation and fast response. A hybrid simulation is conducted to verify the flexibility and capability of the whole system whose experimental substructure is one spring brace and numerical substructure is a two-storey steel frame structure. Experimental and numerical results show the feasibility and applicability of the whole system.

Study on magnetic force of electromagnetic levitation circular knitting machine

NASA Astrophysics Data System (ADS)

Wu, X. G.; Zhang, C.; Xu, X. S.; Zhang, J. G.; Yan, N.; Zhang, G. Z.

2018-06-01

The structure of the driving coil and the electromagnetic force of the test prototype of electromagnetic-levitation (EL) circular knitting machine are studied. In this paper, the driving coil’s structure and working principle of the EL circular knitting machine are firstly introduced, then the mathematical modelling analysis of the driving electromagnetic force is carried out, and through the Ansoft Maxwell finite element simulation software the coil’s magnetic induction intensity and the needle’s electromagnetic force is simulated, finally an experimental platform is built to measure the coil’s magnetic induction intensity and the needle’s electromagnetic force. The results show that the theoretical analysis, the simulation analysis and the results of the test are very close, which proves the correctness of the proposed model.

Electronic vending machines for dispensing rapid HIV self-testing kits: a case study.

PubMed

Young, Sean D; Klausner, Jeffrey; Fynn, Risa; Bolan, Robert

2014-02-01

This short report evaluates the feasibility of using electronic vending machines for dispensing oral, fluid, rapid HIV self-testing kits in Los Angeles County. Feasibility criteria that needed to be addressed were defined as: (1) ability to find a manufacturer who would allow dispensing of HIV testing kits and could fit them to the dimensions of a vending machine, (2) ability to identify and address potential initial obstacles, trade-offs in choosing a machine location, and (3) ability to gain community approval for implementing this approach in a community setting. To address these issues, we contracted a vending machine company who could supply a customized, Internet-enabled machine that could dispense HIV kits and partnered with a local health center available to host the machine onsite and provide counseling to participants, if needed. Vending machines appear to be feasible technologies that can be used to distribute HIV testing kits.

Electronic vending machines for dispensing rapid HIV self-testing kits: A case study

PubMed Central

Young, Sean D.; Klausner, Jeffrey; Fynn, Risa; Bolan, Robert

2014-01-01

This short report evaluates the feasibility of using electronic vending machines for dispensing oral, fluid, rapid HIV-self testing kits in Los Angeles County. Feasibility criteria that needed to be addressed were defined as: 1) ability to find a manufacturer who would allow dispensing of HIV testing kits and could fit them to the dimensions of a vending machine, 2) ability to identify and address potential initial obstacles, trade-offs in choosing a machine location, and 3) ability to gain community approval for implementing this approach in a community setting. To address these issues, we contracted a vending machine company who could supply a customized, Internet-enabled machine that could dispense HIV kits and partnered with a local health center available to host the machine onsite and provide counseling to participants, if needed. Vending machines appear to be feasible technologies that can be used to distribute HIV testing kits. PMID:23777528

TU-FG-201-05: Varian MPC as a Statistical Process Control Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carver, A; Rowbottom, C

Purpose: Quality assurance in radiotherapy requires the measurement of various machine parameters to ensure they remain within permitted values over time. In Truebeam release 2.0 the Machine Performance Check (MPC) was released allowing beam output and machine axis movements to be assessed in a single test. We aim to evaluate the Varian Machine Performance Check (MPC) as a tool for Statistical Process Control (SPC). Methods: Varian’s MPC tool was used on three Truebeam and one EDGE linac for a period of approximately one year. MPC was commissioned against independent systems. After this period the data were reviewed to determine whethermore » or not the MPC was useful as a process control tool. Analyses on individual tests were analysed using Shewhart control plots, using Matlab for analysis. Principal component analysis was used to determine if a multivariate model was of any benefit in analysing the data. Results: Control charts were found to be useful to detect beam output changes, worn T-nuts and jaw calibration issues. Upper and lower control limits were defined at the 95% level. Multivariate SPC was performed using Principal Component Analysis. We found little evidence of clustering beyond that which might be naively expected such as beam uniformity and beam output. Whilst this makes multivariate analysis of little use it suggests that each test is giving independent information. Conclusion: The variety of independent parameters tested in MPC makes it a sensitive tool for routine machine QA. We have determined that using control charts in our QA programme would rapidly detect changes in machine performance. The use of control charts allows large quantities of tests to be performed on all linacs without visual inspection of all results. The use of control limits alerts users when data are inconsistent with previous measurements before they become out of specification. A. Carver has received a speaker’s honorarium from Varian.« less

ODC-Free Solvent Implementation for Phenolics Cleaning

NASA Technical Reports Server (NTRS)

Wurth, Laura; Biegert, Lydia; Lamont, DT; McCool, Alex (Technical Monitor)

2001-01-01

During phenolic liner manufacture, resin-impregnated (pre-preg) bias tape of silica, glass, or carbon cloth is tape-wrapped, cured, machined, and then wiped with 1,1,1 tri-chloroethane (TCA) to remove contaminants that may have been introduced during machining and handling. Following the TCA wipe, the machined surface is given a resin wet-coat and over-wrapped with more prepreg and cured. A TCA replacement solvent for these wiping operations must effectively remove both surface contaminants, and sub-surface oils and greases while not compromising the integrity of this interface. Selection of a TCA replacement solvent for phenolic over-wrap interface cleaning began with sub-scale compatibility tests with cured phenolics. Additional compatibility tests included assessment of solvent retention in machined phenolic surfaces. Results from these tests showed that, while the candidate solvent did not degrade the cured phenolics, it was retained in higher concentrations than TCA in phenolic surfaces. This effect was most pronounced with glass and silica cloth phenolics with steep ply angles relative to the wiped surfaces.

Manufacturing Methods for High Speed Machining of Aluminum

DTIC Science & Technology

1978-02-01

Tests 53 4.4.3 Intergrmnular Corrosion Tests. ........... 53 4.4.4 Cost Analysis . .. ............... . .. .... 60 4.5 Conclusions...Corporat~ion and Others to equuip an existing Uwidstvahd, five-axes, Modal as-i, oidail with a 20,000 rVIL 20 hOW~pse spindle, Based anresults obtained...economic analysis for high-speed machining wan also conducted by Metout, and the results are given in Section 11.0. Xn Section 12.0, conclusions and

Impact of machining on the flexural fatigue strength of glass and polycrystalline CAD/CAM ceramics.

PubMed

Fraga, Sara; Amaral, Marina; Bottino, Marco Antônio; Valandro, Luiz Felipe; Kleverlaan, Cornelis Johannes; May, Liliana Gressler

2017-11-01

To assess the effect of machining on the flexural fatigue strength and on the surface roughness of different computer-aided design, computer-aided manufacturing (CAD/CAM) ceramics by comparing machined and polished after machining specimens. Disc-shaped specimens of yttria-stabilized polycrystalline tetragonal zirconia (Y-TZP), leucite-, and lithium disilicate-based glass ceramics were prepared by CAD/CAM machining, and divided into two groups: machining (M) and machining followed by polishing (MP). The surface roughness was measured and the flexural fatigue strength was evaluated by the step-test method (n=20). The initial load and the load increment for each ceramic material were based on a monotonic test (n=5). A maximum of 10,000 cycles was applied in each load step, at 1.4Hz. Weibull probability statistics was used for the analysis of the flexural fatigue strength, and Mann-Whitney test (α=5%) to compare roughness between the M and MP conditions. Machining resulted in lower values of characteristic flexural fatigue strength than machining followed by polishing. The greatest reduction in flexural fatigue strength from MP to M was observed for Y-TZP (40%; M=536.48MPa; MP=894.50MPa), followed by lithium disilicate (33%; M=187.71MPa; MP=278.93MPa) and leucite (29%; M=72.61MPa; MP=102.55MPa). Significantly higher values of roughness (Ra) were observed for M compared to MP (leucite: M=1.59μm and MP=0.08μm; lithium disilicate: M=1.84μm and MP=0.13μm; Y-TZP: M=1.79μm and MP=0.18μm). Machining negatively affected the flexural fatigue strength of CAD/CAM ceramics, indicating that machining of partially or fully sintered ceramics is deleterious to fatigue strength. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Method and apparatus for tensile testing of metal foil

NASA Technical Reports Server (NTRS)

Wade, O. W. (Inventor)

1976-01-01

A method for obtaining accurate and reproducible results in the tensile testing of metal foils in tensile testing machines is described. Before the test specimen are placed in the machine, foil side edges are worked until they are parallel and flaw free. The specimen are also aligned between and secured to grip end members. An aligning apparatus employed in the method is comprised of an alignment box with a longitudinal bottom wall and two upright side walls, first and second removable grip end members at each end of the box, and a means for securing the grip end members within the box.

Measurement of W + bb and a search for MSSM Higgs bosons with the CMS detector at the LHC

NASA Astrophysics Data System (ADS)

O'Connor, Alexander Pinpin

Tooling used to cure composite laminates in the aerospace and automotive industries must provide a dimensionally stable geometry throughout the thermal cycle applied during the part curing process. This requires that the Coefficient of Thermal Expansion (CTE) of the tooling materials match that of the composite being cured. The traditional tooling material for production applications is a nickel alloy. Poor machinability and high material costs increase the expense of metallic tooling made from nickel alloys such as 'Invar 36' or 'Invar 42'. Currently, metallic tooling is unable to meet the needs of applications requiring rapid affordable tooling solutions. In applications where the tooling is not required to have the durability provided by metals, such as for small area repair, an opportunity exists for non-metallic tooling materials like graphite, carbon foams, composites, or ceramics and machinable glasses. Nevertheless, efficient machining of brittle, non-metallic materials is challenging due to low ductility, porosity, and high hardness. The machining of a layup tool comprises a large portion of the final cost. Achieving maximum process economy requires optimization of the machining process in the given tooling material. Therefore, machinability of the tooling material is a critical aspect of the overall cost of the tool. In this work, three commercially available, brittle/porous, non-metallic candidate tooling materials were selected, namely: (AAC) Autoclaved Aerated Concrete, CB1100 ceramic block and Cfoam carbon foam. Machining tests were conducted in order to evaluate the machinability of these materials using end milling. Chip formation, cutting forces, cutting tool wear, machining induced damage, surface quality and surface integrity were investigated using High Speed Steel (HSS), carbide, diamond abrasive and Polycrystalline Diamond (PCD) cutting tools. Cutting forces were found to be random in magnitude, which was a result of material porosity. The abrasive nature of Cfoam produced rapid tool wear when using HSS and PCD type cutting tools. However, tool wear was not significant in AAC or CB1100 regardless of the type of cutting edge. Machining induced damage was observed in the form of macro-scale chipping and fracture in combination with micro-scale cracking. Transverse rupture test results revealed significant reductions in residual strength and damage tolerance in CB1100. In contrast, AAC and Cfoam showed no correlation between machining induced damage and a reduction in surface integrity. Cutting forces in machining were modeled for all materials. Cutting force regression models were developed based on Design of Experiment and Analysis of Variance. A mechanistic cutting force model was proposed based upon conventional end milling force models and statistical distributions of material porosity. In order to validate the model, predicted cutting forces were compared to experimental results. Predicted cutting forces agreed well with experimental measurements. Furthermore, over the range of cutting conditions tested, the proposed model was shown to have comparable predictive accuracy to empirically produced regression models; greatly reducing the number of cutting tests required to simulate cutting forces. Further, this work demonstrates a key adaptation of metallic cutting force models to brittle porous material; a vital step in the research into the machining of these materials using end milling.

Effect of Ceramic Surface Treatments After Machine Grinding on the Biaxial Flexural Strength of Different CAD/CAM Dental Ceramics

PubMed Central

Bagheri, Hossein; Aghajani, Farzaneh

2015-01-01

Objectives: This study aimed to evaluate the effect of different ceramic surface treatments after machining grinding on the biaxial flexural strength (BFS) of machinable dental ceramics with different crystalline phases. Materials and Methods: Disk-shape specimens (10mm in diameter and 1.3mm in thickness) of machinable ceramic cores (two silica-based and one zirconia-based ceramics) were prepared. Each type of the ceramic surfaces was then randomly treated (n=15) with different treatments as follows: 1) machined finish as control, 2) machined finish and sandblasting with alumina, and 3) machined finish and hydrofluoric acid etching for the leucite and lithium disilicate-based ceramics, and for the zirconia; 1) machined finish and post-sintered as control, 2) machined finish, post-sintered, and sandblasting, and 3) machined finish, post-sintered, and Nd;YAG laser irradiation. The BFS were measured in a universal testing machine. Data based were analyzed by ANOVA and Tukey’s multiple comparisons post-hoc test (α=0.05). Results: The mean BFS of machined finish only surfaces for leucite ceramic was significantly higher than that of sandblasted (P=0.001) and acid etched surfaces (P=0.005). A significantly lower BFS was found after sandblasting for lithium disilicate compared with that of other groups (P<0.05). Sandblasting significantly increased the BFS for the zirconia (P<0.05), but the BFS was significantly decreased after laser irradiation (P<0.05). Conclusions: The BFS of the machinable ceramics was affected by the type of ceramic material and surface treatment method. Sandblasting with alumina was detrimental to the strength of only silica-based ceramics. Nd:YAG laser irradiation may lead to substantial strength degradation of zirconia. PMID:27148372

Laser Induced Damage of Potassium Dihydrogen Phosphate (KDP) Optical Crystal Machined by Water Dissolution Ultra-Precision Polishing Method

PubMed Central

Gao, Hang; Wang, Xu; Guo, Dongming; Liu, Ziyuan

2018-01-01

Laser induced damage threshold (LIDT) is an important optical indicator for nonlinear Potassium Dihydrogen Phosphate (KDP) crystal used in high power laser systems. In this study, KDP optical crystals are initially machined with single point diamond turning (SPDT), followed by water dissolution ultra-precision polishing (WDUP) and then tested with 355 nm nanosecond pulsed-lasers. Power spectral density (PSD) analysis shows that WDUP process eliminates the laser-detrimental spatial frequencies band of micro-waviness on SPDT machined surface and consequently decreases its modulation effect on the laser beams. The laser test results show that LIDT of WDUP machined crystal improves and its stability has a significant increase by 72.1% compared with that of SPDT. Moreover, a subsequent ultrasonic assisted solvent cleaning process is suggested to have a positive effect on the laser performance of machined KDP crystal. Damage crater investigation indicates that the damage morphologies exhibit highly thermal explosion features of melted cores and brittle fractures of periphery material, which can be described with the classic thermal explosion model. The comparison result demonstrates that damage mechanisms for SPDT and WDUP machined crystal are the same and WDUP process reveals the real bulk laser resistance of KDP optical crystal by removing the micro-waviness and subsurface damage on SPDT machined surface. This improvement of WDUP method makes the LIDT more accurate and will be beneficial to the laser performance of KDP crystal. PMID:29534032

Performance testing of a high frequency link converter for Space Station power distribution system

NASA Technical Reports Server (NTRS)

Sul, S. K.; Alan, I.; Lipo, T. A.

1989-01-01

The testing of a brassboard version of a 20-kHz high-frequency ac voltage link prototype converter dynamics for Space Station application is presented. The converter is based on a three-phase six-pulse bridge concept. The testing includes details of the operation of the converter when it is driving an induction machine source/load. By adapting a field orientation controller (FOC) to the converter, four-quadrant operation of the induction machine from the converter has been achieved. Circuit modifications carried out to improve the performance of the converter are described. The performance of two 400-Hz induction machines powered by the converter with simple V/f regulation mode is reported. The testing and performance results for the converter utilizing the FOC, which provides the capability for rapid torque changes, speed reversal, and four-quadrant operation, are reported.

A Two-Layer Least Squares Support Vector Machine Approach to Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Liu, Jingli; Li, Jianping; Xu, Weixuan; Shi, Yong

Least squares support vector machine (LS-SVM) is a revised version of support vector machine (SVM) and has been proved to be a useful tool for pattern recognition. LS-SVM had excellent generalization performance and low computational cost. In this paper, we propose a new method called two-layer least squares support vector machine which combines kernel principle component analysis (KPCA) and linear programming form of least square support vector machine. With this method sparseness and robustness is obtained while solving large dimensional and large scale database. A U.S. commercial credit card database is used to test the efficiency of our method and the result proved to be a satisfactory one.

Machine Shop. Criterion-Referenced Test (CRT) Item Bank.

ERIC Educational Resources Information Center

Davis, Diane, Ed.

This drafting criterion-referenced test item bank is keyed to the machine shop competency profile developed by industry and education professionals in Missouri. The 16 references used for drafting the test items are listed. Test items are arranged under these categories: orientation to machine shop; performing mathematical calculations; performing…

Recent R&D status for 70 MW class superconducting generators in the Super-GM project

NASA Astrophysics Data System (ADS)

Ageta, Takasuke

2000-05-01

Three types of 70 MW class superconducting generators called model machines have been developed to establish basic technologies for a pilot machine. The series of on-site verification tests was completed in June 1999. The world's highest generator output (79 MW), the world's longest continuous operation (1500 hours) and other excellent results were obtained. The model machine was connected to a commercial power grid and fundamental data were collected for future utilization. It is expected that fundamental technologies on design and manufacture required for a 200 MW class pilot machine are established.

Investigation of the influence of coolant-lubricant modification on selected effects of pull broaching

NASA Astrophysics Data System (ADS)

Adamczuk, Krzysztof; Legutko, Stanisław; Laber, Alicja; Serwa, Wojciech

2017-10-01

The paper presents the results of testing the wear of the tool (pull broach) and a gear wheel splineway surface roughness after the friction node of pull broach/gear wheel (CuSn12Ni2) had been lubricated with metal machining oil and the same oil modified with chemically active exploitation additive. To designate the influence of modifying metal machining oil by the exploitation additive on the lubricating properties, anti-wear and antiseizure indicators have been appointed. Exploitation tests have proved purposefulness of modifying metal machining oil. Modification of the lubricant has contributed to reduction of the wear of the tools - pull broaches and to reduction of roughness of the splineway surfaces.

Materials and processes laboratory composite materials characterization task, part 1. Damage tolerance

NASA Technical Reports Server (NTRS)

Nettles, A. T.; Tucker, D. S.; Patterson, W. J.; Franklin, S. W.; Gordon, G. H.; Hart, L.; Hodge, A. J.; Lance, D. G.; Russel, S. S.

1991-01-01

A test run was performed on IM6/3501-6 carbon-epoxy in which the material was processed, machined into specimens, and tested for damage tolerance capabilities. Nondestructive test data played a major role in this element of composite characterization. A time chart was produced showing the time the composite material spent within each Branch or Division in order to identify those areas which produce a long turnaround time. Instrumented drop weight testing was performed on the specimens with nondestructive evaluation being performed before and after the impacts. Destructive testing in the form of cross-sectional photomicrography and compression-after-impact testing were used. Results show that the processing and machining steps needed to be performed more rapidly if data on composite material is to be collected within a reasonable timeframe. The results of the damage tolerance testing showed that IM6/3501-6 is a brittle material that is very susceptible to impact damage.

AgRISTARS: Foreign commodity production forecasting. The 1980 US corn and soybeans exploratory experiment

NASA Technical Reports Server (NTRS)

Malin, J. T.; Carnes, J. G. (Principal Investigator)

1981-01-01

The U.S. corn and soybeans exploratory experiment is described which consisted of evaluations of two technology components of a production forecasting system: classification procedures (crop labeling and proportion estimation at the level of a sampling unit) and sampling and aggregation procedures. The results from the labeling evaluations indicate that the corn and soybeans labeling procedure works very well in the U.S. corn belt with full season (after tasseling) LANDSAT data. The procedure should be readily adaptable to corn and soybeans labeling required for subsequent exploratory experiments or pilot tests. The machine classification procedures evaluated in this experiment were not effective in improving the proportion estimates. The corn proportions produced by the machine procedures had a large bias when the bias correction was not performed. This bias was caused by the manner in which the machine procedures handled spectrally impure pixels. The simulation test indicated that the weighted aggregation procedure performed quite well. Although further work can be done to improve both the simulation tests and the aggregation procedure, the results of this test show that the procedure should serve as a useful baseline procedure in future exploratory experiments and pilot tests.

Creep Laboratory manual

NASA Astrophysics Data System (ADS)

Osgerby, S.; Loveday, M. S.

1992-06-01

A manual for the NPL Creep Laboratory, a collective name given to two testing laboratories, the Uniaxial Creep Laboratory and the Advanced High Temperature Mechanical Testing Laboratory, is presented. The first laboratory is devoted to uniaxial creep testing and houses approximately 50 high sensitivity creep machines including 10 constant stress cam lever machines. The second laboratory houses a low cycle fatigue testing machine of 100 kN capacity driven by a servo-electric actuator, five machines for uniaxial tensile creep testing of engineering ceramics at temperatures up to 1600C, and an electronic creep machine. Details of the operational procedures for carrying out uniaxial creep testing are given. Calibration procedures to be followed in order to comply with the specifications laid down by British standards, and to provide traceability back to the primary standards are described.

Analysis of rolling contact spall life in 440 C steel bearing rims

NASA Technical Reports Server (NTRS)

Bastias, P. C.; Bhargava, V.; Bower, A. P.; Du, J.; Gupta, V.; Hahn, G. T.; Kulkarni, S. M.; Kumar, A. M.; Leng, X.; Rubin, C. A.

1991-01-01

The results of a two year study of the mechanisms of spall failure in the HPOTP bearings are described. The objective was to build a foundation for detailed analyses of the contact life in terms of: cyclic plasticity, contact mechanics, spall nucleation, and spall growth. Since the laboratory rolling contact testing is carried out in the 3 ball/rod contact fatigue testing machine, the analysis of the contacts and contact lives produced in this machine received attention. The results from the experimentally observed growth lives are compared with calculated predictions derived from the fracture mechanics calculations.

Blood Test: Immunoglobulin A (IgA)

MedlinePlus

... before this test. On the day of the test, having your child wear a T-shirt or short-sleeved shirt can ... The blood sample will be processed by a machine. The results are commonly ... further tests. Risks This test is considered a safe procedure. ...

10 CFR 431.294 - Uniform test method for the measurement of energy consumption of refrigerated bottled or canned...

Code of Federal Regulations, 2011 CFR

2011-01-01

... consumption of refrigerated bottled or canned beverage vending machines. 431.294 Section 431.294 Energy... EQUIPMENT Refrigerated Bottled or Canned Beverage Vending Machines Test Procedures § 431.294 Uniform test... machines. (a) Scope. This section provides test procedures for measuring, pursuant to EPCA, the energy...

The influence of machining condition and cutting tool wear on surface roughness of AISI 4340 steel

NASA Astrophysics Data System (ADS)

Natasha, A. R.; Ghani, J. A.; Che Haron, C. H.; Syarif, J.

2018-01-01

Sustainable machining by using cryogenic coolant as the cutting fluid has been proven to enhance some machining outputs. The main objective of the current work was to investigate the influence of machining conditions; dry and cryogenic, as well as the cutting tool wear on the machined surface roughness of AISI 4340 steel. The experimental tests were performed using chemical vapor deposition (CVD) coated carbide inserts. The value of machined surface roughness were measured at 3 cutting intervals; beginning, middle, and end of the cutting based on the readings of the tool flank wear. The results revealed that cryogenic turning had the greatest influence on surface roughness when machined at lower cutting speed and higher feed rate. Meanwhile, the cutting tool wear was also found to influence the surface roughness, either improving it or deteriorating it, based on the severity and the mechanism of the flank wear.

Prediction of outcome in internet-delivered cognitive behaviour therapy for paediatric obsessive-compulsive disorder: A machine learning approach.

PubMed

Lenhard, Fabian; Sauer, Sebastian; Andersson, Erik; Månsson, Kristoffer Nt; Mataix-Cols, David; Rück, Christian; Serlachius, Eva

2018-03-01

There are no consistent predictors of treatment outcome in paediatric obsessive-compulsive disorder (OCD). One reason for this might be the use of suboptimal statistical methodology. Machine learning is an approach to efficiently analyse complex data. Machine learning has been widely used within other fields, but has rarely been tested in the prediction of paediatric mental health treatment outcomes. To test four different machine learning methods in the prediction of treatment response in a sample of paediatric OCD patients who had received Internet-delivered cognitive behaviour therapy (ICBT). Participants were 61 adolescents (12-17 years) who enrolled in a randomized controlled trial and received ICBT. All clinical baseline variables were used to predict strictly defined treatment response status three months after ICBT. Four machine learning algorithms were implemented. For comparison, we also employed a traditional logistic regression approach. Multivariate logistic regression could not detect any significant predictors. In contrast, all four machine learning algorithms performed well in the prediction of treatment response, with 75 to 83% accuracy. The results suggest that machine learning algorithms can successfully be applied to predict paediatric OCD treatment outcome. Validation studies and studies in other disorders are warranted. Copyright © 2017 John Wiley & Sons, Ltd.

A new method for getting the three-dimensional curve of the groove of a spectacle frame by optical measuring

NASA Astrophysics Data System (ADS)

Rückwardt, M.; Göpfert, A.; Schnellhorn, M.; Correns, M.; Rosenberger, M.; Linß, G.

2010-07-01

Precise measuring of spectacle frames is an important field of quality assurance for opticians and their customers. Different supplier and a number of measuring methods are available but all of them are tactile ones. In this paper the possible employment of optical coordinate measuring machines is discussed for detecting the groove of a spectacle frame. The ambient conditions like deviation and measuring time are even multifaceted like quantity of quality characteristics and measuring objects itself and have to be tested. But the main challenge for an optical coordinate measuring machine is the blocked optical path, because the device under test is located behind an undercut. In this case it is necessary to deflect the beam of the machine for example with a rotating plane mirror. In the next step the difficulties of machine vision connecting to the spectacle frame are explained. Finally first results are given.

The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction

PubMed Central

Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J.

2018-01-01

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future. PMID:29538331

The reflection of evolving bearing faults in the stator current's extended park vector approach for induction machines

NASA Astrophysics Data System (ADS)

Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan

2018-07-01

Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.

The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction.

PubMed

Li, Hongjian; Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J

2018-03-14

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future.

Machine Learning Based Evaluation of Reading and Writing Difficulties.

PubMed

Iwabuchi, Mamoru; Hirabayashi, Rumi; Nakamura, Kenryu; Dim, Nem Khan

2017-01-01

The possibility of auto evaluation of reading and writing difficulties was investigated using non-parametric machine learning (ML) regression technique for URAWSS (Understanding Reading and Writing Skills of Schoolchildren) [1] test data of 168 children of grade 1 - 9. The result showed that the ML had better prediction than the ordinary rule-based decision.

TEACHING MACHINES AND PROGRAMMED LEARNING, A SOURCE BOOK.

ERIC Educational Resources Information Center

LUMSDAINE, A.A., ED.; GLASER, ROBERT, ED.

BROUGHT TOGETHER HERE IS THE WIDELY-SCATTERED LITERATURE ON SELF-INSTRUCTIONAL PROGRAMS AND DEVICES BY LEADERS, PAST AND PRESENT, IN THEIR DEVELOPMENT. S.L. PRESSEY IN HIS ARTICLES DESCRIBES THE APPARATUS, METHODS, THEORY, AND RESULTS ATTENDANT UPON USE OF HIS TEST-SCORING DEVICES. B.F. SKINNER IN HIS ARTICLES DEVELOPS THEORY, DESCRIBES MACHINES,…

Pulmonary Function Tests

MedlinePlus

... heavily for at least 30 minutes before the test. ■■ Do not wear tight clothing that makes it difficult for you ... be blowing into a tube connected to a machine (spirometer). To get the “best” test result, the test is repeated three times. You ...

Software platform virtualization in chemistry research and university teaching

PubMed Central

2009-01-01

Background Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Results Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Conclusion Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide. PMID:20150997

Fifth Graders' Learning About Simple Machines Through Engineering Design-Based Instruction Using LEGO™ Materials

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Mike

2013-10-01

This study is part of a 5-year National Science Foundation-funded project, Transforming Elementary Science Learning Through LEGO™ Engineering Design. In this study, we report on the successes and challenges of implementing an engineering design-based and LEGO™-oriented unit in an urban classroom setting and we focus on the impact of the unit on students' content understanding of simple machines. The LEGO™ engineering-based simple machines module, which was developed for fifth graders by our research team, was implemented in an urban school in a large city in the Northeastern region of the USA. Thirty-three fifth grade students participated in the study, and they showed significant growth in content understanding. We measured students' content knowledge by using identical paper tests and semistructured interviews before and after instruction. Our paired t test analysis results showed that students significantly improved their test and interview scores (t = -3.62, p < 0.001 for multiple-choice items and t = -9.06, p < 0.000 for the open-ended items in the test and t = -12.11, p < 0.000 for the items in interviews). We also identified several alternative conceptions that are held by students on simple machines.

Fatigue testing of energy storing prosthetic feet.

PubMed

Toh, S L; Goh, J C; Tan, P H; Tay, T E

1993-12-01

This paper describes a simple approach to the fatigue testing of prosthetic feet. A fatigue testing machine for prosthetic feet was designed as part of the programme to develop an energy storing prosthetic foot (ESPF). The fatigue tester does not simulate the loading pattern on the foot during normal walking. However, cyclic vertical loads are applied to the heel and forefoot during heel-strike and toe-off respectively, for 500,000 cycles. The maximum load applied was chosen to be 1.5 times that applied by the bodyweight of the amputee and the test frequency was chosen to be 2 Hz to shorten the test duration. Four prosthetic feet were tested: two Lambda feet (a newly developed ESPF), a Kingsley SACH foot and a Proteor SACH foot. It was found that the Lambda feet have very good fatigue properties. The Kingsley SACH foot performed better than the Proteor model, with no signs of wear at the heel. The results obtained using the simple approach was found to be comparable to the results from more complex fatigue machines which simulate the load pattern during normal walking. This suggests that simple load simulating machines, which are less costly and require less maintenance, are useful substitutes in studying the fatigue properties of prosthetic feet.

40 CFR 63.3960 - By what date must I conduct performance tests and other initial compliance demonstrations?

Code of Federal Regulations, 2011 CFR

2011-07-01

... performance test of one representative magnet wire coating machine for each group of identical or very similar... you complete the performance test of a representative magnet wire coating machine. The requirements in... operations, you may, with approval, conduct a performance test of a single magnet wire coating machine that...

Development of improved high temperature seals and lubricants for downhole motors in geothermal applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

De La Fosse, P.H.; Black, A.D.; DiBona, B.G.

1983-01-01

A major limitation of downhole mud motors for geothermal drilling, as well as straight-hole oil and gas drilling, is the bearing section. Reduced bearing life results from the inability to seal a lubricant in the bearing pack. A reliable rotary seal will extend the bearing life and will allow high pressure drops across the bit for improved bottomhole cleaning and increased drilling rate. This paper summarizes the results of a six-year program funded by the U.S. Department of Energy/Division of Geothermal Energy to develop a sealed bearing pack for use with downhole motors in geothermal applications. Descriptions of the Sealmore » Test Machine, Lubricant Test Machine and Bearing Pack Test Facility are presented. Summaries of all seal tests, lubricant tests and bearing pack tests are provided; and a comprehensive program bibliography is presented.« less

Methodological Issues in Predicting Pediatric Epilepsy Surgery Candidates Through Natural Language Processing and Machine Learning

PubMed Central

Cohen, Kevin Bretonnel; Glass, Benjamin; Greiner, Hansel M.; Holland-Bouley, Katherine; Standridge, Shannon; Arya, Ravindra; Faist, Robert; Morita, Diego; Mangano, Francesco; Connolly, Brian; Glauser, Tracy; Pestian, John

2016-01-01

Objective: We describe the development and evaluation of a system that uses machine learning and natural language processing techniques to identify potential candidates for surgical intervention for drug-resistant pediatric epilepsy. The data are comprised of free-text clinical notes extracted from the electronic health record (EHR). Both known clinical outcomes from the EHR and manual chart annotations provide gold standards for the patient’s status. The following hypotheses are then tested: 1) machine learning methods can identify epilepsy surgery candidates as well as physicians do and 2) machine learning methods can identify candidates earlier than physicians do. These hypotheses are tested by systematically evaluating the effects of the data source, amount of training data, class balance, classification algorithm, and feature set on classifier performance. The results support both hypotheses, with F-measures ranging from 0.71 to 0.82. The feature set, classification algorithm, amount of training data, class balance, and gold standard all significantly affected classification performance. It was further observed that classification performance was better than the highest agreement between two annotators, even at one year before documented surgery referral. The results demonstrate that such machine learning methods can contribute to predicting pediatric epilepsy surgery candidates and reducing lag time to surgery referral. PMID:27257386

Information extraction from dynamic PS-InSAR time series using machine learning

NASA Astrophysics Data System (ADS)

van de Kerkhof, B.; Pankratius, V.; Chang, L.; van Swol, R.; Hanssen, R. F.

2017-12-01

Due to the increasing number of SAR satellites, with shorter repeat intervals and higher resolutions, SAR data volumes are exploding. Time series analyses of SAR data, i.e. Persistent Scatterer (PS) InSAR, enable the deformation monitoring of the built environment at an unprecedented scale, with hundreds of scatterers per km2, updated weekly. Potential hazards, e.g. due to failure of aging infrastructure, can be detected at an early stage. Yet, this requires the operational data processing of billions of measurement points, over hundreds of epochs, updating this data set dynamically as new data come in, and testing whether points (start to) behave in an anomalous way. Moreover, the quality of PS-InSAR measurements is ambiguous and heterogeneous, which will yield false positives and false negatives. Such analyses are numerically challenging. Here we extract relevant information from PS-InSAR time series using machine learning algorithms. We cluster (group together) time series with similar behaviour, even though they may not be spatially close, such that the results can be used for further analysis. First we reduce the dimensionality of the dataset in order to be able to cluster the data, since applying clustering techniques on high dimensional datasets often result in unsatisfying results. Our approach is to apply t-distributed Stochastic Neighbor Embedding (t-SNE), a machine learning algorithm for dimensionality reduction of high-dimensional data to a 2D or 3D map, and cluster this result using Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The results show that we are able to detect and cluster time series with similar behaviour, which is the starting point for more extensive analysis into the underlying driving mechanisms. The results of the methods are compared to conventional hypothesis testing as well as a Self-Organising Map (SOM) approach. Hypothesis testing is robust and takes the stochastic nature of the observations into account, but is time consuming. Therefore, we successively apply our machine learning approach with the hypothesis testing approach in order to benefit from both the reduced computation time of the machine learning approach as from the robust quality metrics of hypothesis testing. We acknowledge support from NASA AISTNNX15AG84G (PI V. Pankratius)

Dynamic modeling of brushless dc motors for aerospace actuation

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Nehl, T. W.

1980-01-01

A discrete time model for simulation of the dynamics of samarium cobalt-type permanent magnet brushless dc machines is presented. The simulation model includes modeling of the interaction between these machines and their attached power conditioners. These are transistorized conditioner units. This model is part of an overall discrete-time analysis of the dynamic performance of electromechanical actuators, which was conducted as part of prototype development of such actuators studied and built for NASA-Johnson Space Center as a prospective alternative to hydraulic actuators presently used in shuttle orbiter applications. The resulting numerical simulations of the various machine and power conditioner current and voltage waveforms gave excellent correlation to the actual waveforms collected from actual hardware experimental testing. These results, numerical and experimental, are presented here for machine motoring, regeneration and dynamic braking modes. Application of the resulting model to the determination of machine current and torque profiles during closed-loop actuator operation were also analyzed and the results are given here. These results are given in light of an overall view of the actuator system components. The applicability of this method of analysis to design optimization and trouble-shooting in such prototype development is also discussed in light of the results at hand.

Machinability evaluation of titanium alloys (Part 2)--Analyses of cutting force and spindle motor current.

PubMed

Kikuchi, Masafumi; Okuno, Osamu

2004-12-01

To establish a method of determining the machinability of dental materials for CAD/CAM systems, the machinability of titanium, two titanium alloys (Ti-6Al-4V and Ti-6Al-7Nb), and free-cutting brass was evaluated through cutting force and spindle motor current. The metals were slotted using a milling machine and square end mills at four cutting conditions. Both the static and dynamic components of the cutting force represented well the machinability of the metals tested: the machinability of Ti-6Al-4V and Ti-6Al-7Nb was worse than that of titanium, while that of free-cutting brass was better. On the other hand, the results indicated that the spindle motor current was not sensitive enough to detect the material difference among the titanium and its alloys.

An Integrated 520-600 GHz Sub-Harmonic Mixer and Tripler Combination Based on GaAs MMIC Membrane Planar Schottky Diodes

NASA Technical Reports Server (NTRS)

Thomas, B.; Gill, J.; Maestrini, A.; Lee, C.; Lin, R.; Sin, S.; Peralta, A.; Mehdi, I.

2011-01-01

We present here the design, development and test of an integrated sub-millimeter front-end featuring a 520-600 GHz sub-harmonic mixer and a 260-300 GHz frequency tripler in a single cavity. Both devices used GaAs MMIC membrane planar Schottky diode technology. The sub-harmonic mixer/tripler circuit has been tested using conventional machined as well as silicon micro-machined blocks. Measurement results on the metal block give best DSB mixer noise temperature of 2360 K and conversion losses of 7.7 dB at 520 GHz. Preliminary results on the silicon micro-machined blocks give a DSB mixer noise temperature of 4860 K and conversion losses of 12.16 dB at 540 GHz. The LO input power required to pump the integrated tripler/sub-harmonic mixer for both packages is between 30 and 50 mW

An Integrated 520-600 GHz Sub-Harmonic Mixer and Tripler Combination Based on GaAs MMIC Membrane Planar Schottky Diodes

NASA Technical Reports Server (NTRS)

Thomas, B.; Gill, J.; Maestrini, A.; Lee, C.; Lin, R.; Sin, S.; Peralta, A.; Mehdi, I.

2010-01-01

We present here the design, development and test of an integrated sub-millimeter front-end featuring a 520-600 GHz sub-harmonic mixer and a 260-300 GHz frequency tripler in a single cavity. Both devices used GaAs MMIC membrane planar Schottky diode technology. The sub-harmonic mixer/tripler circuit has been tested using conventional machined as well as silicon micro-machined blocks. Measurement results on the metal block give best DSB mixer noise temperature of 2360 K and conversion losses of 7.7 dB at 520 GHz. Preliminary results on the silicon micro-machined blocks give a DSB mixer noise temperature of 4860 K and conversion losses of 12.16 dB at 540 GHz. The LO input power required to pump the integrated tripler/sub-harmonic mixer for both packages is between 30 and 50 mW.

Experimental investigation of the tip based micro/nano machining

NASA Astrophysics Data System (ADS)

Guo, Z.; Tian, Y.; Liu, X.; Wang, F.; Zhou, C.; Zhang, D.

2017-12-01

Based on the self-developed three dimensional micro/nano machining system, the effects of machining parameters and sample material on micro/nano machining are investigated. The micro/nano machining system is mainly composed of the probe system and micro/nano positioning stage. The former is applied to control the normal load and the latter is utilized to realize high precision motion in the xy plane. A sample examination method is firstly introduced to estimate whether the sample is placed horizontally. The machining parameters include scratching direction, speed, cycles, normal load and feed. According to the experimental results, the scratching depth is significantly affected by the normal load in all four defined scratching directions but is rarely influenced by the scratching speed. The increase of scratching cycle number can increase the scratching depth as well as smooth the groove wall. In addition, the scratching tests of silicon and copper attest that the harder material is easier to be removed. In the scratching with different feed amount, the machining results indicate that the machined depth increases as the feed reduces. Further, a cubic polynomial is used to fit the experimental results to predict the scratching depth. With the selected machining parameters of scratching direction d3/d4, scratching speed 5 μm/s and feed 0.06 μm, some more micro structures including stair, sinusoidal groove, Chinese character '田', 'TJU' and Chinese panda have been fabricated on the silicon substrate.

A Novel Approach for Lie Detection Based on F-Score and Extreme Learning Machine

PubMed Central

Gao, Junfeng; Wang, Zhao; Yang, Yong; Zhang, Wenjia; Tao, Chunyi; Guan, Jinan; Rao, Nini

2013-01-01

A new machine learning method referred to as F-score_ELM was proposed to classify the lying and truth-telling using the electroencephalogram (EEG) signals from 28 guilty and innocent subjects. Thirty-one features were extracted from the probe responses from these subjects. Then, a recently-developed classifier called extreme learning machine (ELM) was combined with F-score, a simple but effective feature selection method, to jointly optimize the number of the hidden nodes of ELM and the feature subset by a grid-searching training procedure. The method was compared to two classification models combining principal component analysis with back-propagation network and support vector machine classifiers. We thoroughly assessed the performance of these classification models including the training and testing time, sensitivity and specificity from the training and testing sets, as well as network size. The experimental results showed that the number of the hidden nodes can be effectively optimized by the proposed method. Also, F-score_ELM obtained the best classification accuracy and required the shortest training and testing time. PMID:23755136

A cost-effective, accurate machine for testing the torsional strength of sheep long bones.

PubMed

Jämsä, T; Jalovaara, P

1996-07-01

A cost-effective torsional testing machine for sheep long bones was constructed. The machine was fabricated on a disused standard turning lathe. The angular speed used was 6.5 degrees/s. A precision amplifier using modern low-noise, low-drift operational amplifiers was developed. The maximum torsional load was 250 Nm, the sensitivity 0.5 Nm and the total machine inaccuracy less than 1.0%. The standard error of torsional testing was 3.0% when seven pairs of intact sheep tibiae were tested.

Development of testing machine for tunnel inspection using multi-rotor UAV

NASA Astrophysics Data System (ADS)

Iwamoto, Tatsuya; Enaka, Tomoya; Tada, Keijirou

2017-05-01

Many concrete structures are deteriorating to dangerous levels throughout Japan. These concrete structures need to be inspected regularly to be sure that they are safe enough to be used. The inspection method for these concrete structures is typically the impact acoustic method. In the impact acoustic method, the worker taps the surface of the concrete with a hammer. Thus, it is necessary to set up scaffolding to access tunnel walls for inspection. Alternatively, aerial work platforms can be used. However, setting up scaffolding and aerial work platforms is not economical with regard to time or money. Therefore, we developed a testing machine using a multirotor UAV for tunnel inspection. This test machine flies by a plurality of rotors, and it is pushed along a concrete wall and moved by using rubber crawlers. The impact acoustic method is used in this testing machine. This testing machine has a hammer to make an impact, and a microphone to acquire the impact sound. The impact sound is converted into an electrical signal and is wirelessly transmitted to the computer. At the same time, the position of the testing machine is measured by image processing using a camera. The weight and dimensions of the testing machine are approximately 1.25 kg and 500 mm by 500 mm by 250 mm, respectively.

Effects of pole flux distribution in a homopolar linear synchronous machine

NASA Astrophysics Data System (ADS)

Balchin, M. J.; Eastham, J. F.; Coles, P. C.

1994-05-01

Linear forms of synchronous electrical machine are at present being considered as the propulsion means in high-speed, magnetically levitated (Maglev) ground transportation systems. A homopolar form of machine is considered in which the primary member, which carries both ac and dc windings, is supported on the vehicle. Test results and theoretical predictions are presented for a design of machine intended for driving a 100 passenger vehicle at a top speed of 400 km/h. The layout of the dc magnetic circuit is examined to locate the best position for the dc winding from the point of view of minimum core weight. Measurements of flux build-up under the machine at different operating speeds are given for two types of secondary pole: solid and laminated. The solid pole results, which are confirmed theoretically, show that this form of construction is impractical for high-speed drives. Measured motoring characteristics are presented for a short length of machine which simulates conditions at the leading and trailing ends of the full-sized machine. Combination of the results with those from a cylindrical version of the machine make it possible to infer the performance of the full-sized traction machine. This gives 0.8 pf and 0.9 efficiency at 300 km/h, which is much better than the reported performance of a comparable linear induction motor (0.52 pf and 0.82 efficiency). It is therefore concluded that in any projected high-speed Maglev systems, a linear synchronous machine should be the first choice as the propulsion means.

Stirling machine operating experience

NASA Technical Reports Server (NTRS)

Ross, Brad; Dudenhoefer, James E.

1991-01-01

Numerous Stirling machines have been built and operated, but the operating experience of these machines is not well known. It is important to examine this operating experience in detail, because it largely substantiates the claim that Stirling machines are capable of reliable and lengthy lives. The amount of data that exists is impressive, considering that many of the machines that have been built are developmental machines intended to show proof of concept, and were not expected to operate for any lengthy period of time. Some Stirling machines (typically free-piston machines) achieve long life through non-contact bearings, while other Stirling machines (typically kinematic) have achieved long operating lives through regular seal and bearing replacements. In addition to engine and system testing, life testing of critical components is also considered.

Novel fabrication method for zirconia restorations: bonding strength of machinable ceramic to zirconia with resin cements.

PubMed

Kuriyama, Soichi; Terui, Yuichi; Higuchi, Daisuke; Goto, Daisuke; Hotta, Yasuhiro; Manabe, Atsufumi; Miyazaki, Takashi

2011-01-01

A novel method was developed to fabricate all-ceramic restorations which comprised CAD/CAM-fabricated machinable ceramic bonded to CAD/CAM-fabricated zirconia framework using resin cement. The feasibility of this fabrication method was assessed in this study by investigating the bonding strength of a machinable ceramic to zirconia. A machinable ceramic was bonded to a zirconia plate using three kinds of resin cements: ResiCem (RE), Panavia (PA), and Multilink (ML). Conventional porcelain-fused-to-zirconia specimens were also prepared to serve as control. Shear bond strength test (SBT) and Schwickerath crack initiation test (SCT) were carried out. SBT revealed that PA (40.42 MPa) yielded a significantly higher bonding strength than RE (28.01 MPa) and ML (18.89 MPa). SCT revealed that the bonding strengths of test groups using resin cement were significantly higher than those of Control. Notably, the bonding strengths of RE and ML were above 25 MPa even after 10,000 times of thermal cycling -adequately meeting the ISO 9693 standard for metal-ceramic restorations. These results affirmed the feasibility of the novel fabrication method, in that a CAD/CAM-fabricated machinable ceramic is bonded to a CAD/CAM-fabricated zirconia framework using a resin cement.

Design features and results from fatigue reliability research machines.

NASA Technical Reports Server (NTRS)

Lalli, V. R.; Kececioglu, D.; Mcconnell, J. B.

1971-01-01

The design, fabrication, development, operation, calibration and results from reversed bending combined with steady torque fatigue research machines are presented. Fifteen-centimeter long, notched, SAE 4340 steel specimens are subjected to various combinations of these stresses and cycled to failure. Failure occurs when the crack in the notch passes through the specimen automatically shutting down the test machine. These cycles-to-failure data are statistically analyzed to develop a probabilistic S-N diagram. These diagrams have many uses; a rotating component design example given in the literature shows that minimum size and weight for a specified number of cycles and reliability can be calculated using these diagrams.

Analysis of Flatness Deviations for Austenitic Stainless Steel Workpieces after Efficient Surface Machining

NASA Astrophysics Data System (ADS)

Nadolny, K.; Kapłonek, W.

2014-08-01

The following work is an analysis of flatness deviations of a workpiece made of X2CrNiMo17-12-2 austenitic stainless steel. The workpiece surface was shaped using efficient machining techniques (milling, grinding, and smoothing). After the machining was completed, all surfaces underwent stylus measurements in order to obtain surface flatness and roughness parameters. For this purpose the stylus profilometer Hommel-Tester T8000 by Hommelwerke with HommelMap software was used. The research results are presented in the form of 2D surface maps, 3D surface topographies with extracted single profiles, Abbott-Firestone curves, and graphical studies of the Sk parameters. The results of these experimental tests proved the possibility of a correlation between flatness and roughness parameters, as well as enabled an analysis of changes in these parameters from shaping and rough grinding to finished machining. The main novelty of this paper is comprehensive analysis of measurement results obtained during a three-step machining process of austenitic stainless steel. Simultaneous analysis of individual machining steps (milling, grinding, and smoothing) enabled a complementary assessment of the process of shaping the workpiece surface macro- and micro-geometry, giving special consideration to minimize the flatness deviations

Mobile Landing Platform with Core Capability Set (MLP w/CCS): Combined Initial Operational Test and Evaluation and Live Fire Test and Evaluation Report

DTIC Science & Technology

2015-07-01

annex.   iii Self-defense testing was limited to structural test firing from each machine gun mount and an ammunition resupply drill. Robust self...provided in the classified annex. Self-   8 defense testing was limited to structural test firing from each machine gun mount and a single...Caliber Machine Gun Mount Structural Test Fire November 2014 San Diego, Offshore Ship Weapons Range Operating Independently       9 Section Three

Effect of heat treatments on machinability of gold alloy with age-hardenability at intraoral temperature.

PubMed

Watanabe, I; Baba, N; Watanabe, E; Atsuta, M; Okabe, T

2004-01-01

This study investigated the effect of heat treatment on the machinability of heat-treated cast gold alloy with age-hardenability at intraoral temperature using a handpiece engine with SiC wheels and an air-turbine handpiece with carbide burs and diamond points. Cast gold alloy specimens underwent various heat treatments [As-cast (AC); Solution treatment (ST); High-temperature aging (HA), Intraoral aging (IA)] before machinability testing. The machinability test was conducted at a constant machining force of 0.784N. The three circumferential speeds used for the handpiece engine were 500, 1,000 and 1,500 m/min. The machinability index (M-index) was determined as the amount of metal removed by machining (volume loss, mm(3)). The results were analyzed by ANOVA and Scheffé's test. When an air-turbine handpiece was used, there was no difference in the M-index of the gold alloy among the heat treatments. The air-turbine carbide burs showed significantly (p<0.05) higher M-indexes than the diamond points after any heat treatments. With the SiC wheels, increasing the circumferential speed increased the M-index values for each heat treatment. The specimens heat-treated with AC, HA and IA had similar M-indexes at the lower speeds (500 and 1,000 m/min). The ST specimens exhibited the lowest M-index at the lower speeds. However, at the highest speed (1,500 m/min), there were no significant differences in the M-indexes among the heat treatments except for HA, which showed the highest M-index. There was no effect of heat treatment on the machinability of the gold alloy using the air-turbine handpiece. The heat treatments had a small effect on the M-index of the gold alloy machined with a SiC wheel for a handpiece engine.

A portable fracture toughness tester for biological materials

NASA Astrophysics Data System (ADS)

Darvell, B. W.; Lee, P. K. D.; Yuen, T. D. B.; Lucas, P. W.

1996-06-01

A portable mechanical tester is described which is both lightweight and cheap to produce. The machine is simple and convenient to operate and requires only a minimum of personnel training. It can be used to measure the fundamental mechanical properties of pliant solids, particularly toughness (in the sense of `work of fracture') using either scissors or wedge tests. This is achieved through a novel hardware integration technique. The circuits are described. The use of the machine does not require a chart recorder but it can be linked to a personal computer, either to show force - displacement relationships or for data storage. The design allows the use of any relatively `soft' mechanical test, i.e. tests in which the deformability of the frame of the machine and its load cell do not introduce significant errors into the results. Examples of its use in measuring the toughness of biomaterials by scissors (paper, wood) and wedges (mung bean starch gels) are given.

Fabrication and Tests of M240 Machine Gun Barrels Lined with Stellite 25

DTIC Science & Technology

2016-04-01

ARL-TR-7662 ● APR 2016 US Army Research Laboratory Fabrication and Tests of M240 Machine Gun Barrels Lined with Stellite 25...Fabrication and Tests of M240 Machine Gun Barrels Lined with Stellite 25 by William S de Rosset and Sean Fudger Weapons and Materials Research...

Effect of mesh-peel ply variation on mechanical properties of E-glas composite by infusion vacuum method

NASA Astrophysics Data System (ADS)

Abdurohman, K.; Siahaan, Mabe

2018-04-01

Composite materials made of glass fiber EW-135 with epoxy lycal resin with vacuum infusion method have been performed. The dried glass fiber is arranged in a mold then connected to a vacuum machine and a resin tube. Then, the vacuum machine is turned on and at the same time the resin is sucked and flowed into the mold. This paper reports on the effect of using mesh- peel ply singles on upper-side laminates called A and the effect of using double mesh-peel ply on upper and lower-side laminates call B with glass fiber arrangement is normal and ± 450 in vacuum infusion process. Followed by the manufacture of tensile test specimen and tested its tensile strength with universal test machine 100kN Tensilon RTF 2410, at room temperature with constant crosshead speed. From tensile test results using single and double layers showed that double mesh-peel ply can increase tensile strength 14% and Young modulus 17%.

Improving Non-Destructive Concrete Strength Tests Using Support Vector Machines

PubMed Central

Shih, Yi-Fan; Wang, Yu-Ren; Lin, Kuo-Liang; Chen, Chin-Wen

2015-01-01

Non-destructive testing (NDT) methods are important alternatives when destructive tests are not feasible to examine the in situ concrete properties without damaging the structure. The rebound hammer test and the ultrasonic pulse velocity test are two popular NDT methods to examine the properties of concrete. The rebound of the hammer depends on the hardness of the test specimen and ultrasonic pulse travelling speed is related to density, uniformity, and homogeneity of the specimen. Both of these two methods have been adopted to estimate the concrete compressive strength. Statistical analysis has been implemented to establish the relationship between hammer rebound values/ultrasonic pulse velocities and concrete compressive strength. However, the estimated results can be unreliable. As a result, this research proposes an Artificial Intelligence model using support vector machines (SVMs) for the estimation. Data from 95 cylinder concrete samples are collected to develop and validate the model. The results show that combined NDT methods (also known as SonReb method) yield better estimations than single NDT methods. The results also show that the SVMs model is more accurate than the statistical regression model. PMID:28793627

Composite Material Testing Data Reduction to Adjust for the Systematic 6-DOF Testing Machine Aberrations

Treesearch

Athanasios lliopoulos; John G. Michopoulos; John G. C. Hermanson

2012-01-01

This paper describes a data reduction methodology for eliminating the systematic aberrations introduced by the unwanted behavior of a multiaxial testing machine, into the massive amounts of experimental data collected from testing of composite material coupons. The machine in reference is a custom made 6-DoF system called NRL66.3 and developed at the NAval...

Surface integrity and fatigue behaviour of electric discharged machined and milled austenitic stainless steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lundberg, Mattias, E-mail: mattias.lundberg@liu.se

Machining of austenitic stainless steels can result in different surface integrities and different machining process parameters will have a great impact on the component fatigue life. Understanding how machining processes affect the cyclic behaviour and microstructure are of outmost importance in order to improve existing and new life estimation models. Milling and electrical discharge machining (EDM) have been used to manufacture rectangular four-point bend fatigue test samples; subjected to high cycle fatigue. Before fatigue testing, surface integrity characterisation of the two surface conditions was conducted using scanning electron microscopy, surface roughness, residual stress profiles, and hardness profiles. Differences in cyclicmore » behaviour were observed between the two surface conditions by the fatigue testing. The milled samples exhibited a fatigue limit. EDM samples did not show the same behaviour due to ratcheting. Recrystallized nano sized grains were identified at the severely plastically deformed surface of the milled samples. Large amounts of bent mechanical twins were observed ~ 5 μm below the surface. Grain shearing and subsequent grain rotation from milling bent the mechanical twins. EDM samples showed much less plastic deformation at the surface. Surface tensile residual stresses of ~ 500 MPa and ~ 200 MPa for the milled and EDM samples respectively were measured. - Highlights: •Milled samples exhibit fatigue behaviour, but not EDM samples. •Four-point bending is not suitable for materials exhibiting pronounced ratcheting. •LAGB density can be used to quantitatively measure plastic deformation. •Grain shearing and rotation result in bent mechanical twins. •Nano sized grains evolve due to the heat of the operation.« less

MachineProse: an Ontological Framework for Scientific Assertions

PubMed Central

Dinakarpandian, Deendayal; Lee, Yugyung; Vishwanath, Kartik; Lingambhotla, Rohini

2006-01-01

Objective: The idea of testing a hypothesis is central to the practice of biomedical research. However, the results of testing a hypothesis are published mainly in the form of prose articles. Encoding the results as scientific assertions that are both human and machine readable would greatly enhance the synergistic growth and dissemination of knowledge. Design: We have developed MachineProse (MP), an ontological framework for the concise specification of scientific assertions. MP is based on the idea of an assertion constituting a fundamental unit of knowledge. This is in contrast to current approaches that use discrete concept terms from domain ontologies for annotation and assertions are only inferred heuristically. Measurements: We use illustrative examples to highlight the advantages of MP over the use of the Medical Subject Headings (MeSH) system and keywords in indexing scientific articles. Results: We show how MP makes it possible to carry out semantic annotation of publications that is machine readable and allows for precise search capabilities. In addition, when used by itself, MP serves as a knowledge repository for emerging discoveries. A prototype for proof of concept has been developed that demonstrates the feasibility and novel benefits of MP. As part of the MP framework, we have created an ontology of relationship types with about 100 terms optimized for the representation of scientific assertions. Conclusion: MachineProse is a novel semantic framework that we believe may be used to summarize research findings, annotate biomedical publications, and support sophisticated searches. PMID:16357355

The simplest chronoscope II: reaction time measured by meterstick versus machine.

PubMed

Montare, Alberto

2010-12-01

Visual simple reaction time (SRT) scores measured in 31 college students of both sexes by use of the simplest chronoscope methodology (meterstick SRT) were compared to scores obtained by use of an electromechanical multi-choice reaction timer (machine SRT). Four hypotheses were tested. Results indicated that the previous mean value of meterstick SRT was replicated; meterstick SRT was significantly faster than long-standing population estimates of mean SRT; and machine SRT was significantly slower than the same long-standing mean SRT estimates for the population. Also, the mean meterstick SRT of 181 msec. was significantly faster than the mean machine SRT of 294 msec. It was theorized that differential visual information processing occurred such that the dorsal visual stream subserved meterstick SRT; whereas the ventral visual stream subserved machine SRT.

Preliminary Comparison of Properties between Ni-electroplated Stainless Steel Parts Fabricated with Laser Additive Manufacturing and Conventional Machining

NASA Astrophysics Data System (ADS)

Mäkinen, Mika; Jauhiainen, Eeva; Matilainen, Ville-Pekka; Riihimäki, Jaakko; Ritvanen, Jussi; Piili, Heidi; Salminen, Antti

Laser additive manufacturing (LAM) is a fabrication technology, which enables production of complex parts from metallic materials with mechanical properties comparable to those of conventionally machined parts. These LAM parts are manufactured via melting metallic powder layer by layer with laser beam. Aim of this study is to define preliminarily the possibilities of using electroplating to supreme surface properties. Electrodeposited nickel and chromium as well as electroless (autocatalytic) deposited nickel was used to enhance laser additive manufactured and machined parts properties, like corrosion resistance, friction and wearing. All test pieces in this study were manufactured with a modified research AM equipment, equal to commercial EOS M series. The laser system used for tests was IPG 200 W CW fiber laser. The material used in this study for additive manufacturing was commercial stainless steel powder grade named SS316L. This SS316L is not equal to AISI 316L grade, but commercial name of this kind of powder is widely known in additive manufacturing as SS316L. Material used for fabrication of comparison test pieces (i.e. conventionally manufactured) was AISI 316L stainless steel bar. Electroplating was done in matrix cell and electroless was done in plastic sink properties of plated parts were tested within acetic acid salt spray corrosion chamber (AASS, SFS-EN-ISO 9227 standard). Adhesion of coating, friction and wearing properties were tested with Pin-On-Rod machine. Results show that in these preliminary tests, LAM parts and machined parts have certain differences due to manufacturing route and surface conditions. These have an effect on electroplated and electroless parts features on adhesion, corrosion, wearing and friction. However, further and more detailed studies are needed to fully understand these phenomena.

Predicting competency in automated machine use in an acquired brain injury population using neuropsychological measures.

PubMed

Crowe, Simon F; Mahony, Kate; Jackson, Martin

2004-08-01

The purpose of the current study was to explore whether performance on standardised neuropsychological measures could predict functional ability with automated machines and services among people with an acquired brain injury (ABI). Participants were 45 individuals who met the criteria for mild, moderate or severe ABI and 15 control participants matched on demographic variables including age- and education. Each participant was required to complete a battery of neuropsychological tests, as well as performing three automated service delivery tasks: a transport automated ticketing machine, an automated teller machine (ATM) and an automated telephone service. The results showed consistently high relationship between the neuropsychological measures, both as single predictors and in combination, and level of competency with the automated machines. Automated machines are part of a relatively new phenomena in service delivery and offer an ecologically valid functional measure of performance that represents a true indication of functional disability.

SU-G-BRB-02: An Open-Source Software Analysis Library for Linear Accelerator Quality Assurance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerns, J; Yaldo, D

Purpose: Routine linac quality assurance (QA) tests have become complex enough to require automation of most test analyses. A new data analysis software library was built that allows physicists to automate routine linear accelerator quality assurance tests. The package is open source, code tested, and benchmarked. Methods: Images and data were generated on a TrueBeam linac for the following routine QA tests: VMAT, starshot, CBCT, machine logs, Winston Lutz, and picket fence. The analysis library was built using the general programming language Python. Each test was analyzed with the library algorithms and compared to manual measurements taken at the timemore » of acquisition. Results: VMAT QA results agreed within 0.1% between the library and manual measurements. Machine logs (dynalogs & trajectory logs) were successfully parsed; mechanical axis positions were verified for accuracy and MLC fluence agreed well with EPID measurements. CBCT QA measurements were within 10 HU and 0.2mm where applicable. Winston Lutz isocenter size measurements were within 0.2mm of TrueBeam’s Machine Performance Check. Starshot analysis was within 0.2mm of the Winston Lutz results for the same conditions. Picket fence images with and without a known error showed that the library was capable of detecting MLC offsets within 0.02mm. Conclusion: A new routine QA software library has been benchmarked and is available for use by the community. The library is open-source and extensible for use in larger systems.« less

Natural Fiber Cut Machine Semi-Automatic Linear Motion System for Empty Fiber Bunches: Re-designing for Local Use

NASA Astrophysics Data System (ADS)

Asfarizal; Kasim, Anwar; Gunawarman; Santosa

2017-12-01

Empty Palm bunches of fiber is local ingredient in Indonesia that easy to obtain. Empty Palm bunches of fiber can be obtained from the palm oil industry such as in West Pasaman. The character of the empty Palm bunches of fiber that is strong and pliable has high-potential for particle board. To transform the large quantities of fiber become particles in size 0-10 mm requires a specially designed cut machine. Therefore, the machine is designed in two-stage system that is mechanical system, structure and cutting knife. Components that have been made, assembled and then tested to reveal the ability of the machine to cut. The results showed that the straight back and forth motion cut machine is able to cut out the empty oil palm bunches of fiber with a length 0-1 cm, 2 cm, 8 cm and the surface of the cut is not stringy. The cutting capacity is at a length of 2 cm in the result 24.4 (kg/h) and 8 cm obtained results of up to 84 (kg/h)

Investigation of Dynamic Force/Vibration Transmission Characteristics of Four-Square Type Gear Durability Test Machines

NASA Technical Reports Server (NTRS)

Kahraman, Ahmet

2002-01-01

In this study, design requirements for a dynamically viable, four-square type gear test machine are investigated. Variations of four-square type gear test machines have been in use for durability and dynamics testing of both parallel- and cross-axis gear set. The basic layout of these machines is illustrated. The test rig is formed by two gear pairs, of the same reduction ratio, a test gear pair and a reaction gear pair, connected to each other through shafts of certain torsional flexibility to form an efficient, closed-loop system. A desired level of constant torque is input to the circuit through mechanical (a split coupling with a torque arm) or hydraulic (a hydraulic actuator) means. The system is then driven at any desired speed by a small DC motor. The main task in hand is the isolation of the test gear pair from the reaction gear pair under dynamic conditions. Any disturbances originated at the reaction gear mesh might potentially travel to the test gearbox, altering the dynamic loading conditions of the test gear mesh, and hence, influencing the outcome of the durability or dynamics test. Therefore, a proper design of connecting structures becomes a major priority. Also, equally important is the issue of how close the operating speed of the machine is to the resonant frequencies of the gear meshes. This study focuses on a detailed analysis of the current NASA Glenn Research Center gear pitting test machine for evaluation of its resonance and vibration isolation characteristics. A number of these machines as the one illustrated has been used over last 30 years to establish an extensive database regarding the influence of the gear materials, processes surface treatments and lubricants on gear durability. This study is intended to guide an optimum design of next generation test machines for the most desirable dynamic characteristics.

Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

PubMed

Bozkurt, Selen; Bostanci, Asli; Turhan, Murat

2017-08-11

The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic variables: 1) clinical data, 2) symptoms and 3) physical examination. In order to produce classification models for OSA severity, five different machine learning methods (Bayesian network, Decision Tree, Random Forest, Neural Networks and Logistic Regression) were trained while relevant variables and their relationships were derived empirically from observed data. Each model was trained and evaluated using 10-fold cross-validation and to evaluate classification performances of all methods, true positive rate (TPR), false positive rate (FPR), Positive Predictive Value (PPV), F measure and Area Under Receiver Operating Characteristics curve (ROC-AUC) were used. Results of 10-fold cross validated tests with different variable settings promisingly indicated that the OSA severity of suspected OSA patients can be classified, using non-polysomnographic features, with 0.71 true positive rate as the highest and, 0.15 false positive rate as the lowest, respectively. Moreover, the test results of different variables settings revealed that the accuracy of the classification models was significantly improved when physical examination variables were added to the model. Study results showed that machine learning methods can be used to estimate the probabilities of no, mild, moderate, and severe obstructive sleep apnea and such approaches may improve accurate initial OSA screening and help referring only the suspected moderate or severe OSA patients to sleep laboratories for the expensive tests.

Evaluating the accuracy of tooth color measurement by combining the Munsell color system and dental colorimeter.

PubMed

Chang, Jiun-Yao; Chen, Wen-Cheng; Huang, Ta-Ko; Wang, Jen-Chyan; Fu, Po-Sung; Chen, Jeng-Huey; Hung, Chun-Cheng

2012-09-01

As we pay increasing attention to dental aesthetics, tooth color matching has become an important part of daily dental practice. This aim of this study was to develop a method to enhance the accuracy of a tooth color matching machine. The Munsell color tabs in the range of natural human teeth were measured using a tooth color measuring machine (ShadeEye NCC). The machine's accuracy was analyzed using an analysis of variance test and a Tukey post-hoc test. When matching the Munsell color tabs with the ShadeEye NCC colorimeter, settings of Chroma greater than 6 and Value less than 4 showed unacceptable clinical results. When the CIELAB mode was used, the a* value (which represents the red-green axis in the Commission Internationale de l'Eclairage color space) made no significant difference (p=0.84), the L* value (which represents the lightness) resulted in a negative correlation, and the b* value (which represents the yellow-blue axis) resulted in a positive correlation with ΔE. When the Munsell color tabs and the Vitapan were measured in the same mode and compared, the inaccuracies showed that the Vitapan was not a proper tool for evaluating the stability and accuracy of ShadeEye NCC. By knowing the limitations of the machine, we evaluated the data using the Munsell color tabs; shade beyond the acceptable range should be reevaluated using a visual shade matching method, or if measured by another machine, this shade range should be covered to obtain more accurate results. Copyright © 2012. Published by Elsevier B.V.

Distribution of man-machine controls in space teleoperation

NASA Technical Reports Server (NTRS)

Bejczy, A. K.

1982-01-01

The distribution of control between man and machine is dependent on the tasks, available technology, human performance characteristics and control goals. This dependency has very specific projections on systems designed for teleoperation in space. This paper gives a brief outline of the space-related issues and presents the results of advanced teleoperator research and development at the Jet Propulsion Laboratory (JPL). The research and development work includes smart sensors, flexible computer controls and intelligent man-machine interface devices in the area of visual displays and kinesthetic man-machine coupling in remote control of manipulators. Some of the development results have been tested at the Johnson Space Center (JSC) using the simulated full-scale Shuttle Remote Manipulator System (RMS). The research and development work for advanced space teleoperation is far from complete and poses many interdisciplinary challenges.

Simulation of router action on a lathe to test the cutting tool performance in edge-trimming of graphite/epoxy composite

NASA Astrophysics Data System (ADS)

Ramulu, M.; Rogers, E.

1994-04-01

The predominant machining application with graphite/epoxy composite materials in aerospace industry is peripheral trimming. The computer numerically controlled (CNC) high speed routers required to do edge trimming work are generally scheduled for production work in industry and are not available for extensive cutter testing. Therefore, an experimental method of simulating the conditions of periphery trim using a lathe is developed in this paper. The validity of the test technique will be demonstrated by conducting carbide tool wear tests under dry cutting conditions. The experimental results will be analyzed to characterize the wear behavior of carbide cutting tools in machining the composite materials.

Can Machine Scoring Deal with Broad and Open Writing Tests as Well as Human Readers?

ERIC Educational Resources Information Center

McCurry, Doug

2010-01-01

This article considers the claim that machine scoring of writing test responses agrees with human readers as much as humans agree with other humans. These claims about the reliability of machine scoring of writing are usually based on specific and constrained writing tasks, and there is reason for asking whether machine scoring of writing requires…

Automation of energy demand forecasting

NASA Astrophysics Data System (ADS)

Siddique, Sanzad

Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

Blood Test: Estradiol

MedlinePlus

... for this test. On the day of the test, having your child wear a T-shirt or short-sleeved shirt can ... The blood sample will be processed by a machine. The results usually are available within a few days. Risks The estradiol blood test is considered a safe procedure. However, as with ...

Time to B. cereus about hot chocolate.

PubMed

Nelms, P K; Larson, O; Barnes-Josiah, D

1997-01-01

To determine the cause of illnesses experienced by employees of a Minneapolis manufacturing plant after drinking hot chocolate bought from a vending machine and to explore the prevalence of similar vending machine-related illnesses. The authors inspected the vending machines at the manufacturing plant where employees reported illnesses and at other locations in the city where hot chocolate beverages were sold in machines. Tests were performed on dry mix, water, and beverage samples and on machine parts. Laboratory analyses confirmed the presence of B. cereus in dispensed beverages at a concentration capable of causing illness (170,000 count/gm). In citywide testing of vending machines dispensing hot chocolate, 7 of the 39 licensed machines were found to be contaminated, with two contaminated machines having B. cereus levels capable of causing illness. Hot chocolate sold in vending machines may contain organisms capable of producing toxins that under favorable conditions, can induce illness. Such illnesses are likely to be underreported. Even low concentrations of B. cereus may be dangerous for vulnerable populations such as the aged or immunosuppressed. Periodic testing of vending machines is thus warranted. The relationship between cleaning practices and B. cereus contamination is an issue for further study.

Tensile properties of nicalon fiber-reinforced carbon following aerospace turbine engine testing

NASA Astrophysics Data System (ADS)

Pierce, J. L.; Zawada, L. P.; Srinivasan, R.

2003-06-01

The durability of coated Nicalon silicon carbide fiber-reinforced carbon (SiC/C) as the flap and seal exhaust nozzle components in a military aerospace turbine engine was studied. Test specimens machined from both a flap and a seal component were tested for residual strength following extended ground engine testing on a General Electric F414 afterburning turbofan engine. Although small amounts of damage to the protective exterior coating were identified on each component following engine testing, the tensile strengths were equal to the as-fabricated tensile strength of the material. Differences in strength between the two components and variability within the data sets could be traced back to the fabrication process using witness coupon test data from the manufacturer. It was also observed that test specimens machined transversely across the flap and seal components were stronger than those machined along the length. The excellent retained strength of the coated SiC/C material after extended exposure to the severe environment in the afterburner exhaust section of an aerospace turbofan engine has resulted in this material being selected as the baseline material for the F414 exhaust nozzle system.

Design of a hydraulic bending machine

Treesearch

Steven G. Hankel; Marshall Begel

2004-01-01

To keep pace with customer demands while phasing out old and unserviceable test equipment, the staff of the Engineering Mechanics Laboratory (EML) at the USDA Forest Service, Forest Products Laboratory, designed and assembled a hydraulic bending test machine. The EML built this machine to test dimension lumber, nominal 2 in. thick and up to 12 in. deep, at spans up to...

Machine Tests Optical Fibers In Flexure

NASA Technical Reports Server (NTRS)

Darejeh, Hadi; Thomas, Henry; Delcher, Ray

1993-01-01

Machine repeatedly flexes single optical fiber or cable or bundle of optical fibers at low temperature. Liquid nitrogen surrounds specimen as it is bent back and forth by motion of piston. Machine inexpensive to build and operate. Tests under repeatable conditions so candidate fibers, cables, and bundles evaluated for general robustness before subjected to expensive shock and vibration tests.

A new class of high-G and long-duration shock testing machines

NASA Astrophysics Data System (ADS)

Rastegar, Jahangir

2018-03-01

Currently available methods and systems for testing components for survival and performance under shock loading suffer from several shortcomings for use to simulate high-G acceleration events with relatively long duration. Such events include most munitions firing and target impact, vehicular accidents, drops from relatively high heights, air drops, impact between machine components, and other similar events. In this paper, a new class of shock testing machines are presented that can be used to subject components to be tested to high-G acceleration pulses of prescribed amplitudes and relatively long durations. The machines provide for highly repeatable testing of components. The components are mounted on an open platform for ease of instrumentation and video recording of their dynamic behavior during shock loading tests.

Efficient forced vibration reanalysis method for rotating electric machines

NASA Astrophysics Data System (ADS)

Saito, Akira; Suzuki, Hiromitsu; Kuroishi, Masakatsu; Nakai, Hideo

2015-01-01

Rotating electric machines are subject to forced vibration by magnetic force excitation with wide-band frequency spectrum that are dependent on the operating conditions. Therefore, when designing the electric machines, it is inevitable to compute the vibration response of the machines at various operating conditions efficiently and accurately. This paper presents an efficient frequency-domain vibration analysis method for the electric machines. The method enables the efficient re-analysis of the vibration response of electric machines at various operating conditions without the necessity to re-compute the harmonic response by finite element analyses. Theoretical background of the proposed method is provided, which is based on the modal reduction of the magnetic force excitation by a set of amplitude-modulated standing-waves. The method is applied to the forced response vibration of the interior permanent magnet motor at a fixed operating condition. The results computed by the proposed method agree very well with those computed by the conventional harmonic response analysis by the FEA. The proposed method is then applied to the spin-up test condition to demonstrate its applicability to various operating conditions. It is observed that the proposed method can successfully be applied to the spin-up test conditions, and the measured dominant frequency peaks in the frequency response can be well captured by the proposed approach.

Machined versus roughened immediately loaded and finally restored single implants inserted flapless: Preliminary 6-month data from a split- mouth randomised controlled trial.

PubMed

Cannizzaro, Gioacchino; Felice, Pietro; Loi, Ignazio; Viola, Paolo; Ferri, Vittorio; Leone, Michele; Lazzarini, Matteo; Trullenque-Eriksson, Anna; Esposito, Marco

To compare the outcome of immediately loaded single implants with a machined or a roughened surface. Fifty patients had two implant sites randomly allocated to receive flaplessplaced single Syra implants (Sweden & Martina), one with a machined and one with a roughened surface (sand-blasted with zirconia powder and acid etched), according to a split-mouth design. To be loaded immediately, implants had to be inserted with a torque superior to 50 Ncm. Implants were restored with definitive crowns in direct occlusal contact within 48 h. Patients were followed for 6 months after loading. Outcome measures were prosthetic and implant failures and complications. Two machined implants and four roughened implants were not loaded immediately. Six months after loading no dropout occurred. One implant loaded late, which had a rough implant surface, failed 20 days after loading (P (McNemar test) = 0.625; difference in proportions = -0.04; 95% CI: -0.15 to 0.07). Three crowns had to be remade on machined implants and four on roughened implants (P (McNemar test) = 1.000; difference in proportions = -0.02; 95% CI: -0.12 to 0.08). Three machined and five roughened implants experienced complications (P (McNemar test) = 0.625; difference in proportions = -0.04; 95% CI: -0.15 to 0.07). There were no statistically significant differences between groups for crown and implant losses as well as complications. Up to 6 months after loading both machined and roughened flapless-placed and immediately loaded single implants provided good and similar results, however, longer follow-ups are needed to evaluate the long-term prognosis of implants with different surfaces.

Application de la methode de la reponse frequentielle a l'arret "SSFR", sur une machine synchrone a poles saillants de grande puissance

NASA Astrophysics Data System (ADS)

Belqorchi, Abdelghafour

Forty years after Watson and Manchur conducted the Stand-Still Frequency Response (SSFR) test on a large turbogenerator, the applicability of this technic on a powerful salient pole synchronous generator has yet to be confirmed. The scientific literature on the subject is rare and very few have attempted to compare SSFR parameter results with those deduced by classical tests. The validity of SSFR on large salient pole machines has still to be proven. The present work aims in participating to fill this knowledge gap. It can be used to build a database of measurements highly needed to draw the validity of the technic. Also, the author hopes to demonstrate the potential of SSFR model to represent the machine, not only in cases of weak disturbances but also strong ones such as instantaneous three-phase short-circuit faults. The difficulties raised by previous searchers are: The lack of accuracy in very low frequency measurements; The difficulty in rotor positioning, according to d and q axes, in case of salient pole machines; The measurement current level influence on magnetizing inductances, in axes-d and; The rotation impact on damper circuits for some rotors design. Aware of the above difficulties, the author conducted an SSFR test on a large salient pole machine (285 MVA). The generator under test has laminated non isolated rotor and an integral slot number. The damper windings in adjacent poles are connected together, via the polar core and the rotor rim. Finally, the damping circuit is unaffected by rotation. To improve the measurement accuracy, in very low frequencies, the most precise frequency response analyser available on the market was used. Besides, the frequency responses of the signals conditioning modules (i.e., isolation, amplification...) were accounted for to correct the four measured SSFR transfer functions. Immunization against noise and use of instrumentation in their optimum range, were other technics rigorously applied. Magnetizing inductances, being influenced by the measurement current magnitude, the latter was maintained constant in the range 1mHz-20Hz. Other problems such as the rotation impact on damper circuits or the difficulty of rotor positioning are eliminated or attenuated by the intrinsic characteristics of the machine. Regarding the data analysis, the Maximum Likelihood Estimation (MLE) method was used to determine the third and second order equivalent circuit from SSFR measurements. In d-axis, the approaches of adjustment to two and three transfer functions (Ld(s), sG(s) and Lafo(s)) were explored. The second order model, derived from (Ld( s) and G(s)), was used to deduce the machine standard parameters. The latter were compared with the values given by the manufacturer and by conventional on-site tests: Instantaneous three-phase short-circuit, Dalton-Cameron and the d-axis transient time constant at open stator (T'do). The comparison showed the good accuracy of SSFR values. Subsequently, a machine model was built in EMTP-RV based on SSFR standard parameters. The model was able to reproduce stator and rotor currents measured during instantaneous three-phase short-circuit test. Some adjustments, to SSFR parameters, were needed to reproduce stator voltage and rotor current acquired during load rejection d-axis test. It is worthwhile noting that the load rejection d-axis test, recently added to IEEE 115-2009 annex, must be modified to take into account the saturation and excitation impedance impact on deduced parameters. Regarding this issue, some suggestions are proposed by the author. The obtained SSFR results, contribute to raise confidence on SSFR application on large salient pole machines. In addition, it shows the aptitude of the SSFR model to represent the machine in both cases of weak and strong disturbances, at least on machines similar the one studied. Index Terms: Salient pole, frequency response, SSFR, equivalent circuit, operational inductance.

Analysis of 3D printing parameters of gears for hybrid manufacturing

NASA Astrophysics Data System (ADS)

Budzik, Grzegorz; Przeszlowski, Łukasz; Wieczorowski, Michal; Rzucidlo, Arkadiusz; Gapinski, Bartosz; Krolczyk, Grzegorz

2018-05-01

The paper deals with analysis and selection of parameters of rapid prototyping of gears by selective sintering of metal powders. Presented results show wide spectrum of application of RP systems in manufacturing processes of machine elements, basing on analysis of market in term of application of additive manufacturing technology in different sectors of industry. Considerable growth of these methods over the past years can be observed. The characteristic errors of printed model with respect to ideal one for each technique were pointed out. Special attention was paid to the method of preparation of numerical data CAD/STL/RP. Moreover the analysis of manufacturing processes of gear type elements was presented. The tested gears were modeled with different allowances for final machining and made by DMLS. Metallographic analysis and strength tests on prepared specimens were performed. The above mentioned analysis and tests were used to compare the real properties of material with the nominal ones. To improve the quality of surface after sintering the gears were subjected to final machining. The analysis of geometry of gears after hybrid manufacturing method was performed (fig.1). The manufacturing process was defined in a traditional way as well as with the aid of modern manufacturing techniques. Methodology and obtained results can be used for other machine elements than gears and constitutes the general theory of production processes in rapid prototyping methods as well as in designing and implementation of production.

Classifying BCI signals from novice users with extreme learning machine

NASA Astrophysics Data System (ADS)

Rodríguez-Bermúdez, Germán; Bueno-Crespo, Andrés; José Martinez-Albaladejo, F.

2017-07-01

Brain computer interface (BCI) allows to control external devices only with the electrical activity of the brain. In order to improve the system, several approaches have been proposed. However it is usual to test algorithms with standard BCI signals from experts users or from repositories available on Internet. In this work, extreme learning machine (ELM) has been tested with signals from 5 novel users to compare with standard classification algorithms. Experimental results show that ELM is a suitable method to classify electroencephalogram signals from novice users.

Comparison of polyester, film-yarn composite, balloon materials subjected to shear and biaxial loading

NASA Technical Reports Server (NTRS)

Niccum, R. J.

1972-01-01

A series of candidate materials for use in large balloons was tested and their tensile and shear strength capabilities were compared. The tests were done in a cold box at -68 C (-90 F). Some of these materials were fabricated on a special machine called the flying thread loom. This machine laminates various patterns of polyester yarn to a thin polyester film. The results show that the shear strength of materials changes with the angle selected for the transverse yarns, and substantial increases in biaxial load carrying capabilities, compared to materials formerly used, are possible. The loom capabilities and the test methods are discussed.

Extreme learning machine: a new alternative for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters.

PubMed

Liu, Zhijian; Li, Hao; Tang, Xindong; Zhang, Xinyu; Lin, Fan; Cheng, Kewei

2016-01-01

Heat collection rate and heat loss coefficient are crucial indicators for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, wasting too much time and manpower. To address this problem, we previously used artificial neural networks and support vector machine to develop precise knowledge-based models for predicting the heat collection rates and heat loss coefficients of water-in-glass evacuated tube solar water heaters, setting the properties measured by "portable test instruments" as the independent variables. A robust software for determination was also developed. However, in previous results, the prediction accuracy of heat loss coefficients can still be improved compared to those of heat collection rates. Also, in practical applications, even a small reduction in root mean square errors (RMSEs) can sometimes significantly improve the evaluation and business processes. As a further study, in this short report, we show that using a novel and fast machine learning algorithm-extreme learning machine can generate better predicted results for heat loss coefficient, which reduces the average RMSEs to 0.67 in testing.

Motor-response learning at a process control panel by an autonomous robot

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spelt, P.F.; de Saussure, G.; Lyness, E.

1988-01-01

The Center for Engineering Systems Advanced Research (CESAR) was founded at Oak Ridge National Laboratory (ORNL) by the Department of Energy's Office of Energy Research/Division of Engineering and Geoscience (DOE-OER/DEG) to conduct basic research in the area of intelligent machines. Therefore, researchers at the CESAR Laboratory are engaged in a variety of research activities in the field of machine learning. In this paper, we describe our approach to a class of machine learning which involves motor response acquisition using feedback from trial-and-error learning. Our formulation is being experimentally validated using an autonomous robot, learning tasks of control panel monitoring andmore » manipulation for effect process control. The CLIPS Expert System and the associated knowledge base used by the robot in the learning process, which reside in a hypercube computer aboard the robot, are described in detail. Benchmark testing of the learning process on a robot/control panel simulation system consisting of two intercommunicating computers is presented, along with results of sample problems used to train and test the expert system. These data illustrate machine learning and the resulting performance improvement in the robot for problems similar to, but not identical with, those on which the robot was trained. Conclusions are drawn concerning the learning problems, and implications for future work on machine learning for autonomous robots are discussed. 16 refs., 4 figs., 1 tab.« less

Study of the Effect of Lubricant Emulsion Percentage and Tool Material on Surface Roughness in Machining of EN-AC 48000 Alloy

NASA Astrophysics Data System (ADS)

Soltani, E.; Shahali, H.; Zarepour, H.

2011-01-01

In this paper, the effect of machining parameters, namely, lubricant emulsion percentage and tool material on surface roughness has been studied in machining process of EN-AC 48000 aluminum alloy. EN-AC 48000 aluminum alloy is an important alloy in industries. Machining of this alloy is of vital importance due to built-up edge and tool wear. A L9 Taguchi standard orthogonal array has been applied as experimental design to investigate the effect of the factors and their interaction. Nine machining tests have been carried out with three random replications resulting in 27 experiments. Three type of cutting tools including coated carbide (CD1810), uncoated carbide (H10), and polycrystalline diamond (CD10) have been used in this research. Emulsion percentage of lubricant is selected at three levels including 3%, 5% and 10%. Statistical analysis has been employed to study the effect of factors and their interactions using ANOVA method. Moreover, the optimal factors level has been achieved through signal to noise ratio (S/N) analysis. Also, a regression model has been provided to predict the surface roughness. Finally, the results of the confirmation tests have been presented to verify the adequacy of the predictive model. In this research, surface quality was improved by 9% using lubricant and statistical optimization method.

Predicting Mouse Liver Microsomal Stability with “Pruned” Machine Learning Models and Public Data

PubMed Central

Perryman, Alexander L.; Stratton, Thomas P.; Ekins, Sean; Freundlich, Joel S.

2015-01-01

Purpose Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Methods Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). Results “Pruning” out the moderately unstable/moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 hour. Conclusions Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources. PMID:26415647

Precise on-machine extraction of the surface normal vector using an eddy current sensor array

NASA Astrophysics Data System (ADS)

Wang, Yongqing; Lian, Meng; Liu, Haibo; Ying, Yangwei; Sheng, Xianjun

2016-11-01

To satisfy the requirements of on-machine measurement of the surface normal during complex surface manufacturing, a highly robust normal vector extraction method using an Eddy current (EC) displacement sensor array is developed, the output of which is almost unaffected by surface brightness, machining coolant and environmental noise. A precise normal vector extraction model based on a triangular-distributed EC sensor array is first established. Calibration of the effects of object surface inclination and coupling interference on measurement results, and the relative position of EC sensors, is involved. A novel apparatus employing three EC sensors and a force transducer was designed, which can be easily integrated into the computer numerical control (CNC) machine tool spindle and/or robot terminal execution. Finally, to test the validity and practicability of the proposed method, typical experiments were conducted with specified testing pieces using the developed approach and system, such as an inclined plane and cylindrical and spherical surfaces.

Using Linguistic Knowledge in Statistical Machine Translation

DTIC Science & Technology

2010-09-01

on newswire test data . . . . . . . . . . . . . . . . . . . . . 65 3.4 Arabic to English MT results for Arabic morphological segmentation, measured on...web test data. . . . . . . . . . . . . . . . . . . . . . . . 65 3.5 Recombination Results. Percentage of sentences with mis-combined words...scores for syntactic reordering of the Spoken Language Domain. 90 5.1 Normalized likelihood of the test set alignments without decision trees, and then

Ada (Tradename) Compiler Validation Summary Report. International Business Machines Corporation. IBM Development System for the Ada Language for VM/CMS, Version 1.0. IBM 4381 (IBM System/370) under VM/CMS.

DTIC Science & Technology

1986-04-29

COMPILER VALIDATION SUMMARY REPORT: International Business Machines Corporation IBM Development System for the Ada Language for VM/CMS, Version 1.0 IBM 4381...tested using command scripts provided by International Business Machines Corporation. These scripts were reviewed by the validation team. Test.s were run...s): IBM 4381 (System/370) Operating System: VM/CMS, release 3.6 International Business Machines Corporation has made no deliberate extensions to the

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2013 CFR

2013-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2012 CFR

2012-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2014 CFR

2014-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

Time-Frequency Learning Machines for Nonstationarity Detection Using Surrogates

NASA Astrophysics Data System (ADS)

Borgnat, Pierre; Flandrin, Patrick; Richard, Cédric; Ferrari, André; Amoud, Hassan; Honeine, Paul

2012-03-01

Time-frequency representations provide a powerful tool for nonstationary signal analysis and classification, supporting a wide range of applications [12]. As opposed to conventional Fourier analysis, these techniques reveal the evolution in time of the spectral content of signals. In Ref. [7,38], time-frequency analysis is used to test stationarity of any signal. The proposed method consists of a comparison between global and local time-frequency features. The originality is to make use of a family of stationary surrogate signals for defining the null hypothesis of stationarity and, based upon this information, to derive statistical tests. An open question remains, however, about how to choose relevant time-frequency features. Over the last decade, a number of new pattern recognition methods based on reproducing kernels have been introduced. These learning machines have gained popularity due to their conceptual simplicity and their outstanding performance [30]. Initiated by Vapnik’s support vector machines (SVM) [35], they offer now a wide class of supervised and unsupervised learning algorithms. In Ref. [17-19], the authors have shown how the most effective and innovative learning machines can be tuned to operate in the time-frequency domain. This chapter follows this line of research by taking advantage of learning machines to test and quantify stationarity. Based on one-class SVM, our approach uses the entire time-frequency representation and does not require arbitrary feature extraction. Applied to a set of surrogates, it provides the domain boundary that includes most of these stationarized signals. This allows us to test the stationarity of the signal under investigation. This chapter is organized as follows. In Section 22.2, we introduce the surrogate data method to generate stationarized signals, namely, the null hypothesis of stationarity. The concept of time-frequency learning machines is presented in Section 22.3, and applied to one-class SVM in order to derive a stationarity test in Section 22.4. The relevance of the latter is illustrated by simulation results in Section 22.5.

Spindle Thermal Error Optimization Modeling of a Five-axis Machine Tool

NASA Astrophysics Data System (ADS)

Guo, Qianjian; Fan, Shuo; Xu, Rufeng; Cheng, Xiang; Zhao, Guoyong; Yang, Jianguo

2017-05-01

Aiming at the problem of low machining accuracy and uncontrollable thermal errors of NC machine tools, spindle thermal error measurement, modeling and compensation of a two turntable five-axis machine tool are researched. Measurement experiment of heat sources and thermal errors are carried out, and GRA(grey relational analysis) method is introduced into the selection of temperature variables used for thermal error modeling. In order to analyze the influence of different heat sources on spindle thermal errors, an ANN (artificial neural network) model is presented, and ABC(artificial bee colony) algorithm is introduced to train the link weights of ANN, a new ABC-NN(Artificial bee colony-based neural network) modeling method is proposed and used in the prediction of spindle thermal errors. In order to test the prediction performance of ABC-NN model, an experiment system is developed, the prediction results of LSR (least squares regression), ANN and ABC-NN are compared with the measurement results of spindle thermal errors. Experiment results show that the prediction accuracy of ABC-NN model is higher than LSR and ANN, and the residual error is smaller than 3 μm, the new modeling method is feasible. The proposed research provides instruction to compensate thermal errors and improve machining accuracy of NC machine tools.

Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: a case study

NASA Astrophysics Data System (ADS)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani; Kareem, Buliaminu

2016-03-01

This article describes the integration of temperature and vibration models for maintenance monitoring of conventional machinery parts in which their optimal and best functionalities are affected by abnormal changes in temperature and vibration values thereby resulting in machine failures, machines breakdown, poor quality of products, inability to meeting customers' demand, poor inventory control and just to mention a few. The work entails the use of temperature and vibration sensors as monitoring probes programmed in microcontroller using C language. The developed hardware consists of vibration sensor of ADXL345, temperature sensor of AD594/595 of type K thermocouple, microcontroller, graphic liquid crystal display, real time clock, etc. The hardware is divided into two: one is based at the workstation (majorly meant to monitor machines behaviour) and the other at the base station (meant to receive transmission of machines information sent from the workstation), working cooperatively for effective functionalities. The resulting hardware built was calibrated, tested using model verification and validated through principles pivoted on least square and regression analysis approach using data read from the gear boxes of extruding and cutting machines used for polyethylene bag production. The results got therein confirmed related correlation existing between time, vibration and temperature, which are reflections of effective formulation of the developed concept.

Research on electrodischarge drilling of polycrystalline diamond with increased gap voltage

NASA Astrophysics Data System (ADS)

Skoczypiec, Sebastian; Bizoń, Wojciech; Żyra, Agnieszka

2018-05-01

This paper presents an experimental investigation of the machining characteristics of polycrystalline diamond (PCD). Machining of PCD by conventional technologies is not an effective solution. Due to presence of cobalt this material can be machined by application of electrical discharges. On the other side, electrical conductivity of PCD is on the limit of electrodischarge machining (EDM) possibilities. Proposed paper reports experimental investigation on electrodischarge drilling of PCD samples. The test were carried out with application on of high-voltage (up to 550 V) pulse power unit for two kinds of dielectrics: carbon based (Exxsol D80) and de-ionized water. As output parameters machining accuracy (side gap), material removal rate were selected. Also, based on SEM photographs and energy dispersive X-ray spectroscopy (EDS) analysis, a qualitative evaluation of the obtained results was presented.

Reactive power generation in high speed induction machines by continuously occurring space-transients

NASA Astrophysics Data System (ADS)

Laithwaite, E. R.; Kuznetsov, S. B.

1980-09-01

A new technique of continuously generating reactive power from the stator of a brushless induction machine is conceived and tested on a 10-kw linear machine and on 35 and 150 rotary cage motors. An auxiliary magnetic wave traveling at rotor speed is artificially created by the space-transient attributable to the asymmetrical stator winding. At least two distinct windings of different pole-pitch must be incorporated. This rotor wave drifts in and out of phase repeatedly with the stator MMF wave proper and the resulting modulation of the airgap flux is used to generate reactive VA apart from that required for magnetization or leakage flux. The VAR generation effect increases with machine size, and leading power factor operation of the entire machine is viable for large industrial motors and power system induction generators.

Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV).

PubMed

Piette, Elizabeth R; Moore, Jason H

2018-01-01

Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning analyses of GWAS can be hampered by biological and statistical factors, particularly so for the investigation of non-additive genetic interactions. Application of traditional cross validation to a GWAS data set may result in poor consistency between the training and testing data set splits due to an imbalance of the interaction genotypes relative to the data as a whole. We propose a new cross validation method, proportional instance cross validation (PICV), that preserves the original distribution of an independent variable when splitting the data set into training and testing partitions. We apply PICV to simulated GWAS data with epistatic interactions of varying minor allele frequencies and prevalences and compare performance to that of a traditional cross validation procedure in which individuals are randomly allocated to training and testing partitions. Sensitivity and positive predictive value are significantly improved across all tested scenarios for PICV compared to traditional cross validation. We also apply PICV to GWAS data from a study of primary open-angle glaucoma to investigate a previously-reported interaction, which fails to significantly replicate; PICV however improves the consistency of testing and training results. Application of traditional machine learning procedures to biomedical data may require modifications to better suit intrinsic characteristics of the data, such as the potential for highly imbalanced genotype distributions in the case of epistasis detection. The reproducibility of genetic interaction findings can be improved by considering this variable imbalance in cross validation implementation, such as with PICV. This approach may be extended to problems in other domains in which imbalanced variable distributions are a concern.

Space fabrication demonstration system: Executive summary. [for large space structures

NASA Technical Reports Server (NTRS)

1979-01-01

The results of analysis and tests conducted to define the basic 1-m beam configuration required, and the design, development, fabrication, and verification tests of the machine required to automatically produce these beams are presented.

In situ surface roughness measurement using a laser scattering method

NASA Astrophysics Data System (ADS)

Tay, C. J.; Wang, S. H.; Quan, C.; Shang, H. M.

2003-03-01

In this paper, the design and development of an optical probe for in situ measurement of surface roughness are discussed. Based on this light scattering principle, the probe which consists of a laser diode, measuring lens and a linear photodiode array, is designed to capture the scattered light from a test surface with a relatively large scattering angle ϕ (=28°). This capability increases the measuring range and enhances repeatability of the results. The coaxial arrangement that incorporates a dual-laser beam and a constant compressed air stream renders the proposed system insensitive to movement or vibration of the test surface as well as surface conditions. Tests were conducted on workpieces which were mounted on a turning machine that operates with different cutting speeds. Test specimens which underwent different machining processes and of different surface finish were also studied. The results obtained demonstrate the feasibility of surface roughness measurement using the proposed method.

Effects of Notch Misalignment and Tip Radius on Displacement Field in V-Notch Rail Shear Test as Determined by Photogrammetry

NASA Technical Reports Server (NTRS)

Hill, Charles S.; Oliveras, Ovidio M.

2011-01-01

Evolution of the 3D strain field during ASTM-D-7078 v-notch rail shear tests on 8-ply quasi-isotropic carbon fiber/epoxy laminates was determined by optical photogrammetry using an ARAMIS system. Specimens having non-optimal geometry and minor discrepancies in dimensional tolerances were shown to display non-symmetry and/or stress concentration in the vicinity of the notch relative to a specimen meeting the requirements of the standard, but resulting shear strength and modulus values remained within acceptable bounds of standard deviation. Based on these results, and reported difficulty machining specimens to the required tolerances using available methods, it is suggested that a parametric study combining analytical methods and experiment may provide rationale to increase the tolerances on some specimen dimensions, reducing machining costs, increasing the proportion of acceptable results, and enabling a wider adoption of the test method.

Open-source software for collision detection in external beam radiation therapy

NASA Astrophysics Data System (ADS)

Suriyakumar, Vinith M.; Xu, Renee; Pinter, Csaba; Fichtinger, Gabor

2017-03-01

PURPOSE: Collision detection for external beam radiation therapy (RT) is important for eliminating the need for dryruns that aim to ensure patient safety. Commercial treatment planning systems (TPS) offer this feature but they are expensive and proprietary. Cobalt-60 RT machines are a viable solution to RT practice in low-budget scenarios. However, such clinics are hesitant to invest in these machines due to a lack of affordable treatment planning software. We propose the creation of an open-source room's eye view visualization module with automated collision detection as part of the development of an open-source TPS. METHODS: An openly accessible linac 3D geometry model is sliced into the different components of the treatment machine. The model's movements are based on the International Electrotechnical Commission standard. Automated collision detection is implemented between the treatment machine's components. RESULTS: The room's eye view module was built in C++ as part of SlicerRT, an RT research toolkit built on 3D Slicer. The module was tested using head and neck and prostate RT plans. These tests verified that the module accurately modeled the movements of the treatment machine and radiation beam. Automated collision detection was verified using tests where geometric parameters of the machine's components were changed, demonstrating accurate collision detection. CONCLUSION: Room's eye view visualization and automated collision detection are essential in a Cobalt-60 treatment planning system. Development of these features will advance the creation of an open-source TPS that will potentially help increase the feasibility of adopting Cobalt-60 RT.

Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder.

PubMed

Mwangi, Benson; Ebmeier, Klaus P; Matthews, Keith; Steele, J Douglas

2012-05-01

Quantitative abnormalities of brain structure in patients with major depressive disorder have been reported at a group level for decades. However, these structural differences appear subtle in comparison with conventional radiologically defined abnormalities, with considerable inter-subject variability. Consequently, it has not been possible to readily identify scans from patients with major depressive disorder at an individual level. Recently, machine learning techniques such as relevance vector machines and support vector machines have been applied to predictive classification of individual scans with variable success. Here we describe a novel hybrid method, which combines machine learning with feature selection and characterization, with the latter aimed at maximizing the accuracy of machine learning prediction. The method was tested using a multi-centre dataset of T(1)-weighted 'structural' scans. A total of 62 patients with major depressive disorder and matched controls were recruited from referred secondary care clinical populations in Aberdeen and Edinburgh, UK. The generalization ability and predictive accuracy of the classifiers was tested using data left out of the training process. High prediction accuracy was achieved (~90%). While feature selection was important for maximizing high predictive accuracy with machine learning, feature characterization contributed only a modest improvement to relevance vector machine-based prediction (~5%). Notably, while the only information provided for training the classifiers was T(1)-weighted scans plus a categorical label (major depressive disorder versus controls), both relevance vector machine and support vector machine 'weighting factors' (used for making predictions) correlated strongly with subjective ratings of illness severity. These results indicate that machine learning techniques have the potential to inform clinical practice and research, as they can make accurate predictions about brain scan data from individual subjects. Furthermore, machine learning weighting factors may reflect an objective biomarker of major depressive disorder illness severity, based on abnormalities of brain structure.

Experimental research of kinetic and dynamic characteristics of temperature movements of machines

NASA Astrophysics Data System (ADS)

Parfenov, I. V.; Polyakov, A. N.

2018-03-01

Nowadays, the urgency of informational support of machines at different stages of their life cycle is increasing in the form of various experimental characteristics that determine the criteria for working capacity. The effectiveness of forming the base of experimental characteristics of machines is related directly to the duration of their field tests. In this research, the authors consider a new technique that allows reducing the duration of full-scale testing of machines by 30%. To this end, three new indicator coefficients were calculated in real time to determine the moments corresponding to the characteristic points. In the work, new terms for thermal characteristics of machine tools are introduced: kinetic and dynamic characteristics of the temperature movements of the machine. This allow taking into account not only the experimental values for the temperature displacements of the elements of the carrier system of the machine, but also their derivatives up to the third order, inclusively. The work is based on experimental data obtained in the course of full-scale thermal tests of a drilling-milling and boring CNC machine.

High speed operation of permanent magnet machines

NASA Astrophysics Data System (ADS)

El-Refaie, Ayman M.

This work proposes methods to extend the high-speed operating capabilities of both the interior PM (IPM) and surface PM (SPM) machines. For interior PM machines, this research has developed and presented the first thorough analysis of how a new bi-state magnetic material can be usefully applied to the design of IPM machines. Key elements of this contribution include identifying how the unique properties of the bi-state magnetic material can be applied most effectively in the rotor design of an IPM machine by "unmagnetizing" the magnet cavity center posts rather than the outer bridges. The importance of elevated rotor speed in making the best use of the bi-state magnetic material while recognizing its limitations has been identified. For surface PM machines, this research has provided, for the first time, a clear explanation of how fractional-slot concentrated windings can be applied to SPM machines in order to achieve the necessary conditions for optimal flux weakening. A closed-form analytical procedure for analyzing SPM machines designed with concentrated windings has been developed. Guidelines for designing SPM machines using concentrated windings in order to achieve optimum flux weakening are provided. Analytical and numerical finite element analysis (FEA) results have provided promising evidence of the scalability of the concentrated winding technique with respect to the number of poles, machine aspect ratio, and output power rating. Useful comparisons between the predicted performance characteristics of SPM machines equipped with concentrated windings and both SPM and IPM machines designed with distributed windings are included. Analytical techniques have been used to evaluate the impact of the high pole number on various converter performance metrics. Both analytical techniques and FEA have been used for evaluating the eddy-current losses in the surface magnets due to the stator winding subharmonics. Techniques for reducing these losses have been investigated. A 6kW, 36slot/30pole prototype SPM machine has been designed and built. Experimental measurements have been used to verify the analytical and FEA results. These test results have demonstrated that wide constant-power speed range can be achieved. Other important machine features such as the near-sinusoidal back-emf, high efficiency, and low cogging torque have also been demonstrated.

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

PubMed

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further using multiple metrics with much larger scale comparisons, prospective testing as well as assessment of different fingerprints and DNN architectures beyond those used.

Extra high speed modified Lundell alternator parameters and open/short-circuit characteristics from global 3D-FE magnetic field solutions

NASA Astrophysics Data System (ADS)

Wang, R.; Demerdash, N. A.

1992-06-01

The combined magnetic vector potential - magnetic scalar potential method of computation of 3D magnetic fields by finite elements, introduced in a companion paper, is used for global 3D field analysis and machine performance computations under open-circuit and short-circuit conditions for an example 14.3 kVA modified Lundell alternator, whose magnetic field is of intrinsic 3D nature. The computed voltages and currents under these machine test conditions were verified and found to be in very good agreement with corresponding test data. Results of use of this modelling and computation method in the study of a design alteration example, in which the stator stack length of the example alternator is stretched in order to increase voltage and volt-ampere rating, are given here. These results demonstrate the inadequacy of conventional 2D-based design concepts and the imperative of use of this type of 3D magnetic field modelling in the design and investigation of such machines.

Extra high speed modified Lundell alternator parameters and open/short-circuit characteristics from global 3D-FE magnetic field solutions

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1992-01-01

The combined magnetic vector potential - magnetic scalar potential method of computation of 3D magnetic fields by finite elements, introduced in a companion paper, is used for global 3D field analysis and machine performance computations under open-circuit and short-circuit conditions for an example 14.3 kVA modified Lundell alternator, whose magnetic field is of intrinsic 3D nature. The computed voltages and currents under these machine test conditions were verified and found to be in very good agreement with corresponding test data. Results of use of this modelling and computation method in the study of a design alteration example, in which the stator stack length of the example alternator is stretched in order to increase voltage and volt-ampere rating, are given here. These results demonstrate the inadequacy of conventional 2D-based design concepts and the imperative of use of this type of 3D magnetic field modelling in the design and investigation of such machines.

An Adaptive Genetic Association Test Using Double Kernel Machines.

PubMed

Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

2015-10-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

Chemical Demilitarization - Assembled Chemical Weapons Assessment (ACWA): Root Cause Analysis

DTIC Science & Technology

2011-07-01

BGCAPP, supercritical water oxidation (SCWO) will subject the hydrolysate to very high temperatures and pressures, breaking it down into carbon dioxide ...ANS. The resulting hydrolysates from both the chemical and energetic process are then broken down into carbon dioxide , water and salts in the SCWO...Cutter Machine RDT&E Research, Development, Test and Evaluation RSM Rocket Shear Machine SAR Selected Acquisition Report SCWO Supercritical Water

Long-range nanopositioning and nanomeasuring machine for application to micro- and nanotechnology

NASA Astrophysics Data System (ADS)

Jäger, Gerd; Hausotte, Tino; Büchner, Hans-Joachim; Manske, Eberhard; Schmidt, Ingomar; Mastylo, Rostyslav

2006-03-01

The paper describes the operation of a high-precision long range three-dimensional nanopositioning and nanomeasuring machine (NPM-Machine). The NPM-Machine has been developed by the Institute of Process Measurement and Sensor Technology of the Technische Universität Ilmenau. The machine was successfully tested and continually improved in the last few years. The machines are operating successfully in several German and foreign research institutes including the Physikalisch-Technische Bundesanstalt (PTB). Three plane mirror miniature interferometers are installed into the NPM-machine having a resolution of less than 0,1 nm over the entire positioning and measuring range of 25 mm x 25 mm x 5 mm. An Abbe offset-free design of the three miniature plane mirror interferometers and applying a new concept for compensating systematic errors resulting from mechanical guide systems provide extraordinary accuracy with an expanded uncertainty of only 5 - 10 nm. The integration of several, optical and tactile probe systems and nanotools makes the NPM-Machine suitable for various tasks, such as large-area scanning probe microscopy, mask and wafer inspection, nanostructuring, biotechnology and genetic engineering as well as measuring mechanical precision workpieces, precision treatment and for engineering new material. Various developed probe systems have been integrated into the NPM-Machine. The measurement results of a focus sensor, metrological AFM, white light sensor, tactile stylus probe and of a 3D-micro-touch-probe are presented. Single beam-, double beam- and triple beam interferometers built in the NPM-Machine for six degrees of freedom measurements are described.

Optimising the laboratory supply chain: The key to effective laboratory services

PubMed Central

Williams, Jason; Smith, Peter; Kuritsky, Joel

2014-01-01

Background The Supply Chain Management System (SCMS) is a contract managed under the Partnership for Supply Chain Management (PFSCM) consortium by the United States Agency for International Development (USAID). SCMS procures commodities for programmes supported by the US President’s Emergency Plan for AIDS Relief (PEPFAR). From 2005 to mid-2012, PEPFAR, through SCMS, spent approximately $384 million on non-pharmaceutical commodities. Of this, an estimated $90m was used to purchase flow cytometry technology, largely for flow cytometry platforms and reagents. Objectives The purpose of this paper is to highlight the cost differences between low, medium and high utilisation rates of common CD4 testing instruments that have been procured though PEPFAR funding. Method A scale of costs per test as a function of test volume through the machine was calculated for the two most common CD4 testing machines used in HIV programmes: Becton Dickinson (BD) FACSCount™ and BD FACSCalibur™. Instrument utilisation data collected at the facility level in three selected countries were then used to calculate the onsite cost-per-test experienced in each country. Results Cost analyses indicated that a target of at least 40% utilisation for FACSCount™ and 15% utilisation for FACSCalibur™, respectively, closely approach maximal per-test cost efficiency. The average utilisation rate for CD4 testing instruments varies widely by country, level of laboratory and partner (0% − 68%). Conclusion Our analysis indicates that, because cost-per-test is related inversely to sample throughput, the underutilisation of flow cytometry machines is resulting in an increase in average cost-per-test for many instruments. PMID:29043175

Prediction of Skin Sensitization with a Particle Swarm Optimized Support Vector Machine

PubMed Central

Yuan, Hua; Huang, Jianping; Cao, Chenzhong

2009-01-01

Skin sensitization is the most commonly reported occupational illness, causing much suffering to a wide range of people. Identification and labeling of environmental allergens is urgently required to protect people from skin sensitization. The guinea pig maximization test (GPMT) and murine local lymph node assay (LLNA) are the two most important in vivo models for identification of skin sensitizers. In order to reduce the number of animal tests, quantitative structure-activity relationships (QSARs) are strongly encouraged in the assessment of skin sensitization of chemicals. This paper has investigated the skin sensitization potential of 162 compounds with LLNA results and 92 compounds with GPMT results using a support vector machine. A particle swarm optimization algorithm was implemented for feature selection from a large number of molecular descriptors calculated by Dragon. For the LLNA data set, the classification accuracies are 95.37% and 88.89% for the training and the test sets, respectively. For the GPMT data set, the classification accuracies are 91.80% and 90.32% for the training and the test sets, respectively. The classification performances were greatly improved compared to those reported in the literature, indicating that the support vector machine optimized by particle swarm in this paper is competent for the identification of skin sensitizers. PMID:19742136

Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.

PubMed

Kunimatsu, Akira; Kunimatsu, Natsuko; Yasaka, Koichiro; Akai, Hiroyuki; Kamiya, Kouhei; Watadani, Takeyuki; Mori, Harushi; Abe, Osamu

2018-05-16

Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classification by support vector machine, a method of traditional machine learning, using texture features computed from contrast-enhanced T 1 -weighted images. This retrospective study on preoperative brain tumor MRI included 76 consecutives, initially treated patients with glioblastoma (n = 55) or PCNSL (n = 21) from one institution, consisting of independent training group (n = 60: 44 glioblastomas and 16 PCNSLs) and test group (n = 16: 11 glioblastomas and 5 PCNSLs) sequentially separated by time periods. A total set of 67 texture features was computed on routine contrast-enhanced T 1 -weighted images of the training group, and the top four most discriminating features were selected as input variables to train support vector machine classifiers. These features were then evaluated on the test group with subsequent image classification. The area under the receiver operating characteristic curves on the training data was calculated at 0.99 (95% confidence interval [CI]: 0.96-1.00) for the classifier with a Gaussian kernel and 0.87 (95% CI: 0.77-0.95) for the classifier with a linear kernel. On the test data, both of the classifiers showed prediction accuracy of 75% (12/16) of the test images. Although further improvement is needed, our preliminary results suggest that machine learning-based image classification may provide complementary diagnostic information on routine brain MRI.

10 CFR 431.295 - Units to be tested.

Code of Federal Regulations, 2011 CFR

2011-01-01

... EQUIPMENT Refrigerated Bottled or Canned Beverage Vending Machines Test Procedures § 431.295 Units to be tested. For each basic model of refrigerated bottled or canned beverage vending machine selected for...

Copper Hugoniot measurements to 2.8 TPa on Z.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Furnish, Michael D.; Haill, Thomas A

We conducted three Hugoniot and release experiments on copper on the Z machine at Hugoniot stress levels of 0.34 and 2.6 TPa, using two-layer copper/aluminum impactors travelling at 8 and 27 km/s and Z-quartz windows. Velocity histories were recorded for 4 samples of different thicknesses and 5 locations on the flyer plate (3 and 4 for the first two experiments). On-sample measurements provided Hugoniot points (via transit time) and partial release states (via Z-quartz wavespeed). Fabrication of the impactor required thick plating and several diamond-machining steps. The lower-pressure test was planned as a 2.5 TPa test, but a failure onmore » the Z machine degraded its performance; however, these results corroborated earlier Cu data in the same stress region. The second test suffered from significant flyer plate bowing, but the third did not. The Hugoniot data are compared with the APtshuler/Nellis nuclear-driven data, other data from Z and elsewhere, and representative Sesame models.« less

Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains

PubMed Central

Souza, Junior Silva; da Silva, Gercina Gonçalves

2016-01-01

The classification of pollen species and types is an important task in many areas like forensic palynology, archaeological palynology and melissopalynology. This paper presents the first annotated image dataset for the Brazilian Savannah pollen types that can be used to train and test computer vision based automatic pollen classifiers. A first baseline human and computer performance for this dataset has been established using 805 pollen images of 23 pollen types. In order to access the computer performance, a combination of three feature extractors and four machine learning techniques has been implemented, fine tuned and tested. The results of these tests are also presented in this paper. PMID:27276196

Characterization of Subsurface Defects in Ceramic Rods by Laser Scattering and Fractography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, J. M.; Sun, J. G.; Andrews, M. J.

2006-03-06

Silicon nitride ceramics are leading materials being evaluated for valve train components in diesel engine applications. The surface and subsurface defects and damage induced by surface machining can significantly affect component strength and lifetime. In this study, a nondestructive evaluation (NDE) technique based upon laser scattering has been utilized to analyze eight transversely ground silicon nitride cylindrical rods before fracture tests. The fracture origins (machining cracks or material-inherent flaws) identified by fractography after fracture testing were correlated with laser scattering images. The results indicate that laser scattering is able to identify possible fracture origin in the silicon nitride subsurface withoutmore » the need for destructive fracture tests.« less

Relevance Vector Machine and Support Vector Machine Classifier Analysis of Scanning Laser Polarimetry Retinal Nerve Fiber Layer Measurements

PubMed Central

Bowd, Christopher; Medeiros, Felipe A.; Zhang, Zuohua; Zangwill, Linda M.; Hao, Jiucang; Lee, Te-Won; Sejnowski, Terrence J.; Weinreb, Robert N.; Goldbaum, Michael H.

2010-01-01

Purpose To classify healthy and glaucomatous eyes using relevance vector machine (RVM) and support vector machine (SVM) learning classifiers trained on retinal nerve fiber layer (RNFL) thickness measurements obtained by scanning laser polarimetry (SLP). Methods Seventy-two eyes of 72 healthy control subjects (average age = 64.3 ± 8.8 years, visual field mean deviation =−0.71 ± 1.2 dB) and 92 eyes of 92 patients with glaucoma (average age = 66.9 ± 8.9 years, visual field mean deviation =−5.32 ± 4.0 dB) were imaged with SLP with variable corneal compensation (GDx VCC; Laser Diagnostic Technologies, San Diego, CA). RVM and SVM learning classifiers were trained and tested on SLP-determined RNFL thickness measurements from 14 standard parameters and 64 sectors (approximately 5.6° each) obtained in the circumpapillary area under the instrument-defined measurement ellipse (total 78 parameters). Tenfold cross-validation was used to train and test RVM and SVM classifiers on unique subsets of the full 164-eye data set and areas under the receiver operating characteristic (AUROC) curve for the classification of eyes in the test set were generated. AUROC curve results from RVM and SVM were compared to those for 14 SLP software-generated global and regional RNFL thickness parameters. Also reported was the AUROC curve for the GDx VCC software-generated nerve fiber indicator (NFI). Results The AUROC curves for RVM and SVM were 0.90 and 0.91, respectively, and increased to 0.93 and 0.94 when the training sets were optimized with sequential forward and backward selection (resulting in reduced dimensional data sets). AUROC curves for optimized RVM and SVM were significantly larger than those for all individual SLP parameters. The AUROC curve for the NFI was 0.87. Conclusions Results from RVM and SVM trained on SLP RNFL thickness measurements are similar and provide accurate classification of glaucomatous and healthy eyes. RVM may be preferable to SVM, because it provides a Bayesian-derived probability of glaucoma as an output. These results suggest that these machine learning classifiers show good potential for glaucoma diagnosis. PMID:15790898

Binary pressure-sensitive paint measurements using miniaturised, colour, machine vision cameras

NASA Astrophysics Data System (ADS)

Quinn, Mark Kenneth

2018-05-01

Recent advances in machine vision technology and capability have led to machine vision cameras becoming applicable for scientific imaging. This study aims to demonstrate the applicability of machine vision colour cameras for the measurement of dual-component pressure-sensitive paint (PSP). The presence of a second luminophore component in the PSP mixture significantly reduces its inherent temperature sensitivity, increasing its applicability at low speeds. All of the devices tested are smaller than the cooled CCD cameras traditionally used and most are of significantly lower cost, thereby increasing the accessibility of such technology and techniques. Comparisons between three machine vision cameras, a three CCD camera, and a commercially available specialist PSP camera are made on a range of parameters, and a detailed PSP calibration is conducted in a static calibration chamber. The findings demonstrate that colour machine vision cameras can be used for quantitative, dual-component, pressure measurements. These results give rise to the possibility of performing on-board dual-component PSP measurements in wind tunnels or on real flight/road vehicles.

Currency crisis indication by using ensembles of support vector machine classifiers

NASA Astrophysics Data System (ADS)

Ramli, Nor Azuana; Ismail, Mohd Tahir; Wooi, Hooy Chee

2014-07-01

There are many methods that had been experimented in the analysis of currency crisis. However, not all methods could provide accurate indications. This paper introduces an ensemble of classifiers by using Support Vector Machine that's never been applied in analyses involving currency crisis before with the aim of increasing the indication accuracy. The proposed ensemble classifiers' performances are measured using percentage of accuracy, root mean squared error (RMSE), area under the Receiver Operating Characteristics (ROC) curve and Type II error. The performances of an ensemble of Support Vector Machine classifiers are compared with the single Support Vector Machine classifier and both of classifiers are tested on the data set from 27 countries with 12 macroeconomic indicators for each country. From our analyses, the results show that the ensemble of Support Vector Machine classifiers outperforms single Support Vector Machine classifier on the problem involving indicating a currency crisis in terms of a range of standard measures for comparing the performance of classifiers.

Acceptability of using electronic vending machines to deliver oral rapid HIV self-testing kits: a qualitative study.

PubMed

Young, Sean D; Daniels, Joseph; Chiu, ChingChe J; Bolan, Robert K; Flynn, Risa P; Kwok, Justin; Klausner, Jeffrey D

2014-01-01

Rates of unrecognized HIV infection are significantly higher among Latino and Black men who have sex with men (MSM). Policy makers have proposed that HIV self-testing kits and new methods for delivering self-testing could improve testing uptake among minority MSM. This study sought to conduct qualitative assessments with MSM of color to determine the acceptability of using electronic vending machines to dispense HIV self-testing kits. African American and Latino MSM were recruited using a participant pool from an existing HIV prevention trial on Facebook. If participants expressed interest in using a vending machine to receive an HIV self-testing kit, they were emailed a 4-digit personal identification number (PIN) code to retrieve the test from the machine. We followed up with those who had tested to assess their willingness to participate in an interview about their experience. Twelve kits were dispensed and 8 interviews were conducted. In general, participants expressed that the vending machine was an acceptable HIV test delivery method due to its novelty and convenience. Acceptability of this delivery model for HIV testing kits was closely associated with three main factors: credibility, confidentiality, and convenience. Future research is needed to address issues, such as user-induced errors and costs, before scaling up the dispensing method.

Communication Studies of DMP and SMP Machines

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

Understanding the interplay between machines and problems is key to obtaining high performance on parallel machines. This paper investigates the interplay between programming paradigms and communication capabilities of parallel machines. In particular, we explicate the communication capabilities of the IBM SP-2 distributed-memory multiprocessor and the SGI PowerCHALLENGEarray symmetric multiprocessor. Two benchmark problems of bitonic sorting and Fast Fourier Transform are selected for experiments. Communication-efficient algorithms are developed to exploit the overlapping capabilities of the machines. Programs are written in Message-Passing Interface for portability and identical codes are used for both machines. Various data sizes and message sizes are used to test the machines' communication capabilities. Experimental results indicate that the communication performance of the multiprocessors are consistent with the size of messages. The SP-2 is sensitive to message size but yields a much higher communication overlapping because of the communication co-processor. The PowerCHALLENGEarray is not highly sensitive to message size and yields a low communication overlapping. Bitonic sorting yields lower performance compared to FFT due to a smaller computation-to-communication ratio.

Development of structural test articles from magnesium-lithium and beryllium

NASA Technical Reports Server (NTRS)

Alario, R.

1969-01-01

Study on the fabrication and testing of a magnesium-lithium box beam shows the formability and machinability characteristics of that alloy to be excellent. Results of forming tests for shrink and stretch flanges show values for both flange heights that may be used in future beryllium design.

Computational Fluid Dynamic Simulation of Flow in Abrasive Water Jet Machining

NASA Astrophysics Data System (ADS)

Venugopal, S.; Sathish, S.; Jothi Prakash, V. M.; Gopalakrishnan, T.

2017-03-01

Abrasive water jet cutting is one of the most recently developed non-traditional manufacturing technologies. In this machining, the abrasives are mixed with suspended liquid to form semi liquid mixture. The general nature of flow through the machining, results in fleeting wear of the nozzle which decrease the cutting performance. The inlet pressure of the abrasive water suspension has main effect on the major destruction characteristics of the inner surface of the nozzle. The aim of the project is to analyze the effect of inlet pressure on wall shear and exit kinetic energy. The analysis could be carried out by changing the taper angle of the nozzle, so as to obtain optimized process parameters for minimum nozzle wear. The two phase flow analysis would be carried by using computational fluid dynamics tool CFX. It is also used to analyze the flow characteristics of abrasive water jet machining on the inner surface of the nozzle. The availability of optimized process parameters of abrasive water jet machining (AWJM) is limited to water and experimental test can be cost prohibitive. In this case, Computational fluid dynamics analysis would provide better results.

Design and fabrication of a freeform phase plate for high-order ocular aberration correction

NASA Astrophysics Data System (ADS)

Yi, Allen Y.; Raasch, Thomas W.

2005-11-01

In recent years it has become possible to measure and in some instances to correct the high-order aberrations of human eyes. We have investigated the correction of wavefront error of human eyes by using phase plates designed to compensate for that error. The wavefront aberrations of the four eyes of two subjects were experimentally determined, and compensating phase plates were machined with an ultraprecision diamond-turning machine equipped with four independent axes. A slow-tool servo freeform trajectory was developed for the machine tool path. The machined phase-correction plates were measured and compared with the original design values to validate the process. The position of the phase-plate relative to the pupil is discussed. The practical utility of this mode of aberration correction was investigated with visual acuity testing. The results are consistent with the potential benefit of aberration correction but also underscore the critical positioning requirements of this mode of aberration correction. This process is described in detail from optical measurements, through machining process design and development, to final results.

A Real-Time Tool Positioning Sensor for Machine-Tools

PubMed Central

Ruiz, Antonio Ramon Jimenez; Rosas, Jorge Guevara; Granja, Fernando Seco; Honorato, Jose Carlos Prieto; Taboada, Jose Juan Esteve; Serrano, Vicente Mico; Jimenez, Teresa Molina

2009-01-01

In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool's drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations. PMID:22408472

Microstructural and hardness changes in aluminum alloy Al-7075: Correlating machining and equal channel angular pressing

NASA Astrophysics Data System (ADS)

Imbrogno, Stano; Segebade, Eric; Fellmeth, Andreas; Gerstenmeyer, Michael; Zanger, Frederik; Schulze, Volker; Umbrello, Domenico

2017-10-01

Recently, the study and understanding of surface integrity of various materials after machining is becoming one of the interpretative keys to quantify a product's quality and life cycle performance. The possibility to provide fundamental details about the mechanical response and the behavior of the affected material layers caused by thermo-mechanical loads resulting from machining operations can help the designer to produce parts with superior quality. The aim of this work is to study the experimental outcomes obtained from orthogonal cutting tests and a Severe Plastic Deformation (SPD) process known as Equal Channel Angular Pressing (ECAP) in order to find possible links regarding induced microstructural and hardness changes between machined surface layer and SPD-bulk material for Al-7075. This scientific investigation aims to establish the basis for an innovative method to study and quantify metallurgical phenomena that occur beneath the machined surface of bulk material.

Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

NASA Astrophysics Data System (ADS)

Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

2018-03-01

Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

A High Performance Torque Sensor for Milling Based on a Piezoresistive MEMS Strain Gauge

PubMed Central

Qin, Yafei; Zhao, Yulong; Li, Yingxue; Zhao, You; Wang, Peng

2016-01-01

In high speed and high precision machining applications, it is important to monitor the machining process in order to ensure high product quality. For this purpose, it is essential to develop a dynamometer with high sensitivity and high natural frequency which is suited to these conditions. This paper describes the design, calibration and performance of a milling torque sensor based on piezoresistive MEMS strain. A detailed design study is carried out to optimize the two mutually-contradictory indicators sensitivity and natural frequency. The developed torque sensor principally consists of a thin-walled cylinder, and a piezoresistive MEMS strain gauge bonded on the surface of the sensing element where the shear strain is maximum. The strain gauge includes eight piezoresistances and four are connected in a full Wheatstone circuit bridge, which is used to measure the applied torque force during machining procedures. Experimental static calibration results show that the sensitivity of torque sensor has been improved to 0.13 mv/Nm. A modal impact test indicates that the natural frequency of torque sensor reaches 1216 Hz, which is suitable for high speed machining processes. The dynamic test results indicate that the developed torque sensor is stable and practical for monitoring the milling process. PMID:27070620

Power training using pneumatic machines vs. plate-loaded machines to improve muscle power in older adults.

PubMed

Balachandran, Anoop T; Gandia, Kristine; Jacobs, Kevin A; Streiner, David L; Eltoukhy, Moataz; Signorile, Joseph F

2017-11-01

Power training has been shown to be more effective than conventional resistance training for improving physical function in older adults; however, most trials have used pneumatic machines during training. Considering that the general public typically has access to plate-loaded machines, the effectiveness and safety of power training using plate-loaded machines compared to pneumatic machines is an important consideration. The purpose of this investigation was to compare the effects of high-velocity training using pneumatic machines (Pn) versus standard plate-loaded machines (PL). Independently-living older adults, 60years or older were randomized into two groups: pneumatic machine (Pn, n=19) and plate-loaded machine (PL, n=17). After 12weeks of high-velocity training twice per week, groups were analyzed using an intention-to-treat approach. Primary outcomes were lower body power measured using a linear transducer and upper body power using medicine ball throw. Secondary outcomes included lower and upper body muscle muscle strength, the Physical Performance Battery (PPB), gallon jug test, the timed up-and-go test, and self-reported function using the Patient Reported Outcomes Measurement Information System (PROMIS) and an online video questionnaire. Outcome assessors were blinded to group membership. Lower body power significantly improved in both groups (Pn: 19%, PL: 31%), with no significant difference between the groups (Cohen's d=0.4, 95% CI (-1.1, 0.3)). Upper body power significantly improved only in the PL group, but showed no significant difference between the groups (Pn: 3%, PL: 6%). For balance, there was a significant difference between the groups favoring the Pn group (d=0.7, 95% CI (0.1, 1.4)); however, there were no statistically significant differences between groups for PPB, gallon jug transfer, muscle muscle strength, timed up-and-go or self-reported function. No serious adverse events were reported in either of the groups. Pneumatic and plate-loaded machines were effective in improving lower body power and physical function in older adults. The results suggest that power training can be safely and effectively performed by older adults using either pneumatic or plate-loaded machines. Copyright © 2017 Elsevier Inc. All rights reserved.

An Adaptive Genetic Association Test Using Double Kernel Machines

PubMed Central

Zhan, Xiang; Epstein, Michael P.; Ghosh, Debashis

2014-01-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study. PMID:26640602

Estimation of wear in total hip replacement using a ten station hip simulator.

PubMed

Brummitt, K; Hardaker, C S

1996-01-01

The results of hip simulator tests on a total of 16 total hip joints, all of them 22.25 mm Charnley designs, are presented. Wear at up to 6.75 million cycles was assessed by using a coordinate measuring machine. The results gave good agreement with clinical estimates of wear rate on the same design of joint replacement from a number of sources. Good agreement was also obtained when comparison was made with the published results from more sophisticated simulators. The major source of variation in the results was found to occur in the first million cycles where creep predominates. The results of this study support the use of this type of simplified simulator for estimating wear in a total hip prosthesis. The capability to test a significant number of joints simultaneously may make this mechanism preferable to more complex machines in many cases.

Novel diesel exhaust filters for underground mining vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bickel, K.L.; Taubert, T.R.

1995-12-31

The U.S. Bureau of Mines (USBM) pioneered the development of disposable filters for reducing diesel particulate emissions from permissible mining machines. The USBM is now evaluating filter media that can withstand the high exhaust temperatures on nonpermissible machines. The goal of the evaluation is to find an inexpensive medium that can be cleaned or disposed of after use, and will reduce particulate emissions by 50 % or more. This report summarizes the results from screening tests of a lava rock and woven fiberglass filter media. The lava rock media exhibited low collection efficiencies, but with very low increases in exhaustmore » back pressure. Preliminary results indicate a collection efficiency exceeding 80 % for the woven fiber media. Testing of both media is continuing.« less

Could machine learning improve the prediction of pelvic nodal status of prostate cancer patients? Preliminary results of a pilot study.

PubMed

De Bari, B; Vallati, M; Gatta, R; Simeone, C; Girelli, G; Ricardi, U; Meattini, I; Gabriele, P; Bellavita, R; Krengli, M; Cafaro, I; Cagna, E; Bunkheila, F; Borghesi, S; Signor, M; Di Marco, A; Bertoni, F; Stefanacci, M; Pasinetti, N; Buglione, M; Magrini, S M

2015-07-01

We tested and compared performances of Roach formula, Partin tables and of three Machine Learning (ML) based algorithms based on decision trees in identifying N+ prostate cancer (PC). 1,555 cN0 and 50 cN+ PC were analyzed. Results were also verified on an independent population of 204 operated cN0 patients, with a known pN status (187 pN0, 17 pN1 patients). ML performed better, also when tested on the surgical population, with accuracy, specificity, and sensitivity ranging between 48-86%, 35-91%, and 17-79%, respectively. ML potentially allows better prediction of the nodal status of PC, potentially allowing a better tailoring of pelvic irradiation.

[The testing system for OCP of the digital X-ray machine].

PubMed

Wang, Yan; Mo, Guoming; Wang, Juru; Zhou, Tao; Yu, Jianguo

2011-09-01

In this paper, we designed a testing system for operator control panel of a high-voltage and high-frequency X-ray machine, and an online testing software for functional components, in order to help the testing engineers to improve their work efficiency.

Sample Holder for Cryogenic Adhesive Shear Test

NASA Technical Reports Server (NTRS)

Ledbetter, F. E.; Clemons, J. M.; White, W. T.; Penn, B.; Semmel, M. L.

1983-01-01

Five samples tested in one cooldown. Holder mounted in testing machine. Submerged in cryogenic liquid held in cryostat. Movable crosshead of testing machine moves gradually downward. Samples placed under tension, one after another, starting with top one; each sample fails in turn before next is stressed.

CD process control through machine learning

NASA Astrophysics Data System (ADS)

Utzny, Clemens

2016-10-01

For the specific requirements of the 14nm and 20nm site applications a new CD map approach was developed at the AMTC. This approach relies on a well established machine learning technique called recursive partitioning. Recursive partitioning is a powerful technique which creates a decision tree by successively testing whether the quantity of interest can be explained by one of the supplied covariates. The test performed is generally a statistical test with a pre-supplied significance level. Once the test indicates significant association between the variable of interest and a covariate a split performed at a threshold value which minimizes the variation within the newly attained groups. This partitioning is recurred until either no significant association can be detected or the resulting sub group size falls below a pre-supplied level.

Mechanical Testing of Common-Use Polymeric Materials with an In-House-Built Apparatus

ERIC Educational Resources Information Center

Pedrosa, Cristiana; Mendes, Joaquim; Magalhaes, Fernao D.

2006-01-01

A low-cost tensile testing machine was built for testing polymeric films. This apparatus also allows for tear-strength and flexural tests. The experimental results, obtained from common-use materials, selected by the students, such as plastic bags, illustrate important aspects of the mechanical behavior of polymeric materials. Some of the tests…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saleh, Z; Tang, X; Song, Y

Purpose: To investigate the long term stability and viability of using EPID-based daily output QA via in-house and vendor driven protocol, to replace conventional QA tools and improve QA efficiency. Methods: Two Varian TrueBeam machines (TB1&TB2) equipped with electronic portal imaging devices (EPID) were employed in this study. Both machines were calibrated per TG-51 and used clinically since Oct 2014. Daily output measurement for 6/15 MV beams were obtained using SunNuclear DailyQA3 device as part of morning QA. In addition, in-house protocol was implemented for EPID output measurement (10×10 cm fields, 100 MU, 100cm SID, output defined over an ROImore » of 2×2 cm around central axis). Moreover, the Varian Machine Performance Check (MPC) was used on both machines to measure machine output. The EPID and DailyQA3 based measurements of the relative machine output were compared and cross-correlated with monthly machine output as measured by an A12 Exradin 0.65cc Ion Chamber (IC) serving as ground truth. The results were correlated using Pearson test. Results: The correlations among DailyQA3, in-house EPID and Varian MPC output measurements, with the IC for 6/15 MV were similar for TB1 (0.83–0.95) and TB2 (0.55–0.67). The machine output for the 6/15MV beams on both machines showed a similar trend, namely an increase over time as indicated by all measurements, requiring a machine recalibration after 6 months. This drift is due to a known issue with pressurized monitor chamber which tends to leak over time. MPC failed occasionally but passed when repeated. Conclusion: The results indicate that the use of EPID for daily output measurements has the potential to become a viable and efficient tool for daily routine LINAC QA, thus eliminating weather (T,P) and human setup variability and increasing efficiency of the QA process.« less

Deployment and evaluation of a dual-sensor autofocusing method for on-machine measurement of patterns of small holes on freeform surfaces.

PubMed

Chen, Xiaomei; Longstaff, Andrew; Fletcher, Simon; Myers, Alan

2014-04-01

This paper presents and evaluates an active dual-sensor autofocusing system that combines an optical vision sensor and a tactile probe for autofocusing on arrays of small holes on freeform surfaces. The system has been tested on a two-axis test rig and then integrated onto a three-axis computer numerical control (CNC) milling machine, where the aim is to rapidly and controllably measure the hole position errors while the part is still on the machine. The principle of operation is for the tactile probe to locate the nominal positions of holes, and the optical vision sensor follows to focus and capture the images of the holes. The images are then processed to provide hole position measurement. In this paper, the autofocusing deviations are analyzed. First, the deviations caused by the geometric errors of the axes on which the dual-sensor unit is deployed are estimated to be 11 μm when deployed on a test rig and 7 μm on the CNC machine tool. Subsequently, the autofocusing deviations caused by the interaction of the tactile probe, surface, and small hole are mathematically analyzed and evaluated. The deviations are a result of the tactile probe radius, the curvatures at the positions where small holes are drilled on the freeform surface, and the effect of the position error of the hole on focusing. An example case study is provided for the measurement of a pattern of small holes on an elliptical cylinder on the two machines. The absolute sum of the autofocusing deviations is 118 μm on the test rig and 144 μm on the machine tool. This is much less than the 500 μm depth of field of the optical microscope. Therefore, the method is capable of capturing a group of clear images of the small holes on this workpiece for either implementation.

Real-Time Deflection Monitoring for Milling of a Thin-Walled Workpiece by Using PVDF Thin-Film Sensors with a Cantilevered Beam as a Case Study

PubMed Central

Luo, Ming; Liu, Dongsheng; Luo, Huan

2016-01-01

Thin-walled workpieces, such as aero-engine blisks and casings, are usually made of hard-to-cut materials. The wall thickness is very small and it is easy to deflect during milling process under dynamic cutting forces, leading to inaccurate workpiece dimensions and poor surface integrity. To understand the workpiece deflection behavior in a machining process, a new real-time nonintrusive method for deflection monitoring is presented, and a detailed analysis of workpiece deflection for different machining stages of the whole machining process is discussed. The thin-film polyvinylidene fluoride (PVDF) sensor is attached to the non-machining surface of the workpiece to copy the deflection excited by the dynamic cutting force. The relationship between the input deflection and the output voltage of the monitoring system is calibrated by testing. Monitored workpiece deflection results show that the workpiece experiences obvious vibration during the cutter entering the workpiece stage, and vibration during the machining process can be easily tracked by monitoring the deflection of the workpiece. During the cutter exiting the workpiece stage, the workpiece experiences forced vibration firstly, and free vibration exists until the amplitude reduces to zero after the cutter exits the workpiece. Machining results confirmed the suitability of the deflection monitoring system for machining thin-walled workpieces with the application of PVDF sensors. PMID:27626424

A Power Transformers Fault Diagnosis Model Based on Three DGA Ratios and PSO Optimization SVM

NASA Astrophysics Data System (ADS)

Ma, Hongzhe; Zhang, Wei; Wu, Rongrong; Yang, Chunyan

2018-03-01

In order to make up for the shortcomings of existing transformer fault diagnosis methods in dissolved gas-in-oil analysis (DGA) feature selection and parameter optimization, a transformer fault diagnosis model based on the three DGA ratios and particle swarm optimization (PSO) optimize support vector machine (SVM) is proposed. Using transforming support vector machine to the nonlinear and multi-classification SVM, establishing the particle swarm optimization to optimize the SVM multi classification model, and conducting transformer fault diagnosis combined with the cross validation principle. The fault diagnosis results show that the average accuracy of test method is better than the standard support vector machine and genetic algorithm support vector machine, and the proposed method can effectively improve the accuracy of transformer fault diagnosis is proved.

Reducing the uncertainty in robotic machining by modal analysis

NASA Astrophysics Data System (ADS)

Alberdi, Iñigo; Pelegay, Jose Angel; Arrazola, Pedro Jose; Ørskov, Klaus Bonde

2017-10-01

The use of industrial robots for machining could lead to high cost and energy savings for the manufacturing industry. Machining robots offer several advantages respect to CNC machines such as flexibility, wide working space, adaptability and relatively low cost. However, there are some drawbacks that are preventing a widespread adoption of robotic solutions namely lower stiffness, vibration/chatter problems and lower accuracy and repeatability. Normally due to these issues conservative cutting parameters are chosen, resulting in a low material removal rate (MRR). In this article, an example of a modal analysis of a robot is presented. For that purpose the Tap-testing technology is introduced, which aims at maximizing productivity, reducing the uncertainty in the selection of cutting parameters and offering a stable process free from chatter vibrations.

Automated inspection and precision grinding of spiral bevel gears

NASA Technical Reports Server (NTRS)

Frint, Harold

1987-01-01

The results are presented of a four phase MM&T program to define, develop, and evaluate an improved inspection system for spiral bevel gears. The improved method utilizes a multi-axis coordinate measuring machine which maps the working flank of the tooth and compares it to nominal reference values stored in the machine's computer. A unique feature of the system is that corrective grinding machine settings can be automatically calculated and printed out when necessary to correct an errant tooth profile. This new method eliminates most of the subjective decision making involved in the present method, which compares contact patterns obtained when the gear set is run under light load in a rolling test machine. It produces a higher quality gear with significant inspection time and cost savings.

Enhanced automated spiral bevel gear inspection

NASA Technical Reports Server (NTRS)

Frint, Harold K.; Glasow, Warren

1992-01-01

Presented here are the results of a manufacturing and technology program to define, develop, and evaluate an enhanced inspection system for spiral bevel gears. The method uses a multi-axis coordinate measuring machine which maps the working surface of the tooth and compares it with nominal reference values stored in the machine's computer. The enhanced technique features a means for automatically calculating corrective grinding machine settings, involving both first and second order changes, to control the tooth profile to within specified tolerance limits. This enhanced method eliminates the subjective decision making involved in the tooth patterning method, still in use today, which compares contract patterns obtained when the gear is set to run under light load in a rolling test machine. It produces a higher quality gear with significant inspection time and cost savings.

Stability Analysis of Radial Turning Process for Superalloys

NASA Astrophysics Data System (ADS)

Jiménez, Alberto; Boto, Fernando; Irigoien, Itziar; Sierra, Basilio; Suarez, Alfredo

2017-09-01

Stability detection in machining processes is an essential component for the design of efficient machining processes. Automatic methods are able to determine when instability is happening and prevent possible machine failures. In this work a variety of methods are proposed for detecting stability anomalies based on the measured forces in the radial turning process of superalloys. Two different methods are proposed to determine instabilities. Each one is tested on real data obtained in the machining of Waspalloy, Haynes 282 and Inconel 718. Experimental data, in both Conventional and High Pressure Coolant (HPC) environments, are set in four different states depending on materials grain size and Hardness (LGA, LGS, SGA and SGS). Results reveal that PCA method is useful for visualization of the process and detection of anomalies in online processes.

Reliability Analysis of Uniaxially Ground Brittle Materials

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.; Nemeth, Noel N.; Powers, Lynn M.; Choi, Sung R.

1995-01-01

The fast fracture strength distribution of uniaxially ground, alpha silicon carbide was investigated as a function of grinding angle relative to the principal stress direction in flexure. Both as-ground and ground/annealed surfaces were investigated. The resulting flexural strength distributions were used to verify reliability models and predict the strength distribution of larger plate specimens tested in biaxial flexure. Complete fractography was done on the specimens. Failures occurred from agglomerates, machining cracks, or hybrid flaws that consisted of a machining crack located at a processing agglomerate. Annealing eliminated failures due to machining damage. Reliability analyses were performed using two and three parameter Weibull and Batdorf methodologies. The Weibull size effect was demonstrated for machining flaws. Mixed mode reliability models reasonably predicted the strength distributions of uniaxial flexure and biaxial plate specimens.

Friction-Testing Machine

NASA Technical Reports Server (NTRS)

Benz, F. J.; Dixon, D. S.; Shaw, R. C.

1986-01-01

Testing machine evaluates wear and ignition characteristics of materials in rubbing contact. Offers advantages over other laboratory methods of measuring wear because it simulates operating conditions under which material will actually be used. Machine used to determine wear characteristics, rank and select materials for service with such active oxidizers as oxygen, halogens, and oxides of nitrogen, measure wear characteristics, and determine coefficients of friction.

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

PubMed

Pyo, Sujin; Lee, Jaewook; Cha, Mincheol; Jang, Huisu

2017-01-01

The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction.

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets

PubMed Central

Pyo, Sujin; Lee, Jaewook; Cha, Mincheol

2017-01-01

The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction. PMID:29136004

Improved multiple-shot gun for use as a combustion stability rating device

NASA Technical Reports Server (NTRS)

Sokolowski, D. E.

1973-01-01

A program was conducted to develop and experimentally evaluate an improved version of a modified machine gun for use as a device for rating the relative combustion stability of various rocket combustors. Following the results of a previous study involving a caliber .30 machine gun, a caliber .50 machine gun was modified in order to extend the charge-size range of the device. Nitrocellulose charge sizes ranging from 1.004 to 9.720 grams were fired at rates up to four shots per second. Shock pressures up to 25,512 kN/sq m were measured near the end of a shortened gun barrel. A minimal resistance type of check valve permitted the gun to fire into pressurized regions; back pressures up to 3448 kN/sq m abs were tested. The final modified assembly was evaluated during combustion stability tests on rocket combustors burning a FLOX-methane propellant combination.

DOE/NASA Mod-0 100KW wind turbine test results

NASA Technical Reports Server (NTRS)

Glasgow, J. C.

1978-01-01

The Wind Turbine demonstrates the capability of automatic unattended operation, including startup, achieving synchronism, and shutdown as dictated by wind conditions. During the course of these operations, a wealth of engineering data was generated. Some of the data which is associated with rotor and machine dynamics problems encountered, and the machine modifications incorporated as a solution are presented. These include high blade loads due to tower shadow, excessive nacelle yawing motion, and power oscillations. The results of efforts to correlate measured wind velocity with power output and wind turbine loads are also discussed.

Open Architecture Data System for NASA Langley Combined Loads Test System

NASA Technical Reports Server (NTRS)

Lightfoot, Michael C.; Ambur, Damodar R.

1998-01-01

The Combined Loads Test System (COLTS) is a new structures test complex that is being developed at NASA Langley Research Center (LaRC) to test large curved panels and cylindrical shell structures. These structural components are representative of aircraft fuselage sections of subsonic and supersonic transport aircraft and cryogenic tank structures of reusable launch vehicles. Test structures are subjected to combined loading conditions that simulate realistic flight load conditions. The facility consists of two pressure-box test machines and one combined loads test machine. Each test machine possesses a unique set of requirements or research data acquisition and real-time data display. Given the complex nature of the mechanical and thermal loads to be applied to the various research test articles, each data system has been designed with connectivity attributes that support both data acquisition and data management functions. This paper addresses the research driven data acquisition requirements for each test machine and demonstrates how an open architecture data system design not only meets those needs but provides robust data sharing between data systems including the various control systems which apply spectra of mechanical and thermal loading profiles.

Machining and characterization of self-reinforced polymers

NASA Astrophysics Data System (ADS)

Deepa, A.; Padmanabhan, K.; Kuppan, P.

2017-11-01

This Paper focuses on obtaining the mechanical properties and the effect of the different machining techniques on self-reinforced composites sample and to derive the best machining method with remarkable properties. Each sample was tested by the Tensile and Flexural tests, fabricated using hot compaction test and those loads were calculated. These composites are machined using conventional methods because of lack of advanced machinery in most of the industries. The advanced non-conventional methods like Abrasive water jet machining were used. These machining techniques are used to get the better output for the composite materials with good mechanical properties compared to conventional methods. But the use of non-conventional methods causes the changes in the work piece, tool properties and more economical compared to the conventional methods. Finding out the best method ideal for the designing of these Self Reinforced Composites with and without defects and the use of Scanning Electron Microscope (SEM) analysis for the comparing the microstructure of the PP and PE samples concludes our process.

Vision based nutrient deficiency classification in maize plants using multi class support vector machines

NASA Astrophysics Data System (ADS)

Leena, N.; Saju, K. K.

2018-04-01

Nutritional deficiencies in plants are a major concern for farmers as it affects productivity and thus profit. The work aims to classify nutritional deficiencies in maize plant in a non-destructive mannerusing image processing and machine learning techniques. The colored images of the leaves are analyzed and classified with multi-class support vector machine (SVM) method. Several images of maize leaves with known deficiencies like nitrogen, phosphorous and potassium (NPK) are used to train the SVM classifier prior to the classification of test images. The results show that the method was able to classify and identify nutritional deficiencies.

Performance of a plasma fluid code on the Intel parallel computers

NASA Technical Reports Server (NTRS)

Lynch, V. E.; Carreras, B. A.; Drake, J. B.; Leboeuf, J. N.; Liewer, P.

1992-01-01

One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchtone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchtone Delta machine, the corresponding improvement factor is 16. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel (sigma) machine gives an improvement factor close to 64 over the single-processor CRAY-2.

Laser-machined piezoelectric cantilevers for mechanical energy harvesting.

PubMed

Kim, HyunUk; Bedekar, Vishwas; Islam, Rashed Adnan; Lee, Woo-Ho; Leo, Don; Priya, Shashank

2008-09-01

In this study, we report results on a piezoelectric- material-based mechanical energy-harvesting device that was fabricated by combining laser machining with microelectronics packaging technology. It was found that the laser-machining process did not have significant effect on the electrical properties of piezoelectric material. The fabricated device was tested in the low-frequency regime of 50 to 1000 Hz at constant force of 8 g (where g = 9.8 m/s(2)). The device was found to generate continuous power of 1.13 microW at 870 Hz across a 288.5 kOmega load with a power density of 301.3 microW/cm(3).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, J; Hardin, M; Giaddui, T

Purpose: To test whether unified vendor specified beam conformance for matched machines implies volumetric modulated arc radiotherapy(VMAT) delivery consistency. Methods: Twenty-two identical patient QA plans, eleven 6MV and eleven 15MV, were delivered to the Delta{sup 4}(Scandidos, Uppsala, Sweden) on two Varian TrueBEAM matched machines. Sixteen patient QA plans, nine 6 MV and seven 10 MV, were delivered to Delta{sup 4} on two Elekta Agility matched machines. The percent dose deviation(%DDev), distance-to-agreement(DTA), and the gamma analysis(γ) were collected for all plans and the differences in measurements were tabulated between matched machines. A paired t-test analysis of the data with an alphamore » of 0.05 determines statistical significance. Power(P) was calculated to detect a difference of 5%; all data except Elekta %DDev sets were strong with above a 0.85 power. Results: The average differences for Varian machines (%DDev, DTA, and γ) are 6.4%, 1.6% and 2.7% for 6MV, respectively, and 8.0%, 0.6%, and 2.5% for 15MV. The average differences for matched Elekta machines (%DDev, DTA, and γ) are 10.2%, 0.6% and 0.9% for 6 MV, respectively, and 7.0%, 1.9%, and 2.8% for 10MV.A paired t-test shows for Varian the %DDev difference is significant for 6MV and 15MV(p-value6MV=0.019, P6MV=0.96; p-value15MV=0.0003, P15MV=0.86). Differences in DTA are insignificant for both 6MV and 15MV(p-value6MV=0.063, P6MV=1; p-value15MV=0.907, P15MV=1). Varian differences in gamma are significant for both energies(p-value6MV=0.025, P6MV=0.99; p-value15MV=0.013, P15MV=1). A paired t-test shows for Elekta the difference in %DDev is significant for 6MV but not 10MV(p-value6MV=0.00065, P6MV=0.68; p-value10MV=0.262, P10MV=0.39). Differences in DTA are statistically insignificant(p-value6MV=0.803, P6MV = 1; p-value10MV=0.269, P10MV=1). Elekta differences in gamma are significant for 10MV only(p-value6MV=0.094, P6MV=1; p-value10MV=0.011, P10MV=1). Conclusion: These results show vendor specified beam conformance across machines does not ensure equivalent patient specific QA pass rates. Gamma differences are statistically significant in three of the four comparisons for two pairs of vendor matched machines.« less

Daily sea level prediction at Chiayi coast, Taiwan using extreme learning machine and relevance vector machine

NASA Astrophysics Data System (ADS)

Imani, Moslem; Kao, Huan-Chin; Lan, Wen-Hau; Kuo, Chung-Yen

2018-02-01

The analysis and the prediction of sea level fluctuations are core requirements of marine meteorology and operational oceanography. Estimates of sea level with hours-to-days warning times are especially important for low-lying regions and coastal zone management. The primary purpose of this study is to examine the applicability and capability of extreme learning machine (ELM) and relevance vector machine (RVM) models for predicting sea level variations and compare their performances with powerful machine learning methods, namely, support vector machine (SVM) and radial basis function (RBF) models. The input dataset from the period of January 2004 to May 2011 used in the study was obtained from the Dongshi tide gauge station in Chiayi, Taiwan. Results showed that the ELM and RVM models outperformed the other methods. The performance of the RVM approach was superior in predicting the daily sea level time series given the minimum root mean square error of 34.73 mm and the maximum determination coefficient of 0.93 (R2) during the testing periods. Furthermore, the obtained results were in close agreement with the original tide-gauge data, which indicates that RVM approach is a promising alternative method for time series prediction and could be successfully used for daily sea level forecasts.

Parametric effects of turning Ti-6Al-4V alloys with aluminum oxide nanolubricants with SDBS

NASA Astrophysics Data System (ADS)

Ali, M. A. M.; Azmi, A. I.; Khalil, A. N. M.

2017-09-01

Applications of nanolubricants have been claimed to improve machinability of aerospace metals due to reduction of friction as a results of the rolling action of billions of nanoparticles at the tool-chip interface. In addition, the need to pursue for an eco-friendly machining has pushed researchers toward implementing alternative lubrication methods through minimal quantity lubrication (MQL). However, the gap in the current literature regarding the performance of nanolubricants via MQL has restricted the widespread use of this lubricant and technique in industries. The present work aims to understand the parametric effects of nanoparticles concentration, cutting speed, feed rate and nozzle angle during machining of titanium alloy, Ti-6AL-4V. Multiple performance of machinability outputs such as surface roughness, tool wear and power consumption were simultaneously determined via Taguchi orthogonal array and grey relational analyses. Prior to machining tests, the nanolubricants stabilities were investigated through the addition of surfactant; sodium dodecyl benzene sulfonate (SDBS). The results clearly indicated that inclusion of SDBS surfactant managed to reduce agglomeration in the base lubricant. Meanwhile, grey relational analyses revealed that the combination of 0.6 % nanoparticles concentration, cutting speed of 85 m/min, feed rate of 0.1 mm/rev and nozzle angle of 60o as desired setting for all the three machining outputs.

[Evaluation of the reliability of freight elevator operators].

PubMed

Gosk, A; Borodulin-Nadzieja, L; Janocha, A; Salomon, E

1991-01-01

The study involved 58 workers employed at winding machines. Their reliability was estimated from the results of psychomotoric test precision, condition of the vegetative nervous system, and from the results of psychological tests. The tests were carried out at the laboratory and at the workplaces, with all distractive factors and functional connection of the work process present. We have found that the reliability of the workers may be affected by a variety of factors. Among the winding machine operators, work monotony can lead to "monotony syndrome". Among the signalists , the appreciation of great responsibility can lead to unpredictable and non-adequate reactions. From both groups, persons displaying a lower-than-average precision were isolated. All those persons demonstrated a reckless attitude and the opinion of their superiors about them was poor. Those persons constitute potential risk for the reliable operation of the discussed team.

The use of fatigue tests in the manufacture of automotive steel wheels.

NASA Astrophysics Data System (ADS)

Drozyner, P.; Rychlik, A.

2016-08-01

Production for the automotive industry must be particularly sensitive to the aspect of safety and reliability of manufactured components. One of such element is the rim, where durability is a feature which significantly affects the safety of transport. Customer complaints regarding this element are particularly painful for the manufacturer because it is almost always associated with the event of accident or near-accident. Authors propose original comprehensive method of quality control at selected stages of rims production: supply of materials, production and pre-shipment inspections. Tests by the proposed method are carried out on the originally designed inertial fatigue machine The machine allows bending fatigue tests in the frequency range of 0 to 50 Hz at controlled increments of vibration amplitude. The method has been positively verified in one of rims factory in Poland. Implementation resulted in an almost complete elimination of complaints resulting from manufacturing and material errors.

Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

NASA Astrophysics Data System (ADS)

Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

2010-10-01

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

Reliability analysis of component of affination centrifugal 1 machine by using reliability engineering

NASA Astrophysics Data System (ADS)

Sembiring, N.; Ginting, E.; Darnello, T.

2017-12-01

Problems that appear in a company that produces refined sugar, the production floor has not reached the level of critical machine availability because it often suffered damage (breakdown). This results in a sudden loss of production time and production opportunities. This problem can be solved by Reliability Engineering method where the statistical approach to historical damage data is performed to see the pattern of the distribution. The method can provide a value of reliability, rate of damage, and availability level, of an machine during the maintenance time interval schedule. The result of distribution test to time inter-damage data (MTTF) flexible hose component is lognormal distribution while component of teflon cone lifthing is weibull distribution. While from distribution test to mean time of improvement (MTTR) flexible hose component is exponential distribution while component of teflon cone lifthing is weibull distribution. The actual results of the flexible hose component on the replacement schedule per 720 hours obtained reliability of 0.2451 and availability 0.9960. While on the critical components of teflon cone lifthing actual on the replacement schedule per 1944 hours obtained reliability of 0.4083 and availability 0.9927.

Analysis of the application of poly-nanocrystalline diamond tools for ultra precision machining of steel with ultrasonic assistance

NASA Astrophysics Data System (ADS)

Doetz, M.; Dambon, O.; Klocke, F.; Bulla, B.; Schottka, K.; Robertson, D. J.

2017-10-01

Ultra-precision diamond turning enables the manufacturing of parts with mirror-like surfaces and highest form accuracies out of non-ferrous, a few crystalline and plastic materials. Furthermore, an ultrasonic assistance has the ability to push these boundaries and enables the machining of materials like steel, which is not possible in a conventional way due to the excessive tool wear caused by the affinity of carbon to iron. Usually monocrystalline diamonds tools are applied due to their unsurpassed cutting edge properties. New cutting tool material developments have shown that it is possible to produce tools made of nano-polycrystalline diamonds with cutting edges equivalent to monocrystalline diamonds. In nano-polycrystalline diamonds ultra-fine grains of a few tens of nanometers are firmly and directly bonded together creating an unisotropic structure. The properties of this material are described to be isotropic, harder and tougher than those of the monocrystalline diamonds, which are unisotropic. This publication will present machining results from the newest investigations of the process potential of this new polycrystalline cutting material. In order to provide a baseline with which to characterize the cutting material cutting experiments on different conventional machinable materials like Cooper or Aluminum are performed. The results provide information on the roughness and the topography of the surface focusing on the comparison to the results while machining with monocrystalline diamond. Furthermore, the cutting material is tested in machining steel with ultrasonic assistance with a focus on tool life time and surface roughness. An outlook on the machinability of other materials will be given.

Efficacy of Cruise Control in controlling postocclusion surge with Legacy and Millennium venturi phacoemulsification machines.

PubMed

Wade, Matthew; Isom, Ryan; Georgescu, Dan; Olson, Randall J

2007-06-01

To determine the efficacy of the Cruise Control surge-limiting device (Staar Surgical) with phacoemulsification machines known to have high levels of surge. John A. Moran Eye Center Clinical Laboratories. In an in vitro study, postocclusion anterior chamber depth changes were measured in fresh phakic human eye-bank eyes using the Alcon Legacy and Bausch & Lomb Millennium venturi machines in conjunction with the Staar Cruise Control device. Both machines were tested with 19-gauge non-Aspiration Bypass System tips at high-surge settings (500 mm Hg vacuum pressure, 75 cm bottle height, 40 mL/min flow rate for the Legacy) and low-surge settings (400 mm Hg vacuum pressure, 125 cm bottle height, 40 mL/min flow rate for the Legacy). Adjusted parameters of flow, vacuum, and irrigation were used based on previous studies to create identical conditions for each device tested. The effect of the Cruise Control device on aspiration rates was also tested with both machines at the low-surge settings. At the high setting with the addition of Cruise Control, surge decreased significantly with the Legacy but was too large to measure with the Millennium venturi. At the low setting with the addition of Cruise Control, surge decreased significantly with both machines. Surge with the Millennium decreased from more than 1.0 mm to a mean of 0.21 mm +/- 0.02 (SD) (P<.0001). Surge with the Legacy decreased from a mean of 0.09 +/- 0.02 mm to 0.05 +/- 0 mm, a 42.9% decrease (P<.0001). The Millennium had the highest surge and aspiration rate before Cruise Control and the greatest percentage decrease in the surge and aspiration rates as a result of the addition of Cruise Control. In the Legacy machine, the Cruise Control device had a statistically and clinically significant effect. Cruise Control had a large effect on fluidics as well as surge amplitude with the Millennium machine. The greater the flow or greater the initial surge, the greater the impact of the Cruise Control device.

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

PubMed

Hotz, Christine S; Templeton, Steven J; Christopher, Mary M

2005-03-01

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang

2017-07-01

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.

Stacked Denoising Autoencoders Applied to Star/Galaxy Classification

NASA Astrophysics Data System (ADS)

Qin, Hao-ran; Lin, Ji-ming; Wang, Jun-yi

2017-04-01

In recent years, the deep learning algorithm, with the characteristics of strong adaptability, high accuracy, and structural complexity, has become more and more popular, but it has not yet been used in astronomy. In order to solve the problem that the star/galaxy classification accuracy is high for the bright source set, but low for the faint source set of the Sloan Digital Sky Survey (SDSS) data, we introduced the new deep learning algorithm, namely the SDA (stacked denoising autoencoder) neural network and the dropout fine-tuning technique, which can greatly improve the robustness and antinoise performance. We randomly selected respectively the bright source sets and faint source sets from the SDSS DR12 and DR7 data with spectroscopic measurements, and made preprocessing on them. Then, we randomly selected respectively the training sets and testing sets without replacement from the bright source sets and faint source sets. At last, using these training sets we made the training to obtain the SDA models of the bright sources and faint sources in the SDSS DR7 and DR12, respectively. We compared the test result of the SDA model on the DR12 testing set with the test results of the Library for Support Vector Machines (LibSVM), J48 decision tree, Logistic Model Tree (LMT), Support Vector Machine (SVM), Logistic Regression, and Decision Stump algorithm, and compared the test result of the SDA model on the DR7 testing set with the test results of six kinds of decision trees. The experiments show that the SDA has a better classification accuracy than other machine learning algorithms for the faint source sets of DR7 and DR12. Especially, when the completeness function is used as the evaluation index, compared with the decision tree algorithms, the correctness rate of SDA has improved about 15% for the faint source set of SDSS-DR7.

SU-E-T-660: Quantitative Fault Testing for Commissioning of Proton Therapy Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reilly, M; Rankine, L; Grantham, K

2015-06-15

Purpose: To ensure proper fault testing for the first single room proton therapy machine by establishing a common set of acceptance testing and commissioning parameters with the manufacturer. The following work details the parameters tested and associated results. Methods: Dose rates in service mode were varied to ensure that when the threshold for maximum or minimum MU/min was met, the beam promptly shut off. The flatness parameter was tested by purposely assigning an incorrect secondary scatter, to ensure the beam shut off when detecting a heterogeneous profile. The beam symmetry parameter was tested by altering the steering coil up tomore » 3.0A, thereby forcing the beam to be asymmetric and shut off. Lastly, the quench system was tested by ramping down the magnet to 5% capacity, whereby the quench button was engaged to bring down the magnet current to a safe level. Results: A dose rate increase or decrease in excess of 10% shut the beam off within 5 seconds as observed by the current on a Matrixx ionization chamber array (IBA Dosimetry, Bartlett, TN) A 3.0A change in the beam steering coil introduced a 2% change in the flatness and symmetry profiles with respect to baseline measurements resulting in the beam shutting off within 5 seconds. An incorrect 2nd scatterer introduced a flatness of 4.1% and symmetry of 6.4% which immediately triggered a beam shut off. Finally, the quench system worked as expected during the ramp down procedure. Conclusion: A fault testing plan to check dosimetric faults and the quench system was performed for the first single room proton therapy system. All dosimetric parameters and machine conditions were met to our satisfaction. We propose that the same type of fault testing should be applied to any proton system during commissioning, including scanning beam systems.« less

Development of a low energy micro sheet forming machine

NASA Astrophysics Data System (ADS)

Razali, A. R.; Ann, C. T.; Shariff, H. M.; Kasim, N. I.; Musa, M. A.; Ahmad, A. F.

2017-10-01

It is expected that with the miniaturization of materials being processed, energy consumption is also being `miniaturized' proportionally. The focus of this study was to design a low energy micro-sheet-forming machine for thin sheet metal application and fabricate a low direct current powered micro-sheet-forming machine. A prototype of low energy system for a micro-sheet-forming machine which includes mechanical and electronic elements was developed. The machine was tested for its performance in terms of natural frequency, punching forces, punching speed and capability, energy consumption (single punch and frequency-time based). Based on the experiments, the machine can do 600 stroke per minute and the process is unaffected by the machine's natural frequency. It was also found that sub-Joule of power was required for a single stroke of punching/blanking process. Up to 100micron thick carbon steel shim was successfully tested and punched. It concludes that low power forming machine is feasible to be developed and be used to replace high powered machineries to form micro-products/parts.

Corrosion Induced Loss of Capacity of Post Tensioned Seven Wire Strand Cable Used in Multistrand Anchor Systems Installed at Corps Projects

DTIC Science & Technology

2016-12-01

Universal Test Machine. .................. 7 Figure 2.2. Pull-test results of PT seven-wire strand cable surrounded by a quickset, steel - reinforced epoxy...13 Figure 2.7. Pull-test results of PT seven-wire strand cable surrounded by a quickset, steel - reinforced...surrounded by a thick layer of quickset, steel -reinforced epoxy and with 40% reduced wedges. ....................................................... 15

The prototype of high stiffness load cell for Rockwell hardness testing machine calibration according to ISO 6508-2:2015

NASA Astrophysics Data System (ADS)

Pakkratoke, M.; Sanponpute, T.

2017-09-01

The penetrated depth of the Rockwell hardness testing machine is normally not more than 0.260 mm. Using commercial load cell cannot achieve the proposed force calibration according to ISO 6508-2[1]. For these reason, the high stiffness load cell (HSL) was fabricated. Its obvious advantage is deformation less than 0.020 mm at 150 kgf maximum load applied. The HSL prototype was designed in concept of direct compression and then confirmed with finite element analysis, FEA. The results showed that the maximum deformation was lower than 0.012 mm at capacity.

On the Stability of Jump-Linear Systems Driven by Finite-State Machines with Markovian Inputs

NASA Technical Reports Server (NTRS)

Patilkulkarni, Sudarshan; Herencia-Zapana, Heber; Gray, W. Steven; Gonzalez, Oscar R.

2004-01-01

This paper presents two mean-square stability tests for a jump-linear system driven by a finite-state machine with a first-order Markovian input process. The first test is based on conventional Markov jump-linear theory and avoids the use of any higher-order statistics. The second test is developed directly using the higher-order statistics of the machine s output process. The two approaches are illustrated with a simple model for a recoverable computer control system.

High Temperature Monotonic and Cyclic Deformation in a Directionally Solidified Nickel-Base Superalloy.

DTIC Science & Technology

1986-05-01

was conducted in air, using a SATEC Systems computer-controlled servohydraulic testing machine. This machine uses a minicomputer (Digital PDP 11/34...overall test program) was run. This test was performed using a feature of the SATEC machine called combinatorial feedback, which allowed a user-defined...Rn) l/T + (in Es /A)/n (4.3) Q can be calculated from 0*: b Q=n (4.4) Creep data for DS MAR-M246, containing no Hafnium, from Reference 99 was used to

Predicting a small molecule-kinase interaction map: A machine learning approach

PubMed Central

2011-01-01

Background We present a machine learning approach to the problem of protein ligand interaction prediction. We focus on a set of binding data obtained from 113 different protein kinases and 20 inhibitors. It was attained through ATP site-dependent binding competition assays and constitutes the first available dataset of this kind. We extract information about the investigated molecules from various data sources to obtain an informative set of features. Results A Support Vector Machine (SVM) as well as a decision tree algorithm (C5/See5) is used to learn models based on the available features which in turn can be used for the classification of new kinase-inhibitor pair test instances. We evaluate our approach using different feature sets and parameter settings for the employed classifiers. Moreover, the paper introduces a new way of evaluating predictions in such a setting, where different amounts of information about the binding partners can be assumed to be available for training. Results on an external test set are also provided. Conclusions In most of the cases, the presented approach clearly outperforms the baseline methods used for comparison. Experimental results indicate that the applied machine learning methods are able to detect a signal in the data and predict binding affinity to some extent. For SVMs, the binding prediction can be improved significantly by using features that describe the active site of a kinase. For C5, besides diversity in the feature set, alignment scores of conserved regions turned out to be very useful. PMID:21708012

Reducing Sweeping Frequencies in Microwave NDT Employing Machine Learning Feature Selection

PubMed Central

Moomen, Abdelniser; Ali, Abdulbaset; Ramahi, Omar M.

2016-01-01

Nondestructive Testing (NDT) assessment of materials’ health condition is useful for classifying healthy from unhealthy structures or detecting flaws in metallic or dielectric structures. Performing structural health testing for coated/uncoated metallic or dielectric materials with the same testing equipment requires a testing method that can work on metallics and dielectrics such as microwave testing. Reducing complexity and expenses associated with current diagnostic practices of microwave NDT of structural health requires an effective and intelligent approach based on feature selection and classification techniques of machine learning. Current microwave NDT methods in general based on measuring variation in the S-matrix over the entire operating frequency ranges of the sensors. For instance, assessing the health of metallic structures using a microwave sensor depends on the reflection or/and transmission coefficient measurements as a function of the sweeping frequencies of the operating band. The aim of this work is reducing sweeping frequencies using machine learning feature selection techniques. By treating sweeping frequencies as features, the number of top important features can be identified, then only the most influential features (frequencies) are considered when building the microwave NDT equipment. The proposed method of reducing sweeping frequencies was validated experimentally using a waveguide sensor and a metallic plate with different cracks. Among the investigated feature selection techniques are information gain, gain ratio, relief, chi-squared. The effectiveness of the selected features were validated through performance evaluations of various classification models; namely, Nearest Neighbor, Neural Networks, Random Forest, and Support Vector Machine. Results showed good crack classification accuracy rates after employing feature selection algorithms. PMID:27104533

High frequency testing of rubber mounts.

PubMed

Vahdati, Nader; Saunders, L Ken Lauderbaugh

2002-04-01

Rubber and fluid-filled rubber engine mounts are commonly used in automotive and aerospace applications to provide reduced cabin noise and vibration, and/or motion accommodations. In certain applications, the rubber mount may operate at frequencies as high as 5000 Hz. Therefore, dynamic stiffness of the mount needs to be known in this frequency range. Commercial high frequency test machines are practically nonexistent, and the best high frequency test machine on the market is only capable of frequencies as high as 1000 Hz. In this paper, a high frequency test machine is described that allows test engineers to study the high frequency performance of rubber mounts at frequencies up to 5000 Hz.

Metal release from coffee machines and electric kettles.

PubMed

Müller, Frederic D; Hackethal, Christin; Schmidt, Roman; Kappenstein, Oliver; Pfaff, Karla; Luch, Andreas

2015-01-01

The release of elemental ions from 8 coffee machines and 11 electric kettles into food simulants was investigated. Three different types of coffee machines were tested: portafilter espresso machines, pod machines and capsule machines. All machines were tested subsequently on 3 days before and on 3 days after decalcification. Decalcification of the machines was performed with agents according to procedures as specified in the respective manufacturer's manuals. The electric kettles showed only a low release of the elements analysed. For the coffee machines decreasing concentrations of elements were found from the first to the last sample taken in the course of 1 day. Metal release on consecutive days showed a decreasing trend as well. After decalcification a large increase in the amounts of elements released was encountered. In addition, the different machine types investigated clearly differed in their extent of element release. By far the highest leaching, both quantitatively and qualitatively, was found for the portafilter machines. With these products releases of Pb, Ni, Mn, Cr and Zn were in the range and beyond the release limits as proposed by the Council of Europe. Therefore, a careful rinsing routine, especially after decalcification, is recommended for these machines. The comparably lower extent of release of one particular portafilter machine demonstrates that metal release at levels above the threshold that triggers health concerns are technically avoidable.

Ada Compiler Validation Summary Report: Certificate Number: 890420W1. 10066 International Business Machines Corporation, IBM Development System for the Ada Language, AIX/RT Ada Compiler, Version 1.1.1, IBM RT PC 6150-125

DTIC Science & Technology

1989-04-20

International Business Machines Corporation, IBM Development System. for the Ada Language AIX/RT Ada Compiler, Version 1.1.1, Wright-Patterson APB...Certificate Number: 890420V1.10066 International Business Machines Corporation IBM Development System for the Ada Language AIX/RT Ada Compiler, Version 1.1.1...TEST INFORMATION The compiler was tested using command scripts provided by International Business Machines Corporation and reviewed by the validation

A Machine-to-Machine protocol benchmark for eHealth applications - Use case: Respiratory rehabilitation.

PubMed

Talaminos-Barroso, Alejandro; Estudillo-Valderrama, Miguel A; Roa, Laura M; Reina-Tosina, Javier; Ortega-Ruiz, Francisco

2016-06-01

M2M (Machine-to-Machine) communications represent one of the main pillars of the new paradigm of the Internet of Things (IoT), and is making possible new opportunities for the eHealth business. Nevertheless, the large number of M2M protocols currently available hinders the election of a suitable solution that satisfies the requirements that can demand eHealth applications. In the first place, to develop a tool that provides a benchmarking analysis in order to objectively select among the most relevant M2M protocols for eHealth solutions. In the second place, to validate the tool with a particular use case: the respiratory rehabilitation. A software tool, called Distributed Computing Framework (DFC), has been designed and developed to execute the benchmarking tests and facilitate the deployment in environments with a large number of machines, with independence of the protocol and performance metrics selected. DDS, MQTT, CoAP, JMS, AMQP and XMPP protocols were evaluated considering different specific performance metrics, including CPU usage, memory usage, bandwidth consumption, latency and jitter. The results obtained allowed to validate a case of use: respiratory rehabilitation of chronic obstructive pulmonary disease (COPD) patients in two scenarios with different types of requirement: Home-Based and Ambulatory. The results of the benchmark comparison can guide eHealth developers in the choice of M2M technologies. In this regard, the framework presented is a simple and powerful tool for the deployment of benchmark tests under specific environments and conditions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An imperialist competitive algorithm for virtual machine placement in cloud computing

NASA Astrophysics Data System (ADS)

Jamali, Shahram; Malektaji, Sepideh; Analoui, Morteza

2017-05-01

Cloud computing, the recently emerged revolution in IT industry, is empowered by virtualisation technology. In this paradigm, the user's applications run over some virtual machines (VMs). The process of selecting proper physical machines to host these virtual machines is called virtual machine placement. It plays an important role on resource utilisation and power efficiency of cloud computing environment. In this paper, we propose an imperialist competitive-based algorithm for the virtual machine placement problem called ICA-VMPLC. The base optimisation algorithm is chosen to be ICA because of its ease in neighbourhood movement, good convergence rate and suitable terminology. The proposed algorithm investigates search space in a unique manner to efficiently obtain optimal placement solution that simultaneously minimises power consumption and total resource wastage. Its final solution performance is compared with several existing methods such as grouping genetic and ant colony-based algorithms as well as bin packing heuristic. The simulation results show that the proposed method is superior to other tested algorithms in terms of power consumption, resource wastage, CPU usage efficiency and memory usage efficiency.

Deviation Value for Conventional X-ray in Hospitals in South Sulawesi Province from 2014 to 2016

NASA Astrophysics Data System (ADS)

Bachtiar, Ilham; Abdullah, Bualkar; Tahir, Dahlan

2018-03-01

This paper describes the conventional X-ray machine parameters tested in the region of South Sulawesi from 2014 to 2016. The objective of this research is to know deviation of every parameter of conventional X-ray machine. The testing parameters were analyzed by using quantitative methods with participatory observational approach. Data collection was performed by testing the output of conventional X-ray plane using non-invasive x-ray multimeter. The test parameters include tube voltage (kV) accuracy, radiation output linearity, reproducibility and radiation beam value (HVL) quality. The results of the analysis show four conventional X-ray test parameters have varying deviation spans, where the tube voltage (kV) accuracy has an average value of 4.12%, the average radiation output linearity is 4.47% of the average reproducibility of 0.62% and the averaged of the radiation beam (HVL) is 3.00 mm.

Life and Reliability Characteristics of TurboBrayton Coolers

NASA Technical Reports Server (NTRS)

Breedlove, Jeff J.; Zagarola, Mark; Nellis, Greg; Dolan, Frank; Swift, Walt; Gibbon, Judith; Obenschain, Arthur F. (Technical Monitor)

2000-01-01

Wear and internal contaminants are two of the primary factors that influence reliable, long-life operation of turbo-Brayton cryocoolers. This paper describes tests that have been conducted and methods that have been developed for turbo-Brayton components and systems to assure reliable operation. The turbomachines used in these coolers employ self-acting gas bearings to support the miniature high-speed shafts, thus providing vibration-free operation. Because the bearings are self-acting, rubbing contact occurs during initial start-up and shutdown of the machines. Bearings and shafts are designed to endure multiple stop/start cycles without producing particles or surface features that would impair the proper operation of the machines. Test results are presented for a variety of turbomachines used in these systems. The tests document extended operating life and start/stop cycling behavior for machines over a range of time and temperature scales. Contaminants such as moisture and other residual gas impurities can be a source of degraded operation if they freeze out in sufficient quantities to block flow passages or if they mechanically affect the operation of the machines. A post-fabrication bakeout procedure has been successfully used to reduce residual internal contamination to acceptable levels in a closed cycle system. The process was developed during space qualification tests on the NICMOS cryocooler. Moisture levels were sampled over a six-month time interval confirming the effectiveness of the technique. A description of the bakeout procedure is presented.

Wear behavior of carbide tool coated with Yttria-stabilized zirconia nano particles.

NASA Astrophysics Data System (ADS)

Jadhav, Pavandatta M.; Reddy, Narala Suresh Kumar

2018-04-01

Wear mechanism takes predominant role in reducing the tool life during machining of Titanium alloy. Challenges of wear mechanisms such as variation in chip, high pressure loads and spring back are responsible for tool wear. In addition, many tool materials are inapt for machining due to low thermal conductivity and volume specific heat of these materials results in high cutting temperature during machining. To confront this issue Electrostatic Spray Coating (ESC) coating technique is utilized to enhance the tool life to an acceptable level. The Yttria Stabilized Zirconia (YSZ) acts as a thermal barrier coating having high thermal expansion coefficient and thermal shock resistance. This investigation focuses on the influence of YSZ nanocoating on the tungsten carbide tool material and improve the machinability of Ti-6Al-4V alloy. YSZ nano powder was coated on the tungsten carbide pin by using ESC technique. The coatings have been tested for wear and friction behavior by using a pin-on-disc tribological tester. The dry sliding wear test was performed on Titanium alloy (Ti-6Al-4V) disc and YSZ coated tungsten carbide (pin) at ambient atmosphere. The performance parameters like wear rate and temperature rise were considered upon performing the dry sliding test on Ti-6Al-4V alloy disc. The performance parameters were calculated by using coefficient of friction and frictional force values which were obtained from the pin on disc test. Substantial resistance to wear was achieved by the coating.

Prediction of skin sensitization potency using machine learning approaches.

PubMed

Zang, Qingda; Paris, Michael; Lehmann, David M; Bell, Shannon; Kleinstreuer, Nicole; Allen, David; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Strickland, Judy

2017-07-01

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Prediction of beta-turns with learning machines.

PubMed

Cai, Yu-Dong; Liu, Xiao-Jun; Li, Yi-Xue; Xu, Xue-biao; Chou, Kuo-Chen

2003-05-01

The support vector machine approach was introduced to predict the beta-turns in proteins. The overall self-consistency rate by the re-substitution test for the training or learning dataset reached 100%. Both the training dataset and independent testing dataset were taken from Chou [J. Pept. Res. 49 (1997) 120]. The success prediction rates by the jackknife test for the beta-turn subset of 455 tetrapeptides and non-beta-turn subset of 3807 tetrapeptides in the training dataset were 58.1 and 98.4%, respectively. The success rates with the independent dataset test for the beta-turn subset of 110 tetrapeptides and non-beta-turn subset of 30,231 tetrapeptides were 69.1 and 97.3%, respectively. The results obtained from this study support the conclusion that the residue-coupled effect along a tetrapeptide is important for the formation of a beta-turn.

A 34-meter VAWT (Vertical Axis Wind Turbine) point design

NASA Astrophysics Data System (ADS)

Ashwill, T. D.; Berg, D. E.; Dodd, H. M.; Rumsey, M. A.; Sutherland, H. J.; Veers, P. S.

The Wind Energy Division at Sandia National Laboratories recently completed a point design based on the 34-m Vertical Axis Wind Turbine (VAWT) Test Bed. The 34-m Test Bed research machine incorporates several innovations that improve Darrieus technology, including increased energy production, over previous machines. The point design differs minimally from the Test Bed; but by removing research-related items, its estimated cost is substantially reduced. The point design is a first step towards a Test-Bed-based commercial machine that would be competitive with conventional sources of power in the mid-1990s.

Detection of Splice Sites Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Varadwaj, Pritish; Purohit, Neetesh; Arora, Bhumika

Automatic identification and annotation of exon and intron region of gene, from DNA sequences has been an important research area in field of computational biology. Several approaches viz. Hidden Markov Model (HMM), Artificial Intelligence (AI) based machine learning and Digital Signal Processing (DSP) techniques have extensively and independently been used by various researchers to cater this challenging task. In this work, we propose a Support Vector Machine based kernel learning approach for detection of splice sites (the exon-intron boundary) in a gene. Electron-Ion Interaction Potential (EIIP) values of nucleotides have been used for mapping character sequences to corresponding numeric sequences. Radial Basis Function (RBF) SVM kernel is trained using EIIP numeric sequences. Furthermore this was tested on test gene dataset for detection of splice site by window (of 12 residues) shifting. Optimum values of window size, various important parameters of SVM kernel have been optimized for a better accuracy. Receiver Operating Characteristic (ROC) curves have been utilized for displaying the sensitivity rate of the classifier and results showed 94.82% accuracy for splice site detection on test dataset.

Basic space payload fastener

NASA Technical Reports Server (NTRS)

Vranish, J. M.; Gorevan, Stephen

1995-01-01

A new basic space fastener has been developed and tested by the GSFC. The purposes of this fastener are to permit assembly and servicing in space by astronauts and/or robots and to facilitate qualification of payloads on Earth prior to launch by saving time and money during the systems integration and component testing and qualification processes. The space fastener is a rework of the basic machine screw such that crossthreading is impossible; it is self-locking and will not work its way out during launch (vibration proof); it will not wear out despite repeated use; it occupies a small foot print which is comparable to its machine screw equivalent, and it provides force and exhibits strength comparable to its machine screw equivalent. Construction is ultra-simple and cost effective and the principle is applicable across the full range of screw sizes ranging from a #10 screw to 2.5 cm (1 in) or more. In this paper, the fastener principles of operation will be discussed along with test results and construction details. The new fastener also has considerable potential in the commercial sector. A few promising applications will be presented.

Enhancement of hepatitis virus immunoassay outcome predictions in imbalanced routine pathology data by data balancing and feature selection before the application of support vector machines.

PubMed

Richardson, Alice M; Lidbury, Brett A

2017-08-14

Data mining techniques such as support vector machines (SVMs) have been successfully used to predict outcomes for complex problems, including for human health. Much health data is imbalanced, with many more controls than positive cases. The impact of three balancing methods and one feature selection method is explored, to assess the ability of SVMs to classify imbalanced diagnostic pathology data associated with the laboratory diagnosis of hepatitis B (HBV) and hepatitis C (HCV) infections. Random forests (RFs) for predictor variable selection, and data reshaping to overcome a large imbalance of negative to positive test results in relation to HBV and HCV immunoassay results, are examined. The methodology is illustrated using data from ACT Pathology (Canberra, Australia), consisting of laboratory test records from 18,625 individuals who underwent hepatitis virus testing over the decade from 1997 to 2007. Overall, the prediction of HCV test results by immunoassay was more accurate than for HBV immunoassay results associated with identical routine pathology predictor variable data. HBV and HCV negative results were vastly in excess of positive results, so three approaches to handling the negative/positive data imbalance were compared. Generating datasets by the Synthetic Minority Oversampling Technique (SMOTE) resulted in significantly more accurate prediction than single downsizing or multiple downsizing (MDS) of the dataset. For downsized data sets, applying a RF for predictor variable selection had a small effect on the performance, which varied depending on the virus. For SMOTE, a RF had a negative effect on performance. An analysis of variance of the performance across settings supports these findings. Finally, age and assay results for alanine aminotransferase (ALT), sodium for HBV and urea for HCV were found to have a significant impact upon laboratory diagnosis of HBV or HCV infection using an optimised SVM model. Laboratories looking to include machine learning via SVM as part of their decision support need to be aware that the balancing method, predictor variable selection and the virus type interact to affect the laboratory diagnosis of hepatitis virus infection with routine pathology laboratory variables in different ways depending on which combination is being studied. This awareness should lead to careful use of existing machine learning methods, thus improving the quality of laboratory diagnosis.

SU-F-T-459: ArcCHECK Machine QA : Highly Efficient Quality Assurance Tool for VMAT, SRS & SBRT Linear Accelerator Delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mhatre, V; Patwe, P; Dandekar, P

Purpose: Quality assurance (QA) of complex linear accelerators is critical and highly time consuming. ArcCHECK Machine QA tool is used to test geometric and delivery aspects of linear accelerator. In this study we evaluated the performance of this tool. Methods: Machine QA feature allows user to perform quality assurance tests using ArcCHECK phantom. Following tests were performed 1) Gantry Speed 2) Gantry Rotation 3) Gantry Angle 4)MLC/Collimator QA 5)Beam Profile Flatness & Symmetry. Data was collected on trueBEAM stX machine for 6 MV for a period of one year. The Gantry QA test allows to view errors in gantry angle,more » rotation & assess how accurately the gantry moves around the isocentre. The MLC/Collimator QA tool is used to analyze & locate the differences between leaf bank & jaw position of linac. The flatness & Symmetry test quantifies beam flatness & symmetry in IEC-y & x direction. The Gantry & Flatness/Symmetry test can be performed for static & dynamic delivery. Results: The Gantry speed was 3.9 deg/sec with speed maximum deviation around 0.3 deg/sec. The Gantry Isocentre for arc delivery was 0.9mm & static delivery was 0.4mm. The maximum percent positive & negative difference was found to be 1.9 % & – 0.25 % & maximum distance positive & negative diff was 0.4mm & – 0.3 mm for MLC/Collimator QA. The Flatness for Arc delivery was 1.8 % & Symmetry for Y was 0.8 % & X was 1.8 %. The Flatness for gantry 0°,270°,90° & 180° was 1.75,1.9,1.8 & 1.6% respectively & Symmetry for X & Y was 0.8,0.6% for 0°, 0.6,0.7% for 270°, 0.6,1% for 90° & 0.6,0.7% for 180°. Conclusion: ArcCHECK Machine QA is an useful tool for QA of Modern linear accelerators as it tests both geometric & delivery aspects. This is very important for VMAT, SRS & SBRT treatments.« less

Improved Tensile Test for Ceramics

NASA Technical Reports Server (NTRS)

Osiecki, R. A.

1982-01-01

For almost-nondestructive tensile testing of ceramics, steel rod is bonded to sample of ceramic. Assembly is then pulled apart in conventional tensile-test machine. Test destroys only shallow surface layer which can be machined away making specimen ready for other uses. Method should be useful as manufacturing inspection procedure for low-strength brittle materials.

Model of the multipolar engine with decreased cogging torque by asymmetrical distribution of the magnets

NASA Astrophysics Data System (ADS)

Goryca, Zbigniew; Paduszyński, Kamil; Pakosz, Artur

2018-03-01

This paper presents the results of field calculations of cogging torque for a 12-pole torque motor with an 18-slot stator. A constant angular velocity magnet and the same size gap between n-1 magnets were assumed. In these conditions, the effect of change of the n-th gap between magnets on the cogging torque was tested. Due to considerable length of the machine the calculations were performed using a 2D model. The n-th gap for which the cogging torque assumed the lowest value was evaluated. The cogging torque of the machine with symmetrical magnetic circuit (the same size of gap between magnets) was compared to the one of the asymmetrical machine. With proper choice of asymmetry, the cogging torque for the machine decreased by four times.

Experimental investigation of various surface integrity aspects in hard turning of AISI 4340 alloy steel with coated and uncoated cermet

NASA Astrophysics Data System (ADS)

Das, Anshuman; Patel, S. K.; Sateesh Kumar, Ch.; Biswal, B. B.

2018-03-01

The newer technological developments are exerting immense pressure on domain of production. These fabrication industries are busy finding solutions to reduce the costs of cutting materials, enhance the machined parts quality and testing different materials, which can be made versatile for cutting materials, which are difficult for machining. High-speed machining has been the domain of paramount importance for mechanical engineering. In this study, the variation of surface integrity parameters of hardened AISI 4340 alloy steel was analyzed. The surface integrity parameters like surface roughness, micro hardness, machined surface morphology and white layer of hardened AISI 4340 alloy steel were compared using coated and uncoated cermet inserts under dry cutting condition. From the results, it was deduced that coated insert outperformed uncoated one in terms of different surface integrity characteristics.

Diamond turning of glass

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blackley, W.S.; Scattergood, R.O.

A new research initiative will be undertaken to investigate the critical cutting depth concepts for single point diamond turning of brittle, amorphous materials. Inorganic glasses and a brittle, thermoset polymer (organic glass) are the principal candidate materials. Interrupted cutting tests similar to those done in earlier research are Ge and Si crystals will be made to obtain critical depth values as a function of machining parameters. The results will provide systematic data with which to assess machining performance on glasses and amorphous materials

An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring.

PubMed

Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen

2016-02-23

An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies.

An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring

PubMed Central

Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen

2016-01-01

An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies. PMID:26907297

HAL/S-360 compiler test activity report

NASA Technical Reports Server (NTRS)

Helmers, C. T.

1974-01-01

The levels of testing employed in verifying the HAL/S-360 compiler were as follows: (1) typical applications program case testing; (2) functional testing of the compiler system and its generated code; and (3) machine oriented testing of compiler implementation on operational computers. Details of the initial test plan and subsequent adaptation are reported, along with complete test results for each phase which examined the production of object codes for every possible source statement.

Developing Lathing Parameters for PBX 9501

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodrum, Randall Brock

This thesis presents the work performed on lathing PBX 9501 to gather and analyze cutting force and temperature data during the machining process. This data will be used to decrease federal-regulation-constrained machining time of the high explosive PBX 9501. The effects of machining parameters depth of cut, surface feet per minute, and inches per revolution on cutting force and cutting interface were evaluated. Cutting tools of tip radius 0.005 -inches and 0.05 -inches were tested to determine what effect the tool shape had on the machining process as well. A consistently repeatable relationship of temperature to changing depth of cutmore » and surface feet per minute is found, while only a weak dependence was found to changing inches per revolution. Results also show the relation of cutting force to depth of cut and inches per revolution, while weak dependence on SFM is found. Conclusions suggest rapid, shallow cuts optimize machining time for a billet of PBX 9501, while minimizing temperature increase and cutting force.« less

Fluidics and heat generation of Alcon Infiniti and Legacy, Bausch & Lomb Millennium, and advanced medical optics sovereign phacoemulsification systems.

PubMed

Floyd, Michael S; Valentine, Jeremy R; Olson, Randall J

2006-09-01

To study heat generation, vacuum, and flow characteristics of the Alcon Infiniti and Bausch & Lomb Millennium with results compared with the Alcon Legacy and advanced medical optics (AMO) Sovereign machines previously studied. Experimental study. Heat generation with continuous ultrasound was determined with and without a 200-g weight. Flow and vacuum were determined from 12 to 40-ml/min in 2-ml/min steps. The impact of a STAAR Cruise Control was also tested. Millennium created the most heat/20% of power (5.67 +/- 0.51 degrees C unweighted and 6.80 +/- 0.80 degrees C weighted), followed by Sovereign (4.59 +/- 0.70 degrees C unweighted and 5.65 +/- 0.72 degrees C weighted), Infiniti (2.79 +/- 0.62 degrees C unweighted and 3.96 +/- 0.31 degrees C weighted), and Legacy (1.99 +/- 0.49 degrees C unweighted and 4.27 +/- 0.76 degrees C weighted; P < .0001 for all comparisons between machines except Infiniti vs Legacy, both weighted). Flow studies revealed that Millennium Peristaltic was 17% less than indicated (P < .0001 to all other machines), and all other machines were within 3.5% of indicated. Cruise Control decreased flow by 4.1% (P < .0001 for same machine without it). Millennium Venturi had the greatest vacuum (81% more than the least Sovereign; P < .0001), and Cruise Control increased vacuum in a peristaltic machine 35% more than the Venturi system (P < .0001). Percent power is not consistent in regard to heat generation, however, flow was accurate for all machines except Millennium Peristaltic. Restriction with Cruise Control elevates unoccluded vacuum to levels greater than the Venturi system tested.

Determining the compactive effort required to model pavement voids using the Corps of Engineers gyratory testing machine.

DOT National Transportation Integrated Search

1997-11-01

Various agencies have used the Corps of Engineers gyratory testing machine (GTM) to design and test asphalt mixes. Materials properties such as shear strength and strain are measured during the compaction process. However, a compaction process duplic...

Evaluation of an Integrated Multi-Task Machine Learning System with Humans in the Loop

DTIC Science & Technology

2007-01-01

machine learning components natural language processing, and optimization...was examined with a test explicitly developed to measure the impact of integrated machine learning when used by a human user in a real world setting...study revealed that integrated machine learning does produce a positive impact on overall performance. This paper also discusses how specific machine learning components contributed to human-system

Comparative evaluation of bonding strength of computer aided machined ceramic, pressable ceramic, and milled metal implant abutment copings and effect of surface conditioning on bonding strength: An in vitro study

PubMed Central

Rani, Sapna; Verma, Mahesh; Gill, Shubhra; Gupta, Rekha

2016-01-01

Background/Purpose: The aim of this study was to compare the shear bond strength of computer aided design/computer aided machined ceramic (CAD/CAM), pressable ceramic, and milled metal implant copings on abutment and the effect of surface conditioning on bonding strength. Materials and Methods: A total of 90 test samples were fabricated on three titanium abutments. Among 90 test samples, 30 copings were fabricated by CAD/CAM, 30 by pressable, and 30 by milling of titanium metal. These 30 test samples in each group were further subdivided equally for surface treatment. Fifteen out of 30 test samples in each group were surface conditioned with airborne particle abrasion. All the 90 test samples were luted on abutment with glass ionomer cement. Bonding strength was evaluated for all the samples using universal testing machine at a crosshead speed of 5 mm/min. The results obtained were compared and evaluated using one-way ANOVA with post-hoc and unpaired t-test at a significance level of 0.05. Results: The mean difference for CAD/CAM surface conditioned subgroup was 1.28 ± 0.12, for nonconditioned subgroup was 1.20 ± 0.11. The mean difference for pressable surface conditioned subgroup was 1.18 ± 0.04, and for nonconditioned subgroup was 0.75 ± 0.28. The mean difference for milled metal surface conditioned subgroup was 2.57 ± 0.58, and for nonconditioned subgroup was 1.49 ± 0.15. Conclusions: On comparison of bonding strength, milled metal copings had an edge over the other two materials, and surface conditioning increased the bond strength. PMID:27141163

Seizure Forecasting and the Preictal State in Canine Epilepsy.

PubMed

Varatharajah, Yogatheesan; Iyer, Ravishankar K; Berry, Brent M; Worrell, Gregory A; Brinkmann, Benjamin H

2017-02-01

The ability to predict seizures may enable patients with epilepsy to better manage their medications and activities, potentially reducing side effects and improving quality of life. Forecasting epileptic seizures remains a challenging problem, but machine learning methods using intracranial electroencephalographic (iEEG) measures have shown promise. A machine-learning-based pipeline was developed to process iEEG recordings and generate seizure warnings. Results support the ability to forecast seizures at rates greater than a Poisson random predictor for all feature sets and machine learning algorithms tested. In addition, subject-specific neurophysiological changes in multiple features are reported preceding lead seizures, providing evidence supporting the existence of a distinct and identifiable preictal state.

Analysis, testing, and evaluation of faulted and unfaulted Wye, Delta, and open Delta connected electromechanical actuators

NASA Technical Reports Server (NTRS)

Nehl, T. W.; Demerdash, N. A.

1983-01-01

Mathematical models capable of simulating the transient, steady state, and faulted performance characteristics of various brushless dc machine-PSA (power switching assembly) configurations were developed. These systems are intended for possible future use as primemovers in EMAs (electromechanical actuators) for flight control applications. These machine-PSA configurations include wye, delta, and open-delta connected systems. The research performed under this contract was initially broken down into the following six tasks: development of mathematical models for various machine-PSA configurations; experimental validation of the model for failure modes; experimental validation of the mathematical model for shorted turn-failure modes; tradeoff study; and documentation of results and methodology.

SEIZURE FORECASTING AND THE PREICTAL STATE IN CANINE EPILEPSY

PubMed Central

Varatharajah, Yogatheesan; Iyer, Ravishankar K.; Berry, Brent M.; Worrell, Gregory A.; Brinkmann, Benjamin H.

2017-01-01

The ability to predict seizures may enable patients with epilepsy to better manage their medications and activities, potentially reducing side effects and improving quality of life. Forecasting epileptic seizures remains a challenging problem, but machine learning methods using intracranial electroencephalographic (iEEG) measures have shown promise. A machine-learning-based pipeline was developed to process iEEG recordings and generate seizure warnings. Results support the ability to forecast seizures at rates greater than a Poisson random predictor for all feature sets and machine learning algorithms tested. In addition, subject-specific neurophysiological changes in multiple features are reported preceding lead seizures, providing evidence supporting the existence of a distinct and identifiable preictal state. PMID:27464854

Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

PubMed Central

2011-01-01

Background Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'. Methods The FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from these. All records were labelled as 'normal' or 'at risk' by two experienced obstetricians. A training set was formed by 60 records, the remaining 30 left as the testing set. The standard deviations of the EMD components are input as features to a support vector machine (SVM) to classify FHR samples. Results For the training set, a five-fold cross validation test resulted in an accuracy of 86% whereas the overall geometric mean of sensitivity and specificity was 94.8%. The Kappa value for the training set was .923. Application of the proposed method to the testing set (30 records) resulted in a geometric mean of 81.5%. The Kappa value for the testing set was .684. Conclusions Based on the overall performance of the system it can be stated that the proposed methodology is a promising new approach for the feature extraction and classification of FHR signals. PMID:21244712

Varying execution discipline to increase performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, P.L.; Maccabe, A.B.

1993-12-22

This research investigates the relationship between execution discipline and performance. The hypothesis has two parts: 1. Different execution disciplines exhibit different performance for different computations, and 2. These differences can be effectively predicted by heuristics. A machine model is developed that can vary its execution discipline. That is, the model can execute a given program using either the control-driven, data-driven or demand-driven execution discipline. This model is referred to as a ``variable-execution-discipline`` machine. The instruction set for the model is the Program Dependence Web (PDW). The first part of the hypothesis will be tested by simulating the execution of themore » machine model on a suite of computations, based on the Livermore Fortran Kernel (LFK) Test (a.k.a. the Livermore Loops), using all three execution disciplines. Heuristics are developed to predict relative performance. These heuristics predict (a) the execution time under each discipline for one iteration of each loop and (b) the number of iterations taken by that loop; then the heuristics use those predictions to develop a prediction for the execution of the entire loop. Similar calculations are performed for branch statements. The second part of the hypothesis will be tested by comparing the results of the simulated execution with the predictions produced by the heuristics. If the hypothesis is supported, then the door is open for the development of machines that can vary execution discipline to increase performance.« less

Modelling rollover behaviour of exacavator-based forest machines

Treesearch

M.W. Veal; S.E. Taylor; Robert B. Rummer

2003-01-01

This poster presentation provides results from analytical and computer simulation models of rollover behaviour of hydraulic excavators. These results are being used as input to the operator protective structure standards development process. Results from rigid body mechanics and computer simulation methods agree well with field rollover test data. These results show...

Computer-Based Arithmetic Test Generation

ERIC Educational Resources Information Center

Trocchi, Robert F.

1973-01-01

The computer can be a welcome partner in the instructional process, but only if there is man-machine interaction. Man should not compromise system design because of available hardware; the computer must fit the system design for the result to represent an acceptable solution to instructional technology. The Arithmetic Test Generator system fits…

Current Status of an Organic Rankine Cycle Engine Development Program

NASA Technical Reports Server (NTRS)

Barber, R. E.

1984-01-01

The steps taken to achieve improved bearing life in the organic Rankine cycle (ORC) engine being developed for use on solar parabolic dishes are presented. A summary of test results is given. Dynamic tests on the machine shaft and rotors of the ORC engine are also discussed.

2007 SB14 Source Reduction Plan/Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, L

2007-07-24

Aqueous solutions (mixed waste) generated from various LLNL operations, such as debris washing, sample preparation and analysis, and equipment maintenance and cleanout, were combined for storage in the B695 tank farm. Prior to combination the individual waste streams had different codes depending on the particular generating process and waste characteristics. The largest streams were CWC 132, 791, 134, 792. Several smaller waste streams were also included. This combined waste stream was treated at LLNL's waste treatment facility using a vacuum filtration and cool vapor evaporation process in preparation for discharge to sanitary sewer. Prior to discharge, the treated waste streammore » was sampled and the results were reviewed by LLNL's water monitoring specialists. The treated solution was discharged following confirmation that it met the discharge criteria. A major source, accounting for 50% for this waste stream, is metal machining, cutting and grinding operations in the engineering machine shops in B321/B131. An additional 7% was from similar operations in B131 and B132S. This waste stream primarily contains metal cuttings from machined parts, machining coolant and water, with small amounts of tramp oil from the machining and grinding equipment. Several waste reduction measures for the B321 machine shop have been taken, including the use of a small point-of-use filtering/tramp-oil coalescing/UV-sterilization coolant recycling unit, and improved management techniques (testing and replenishing) for coolants. The recycling unit had some operational problems during 2006. The machine shop is planning to have it repaired in the near future. A major source, accounting for 50% for this waste stream, is metal machining, cutting and grinding operations in the engineering machine shops in B321/B131. An additional 7% was from similar operations in B131 and B132S. This waste stream primarily contains metal cuttings from machined parts, machining coolant and water, with small amounts of tramp oil from the machining and grinding equipment. Several waste reduction measures for the B321 machine shop have been taken, including the use of a small point-of-use filtering/tramp-oil coalescing/UV-sterilization coolant recycling unit, and improved management techniques (testing and replenishing) for coolants. The recycling unit had some operational problems during 2006. The machine shop is planning to have it repaired in the near future. Quarterly waste generation data prepared by the Environmental Protection Department's P2 Team are regularly provided to engineering shops as well as other facilities so that generators can track the effectiveness of their waste minimization efforts.« less

Prediction of Return-to-original-work after an Industrial Accident Using Machine Learning and Comparison of Techniques

PubMed Central

2018-01-01

Background Many studies have tried to develop predictors for return-to-work (RTW). However, since complex factors have been demonstrated to predict RTW, it is difficult to use them practically. This study investigated whether factors used in previous studies could predict whether an individual had returned to his/her original work by four years after termination of the worker's recovery period. Methods An initial logistic regression analysis of 1,567 participants of the fourth Panel Study of Worker's Compensation Insurance yielded odds ratios. The participants were divided into two subsets, a training dataset and a test dataset. Using the training dataset, logistic regression, decision tree, random forest, and support vector machine models were established, and important variables of each model were identified. The predictive abilities of the different models were compared. Results The analysis showed that only earned income and company-related factors significantly affected return-to-original-work (RTOW). The random forest model showed the best accuracy among the tested machine learning models; however, the difference was not prominent. Conclusion It is possible to predict a worker's probability of RTOW using machine learning techniques with moderate accuracy. PMID:29736160

Development of a high-efficiency motor/generator for flywheel energy storage

NASA Astrophysics Data System (ADS)

Lashley, Christopher; Anand, Dave K.; Kirk, James A.; Zmood, Ronald B.

This study addresses the design changes and extensions necessary to construct and test a working prototype of a motor/generator for a magnetically suspended flywheel energy storage system. The brushless motor controller for the motor was specified and the electronic commutation arrangement designed. The laminations were redesigned and fabricated using laser machining. Flux density measurements were made and the results used to redesign the armature windings. A test rig was designed and built, and the motor/generator was installed and speed tested to 9000 rpm. Experimental methods of obtaining the machine voltage and torque constants Kv and Kt, obtaining the useful air-gap flux density, and characterizing the motor and other system components are described. The measured Kv and Kt were approximately 40 percent greater than predicted by theory and initial experiment.

Development of a high-efficiency motor/generator for flywheel energy storage

NASA Technical Reports Server (NTRS)

Lashley, Christopher; Anand, Dave K.; Kirk, James A.; Zmood, Ronald B.

1991-01-01

This study addresses the design changes and extensions necessary to construct and test a working prototype of a motor/generator for a magnetically suspended flywheel energy storage system. The brushless motor controller for the motor was specified and the electronic commutation arrangement designed. The laminations were redesigned and fabricated using laser machining. Flux density measurements were made and the results used to redesign the armature windings. A test rig was designed and built, and the motor/generator was installed and speed tested to 9000 rpm. Experimental methods of obtaining the machine voltage and torque constants Kv and Kt, obtaining the useful air-gap flux density, and characterizing the motor and other system components are described. The measured Kv and Kt were approximately 40 percent greater than predicted by theory and initial experiment.

Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

PubMed

Perryman, Alexander L; Stratton, Thomas P; Ekins, Sean; Freundlich, Joel S

2016-02-01

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). "Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h. Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

Assessment of Genetic and Nongenetic Interactions for the Prediction of Depressive Symptomatology: An Analysis of the Wisconsin Longitudinal Study Using Machine Learning Algorithms

PubMed Central

Roetker, Nicholas S.; Yonker, James A.; Chang, Vicky; Roan, Carol L.; Herd, Pamela; Hauser, Taissa S.; Hauser, Robert M.

2013-01-01

Objectives. We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. Methods. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors—13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors—18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. Results. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. Conclusions. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic–environmental–sociobehavioral interactions in depressive symptoms. PMID:23927508

29 CFR 1919.15 - Periodic tests, examinations and inspections.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Periodic tests, examinations and inspections. After being taken into use, every hoisting machine, all fixed... 29 Labor 7 2013-07-01 2013-07-01 false Periodic tests, examinations and inspections. 1919.15... the attachments, as a unit; and cranes and other hoisting machines with their accessory gear, as a...

29 CFR 1919.15 - Periodic tests, examinations and inspections.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Periodic tests, examinations and inspections. After being taken into use, every hoisting machine, all fixed... 29 Labor 7 2010-07-01 2010-07-01 false Periodic tests, examinations and inspections. 1919.15... the attachments, as a unit; and cranes and other hoisting machines with their accessory gear, as a...

29 CFR 1919.15 - Periodic tests, examinations and inspections.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Periodic tests, examinations and inspections. After being taken into use, every hoisting machine, all fixed... 29 Labor 7 2011-07-01 2011-07-01 false Periodic tests, examinations and inspections. 1919.15... the attachments, as a unit; and cranes and other hoisting machines with their accessory gear, as a...

29 CFR 1919.15 - Periodic tests, examinations and inspections.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Periodic tests, examinations and inspections. After being taken into use, every hoisting machine, all fixed... 29 Labor 7 2014-07-01 2014-07-01 false Periodic tests, examinations and inspections. 1919.15... the attachments, as a unit; and cranes and other hoisting machines with their accessory gear, as a...

29 CFR 1919.15 - Periodic tests, examinations and inspections.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Periodic tests, examinations and inspections. After being taken into use, every hoisting machine, all fixed... 29 Labor 7 2012-07-01 2012-07-01 false Periodic tests, examinations and inspections. 1919.15... the attachments, as a unit; and cranes and other hoisting machines with their accessory gear, as a...

Characterization of irradiated AISI 316L stainless steel disks removed from the Spallation Neutron Source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vevera, Bradley J; Hyres, James W; McClintock, David A

2014-01-01

Irradiated AISI 316L stainless steel disks were removed from the Spallation Neutron Source (SNS) for post-irradiation examination (PIE) to assess mechanical property changes due to radiation damage and erosion of the target vessel. Topics reviewed include high-resolution photography of the disk specimens, cleaning to remove mercury (Hg) residue and surface oxides, profile mapping of cavitation pits using high frequency ultrasonic testing (UT), high-resolution surface replication, and machining of test specimens using wire electrical discharge machining (EDM), tensile testing, Rockwell Superficial hardness testing, Vickers microhardness testing, scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). The effectiveness of the cleaning proceduremore » was evident in the pre- and post-cleaning photography and permitted accurate placement of the test specimens on the disks. Due to the limited amount of material available and the unique geometry of the disks, machine fixturing and test specimen design were critical aspects of this work. Multiple designs were considered and refined during mock-up test runs on unirradiated disks. The techniques used to successfully machine and test the various specimens will be presented along with a summary of important findings from the laboratory examinations.« less

The Universal Anaesthesia Machine (UAM): assessment of a new anaesthesia workstation built with global health in mind.

PubMed

de Beer, D A H; Nesbitt, F D; Bell, G T; Rapuleng, A

2017-04-01

The Universal Anaesthesia Machine has been developed as a complete anaesthesia workstation for use in low- and middle-income countries, where the provision of safe general anaesthesia is often compromised by unreliable supply of electricity and anaesthetic gases. We performed a functional and clinical assessment of this anaesthetic machine, with particular reference to novel features and functioning in the intended environment. The Universal Anaesthesia Machine was found to be reliable, safe and consistent across a range of tests during targeted functional testing. © 2016 The Association of Anaesthetists of Great Britain and Ireland.

The evolution of machining-induced surface of single-crystal FCC copper via nanoindentation

NASA Astrophysics Data System (ADS)

Zhang, Lin; Huang, Hu; Zhao, Hongwei; Ma, Zhichao; Yang, Yihan; Hu, Xiaoli

2013-05-01

The physical properties of the machining-induced new surface depend on the performance of the initial defect surface and deformed layer in the subsurface of the bulk material. In this paper, three-dimensional molecular dynamics simulations of nanoindentation are preformed on the single-point diamond turning surface of single-crystal copper comparing with that of pristine single-crystal face-centered cubic copper. The simulation results indicate that the nucleation of dislocations in the nanoindentation test on the machining-induced surface and pristine single-crystal copper is different. The dislocation embryos are gradually developed from the sites of homogeneous random nucleation around the indenter in the pristine single-crystal specimen, while the dislocation embryos derived from the vacancy-related defects are distributed in the damage layer of the subsurface beneath the machining-induced surface. The results show that the hardness of the machining-induced surface is softer than that of pristine single-crystal copper. Then, the nanocutting simulations are performed along different crystal orientations on the same crystal surface. It is shown that the crystal orientation directly influences the dislocation formation and distribution of the machining-induced surface. The crystal orientation of nanocutting is further verified to affect both residual defect generations and their propagation directions which are important in assessing the change of mechanical properties, such as hardness and Young's modulus, after nanocutting process.

Design and Development of E3 Antenna Container,

DTIC Science & Technology

1985-09-03

reinforced with square tubing. The walls and ceiling shall be insulated with expanded polystyrene . TEST LOCATION - This test will be performed at the...ceiling shall be insulated with expanded polystyrene . TEST LOCATION - This test will be performed at the Edgewater Machine & Fabricator’s facility...insulated with expanded polystyrene . TEST LOCATION - This test will be performed at the Edgewater Machine & Fabricator’s facility located at 200 N

Ship Model Testing

DTIC Science & Technology

2016-01-15

state-of-the-art equipment and to continue to produce excellent graduates in our field. Technical Approach In order to address our current testing ...New Additions • New material testing machine with environmental chamber • New dual-fuel test bed for Haeberle Laboratory • Upgrade existing...Southwark Emery universal test machine • 3D printer with ultra-high surface definition • CFD Workstations Since the inception of this grant, Webb

The responses of subjective feeling, task performance ability, cortisol and HRV for the various types of floor impact sound: a pilot study.

PubMed

Yun, Seok Hyeon; Park, Sang Jin; Sim, Chang Sun; Sung, Joo Hyun; Kim, Ahra; Lee, Jang Myeong; Lee, Sang Hyun; Lee, Jiho

2017-01-01

Recently, noise coming from the neighborhood via floor wall has become a great social problem. The noise between the floors can be a cause of physical and psychological problems, and the different types of floor impact sound (FIS) may have the different effects on the human's body and mind. The purpose of this study is to assess the responses of subjective feeling, task performance ability, cortisol and HRV for the various types of floor impact. Ten men and 5 women were enrolled in our study, and the English listening test was performed under the twelve different types of FIS, which were made by the combinations of bang machine (B), tapping machine (T), impact ball (I) and sound-proof mattress (M). The 15 subjects were exposed to each FIS for about 3 min, and the subjective annoyance, performance ability (English listening test), cortisol level of urine/saliva and heart rate variability (HRV) were examined. The sound pressure level (SPL) and frequency of FIS were analyzed. Repeated-measures ANOVA, paired t-test, Wilcoxon signed rank test were performed for data analysis. The SPL of tapping machine (T) was reduced with the soundproof mattress (M) by 3.9-7.3 dBA. Impact ball (I) was higher than other FIS in low frequency (31.5-125 Hz) by 10 dBA, and tapping machine (T) was higher than other FIS in high frequency (2-4 k Hz) by 10 dBA. The subjective annoyance is highest in the combination of bang machine and tapping machine (BT), and next in the tapping machine (T). The English listening score was also lowest in the BT, and next in T. The difference of salivary cortisol levels between various types of FIS was significant ( p  = 0.003). The change of HRV parameters by the change of FIS types was significant in some parameters, which were total power (TP) ( p  = 0.004), low frequency (LF) ( p  = 0.002) and high frequency (HF) ( p  = 0.011). These results suggest that the human's subjective and objective responses were different according to FIS types and those combinations.

Development of a Pressure Box to Evaluate Reusable-Launch-Vehicle Cryogenic-Tank Panels

NASA Technical Reports Server (NTRS)

Ambur, Damodar R.; Sikora, Joseph; Maguire, James F.; Winn, Peter M.

1996-01-01

A cryogenic pressure-box test machine has been designed and is being developed to test full-scale reusable-launch-vehicle cryogenic-tank panels. This machine is equipped with an internal pressurization system, a cryogenic cooling system, and a heating system to simulate the mechanical and thermal loading conditions that are representative of a reusable-launch-vehicle mission profile. The cryogenic cooling system uses liquid helium and liquid nitrogen to simulate liquid hydrogen and liquid oxygen tank internal temperatures. A quartz lamp heating system is used for heating the external surface of the test panels to simulate cryogenic-tank external surface temperatures during re-entry of the launch vehicle. The pressurization system uses gaseous helium and is designed to be controlled independently of the cooling system. The tensile loads in the axial direction of the test panel are simulated by means of hydraulic actuators and a load control system. The hoop loads in the test panel are reacted by load-calibrated turnbuckles attached to the skin and frame elements of the test panel. The load distribution in the skin and frames can be adjusted to correspond to the tank structure by using these turnbuckles. The seal between the test panel and the cryogenic pressure box is made from a reinforced Teflon material which can withstand pressures greater than 52 psig at cryogenic temperatures. Analytical results and tests on prototype test components indicate that most of the cryogenic-tank loading conditions that occur in flight can be simulated in the cryogenic pressure-box test machine.

[Effect of manual cleaning and machine cleaning for dental handpiece].

PubMed

Zhou, Xiaoli; Huang, Hao; He, Xiaoyan; Chen, Hui; Zhou, Xiaoying

2013-08-01

Comparing the dental handpiece' s cleaning effect between manual cleaning and machine cleaning. Eighty same contaminated dental handpieces were randomly divided into experimental group and control group, each group contains 40 pieces. The experimental group was treated by full automatic washing machine, and the control group was cleaned manually. The cleaning method was conducted according to the operations process standard, then ATP bioluminescence was used to test the cleaning results. Average relative light units (RLU) by ATP bioluminescence detection were as follows: Experimental group was 9, control group was 41. The two groups were less than the recommended RLU value provided by the instrument manufacturer (RLU < or = 45). There was significant difference between the two groups (P < 0.05). The cleaning quality of the experimental group was better than that of control group. It is recommended that the central sterile supply department should clean dental handpieces by machine to ensure the cleaning effect and maintain the quality.

[Study on high strength mica-based machinable glass-ceramic].

PubMed

Li, Hong; Ran, Junguo; Gou, Li; Wang, Fanghu

2004-02-01

The phase constitution, microstructure and properties of a new type of machinable glass-ceramics containing fluorophlogopite-type (FPT) Ca-mica for used in restorative dentistry were investigated. According to the results of X-ray diffraction (XRD) and energy-dispersive spectrometry(EDS), its main crystalline phases were FPT Ca-mica and t-ZrO2, together with few KxCa(1-x)/2Mg2Si4O10F2, m-ZrO2. The flexible strength was 235 MPa, which was nearly two times larger than that of the present mica-based dental materials, and the highest fracture toughness was 2.17 MPa.m1/2. The microstructure had a great effect on properties, the glass-ceramics contained a large volume, and the fine crystals showed higher strength. The material possessed typical microstructure of machinable glass-ceramics and displayed excellent machinability during drilling test and CAD/CAM.

Modeling of solid-state and excimer laser processes for 3D micromachining

NASA Astrophysics Data System (ADS)

Holmes, Andrew S.; Onischenko, Alexander I.; George, David S.; Pedder, James E.

2005-04-01

An efficient simulation method has recently been developed for multi-pulse ablation processes. This is based on pulse-by-pulse propagation of the machined surface according to one of several phenomenological models for the laser-material interaction. The technique allows quantitative predictions to be made about the surface shapes of complex machined parts, given only a minimal set of input data for parameter calibration. In the case of direct-write machining of polymers or glasses with ns-duration pulses, this data set can typically be limited to the surface profiles of a small number of standard test patterns. The use of phenomenological models for the laser-material interaction, calibrated by experimental feedback, allows fast simulation, and can achieve a high degree of accuracy for certain combinations of material, laser and geometry. In this paper, the capabilities and limitations of the approach are discussed, and recent results are presented for structures machined in SU8 photoresist.

Efficient Prediction of Low-Visibility Events at Airports Using Machine-Learning Regression

NASA Astrophysics Data System (ADS)

Cornejo-Bueno, L.; Casanova-Mateo, C.; Sanz-Justo, J.; Cerro-Prada, E.; Salcedo-Sanz, S.

2017-11-01

We address the prediction of low-visibility events at airports using machine-learning regression. The proposed model successfully forecasts low-visibility events in terms of the runway visual range at the airport, with the use of support-vector regression, neural networks (multi-layer perceptrons and extreme-learning machines) and Gaussian-process algorithms. We assess the performance of these algorithms based on real data collected at the Valladolid airport, Spain. We also propose a study of the atmospheric variables measured at a nearby tower related to low-visibility atmospheric conditions, since they are considered as the inputs of the different regressors. A pre-processing procedure of these input variables with wavelet transforms is also described. The results show that the proposed machine-learning algorithms are able to predict low-visibility events well. The Gaussian process is the best algorithm among those analyzed, obtaining over 98% of the correct classification rate in low-visibility events when the runway visual range is {>}1000 m, and about 80% under this threshold. The performance of all the machine-learning algorithms tested is clearly affected in extreme low-visibility conditions ({<}500 m). However, we show improved results of all the methods when data from a neighbouring meteorological tower are included, and also with a pre-processing scheme using a wavelet transform. Also presented are results of the algorithm performance in daytime and nighttime conditions, and for different prediction time horizons.

VIEW EASTLEFTBUILDING 2 PHYSICAL TESTING HOUSE (1928) RIGHTBUILDING 7 MACHINE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

VIEW EAST-LEFT-BUILDING 2 PHYSICAL TESTING HOUSE (1928) RIGHT-BUILDING 7 MACHINE SHOP (1901 SECTION) - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

A low-cost machine vision system for the recognition and sorting of small parts

NASA Astrophysics Data System (ADS)

Barea, Gustavo; Surgenor, Brian W.; Chauhan, Vedang; Joshi, Keyur D.

2018-04-01

An automated machine vision-based system for the recognition and sorting of small parts was designed, assembled and tested. The system was developed to address a need to expose engineering students to the issues of machine vision and assembly automation technology, with readily available and relatively low-cost hardware and software. This paper outlines the design of the system and presents experimental performance results. Three different styles of plastic gears, together with three different styles of defective gears, were used to test the system. A pattern matching tool was used for part classification. Nine experiments were conducted to demonstrate the effects of changing various hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. It was found that the system could achieve a maximum system accuracy of 95% at a feed rate of 60 parts/min, for a given set of parameter settings. Future work will be looking at the effect of lighting.

Advanced warfighter machine interface (Invited Paper)

NASA Astrophysics Data System (ADS)

Franks, Erin

2005-05-01

Future military crewmen may have more individual and shared tasks to complete throughout a mission as a result of smaller crew sizes and an increased number of technology interactions. To maintain reasonable workload levels, the Warfighter Machine Interface (WMI) must provide information in a consistent, logical manner, tailored to the environment in which the soldier will be completing their mission. This paper addresses design criteria for creating an advanced, multi-modal warfighter machine interface for on-the-move mounted operations. The Vetronics Technology Integration (VTI) WMI currently provides capabilities such as mission planning and rehearsal, voice and data communications, and manned/unmanned vehicle payload and mobility control. A history of the crewstation and more importantly, the WMI software will be provided with an overview of requirements and criteria used for completing the design. Multiple phases of field and laboratory testing provide the opportunity to evaluate the design and hardware in stationary and motion environments. Lessons learned related to system usability and user performance are presented with mitigation strategies to be tested in the future.

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

PubMed

Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

2014-09-04

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

Design and application of the falling vertical sorting machine

NASA Astrophysics Data System (ADS)

Zuo, Ping; Peng, Tao; Yang, Hai

2018-04-01

In the process of tobacco production, it is necessary to pack the smoke according to the needs of different customers. A sorting machine is used to pick up the cigarette at present, there is a launch channel machine, a percussible vertical machine, But in the sorting process, the rolling channel machine is different in terms of the quality of smoke and the frictional force. It is difficult to ensure the location and posture of the belt sorting line, which causes the manipulator to not grasp. The strike type vertical machine is difficult to control the parallelism of the smoke. Now this team has developed a falling sorting machine, which has solved the smoke drop of a cigarette to the transmission belt. There will not be no code, can satisfy most of the different types of smoke sorting and no damage to smoke status. The dynamic characteristics such as the angular error of the opening and closing mechanism are carried out by ADAMS software. The simulation results show that the maximum angular error is 0.016rad. Through the test of the device, the goods falling speed is 7031/hour, the good of the falling position error within 2mm, meet the crawl accuracy requirements of the palletizing robot.

Two Body Wear of Newly Introduced Nanocomposite Teeth and Cross Linked Four Layered Acrylic Teeth: a Comparitive In Vitro Study.

PubMed

Ilangkumaran, R; Srinivasan, J; Baburajan, K; Balaji, N

2014-12-01

Wear of complete denture teeth results in compromise in denture esthetics and functions. To counteract this problem, artificial teeth with increased wear resistance had been introduced in the market such as nanocomposite teeth. The purpose of this study was to compare the amount of wear between nanocomposite teeth and acrylic teeth. Fifteen specimens were chosen from each group namely the nanocomposite teeth (SR_-PHONARES) and the acrylic teeth (ACRY PLUS). Maxillary premolar was only chosen for testing and the samples were customized according to the specifications of the pin on disc machine. Pin on disc machine is a two body tribometer which quantifies the amount of wear under a specific load and time. Test samples were mounted on to the receptacle of the pin on disc machine and tested under a load of 0.3 kg for 1,000 cycles of rotation against a 600 grit emery paper. The amount of wear is displayed from the digital reading obtained from the pin on disc machine. After statistical analysis, it was found that, the amount of wear is more in four layered acrylic teeth. The p value obtained is 0.002 (<0.005) thus implies that the difference in wear between nanocomposite teeth and acrylic teeth is statistically significant. Though the nanocomposite teeth has less amount of wear than the four layered acrylic teeth, the difference is very less and adds only to a little clinical significance but the cost of the nanocomposite is four times that of the acrylic teeth. Further clinical studies must be performed to confirm our results.

Image processing and machine learning for fully automated probabilistic evaluation of medical images.

PubMed

Sajn, Luka; Kukar, Matjaž

2011-12-01

The paper presents results of our long-term study on using image processing and data mining methods in a medical imaging. Since evaluation of modern medical images is becoming increasingly complex, advanced analytical and decision support tools are involved in integration of partial diagnostic results. Such partial results, frequently obtained from tests with substantial imperfections, are integrated into ultimate diagnostic conclusion about the probability of disease for a given patient. We study various topics such as improving the predictive power of clinical tests by utilizing pre-test and post-test probabilities, texture representation, multi-resolution feature extraction, feature construction and data mining algorithms that significantly outperform medical practice. Our long-term study reveals three significant milestones. The first improvement was achieved by significantly increasing post-test diagnostic probabilities with respect to expert physicians. The second, even more significant improvement utilizes multi-resolution image parametrization. Machine learning methods in conjunction with the feature subset selection on these parameters significantly improve diagnostic performance. However, further feature construction with the principle component analysis on these features elevates results to an even higher accuracy level that represents the third milestone. With the proposed approach clinical results are significantly improved throughout the study. The most significant result of our study is improvement in the diagnostic power of the whole diagnostic process. Our compound approach aids, but does not replace, the physician's judgment and may assist in decisions on cost effectiveness of tests. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Systematics for checking geometric errors in CNC lathes

NASA Astrophysics Data System (ADS)

Araújo, R. P.; Rolim, T. L.

2015-10-01

Non-idealities presented in machine tools compromise directly both the geometry and the dimensions of machined parts, generating distortions in the project. Given the competitive scenario among different companies, it is necessary to have knowledge of the geometric behavior of these machines in order to be able to establish their processing capability, avoiding waste of time and materials as well as satisfying customer requirements. But despite the fact that geometric tests are important and necessary to clarify the use of the machine correctly, therefore preventing future damage, most users do not apply such tests on their machines for lack of knowledge or lack of proper motivation, basically due to two factors: long period of time and high costs of testing. This work proposes a systematics for checking straightness and perpendicularity errors in CNC lathes demanding little time and cost with high metrological reliability, to be used on factory floors of small and medium-size businesses to ensure the quality of its products and make them competitive.

Evaluation of machine learning tools for inspection of steam generator tube structures using pulsed eddy current

NASA Astrophysics Data System (ADS)

Buck, J. A.; Underhill, P. R.; Morelli, J.; Krause, T. W.

2017-02-01

Degradation of nuclear steam generator (SG) tubes and support structures can result in a loss of reactor efficiency. Regular in-service inspection, by conventional eddy current testing (ECT), permits detection of cracks, measurement of wall loss, and identification of other SG tube degradation modes. However, ECT is challenged by overlapping degradation modes such as might occur for SG tube fretting accompanied by tube off-set within a corroding ferromagnetic support structure. Pulsed eddy current (PEC) is an emerging technology examined here for inspection of Alloy-800 SG tubes and associated carbon steel drilled support structures. Support structure hole size was varied to simulate uniform corrosion, while SG tube was off-set relative to hole axis. PEC measurements were performed using a single driver with an 8 pick-up coil configuration in the presence of flat-bottom rectangular frets as an overlapping degradation mode. A modified principal component analysis (MPCA) was performed on the time-voltage data in order to reduce data dimensionality. The MPCA scores were then used to train a support vector machine (SVM) that simultaneously targeted four independent parameters associated with; support structure hole size, tube off-centering in two dimensions and fret depth. The support vector machine was trained, tested, and validated on experimental data. Results were compared with a previously developed artificial neural network (ANN) trained on the same data. Estimates of tube position showed comparable results between the two machine learning tools. However, the ANN produced better estimates of hole inner diameter and fret depth. The better results from ANN analysis was attributed to challenges associated with the SVM when non-constant variance is present in the data.

77 FR 3726 - Tire Fuel Efficiency Consumer Information Program

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-25

... test machine(s) for the TFECIP. This would allow tire manufacturers to know the identity of the machine... will I have to speak at the public workshop? Once NHTSA learns how many people have registered to speak...

The Efficacy of Machine Learning Programs for Navy Manpower Analysis

DTIC Science & Technology

1993-03-01

This thesis investigated the efficacy of two machine learning programs for Navy manpower analysis. Two machine learning programs, AIM and IXL, were...to generate models from the two commercial machine learning programs. Using a held out sub-set of the data the capabilities of the three models were...partial effects. The author recommended further investigation of AIM’s capabilities, and testing in an operational environment.... Machine learning , AIM, IXL.

A superconducting homopolar motor and generator—new approaches

NASA Astrophysics Data System (ADS)

Fuger, Rene; Matsekh, Arkadiy; Kells, John; Sercombe, D. B. T.; Guina, Ante

2016-03-01

Homopolar machines were the first continuously running electromechanical converters ever demonstrated but engineering challenges and the rapid development of AC technology prevented wider commercialisation. Recent developments in superconducting, cryogenic and sliding contact technology together with new areas of application have led to a renewed interest in homopolar machines. Some of the advantages of these machines are ripple free constant torque, pure DC operation, high power-to-weight ratio and that rotating magnets or coils are not required. In this paper we present our unique approach to high power and high torque homopolar electromagnetic turbines using specially designed high field superconducting magnets and liquid metal current collectors. The unique arrangement of the superconducting coils delivers a high static drive field as well as effective shielding for the field critical sliding contacts. The novel use of additional shielding coils reduces weight and stray field of the system. Liquid metal current collectors deliver a low resistance, stable and low maintenance sliding contact by using a thin liquid metal layer that fills a circular channel formed by the moving edge of a rotor and surrounded by a conforming stationary channel of the stator. Both technologies are critical to constructing high performance machines. Homopolar machines are pure DC devices that utilise only DC electric and magnetic fields and have no AC losses in the coils or the supporting structure. Guina Energy Technologies has developed, built and tested different motor and generator concepts over the last few years and has combined its experience to develop a new generation of homopolar electromagnetic turbines. This paper summarises the development process, general design parameters and first test results of our high temperature superconducting test motor.

Optimal input selection for neural machine interfaces predicting multiple non-explicit outputs.

PubMed

Krepkovich, Eileen T; Perreault, Eric J

2008-01-01

This study implemented a novel algorithm that optimally selects inputs for neural machine interface (NMI) devices intended to control multiple outputs and evaluated its performance on systems lacking explicit output. NMIs often incorporate signals from multiple physiological sources and provide predictions for multidimensional control, leading to multiple-input multiple-output systems. Further, NMIs often are used with subjects who have motor disabilities and thus lack explicit motor outputs. Our algorithm was tested on simulated multiple-input multiple-output systems and on electromyogram and kinematic data collected from healthy subjects performing arm reaches. Effects of output noise in simulated systems indicated that the algorithm could be useful for systems with poor estimates of the output states, as is true for systems lacking explicit motor output. To test efficacy on physiological data, selection was performed using inputs from one subject and outputs from a different subject. Selection was effective for these cases, again indicating that this algorithm will be useful for predictions where there is no motor output, as often is the case for disabled subjects. Further, prediction results generalized for different movement types not used for estimation. These results demonstrate the efficacy of this algorithm for the development of neural machine interfaces.

Machine learning-based coreference resolution of concepts in clinical documents

PubMed Central

Ware, Henry; Mullett, Charles J; El-Rawas, Oussama

2012-01-01

Objective Coreference resolution of concepts, although a very active area in the natural language processing community, has not yet been widely applied to clinical documents. Accordingly, the 2011 i2b2 competition focusing on this area is a timely and useful challenge. The objective of this research was to collate coreferent chains of concepts from a corpus of clinical documents. These concepts are in the categories of person, problems, treatments, and tests. Design A machine learning approach based on graphical models was employed to cluster coreferent concepts. Features selected were divided into domain independent and domain specific sets. Training was done with the i2b2 provided training set of 489 documents with 6949 chains. Testing was done on 322 documents. Results The learning engine, using the un-weighted average of three different measurement schemes, resulted in an F measure of 0.8423 where no domain specific features were included and 0.8483 where the feature set included both domain independent and domain specific features. Conclusion Our machine learning approach is a promising solution for recognizing coreferent concepts, which in turn is useful for practical applications such as the assembly of problem and medication lists from clinical documents. PMID:22582205

A high reliability module with thermoelectric device by molding technology for M2M wireless sensor network

NASA Astrophysics Data System (ADS)

Nakagawa, K.; Tanaka, T.; Suzuki, T.

2015-10-01

This paper presents the fabrication of a new energy harvesting module that uses a thermoelectric device (TED) by using molding technology. Through molding technology, the TED and circuit board can be properly protected and a heat-radiating fin structure can be simultaneously constructed. The output voltage per heater temperature of the TED module at 20 °C ambient temperature is 8 mV K-1, similar to the result with the aluminum heat sink which is almost the same fin size as the TED module. The accelerated environmental tests are performed on a damp heat test, which is an aging test under high temperature and high humidity, highly accelerated temperature, and humidity stress test (HAST) for the purpose of evaluating the electrical reliability in harsh environments, cold test and thermal cycle test to evaluate degrading characteristics by cycling through two temperatures. All test results indicate that the TED and circuit board can be properly protected from harsh temperature and humidity by using molding technology because the output voltage of after-tested modules is reduced by less than 5%. This study presents a novel fabrication method for a high reliability TED-installed module appropriate for Machine to Machine wireless sensor networks.

A formal protocol test procedure for the Survivable Adaptable Fiber Optic Embedded Network (SAFENET)

NASA Astrophysics Data System (ADS)

High, Wayne

1993-03-01

This thesis focuses upon a new method for verifying the correct operation of a complex, high speed fiber optic communication network. These networks are of growing importance to the military because of their increased connectivity, survivability, and reconfigurability. With the introduction and increased dependence on sophisticated software and protocols, it is essential that their operation be correct. Because of the speed and complexity of fiber optic networks being designed today, they are becoming increasingly difficult to test. Previously, testing was accomplished by application of conformance test methods which had little connection with an implementation's specification. The major goal of conformance testing is to ensure that the implementation of a profile is consistent with its specification. Formal specification is needed to ensure that the implementation performs its intended operations while exhibiting desirable behaviors. The new conformance test method presented is based upon the System of Communicating Machine model which uses a formal protocol specification to generate a test sequence. The major contribution of this thesis is the application of the System of Communicating Machine model to formal profile specifications of the Survivable Adaptable Fiber Optic Embedded Network (SAFENET) standard which results in the derivation of test sequences for a SAFENET profile. The results applying this new method to SAFENET's OSI and Lightweight profiles are presented.

Can a Smartphone Diagnose Parkinson Disease? A Deep Neural Network Method and Telediagnosis System Implementation.

PubMed

Zhang, Y N

2017-01-01

Parkinson's disease (PD) is primarily diagnosed by clinical examinations, such as walking test, handwriting test, and MRI diagnostic. In this paper, we propose a machine learning based PD telediagnosis method for smartphone. Classification of PD using speech records is a challenging task owing to the fact that the classification accuracy is still lower than doctor-level. Here we demonstrate automatic classification of PD using time frequency features, stacked autoencoders (SAE), and K nearest neighbor (KNN) classifier. KNN classifier can produce promising classification results from useful representations which were learned by SAE. Empirical results show that the proposed method achieves better performance with all tested cases across classification tasks, demonstrating machine learning capable of classifying PD with a level of competence comparable to doctor. It concludes that a smartphone can therefore potentially provide low-cost PD diagnostic care. This paper also gives an implementation on browser/server system and reports the running time cost. Both advantages and disadvantages of the proposed telediagnosis system are discussed.

Can a Smartphone Diagnose Parkinson Disease? A Deep Neural Network Method and Telediagnosis System Implementation

PubMed Central

2017-01-01

Parkinson's disease (PD) is primarily diagnosed by clinical examinations, such as walking test, handwriting test, and MRI diagnostic. In this paper, we propose a machine learning based PD telediagnosis method for smartphone. Classification of PD using speech records is a challenging task owing to the fact that the classification accuracy is still lower than doctor-level. Here we demonstrate automatic classification of PD using time frequency features, stacked autoencoders (SAE), and K nearest neighbor (KNN) classifier. KNN classifier can produce promising classification results from useful representations which were learned by SAE. Empirical results show that the proposed method achieves better performance with all tested cases across classification tasks, demonstrating machine learning capable of classifying PD with a level of competence comparable to doctor. It concludes that a smartphone can therefore potentially provide low-cost PD diagnostic care. This paper also gives an implementation on browser/server system and reports the running time cost. Both advantages and disadvantages of the proposed telediagnosis system are discussed. PMID:29075547

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

PubMed Central

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-01-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008–2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0. PMID:27892471

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies.

PubMed

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-28

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Reliability Study of Solder Paste Alloy for the Improvement of Solder Joint at Surface Mount Fine-Pitch Components.

PubMed

Rahman, Mohd Nizam Ab; Zubir, Noor Suhana Mohd; Leuveano, Raden Achmad Chairdino; Ghani, Jaharah A; Mahmood, Wan Mohd Faizal Wan

2014-12-02

The significant increase in metal costs has forced the electronics industry to provide new materials and methods to reduce costs, while maintaining customers' high-quality expectations. This paper considers the problem of most electronic industries in reducing costly materials, by introducing a solder paste with alloy composition tin 98.3%, silver 0.3%, and copper 0.7%, used for the construction of the surface mount fine-pitch component on a Printing Wiring Board (PWB). The reliability of the solder joint between electronic components and PWB is evaluated through the dynamic characteristic test, thermal shock test, and Taguchi method after the printing process. After experimenting with the dynamic characteristic test and thermal shock test with 20 boards, the solder paste was still able to provide a high-quality solder joint. In particular, the Taguchi method is used to determine the optimal control parameters and noise factors of the Solder Printer (SP) machine, that affects solder volume and solder height. The control parameters include table separation distance, squeegee speed, squeegee pressure, and table speed of the SP machine. The result shows that the most significant parameter for the solder volume is squeegee pressure (2.0 mm), and the solder height is the table speed of the SP machine (2.5 mm/s).

Reliability Study of Solder Paste Alloy for the Improvement of Solder Joint at Surface Mount Fine-Pitch Components

PubMed Central

Rahman, Mohd Nizam Ab.; Zubir, Noor Suhana Mohd; Leuveano, Raden Achmad Chairdino; Ghani, Jaharah A.; Mahmood, Wan Mohd Faizal Wan

2014-01-01

The significant increase in metal costs has forced the electronics industry to provide new materials and methods to reduce costs, while maintaining customers’ high-quality expectations. This paper considers the problem of most electronic industries in reducing costly materials, by introducing a solder paste with alloy composition tin 98.3%, silver 0.3%, and copper 0.7%, used for the construction of the surface mount fine-pitch component on a Printing Wiring Board (PWB). The reliability of the solder joint between electronic components and PWB is evaluated through the dynamic characteristic test, thermal shock test, and Taguchi method after the printing process. After experimenting with the dynamic characteristic test and thermal shock test with 20 boards, the solder paste was still able to provide a high-quality solder joint. In particular, the Taguchi method is used to determine the optimal control parameters and noise factors of the Solder Printer (SP) machine, that affects solder volume and solder height. The control parameters include table separation distance, squeegee speed, squeegee pressure, and table speed of the SP machine. The result shows that the most significant parameter for the solder volume is squeegee pressure (2.0 mm), and the solder height is the table speed of the SP machine (2.5 mm/s). PMID:28788270

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

NASA Astrophysics Data System (ADS)

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Evolution of tensile design stresses for lumber

Treesearch

William L. Galligan; C. C. Gerhards; R. L. Ethington

1979-01-01

Until approximately 1965, allowable design stresses for lumber in tension were taken as equal to those assigned for bending. As interest in tensile properties increased, testing machines were designed specifically to stress lumber in tension. Research results that accumulated on tensile tests of full-size lumber suggested lower design stresses for tension than for...

Skyline Harvesting in Appalachia

Treesearch

J. N. Kochenderfer; G. W. Wendel

1978-01-01

The URUS, a small standing skyline system, was tested in the Appalachian Mountains of north-central West Virginia. Some problems encountered with this small, mobile system are discussed. From the results of this test and observation of skyline systems used in the western United States, the authors suggest some machine characteristics that would be desirable for use in...

Improvement of a Harvester Based, Multispectral, Seed Cotton Fiber Quality Sensor

USDA-ARS?s Scientific Manuscript database

A multispectral sensor for in-situ seed cotton fiber quality measurement was developed and tested at Texas A&M University. Results of initial testing of the sensor using machine harvested seed cotton have shown promise. Improvements have been made to the system and the measurement method to meet t...

Test build from Robotic Fiber Placement Machine

NASA Image and Video Library

2015-10-01

MAJID BABAI, LEFT, CHIEF OF THE NONMETALLIC MANUFACTURING BRANCH AT MARSHALL, AND STEPHEN RICHARDSON, LEAD FOR THE STRUCTURAL DEVELOPMENT TEAM, TAKE A CLOSER LOOK AT ONE OF THE FIRST TEST BUILDS MADE BY THE NEW ROBOTIC FIBER PLACEMENT MACHINE BEHIND THEM.

Tensile strength of ramie yarn (spinning by machine)/HDPE thermoplastic matrix composites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banowati, Lies, E-mail: liesbano@gmail.com; Hadi, Bambang K., E-mail: bkhadi@ae.itb.ac.id; Suratman, Rochim, E-mail: rochim@material.itb.ac.id

2016-03-29

Technological developments should be trooped to prevent a gap between technology and environmental sustainability, then it needs to be developed “Green technology”. In this research is making of green composites which use natural fiber ramie as reinforcement. Whereas the matrix used was HDPE (High Density Polyethylene) thermoplastic polymer which could be recycled and had a good formability and flexibility. The ramie yarns and fibers for unidirectional (0°) direction respectively were mixed with HDPE powder and processed using hot compression molding. The surface morphology was observed by SEM (Scanning Electrone Microscopy). Results showed that both tensile strength of the ramie fiber/HDPEmore » composites increased in comparison with the ramie yarn (spinning by machine)/HDPE composites. However, the ramie yarn (spinning by machine)/HDPE composites have a good producibility for wider application. Analysis of the test results using the Weibull distribution as approaches to modeling the reliability of the specimens.« less

Analysis of noise pollution in an andesite quarry with the use of simulation studies and evaluation indices.

PubMed

Kosała, Krzysztof; Stępień, Bartłomiej

2016-01-01

This paper presents the verification of two partial indices proposed for the evaluation of continuous and impulse noise pollution in quarries. These indices, together with the sound power of machines index and the noise hazard index at the workstation, are components of the global index of assessment of noise hazard in the working environment of a quarry. This paper shows the results of acoustic tests carried out in an andesite quarry. Noise generated by machines and from performed blasting works was investigated. On the basis of acoustic measurements carried out in real conditions, the sound power levels of machines and the phenomenon of explosion were determined and, based on the results, three-dimensional models of acoustic noise propagation in the quarry were developed. To assess the degree of noise pollution in the area of the quarry, the continuous and impulse noise indices were used.

Ada Compiler Validation Summary Report. Certificate Number: 891129W1. 10198 International Business Machines Corporation, the IBM Development System for the Ada Language AIX/RT Follow-on, Version 1.1 IBM RT Follow-on. Completion of On-Site Testing: 29 November 1989

DTIC Science & Technology

1989-11-29

nvmbe’j International Business Machines Corporation Wright-Patterson AFB, The IBM Development System for the Ada Language AIX/RT follow-on, Version 1.1...Certificate Number: 891129W1.10198 International Business Machines Corporation The IBM Development System for the Ada Language AIX/RT Follow-on, Version 1.1 IBM...scripts provided by International Business Machines Corporation and reviewed by the validation team. The compiler was tested using all the following

Telescoping magnetic ball bar test gage

DOEpatents

Bryan, J.B.

1982-03-15

A telescoping magnetic ball bar test gage for determining the accuracy of machine tools, including robots, and those measuring machines having non-disengagable servo drives which cannot be clutched out. Two gage balls are held and separated from one another by a telescoping fixture which allows them relative radial motional freedom but not relative lateral motional freedom. The telescoping fixture comprises a parallel reed flexure unit and a rigid member. One gage ball is secured by a magnetic socket knuckle assembly which fixes its center with respect to the machine being tested. The other gage ball is secured by another magnetic socket knuckle assembly which is engaged or held by the machine in such manner that the center of that ball is directed to execute a prescribed trajectory, all points of which are equidistant from the center of the fixed gage ball. As the moving ball executes its trajectory, changes in the radial distance between the centers of the two balls caused by inaccuracies in the machine are determined or measured by a linear variable differential transformer (LVDT) assembly actuated by the parallel reed flexure unit. Measurements can be quickly and easily taken for multiple trajectories about several different fixed ball locations, thereby determining the accuracy of the machine.

Phacoemulsification tip vacuum pressure: Comparison of 4 devices.

PubMed

Payne, Marielle; Georgescu, Dan; Waite, Aaron N; Olson, Randall J

2006-08-01

To determine the vacuum pressure generated by 4 phacoemulsification devices measured at the phacoemulsification tip. University ophthalmology department. The effective vacuum pressures generated by the Sovereign (AMO), Millennium (Bausch & Lomb), Legacy AdvanTec (Alcon Laboratories), and Infiniti (Alcon Laboratories) phacoemulsification machines were measured with a device that isolated the phacoemulsification tip in a chamber connected to a pressure gauge. The 4 machines were tested at multiple vacuum limit settings, and the values were recorded after the foot pedal was fully depressed and the pressure had stabilized. The AdvanTec and Infiniti machines were tested with and without occlusion of the Aspiration Bypass System (ABS) side port (Alcon Laboratories). The Millennium machine was tested using venturi and peristaltic pumps. The machines generated pressures close to the expected at maximum vacuum settings between 100 mm Hg and 500 mm Hg with few intermachine variations. There was no significant difference between pressures generated using 19- or 20-gauge tips (Millennium and Sovereign). The addition of an ABS side port decreased vacuum by a mean of 12.1% (P < .0001). Although there were some variations in vacuum pressures among phacoemulsification machines, particularly when an aspiration bypass tip was used, these discrepancies are probably not clinically significant.

Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

NASA Astrophysics Data System (ADS)

Pasquato, Mario; Chung, Chul

2016-05-01

Context. Machine-learning (ML) solves problems by learning patterns from data with limited or no human guidance. In astronomy, ML is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims: We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify globular clusters (GCs) that may have a history of merging from observational data. Methods: We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After carrying out dimensionality reduction on the feature space, the resulting datapoints are fed in to various classification algorithms. Using repeated random subsampling validation, we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations. Results: The three algorithms we considered (C5.0 trees, k-nearest neighbour, and support-vector machines) all achieve a test misclassification rate of about 10% without parameter tuning, with support-vector machines slightly outperforming the others. The first principal component of feature space correlates with cluster concentration. If we exclude it from the regression, the performance of the algorithms is only slightly reduced.

Graph-based structural change detection for rotating machinery monitoring

NASA Astrophysics Data System (ADS)

Lu, Guoliang; Liu, Jie; Yan, Peng

2018-01-01

Detection of structural changes is critically important in operational monitoring of a rotating machine. This paper presents a novel framework for this purpose, where a graph model for data modeling is adopted to represent/capture statistical dynamics in machine operations. Meanwhile we develop a numerical method for computing temporal anomalies in the constructed graphs. The martingale-test method is employed for the change detection when making decisions on possible structural changes, where excellent performance is demonstrated outperforming exciting results such as the autoregressive-integrated-moving average (ARIMA) model. Comprehensive experimental results indicate good potentials of the proposed algorithm in various engineering applications. This work is an extension of a recent result (Lu et al., 2017).

List of Research Publications 1940-1980

DTIC Science & Technology

1981-10-01

comparison of the amount of tolerance for misplaced answers found in the GPO and the IBM machine-scored answer sheets. January 1942. (X6304) 1-18 A& .1...machine scoring of answer sheets. March 1942. The effect of the use of No. I pencils on the accuracy of scoring IBM answer sheets by machine. July 1942...X6427) 482 Hobbies - IBM code. 483 Relationship of Classification Test, R-I and WAC Classi- 4023 fication Test-2 for a recruiting station population

Correlation of Noise Signature to Pulsed Power Events at the HERMES III Accelerator.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Barbara; Joseph, Nathan Ryan; Salazar, Juan Diego

2016-11-01

The HERMES III accelerator, which is located at Sandia National Laboratories' Tech Area IV, is the largest pulsed gamma X-ray source in the world. The accelerator is made up of 20 inductive cavities that are charged to 1 MV each by complex pulsed power circuitry. The firing time of the machine components ranges between the microsecond and nanosecond timescales. This results in a variety of electromagnetic frequencies when the accelerator fires. Testing was done to identify the HERMES electromagnetic noise signal and to map it to the various accelerator trigger events. This report will show the measurement methods used tomore » capture the noise spectrum produced from the machine and correlate this noise signature with machine events.« less

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed

Nadkarni, P M; Miller, P L

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques.

PubMed

Monte-Moreno, Enric

2011-10-01

This work presents a system for a simultaneous non-invasive estimate of the blood glucose level (BGL) and the systolic (SBP) and diastolic (DBP) blood pressure, using a photoplethysmograph (PPG) and machine learning techniques. The method is independent of the person whose values are being measured and does not need calibration over time or subjects. The architecture of the system consists of a photoplethysmograph sensor, an activity detection module, a signal processing module that extracts features from the PPG waveform, and a machine learning algorithm that estimates the SBP, DBP and BGL values. The idea that underlies the system is that there is functional relationship between the shape of the PPG waveform and the blood pressure and glucose levels. As described in this paper we tested this method on 410 individuals without performing any personalized calibration. The results were computed after cross validation. The machine learning techniques tested were: ridge linear regression, a multilayer perceptron neural network, support vector machines and random forests. The best results were obtained with the random forest technique. In the case of blood pressure, the resulting coefficients of determination for reference vs. prediction were R(SBP)(2)=0.91, R(DBP)(2)=0.89, and R(BGL)(2)=0.90. For the glucose estimation, distribution of the points on a Clarke error grid placed 87.7% of points in zone A, 10.3% in zone B, and 1.9% in zone D. Blood pressure values complied with the grade B protocol of the British Hypertension society. An effective system for estimate of blood glucose and blood pressure from a photoplethysmograph is presented. The main advantage of the system is that for clinical use it complies with the grade B protocol of the British Hypertension society for the blood pressure and only in 1.9% of the cases did not detect hypoglycemia or hyperglycemia. Copyright © 2011 Elsevier B.V. All rights reserved.

Development and testing of a computer assisted remote-control system for the compact loader-trammer. Report of Investigations/1992

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruff, T.M.

1992-01-01

A prototype mucking machine designed to operate in narrow vein stopes was developed by Foster-Miller, Inc., Waltham, MA, under contract with the U.S. Bureau of Mines. The machine, called a compact loader/trammer, or minimucker, was designed to replace slusher muckers in narrow-vein underground mines. The minimucker is a six-wheel-drive, skid-steered, load-haul-dump machine that loads muck at the front with a novel slide-bucket system and ejects it out the rear so that the machine does not have to be turned around. To correct deficiencies of the tether remote control system, a computer-based, radio remote control was retrofitted to the minimucker. Initialmore » tests indicated a need to assist the operator in guiding the machine in narrow stopes and an automatic guidance system that used ultrasonic ranging sensors and a wall-following algorithm was installed. Additional tests in a simulated test stope showed that these changes improved the operation of the minimucker. The design and functions of the minimucker and its computer-based, remote control system are reviewed, and an ultrasonic, sensor-based guidance system is described.« less

Reducing forces during drilling brittle hard materials by using ultrasonic and variation of coolant

NASA Astrophysics Data System (ADS)

Schopf, C.; Rascher, R.

2016-11-01

The process of ultrasonic machining is especially used for brittle hard materials as the additional ultrasonic vibration of the tool at high frequencies and low amplitudes acts like a hammer on the surface. With this technology it is possible to drill holes with lower forces, therefor the machining can be done faster and the worktime is much less than conventionally. A three-axis dynamometer was used to measure the forces, which act between the tool and the sample part. A focus is set on the sharpness of the tool. The results of a test series are based on the Sauer Ultrasonic Grinding Centre. On the same machine it is possible to drill holes in the conventional way. Additional to the ultasonic Input the type an concentration of coolant is important for the Drilling-force. In the test there were three different coolant and three different concentrations tested. The combination of ultrasonic vibration and the right coolant and concentration is the best way to reduce the Forces. Another positive effect is, that lower drilling-forces produce smaller chipping on the edge of the hole. The way to reduce the forces and chipping is the main issue of this paper.

A tensile machine with a novel optical load cell for soft biological tissues application.

PubMed

Faturechi, Rahim; Hashemi, Ata; Abolfathi, Nabiollah

2014-11-01

The uniaxial tensile testing machine is the most common device used to measure the mechanical properties of industrial and biological materials. The need for a low-cost uniaxial tension testing device for small research centers has always been the subject of research. To address this need, a novel uniaxial tensile testing machine was designed and fabricated to measure the mechanical properties of soft biological tissues. The device is equipped with a new low-cost load cell which works based on the linear displacement/force relationship of beams. The deflection of the beam load cell is measured optically by a digital microscope with an accuracy of 1 µm. The stiffness of the designed load cell was experimentally and theoretically determined at 100 N mm(-1). The stiffness of the load cell can be easily adjusted according to the tissue's strength. The force-time behaviour of soft tissue specimens was obtained by an in-house image processing program. To demonstrate the efficiency of the fabricated device, the mechanical properties of amnion tissue was measured and compared with available data. The obtained results indicate a strong agreement with that of previous studies.

Wear Characterization of Carbon Nanotubes Reinforced Acetal Spur, Helical, Bevel and Worm Gears Using a TS Universal Test Rig

NASA Astrophysics Data System (ADS)

Yousef, Samy; Osman, T. A.; Abdalla, Abdelrahman H.; Zohdy, Gamal A.

2015-12-01

Although the applications of nanotechnologies are increasing, there remains a significant barrier between nanotechnology and machine element applications. This work aims to remove this barrier by blending carbon nanotubes (CNT) with common types of acetal polymer gears (spur, helical, bevel and worm). This was done by using adhesive oil (paraffin) during injection molding to synthesize a flange and short bars containing 0.02% CNT by weight. The flanges and short bars were machined using hobbing and milling machines to produce nanocomposite polymer gears. Some defects that surfaced in previous work, such as the appearance of bubbles and unmelted pellets during the injection process, were avoided to produce an excellent dispersion of CNT in the acetal. The wear resistances of the gears were measured by using a TS universal test rig using constant parameters for all of the gears that were fabricated. The tests were run at a speed of 1420 rpm and a torque of 4 Nm. The results showed that the wear resistances of the CNT/acetal gears were increased due to the addition of CNT, especially the helical, bevel and worm gears.

Transformer and Meter Tester

NASA Technical Reports Server (NTRS)

Stoms, R. M.

1984-01-01

Numerically-controlled 5-axis machine tool uses transformer and meter to determine and indicate whether tool is in home position, but lacks built-in test mode to check them. Tester makes possible test, and repair of components at machine rather then replace them when operation seems suspect.

Starter/generator testing

NASA Astrophysics Data System (ADS)

Anon

1994-10-01

Sundstrand Aerospace and GE Aircraft Engines have studied the switched reluctance machine for use as an integral starter/generator for future aircraft engines. They have conducted an initial, low-power testing of the starter/generator, which is based on power inverters using IGBT-technology semiconductors, to verify its feasibility in the externally mounted version of the integral starter/generator. This preliminary testing of the 250-kW starter/generator reveals favorable results.

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

Optimization of Support Vector Machine (SVM) for Object Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew; Dhingra, Neil; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

The Support Vector Machine (SVM) is a powerful algorithm, useful in classifying data into species. The SVMs implemented in this research were used as classifiers for the final stage in a Multistage Automatic Target Recognition (ATR) system. A single kernel SVM known as SVMlight, and a modified version known as a SVM with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SVM as a method for classification. From trial to trial, SVM produces consistent results.

Determination of the technical constants of laminates in oblique directions

NASA Technical Reports Server (NTRS)

Vidouse, F.

1979-01-01

An off-axis tensile test theory based on Hooke's Law is applied to glass fiber reinforced laminates. A corrective parameter dependent on the characteristics of the strain gauge used is introduced by testing machines set up for isotropic materials. Theoretical results for a variety of strain gauges are compared with those obtained by a finite element method and with experimental results obtained on laminates reinforced with glass.

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

NASA Astrophysics Data System (ADS)

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-01

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Predicting Protein–protein Association Rates using Coarse-grained Simulation and Machine Learning

PubMed Central

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-01-01

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate. PMID:28418043

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

PubMed

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-18

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Impact of the HEALTHY Study on Vending Machine Offerings in Middle Schools

PubMed Central

Hartstein, Jill; Cullen, Karen W.; Virus, Amy; El Ghormli, Laure; Volpe, Stella L.; Staten, Myrlene A; Bridgman, Jessica C.; Stadler, Diane D.; Gillis, Bonnie; McCormick, Sarah B.; Mobley, Connie C.

2013-01-01

Purpose/Objectives The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminate 100% fruit juice and beverages with added sugar. Methods Six schools in each of seven cities (Houston, TX, San Antonio, TX, Irvine, CA, Portland, OR, Pittsburg, PA, Philadelphia, PA, and Chapel Hill, NC) were randomized into intervention (n=21 schools) or control (n=21 schools) groups, with three intervention and three control schools per city. All items in vending machine slots were tallied twice in the fall of 2006 for baseline data and twice at the end of the study, in 2009. The percentage of total slots for each food/beverage category was calculated and compared between intervention and control schools at the end of study, using the Pearson chi-square test statistic. Results At baseline, 15 intervention and 15 control schools had beverage and/or snack vending machines, compared with 11 intervention and 11 control schools at the end of the study. At the end of study, all of the intervention schools with beverage vending machines, but only one out of the nine control schools, met the beverage goal. The snack goal was met by all of the intervention schools and only one of the four control schools with snack vending machines. Applications to Child Nutrition Professionals The HEALTHY study’s vending machine beverage and snack goals were successfully achieved in intervention schools, reducing access to less healthy food items outside the school meals program. Although the effect of these changes on student diet, energy balance and growth is unknown, these results suggest that healthier options for snacks can successfully be offered in school vending machines. PMID:23687471

Vibration Damping Analysis of Lightweight Structures in Machine Tools

PubMed Central

Aggogeri, Francesco; Borboni, Alberto; Merlo, Angelo; Pellegrini, Nicola; Ricatto, Raffaele

2017-01-01

The dynamic behaviour of a machine tool (MT) directly influences the machining performance. The adoption of lightweight structures may reduce the effects of undesired vibrations and increase the workpiece quality. This paper aims to present and compare a set of hybrid materials that may be excellent candidates to fabricate the MT moving parts. The selected materials have high dynamic characteristics and capacity to dampen mechanical vibrations. In this way, starting from the kinematic model of a milling machine, this study evaluates a number of prototypes made of Al foam sandwiches (AFS), Al corrugated sandwiches (ACS) and composite materials reinforced by carbon fibres (CFRP). These prototypes represented the Z-axis ram of a commercial milling machine. The static and dynamical properties have been analysed by using both finite element (FE) simulations and experimental tests. The obtained results show that the proposed structures may be a valid alternative to the conventional materials of MT moving parts, increasing machining performance. In particular, the AFS prototype highlighted a damping ratio that is 20 times greater than a conventional ram (e.g., steel). Its application is particularly suitable to minimize unwanted oscillations during high-speed finishing operations. The results also show that the CFRP structure guarantees high stiffness with a weight reduced by 48.5%, suggesting effective applications in roughing operations, saving MT energy consumption. The ACS structure has a good trade-off between stiffness and damping and may represent a further alternative, if correctly evaluated. PMID:28772653

Passing the Turing Test Does Not Mean the End of Humanity.

PubMed

Warwick, Kevin; Shah, Huma

In this paper we look at the phenomenon that is the Turing test. We consider how Turing originally introduced his imitation game and discuss what this means in a practical scenario. Due to its popular appeal we also look into different representations of the test as indicated by numerous reviewers. The main emphasis here, however, is to consider what it actually means for a machine to pass the Turing test and what importance this has, if any. In particular does it mean that, as Turing put it, a machine can "think". Specifically we consider claims that passing the Turing test means that machines will have achieved human-like intelligence and as a consequence the singularity will be upon us in the blink of an eye.

Virtual Employment Test Bed Operational Research and Systems Analysis to Test Armaments Designs Early in the Life Cycle

DTIC Science & Technology

2014-06-01

motion capture data used to determine position and orientation of a Soldier’s head, turret and the M2 machine gun • Controlling and acquiring user/weapon...data from the M2 simulation machine gun • Controlling paintball guns used to fire at the GPK during an experimental run • Sending and receiving TCP...Mounted, Armor/Cavalry, Combat Engineers, Field Artillery Cannon Crewmember, or MP duty assignment – Currently M2 .50 Caliber Machine Gun qualified

New Single Piece Blast Hardware design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ulrich, Andri; Steinzig, Michael Louis; Aragon, Daniel Adrian

W, Q and PF engineers and machinists designed and fabricated, on the new Mazak i300, the first Single Piece Blast Hardware (unclassified design shown) reducing fabrication and inspection time by over 50%. The first DU Single Piece is completed and will be used for Hydro Test 3680. Past hydro tests used a twopiece assembly due to a lack of equipment capable of machining the complex saddle shape in a single piece. The i300 provides turning and milling 5-axis machining on one machine. The milling head on the i300 can machine past 90 relative to the spindle axis. This makes itmore » possible to machine the complex saddle surface on a single piece. Going to a single piece eliminates tolerance problems, such as tilting and eccentricity, that typically occurred when assembling the two pieces together« less

Doppler ultrasound compatible plastic material for use in rigid flow models.

PubMed

Wong, Emily Y; Thorne, Meghan L; Nikolov, Hristo N; Poepping, Tamie L; Holdsworth, David W

2008-11-01

A technique for the rapid but accurate fabrication of multiple flow phantoms with variations in vascular geometry would be desirable in the investigation of carotid atherosclerosis. This study demonstrates the feasibility and efficacy of implementing numerically controlled direct-machining of vascular geometries into Doppler ultrasound (DUS)-compatible plastic for the easy fabrication of DUS flow phantoms. Candidate plastics were tested for longitudinal speed of sound (SoS) and acoustic attenuation at the diagnostic frequency of 5 MHz. Teflon was found to have the most appropriate SoS (1376 +/- 40 m s(-1) compared with 1540 m s(-1) in soft tissue) and thus was selected to construct a carotid bifurcation flow model with moderate eccentric stenosis. The vessel geometry was machined directly into Teflon using a numerically controlled milling technique. Geometric accuracy of the phantom lumen was verified using nondestructive micro-computed tomography. Although Teflon displayed a higher attenuation coefficient than other tested materials, Doppler data acquired in the Teflon flow model indicated that sufficient signal power was delivered throughout the depth of the vessel and provided comparable velocity profiles to that obtained in the tissue-mimicking phantom. Our results indicate that Teflon provides the best combination of machinability and DUS compatibility, making it an appropriate choice for the fabrication of rigid DUS flow models using a direct-machining method.

Classification of Strawberry Fruit Shape by Machine Learning

NASA Astrophysics Data System (ADS)

Ishikawa, T.; Hayashi, A.; Nagamatsu, S.; Kyutoku, Y.; Dan, I.; Wada, T.; Oku, K.; Saeki, Y.; Uto, T.; Tanabata, T.; Isobe, S.; Kochi, N.

2018-05-01

Shape is one of the most important traits of agricultural products due to its relationships with the quality, quantity, and value of the products. For strawberries, the nine types of fruit shape were defined and classified by humans based on the sampler patterns of the nine types. In this study, we tested the classification of strawberry shapes by machine learning in order to increase the accuracy of the classification, and we introduce the concept of computerization into this field. Four types of descriptors were extracted from the digital images of strawberries: (1) the Measured Values (MVs) including the length of the contour line, the area, the fruit length and width, and the fruit width/length ratio; (2) the Ellipse Similarity Index (ESI); (3) Elliptic Fourier Descriptors (EFDs), and (4) Chain Code Subtraction (CCS). We used these descriptors for the classification test along with the random forest approach, and eight of the nine shape types were classified with combinations of MVs + CCS + EFDs. CCS is a descriptor that adds human knowledge to the chain codes, and it showed higher robustness in classification than the other descriptors. Our results suggest machine learning's high ability to classify fruit shapes accurately. We will attempt to increase the classification accuracy and apply the machine learning methods to other plant species.

Effect of Ceramic Surface Treatments After Machine Grinding on the Biaxial Flexural Strength of Different CAD/CAM Dental Ceramics.

PubMed

Bagheri, Hossein; Hooshmand, Tabassom; Aghajani, Farzaneh

2015-09-01

This study aimed to evaluate the effect of different ceramic surface treatments after machining grinding on the biaxial flexural strength (BFS) of machinable dental ceramics with different crystalline phases. Disk-shape specimens (10mm in diameter and 1.3mm in thickness) of machinable ceramic cores (two silica-based and one zirconia-based ceramics) were prepared. Each type of the ceramic surfaces was then randomly treated (n=15) with different treatments as follows: 1) machined finish as control, 2) machined finish and sandblasting with alumina, and 3) machined finish and hydrofluoric acid etching for the leucite and lithium disilicate-based ceramics, and for the zirconia; 1) machined finish and post-sintered as control, 2) machined finish, post-sintered, and sandblasting, and 3) machined finish, post-sintered, and Nd;YAG laser irradiation. The BFS were measured in a universal testing machine. Data based were analyzed by ANOVA and Tukey's multiple comparisons post-hoc test (α=0.05). The mean BFS of machined finish only surfaces for leucite ceramic was significantly higher than that of sandblasted (P=0.001) and acid etched surfaces (P=0.005). A significantly lower BFS was found after sandblasting for lithium disilicate compared with that of other groups (P<0.05). Sandblasting significantly increased the BFS for the zirconia (P<0.05), but the BFS was significantly decreased after laser irradiation (P<0.05). The BFS of the machinable ceramics was affected by the type of ceramic material and surface treatment method. Sandblasting with alumina was detrimental to the strength of only silica-based ceramics. Nd:YAG laser irradiation may lead to substantial strength degradation of zirconia.

METAPHOR: Probability density estimation for machine learning based photometric redshifts

NASA Astrophysics Data System (ADS)

Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.

2017-06-01

We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).

Application of earth resources technology satellite data to urban and regional planning: Test site, County of Los Angeles

NASA Technical Reports Server (NTRS)

Raje, S.; Mcknight, J.; Willoughby, G.; Economy, R. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The County of Los Angeles photointerpreted ERTS film products to define problems of interest, coordinated ground truth over the complex test site including interfaces with secondary users as well as participated in on-line analyses of the GE multispectral information extraction systems. Interactive machine analyses were carried out, developing techniques and procedures as well as evaluating the outputs for community and regional planning. Extensive aircraft underflight coverage was provided that was valuable both in inputs preparation and outputs evaluation of the machine-aided analyses. One of the nonstandard ERTS images led to the discovery of a major new fault lineament on the northern slope of the Santa Monica Mountains.

Development of a synchrotron biaxial tensile device for in situ characterization of thin films mechanical response.

PubMed

Geandier, G; Thiaudière, D; Randriamazaoro, R N; Chiron, R; Djaziri, S; Lamongie, B; Diot, Y; Le Bourhis, E; Renault, P O; Goudeau, P; Bouaffad, A; Castelnau, O; Faurie, D; Hild, F

2010-10-01

We have developed on the DIFFABS-SOLEIL beamline a biaxial tensile machine working in the synchrotron environment for in situ diffraction characterization of thin polycrystalline films mechanical response. The machine has been designed to test compliant substrates coated by the studied films under controlled, applied strain field. Technological challenges comprise the sample design including fixation of the substrate ends, the related generation of a uniform strain field in the studied (central) volume, and the operations from the beamline pilot. Preliminary tests on 150 nm thick W films deposited onto polyimide cruciform substrates are presented. The obtained results for applied strains using x-ray diffraction and digital image correlation methods clearly show the full potentialities of this new setup.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Novel method for fabrication of monolithic multi-cavity molds and wafer optics

NASA Astrophysics Data System (ADS)

Wielandts, Marc; Wielandts, Remi

2015-10-01

One lens at a time on axis diamond turning or grinding of lens arrays with a large number of lenses is conventionally impractical because of the difficulties to shift and balance the substrate for each lens position. A novel method for automatic indexing was developed. This method uses an innovative mechatronics tooling (patent pending) that allows dynamic indexing at constant work spindle speed for maximum productivity and thermal stability of the work spindle while the balancing condition is maintained. In this paper we shall compare the machining capabilities of this method to free-form machining techniques, discuss about the main issues, present the concept and design of the working prototype and specific test bed, and present the results of the first cutting tests.

Inspection of wear particles in oils by using a fuzzy classifier

NASA Astrophysics Data System (ADS)

Hamalainen, Jari J.; Enwald, Petri

1994-11-01

The reliability of stand-alone machines and larger production units can be improved by automated condition monitoring. Analysis of wear particles in lubricating or hydraulic oils helps diagnosing the wear states of machine parts. This paper presents a computer vision system for automated classification of wear particles. Digitized images from experiments with a bearing test bench, a hydraulic system with an industrial company, and oil samples from different industrial sources were used for algorithm development and testing. The wear particles were divided into four classes indicating different wear mechanisms: cutting wear, fatigue wear, adhesive wear, and abrasive wear. The results showed that the fuzzy K-nearest neighbor classifier utilized gave the same distribution of wear particles as the classification by a human expert.

Fabrication of Flex Joint Utilizing Additively Manufactured Parts

NASA Technical Reports Server (NTRS)

Eddleman, David; Richard, Jim

2015-01-01

The Selective Laser Melting (SLM) manufacturing technique has been utilized in the manufacture of a flex joint typical of those found in rocket engine and main propulsion system ducting. The SLM process allowed for the combination of parts that are typically machined separately and welded together. This resulted in roughly a 65% reduction of the total number of parts, roughly 70% reduction in the total number of welds, and an estimated 60% reduction in the number of machining operations. The majority of the new design was in three SLM pieces. These pieces, as well as a few traditionally fabricated parts, were assembled into a complete unit, which has been pressure tested. The design and planned cryogenic testing of the unit will be presented.

A Performance Comparison Study of Uncoated and TiAlN Coated Carbide End Mill on Machining of the Al-35Zn Alloy

NASA Astrophysics Data System (ADS)

Bayraktar, S.; Hekimoglu, A. P.; Turgut, Y.; Haciosmanoglu, M.

2018-01-01

In this study, Al-35Zn alloy was produced by permanent mold casting. To investigate the cutting performance of uncoated and TiAlN coated carbide end mills on this alloy, a series of tests were carried out in the CNC vertical machining center at a constant cutting speed, feed rate and depth of cut. The results obtained from the tests showed that uncoated carbide end mill have lower cutting force and surface roughness than TiAlN coated carbide end mill. These observations are discussed in terms of the alloys properties, cutting tool surfaces, and friction and wear behavior between the cutting tool and the material.

Experiments on PIM in Support of the Development of IVA Technology for Radiography at AWE

NASA Astrophysics Data System (ADS)

Clough, Stephen G.; Thomas, Kenneth J.; Williamson, Mark C.; Phillips, Martin J.; Smith, Ian D.; Bailey, Vernon L.; Kishi, Hiroshi J.; Maenchen, John E.; Johnson, David L.

2002-12-01

The PIM machine has been designed and constructed at AWE as part of a program to investigate IVA technology for radiographic applications. PIM, as originally constructed, was a prospective single module of a 14 MV, 100 kA, ten module machine. The design of such a machine is a primary goal of the program as several are required to provide multi-axis radiography in a new Hydrodynamics Research Facility (HRF). Another goal is to design lower voltage machines (ranging from 1 to 5 MV) utilizing PIM style components. The original PIM machine consisted of a single inductive cavity pulsed by a 10 ohm water dielectric Blumlein pulse forming line (PFL) charged by a Marx generator. These components successfully achieved their design voltages and data on the prepulse was obtained showing it to be worse than expected. This information provided a basis for design work on the 14 MV HRF IVA, carried out by Titan-PSD, resulting in a proposal for a prepulse switch, a prototype of which should be installed on PIM by the end of this year. The original single, coaxial switch used to initiate the Blumlein has been replaced by a prototype laser triggered switching arrangement, also designed by Titan-PSD, which it was desired to test prior to its eventual use in the HRF. Despite problems with the laser, which will necessitate further experiments, it was determined that laser triggering with low jitter was occurring. A split oil co-ax feed has now been used to install a second cavity, in parallel with the first, on the PIM Blumlein. This two cavity configuration provides a prototype for future radiographic machines operating at up to 3 MV and a test facility for diode research.

Design, fabrication, and operation of a test rig for high-speed tapered-roller bearings

NASA Technical Reports Server (NTRS)

Signer, H. R.

1974-01-01

A tapered-roller bearing test machine was designed, fabricated and successfully operated at speeds to 20,000 rpm. Infinitely variable radial loads to 26,690 N (6,000 lbs.) and thrust loads to 53,380 N (12,000 lbs.) can be applied to test bearings. The machine instrumentation proved to have the accuracy and reliability required for parametric bearing performance testing and has the capability of monitoring all programmed test parameters at continuous operation during life testing. This system automatically shuts down a test if any important test parameter deviates from the programmed conditions, or if a bearing failure occurs. A lubrication system was developed as an integral part of the machine, capable of lubricating test bearings by external jets and by means of passages feeding through the spindle and bearing rings into the critical internal bearing surfaces. In addition, provisions were made for controlled oil cooling of inner and outer rings to effect the type of bearing thermal management that is required when testing at high speeds.

Fourdrinier-Machine Tender (paper & pulp, wallboard) 539.782; Back Tender, Paper Machine (paper & pulp) 534.782--Technical Report on Development of USTES Aptitude Test Battery.

ERIC Educational Resources Information Center

Manpower Administration (DOL), Washington, DC. U.S. Training and Employment Service.

The United States Training and Employment Service General Aptitude Test Battery (GATB), first published in 1947, has been included in a continuing program of research to validate the tests against success in many different occupations. The GATB consists of 12 tests which measure nine aptitudes: General Learning Ability; Verbal Aptitude; Numerical…

Numerical Simulation of Earth Pressure on Head Chamber of Shield Machine with FEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Shouju; Kang Chengang; Sun, Wei

2010-05-21

Model parameters of conditioned soils in head chamber of shield machine are determined based on tree-axial compression tests in laboratory. The loads acting on tunneling face are estimated according to static earth pressure principle. Based on Duncan-Chang nonlinear elastic constitutive model, the earth pressures on head chamber of shield machine are simulated in different aperture ratio cases for rotating cutterhead of shield machine. Relationship between pressure transportation factor and aperture ratio of shield machine is proposed by using aggression analysis.

Signal injection as a fault detection technique.

PubMed

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.

Signal Injection as a Fault Detection Technique

PubMed Central

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. PMID:22163801

24 CFR 3280.607 - Plumbing fixtures.

Code of Federal Regulations, 2014 CFR

2014-04-01

... two or more compartments, dishwashers, clothes washing machines, laundry tubs, bath tubs, and not less... for Safety Performance Specifications and Methods of Test for Safety Glazing Materials Used in...) Dishwashing machines. (i) A dishwashing machine shall not be directly connected to any waste piping, but shall...

Multivariate models for prediction of human skin sensitization hazard.

PubMed

Strickland, Judy; Zang, Qingda; Paris, Michael; Lehmann, David M; Allen, David; Choksi, Neepa; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Kleinstreuer, Nicole

2017-03-01

One of the Interagency Coordinating Committee on the Validation of Alternative Method's (ICCVAM) top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays - the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens™ assay - six physicochemical properties and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches, logistic regression and support vector machine, to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three logistic regression and three support vector machine) with the highest accuracy (92%) used: (1) DPRA, h-CLAT and read-across; (2) DPRA, h-CLAT, read-across and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens and log P. The models performed better at predicting human skin sensitization hazard than the murine local lymph node assay (accuracy 88%), any of the alternative methods alone (accuracy 63-79%) or test batteries combining data from the individual methods (accuracy 75%). These results suggest that computational methods are promising tools to identify effectively the potential human skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Grindability measurements on low-rank fuels. [Prediction of large pulverizer performance from small scale test equipment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peipho, R.R.; Dougan, D.R.

1981-01-01

Experience has shown that the grinding characteristics of low rank coals are best determined by testing them in a pulverizer. Test results from a small MPS-32 Babcock and Wilcox pulverizer to predict large, full-scale pulverizer performance are presented. The MPS-32 apparatus, test procedure and evaluation of test results is described. The test data show that the Hardgrove apparatus and the ASTM test method must be used with great caution when considering low-rank fuels. The MPS-32 meets the needs for real-machine simulation but with some disadvantages. A smaller pulverizer is desirable. 1 ref.

Comparison of fiber orientation and tensile-stiffness orientation measurements in paper

Treesearch

David W. Vahey; John M. Considine; Andy Kahra; Mark Scotch

2008-01-01

We have had the opportunity to subject cross-machine paper strips from two mills to both ultrasound and optical "fiber-orientation" tests to examine the relationships between the results. Both determine an orientation angle, in degrees. Both measure sheet anisotropy as an MD/CD orientation ratio. The optical test has no counterpart to the ultrasonic...

Development of an After-Sales Support Inter-Enterprise Collaboration System Using Information Technologies

NASA Astrophysics Data System (ADS)

Kimura, Toshiaki; Kasai, Fumio; Kamio, Yoichi; Kanda, Yuichi

This research paper discusses a manufacturing support system which supports not only maintenance services but also consulting services for manufacturing systems consisting of multi-vendor machine tools. In order to do this system enables inter-enterprise collaboration between engineering companies and machine tool vendors. The system is called "After-Sales Support Inter-enterprise collaboration System using information Technologies" (ASSIST). This paper describes the concept behind the planned ASSIST, the development of a prototype of the system, and discusses test operation results of the system.

Machining and brazing of accelerating RF cavity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghodke, S.R.; Barnwal, Rajesh; Mondal, Jayant, E-mail: ghodke_barc@yahoo.co.in

2014-07-01

BARC has developed 2856 MHz accelerating cavities for 6 MeV, 9 MeV and 10 MeV RF Linac. New vendors are developed for mass production of accelerating cavity for future projects. New vendors are developing for diamond turning machining, cleaning and brazing processes. Fabrication involved material testing, CNC diamond turning of cavity, cavity cleaning and brazing. Before and after brazing resonance frequency (RF) of cavity was checked with vector network analyser (VNA). A power feed test setup is also fabricated to test power feed cavity before brazing. This test setup will be used to find out assembly performance of power feedmore » cavity and its coupler. This paper discusses about nano machining, cleaning and brazing processes of RF cavities. (author)« less

A COMPARATIVE STUDY OF VIDEO TAPE RECORDINGS.

ERIC Educational Resources Information Center

WIENS, JACOB H.

THE COMPARATIVE EFFECTIVENESS OF PRESENTLY AVAILABLE VIDEO TAPE MACHINES IS REPORTED, FOR THE CONVENIENCE OF SCHOOL ADMINISTRATORS PLANNING TO USE SUCH EQUIPMENT IN EDUCATIONAL PROGRAMS. TESTS WERE CONDUCTED AT THE WIENS ELECTRONIC LABORATORIES. MACHINE BRANDS TESTED WERE AMPEX, CONCORD, MACHTRONICS, PRECISION, RCA, SONY, AND WOLLENSAK. A DETAILED…

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection... place at which a field approval investigation will be conducted with respect to any machine, the...

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection... place at which a field approval investigation will be conducted with respect to any machine, the...

24 CFR 3280.607 - Plumbing fixtures.

Code of Federal Regulations, 2010 CFR

2010-04-01

... less than 11/2 inches for sinks of two or more compartments, dishwashers, clothes washing machines... of Test for Safety Glazing Materials Used in Buildings, ANSI Z97.1-1984. (iv) Prefabricated plumbing fixtures shall be approved or listed. (4) Dishwashing machines. (i) A dishwashing machine shall not be...

24 CFR 3280.607 - Plumbing fixtures.

Code of Federal Regulations, 2012 CFR

2012-04-01

... less than 11/2 inches for sinks of two or more compartments, dishwashers, clothes washing machines... of Test for Safety Glazing Materials Used in Buildings, ANSI Z97.1-1984. (iv) Prefabricated plumbing fixtures shall be approved or listed. (4) Dishwashing machines. (i) A dishwashing machine shall not be...

24 CFR 3280.607 - Plumbing fixtures.

Code of Federal Regulations, 2011 CFR

2011-04-01

... less than 11/2 inches for sinks of two or more compartments, dishwashers, clothes washing machines... of Test for Safety Glazing Materials Used in Buildings, ANSI Z97.1-1984. (iv) Prefabricated plumbing fixtures shall be approved or listed. (4) Dishwashing machines. (i) A dishwashing machine shall not be...

24 CFR 3280.607 - Plumbing fixtures.

Code of Federal Regulations, 2013 CFR

2013-04-01

... less than 11/2 inches for sinks of two or more compartments, dishwashers, clothes washing machines... of Test for Safety Glazing Materials Used in Buildings, ANSI Z97.1-1984. (iv) Prefabricated plumbing fixtures shall be approved or listed. (4) Dishwashing machines. (i) A dishwashing machine shall not be...

Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines

PubMed Central

Yu, Yang; Niederleithinger, Ernst; Li, Jianchun; Wiggenhauser, Herbert

2017-01-01

This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%. PMID:29258274

Machine-Specific Magnetic Resonance Imaging Quality Control Procedures for Stereotactic Radiosurgery Treatment Planning

PubMed Central

Taghizadeh, Somayeh; Yang, Claus Chunli; R. Kanakamedala, Madhava; Morris, Bart; Vijayakumar, Srinivasan

2017-01-01

Purpose Magnetic resonance (MR) images are necessary for accurate contouring of intracranial targets, determination of gross target volume and evaluation of organs at risk during stereotactic radiosurgery (SRS) treatment planning procedures. Many centers use magnetic resonance imaging (MRI) simulators or regular diagnostic MRI machines for SRS treatment planning; while both types of machine require two stages of quality control (QC), both machine- and patient-specific, before use for SRS, no accepted guidelines for such QC currently exist. This article describes appropriate machine-specific QC procedures for SRS applications. Methods and materials We describe the adaptation of American College of Radiology (ACR)-recommended QC tests using an ACR MRI phantom for SRS treatment planning. In addition, commercial Quasar MRID3D and Quasar GRID3D phantoms were used to evaluate the effects of static magnetic field (B0) inhomogeneity, gradient nonlinearity, and a Leksell G frame (SRS frame) and its accessories on geometrical distortion in MR images. Results QC procedures found in-plane distortions (Maximum = 3.5 mm, Mean = 0.91 mm, Standard deviation = 0.67 mm, >2.5 mm (%) = 2) in X-direction (Maximum = 2.51 mm, Mean = 0.52 mm, Standard deviation = 0.39 mm, > 2.5 mm (%) = 0) and in Y-direction (Maximum = 13. 1 mm , Mean = 2.38 mm, Standard deviation = 2.45 mm, > 2.5 mm (%) = 34) in Z-direction and < 1 mm distortion at a head-sized region of interest. MR images acquired using a Leksell G frame and localization devices showed a mean absolute deviation of 2.3 mm from isocenter. The results of modified ACR tests were all within recommended limits, and baseline measurements have been defined for regular weekly QC tests. Conclusions With appropriate QC procedures in place, it is possible to routinely obtain clinically useful MR images suitable for SRS treatment planning purposes. MRI examination for SRS planning can benefit from the improved localization and planning possible with the superior image quality and soft tissue contrast achieved under optimal conditions. PMID:29487771

Machine-Specific Magnetic Resonance Imaging Quality Control Procedures for Stereotactic Radiosurgery Treatment Planning.

PubMed

Fatemi, Ali; Taghizadeh, Somayeh; Yang, Claus Chunli; R Kanakamedala, Madhava; Morris, Bart; Vijayakumar, Srinivasan

2017-12-18

Purpose Magnetic resonance (MR) images are necessary for accurate contouring of intracranial targets, determination of gross target volume and evaluation of organs at risk during stereotactic radiosurgery (SRS) treatment planning procedures. Many centers use magnetic resonance imaging (MRI) simulators or regular diagnostic MRI machines for SRS treatment planning; while both types of machine require two stages of quality control (QC), both machine- and patient-specific, before use for SRS, no accepted guidelines for such QC currently exist. This article describes appropriate machine-specific QC procedures for SRS applications. Methods and materials We describe the adaptation of American College of Radiology (ACR)-recommended QC tests using an ACR MRI phantom for SRS treatment planning. In addition, commercial Quasar MRID 3D and Quasar GRID 3D phantoms were used to evaluate the effects of static magnetic field (B 0 ) inhomogeneity, gradient nonlinearity, and a Leksell G frame (SRS frame) and its accessories on geometrical distortion in MR images. Results QC procedures found in-plane distortions (Maximum = 3.5 mm, Mean = 0.91 mm, Standard deviation = 0.67 mm, >2.5 mm (%) = 2) in X-direction (Maximum = 2.51 mm, Mean = 0.52 mm, Standard deviation = 0.39 mm, > 2.5 mm (%) = 0) and in Y-direction (Maximum = 13. 1 mm , Mean = 2.38 mm, Standard deviation = 2.45 mm, > 2.5 mm (%) = 34) in Z-direction and < 1 mm distortion at a head-sized region of interest. MR images acquired using a Leksell G frame and localization devices showed a mean absolute deviation of 2.3 mm from isocenter. The results of modified ACR tests were all within recommended limits, and baseline measurements have been defined for regular weekly QC tests. Conclusions With appropriate QC procedures in place, it is possible to routinely obtain clinically useful MR images suitable for SRS treatment planning purposes. MRI examination for SRS planning can benefit from the improved localization and planning possible with the superior image quality and soft tissue contrast achieved under optimal conditions.

Telescoping magnetic ball bar test gage

DOEpatents

Bryan, J.B.

1984-03-13

A telescoping magnetic ball bar test gage for determining the accuracy of machine tools, including robots, and those measuring machines having non-disengageable servo drives which cannot be clutched out is disclosed. Two gage balls are held and separated from one another by a telescoping fixture which allows them relative radial motional freedom but not relative lateral motional freedom. The telescoping fixture comprises a parallel reed flexure unit and a rigid member. One gage ball is secured by a magnetic socket knuckle assembly which fixes its center with respect to the machine being tested. The other gage ball is secured by another magnetic socket knuckle assembly which is engaged or held by the machine in such manner that the center of that ball is directed to execute a prescribed trajectory, all points of which are equidistant from the center of the fixed gage ball. As the moving ball executes its trajectory, changes in the radial distance between the centers of the two balls caused by inaccuracies in the machine are determined or measured by a linear variable differential transformer (LVDT) assembly actuated by the parallel reed flexure unit. Measurements can be quickly and easily taken for multiple trajectories about several different fixed ball locations, thereby determining the accuracy of the machine. 3 figs.

Prophylactic Procurement of University Students in Southern Ethiopia: Stigma and the Value of Condom Machines on Campus

PubMed Central

Wells, Christopher J.; Alano, Abraham

2013-01-01

Introduction Risky sexual behavior among Ethiopian university students, especially females, is a major contributor to young adult morbidity and mortality. Ambaw et al. found that female university students in Ethiopia may fear the humiliation associated with procuring condoms. A study in Thailand suggests condom machines may provide comfortable condom procurement, but the relevance to a high-risk African context is unknown. The objective of this study was to examine if the installation of condom machines in Ethiopia predicts changes in student condom uptake and use, as well as changes in procurement related stigma. Methods Students at a large urban university in Southern Ethiopia completed self reported surveys in 2010 (N  = 2,155 surveys) and again in 2011 (N =  2,000), six months after the installation of condom machines. Mann-Whitney and Chi-square tests were conducted to evaluate significant changes in student sexual behavior, as well as condom procurement and associated stigma over the subsequent one year period. Results After installing condom machines, the average number of trips made to procure condoms on-campus significantly increased 101% for sexually active females and significantly decreased 36% for sexually active males. Additionally, reports of condom use during last sexual intercourse showed a non-significant 4.3% increase for females and a significant 9.0% increase for males. During this time, comfort procuring condoms and ability to convince sexual partners to use condoms were significantly higher for sexually active male students. There was no evidence that the condom machines led to an increase in promiscuity. Conclusions The results suggest that condom machines may be associated with more condom procurement among vulnerable female students in Ethiopia and could be an important component of a comprehensive university health policy. PMID:23565272

Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study

PubMed Central

Burgansky-Eliash, Zvia; Wollstein, Gadi; Chu, Tianjiao; Ramsey, Joseph D.; Glymour, Clark; Noecker, Robert J.; Ishikawa, Hiroshi; Schuman, Joel S.

2007-01-01

Purpose Machine-learning classifiers are trained computerized systems with the ability to detect the relationship between multiple input parameters and a diagnosis. The present study investigated whether the use of machine-learning classifiers improves optical coherence tomography (OCT) glaucoma detection. Methods Forty-seven patients with glaucoma (47 eyes) and 42 healthy subjects (42 eyes) were included in this cross-sectional study. Of the glaucoma patients, 27 had early disease (visual field mean deviation [MD] ≥ −6 dB) and 20 had advanced glaucoma (MD < −6 dB). Machine-learning classifiers were trained to discriminate between glaucomatous and healthy eyes using parameters derived from OCT output. The classifiers were trained with all 38 parameters as well as with only 8 parameters that correlated best with the visual field MD. Five classifiers were tested: linear discriminant analysis, support vector machine, recursive partitioning and regression tree, generalized linear model, and generalized additive model. For the last two classifiers, a backward feature selection was used to find the minimal number of parameters that resulted in the best and most simple prediction. The cross-validated receiver operating characteristic (ROC) curve and accuracies were calculated. Results The largest area under the ROC curve (AROC) for glaucoma detection was achieved with the support vector machine using eight parameters (0.981). The sensitivity at 80% and 95% specificity was 97.9% and 92.5%, respectively. This classifier also performed best when judged by cross-validated accuracy (0.966). The best classification between early glaucoma and advanced glaucoma was obtained with the generalized additive model using only three parameters (AROC = 0.854). Conclusions Automated machine classifiers of OCT data might be useful for enhancing the utility of this technology for detecting glaucomatous abnormality. PMID:16249492

Comparison of Random Forest and Support Vector Machine classifiers using UAV remote sensing imagery

NASA Astrophysics Data System (ADS)

Piragnolo, Marco; Masiero, Andrea; Pirotti, Francesco

2017-04-01

Since recent years surveying with unmanned aerial vehicles (UAV) is getting a great amount of attention due to decreasing costs, higher precision and flexibility of usage. UAVs have been applied for geomorphological investigations, forestry, precision agriculture, cultural heritage assessment and for archaeological purposes. It can be used for land use and land cover classification (LULC). In literature, there are two main types of approaches for classification of remote sensing imagery: pixel-based and object-based. On one hand, pixel-based approach mostly uses training areas to define classes and respective spectral signatures. On the other hand, object-based classification considers pixels, scale, spatial information and texture information for creating homogeneous objects. Machine learning methods have been applied successfully for classification, and their use is increasing due to the availability of faster computing capabilities. The methods learn and train the model from previous computation. Two machine learning methods which have given good results in previous investigations are Random Forest (RF) and Support Vector Machine (SVM). The goal of this work is to compare RF and SVM methods for classifying LULC using images collected with a fixed wing UAV. The processing chain regarding classification uses packages in R, an open source scripting language for data analysis, which provides all necessary algorithms. The imagery was acquired and processed in November 2015 with cameras providing information over the red, blue, green and near infrared wavelength reflectivity over a testing area in the campus of Agripolis, in Italy. Images were elaborated and ortho-rectified through Agisoft Photoscan. The ortho-rectified image is the full data set, and the test set is derived from partial sub-setting of the full data set. Different tests have been carried out, using a percentage from 2 % to 20 % of the total. Ten training sets and ten validation sets are obtained from each test set. The control dataset consist of an independent visual classification done by an expert over the whole area. The classes are (i) broadleaf, (ii) building, (iii) grass, (iv) headland access path, (v) road, (vi) sowed land, (vii) vegetable. The RF and SVM are applied to the test set. The performances of the methods are evaluated using the three following accuracy metrics: Kappa index, Classification accuracy and Classification Error. All three are calculated in three different ways: with K-fold cross validation, using the validation test set and using the full test set. The analysis indicates that SVM gets better results in terms of good scores using K-fold cross or validation test set. Using the full test set, RF achieves a better result in comparison to SVM. It also seems that SVM performs better with smaller training sets, whereas RF performs better as training sets get larger.

The Kansas Squat Test Modality Comparison: Free Weights vs. Smith Machine.

PubMed

Luebbers, Paul E; Fry, Andrew C

2016-08-01

Luebbers, PE and Fry, AC. The Kansas squat test modality comparison: free weights vs. smith machine. J Strength Cond Res 30(8): 2186-2193, 2016-Standardized methods of testing power are instrumental in planning and implementing training regimens for many athletes, and also in tracking training adaptations. Previous work has demonstrated that the Kansas squat test (KST) is a valid test for measuring indices of mean and peak power when compared with the Wingate anaerobic cycle test. Although the KST was designed for use with a Smith machine (SM), many power athletes use free weights for training. The purpose of this study was to determine the feasibility of using free weights (FW) for the KST by comparing it with the SM modality. Twenty-three track and field athletes participated (mean ± SD; weight, 69.7 ± 10.6 kg; age, 20.1 ± 1.1 years) in this study. Each completed familiarization sessions with the FW and SM modalities before data collection. A 1-repetition maximum squat was also determined for both the FW and SM. Correlation coefficients indicated significant relationships between the FW KST and SM KST on measures of peak test power (r = 0.955; p < 0.01) and mean test power (r = 0.959; p < 0.01) but not for relative fatigue (r = -0.198; p > 0.05) or posttest lactate (r = 0.109; p > 0.05). Paired samples t-tests indicated that the FW KST resulted in significantly higher measures of peak power and mean power (p ≤ 0.01), although no differences were observed for relative fatigue or lactate (p > 0.05). These data indicate that the FW KST is a valid and feasible alternative to the SM KST in measuring peak and mean power.

Improved transistor-controlled and commutated brushless DC motors for electric vehicle propulsion

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Miller, R. H.; Nehl, T. W.; Nyamusa, T. A.

1983-01-01

The development, design, construction, and testing processes of two electronically (transistor) controlled and commutated permanent magnet brushless dc machine systems, for propulsion of electric vehicles are detailed. One machine system was designed and constructed using samarium cobalt for permanent magnets, which supply the rotor (field) excitation. Meanwhile, the other machine system was designed and constructed with strontium ferrite permanent magnets as the source of rotor (field) excitation. These machine systems were designed for continuous rated power output of 15 hp (11.2 kw), and a peak one minute rated power output of 35 hp (26.1 kw). Both power ratings are for a rated voltage of 115 volts dc, assuming a voltage drop in the source (battery) of about 5 volts. That is, an internal source voltage of 120 volts dc. Machine-power conditioner system computer-aided simulations were used extensively in the design process. These simulations relied heavily on the magnetic field analysis in these machines using the method of finite elements, as well as methods of modeling of the machine power conditioner system dynamic interaction. These simulation processes are detailed. Testing revealed that typical machine system efficiencies at 15 hp (11.2 kw) were about 88% and 84% for the samarium cobalt and strontium ferrite based machine systems, respectively. Both systems met the peak one minute rating of 35 hp.

Effect of initial contact surface condition on the friction and wear properties of bearing steel in cyclic reciprocating sliding contact

NASA Astrophysics Data System (ADS)

Tanaka, Y.; Endo, M.; Moriyama, S.

2017-05-01

Delamination failure is one of the most important engineering problems. This failure can frequently be detrimental to rolling contact machine elements such as bearings, gear wheels, etc. This phenomenon, called rolling contact fatigue, has a close relationship not only with opening-mode but also with shear-mode fatigue crack growth. The crack face interference is known to significantly affect the shear-mode fatigue crack propagation and its threshold behavior. Quantitative investigation on friction and wear at fatigue crack faces in the material is essentially impossible. Previously, thus, a novel ring-on-ring test by making use of fatigue testing machine was proposed to simulate a cyclic reciprocating sliding contact of crack surfaces. However, this test procedure had some problems. For instance, in order to achieve the uniform contact at the start of test, the rubbing of specimens must be conducted in advance. By this treatment, the specimen surfaces were already damaged before the test. In this study, an improvement of experimental method was made to perform the test using the damage-free specimens. The friction and wear properties for heat-treated high carbon-chromium bearing steel were investigated with this new method and the results were compared to the results obtained by using the initially damaged specimens.

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable.

PubMed

Korjus, Kristjan; Hebart, Martin N; Vicente, Raul

2016-01-01

Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with cross-validation. This is followed by application of the classifier with optimized parameters to a separate test set for estimating the classifier's generalization performance. With limited data, this separation of test data creates a difficult trade-off between having more statistical power in estimating generalization performance versus choosing better parameters and fitting a better model. We propose a novel approach that we term "Cross-validation and cross-testing" improving this trade-off by re-using test data without biasing classifier performance. The novel approach is validated using simulated data and electrophysiological recordings in humans and rodents. The results demonstrate that the approach has a higher probability of discovering significant results than the standard approach of cross-validation and testing, while maintaining the nominal alpha level. In contrast to nested cross-validation, which is maximally efficient in re-using data, the proposed approach additionally maintains the interpretability of individual parameters. Taken together, we suggest an addition to currently used machine learning approaches which may be particularly useful in cases where model weights do not require interpretation, but parameters do.

Ceramic Matrix Composite Vane Subelement Burst Testing

NASA Technical Reports Server (NTRS)

Brewer, David N.; Verrilli, Michael; Calomino, Anthony

2006-01-01

Burst tests were performed on Ceramic Matrix Composite (CMC) vane specimens, manufactured by two vendors, under the Ultra Efficient Engine Technology (UEET) project. Burst specimens were machined from the ends of 76mm long vane sub-elements blanks and from High Pressure Burner Rig (HPBR) tested specimens. The results of burst tests will be used to compare virgin specimens with specimens that have had an Environmental Barrier Coating (EBC) applied, both HPBR tested and untested, as well as a comparison between vendors.

OT calibration and service maintenance manual.

DOT National Transportation Integrated Search

2012-01-01

The machine conditions, as well as the values at the calibration and control parameters, may determine the quality of each test results obtained. In order to keep consistency and accuracy, the conditions, performance and measurements of an OT must be...

Comparison of thin-film resistance heat-transfer gages with thin-skin transient calorimeter gages in conventional hypersonic wind tunnels

NASA Technical Reports Server (NTRS)

Miller, C. G., III

1981-01-01

Thin film gages deposited at the stagnation region of small (8.1-mm-diameter) hemispheres and gages mounted flush with the surface of a sharp-leading-edge flat plate were tested in the Langley continuous-flow hypersonic tunnel and in the Langley hypersonic CF4 tunnel. Two substrate materials were tested, quartz and a machinable glass-ceramic. Small hemispheres were also tested utilizing the thin-skin transient calorimeter technique usually employed in conventional tunnels. One transient calorimeter model was a thin shell of stainless steel, and the other was a thin-skin insert of stainless steel mounted into a hemisphere fabricated from a machinable-glass-ceramic. Measured heat-transfer rates from the various hemispheres were compared with one another and with predicted rates. The results demonstrate the feasibility and advantages of using-film resistance heat-transfer gages in conventional hypersonic wind tunnels over a wide range of conditions.

Strain Rate and Stress Triaxiality Effects on Ductile Damage of Additive Manufactured TI-6AL-4V

NASA Astrophysics Data System (ADS)

Iannitti, Gianluca; Bonora, Nicola; Gentile, Domenico; Ruggiero, Andrew; Testa, Gabriel; Gubbioni, Simone

2017-06-01

In this work, the effects of strain rate and stress triaxiality on ductile damage of additive manufactured Ti-6Al-4V, also considering the build direction, were investigated. Raw material was manufactured by means of EOSSINT M2 80 machine, based on Direct Metal Laser Sintering technology, and machined to obtain round notched bar and Rod-on-Rod (RoR) specimens. Tensile tests on round notched bar specimens were performed in a wide range of strain rates. The failure strains at different stress triaxiality were used to calibrate the Bonora Damage Model. In order to design the RoR tests, numerical simulations were performed for assessing velocities at which incipient and fully developed damage occur. Tests at selected velocities were carried out and soft-recovered specimens were sectioning and polishing to observe the developed damage. Nucleated voids maps were compared with numerical simulations results.

Effect of bionic coupling units' forms on wear resistance of gray cast iron under dry linear reciprocating sliding condition

NASA Astrophysics Data System (ADS)

Pang, Zuobo; Zhou, Hong; Xie, Guofeng; Cong, Dalong; Meng, Chao; Ren, Luquan

2015-07-01

In order to get close to the wear form of guide rails, the homemade linear reciprocating wear testing machine was used for the wear test. In order to improve the wear-resistance of gray cast iron guide rail, bionic coupling units of different forms were manufactured by a laser. Wear behavior of gray-cast-iron with bionic-coupling units has been studied under dry sliding condition at room temperature using the wear testing machine. The wear resistance was evaluated by means of weight loss measurement and wear morphology. The results indicated that bionic coupling unit could improve the wear resistance of gray cast iron. The wear resistance of gray cast iron with reticulation bionic coupling unit is the best. When the load and speed changed, reticulation bionic coupling unit still has excellent performance in improving the wear resistance of gray cast iron.

75 FR 60478 - In the Matter of Certain Machine Vision Software, Machine Vision Systems, and Products Containing...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-30

... Automation, Inc. (``Amistar'') of San Marcos, California; Techno Soft Systemnics, Inc. (``Techno Soft'') of... the claim terms ``test,'' ``match score surface,'' and ``gradient direction,'' all of his infringement... complainants' proposed construction for the claim terms ``test,'' ``match score surface,'' and ``gradient...

40 CFR 63.5460 - What definitions apply to this subpart?

Code of Federal Regulations, 2012 CFR

2012-07-01

... combination of smaller leather pieces and leather fibers, which when joined together, form an integral..., thus, cannot withstand 5,000 Maeser Flexes with a Maeser Flex Testing Machine or a method approved by... Maeser Flex Testing Machine or a method approved by the Administrator prior to initial water penetration...

40 CFR 63.5460 - What definitions apply to this subpart?

Code of Federal Regulations, 2014 CFR

2014-07-01

... combination of smaller leather pieces and leather fibers, which when joined together, form an integral..., thus, cannot withstand 5,000 Maeser Flexes with a Maeser Flex Testing Machine or a method approved by... Maeser Flex Testing Machine or a method approved by the Administrator prior to initial water penetration...

40 CFR 63.5460 - What definitions apply to this subpart?

Code of Federal Regulations, 2013 CFR

2013-07-01

... combination of smaller leather pieces and leather fibers, which when joined together, form an integral..., thus, cannot withstand 5,000 Maeser Flexes with a Maeser Flex Testing Machine or a method approved by... Maeser Flex Testing Machine or a method approved by the Administrator prior to initial water penetration...

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed Central

Nadkarni, P. M.; Miller, P. L.

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations. PMID:1807632

The Trail Making test: a study of its ability to predict falls in the acute neurological in-patient population.

PubMed

Mateen, Bilal Akhter; Bussas, Matthias; Doogan, Catherine; Waller, Denise; Saverino, Alessia; Király, Franz J; Playford, E Diane

2018-05-01

To determine whether tests of cognitive function and patient-reported outcome measures of motor function can be used to create a machine learning-based predictive tool for falls. Prospective cohort study. Tertiary neurological and neurosurgical center. In all, 337 in-patients receiving neurosurgical, neurological, or neurorehabilitation-based care. Binary (Y/N) for falling during the in-patient episode, the Trail Making Test (a measure of attention and executive function) and the Walk-12 (a patient-reported measure of physical function). The principal outcome was a fall during the in-patient stay ( n = 54). The Trail test was identified as the best predictor of falls. Moreover, addition of other variables, did not improve the prediction (Wilcoxon signed-rank P < 0.001). Classical linear statistical modeling methods were then compared with more recent machine learning based strategies, for example, random forests, neural networks, support vector machines. The random forest was the best modeling strategy when utilizing just the Trail Making Test data (Wilcoxon signed-rank P < 0.001) with 68% (± 7.7) sensitivity, and 90% (± 2.3) specificity. This study identifies a simple yet powerful machine learning (Random Forest) based predictive model for an in-patient neurological population, utilizing a single neuropsychological test of cognitive function, the Trail Making test.

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

PubMed

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Performance Comparison of a Set of Periodic and Non-Periodic Tridiagonal Solvers on SP2 and Paragon Parallel Computers

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Moitra, Stuti

1996-01-01

Various tridiagonal solvers have been proposed in recent years for different parallel platforms. In this paper, the performance of three tridiagonal solvers, namely, the parallel partition LU algorithm, the parallel diagonal dominant algorithm, and the reduced diagonal dominant algorithm, is studied. These algorithms are designed for distributed-memory machines and are tested on an Intel Paragon and an IBM SP2 machines. Measured results are reported in terms of execution time and speedup. Analytical study are conducted for different communication topologies and for different tridiagonal systems. The measured results match the analytical results closely. In addition to address implementation issues, performance considerations such as problem sizes and models of speedup are also discussed.

Experimental Investigation of Mechanical Behavior of an Oxide/Oxide Ceramic Composite in Interlaminar Shear and under Combined Tension-Torsion Loading

DTIC Science & Technology

2014-03-27

testing machine was warmed up for at least 30 min using a cyclic command with a sine waveform in displacement control . Gripping sections of each test...the test specimen was inserted into the susceptor. Then the testing machine is placed in displacement control and the top portion of the specimen...the MTS software also triggered the operation of the high speed cameras. 31 The testing system was placed in displacement /rotation control and the

Micro Machining of Injection Mold Inserts for Fluidic Channel of Polymeric Biochips

PubMed Central

Jung, Woo-Chul; Heo, Young-Moo; Yoon, Gil-Sang; Shin, Kwang-Ho; Chang, Sung-Ho; Kim, Gun-Hee; Cho, Myeong-Woo

2007-01-01

Recently, the polymeric micro-fluidic biochip, often called LOC (lab-on-a-chip), has been focused as a cheap, rapid and simplified method to replace the existing biochemical laboratory works. It becomes possible to form miniaturized lab functionalities on a chip with the development of MEMS technologies. The micro-fluidic chips contain many micro-channels for the flow of sample and reagents, mixing, and detection tasks. Typical substrate materials for the chip are glass and polymers. Typical techniques for microfluidic chip fabrication are utilizing various micro pattern forming methods, such as wet-etching, micro-contact printing, and hot-embossing, micro injection molding, LIGA, and micro powder blasting processes, etc. In this study, to establish the basis of the micro pattern fabrication and mass production of polymeric micro-fluidic chips using injection molding process, micro machining method was applied to form micro-channels on the LOC molds. In the research, a series of machining experiments using micro end-mills were performed to determine optimum machining conditions to improve surface roughness and shape accuracy of designed simplified micro-channels. Obtained conditions were used to machine required mold inserts for micro-channels using micro end-mills. Test injection processes using machined molds and COC polymer were performed, and then the results were investigated.

Drilling Machines: Vocational Machine Shop.

ERIC Educational Resources Information Center

Thomas, John C.

The lessons and supportive information in this field tested instructional block provide a guide for teachers in developing a machine shop course of study in drilling. The document is comprised of operation sheets, information sheets, and transparency masters for 23 lessons. Each lesson plan includes a performance objective, material and tools,…

76 FR 54800 - International Business Machines (IBM), Software Group Business Unit, Quality Assurance Group, San...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-02

... Machines (IBM), Software Group Business Unit, Quality Assurance Group, San Jose, California; Notice of... workers of International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA... February 2, 2011 (76 FR 5832). The subject worker group supplies acceptance testing services, design...

Protecting Files Hosted on Virtual Machines With Out-of-Guest Access Control

DTIC Science & Technology

2017-12-01

analyzes the design and methodology of the implemented mechanism, while Chapter 4 explains the test methodology, test cases, and performance testing ...SACL, we verify that the user or group accessing the file has sufficient permissions. If that is correct, the callback function returns control to...ferify. In the first section, we validate our design of ferify. Next, we explain the tests we performed to verify that ferify has the results we expected

Characterization of NiTi Shape Memory Damping Elements designed for Automotive Safety Systems

NASA Astrophysics Data System (ADS)

Strittmatter, Joachim; Clipa, Victor; Gheorghita, Viorel; Gümpel, Paul

2014-07-01

Actuator elements made of NiTi shape memory material are more and more known in industry because of their unique properties. Due to the martensitic phase change, they can revert to their original shape by heating when subjected to an appropriate treatment. This thermal shape memory effect (SME) can show a significant shape change combined with a considerable force. Therefore such elements can be used to solve many technical tasks in the field of actuating elements and mechatronics and will play an increasing role in the next years, especially within the automotive technology, energy management, power, and mechanical engineering as well as medical technology. Beside this thermal SME, these materials also show a mechanical SME, characterized by a superelastic plateau with reversible elongations in the range of 8%. This behavior is based on the building of stress-induced martensite of loaded austenite material at constant temperature and facilitates a lot of applications especially in the medical field. Both SMEs are attended by energy dissipation during the martensitic phase change. This paper describes the first results obtained on different actuator and superelastic NiTi wires concerning their use as damping elements in automotive safety systems. In a first step, the damping behavior of small NiTi wires up to 0.5 mm diameter was examined at testing speeds varying between 0.1 and 50 mm/s upon an adapted tensile testing machine. In order to realize higher testing speeds, a drop impact testing machine was designed, which allows testing speeds up to 4000 mm/s. After introducing this new type of testing machine, the first results of vertical-shock tests of superelastic and electrically activated actuator wires are presented. The characterization of these high dynamic phase change parameters represents the basis for new applications for shape memory damping elements, especially in automotive safety systems.

Concerns of Hydrothermal Degradation in CAD/CAM Zirconia

PubMed Central

Kim, J.-W.; Covel, N.S.; Guess, P.C.; Rekow, E.D.; Zhang, Y.

2010-01-01

Zirconia-based restorations are widely used in prosthetic dentistry; however, their susceptibility to hydrothermal degradation remains elusive. We hypothesized that CAD/CAM machining and subsequent surface treatments, i.e., grinding and/or grit-blasting, have marked effects on the hydrothermal degradation behavior of Y-TZP. CAD/CAM-machined Y-TZP plates (0.5 mm thick), both with and without subsequent grinding with various grit sizes or grit-blasting with airborne alumina particles, were subjected to accelerated aging tests in a steam autoclave. Results showed that the CAD/CAM-machined surfaces initially exhibited superior hydrothermal degradation resistance, but deteriorated at a faster rate upon prolonged autoclave treatment compared with ground and grit-blasted surfaces. The accelerated hydrothermal degradation of CAD/CAM surfaces is attributed to the CAD/CAM machining damage and the absence of surface compressive stresses in the fully sintered material. Clinical relevance for surface treatments of zirconia frameworks in terms of hydrothermal and structural stabilities is addressed. PMID:19966039

Periodical capacity setting methods for make-to-order multi-machine production systems

PubMed Central

Altendorfer, Klaus; Hübl, Alexander; Jodlbauer, Herbert

2014-01-01

The paper presents different periodical capacity setting methods for make-to-order, multi-machine production systems with stochastic customer required lead times and stochastic processing times to improve service level and tardiness. These methods are developed as decision support when capacity flexibility exists, such as, a certain range of possible working hours a week for example. The methods differ in the amount of information used whereby all are based on the cumulated capacity demand at each machine. In a simulation study the methods’ impact on service level and tardiness is compared to a constant provided capacity for a single and a multi-machine setting. It is shown that the tested capacity setting methods can lead to an increase in service level and a decrease in average tardiness in comparison to a constant provided capacity. The methods using information on processing time and customer required lead time distribution perform best. The results found in this paper can help practitioners to make efficient use of their flexible capacity. PMID:27226649

Optimisation and evaluation of hyperspectral imaging system using machine learning algorithm

NASA Astrophysics Data System (ADS)

Suthar, Gajendra; Huang, Jung Y.; Chidangil, Santhosh

2017-10-01

Hyperspectral imaging (HSI), also called imaging spectrometer, originated from remote sensing. Hyperspectral imaging is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the objects physiology, morphology, and composition. The present work involves testing and evaluating the performance of the hyperspectral imaging system. The methodology involved manually taking reflectance of the object in many images or scan of the object. The object used for the evaluation of the system was cabbage and tomato. The data is further converted to the required format and the analysis is done using machine learning algorithm. The machine learning algorithms applied were able to distinguish between the object present in the hypercube obtain by the scan. It was concluded from the results that system was working as expected. This was observed by the different spectra obtained by using the machine-learning algorithm.

Evaluation of Iron Loss in Interior Permanent Magnet Synchronous Motor with Consideration of Rotational Field

NASA Astrophysics Data System (ADS)

Ma, Lei; Sanada, Masayuki; Morimoto, Shigeo; Takeda, Yoji; Kaido, Chikara; Wakisaka, Takeaki

Loss evaluation is an important issue in the design of electrical machines. Due to the complicate structure and flux distribution, it is difficult to predict the iron loss in the machines exactly. This paper studies the iron loss in interior permanent magnet synchronous motors based on the finite element method. The iron loss test data of core material are used in the fitting of the hysteresis and eddy current loss constants. For motors in practical operation, additional iron losses due to the appearance of rotation of flux density vector and harmonic flux density distribution makes the calculation data deviates from the measured ones. Revision is made to account for these excess iron losses which exist in the practical operating condition. Calculation results show good consistence with the experimental ones. The proposed method provides a possible way to predict the iron loss of the electrical machine with good precision, and may be helpful in the selection of the core material which is best suitable for a certain machine.

Design and fabrication of metal briquette machine for shop floor

NASA Astrophysics Data System (ADS)

Pramod, R.; Kumar, G. B. Veeresh; Prashanth B., N.

2017-07-01

Efforts have to be taken to ensure efficient waste management system in shop floors, with minimum utilization of space and energy when it comes to disposing metal chips formed during machining processes. The salvaging of junk metallic chips and the us e of scrap are important for the economic production of a steelworks. For this purpose, we have fabricated a metal chip compaction machine, which can compact the metal chips into small briquettes. The project started with the survey of chips formed in shop floors and the practices involved in waste management. Study was done on the requirements for a better compaction. The heating chamber was designed taking into consideration the temperature required for an easy compaction of the metal chips. The power source for compaction and the pneumatic design for mechanism was done following the appropriate calculations regarding the air pressure provided and thrust required. The processes were tested under different conditions and found effective. The fabrication of the machine has been explained in detail and the results have been discussed.

Designing Anticancer Peptides by Constructive Machine Learning.

PubMed

Grisoni, Francesca; Neuhaus, Claudia S; Gabernet, Gisela; Müller, Alex T; Hiss, Jan A; Schneider, Gisbert

2018-04-21

Constructive (generative) machine learning enables the automated generation of novel chemical structures without the need for explicit molecular design rules. This study presents the experimental application of such a deep machine learning model to design membranolytic anticancer peptides (ACPs) de novo. A recurrent neural network with long short-term memory cells was trained on α-helical cationic amphipathic peptide sequences and then fine-tuned with 26 known ACPs by transfer learning. This optimized model was used to generate unique and novel amino acid sequences. Twelve of the peptides were synthesized and tested for their activity on MCF7 human breast adenocarcinoma cells and selectivity against human erythrocytes. Ten of these peptides were active against cancer cells. Six of the active peptides killed MCF7 cancer cells without affecting human erythrocytes with at least threefold selectivity. These results advocate constructive machine learning for the automated design of peptides with desired biological activities. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Effect of compaction pressure on the properties of dental machinable zirconia ceramic].

PubMed

Huang, Hui; Wei, Bin; Zhang, Fu-qiang; Sun, Jing; Gao, Lian

2010-10-01

To investigate the effect of compaction pressure on the linear shrinkage, sintering property and machinability of the dental zirconia ceramic. The nano-size zirconia powder was compacted at different isostatic pressure and sintered at different temperature. The linear shrinkage of sintered body was measured and the relative density was tested using the Archimedes method. The cylindrical surface of pre-sintering blanks was traversed using a hard metal tool. Surface and edge quality were checked visually using light stereo microscopy. The sintering behaviour depended on the compaction pressure. Increasing compaction pressure led to higher sintering rate and lower sintering temperature. Increasing compaction pressure also led to decreasing linear shrinkage of the sintered bodies, from 24.54% of 50 MPa to 20.9% of 400 MPa. Compaction pressure showed only a weak influence on machinability of zirconia blanks, but the higher compaction pressure resulted in the poor surface quality. The better sintering property and machinability of dental zirconia ceramic is found for 200-300 MPa compaction pressure.

A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms

PubMed Central

2013-01-01

Background An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets. Results The results show that machine learning algorithms can effectively distinguish expected true from expected false vaccine candidates (with an average sensitivity and specificity of 0.97 and 0.98 respectively), for proteins observed to induce immune responses experimentally. Conclusions Vaccine candidates from an in silico approach can only be truly validated in a laboratory. Given any in silico output and appropriate training data, the number of false candidates allocated for validation can be dramatically reduced using a pool of machine learning algorithms. This will ultimately save time and money in the laboratory. PMID:24180526

Structural Benchmark Testing of Superalloy Lattice Block Subelements Completed

NASA Technical Reports Server (NTRS)

2004-01-01

Superalloy lattice block panels, which are produced directly by investment casting, are composed of thin ligaments arranged in three-dimensional triangulated trusslike structures (see the preceding figure). Optionally, solid panel face sheets can be formed integrally during casting. In either form, lattice block panels can easily be produced with weights less than 25 percent of the mass of a solid panel. Inconel 718 (IN 718) and MarM-247 superalloy lattice block panels have been developed under NASA's Ultra-Efficient Engine Technology Project and Higher Operating Temperature Propulsion Components Project to take advantage of the superalloys' high strength and elevated temperature capability with the inherent light weight and high stiffness of the lattice architecture (ref. 1). These characteristics are important in the future development of turbine engine components. Casting quality and structural efficiency were evaluated experimentally using small beam specimens machined from the cast and heat treated 140- by 300- by 11-mm panels. The matrix of specimens included samples of each superalloy in both open-celled and single-face-sheet configurations, machined from longitudinal, transverse, and diagonal panel orientations. Thirty-five beam subelements were tested in Glenn's Life Prediction Branch's material test machine at room temperature and 650 C under both static (see the following photograph) and cyclic load conditions. Surprisingly, test results exceeded initial linear elastic analytical predictions. This was likely a result of the formation of plastic hinges and redundancies inherent in lattice block geometry, which was not considered in the finite element models. The value of a single face sheet was demonstrated by increased bending moment capacity, where the face sheet simultaneously increased the gross section modulus and braced the compression ligaments against early buckling as seen in open-cell specimens. Preexisting flaws in specimens were not a discriminator in flexural, shear, or stiffness measurements, again because of redundant load paths available in the lattice block structure. Early test results are available in references 2 and 3; more complete analyses are scheduled for publication in 2004.

Radial-piston pump for drive of test machines

NASA Astrophysics Data System (ADS)

Nizhegorodov, A. I.; Gavrilin, A. N.; Moyzes, B. B.; Cherkasov, A. I.; Zharkevich, O. M.; Zhetessova, G. S.; Savelyeva, N. A.

2018-01-01

The article reviews the development of radial-piston pump with phase control and alternating-flow mode for seismic-testing platforms and other test machines. The prospects for use of the developed device are proved. It is noted that the method of frequency modulation with the detection of the natural frequencies is easily realized by using the radial-piston pump. The prospects of further research are given proof.

Production of thick uniform-coating films containing rectorite on nanofibers through the use of an automated coating machine.

PubMed

Wu, Yang; Li, Xueyong; Shi, Xiaowen; Zhan, Yingfei; Tu, Hu; Du, Yumin; Deng, Hongbing; Jiang, Linbin

2017-01-01

When an efficient automated coating machine is used to process layer-by-layer (LBL) deposited nanofibrous mats, it causes an obvious planar effect on the surface of the mats, which can be eliminated through ultimate immersion. During this process, chitosan (CS) - rectorite (REC) intercalated composite films are built on the surface of cellulose acetate (CA) nanofibrous mats by a coating machine. Then, the immersion process is utilized to allow positively charged CS or CS-REC intercalated composites to uniformly assemble on the surface of negatively charged CA nanofibers. An investigation into the morphology of the resultant scaffolds confirms that the uniquely small pore size, high specific surface area and typically three-dimensional (3D) structure of nanofibrous mats remain present. The results of Fourier transform infrared (FT-IR) and X-ray photoelectron spectroscopy (XPS) indicate that it is feasible to assemble nanofibrous mats using a coating machine. The intercalated structure of CS-REC is confirmed by the results of small-angle X-ray diffraction (SAXRD) and wide-angle X-ray diffraction (WAXRD). The results of the cell experiment and antibacterial test demonstrate that the addition of REC not only has little impact on the cytocompatibility of the mats but also enhances their ability to inhibit bacteria. Copyright © 2016 Elsevier B.V. All rights reserved.

An Analysis of a Digital Variant of the Trail Making Test Using Machine Learning Techniques

PubMed Central

Dahmen, Jessamyn; Cook, Diane; Fellows, Robert; Schmitter-Edgecombe, Maureen

2017-01-01

BACKGROUND The goal of this work is to develop a digital version of a standard cognitive assessment, the Trail Making Test (TMT), and assess its utility. OBJECTIVE This paper introduces a novel digital version of the TMT and introduces a machine learning based approach to assess its capabilities. METHODS Using digital Trail Making Test (dTMT) data collected from (N=54) older adult participants as feature sets, we use machine learning techniques to analyze the utility of the dTMT and evaluate the insights provided by the digital features. RESULTS Predicted TMT scores correlate well with clinical digital test scores (r=0.98) and paper time to completion scores (r=0.65). Predicted TICS exhibited a small correlation with clinically-derived TICS scores (r=0.12 Part A, r=0.10 Part B). Predicted FAB scores exhibited a small correlation with clinically-derived FAB scores (r=0.13 Part A, r=0.29 for Part B). Digitally-derived features were also used to predict diagnosis (AUC of 0.65). CONCLUSION Our findings indicate that the dTMT is capable of measuring the same aspects of cognition as the paper-based TMT. Furthermore, the dTMT’s additional data may be able to help monitor other cognitive processes not captured by the paper-based TMT alone. PMID:27886019

Assessing a Novel Method to Reduce Anesthesia Machine Contamination: A Prospective, Observational Trial.

PubMed

Biddle, Chuck J; George-Gay, Beverly; Prasanna, Praveen; Hill, Emily M; Davis, Thomas C; Verhulst, Brad

2018-01-01

Anesthesia machines are known reservoirs of bacterial species, potentially contributing to healthcare associated infections (HAIs). An inexpensive, disposable, nonpermeable, transparent anesthesia machine wrap (AMW) may reduce microbial contamination of the anesthesia machine. This study quantified the density and diversity of bacterial species found on anesthesia machines after terminal cleaning and between cases during actual anesthesia care to assess the impact of the AMW. We hypothesized reduced bioburden with the use of the AMW. In a prospective, experimental research design, the AMW was used in 11 surgical cases (intervention group) and not used in 11 control surgical cases. Cases were consecutively assigned to general surgical operating rooms. Seven frequently touched and difficult to disinfect "hot spots" were cultured on each machine preceding and following each case. The density and diversity of cultured colony forming units (CFUs) between the covered and uncovered machines were compared using Wilcoxon signed-rank test and Student's t -tests. There was a statistically significant reduction in CFU density and diversity when the AMW was employed. The protective effect of the AMW during regular anesthetic care provides a reliable and low-cost method to minimize the transmission of pathogens across patients and potentially reduces HAIs.

Langmuir probes for SPIDER (source for the production of ions of deuterium extracted from radio frequency plasma) experiment: Tests in BATMAN (Bavarian test machine for negative ions)

NASA Astrophysics Data System (ADS)

Brombin, M.; Spolaore, M.; Serianni, G.; Pomaro, N.; Taliercio, C.; Palma, M. Dalla; Pasqualotto, R.; Schiesko, L.

2014-11-01

A prototype system of the Langmuir probes for SPIDER (Source for the production of Ions of Deuterium Extracted from RF plasma) was manufactured and experimentally qualified. The diagnostic was operated in RF (Radio Frequency) plasmas with cesium evaporation on the BATMAN (BAvarian Test MAchine for Negative ions) test facility, which can provide plasma conditions as expected in the SPIDER source. A RF passive compensation circuit was realised to operate the Langmuir probes in RF plasmas. The sensors' holder, designed to better simulate the bias plate conditions in SPIDER, was exposed to a severe experimental campaign in BATMAN with cesium evaporation. No detrimental effect on the diagnostic due to cesium evaporation was found during the exposure to the BATMAN plasma and in particular the insulation of the electrodes was preserved. The paper presents the system prototype, the RF compensation circuit, the acquisition system (as foreseen in SPIDER), and the results obtained during the experimental campaigns.

Langmuir probes for SPIDER (Source for the production of Ions of Deuterium Extracted from Radio Frequency plasma) experiment: tests in BATMAN (BAvarian Test Machine for Negative ions).

PubMed

Brombin, M; Spolaore, M; Serianni, G; Pomaro, N; Taliercio, C; Dalla Palma, M; Pasqualotto, R; Schiesko, L

2014-11-01

A prototype system of the Langmuir probes for SPIDER (Source for the production of Ions of Deuterium Extracted from RF plasma) was manufactured and experimentally qualified. The diagnostic was operated in RF (Radio Frequency) plasmas with cesium evaporation on the BATMAN (BAvarian Test MAchine for Negative ions) test facility, which can provide plasma conditions as expected in the SPIDER source. A RF passive compensation circuit was realised to operate the Langmuir probes in RF plasmas. The sensors' holder, designed to better simulate the bias plate conditions in SPIDER, was exposed to a severe experimental campaign in BATMAN with cesium evaporation. No detrimental effect on the diagnostic due to cesium evaporation was found during the exposure to the BATMAN plasma and in particular the insulation of the electrodes was preserved. The paper presents the system prototype, the RF compensation circuit, the acquisition system (as foreseen in SPIDER), and the results obtained during the experimental campaigns.

Age group classification and gender detection based on forced expiratory spirometry.

PubMed

Cosgun, Sema; Ozbek, I Yucel

2015-08-01

This paper investigates the utility of forced expiratory spirometry (FES) test with efficient machine learning algorithms for the purpose of gender detection and age group classification. The proposed method has three main stages: feature extraction, training of the models and detection. In the first stage, some features are extracted from volume-time curve and expiratory flow-volume loop obtained from FES test. In the second stage, the probabilistic models for each gender and age group are constructed by training Gaussian mixture models (GMMs) and Support vector machine (SVM) algorithm. In the final stage, the gender (or age group) of test subject is estimated by using the trained GMM (or SVM) model. Experiments have been evaluated on a large database from 4571 subjects. The experimental results show that average correct classification rate performance of both GMM and SVM methods based on the FES test is more than 99.3 % and 96.8 % for gender and age group classification, respectively.

The Role of Balanced Training and Testing Data Sets for Binary Classifiers in Bioinformatics

PubMed Central

Wei, Qiong; Dunbrack, Roland L.

2013-01-01

Training and testing of conventional machine learning models on binary classification problems depend on the proportions of the two outcomes in the relevant data sets. This may be especially important in practical terms when real-world applications of the classifier are either highly imbalanced or occur in unknown proportions. Intuitively, it may seem sensible to train machine learning models on data similar to the target data in terms of proportions of the two binary outcomes. However, we show that this is not the case using the example of prediction of deleterious and neutral phenotypes of human missense mutations in human genome data, for which the proportion of the binary outcome is unknown. Our results indicate that using balanced training data (50% neutral and 50% deleterious) results in the highest balanced accuracy (the average of True Positive Rate and True Negative Rate), Matthews correlation coefficient, and area under ROC curves, no matter what the proportions of the two phenotypes are in the testing data. Besides balancing the data by undersampling the majority class, other techniques in machine learning include oversampling the minority class, interpolating minority-class data points and various penalties for misclassifying the minority class. However, these techniques are not commonly used in either the missense phenotype prediction problem or in the prediction of disordered residues in proteins, where the imbalance problem is substantial. The appropriate approach depends on the amount of available data and the specific problem at hand. PMID:23874456

Metallic wear debris sensors: promising developments in failure prevention for wind turbine gearsets and similar components

NASA Astrophysics Data System (ADS)

Poley, Jack; Dines, Michael

2011-04-01

Wind turbines are frequently located in remote, hard-to-reach locations, making it difficult to apply traditional oil analysis sampling of the machine's critical gearset at timely intervals. Metal detection sensors are excellent candidates for sensors designed to monitor machine condition in vivo. Remotely sited components, such as wind turbines, therefore, can be comfortably monitored from a distance. Online sensor technology has come of age with products now capable of identifying onset of wear in time to avoid or mitigate failure. Online oil analysis is now viable, and can be integrated with onsite testing to vet sensor alarms, as well as traditional oil analysis, as furnished by offsite laboratories. Controlled laboratory research data were gathered from tests conducted on a typical wind turbine gearbox, wherein total ferrous particle measurement and metallic particle counting were employed and monitored. The results were then compared with a physical inspection for wear experienced by the gearset. The efficacy of results discussed herein strongly suggests the viability of metallic wear debris sensors in today's wind turbine gearsets, as correlation between sensor data and machine trauma were very good. By extension, similar components and settings would also seem amenable to wear particle sensor monitoring. To our knowledge no experiments such as described herein, have previously been conducted and published.

Machine learning landscapes and predictions for patient outcomes

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-07-01

The theory and computational tools developed to interpret and explore energy landscapes in molecular science are applied to the landscapes defined by local minima for neural networks. These machine learning landscapes correspond to fits of training data, where the inputs are vital signs and laboratory measurements for a database of patients, and the objective is to predict a clinical outcome. In this contribution, we test the predictions obtained by fitting to single measurements, and then to combinations of between 2 and 10 different patient medical data items. The effect of including measurements over different time intervals from the 48 h period in question is analysed, and the most recent values are found to be the most important. We also compare results obtained for neural networks as a function of the number of hidden nodes, and for different values of a regularization parameter. The predictions are compared with an alternative convex fitting function, and a strong correlation is observed. The dependence of these results on the patients randomly selected for training and testing decreases systematically with the size of the database available. The machine learning landscapes defined by neural network fits in this investigation have single-funnel character, which probably explains why it is relatively straightforward to obtain the global minimum solution, or a fit that behaves similarly to this optimal parameterization.

Machine for use in monitoring fatigue life for a plurality of elastomeric specimens

NASA Technical Reports Server (NTRS)

Fitzer, G. E. (Inventor)

1977-01-01

An improved machine is described for use in determining the fatigue life for elastomeric specimens. The machine is characterized by a plurality of juxtaposed test stations, specimen support means located at each of the test stations for supporting a plurality of specimens of elastomeric material, and means for subjecting the specimens at each of said stations to sinusoidal strain at a strain rate unique with respect to the strain rate at which the specimens at each of the other stations is subjected to sinusoidal strain.

Standard method of test for grindability of coal by the Hardgrove-machine method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1975-01-01

A procedure is described for sampling coal, grinding in a Hardgrove grinding machine, and passing through standard sieves to determine the degree of pulverization of coals. The grindability index of the coal tested is calculated from a calibration chart prepared by plotting weight of material passing a No. 200 sieve versus the Hardgrove Grindability Index for the standard reference samples. The Hardgrove machine is shown schematically. The method for preparing and determining grindability indexes of standard reference samples is given in the appendix. (BLM)

Machinability of hypereutectic silicon-aluminum alloys

NASA Astrophysics Data System (ADS)

Tanaka, T.; Akasawa, T.

1999-08-01

The machinability of high-silicon aluminum alloys made by a P/M process and by casting was compared. The cutting test was conducted by turning on lathes with the use of cemented carbide tools. The tool wear by machining the P/M alloy was far smaller than the tool wear by machining the cast alloy. The roughness of the machined surface of the P/M alloy is far better than that of the cast alloy, and the turning speed did not affect it greatly at higher speeds. The P/M alloy produced long chips, so the disposal can cause trouble. The size effect of silicon grains on the machinability is discussed.

StruLocPred: structure-based protein subcellular localisation prediction using multi-class support vector machine.

PubMed

Zhou, Wengang; Dickerson, Julie A

2012-01-01

Knowledge of protein subcellular locations can help decipher a protein's biological function. This work proposes new features: sequence-based: Hybrid Amino Acid Pair (HAAP) and two structure-based: Secondary Structural Element Composition (SSEC) and solvent accessibility state frequency. A multi-class Support Vector Machine is developed to predict the locations. Testing on two established data sets yields better prediction accuracies than the best available systems. Comparisons with existing methods show comparable results to ESLPred2. When StruLocPred is applied to the entire Arabidopsis proteome, over 77% of proteins with known locations match the prediction results. An implementation of this system is at http://wgzhou.ece. iastate.edu/StruLocPred/.

Variable Delay Testing Using ONE

NASA Technical Reports Server (NTRS)

Ishac, Joseph

2002-01-01

This paper investigates the effect of long and changing propagation delays on the performance of TCP file transfers. Tests are performed with machines that emulate communication from a low/medium-earth satellite to Earth by way of a geosynchronous satellite. As a result of these tests, we find that TCP is fairly robust to varying delays given a high enough TCP timer granularity. However, performance degrades noticeably for larger file transfers when a finer timer granularity is used. Such results have also been observed in previous simulations by other researchers, and thus, this work serves as an extension of those results.

Software platform virtualization in chemistry research and university teaching.

PubMed

Kind, Tobias; Leamy, Tim; Leary, Julie A; Fiehn, Oliver

2009-11-16

Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide.

Fatigue Lives Of Laser-Cut Metals

NASA Technical Reports Server (NTRS)

Martin, Michael R.

1988-01-01

Fatigue lives made to approach those attainable by traditional grinding methods. Fatigue-test specimens prepared from four metallic alloys, and material removed from specimens by manual grinding, by Nd:glass laser, and by Nd:YAG laser. Results of fatigue tests of all specimens indicated reduction of fatigue strengths of laser-fired specimens. Laser machining holds promise for improved balancing of components of gas turbines.

JPRS Report, Science & Technology, Japan

DTIC Science & Technology

1991-01-31

final test. Keywords: Spherical Pressure Hull, Titanium Alloy , Three-Dimensional Machining, Electron Beam Welding . 1. Introduction In bodies like... processed (the heat treatment involving high-temperature heating and rapid quenching in order to obtain finer grains of the titanium alloy ) and...given m Table 3. The test results were all satisfactory. Forged material of titanium alloy , manufactured by forging, beta processing , and billet

Testing of machine wound second generation HTS tape Vacuum Pressure Impregnated coils

NASA Astrophysics Data System (ADS)

Swaffield, D.; Lewis, C.; Eugene, J.; Ingles, M.; Peach, D.

2014-05-01

Delamination of second generation (2G) High Temperature Superconducting (HTS) tapes has previously been reported when using resin based insulation systems for wound coils. One proposed root cause is the differential thermal contraction between the coil former and the resin encapsulated coil turns resulting in the tape c-axis tensile stress being exceeded. Importantly, delamination results in unacceptable degradation of the superconductor critical current level. To mitigate the delamination risk and prove winding, jointing and Vacuum Pressure Impregnation (VPI) processes in the production of coils for superconducting rotating machines at GE Power Conversion two scaled trial coils have been wound and extensively tested. The coils are wound from 12mm wide 2G HTS tape supplied by AMSC onto stainless steel 'racetrack' coil formers. The coils are wound in two layers which include both in-line and layer-layer joints subject to in-process test. The resin insulation system chosen is VPI and oven cured. Tests included; insulation resistance, repeat quench and recovery of the superconductor, heat runs and measurement of n-value, before and after multiple thermal cycling between ambient and 35 Kelvin. No degradation of coil performance is evidenced.

Assessment and evaluation of noise controls on roof bolting equipment and a method for predicting sound pressure levels in underground coal mining

NASA Astrophysics Data System (ADS)

Matetic, Rudy J.

Over-exposure to noise remains a widespread and serious health hazard in the U.S. mining industries despite 25 years of regulation. Every day, 80% of the nation's miners go to work in an environment where the time weighted average (TWA) noise level exceeds 85 dBA and more than 25% of the miners are exposed to a TWA noise level that exceeds 90 dBA, the permissible exposure limit (PEL). Additionally, MSHA coal noise sample data collected from 2000 to 2002 show that 65% of the equipment whose operators exceeded 100% noise dosage comprise only seven different types of machines; auger miners, bulldozers, continuous miners, front end loaders, roof bolters, shuttle cars (electric), and trucks. In addition, the MSHA data indicate that the roof bolter is third among all the equipment and second among equipment in underground coal whose operators exceed 100% dosage. A research program was implemented to: (1) determine, characterize and to measure sound power levels radiated by a roof bolting machine during differing drilling configurations (thrust, rotational speed, penetration rate, etc.) and utilizing differing types of drilling methods in high compressive strength rock media (>20,000 psi). The research approach characterized the sound power level results from laboratory testing and provided the mining industry with empirical data relative to utilizing differing noise control technologies (drilling configurations and types of drilling methods) in reducing sound power level emissions on a roof bolting machine; (2) distinguish and correlate the empirical data into one, statistically valid, equation, in which, provided the mining industry with a tool to predict overall sound power levels of a roof bolting machine given any type of drilling configuration and drilling method utilized in industry; (3) provided the mining industry with several approaches to predict or determine sound pressure levels in an underground coal mine utilizing laboratory test results from a roof bolting machine and (4) described a method for determining an operators' noise dosage of a roof bolting machine utilizing predicted or determined sound pressure levels.

Effet de l'usinage sur les proprietes mecaniques en tension et controle non-destructif des materiaux composites

NASA Astrophysics Data System (ADS)

Genereux, Louis-Alexandre

The main goal of this work is to evaluate the impact of milling operations on the integrity of unidirectional carbon/epoxy laminate. Milling, often used for finishing composite structures, cause some damage in the form of craters, cracks and thermal damage to the matrix. Here, two approaches are used to qualify and quantify the amount of damage. First, two nondestructive testing methods, namely immersion ultrasonic inspection and pulsed thermography, are evaluated on samples with artificial defects. These techniques are then used on machined samples with realistic machining damages. Only ultrasounds allowed the detection and quantification of the machining damages, but only if the damages are at the surface of the laminate. The depth of damage depends primarily on the fiber orientation of the first ply with respect to the cutting direction. The ultrasonic inspections are also accompanied by scanning electron microscope observations. The second approach is to check whether the presence of the machining damage will affect the mechanical properties of the laminate. To do this, static tensile tests are performed on samples prepared by three different methods, namely, by abrasive diamond saw, by saw cut followed by sanding and finally by milling. The results show that the damages caused by the milling operation are not important enough to affect the ultimate stress and elastic modulus. Despite this, it would be interesting, for future works, to investigate this aspect in fatigue rather than with static tests. The presence of damages on the edge might promote delamination during cyclic loads.

Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

PubMed

Awaysheh, Abdullah; Wilcke, Jeffrey; Elvinger, François; Rees, Loren; Fan, Weiguo; Zimmerman, Kurt L

2016-11-01

Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. We tested the use of supervised machine-learning algorithms to differentiate between the 2 diseases using data generated from noninvasive diagnostic tests. Three prediction models were developed using 3 machine-learning algorithms: naive Bayes, decision trees, and artificial neural networks. The models were trained and tested on data from complete blood count (CBC) and serum chemistry (SC) results for the following 3 groups of client-owned cats: normal, inflammatory bowel disease (IBD), or alimentary lymphoma (ALA). Naive Bayes and artificial neural networks achieved higher classification accuracy (sensitivities of 70.8% and 69.2%, respectively) than the decision tree algorithm (63%, p < 0.0001). The areas under the receiver-operating characteristic curve for classifying cases into the 3 categories was 83% by naive Bayes, 79% by decision tree, and 82% by artificial neural networks. Prediction models using machine learning provided a method for distinguishing between ALA-IBD, ALA-normal, and IBD-normal. The naive Bayes and artificial neural networks classifiers used 10 and 4 of the CBC and SC variables, respectively, to outperform the C4.5 decision tree, which used 5 CBC and SC variables in classifying cats into the 3 classes. These models can provide another noninvasive diagnostic tool to assist clinicians with differentiating between IBD and ALA, and between diseased and nondiseased cats. © 2016 The Author(s).

Seasonal streamflow forecast with machine learning and teleconnection indices in the context non-stationary climate

NASA Astrophysics Data System (ADS)

Haguma, D.; Leconte, R.

2017-12-01

Spatial and temporal water resources variability are associated with large-scale pressure and circulation anomalies known as teleconnections that influence the pattern of the atmospheric circulation. Teleconnection indices have been used successfully to forecast streamflow in short term. However, in some watersheds, classical methods cannot establish relationships between seasonal streamflow and teleconnection indices because of weak correlation. In this study, machine learning algorithms have been applied for seasonal streamflow forecast using teleconnection indices. Machine learning offers an alternative to classical methods to address the non-linear relationship between streamflow and teleconnection indices the context non-stationary climate. Two machine learning algorithms, random forest (RF) and support vector machine (SVM), with teleconnection indices associated with North American climatology, have been used to forecast inflows for one and two leading seasons for the Romaine River and Manicouagan River watersheds, located in Quebec, Canada. The indices are Pacific-North America (PNA), North Atlantic Oscillation (NAO), El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO). The results showed that the machine learning algorithms have an important predictive power for seasonal streamflow for one and two leading seasons. The RF performed better for training and SVM generally have better results with high predictive capability for testing. The RF which is an ensemble method, allowed to assess the uncertainty of the forecast. The integration of teleconnection indices responds to the seasonal forecast of streamflow in the conditions of the non-stationarity the climate, although the teleconnection indices have a weak correlation with streamflow.

Experiments and simulation of thermal behaviors of the dual-drive servo feed system

NASA Astrophysics Data System (ADS)

Yang, Jun; Mei, Xuesong; Feng, Bin; Zhao, Liang; Ma, Chi; Shi, Hu

2015-01-01

The machine tool equipped with the dual-drive servo feed system could realize high feed speed as well as sharp precision. Currently, there is no report about the thermal behaviors of the dual-drive machine, and the current research of the thermal characteristics of machines mainly focuses on steady simulation. To explore the influence of thermal characterizations on the precision of a jib boring machine assembled dual-drive feed system, the thermal equilibrium tests and the research on thermal-mechanical transient behaviors are carried out. A laser interferometer, infrared thermography and a temperature-displacement acquisition system are applied to measure the temperature distribution and thermal deformation at different feed speeds. Subsequently, the finite element method (FEM) is used to analyze the transient thermal behaviors of the boring machine. The complex boundary conditions, such as heat sources and convective heat transfer coefficient, are calculated. Finally, transient variances in temperatures and deformations are compared with the measured values, and the errors between the measurement and the simulation of the temperature and the thermal error are 2 °C and 2.5 μm, respectively. The researching results demonstrate that the FEM model can predict the thermal error and temperature distribution very well under specified operating condition. Moreover, the uneven temperature gradient is due to the asynchronous dual-drive structure that results in thermal deformation. Additionally, the positioning accuracy decreases as the measured point became further away from the motor, and the thermal error and equilibrium period both increase with feed speeds. The research proposes a systematical method to measure and simulate the boring machine transient thermal behaviors.

Thermal measurement of brake pad lining surfaces during the braking process

NASA Astrophysics Data System (ADS)

Piątkowski, Tadeusz; Polakowski, Henryk; Kastek, Mariusz; Baranowski, Pawel; Damaziak, Krzysztof; Małachowski, Jerzy; Mazurkiewicz, Łukasz

2012-06-01

This paper presents the test campaign concept and definition and the analysis of the recorded measurements. One of the most important systems in cars and trucks are brakes. The braking temperature on a lining surface can rise above 500°C. This shows how linings requirements are so strict and, what is more, continuously rising. Besides experimental tests, very supportive method for investigating processes which occur on the brake pad linings are numerical analyses. Experimental tests were conducted on the test machine called IL-68. The main component of IL-68 is so called frictional unit, which consists of: rotational head, which convey a shaft torque and where counter samples are placed and translational head, where samples of coatings are placed and pressed against counter samples. Due to the high rotational speeds and thus the rapid changes in temperature field, the infrared camera was used for testing. The paper presents results of analysis registered thermograms during the tests with different conditions. Furthermore, based on this testing machine, the numerical model was developed. In order to avoid resource demanding analyses only the frictional unit (described above) was taken into consideration. Firstly the geometrical model was performed thanks to CAD techniques, which in the next stage was a base for developing the finite element model. Material properties and boundary conditions exactly correspond to experimental tests. Computations were performed using a dynamic LS-Dyna code where heat generation was estimated assuming full (100%) conversion of mechanical work done by friction forces. Paper presents the results of dynamic thermomechanical analysis too and these results were compared with laboratory tests.

Man-machine Integration Design and Analysis System (MIDAS) Task Loading Model (TLM) experimental and software detailed design report

NASA Technical Reports Server (NTRS)

Staveland, Lowell

1994-01-01

This is the experimental and software detailed design report for the prototype task loading model (TLM) developed as part of the man-machine integration design and analysis system (MIDAS), as implemented and tested in phase 6 of the Army-NASA Aircrew/Aircraft Integration (A3I) Program. The A3I program is an exploratory development effort to advance the capabilities and use of computational representations of human performance and behavior in the design, synthesis, and analysis of manned systems. The MIDAS TLM computationally models the demands designs impose on operators to aide engineers in the conceptual design of aircraft crewstations. This report describes TLM and the results of a series of experiments which were run this phase to test its capabilities as a predictive task demand modeling tool. Specifically, it includes discussions of: the inputs and outputs of TLM, the theories underlying it, the results of the test experiments, the use of the TLM as both stand alone tool and part of a complete human operator simulation, and a brief introduction to the TLM software design.

Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

PubMed

Das, Nilakash; Topalovic, Marko; Janssens, Wim

2018-03-01

The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases. Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies. Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

PubMed

Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

2017-01-01

Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jamieson, Kevin; Davis, IV, Warren L.

Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building themore » system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.« less

Force supplementary comparison at SIM (SIM.M.F-S5), compression testing machines calibration, up to 200 kN

NASA Astrophysics Data System (ADS)

Cárdenas Moctezuma, A.; Torres Guzmán, J. C.

2016-01-01

CENAM, through the Force and Pressure Division, organized a comparison on testing machines calibration, in compression mode. The participating laboratories were SIM National Institutes of Metrology from Colombia, Peru and Costa Rica, where CENAM, Mexico was the pilot and reference laboratory. The results obtained by the laboratories are presented in this paper as well as the analysis of compatibility. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

Strain-rate behavior in tension of the tempered martensitic reduced activation steel Eurofer97

NASA Astrophysics Data System (ADS)

Cadoni, Ezio; Dotta, Matteo; Forni, Daniele; Spätig, Philippe

2011-07-01

The tensile properties of the high-chromium tempered martensitic reduced activation steel Eurofer97 were determined from tests carried out over a wide range of strain-rates on cylindrical specimens. The quasi-static tests were performed with a universal electro-mechanical machine, whereas a hydro-pneumatic machine and a JRC-split Hopkinson tensile bar apparatus were used for medium and high strain-rates respectively. This tempered martensitic stainless steel showed significant strain-rate sensitivity. The constitutive behavior was investigated within a framework of dislocations dynamics model using Kock's approach. The parameters of the model were determined and then used to predict the deformation range of the tensile deformation stability. A very good agreement between the experimental results and predictions of the model was found.

Some preliminary results from the NWTC direct-drive, variable-speed test bed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlin, P.W.; Fingersh, L.J.

1996-10-01

With the remarkable rise in interest in variable-speed operation of larger wind turbines, it has become important for the National Wind Technology Center (NWTC) to have access to a variable-speed test bed that can be specially instrumented for research. Accordingly, a three-bladed, 10-meter, downwind, Grumman Windstream machine has been equipped with a set of composite blades and a direct-coupled, permanent-magnet, 20 kilowatt generator. This machine and its associated control system and data collection system are discussed. Several variations of a maximum power control algorithm have been installed on the control computer. To provide a baseline for comparison, several constant speedmore » algorithms have also been installed. The present major effort is devoted to daytime, semi-autonomous data collection.« less

Installation and checkout of the DOE/NASA Mod-1 2000-kW wind turbine generator

NASA Technical Reports Server (NTRS)

Puthoff, R. L.; Collins, J. L.; Wolf, R. A.

1980-01-01

The paper describes the DOE/NASA Mod-1 wind turbine generator, its assembly and testing, and its installation at Boone, North Carolina. The paper concludes with performance data taken during the initial tests conducted on the machine. The successful installation and initial operation of the Mod-1 wind turbine generator has had the following results: (1) megawatt-size wind turbines can be operated satisfactorily on utility grids; (2) the structural loads can be predicted by existing codes; (3) assembly of the machine on top of the tower presents no major problem; (4) large blades 100 ft long can be transported long distances and over mountain roads; and (5) operating experience and performance data will contribute substantially to the design of future low-cost wind turbines.

Development of a synchrotron biaxial tensile device for in situ characterization of thin films mechanical response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geandier, G.; Synchrotron SOLEIL, L'Orme des Merisiers, BP 48, 91192 Gif sur Yvette; LPMTM, UPR 9001 CNRS, Universite Paris-Nord, 93430 Villetaneuse

2010-10-15

We have developed on the DIFFABS-SOLEIL beamline a biaxial tensile machine working in the synchrotron environment for in situ diffraction characterization of thin polycrystalline films mechanical response. The machine has been designed to test compliant substrates coated by the studied films under controlled, applied strain field. Technological challenges comprise the sample design including fixation of the substrate ends, the related generation of a uniform strain field in the studied (central) volume, and the operations from the beamline pilot. Preliminary tests on 150 nm thick W films deposited onto polyimide cruciform substrates are presented. The obtained results for applied strains usingmore » x-ray diffraction and digital image correlation methods clearly show the full potentialities of this new setup.« less

A bi-axial active boring tool for chatter mitigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redmond, J.M.; Barney, P.S.

This paper summarizes results of metal cutting tests using an actively damped boring bar to suppress regenerative chatter. PZT stack actuators were integrated into a commercially available two-inch diameter boring bar to suppress bending vibrations. Since the modified tool requires no specialized mounting hardware, it can be readily mounted on a variety of machines. A cutting test using the prototype bar to remove metal from a hardened steel workpiece verifies that the authors actively damped tool yields significant vibration reduction and improved surface finish as compared to the open-loop case. In addition, the overall performance of the prototype bar ismore » compared to that of an unmodified bar of pristine geometry, revealing that a significant enlargement of the stable machining envelope is obtained through application of feedback control.« less

10 CFR 431.294 - Uniform test method for the measurement of energy consumption of refrigerated bottled or canned...

Code of Federal Regulations, 2010 CFR

2010-01-01

... consumption of refrigerated bottled or canned beverage vending machines. 431.294 Section 431.294 Energy... method for the measurement of energy consumption of refrigerated bottled or canned beverage vending... test procedure for energy consumption of refrigerated bottled or canned beverage vending machines shall...

Servomotors. (Latest Citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1996-01-01

The bibliography contains citations concerning the design, testing, and application of servomotors. AC, DC, and brushless motor drives are discussed. Applications are examined, including use in hydraulic presses; teleprinters; machine tools; sewing machines; and servocontrol devices for instrumentation, robots, and aircraft control. Testing methods evaluate precision, vibration and vibration reduction, and stability of servomotors.

Multivariate Models for Prediction of Human Skin Sensitization Hazard

PubMed Central

Strickland, Judy; Zang, Qingda; Paris, Michael; Lehmann, David M.; Allen, David; Choksi, Neepa; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Kleinstreuer, Nicole

2016-01-01

One of ICCVAM’s top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays—the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT), and KeratinoSens™ assay—six physicochemical properties, and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches, logistic regression (LR) and support vector machine (SVM), to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three LR and three SVM) with the highest accuracy (92%) used: (1) DPRA, h-CLAT, and read-across; (2) DPRA, h-CLAT, read-across, and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens, and log P. The models performed better at predicting human skin sensitization hazard than the murine local lymph node assay (accuracy = 88%), any of the alternative methods alone (accuracy = 63–79%), or test batteries combining data from the individual methods (accuracy = 75%). These results suggest that computational methods are promising tools to effectively identify potential human skin sensitizers without animal testing. PMID:27480324

Influence of implant surface topography on bone-regenerative potential and mechanical retention in the human maxilla and mandible.

PubMed

Wei, Niu; Bin, Shi; Jing, Zhou; Wei, Sun; Yingqiong, Zhao

2014-06-01

To evaluate the short- and mid-term effects of commercial pure (cp) titanium implant surface topography on osseointegration, bone-regenerative potential and mechanical retention in the human maxilla and mandible. 32 micro-implants with the same geometry but with four different surface treatments were implanted in the maxilla and mandible of eight patients. Each patient received four micro-implants, one of each type. Percentage of bone-to-implant contact analysis and histological evaluation was carried 3, 6 and 12 weeks after implantation. Furthermore, reverse removal torque tests were conducted 3 and 6 weeks after implantation to analyze functional bone attachment. Implant surfaces tested were: machined, grit-blasted, acid-etched, and grit-blasted with acid-etch. One-way ANOVA was performed using the multiple comparison Fisher's test to determine significance of observed differences among test groups. The level of significance was established at 5% (P < 0.05). Mean and standard deviations of the test groups were calculated. Surface roughness had a significant correlation with the evolution of bone regeneration. The surfaces with roughness Ra approximately 4 microim (grit-blasted and grit-blasted with acid-etch), showed rapid tissue colonization compared to machine and acid-etched surfaces. The results of reverse removal torque tests confirmed a significant correlation between surface roughness and functional bone attachment. Grit-blasted and grit-blasted with acid etched surfaces showed higher retention values compared to machine and acid-etched implants. This finding was supported by higher bone-to-implant contact observed for rougher surfaces (grit-blasted and grit-blasted with acid etching).

Comparison Of Flat-Knitted Structures Made Of Poly(P-Phenylene-2,6-Benzobisoxazole) And Para-Aramid Referring To Their Stab Resistance

NASA Astrophysics Data System (ADS)

Obermann, M.; Aumann, S.; Heimlich, F.; Weber, M. O.; Schwarz-Pfeiffer, A.

2016-07-01

In the field of protective gear, developers always aim for lighter and more flexible material in order to increase the wearing comfort. Suppliers now work on knitted garments in the sports-sector as well as in workwear and protective gear for policemen or security-agents. In a recent project different knitted structures made of a poly(p-phenylene-2,6-benzobisoxazole) (PBO)-multifilament were compared to their counterparts made of para-aramid. In focus of the comparison stood the stab-resistance linked to either the mass per unit area or the stitch density. The tested fabrics were produced on hand flat knitting machines as well as on electronical flat knitting machines of the type Stoll CMS 330TC4, in order to analyse fabrics with different tightness factor and machine gauges. The stab resistance of the different knitted fabrics was examined according to the standard of the Association of Test Laboratories for Bullet, Stab or Pike Resistant Materials and Construction Standards. The presentation includes the depiction of the results of the test series and their interpretation. Furthermore it will give an outlook on most suitable combinations of materials and structures to be used in protective gear.

Impact of the HEALTHY Study on Vending Machine Offerings in Middle Schools.

PubMed

Hartstein, Jill; Cullen, Karen W; Virus, Amy; El Ghormli, Laure; Volpe, Stella L; Staten, Myrlene A; Bridgman, Jessica C; Stadler, Diane D; Gillis, Bonnie; McCormick, Sarah B; Mobley, Connie C

2011-01-01

The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminate 100% fruit juice and beverages with added sugar. Six schools in each of seven cities (Houston, TX, San Antonio, TX, Irvine, CA, Portland, OR, Pittsburg, PA, Philadelphia, PA, and Chapel Hill, NC) were randomized into intervention (n=21 schools) or control (n=21 schools) groups, with three intervention and three control schools per city. All items in vending machine slots were tallied twice in the fall of 2006 for baseline data and twice at the end of the study, in 2009. The percentage of total slots for each food/beverage category was calculated and compared between intervention and control schools at the end of study, using the Pearson chi-square test statistic. At baseline, 15 intervention and 15 control schools had beverage and/or snack vending machines, compared with 11 intervention and 11 control schools at the end of the study. At the end of study, all of the intervention schools with beverage vending machines, but only one out of the nine control schools, met the beverage goal. The snack goal was met by all of the intervention schools and only one of the four control schools with snack vending machines. The HEALTHY study's vending machine beverage and snack goals were successfully achieved in intervention schools, reducing access to less healthy food items outside the school meals program. Although the effect of these changes on student diet, energy balance and growth is unknown, these results suggest that healthier options for snacks can successfully be offered in school vending machines.

Method and device for determining bond separation strength using induction heating

NASA Technical Reports Server (NTRS)

Coultrip, Robert H. (Inventor); Johnson, Samuel D. (Inventor); Copeland, Carl E. (Inventor); Phillips, W. Morris (Inventor); Fox, Robert L. (Inventor)

1994-01-01

An induction heating device includes an induction heating gun which includes a housing, a U-shaped pole piece having two spaced apart opposite ends defining a gap there between, the U-shaped pole piece being mounted in one end of the housing, and a tank circuit including an induction coil wrapped around the pole piece and a capacitor connected to the induction coil. A power source is connected to the tank circuit. A pull test machine is provided having a stationary chuck and a movable chuck, the two chucks holding two test pieces bonded together at a bond region. The heating gun is mounted on the pull test machine in close proximity to the bond region of the two test pieces, whereby when the tank circuit is energized, the two test pieces are heated by induction heating while a tension load is applied to the two test pieces by the pull test machine to determine separation strength of the bond region.

Adding Test Generation to the Teaching Machine

ERIC Educational Resources Information Center

Bruce-Lockhart, Michael; Norvell, Theodore; Crescenzi, Pierluigi

2009-01-01

We propose an extension of the Teaching Machine project, called Quiz Generator, that allows instructors to produce assessment quizzes in the field of algorithm and data structures quite easily. This extension makes use of visualization techniques and is based on new features of the Teaching Machine that allow third-party visualizers to be added as…

Preliminary Report on Free Flight Tests

NASA Technical Reports Server (NTRS)

Warner, E P; Norton, F H

1920-01-01

Results are presented for a series of tests made by the Advisory Committee's staff at Langley Field during the summer of 1919 with the objectives of determining the characteristics of airplanes in flight and the extent to which the actual characteristics differ from those predicted from tests on models in the wind tunnel, and of studying the balance of the machines and the forces which must be applied to the controls in order to maintain longitudinal equilibrium.

Design and test of a magnetic thrust bearing

NASA Technical Reports Server (NTRS)

Allaire, P. E.; Mikula, A.; Banerjee, B.; Lewis, D. W.; Imlach, J.

1993-01-01

A magnetic thrust bearing can be employed to take thrust loads in rotating machinery. The design and construction of a prototype magnetic thrust bearing for a high load per weight application is described. The theory for the bearing is developed. Fixtures were designed and the bearing was tested for load capacity using a universal testing machine. Various shims were employed to have known gap thicknesses. A comparison of the theory and measured results is presented.

Dental cutting behaviour of mica-based and apatite-based machinable glass-ceramics.

PubMed

Taira, M; Wakasa, K; Yamaki, M; Matsui, A

1990-09-01

Some recently developed industrial ceramics have excellent machinability properties. The objective of this study was to evaluate the dental cutting behaviour of two machinable glass-ceramics, mica-containing Macor-M and apatite- and diopside-containing Bioram-M, and to compare them with the cutting behaviour of a composite resin typodont tooth enamel and bovine enamel. Weight-load cutting tests were conducted, using a diamond point driven by an air-turbine handpiece, While the transverse load applied on the point was varied, the handpiece speed during cutting and the volume of removal upon cutting were measured. In general, an increase in the applied load caused a decrease in cutting speed and an increase in cutting volume. However, the intensity of this trend was found to differ between four workpieces. Cutting Macor-M resulted in the second-most reduced cutting speed and the maximum cutting volume. Cutting Bioram-M gave the least reduced cutting speed and the minimum cutting volume. It was suggested that two machinable glass-ceramics could be employed as typodont teeth. This study may also contribute to the development of new restorative dental ceramic materials, prepared by machining.

Availability of vending machines and school stores in California schools

PubMed Central

Liles, Sandy; Schmitz, Katharine E.; Kassem, Nada O.F; Irvin, Veronica L; Hovell, Melbourne F.

2015-01-01

Background This study examined the availability of foods sold in vending machines and school stores in US public and private schools, and associations of availability with students' food purchases and consumption. Methods Descriptive analyses, chi-square tests, and Spearman product-moment correlations were conducted on data collected from 521 students aged 8 to15 years recruited from orthodontic offices in California. Results Vending machines were more common in private schools than in public schools, while school stores were common in both private and public schools. The food items most commonly available in both vending machines and school stores in all schools were predominately foods of minimal nutritional value (FMNV). Participant report of availability of food items in vending machines and/or school stores was significantly correlated with: (1) participant purchase of each item from those sources, except for energy drinks, milk, fruits, and vegetables; and (2) participants' friends' consumption of items at lunch, for two categories of FMNV (candy, cookies, or cake; soda or sports drinks). Conclusions Despite the Child Nutrition and WIC reauthorization Act of 2004, FMNV were still available in schools, and may be contributing to unhealthy dietary choices and ultimately to health risks. PMID:26645420

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846

10 CFR 431.291 - Scope.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Refrigerated Bottled or Canned Beverage Vending Machines § 431.291 Scope. This subpart specifies test procedures for certain commercial refrigerated bottled or canned beverage vending machines, pursuant to part...

10 CFR 431.291 - Scope.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Refrigerated Bottled or Canned Beverage Vending Machines § 431.291 Scope. This subpart specifies test procedures for certain commercial refrigerated bottled or canned beverage vending machines, pursuant to part...

Applications of machine learning in cancer prediction and prognosis.

PubMed

Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Applications of Machine Learning in Cancer Prediction and Prognosis

PubMed Central

Cruz, Joseph A.; Wishart, David S.

2006-01-01

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15–25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression. PMID:19458758

Requirements-Based Conformance Testing of ARINC 653 Real-Time Operating Systems

NASA Astrophysics Data System (ADS)

Maksimov, Andrey

2010-08-01

Requirements-based testing is emphasized in avionics certification documents because this strategy has been found to be the most effective at revealing errors. This paper describes the unified requirements-based approach to the creation of conformance test suites for mission-critical systems. The approach uses formal machine-readable specifications of requirements and finite state machine model for test sequences generation on-the-fly. The paper also presents the test system for automated test generation for ARINC 653 services built on this approach. Possible application of the presented approach to various areas of avionics embedded systems testing is discussed.

Preparation of anti-adhesion surfaces on aluminium substrates of rubber plastic moulds using a coupling method of liquid plasma and electrochemical machining

NASA Astrophysics Data System (ADS)

Meng, Jianbing; Dong, Xiaojuan; Wei, Xiuting; Yin, Zhanmin

2014-03-01

Hard anti-adhesion surfaces, with low roughness and wear resistance, on aluminium substrates of rubber plastic moulds were fabricated via a new coupling method of liquid plasma and electrochemical machining. With the aid of liquid plasma thermal polishing and electrochemical anodic dissolution, micro/nano-scale binary structures were prepared as the base of the anti-adhesion surfaces. The anti-adhesion behaviours of the resulting aluminium surfaces were analysed by a surface roughness measuring instrument, a scanning electron microscope (SEM), a Fourier-transform infrared spectrophotometer (FTIR), an X-ray diffractometer (XRD), an optical contact angle meter, a digital Vickers micro-hardness (Hv) tester, and electronic universal testing. The results show that, after the liquid plasma and electrochemical machining, micro/nano-scale binary structures composed of micro-scale pits and nano-scale elongated boss structures were present on the sample surfaces. As a result, the anti-adhesion surfaces fabricated by the above coupling method have good anti-adhesion properties, better wear resistance and lower roughness.

In vivo and in vitro performance of a China-made hemodialysis machine: a multi-center prospective controlled study.

PubMed

Wang, Yong; Chen, Xiang-Mei; Cai, Guang-Yan; Li, Wen-Ge; Zhang, Ai-Hua; Hao, Li-Rong; Shi, Ming; Wang, Rong; Jiang, Hong-Li; Luo, Hui-Min; Zhang, Dong; Sun, Xue-Feng

2017-08-02

To evaluate the in vivo and in vitro performance of a China-made dialysis machine (SWS-4000). This was a multi-center prospective controlled study consisting of both long-term in vitro evaluations and cross-over in vivo tests in 132 patients. The China-made SWS-4000 dialysis machine was compared with a German-made dialysis machine (Fresenius 4008) with regard to Kt/V values, URR values, and dialysis-related adverse reactions in patients on maintenance hemodialysis, as well as the ultrafiltration rate, the concentration of electrolytes in the proportioned dialysate, the rate of heparin injection, the flow rate of the blood pump, and the rate of malfunction. The Kt/V and URR values at the 1st and 4th weeks of dialysis as well as the incidence of adverse effects did not differ between the two groups in cross-over in vivo tests (P > 0.05). There were no significant differences between the two groups in the error values of the ultrafiltration rate, the rate of heparin injection or the concentrations of electrolytes in the proportioned dialysate at different time points under different parameter settings. At weeks 2 and 24, with the flow rate of the blood pump set at 300 mL/min, the actual error of the SWS-4000 dialysis machine was significantly higher than that of the Fresenius 4008 dialysis machine (P < 0.05), but there was no significant difference at other time points or under other settings (P > 0.05). The malfunction rate was higher in the SWS-4000 group than in the Fresenius 4008 group (P < 0.05). The in vivo performance of the SWS-4000 dialysis machine is roughly comparable to that of the Fresenius 4008 dialysis machine; however, the malfunction rate of the former is higher than that of the latter in in vitro tests. The stability and long-term accuracy of the SWS-4000 dialysis machine remain to be improved.

Telescoping magnetic ball bar test gage

DOEpatents

Bryan, James B.

1984-01-01

A telescoping magnetic ball bar test gage for determining the accuracy of machine tools, including robots, and those measuring machines having non-disengageable servo drives which cannot be clutched out. Two gage balls (10, 12) are held and separated from one another by a telescoping fixture which allows them relative radial motional freedom but not relative lateral motional freedom. The telescoping fixture comprises a parallel reed flexure unit (14) and a rigid member (16, 18, 20, 22, 24). One gage ball (10) is secured by a magnetic socket knuckle assembly (34) which fixes its center with respect to the machine being tested. The other gage ball (12) is secured by another magnetic socket knuckle assembly (38) which is engaged or held by the machine in such manner that the center of that ball (12) is directed to execute a prescribed trajectory, all points of which are equidistant from the center of the fixed gage ball (10). As the moving ball (12) executes its trajectory, changes in the radial distance between the centers of the two balls (10, 12) caused by inaccuracies in the machine are determined or measured by a linear variable differential transformer (LVDT) assembly (50, 52, 54, 56, 58, 60) actuated by the parallel reed flexure unit (14). Measurements can be quickly and easily taken for multiple trajectories about several different fixed ball (10) locations, thereby determining the accuracy of the machine.

SU-E-T-88: Comprehensive Automated Daily QA for Hypo- Fractionated Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGuinness, C; Morin, O

2014-06-01

Purpose: The trend towards more SBRT treatments with fewer high dose fractions places increased importance on daily QA. Patient plan specific QA with 3%/3mm gamma analysis and daily output constancy checks may not be enough to guarantee the level of accuracy required for SBRT treatments. But increasing the already extensive amount of QA procedures that are required is a daunting proposition. We performed a feasibility study for more comprehensive automated daily QA that could improve the diagnostic capabilities of QA without increasing workload. Methods: We performed the study on a Siemens Artiste linear accelerator using the integrated flat panel EPID.more » We included square fields, a picket fence, overlap and representative IMRT fields to measure output, flatness, symmetry, beam center, and percent difference from the standard. We also imposed a set of machine errors: MLC leaf position, machine output, and beam steering to compare with the standard. Results: Daily output was consistent within +/− 1%. Change in steering current by 1.4% and 2.4% resulted in a 3.2% and 6.3% change in flatness. 1 and 2mm MLC leaf offset errors were visibly obvious in difference plots, but passed a 3%/3mm gamma analysis. A simple test of transmission in a picket fence can catch a leaf offset error of a single leaf by 1mm. The entire morning QA sequence is performed in less than 30 minutes and images are automatically analyzed. Conclusion: Automated QA procedures could be used to provide more comprehensive information about the machine with less time and human involvement. We have also shown that other simple tests are better able to catch MLC leaf position errors than a 3%/3mm gamma analysis commonly used for IMRT and modulated arc treatments. Finally, this information could be used to watch trends of the machine and predict problems before they lead to costly machine downtime.« less

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable

PubMed Central

Korjus, Kristjan; Hebart, Martin N.; Vicente, Raul

2016-01-01

Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with cross-validation. This is followed by application of the classifier with optimized parameters to a separate test set for estimating the classifier’s generalization performance. With limited data, this separation of test data creates a difficult trade-off between having more statistical power in estimating generalization performance versus choosing better parameters and fitting a better model. We propose a novel approach that we term “Cross-validation and cross-testing” improving this trade-off by re-using test data without biasing classifier performance. The novel approach is validated using simulated data and electrophysiological recordings in humans and rodents. The results demonstrate that the approach has a higher probability of discovering significant results than the standard approach of cross-validation and testing, while maintaining the nominal alpha level. In contrast to nested cross-validation, which is maximally efficient in re-using data, the proposed approach additionally maintains the interpretability of individual parameters. Taken together, we suggest an addition to currently used machine learning approaches which may be particularly useful in cases where model weights do not require interpretation, but parameters do. PMID:27564393

Delay test generation for synchronous sequential circuits

NASA Astrophysics Data System (ADS)

Devadas, Srinivas

1989-05-01

We address the problem of generating tests for delay faults in non-scan synchronous sequential circuits. Delay test generation for sequential circuits is a considerably more difficult problem than delay testing of combinational circuits and has received much less attention. In this paper, we present a method for generating test sequences to detect delay faults in sequential circuits using the stuck-at fault sequential test generator STALLION. The method is complete in that it will generate a delay test sequence for a targeted fault given sufficient CPU time, if such a sequence exists. We term faults for which no delay test sequence exists, under out test methodology, sequentially delay redundant. We describe means of eliminating sequential delay redundancies in logic circuits. We present a partial-scan methodology for enhancing the testability of difficult-to-test of untestable sequential circuits, wherein a small number of flip-flops are selected and made controllable/observable. The selection process guarantees the elimination of all sequential delay redundancies. We show that an intimate relationship exists between state assignment and delay testability of a sequential machine. We describe a state assignment algorithm for the synthesis of sequential machines with maximal delay fault testability. Preliminary experimental results using the test generation, partial-scan and synthesis algorithm are presented.

Redistribution of Welding Residual Stresses of Crack Tip Opening Displacement Specimen by Local Compression.

PubMed

Kim, Young-Gon; Song, Kuk-Hyun; Lee, Dong-Hoon; Joo, Sung-Min

2018-03-01

The demand of crack tip opening displacement (CTOD) test which evaluates fracture toughness of a cracked material is very important to ensure the stability of structure under severe service environment. The validity of the CTOD test result is judged using several criterions of the specification standards. One of them is the artificially generated fatigue pre-crack length inside the specimen. For acceptable CTOD test results, fatigue pre-crack must have a reasonable sharp crack front. The propagation of fatigue crack started from the tip of the machined notch, which might have propagated irregularly due to residual stress field. To overcome this problem, test codes suggest local compression method, reversed bending method and stepwise high-R ratio method to reduce the disparity of residual stress distribution inside the specimen. In this paper, the relation between the degree of local compression and distribution of welding residual stress has been analyzed by finite element analyses in order to determine the amount of effective local compression of the test piece. Analysis results show that initial welding residual stress is dramatically varied three-dimensionally while cutting, notch machining and local compressing due to the change of internal restraint force. From the simulation result, the authors find that there is an optimum amount of local compression to modify regularly for generating fatigue pre-crack propagation. In the case of 0.5% compressions of the model width is the most effective for uniforming residual stress distribution.

High speed turning of compacted graphite iron using controlled modulation

NASA Astrophysics Data System (ADS)

Stalbaum, Tyler Paul

Compacted graphite iron (CGI) is a material which emerged as a candidate material to replace cast iron (CI) in the automotive industry for engine block castings. Its thermal and mechanical properties allow the CGI-based engines to operate at higher cylinder pressures and temperatures than CI-based engines, allowing for lower fuel emissions and increased fuel economy. However, these same properties together with the thermomechanical wear mode in the CGI-CBN system result in poor machinability and inhibit CGI from seeing wide spread use in the automotive industry. In industry, machining of CGI is done only at low speeds, less than V = 200 m/min, to avoid encountering rapid wear of the cutting tools during cutting. Studies have suggested intermittent cutting operations such as milling suffer less severe tool wear than continuous cutting. Furthermore, evidence that a hard sulfide layer which forms over the cutting edge in machining CI at high speeds is absent during machining CGI is a major factor in the difference in machinability of these material systems. The present study addresses both of these issues by modification to the conventional machining process to allow intermittent continuous cutting. The application of controlled modulation superimposed onto the cutting process -- modulation-assisted machining (MAM) -- is shown to be quite effective in reducing the wear of cubic boron nitride (CBN) tools when machining CGI at high machining speeds (> 500 m/min). The tool life is at least 20 times greater than found in conventional machining of CGI. This significant reduction in wear is a consequence of reduction in the severity of the tool-work contact conditions with MAM. The propensity for thermochemical wear of CBN is thus reduced. It is found that higher cutting speed (> 700 m/min) leads to lower tool wear with MAM. The MAM configuration employing feed-direction modulation appears feasible for implementation at high speeds and offers a solution to this challenging class of industrial machining applications. This study's approach is by series of high speed turning tests of CGI with CBN tools, comparing conventional machining to MAM for similar parameters otherwise, by tool wear measurements and machinability observations.

Use of IT platform in determination of efficiency of mining machines

NASA Astrophysics Data System (ADS)

Brodny, Jarosław; Tutak, Magdalena

2018-01-01

Determination of effective use of mining devices has very significant meaning for mining enterprises. High costs of their purchase and tenancy cause that these enterprises tend to the best use of possessed technical potential. However, specifics of mining production causes that this process not always proceeds without interferences. Practical experiences show that determination of objective measure of utilization of machine in mining enterprise is not simple. In the paper a proposition for solution of this problem is presented. For this purpose an IT platform and overall efficiency model OEE were used. This model enables to evaluate the machine in a range of its availability performance and quality of product, and constitutes a quantitative tool of TPM strategy. Adapted to the specificity of mining branch the OEE model together with acquired data from industrial automatic system enabled to determine the partial indicators and overall efficiency of tested machines. Studies were performed for a set of machines directly use in coal exploitation process. They were: longwall-shearer and armoured face conveyor, and beam stage loader. Obtained results clearly indicate that degree of use of machines by mining enterprises are unsatisfactory. Use of IT platforms will significantly facilitate the process of registration, archiving and analytical processing of the acquired data. In the paper there is presented methodology of determination of partial indices and total OEE together with a practical example of its application for investigated machines set. Also IT platform was characterized for its construction, function and application.

Automatic Picking of Foraminifera: Design of the Foraminifera Image Recognition and Sorting Tool (FIRST) Prototype and Results of the Image Classification Scheme

NASA Astrophysics Data System (ADS)

de Garidel-Thoron, T.; Marchant, R.; Soto, E.; Gally, Y.; Beaufort, L.; Bolton, C. T.; Bouslama, M.; Licari, L.; Mazur, J. C.; Brutti, J. M.; Norsa, F.

2017-12-01

Foraminifera tests are the main proxy carriers for paleoceanographic reconstructions. Both geochemical and taxonomical studies require large numbers of tests to achieve statistical relevance. To date, the extraction of foraminifera from the sediment coarse fraction is still done by hand and thus time-consuming. Moreover, the recognition of morphotypes, ecologically relevant, requires some taxonomical skills not easily taught. The automatic recognition and extraction of foraminifera would largely help paleoceanographers to overcome these issues. Recent advances in automatic image classification using machine learning opens the way to automatic extraction of foraminifera. Here we detail progress on the design of an automatic picking machine as part of the FIRST project. The machine handles 30 pre-sieved samples (100-1000µm), separating them into individual particles (including foraminifera) and imaging each in pseudo-3D. The particles are classified and specimens of interest are sorted either for Individual Foraminifera Analyses (44 per slide) and/or for classical multiple analyses (8 morphological classes per slide, up to 1000 individuals per hole). The classification is based on machine learning using Convolutional Neural Networks (CNNs), similar to the approach used in the coccolithophorid imaging system SYRACO. To prove its feasibility, we built two training image datasets of modern planktonic foraminifera containing approximately 2000 and 5000 images each, corresponding to 15 & 25 morphological classes. Using a CNN with a residual topology (ResNet) we achieve over 95% correct classification for each dataset. We tested the network on 160,000 images from 45 depths of a sediment core from the Pacific ocean, for which we have human counts. The current algorithm is able to reproduce the downcore variability in both Globigerinoides ruber and the fragmentation index (r2 = 0.58 and 0.88 respectively). The FIRST prototype yields some promising results for high-resolution paleoceanographic studies and evolutionary studies.

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

NASA Astrophysics Data System (ADS)

Mehmood, Shahid; Shah, Masood; Pasha, Riffat Asim; Sultan, Amir

2017-10-01

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

Thermal Skin fabrication technology

NASA Technical Reports Server (NTRS)

Milam, T. B.

1972-01-01

Advanced fabrication techniques applicable to Thermal Skin structures were investigated, including: (1) chemical machining; (2) braze bonding; (3) diffusion bonding; and (4) electron beam welding. Materials investigated were nickel and nickel alloys. Sample Thermal Skin panels were manufactured using the advanced fabrication techniques studied and were structurally tested. Results of the program included: (1) development of improved chemical machining processes for nickel and several nickel alloys; (2) identification of design geometry limits; (3) identification of diffusion bonding requirements; (4) development of a unique diffusion bonding tool; (5) identification of electron beam welding limits; and (6) identification of structural properties of Thermal Skin material.

Solar prediction and intelligent machines

NASA Technical Reports Server (NTRS)

Johnson, Gordon G.

1987-01-01

The solar prediction program is aimed at reducing or eliminating the need to throughly understand the process previously developed and to still be able to produce a prediction. Substantial progress was made in identifying the procedures to be coded as well as testing some of the presently coded work. Another project involves work on developing ideas and software that should result in a machine capable of learning as well as carrying on an intelligent conversation over a wide range of topics. The underlying idea is to use primitive ideas and construct higher order ideas from these, which can then be easily related one to another.

Implementation of support vector machine for classification of speech marked hijaiyah letters based on Mel frequency cepstrum coefficient feature extraction

NASA Astrophysics Data System (ADS)

Adhi Pradana, Wisnu; Adiwijaya; Novia Wisesty, Untari

2018-03-01

Support Vector Machine or commonly called SVM is one method that can be used to process the classification of a data. SVM classifies data from 2 different classes with hyperplane. In this study, the system was built using SVM to develop Arabic Speech Recognition. In the development of the system, there are 2 kinds of speakers that have been tested that is dependent speakers and independent speakers. The results from this system is an accuracy of 85.32% for speaker dependent and 61.16% for independent speakers.

Electromagnetic inhibition of high frequency thermal bonding machine

NASA Astrophysics Data System (ADS)

He, Hong; Zhang, Qing-qing; Li, Hang; Zhang, Da-jian; Hou, Ming-feng; Zhu, Xian-wei

2011-12-01

The traditional high frequency thermal bonding machine had serious radiation problems at dominant frequency, two times frequency and three times frequency. Combining with its working principle, the problems of electromagnetic compatibility were studied, three following measures were adopted: 1.At the head part of the high frequency thermal bonding machine, resonant circuit attenuator was designed. The notch groove and reaction field can make the radiation being undermined or absorbed; 2.The electromagnetic radiation shielding was made for the high frequency copper power feeder; 3.Redesigned the high-frequency oscillator circuit to reduce the output of harmonic oscillator. The test results showed that these measures can make the output according with the national standard of electromagnetic compatibility (GB4824-2004-2A), the problems of electromagnetic radiation leakage can be solved, and good social, environmental and economic benefits would be brought.

A machine for the preliminary investigation of design features influencing the wear behaviour of knee prostheses.

PubMed

McGloughlin, T M; Murphy, D M; Kavanagh, A G

2004-01-01

Degradation of tibial inserts in vivo has been found to be multifactorial in nature, resulting in a complex interaction of many variables. A range of kinematic conditions occurs at the tibio-femoral interface, giving rise to various degrees of rolling and sliding at this interface. The movement of the tibio-femoral contact point may be an influential factor in the overall wear of ultra-high molecular weight polyethylene (UHMWPE) tibial components. As part of this study a three-station wear-test machine was designed and built to investigate the influence of rolling and sliding on the wear behaviour of specific design aspects of contemporary knee prostheses. Using the machine, it is possible to monitor the effect of various slide roll ratios on the performance of contemporary bearing designs from a geometrical and materials perspective.

Measuring large aspherics using a commercially available 3D-coordinate measuring machine

NASA Astrophysics Data System (ADS)

Otto, Wolfgang; Matthes, Axel; Schiehle, Heinz

2000-07-01

A CNC-controlled precision measuring machine is a very powerful tool in the optical shop not only to determine the surface figure, but also to qualify the radius of curvature and conic constant of aspherics. We used a commercially available 3D-coordinate measuring machine (CMM, ZEISS UPMC 850 CARAT S-ACC) to measure the shape of the GEMINI 1-m convex secondary mirrors at different lapping and polishing stages. To determine the measuring accuracy we compared the mechanical measurements with the results achieved by means of an interferometrical test setup. The data obtained in an early stage of polishing were evaluated in Zernike polynomials which show a very good agreement. The deviation concerning long wave rotational symmetrical errors was 20 nm rms, whereas the accuracy measuring of mid spatial frequency deviations was limited to about 100 nm rms.

The optional selection of micro-motion feature based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Li, Bo; Ren, Hongmei; Xiao, Zhi-he; Sheng, Jing

2017-11-01

Micro-motion form of target is multiple, different micro-motion forms are apt to be modulated, which makes it difficult for feature extraction and recognition. Aiming at feature extraction of cone-shaped objects with different micro-motion forms, this paper proposes the best selection method of micro-motion feature based on support vector machine. After the time-frequency distribution of radar echoes, comparing the time-frequency spectrum of objects with different micro-motion forms, features are extracted based on the differences between the instantaneous frequency variations of different micro-motions. According to the methods based on SVM (Support Vector Machine) features are extracted, then the best features are acquired. Finally, the result shows the method proposed in this paper is feasible under the test condition of certain signal-to-noise ratio(SNR).