Vibration syndrome in railway track maintenance workers.

PubMed

Virokannas, H; Anttonen, H; Niskanen, J

1995-01-01

An inquiry was sent to all railway maintenance workers in three railway districts in Finland and hand-arm vibration was measured on the handlebars of tools used by maintenance workers. The study group included 252 (82%) subjects, whose mean age was 41 years and who had worked in track maintenance for 14 years (SD 9). In Finland there are over 600 railway maintenance workers who use vibrating tools. The frequency-weighted acceleration of hand-arm vibration was calculated according to the ISO 5349 standard. Hand-held tamping machines had caused most of the vibration exposure, and aw4h was 10.6 m/s2 measured on the handlebar of tamping machine, but many workers also used other vibrating tools. The annual vibration level was 2.5 m/s2 when the use of all vibrating tools and the exposure time was taken into account. In the questionnaire the prevalence of vibration-induced white finger (VWF) was 14% in the entire material, and the prevalence of VWF increased significantly with the total duration of the maintenance work. In addition, 39% of the subjects had suffered numbness of the hands, and the prevalence of hand numbness also increased significantly with the total duration of maintenance work. According to the measurements of vibration and the prevalence of hand symptoms the present investigation indicates vibration syndrome as being related to railway track maintenance work. In the exposure group, where tamping machines mainly were used and exposure to other vibration was small, the prevalence of VWF was also significantly higher, but the prevalence of hand numbness insignificant compared with the control group. In this study vascular and nerve hand symptoms were considered to cause serious trouble in work by 4-11% of the maintenance workers.

Computer network defense system

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

Urias, Vincent; Stout, William M. S.; Loverro, Caleb

A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves networkmore » connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.« less

Mobile machine hazardous working zone warning system

DOEpatents

Schiffbauer, William H.; Ganoe, Carl W.

1999-01-01

A warning system is provided for a mobile working machine to alert an individual of a potentially dangerous condition in the event the individual strays into a hazardous working zone of the machine. The warning system includes a transmitter mounted on the machine and operable to generate a uniform magnetic field projecting beyond an outer periphery of the machine in defining a hazardous working zone around the machine during operation thereof. A receiver, carried by the individual and activated by the magnetic field, provides an alarm signal to alert the individual when he enters the hazardous working zone of the machine.

Mobile machine hazardous working zone warning system

DOEpatents

Schiffbauer, W.H.; Ganoe, C.W.

1999-08-17

A warning system is provided for a mobile working machine to alert an individual of a potentially dangerous condition in the event the individual strays into a hazardous working zone of the machine. The warning system includes a transmitter mounted on the machine and operable to generate a uniform magnetic field projecting beyond an outer periphery of the machine in defining a hazardous working zone around the machine during operation. A receiver, carried by the individual and activated by the magnetic field, provides an alarm signal to alert the individual when he enters the hazardous working zone of the machine. 3 figs.

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

PubMed

Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

2016-01-01

Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

Large robotized turning centers described

NASA Astrophysics Data System (ADS)

Kirsanov, V. V.; Tsarenko, V. I.

1985-09-01

The introduction of numerical control (NC) machine tools has made it possible to automate machining in series and small series production. The organization of automated production sections merged NC machine tools with automated transport systems. However, both the one and the other require the presence of an operative at the machine for low skilled operations. Industrial robots perform a number of auxiliary operations, such as equipment loading-unloading and control, changing cutting and auxiliary tools, controlling workpieces and parts, and cleaning of location surfaces. When used with a group of equipment they perform transfer operations between the machine tools. Industrial robots eliminate the need for workers to form auxiliary operations. This underscores the importance of developing robotized manufacturing centers providing for minimal human participation in production and creating conditions for two and three shift operation of equipment. Work carried out at several robotized manufacturing centers for series and small series production is described.

Comulang: towards a collaborative e-learning system that supports student group modeling.

PubMed

Troussas, Christos; Virvou, Maria; Alepis, Efthimios

2013-01-01

This paper describes an e-learning system that is expected to further enhance the educational process in computer-based tutoring systems by incorporating collaboration between students and work in groups. The resulting system is called "Comulang" while as a test bed for its effectiveness a multiple language learning system is used. Collaboration is supported by a user modeling module that is responsible for the initial creation of student clusters, where, as a next step, working groups of students are created. A machine learning clustering algorithm works towards group formatting, so that co-operations between students from different clusters are attained. One of the resulting system's basic aims is to provide efficient student groups whose limitations and capabilities are well balanced.

Machines, medication, modulation: circuits of dependency and self-care in Las Vegas.

PubMed

Schüll, Natasha Dow

2006-06-01

The intensive entertainment infrastructure of Las Vegas is overlaid with a robust therapeutic network for those who become addicted to its technologies. Although the objectives of gambling machines and addiction therapeutics are seemingly at odds--the first work to encourage play, the second to stop it--both gear their interventions around a model of the self as a continuum of behavioral potentials that can be externally modulated. For compulsive gamblers implicated in this circuit of modulation, pharmaceutical drugs that have been prescribed to dampen cravings for machine play sometimes function as intensifiers of its effects. Caught in an intractable play between technologies of harm and technologies of care, recovering gambling addicts are challenged to assemble a technical array through which they can maintain balance; health itself, for these individuals, becomes a state of managed dependency. This essay explores the shifting terms and changing stakes of subjectivity and health in the contemporary United States by way of ethnographic research on compulsive gamblers who live and work in Las Vegas. The analysis draws on interviews with gamblers as well as on observations in local self-help groups, directed group therapy sessions, and chat rooms of Internet recovery Web sites.

Gram staining with an automatic machine.

PubMed

Felek, S; Arslan, A

1999-01-01

This study was undertaken to develop a new Gram-staining machine controlled by a micro-controller and to investigate the quality of slides that were stained in the machine. The machine was designed and produced by the authors. It uses standard 220 V AC. Staining, washing, and drying periods are controlled by a timer built in the micro-controller. A software was made that contains a certain algorithm and time intervals for the staining mode. One-hundred and forty smears were prepared from Escherichia coli, Staphylococcus aureus, Neisseria sp., blood culture, trypticase soy broth, direct pus and sputum smears for comparison studies. Half of the slides in each group were stained with the machine, the other half by hand and then examined by four different microbiologists. Machine-stained slides had a higher clarity and less debris than the hand-stained slides (p < 0.05). In hand-stained slides, some Gram-positive organisms showed poor Gram-positive staining features (p < 0.05). In conclusion, we suggest that Gram staining with the automatic machine increases the staining quality and helps to decrease the work load in a busy diagnostic laboratory.

Organic synthesis: march of the machines.

PubMed

Ley, Steven V; Fitzpatrick, Daniel E; Ingham, Richard J; Myers, Rebecca M

2015-03-09

Organic synthesis is changing; in a world where budgets are constrained and the environmental impacts of practice are scrutinized, it is increasingly recognized that the efficient use of human resource is just as important as material use. New technologies and machines have found use as methods for transforming the way we work, addressing these issues encountered in research laboratories by enabling chemists to adopt a more holistic systems approach in their work. Modern developments in this area promote a multi-disciplinary approach and work is more efficient as a result. This Review focuses on the concepts, procedures and methods that have far-reaching implications in the chemistry world. Technologies have been grouped as topics of opportunity and their recent applications in innovative research laboratories are described. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Environmental and organizational factors associated with elbow/forearm and hand/wrist disorder among sewing machine operators of garment industry in Ethiopia.

PubMed

Kebede Deyyas, Wakjira; Tafese, Ararso

2014-01-01

Occupational health problems related to upper limp musculoskeletal disorders were the major issue among sewing machine operators of garment industries in Ethiopia. The aim of this study was to assess the prevalence and associated risk factors of work related elbow and wrist musculoskeletal disorders among sewing machine operators of garment industries in Galan City, Oromia Regional State. A cross-sectional study was conducted from April 1 to 30, 2012. A total of 422 study subjects were included in this study. Standard Nordic Musculoskeletal Questionnaire was used to collect detailed information on musculoskeletal symptom, sociodemographic data, and factors associated with the problems through face to face interview. From a total of 422 sewing machine operators included in the study 370 (87.7%) were females and 306 (72.5%) were in the age group of <30 years. The prevalence of self-reported work related elbow and wrist musculoskeletal disorders was 40% and 37.7%, respectively. In multivariate analysis, those who had >16 years of service were about five times more likely to develop elbow and wrist musculoskeletal disorders than those who had short (1-5 years) year of services [AOR = 4.7, 95% CI: 1.55-13.02], physical activities [AOR = 5.02, 95% CI: 1.57-16.00], and methods of payment [AOR = 2.01, 95% CI: 1.23-3.28], factors significantly associated with this disorders. Work related elbow and wrist musculoskeletal disorders were high among sewing machine operators in selected garment industries. Moreover, personal and environmental factors were identified as the potential risk factors related to elbow and wrist musculoskeletal disorders among the study group. Therefore, government and the owner of the garment industries should give special attention to prevent and control the problems through proper occupational health and safety policy implementation in the country.

Environmental and Organizational Factors Associated with Elbow/Forearm and Hand/Wrist Disorder among Sewing Machine Operators of Garment Industry in Ethiopia

PubMed Central

Kebede Deyyas, Wakjira; Tafese, Ararso

2014-01-01

Occupational health problems related to upper limp musculoskeletal disorders were the major issue among sewing machine operators of garment industries in Ethiopia. The aim of this study was to assess the prevalence and associated risk factors of work related elbow and wrist musculoskeletal disorders among sewing machine operators of garment industries in Galan City, Oromia Regional State. A cross-sectional study was conducted from April 1 to 30, 2012. A total of 422 study subjects were included in this study. Standard Nordic Musculoskeletal Questionnaire was used to collect detailed information on musculoskeletal symptom, sociodemographic data, and factors associated with the problems through face to face interview. From a total of 422 sewing machine operators included in the study 370 (87.7%) were females and 306 (72.5%) were in the age group of <30 years. The prevalence of self-reported work related elbow and wrist musculoskeletal disorders was 40% and 37.7%, respectively. In multivariate analysis, those who had >16 years of service were about five times more likely to develop elbow and wrist musculoskeletal disorders than those who had short (1–5 years) year of services [AOR = 4.7, 95% CI: 1.55–13.02], physical activities [AOR = 5.02, 95% CI: 1.57–16.00], and methods of payment [AOR = 2.01, 95% CI: 1.23–3.28], factors significantly associated with this disorders. Work related elbow and wrist musculoskeletal disorders were high among sewing machine operators in selected garment industries. Moreover, personal and environmental factors were identified as the potential risk factors related to elbow and wrist musculoskeletal disorders among the study group. Therefore, government and the owner of the garment industries should give special attention to prevent and control the problems through proper occupational health and safety policy implementation in the country. PMID:25298780

Safety of stationary grinding machines - impact resistance of work zone enclosures.

PubMed

Mewes, Detlef; Adler, Christian

2017-09-01

Guards on machine tools are intended to protect persons from being injured by parts ejected with high kinetic energy from the work zone of the machine. Stationary grinding machines are a typical example. Generally such machines are provided with abrasive product guards closely enveloping the grinding wheel. However, many machining tasks do not allow the use of abrasive product guards. In such cases, the work zone enclosure has to be dimensioned so that, in case of failure, grinding wheel fragments remain inside the machine's working zone. To obtain data for the dimensioning of work zone enclosures on stationary grinding machines, which must be operated without an abrasive product guard, burst tests were conducted with vitrified grinding wheels. The studies show that, contrary to widely held opinion, narrower grinding wheels can be more critical concerning the impact resistance than wider wheels although their fragment energy is smaller.

Noise induced hearing loss of forest workers in Turkey.

PubMed

Tunay, M; Melemez, K

2008-09-01

In this study, a total number of 114 workers who were in 3 different groups in terms of age and work underwent audiometric analysis. In order to determine whether there was a statistically significant difference between the hearing loss levels of the workers who were included in the study, variance analysis was applied with the help of the data obtained as a result of the evaluation. Correlation and regression analysis were applied in order to determine the relations between hearing loss and their age and their time of work. As a result of the variance analysis, statistically significant differences were found at 500, 2000 and 4000 Hz frequencies. The most specific difference was observed among chainsaw machine operators at 4000 Hz frequency, which was determined by the variance analysis. As a result of the correlation analysis, significant relations were found between time of work and hearing loss in 0.01 confidence level and between age and hearing loss in 0.05 confidence level. Forest workers using chainsaw machines should be informed, they should wear or use protective materials and less noising chainsaw machines should be used if possible and workers should undergo audiometric tests when they start work and once a year.

Size-selective pulmonary dose indices for metal-working fluid aerosols in machining and grinding operations in the automobile manufacturing industry.

PubMed

Woskie, S R; Smith, T J; Hallock, M F; Hammond, S K; Rosenthal, F; Eisen, E A; Kriebel, D; Greaves, I A

1994-01-01

The current metal-working fluid exposures at three locations that manufacture automotive parts were assessed in conjunction with epidemiological studies of the mortality and respiratory morbidity experiences of workers at these plants. A rationale is presented for selecting and characterizing epidemiologic exposure groups in this environment. More than 475 full-shift personal aerosol samples were taken using a two-stage personal cascade impactor with median size cut-offs of 9.8 microns and 3.5 microns, plus a backup filter. For a sample of 403 workers exposed to aerosols of machining or grinding fluids, the mean total exposure was 706 micrograms/m3 (standard error (SE) = 21 micrograms/m3). Among 72 assemblers unexposed to machining fluids, the mean total exposure was 187 +/- 10 (SE) micrograms/m3. An analysis of variance model identified factors significantly associated with exposure level and permitted estimates of exposure for workers in the unsampled machine type/metal-working fluid groups. Comparison of the results obtained from personal impactor samples with predictions from an aerosol-deposition model for the human respiratory tract showed high correlation. However, the amount collected on the impactor stage underestimates extrathoracic deposition and overestimates tracheobronchial and alveolar deposition, as calculated by the deposition model. When both the impactor concentration and the deposition-model concentration were used to estimate cumulative thoracic concentrations for the worklives of a subset of auto workers, there was no significant difference in the rank order of the subjects' cumulative concentration. However, the cumulative impactor concentration values were significantly higher than the cumulative deposition-model concentration values for the subjects.

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study

PubMed Central

Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients. PMID:29904574

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study.

PubMed

Tacchella, Andrea; Romano, Silvia; Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients.

Evaluation of machinability and flexural strength of a novel dental machinable glass-ceramic.

PubMed

Qin, Feng; Zheng, Shucan; Luo, Zufeng; Li, Yong; Guo, Ling; Zhao, Yunfeng; Fu, Qiang

2009-10-01

To evaluate the machinability and flexural strength of a novel dental machinable glass-ceramic (named PMC), and to compare the machinability property with that of Vita Mark II and human enamel. The raw batch materials were selected and mixed. Four groups of novel glass-ceramics were formed at different nucleation temperatures, and were assigned to Group 1, Group 2, Group 3 and Group 4. The machinability of the four groups of novel glass-ceramics, Vita Mark II ceramic and freshly extracted human premolars were compared by means of drilling depth measurement. A three-point bending test was used to measure the flexural strength of the novel glass-ceramics. The crystalline phases of the group with the best machinability were identified by X-ray diffraction. In terms of the drilling depth, Group 2 of the novel glass-ceramics proves to have the largest drilling depth. There was no statistical difference among Group 1, Group 4 and the natural teeth. The drilling depth of Vita MK II was statistically less than that of Group 1, Group 4 and the natural teeth. Group 3 had the least drilling depth. In respect of the flexural strength, Group 2 exhibited the maximum flexural strength; Group 1 was statistically weaker than Group 2; there was no statistical difference between Group 3 and Group 4, and they were the weakest materials. XRD of Group 2 ceramic showed that a new type of dental machinable glass-ceramic containing calcium-mica had been developed by the present study and was named PMC. PMC is promising for application as a dental machinable ceramic due to its good machinability and relatively high strength.

The methodic of calculation for the need of basic construction machines on construction site when developing organizational and technological documentation

NASA Astrophysics Data System (ADS)

Zhadanovsky, Boris; Sinenko, Sergey

2018-03-01

Economic indicators of construction work, particularly in high-rise construction, are directly related to the choice of optimal number of machines. The shortage of machinery makes it impossible to complete the construction & installation work on scheduled time. Rates of performance of construction & installation works and labor productivity during high-rise construction largely depend on the degree of provision of construction project with machines (level of work mechanization). During calculation of the need for machines in construction projects, it is necessary to ensure that work is completed on scheduled time, increased level of complex mechanization, increased productivity and reduction of manual work, and improved usage and maintenance of machine fleet. The selection of machines and determination of their numbers should be carried out by using formulas presented in this work.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

All about Simple Machines. Physical Science for Children[TM]. Schlessinger Science Library. [Videotape].

ERIC Educational Resources Information Center

2000

All kids know the word "work." But they probably don't understand that work happens whenever a force is used to move something--whether it's lifting a heavy object or playing on a see-saw. All About Simple Machines introduces kids to the concepts of forces, work and how machines are used to make work easier. Six simple machines are…

Understanding of anesthesia machine function is enhanced with a transparent reality simulation.

PubMed

Fischler, Ira S; Kaschub, Cynthia E; Lizdas, David E; Lampotang, Samsun

2008-01-01

Photorealistic simulations may provide efficient transfer of certain skills to the real system, but by being opaque may fail to encourage deeper learning of the structure and function of the system. Schematic simulations that are more abstract, with less visual fidelity but make system structure and function transparent, may enhance deeper learning and optimize retention and transfer of learning. We compared learning effectiveness of these 2 modes of externalizing the output of a common simulation engine (the Virtual Anesthesia Machine, VAM) that models machine function and dynamics and responds in real time to user interventions such as changes in gas flow or ventilation. Undergraduate students (n = 39) and medical students (n = 35) were given a single, 1-hour guided learning session with either a Transparent or an Opaque version of the VAM simulation. The following day, the learners' knowledge of machine components, function, and dynamics was tested. The Transparent-VAM groups scored higher than the Opaque-VAM groups on a set of multiple-choice questions concerning conceptual knowledge about anesthesia machines (P = 0.009), provided better and more complete explanations of component function (P = 0.003), and were more accurate in remembering and inferring cause-and-effect dynamics of the machine and relations among components (P = 0.003). Although the medical students outperformed undergraduates on all measures, a similar pattern of benefits for the Transparent VAM was observed for these 2 groups. Schematic simulations that transparently allow learners to visualize, and explore, underlying system dynamics and relations among components may provide a more effective mental model for certain systems. This may lead to a deeper understanding of how the system works, and therefore, we believe, how to detect and respond to potentially adverse situations.

Work stress of women in sewing machine operation.

PubMed

Nag, A; Desai, H; Nag, P K

1992-06-01

The study examined the work stresses of 107 women who were engaged in sewing machine operation in small garment manufacturing units. Of the three types of sewing machines (motor-operated, full and half shuttle foot-operated), 74% of the machines were foot-operated, where throttle action of the lower limb is required to move the shuttle of the machine. The motor-operated machines were faster than the foot-operated machines. The short cycle sewing work involves repetitive action of hand and feet. The women had to maintain a constant seated position on a stool without backrest and the body inclined forward. Long-term sewing work had a cumulative load on the musculo-skeletal structures, including the vertebral column and reflected in the form of high prevalence of discomfort and pain in different body parts. About 68% of the women complained of back pain, among whom 35% reported a persistent low back pain. Common sewing work accident is piercing of the needle through the fingers, particularly the right forefingers. Unsatisfactory man-machine incompatibility, work posture and fatigue, improper coordination of eye, leg and hand are the major problems of the operators. The design mis-match of the work place may be significantly improved by taking women's anthropometric dimensions in modifying the workplace, i.e. the seat surface, seat height, work height, backrest, etc.

Methodology for creating dedicated machine and algorithm on sunflower counting

NASA Astrophysics Data System (ADS)

Muracciole, Vincent; Plainchault, Patrick; Mannino, Maria-Rosaria; Bertrand, Dominique; Vigouroux, Bertrand

2007-09-01

In order to sell grain lots in European countries, seed industries need a government certification. This certification requests purity testing, seed counting in order to quantify specified seed species and other impurities in lots, and germination testing. These analyses are carried out within the framework of international trade according to the methods of the International Seed Testing Association. Presently these different analyses are still achieved manually by skilled operators. Previous works have already shown that seeds can be characterized by around 110 visual features (morphology, colour, texture), and thus have presented several identification algorithms. Until now, most of the works in this domain are computer based. The approach presented in this article is based on the design of dedicated electronic vision machine aimed to identify and sort seeds. This machine is composed of a FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processor) and a PC bearing the GUI (Human Machine Interface) of the system. Its operation relies on the stroboscopic image acquisition of a seed falling in front of a camera. A first machine was designed according to this approach, in order to simulate all the vision chain (image acquisition, feature extraction, identification) under the Matlab environment. In order to perform this task into dedicated hardware, all these algorithms were developed without the use of the Matlab toolbox. The objective of this article is to present a design methodology for a special purpose identification algorithm based on distance between groups into dedicated hardware machine for seed counting.

Surface dimpling on rotating work piece using rotation cutting tool

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

Bhapkar, Rohit Arun; Larsen, Eric Richard

A combined method of machining and applying a surface texture to a work piece and a tool assembly that is capable of machining and applying a surface texture to a work piece are disclosed. The disclosed method includes machining portions of an outer or inner surface of a work piece. The method also includes rotating the work piece in front of a rotating cutting tool and engaging the outer surface of the work piece with the rotating cutting tool to cut dimples in the outer surface of the work piece. The disclosed tool assembly includes a rotating cutting tool coupledmore » to an end of a rotational machining device, such as a lathe. The same tool assembly can be used to both machine the work piece and apply a surface texture to the work piece without unloading the work piece from the tool assembly.« less

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Manufacturing engineering: Principles for optimization

NASA Astrophysics Data System (ADS)

Koenig, Daniel T.

Various subjects in the area of manufacturing engineering are addressed. The topics considered include: manufacturing engineering organization concepts and management techniques, factory capacity and loading techniques, capital equipment programs, machine tool and equipment selection and implementation, producibility engineering, methods, planning and work management, and process control engineering in job shops. Also discussed are: maintenance engineering, numerical control of machine tools, fundamentals of computer-aided design/computer-aided manufacture, computer-aided process planning and data collection, group technology basis for plant layout, environmental control and safety, and the Integrated Productivity Improvement Program.

A general-purpose machine learning framework for predicting properties of inorganic materials

DOE PAGES

Ward, Logan; Agrawal, Ankit; Choudhary, Alok; ...

2016-08-26

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method formore » partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.« less

A general-purpose machine learning framework for predicting properties of inorganic materials

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

Ward, Logan; Agrawal, Ankit; Choudhary, Alok

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method formore » partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.« less

The risk of occupational injury increased according to severity of noise exposure after controlling for occupational environment status in Korea.

PubMed

Yoon, Jin-Ha; Roh, Jaehoon; Kim, Chi-Nyon; Won, Jong-Uk

2016-01-01

The aim of this study was to examine the relationship between noise exposure and risk of occupational injury. Korean National Health and Nutrition Examination Survey was used for the current study. Self-report questionnaires were used to investigate occupational injury and exposure to noise, chemicals, and machines and equipments. In separate analyses for occupation and occupational hazard, the proportion of occupational injuries increased according to severity of noise exposure (all P < 0.05). Compared to the non-exposure group, the respective odds ratio (95% confidence intervals) for occupational injury was 1.39 (1.07-1.80) and 1.67 (1.13-2.46) in the mild and severe noise exposure groups, after controlling for age, gender, sleep hours, work schedule (shift work), and exposure status to hazardous chemicals and hazardous machines and equipments. The current study highlights the association between noise exposure and risk of occupational injury. Furthermore, risk of occupational injury increased according to severity of noise exposure.

New Learning Method of a Lecture of ‘Machine Fabrication’ by Self-study with Investigation and Presentation Incorporated

NASA Astrophysics Data System (ADS)

Kasuga, Yukio

A new teaching method was developed in learning ‘machine fabrication’ for the undergraduate students. This consists of a few times of lectures, grouping, decision of industrial products which each group wants to investigate, investigation work by library books and internet, arrangement of data containing characteristics of the products, employed materials and processing methods, presentation, discussions and revision followed by another presentation. This new method is derived from one of the Finland‧s way of primary school education. Their way of education is believed to have boosted up to the top ranking in PISA tests by OECD. After starting the new way of learning, students have fresh impressions on this lesson, especially for self-study, the way of investigation, collaborate work and presentation. Also, after four years of implementation, some improvements have been made including less use of internet, and determination of products and fabricating methods in advance which should be investigated. By this, students‧ lecture assessment shows further encouraging results.

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...

Industrial machine systems risk assessment: a critical review of concepts and methods.

PubMed

Etherton, John R

2007-02-01

Reducing the risk of work-related death and injury to machine operators and maintenance personnel poses a continuing occupational safety challenge. The risk of injury from machinery in U.S. workplaces is high. Between 1992 and 2001, there were, on average, 520 fatalities per year involving machines and, on average, 3.8 cases per 10,000 workers of nonfatal caught-in-running-machine injuries involving lost workdays. A U.S. task group recently developed a technical reference guideline, ANSI B11 TR3, "A Guide to Estimate, Evaluate, & Reduce Risks Associated with Machine Tools," that is intended to bring machine tool risk assessment practice in the United States up to or above the level now required by the international standard, ISO 14121. The ANSI guideline emphasizes identifying tasks and hazards not previously considered, particularly those associated with maintenance; and it further emphasizes teamwork among line workers, engineers, and safety professionals. The value of this critical review of concepts and methods resides in (1) its linking current risk theory to machine system risk assessment and (2) its exploration of how various risk estimation tools translate into risk-informed decisions on industrial machine system design and use. The review was undertaken to set the stage for a field evaluation study on machine risk assessment among users of the ANSI B11 TR3 method.

Simple Machines. Physical Science in Action[TM]. Schlessinger Science Library. [Videotape].

ERIC Educational Resources Information Center

2000

In today's world, kids are aware that there are machines all around them. What they may not realize is that the function of all machines is to make work easier in some way. Simple Machines uses engaging visuals and colorful graphics to explain the concept of work and how humans use certain basic tools to help get work done. Students will learn…

Mathematical model of an air-filled alpha stirling refrigerator

NASA Astrophysics Data System (ADS)

McFarlane, Patrick; Semperlotti, Fabio; Sen, Mihir

2013-10-01

This work develops a mathematical model for an alpha Stirling refrigerator with air as the working fluid and will be useful in optimizing the mechanical design of these machines. Two pistons cyclically compress and expand air while moving sinusoidally in separate chambers connected by a regenerator, thus creating a temperature difference across the system. A complete non-linear mathematical model of the machine, including air thermodynamics, and heat transfer from the walls, as well as heat transfer and fluid resistance in the regenerator, is developed. Non-dimensional groups are derived, and the mathematical model is numerically solved. The heat transfer and work are found for both chambers, and the coefficient of performance of each chamber is calculated. Important design parameters are varied and their effect on refrigerator performance determined. This sensitivity analysis, which shows what the significant parameters are, is a useful tool for the design of practical Stirling refrigeration systems.

Translations on Eastern Europe Political, Sociological, and Military Affairs No. 1467

DTIC Science & Technology

1977-11-01

and still does. *A group of a few teenagers, not a large group, has been working there for many years. The group was engaged in photography ...inclucating the Pupils’ Code? It may be that errors existed back at the very assumption of this didactic affair, which, it is true, is not producing...textile industry; with Yugoslavia--in the production of locomotive types, of lorries, of machine- tools , of medium tonnage cargoes. The Romanian-West

Analysis in Motion Initiative – Human Machine Intelligence

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

Blaha, Leslie

As computers and machines become more pervasive in our everyday lives, we are looking for ways for humans and machines to work more intelligently together. How can we help machines understand their users so the team can do smarter things together? The Analysis in Motion Initiative is advancing the science of human machine intelligence — creating human-machine teams that work better together to make correct, useful, and timely interpretations of data.

Catalysis of heat-to-work conversion in quantum machines

PubMed Central

Ghosh, A.; Latune, C. L.; Davidovich, L.; Kurizki, G.

2017-01-01

We propose a hitherto-unexplored concept in quantum thermodynamics: catalysis of heat-to-work conversion by quantum nonlinear pumping of the piston mode which extracts work from the machine. This concept is analogous to chemical reaction catalysis: Small energy investment by the catalyst (pump) may yield a large increase in heat-to-work conversion. Since it is powered by thermal baths, the catalyzed machine adheres to the Carnot bound, but may strongly enhance its efficiency and power compared with its noncatalyzed counterparts. This enhancement stems from the increased ability of the squeezed piston to store work. Remarkably, the fraction of piston energy that is convertible into work may then approach unity. The present machine and its counterparts powered by squeezed baths share a common feature: Neither is a genuine heat engine. However, a squeezed pump that catalyzes heat-to-work conversion by small investment of work is much more advantageous than a squeezed bath that simply transduces part of the work invested in its squeezing into work performed by the machine. PMID:29087326

Catalysis of heat-to-work conversion in quantum machines

NASA Astrophysics Data System (ADS)

Ghosh, A.; Latune, C. L.; Davidovich, L.; Kurizki, G.

2017-11-01

We propose a hitherto-unexplored concept in quantum thermodynamics: catalysis of heat-to-work conversion by quantum nonlinear pumping of the piston mode which extracts work from the machine. This concept is analogous to chemical reaction catalysis: Small energy investment by the catalyst (pump) may yield a large increase in heat-to-work conversion. Since it is powered by thermal baths, the catalyzed machine adheres to the Carnot bound, but may strongly enhance its efficiency and power compared with its noncatalyzed counterparts. This enhancement stems from the increased ability of the squeezed piston to store work. Remarkably, the fraction of piston energy that is convertible into work may then approach unity. The present machine and its counterparts powered by squeezed baths share a common feature: Neither is a genuine heat engine. However, a squeezed pump that catalyzes heat-to-work conversion by small investment of work is much more advantageous than a squeezed bath that simply transduces part of the work invested in its squeezing into work performed by the machine.

Catalysis of heat-to-work conversion in quantum machines.

PubMed

Ghosh, A; Latune, C L; Davidovich, L; Kurizki, G

2017-11-14

We propose a hitherto-unexplored concept in quantum thermodynamics: catalysis of heat-to-work conversion by quantum nonlinear pumping of the piston mode which extracts work from the machine. This concept is analogous to chemical reaction catalysis: Small energy investment by the catalyst (pump) may yield a large increase in heat-to-work conversion. Since it is powered by thermal baths, the catalyzed machine adheres to the Carnot bound, but may strongly enhance its efficiency and power compared with its noncatalyzed counterparts. This enhancement stems from the increased ability of the squeezed piston to store work. Remarkably, the fraction of piston energy that is convertible into work may then approach unity. The present machine and its counterparts powered by squeezed baths share a common feature: Neither is a genuine heat engine. However, a squeezed pump that catalyzes heat-to-work conversion by small investment of work is much more advantageous than a squeezed bath that simply transduces part of the work invested in its squeezing into work performed by the machine.

Exascale Hardware Architectures Working Group

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

Hemmert, S; Ang, J; Chiang, P

2011-03-15

The ASC Exascale Hardware Architecture working group is challenged to provide input on the following areas impacting the future use and usability of potential exascale computer systems: processor, memory, and interconnect architectures, as well as the power and resilience of these systems. Going forward, there are many challenging issues that will need to be addressed. First, power constraints in processor technologies will lead to steady increases in parallelism within a socket. Additionally, all cores may not be fully independent nor fully general purpose. Second, there is a clear trend toward less balanced machines, in terms of compute capability compared tomore » memory and interconnect performance. In order to mitigate the memory issues, memory technologies will introduce 3D stacking, eventually moving on-socket and likely on-die, providing greatly increased bandwidth but unfortunately also likely providing smaller memory capacity per core. Off-socket memory, possibly in the form of non-volatile memory, will create a complex memory hierarchy. Third, communication energy will dominate the energy required to compute, such that interconnect power and bandwidth will have a significant impact. All of the above changes are driven by the need for greatly increased energy efficiency, as current technology will prove unsuitable for exascale, due to unsustainable power requirements of such a system. These changes will have the most significant impact on programming models and algorithms, but they will be felt across all layers of the machine. There is clear need to engage all ASC working groups in planning for how to deal with technological changes of this magnitude. The primary function of the Hardware Architecture Working Group is to facilitate codesign with hardware vendors to ensure future exascale platforms are capable of efficiently supporting the ASC applications, which in turn need to meet the mission needs of the NNSA Stockpile Stewardship Program. This issue is relatively immediate, as there is only a small window of opportunity to influence hardware design for 2018 machines. Given the short timeline a firm co-design methodology with vendors is of prime importance.« less

[Anxiety, life style and obstetric history of women working in a high-fashion clothing industry].

PubMed

Kouri, S; Di Giampaolo, L; Toto, E; Cerrone, T; Boscolo, P

2001-01-01

Women with a mean age of 38 years (range 20-62) were employed in an industry producing clothes of high fashion. A part of them (n = 210) performed their activities with hands and others (n = 90) utilising machines with more repetitive procedures. All the recruited women answered to a questionnaire including the state-trait anxiety inventory (STAI) test, working activities, lifestyle and obstetric history. There was no relation between obstetric history and working activities. The group of women with age ranging from 35 to 42 years showed the score of the STAI higher than that of the younger women and slightly lower than that of the subjects with older age. This may depend on the "healthy worker effect" in the old subjects able to continue their job. The scores of the STAI were also slightly influenced by the repetitive tasks utilising machines. On the whole, the working activity of women had beneficial effect on their role inside the family and in the social life.

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.

Health Informatics via Machine Learning for the Clinical Management of Patients.

PubMed

Clifton, D A; Niehaus, K E; Charlton, P; Colopy, G W

2015-08-13

To review how health informatics systems based on machine learning methods have impacted the clinical management of patients, by affecting clinical practice. We reviewed literature from 2010-2015 from databases such as Pubmed, IEEE xplore, and INSPEC, in which methods based on machine learning are likely to be reported. We bring together a broad body of literature, aiming to identify those leading examples of health informatics that have advanced the methodology of machine learning. While individual methods may have further examples that might be added, we have chosen some of the most representative, informative exemplars in each case. Our survey highlights that, while much research is taking place in this high-profile field, examples of those that affect the clinical management of patients are seldom found. We show that substantial progress is being made in terms of methodology, often by data scientists working in close collaboration with clinical groups. Health informatics systems based on machine learning are in their infancy and the translation of such systems into clinical management has yet to be performed at scale.

Organizational citizenship behavior and the quantity and quality of work group performance.

PubMed

Podsakoff, P M; Ahearne, M; MacKenzie, S B

1997-04-01

Despite the widespread interest in the topic of organizational citizenship behaviors (OCBs), little empirical research has tested the fundamental assumption that these forms of behavior improve the effectiveness of work groups or organizations in which they are exhibited. In the present study, the effects of OCBs on the quantity and quality of the performance of 218 people working in 40 machine crews in a paper mill located in the Northeastern United States were examined. The results indicate that helping behavior and sportsmanship had significant effects on performance quantity and that helping behavior had a significant impact on performance quality. However, civic virtue had no effect on either performance measure.

A method to identify the main mode of machine tool under operating conditions

NASA Astrophysics Data System (ADS)

Wang, Daming; Pan, Yabing

2017-04-01

The identification of the modal parameters under experimental conditions is the most common procedure when solving the problem of machine tool structure vibration. However, the influence of each mode on the machine tool vibration in real working conditions remains unknown. In fact, the contributions each mode makes to the machine tool vibration during machining process are different. In this article, an active excitation modal analysis is applied to identify the modal parameters in operational condition, and the Operating Deflection Shapes (ODS) in frequencies of high level vibration that affect the quality of machining in real working conditions are obtained. Then, the ODS is decomposed by the mode shapes which are identified in operational conditions. So, the contributions each mode makes to machine tool vibration during machining process are got by decomposition coefficients. From the previous steps, we can find out the main modes which effect the machine tool more significantly in working conditions. This method was also verified to be effective by experiments.

14. PIPE MACHINE, WORK BENCH, SCALE, RADIAL DRILL AND STOVE ...

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

14. PIPE MACHINE, WORK BENCH, SCALE, RADIAL DRILL AND STOVE (L TO R) LOOKING WEST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

Diversity in the association between occupation and lung cancer among black and white men.

PubMed

Swanson, G M; Lin, C S; Burns, P B

1993-01-01

A population-based case comparison study of incident lung cancer and occupational risk factors was conducted in the tricounty Detroit metropolitan area. Nearly 6000 lung cancer cases and a comparison group of 3600 colon cancer cases were interviewed. This report includes 3792 white and black male lung cancer cases and 1966 black and white colon cancer referents. Cigarette smoking, age at diagnosis, and lifetime work history were assessed to determine the relationship between length of employment in specific occupations and industries and lung cancer. Diverse patterns of association between work history and lung cancer were observed for black and white men. Significant associations were seen between lung cancer and increasing length of employment in the following occupations: for white men, concrete and terrazzo finishers, grinding machine operators, heat treating machine operators, miscellaneous machine operators, truck drivers, driver sales, and laborers; for black men, farm workers, automobile mechanics, painting machine operators, furnace operators, and garbage collectors; for both black and white men, farmers, slicing and cutting machine operators, and garbage collectors. Distinct patterns for black and white men also were observed for length of employment by industry. This study clearly demonstrates the need to include black men in studies of occupational cancer etiology and to evaluate black and white men separately. It also indicates the necessity for cigarette smoking history to accurately assess workplace cancer risks. We propose guidelines for incorporating the use of biomarkers into further studies of occupational cancer epidemiology.

Machine-learned analysis of the association of next-generation sequencing-based human TRPV1 and TRPA1 genotypes with the sensitivity to heat stimuli and topically applied capsaicin.

PubMed

Kringel, Dario; Geisslinger, Gerd; Resch, Eduard; Oertel, Bruno G; Thrun, Michael C; Heinemann, Sarah; Lötsch, Jörn

2018-03-27

Heat pain and its modulation by capsaicin varies among subjects in experimental and clinical settings. A plausible cause is a genetic component, of which TRPV1 ion channels, by their response to both heat and capsaicin, are primary candidates. However, TRPA1 channels can heterodimerize with TRPV1 channels and carry genetic variants reported to modulate heat pain sensitivity. To address the role of these candidate genes in capsaicin-induced hypersensitization to heat, pain thresholds acquired before and after topical application of capsaicin and TRPA1/TRPV1 exomic sequences derived by next-generation sequencing were assessed in n = 75 healthy volunteers and the genetic information comprised 278 loci. Gaussian mixture modeling indicated 2 phenotype groups with high or low capsaicin-induced hypersensitization to heat. Unsupervised machine learning implemented as swarm-based clustering hinted at differences in the genetic pattern between these phenotype groups. Several methods of supervised machine learning implemented as random forests, adaptive boosting, k-nearest neighbors, naive Bayes, support vector machines, and for comparison, binary logistic regression predicted the phenotype group association consistently better when based on the observed genotypes than when using a random permutation of the exomic sequences. Of note, TRPA1 variants were more important for correct phenotype group association than TRPV1 variants. This indicates a role of the TRPA1 and TRPV1 next-generation sequencing-based genetic pattern in the modulation of the individual response to heat-related pain phenotypes. When considering earlier evidence that topical capsaicin can induce neuropathy-like quantitative sensory testing patterns in healthy subjects, implications for future analgesic treatments with transient receptor potential inhibitors arise.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

PubMed

Frohlich, Holger; Claes, Kasper; De Wolf, Catherine; Van Damme, Xavier; Michel, Anne

2018-05-01

Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Noldus Catwalk system, in which footprints are automatically captured and stored. We present a - to our knowledge - first machine learning based approach for the Catwalk system, which comprises a step decomposition, definition and extraction of meaningful features, multivariate step sequence alignment, feature selection, and training of different classifiers (gradient boosting machine, random forest, and elastic net). Using animal-wise leave-one-out cross validation we demonstrate that with our method we can reliable separate movement patterns of a putative Parkinson's disease animal model and several control groups. Furthermore, we show that we can predict the time point after and the type of different brain lesions and can even forecast the brain region, where the intervention was applied. We provide an in-depth analysis of the features involved into our classifiers via statistical techniques for model interpretation. A machine learning method for automated analysis of data from the Noldus Catwalk system was established. Our works shows the ability of machine learning to discriminate pharmacologically relevant animal groups based on their walking behavior in a multivariate manner. Further interesting aspects of the approach include the ability to learn from past experiments, improve with more data arriving and to make predictions for single animals in future studies.

Progress in machine consciousness.

PubMed

Gamez, David

2008-09-01

This paper is a review of the work that has been carried out on machine consciousness. A clear overview of this diverse field is achieved by breaking machine consciousness down into four different areas, which are used to understand its aims, discuss its relationship with other subjects and outline the work that has been carried out so far. The criticisms that have been made against machine consciousness are also covered, along with its potential benefits, and the work that has been done on analysing systems for signs of consciousness. Some of the social and ethical issues raised by machine consciousness are examined at the end of the paper.

The Risk of Occupational Injury Increased According to Severity of Noise Exposure After Controlling for Occupational Environment Status in Korea

PubMed Central

Yoon, Jin-Ha; Roh, Jaehoon; Kim, Chi-Nyon; Won, Jong-Uk

2016-01-01

Objectives: The aim of this study was to examine the relationship between noise exposure and risk of occupational injury. Materials and Methods: Korean National Health and Nutrition Examination Survey was used for the current study. Self-report questionnaires were used to investigate occupational injury and exposure to noise, chemicals, and machines and equipments. Results: In separate analyses for occupation and occupational hazard, the proportion of occupational injuries increased according to severity of noise exposure (all P < 0.05). Compared to the non-exposure group, the respective odds ratio (95% confidence intervals) for occupational injury was 1.39 (1.07–1.80) and 1.67 (1.13–2.46) in the mild and severe noise exposure groups, after controlling for age, gender, sleep hours, work schedule (shift work), and exposure status to hazardous chemicals and hazardous machines and equipments. Conclusions: The current study highlights the association between noise exposure and risk of occupational injury. Furthermore, risk of occupational injury increased according to severity of noise exposure. PMID:27991467

Research on computer systems benchmarking

NASA Technical Reports Server (NTRS)

Smith, Alan Jay (Principal Investigator)

1996-01-01

This grant addresses the topic of research on computer systems benchmarking and is more generally concerned with performance issues in computer systems. This report reviews work in those areas during the period of NASA support under this grant. The bulk of the work performed concerned benchmarking and analysis of CPUs, compilers, caches, and benchmark programs. The first part of this work concerned the issue of benchmark performance prediction. A new approach to benchmarking and machine characterization was reported, using a machine characterizer that measures the performance of a given system in terms of a Fortran abstract machine. Another report focused on analyzing compiler performance. The performance impact of optimization in the context of our methodology for CPU performance characterization was based on the abstract machine model. Benchmark programs are analyzed in another paper. A machine-independent model of program execution was developed to characterize both machine performance and program execution. By merging these machine and program characterizations, execution time can be estimated for arbitrary machine/program combinations. The work was continued into the domain of parallel and vector machines, including the issue of caches in vector processors and multiprocessors. All of the afore-mentioned accomplishments are more specifically summarized in this report, as well as those smaller in magnitude supported by this grant.

Computational work and time on finite machines.

NASA Technical Reports Server (NTRS)

Savage, J. E.

1972-01-01

Measures of the computational work and computational delay required by machines to compute functions are given. Exchange inequalities are developed for random access, tape, and drum machines to show that product inequalities between storage and time, number of drum tracks and time, number of bits in an address and time, etc., must be satisfied to compute finite functions on bounded machines.

Can ASCII data files be standardized for Earth Science?

NASA Astrophysics Data System (ADS)

Evans, K. D.; Chen, G.; Wilson, A.; Law, E.; Olding, S. W.; Krotkov, N. A.; Conover, H.

2015-12-01

NASA's Earth Science Data Systems Working Groups (ESDSWG) was created over 10 years ago. The role of the ESDSWG is to make recommendations relevant to NASA's Earth science data systems from user experiences. Each group works independently focusing on a unique topic. Participation in ESDSWG groups comes from a variety of NASA-funded science and technology projects, such as MEaSUREs, NASA information technology experts, affiliated contractor, staff and other interested community members from academia and industry. Recommendations from the ESDSWG groups will enhance NASA's efforts to develop long term data products. Each year, the ESDSWG has a face-to-face meeting to discuss recommendations and future efforts. Last year's (2014) ASCII for Science Data Working Group (ASCII WG) completed its goals and made recommendations on a minimum set of information that is needed to make ASCII files at least human readable and usable for the foreseeable future. The 2014 ASCII WG created a table of ASCII files and their components as a means for understanding what kind of ASCII formats exist and what components they have in common. Using this table and adding information from other ASCII file formats, we will discuss the advantages and disadvantages of a standardized format. For instance, Space Geodesy scientists have been using the same RINEX/SINEX ASCII format for decades. Astronomers mostly archive their data in the FITS format. Yet Earth scientists seem to have a slew of ASCII formats, such as ICARTT, netCDF (an ASCII dump) and the IceBridge ASCII format. The 2015 Working Group is focusing on promoting extendibility and machine readability of ASCII data. Questions have been posed, including, Can we have a standardized ASCII file format? Can it be machine-readable and simultaneously human-readable? We will present a summary of the current used ASCII formats in terms of advantages and shortcomings, as well as potential improvements.

Introductory Education for Mechanical Engineering by Exercise in Mechanical Disassembly

NASA Astrophysics Data System (ADS)

Matsui, Yoshio; Asakawa, Naoki; Iwamori, Satoru

An introductory program “Exercise for engineers in mechanical disassembly” is an exercise that ten students of every team disassemble a motor scooter to the components and then assemble again to the initial form in 15 weeks. The purpose of this program is to introduce mechanical engineering by touching the real machine and learning how it is composed from various mechanical parts to the students at the early period after the entrance into the university. Additional short lectures by young teachers and a special lecture by a top engineer in the industry encourage the students to combine the actual machine and the mechanical engineering subjects. Furthermore, various educations such as group leader system, hazard prediction training, parts filing are included in this program. As a result, students recognize the importance of the mechanical engineering study and the way of group working.

Application of machine learning using support vector machines for crater detection from Martian digital topography data

NASA Astrophysics Data System (ADS)

Salamunićcar, Goran; Lončarić, Sven

In our previous work, in order to extend the GT-57633 catalogue [PSS, 56 (15), 1992-2008] with still uncatalogued impact-craters, the following has been done [GRS, 48 (5), in press, doi:10.1109/TGRS.2009.2037750]: (1) the crater detection algorithm (CDA) based on digital elevation model (DEM) was developed; (2) using 1/128° MOLA data, this CDA proposed 414631 crater-candidates; (3) each crater-candidate was analyzed manually; and (4) 57592 were confirmed as correct detections. The resulting GT-115225 catalog is the significant result of this effort. However, to check such a large number of crater-candidates manually was a demanding task. This was the main motivation for work on improvement of the CDA in order to provide better classification of craters as true and false detections. To achieve this, we extended the CDA with the machine learning capability, using support vector machines (SVM). In the first step, the CDA (re)calculates numerous terrain morphometric attributes from DEM. For this purpose, already existing modules of the CDA from our previous work were reused in order to be capable to prepare these attributes. In addition, new attributes were introduced such as ellipse eccentricity and tilt. For machine learning purpose, the CDA is additionally extended to provide 2-D topography-profile and 3-D shape for each crater-candidate. The latter two are a performance problem because of the large number of crater-candidates in combination with the large number of attributes. As a solution, we developed a CDA architecture wherein it is possible to combine the SVM with a radial basis function (RBF) or any other kernel (for initial set of attributes), with the SVM with linear kernel (for the cases when 2-D and 3-D data are included as well). Another challenge is that, in addition to diversity of possible crater types, there are numerous morphological differences between the smallest (mostly very circular bowl-shaped craters) and the largest (multi-ring) impact craters. As a solution to this problem, the CDA classifies crater-candidates according to their diameter into 7 groups (D smaller/larger then 2km, 4km, 8km, 16km, 32km and 64km), and for each group uses separate SVMs for training and prediction. For implementation of the machine-learning part and integration with the rest of the CDA, we used C.-J. Lin's et al. [http://www.csie.ntu.edu.tw/˜cjlin/] LIBSVM (A Library for Support Vector Machines) and LIBLINEAR (A Library for Large Linear Classification) libraries. According to the initial evaluation, now the CDA provides much better classification of craters as true and false detections.

Workplace flexibility, work hours, and work-life conflict: finding an extra day or two.

PubMed

Hill, E Jeffrey; Erickson, Jenet Jacob; Holmes, Erin K; Ferris, Maria

2010-06-01

This study explores the influence of workplace flexibility on work-life conflict for a global sample of workers from four groups of countries. Data are from the 2007 International Business Machines Global Work and Life Issues Survey administered in 75 countries (N = 24,436). We specifically examine flexibility in where (work-at-home) and when (perceived schedule flexibility) workers engage in work-related tasks. Multivariate results indicate that work-at-home and perceived schedule flexibility are generally related to less work-life conflict. Break point analyses of sub-groups reveal that employees with workplace flexibility are able to work longer hours (often equivalent to one or two 8-hr days more per week) before reporting work-life conflict. The benefit of work-at-home is increased when combined with schedule flexibility. These findings were generally consistent across all four groups of countries, supporting the case that workplace flexibility is beneficial both to individuals (in the form of reduced work-life conflict) and to businesses (in the form of capacity for longer work hours). However, work-at-home appears less beneficial in countries with collectivist cultures. (c) 2010 APA, all rights reserved.

Multi-Cultural Competency-Based Vocational Curricula. Machine Trades. Multi-Cultural Competency-Based Vocational/Technical Curricula Series.

ERIC Educational Resources Information Center

Hepburn, Larry; Shin, Masako

This document, one of eight in a multi-cultural competency-based vocational/technical curricula series, is on machine trades. This program is designed to run 36 weeks and cover 6 instructional areas: use of measuring tools; benchwork/tool bit grinding; lathe work; milling work; precision grinding; and combination machine work. A duty-task index…

Inviting Argument by Analogy: Analogical-Mapping-Based Comparison Activities as a Scaffold for Small-Group Argumentation

ERIC Educational Resources Information Center

Emig, Brandon R.; McDonald, Scott; Zembal-Saul, Carla; Strauss, Susan G.

2014-01-01

This study invited small groups to make several arguments by analogy about simple machines. Groups were first provided training on analogical (structure) mapping and were then invited to use analogical mapping as a scaffold to make arguments. In making these arguments, groups were asked to consider three simple machines: two machines that they had…

Feasibility of a portable pedal exercise machine for reducing sedentary time in the workplace.

PubMed

Carr, Lucas J; Walaska, Kristen A; Marcus, Bess H

2012-05-01

Sedentary time is independently associated with an increased risk of metabolic disease. Worksite interventions designed to decrease sedentary time may serve to improve employee health. The purpose of this study is to test the feasibility and use of a pedal exercise machine for reducing workplace sedentary time. Eighteen full-time employees (mean age+SD 40.2+10.7 years; 88% female) working in sedentary occupations were recruited for participation. Demographic and anthropometric data were collected at baseline and 4 weeks. Participants were provided access to a pedal exercise machine for 4 weeks at work. Use of the device was measured objectively by exercise tracking software, which monitors pedal activity and provides the user real-time feedback (eg, speed, time, distance, calories). At 4 weeks, participants completed a feasibility questionnaire. Participants reported sitting 83% of their working days. Participants used the pedal machines an average of 12.2+6.6 out of a possible 20 working days and pedalled an average of 23.4+20.4 min each day used. Feasibility data indicate that participants found the machines feasible for use at work. Participants also reported sedentary time at work decreased due to the machine. Findings from this study suggest that this pedal machine may be a feasible tool for reducing sedentary time while at work. These findings hold public health significance due to the growing number of sedentary jobs in the USA and the potential of the device for use in large-scale worksite health programmes.

Improving machine operation management efficiency via improving the vehicle park structure and using the production operation information database

NASA Astrophysics Data System (ADS)

Koptev, V. Yu

2017-02-01

The work represents the results of studying basic interconnected criteria of separate equipment units of the transport network machines fleet, depending on production and mining factors to improve the transport systems management. Justifying the selection of a control system necessitates employing new methodologies and models, augmented with stability and transport flow criteria, accounting for mining work development dynamics on mining sites. A necessary condition is the accounting of technical and operating parameters related to vehicle operation. Modern open pit mining dispatching systems must include such kinds of the information database. An algorithm forming a machine fleet is presented based on multi-variation task solution in connection with defining reasonable operating features of a machine working as a part of a complex. Proposals cited in the work may apply to mining machines (drilling equipment, excavators) and construction equipment (bulldozers, cranes, pile-drivers), city transport and other types of production activities using machine fleet.

Stroke dynamics and frequency of 3 phacoemulsification machines.

PubMed

Tognetto, Daniele; Cecchini, Paolo; Leon, Pia; Di Nicola, Marta; Ravalico, Giuseppe

2012-02-01

To measure the working frequency and the stroke dynamics of the phaco tip of 3 phacoemulsification machines. University Eye Clinic of Trieste, Italy. Experimental study. A video wet fixture was assembled to measure the working frequency using a micro camera and a micropulsed strobe-light system. A different video wet fixture was created to measure tip displacement as vectorial movement at different phaco powers using a microscopic video apparatus. The working frequency of the Infiniti Ozil machine was 43.0 kHz in longitudinal mode and 31.6 kHz in torsional mode. The frequency of the Whitestar Signature machine was 29.0 kHz in longitudinal mode and 38.0 kHz with the Ellips FX handpiece. The Stellaris machine had a frequency of 28.8 kHz. The longitudinal stroke of the 3 machines at different phaco powers was statistically significantly different. The Stellaris machine had the highest stroke extent (139 μm). The lateral movement of the Infiniti Ozil and Whitestar Signature machines differed significantly. No movement on the y-axis was observed for the Infiniti Ozil machine in torsional mode. The elliptical path of the Ellips FX handpiece had different x and y components at different phaco powers. The 3 phaco machines performed differently in terms of working frequency and stroke dynamics. The knowledge of the peculiar lateral and elliptical path strokes of Infiniti and Whitestar Signature machines may allow the surgeon to fully use these features for lens removal. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

[Machinable property of a novel dental mica glass-ceramic].

PubMed

Chen, Ji-hua; Li, Na; Ma, Xin-pei; Zhao, Ying-hua; Sun, Xiang; Li, Guang-xin

2007-12-01

To investigate the machinability of a novel dental mica glass-ceramic and analyze the effect of heat-treatment on its ductile machinable behavior. The drilling and turning experiment were used to measure the machinabilities of the control group (feldspar ceramic: Vita Mark II) and 7 experiment groups treated with different crystallization techniques. The microstructures were analyzed using scanning electron microscopy (SEM) and X-ray diffraction (XRD). The average drilling depths in 30 s of the experimental groups ranged from (0.5 +/- 0.1) mm to (7.1 +/- 0.8) mm. There were significant differences between the control [(0.8 +/- 0.1) mm] and the experimental groups (P < 0.05) except the group crystallized at 740 degrees C for 60 min. When crystallized at 650 degrees C (60 min), continuous band chips could formed in machining at a high velocity and cut depth. The crystal portion of this group is only about 40%. This material has a satisfactory machinability. The mechanism could be attributed to a combination of the interlocked structure of mica crystals and the low viscosity of glassy phase.

Final Report of Work Done on Contract NONR-4010(03).

ERIC Educational Resources Information Center

Chapanis, Alphonse

The 24 papers listed report the findings of a study funded by the Office of Naval Research. The study concentrated on the sensory and cognitive factors in man-machine interfaces. The papers are categorized into three groups: perception studies, human engineering studies, and methodological papers. A brief summary of the most noteworthy findings in…

A Study of Readability of Texts in Bangla through Machine Learning Approaches

ERIC Educational Resources Information Center

Sinha, Manjira; Basu, Anupam

2016-01-01

In this work, we have investigated text readability in Bangla language. Text readability is an indicator of the suitability of a given document with respect to a target reader group. Therefore, text readability has huge impact on educational content preparation. The advances in the field of natural language processing have enabled the automatic…

Machine characterization based on an abstract high-level language machine

NASA Technical Reports Server (NTRS)

Saavedra-Barrera, Rafael H.; Smith, Alan Jay; Miya, Eugene

1989-01-01

Measurements are presented for a large number of machines ranging from small workstations to supercomputers. The authors combine these measurements into groups of parameters which relate to specific aspects of the machine implementation, and use these groups to provide overall machine characterizations. The authors also define the concept of pershapes, which represent the level of performance of a machine for different types of computation. A metric based on pershapes is introduced that provides a quantitative way of measuring how similar two machines are in terms of their performance distributions. The metric is related to the extent to which pairs of machines have varying relative performance levels depending on which benchmark is used.

Does the Laser-Microtextured Short Implant Collar Design Reduce Marginal Bone Loss in Comparison with a Machined Collar?

PubMed Central

Sirali, Ali; Gultekin, Pinar; Yalcin, Serdar; Mijiritsky, Eitan

2016-01-01

Purpose. To compare marginal bone loss between subgingivally placed short-collar implants with machined collars and those with machined and laser-microtextured collars. Materials and Methods. The investigators used a retrospective study design and included patients who needed missing posterior teeth replaced with implants. Short-collar implants with identical geometries were divided into two groups: an M group, machined collar; and an L group, machined and laser-microtextured collar. Implants were evaluated according to marginal bone loss, implant success, and probing depth (PD) at 3 years of follow-up. Results. Sixty-two patients received 103 implants (56 in the M group and 47 in the L group). The cumulative survival rate was 100%. All implants showed clinically acceptable marginal bone loss, although bone resorption was lower in the L group (0.49 mm) than in the M group (1.38 mm) at 3 years (p < 0.01). A significantly shallower PD was found for the implants in the L group during follow-up (p < 0.01). Conclusions. Our results suggest predictable outcomes with regard to bone loss for both groups; however, bone resorption was less in the L group than in the M group before and after loading. The laser-microtextured collar implant may provide a shallower PD than the machined collar implant. PMID:27660765

[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.

Analysis of machining accuracy during free form surface milling simulation for different milling strategies

NASA Astrophysics Data System (ADS)

Matras, A.; Kowalczyk, R.

2014-11-01

The analysis results of machining accuracy after the free form surface milling simulations (based on machining EN AW- 7075 alloys) for different machining strategies (Level Z, Radial, Square, Circular) are presented in the work. Particular milling simulations were performed using CAD/CAM Esprit software. The accuracy of obtained allowance is defined as a difference between the theoretical surface of work piece element (the surface designed in CAD software) and the machined surface after a milling simulation. The difference between two surfaces describes a value of roughness, which is as the result of tool shape mapping on the machined surface. Accuracy of the left allowance notifies in direct way a surface quality after the finish machining. Described methodology of usage CAD/CAM software can to let improve a time design of machining process for a free form surface milling by a 5-axis CNC milling machine with omitting to perform the item on a milling machine in order to measure the machining accuracy for the selected strategies and cutting data.

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.

[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.

Machinist (AFSC 42750).

ERIC Educational Resources Information Center

Air Univ., Gunter AFS, Ala. Extension Course Inst.

This four-volume student text is designed for use by Air Force personnel enrolled in a self-study extension course for machinists. Covered in the individual volumes are machine shop fundamentals, metallurgy and advanced machine work, advanced machine work, and tool design and shop management. Each volume in the set contains a series of lessons,…

Wind at Work.

ERIC Educational Resources Information Center

Adams, Stephen

1998-01-01

Describes a project in which students create wind machines to harness the wind's power and do mechanical work. Demonstrates kinetic and potential energy conversions and makes work and power calculations meaningful. Students conduct hands-on investigations with their machines. (DDR)

The role of hemodialysis machines dedication in reducing Hepatitis C transmission in the dialysis setting in Iran: A multicenter prospective interventional study

PubMed Central

Shamshirsaz, Alireza Abdollah; Kamgar, Mohammad; Bekheirnia, Mir Reza; Ayazi, Farzam; Hashemi, Seyed Reza; Bouzari, Navid; Habibzadeh, Mohammad Reza; Pourzahedgilani, Nima; Broumand, Varshasb; Shamshirsaz, Amirhooshang Abdollah; Moradi, Maziyar; Borghei, Mehrdad; Haghighi, Niloofar Nobakht; Broumand, Behrooz

2004-01-01

Background Hepatitis C virus (HCV) infection is a significant problem among patients undergoing maintenance hemodialysis (HD). We conducted a prospective multi-center study to evaluate the effect of dialysis machine separation on the spread of HCV infection. Methods Twelve randomly selected dialysis centers in Tehran, Iran were randomly divided into two groups; those using dedicated machines (D) for HCV infected individuals and those using non-dedicated HD machines (ND). 593 HD cases including 51 HCV positive (RT-PCR) cases and 542 HCV negative patients were enrolled in this study. The prevalence of HCV infection in the D group was 10.1% (range: 4.6%– 13.2%) and it was 7.1% (range: 4.2%–16.8%) in the ND group. During the study conduction 5 new HCV positive cases and 169 new HCV negative cases were added. In the D group, PCR positive patients were dialyzed on dedicated machines. In the ND group all patients shared the same machines. Results In the first follow-up period, the incidence of HCV infection was 1.6% and 4.7% in the D and ND group respectively (p = 0.05). In the second follow-up period, the incidence of HCV infection was 1.3% in the D group and 5.7% in the ND group (p < 0.05). Conclusions In this study the incidence of HCV in HD patients decreased by the use of dedicated HD machines for HCV infected patients. Additional studies may help to clarify the role of machine dedication in conjunction with application of universal precautions in reducing HCV transmission. PMID:15469615

CHISSL: A Human-Machine Collaboration Space for Unsupervised Learning

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

Arendt, Dustin L.; Komurlu, Caner; Blaha, Leslie M.

We developed CHISSL, a human-machine interface that utilizes supervised machine learning in an unsupervised context to help the user group unlabeled instances by her own mental model. The user primarily interacts via correction (moving a misplaced instance into its correct group) or confirmation (accepting that an instance is placed in its correct group). Concurrent with the user's interactions, CHISSL trains a classification model guided by the user's grouping of the data. It then predicts the group of unlabeled instances and arranges some of these alongside the instances manually organized by the user. We hypothesize that this mode of human andmore » machine collaboration is more effective than Active Learning, wherein the machine decides for itself which instances should be labeled by the user. We found supporting evidence for this hypothesis in a pilot study where we applied CHISSL to organize a collection of handwritten digits.« less

A study on the effect of tool electrode thickness on MRR, and TWR in electrical discharge turning process

NASA Astrophysics Data System (ADS)

Gohil, Vikas; Puri, YM

2018-04-01

Turning by electrical discharge machining (EDM) is an emerging area of research. Generally, wire-EDM is used in EDM turning because it is not concerned with electrode tooling cost. In EDM turning wire electrode leaves cusps on the machined surface because of its small diameters and wire breakage which greatly affect the surface finish of the machined part. Moreover, one of the limitations of the process is low machining speed as compared to constituent processes. In this study, conventional EDM was employed for turning purpose in order to generate free-form cylindrical geometries on difficult-to-cut materials. Therefore, a specially designed turning spindle was mounted on a conventional die-sinking EDM machine to rotate the work piece. A conductive preshaped strip of copper as a forming tool is fed (reciprocate) continuously against the rotating work piece; thus, a mirror image of the tool is formed on the circumference of the work piece. In this way, an axisymmetric work piece can be made with small tools. The developed process is termed as the electrical discharge turning (EDT). In the experiments, the effect of machining parameters, such as pulse-on time, peak current, gap voltage and tool thickness on the MRR, and TWR were investigated and practical machining was carried out by turning of SS-304 stainless steel work piece.

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

Mechanical and Histological Effects of Resorbable Blasting Media Surface Treatment on the Initial Stability of Orthodontic Mini-Implants

PubMed Central

2016-01-01

Introduction. This study aimed to evaluate the effects of resorbable blasting media (RBM) treatment on early stability of orthodontic mini-implants by mechanical, histomorphometric, and histological analyses. Methods. Ninety-six (64 for mechanical study and 32 for histological study and histomorphometric analysis) titanium orthodontic mini-implants (OMIs) with machined (machined group) or RBM-treated (CaP) surface (RBM group) were implanted in the tibiae of 24 rabbits. Maximum initial torque (MIT) was measured during insertion, and maximum removal torque (MRT) and removal angular momentum (RAM) were measured at 2 and 4 weeks after implantation. Bone-to-implant contact (BIC) and bone area (BA) were analyzed at 4 weeks after implantation. Results. RBM group exhibited significantly lower MIT and significantly higher MRT and RAM at 2 weeks than machined group. No significant difference in MRT, RAM, and BIC between the two groups was noted at 4 weeks, although BA was significantly higher in RBM group than in machined group. RBM group showed little bone resorption, whereas machined group showed new bone formation after bone resorption. Conclusions. RBM surface treatment can provide early stability of OMIs around 2 weeks after insertion, whereas stability of machined surface OMIs may decrease in early stages because of bone resorption, although it can subsequently recover by new bone apposition. PMID:26942200

Applications of machine learning and data mining methods to detect associations of rare and common variants with complex traits.

PubMed

Lu, Ake Tzu-Hui; Austin, Erin; Bonner, Ashley; Huang, Hsin-Hsiung; Cantor, Rita M

2014-09-01

Machine learning methods (MLMs), designed to develop models using high-dimensional predictors, have been used to analyze genome-wide genetic and genomic data to predict risks for complex traits. We summarize the results from six contributions to our Genetic Analysis Workshop 18 working group; these investigators applied MLMs and data mining to analyses of rare and common genetic variants measured in pedigrees. To develop risk profiles, group members analyzed blood pressure traits along with single-nucleotide polymorphisms and rare variant genotypes derived from sequence and imputation analyses in large Mexican American pedigrees. Supervised MLMs included penalized regression with varying penalties, support vector machines, and permanental classification. Unsupervised MLMs included sparse principal components analysis and sparse graphical models. Entropy-based components analyses were also used to mine these data. None of the investigators fully capitalized on the genetic information provided by the complete pedigrees. Their approaches either corrected for the nonindependence of the individuals within the pedigrees or analyzed only those who were independent. Some methods allowed for covariate adjustment, whereas others did not. We evaluated these methods using a variety of metrics. Four contributors conducted primary analyses on the real data, and the other two research groups used the simulated data with and without knowledge of the underlying simulation model. One group used the answers to the simulated data to assess power and type I errors. Although the MLMs applied were substantially different, each research group concluded that MLMs have advantages over standard statistical approaches with these high-dimensional data. © 2014 WILEY PERIODICALS, INC.

Chain Experiment competition inspires learning of physics

NASA Astrophysics Data System (ADS)

Dziob, Daniel; Górska, Urszula; Kołodziej, Tomasz

2017-05-01

The Chain Experiment is an annual competition which originated in Slovenia in 2005 and later expanded to Poland in 2013. For the purpose of the event, each participating team designs and builds a contraption that transports a small steel ball from one end to the other. At the same time the constructed machine needs to use a number of interesting phenomena and physics laws. In the competition’s finale, all contraptions are connected to each other to form a long chain transporting steel balls. In brief, they are all evaluated for qualities such as: creativity and advance in theoretical background, as well as the reliability of the constructed machine to work without human help. In this article, we present the contraptions developed by students taking part in the competition in order to demonstrate the advance in theoretical basis together with creativity in design and outstanding engineering skills of its participants. Furthermore, we situate the Chain Experiment in the context of other group competitions, at the same time demonstrating that—besides activating numerous group work skills—it also improves the ability to think critically and present one’s knowledge to a broader audience. We discussed it in the context of problem based learning, gamification and collaborative testing.

[Comparison of machinability of two types of dental machinable ceramic].

PubMed

Fu, Qiang; Zhao, Yunfeng; Li, Yong; Fan, Xinping; Li, Yan; Lin, Xuefeng

2002-11-01

In terms of the problems of now available dental machinable ceramics, a new type of calcium-mica glass-ceramic, PMC-I ceramic, was developed, and its machinability was compared with that of Vita MKII quantitatively. Moreover, the relationship between the strength and the machinability of PMC-I ceramic was studied. Samples of PMC-I ceramic were divided into four groups according to their nucleation procedures. 600-seconds drilling tests were conducted with high-speed steel tools (Phi = 2.3 mm) to measure the drilling depths of Vita MKII ceramic and PMC-I ceramic, while constant drilling speed of 600 rpm and constant axial load of 39.2 N were used. And the 3-point bending strength of the four groups of PMC-I ceramic were recorded. Drilling depth of Vita MKII was 0.71 mm, while the depths of the four groups of PMC-I ceramic were 0.88 mm, 1.40 mm, 0.40 mm and 0.90 mm, respectively. Group B of PMC-I ceramic showed the largest depth of 1.40 mm and was statistically different from other groups and Vita MKII. And the strength of the four groups of PMC-I ceramic were 137.7, 210.2, 118.0 and 106.0 MPa, respectively. The machinability of the new developed dental machinable ceramic of PMC-I could meet the need of the clinic.

76 FR 46853 - International Business Machines Corporation, ITD Business Unit, Division 7, E-mail and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-03

...] International Business Machines Corporation, ITD Business Unit, Division 7, E-mail and Collaboration Group... Business Machines Corporation (IBM), ITD Business Unit, Division 7, E- mail and Collaboration Group... Business Unit, Division 7, E-mail and Collaboration [[Page 46854

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2012 CFR

2012-07-01

... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section shooting off the solid. On the loading machine operator or on the loading machine within 36 inches inby the...

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2014 CFR

2014-07-01

... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section shooting off the solid. On the loading machine operator or on the loading machine within 36 inches inby the...

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2013 CFR

2013-07-01

... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section shooting off the solid. On the loading machine operator or on the loading machine within 36 inches inby the...

33 CFR 157.124 - COW tank washing machines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false COW tank washing machines. 157....124 COW tank washing machines. (a) COW machines must be permanently mounted in each cargo tank. (b) The COW machines in each tank must have sufficient nozzles with the proper diameter, working pressure...

Metalworking Lathe; Machine Shop Work--Intermediate: 9555.03.

ERIC Educational Resources Information Center

Dade County Public Schools, Miami, FL.

The course outline has been prepared as a guide to assist the instructor to plan systematically and to present meaningful lessons to provide the training needed by the machine shop student. This is the third course of instruction in a series of machine shop work courses. The six blocks of instruction contained in this outline are designed to…

Bench Work and Support Operations, Machine Shop Work--Intermediate: 9555.02.

ERIC Educational Resources Information Center

Dade County Public Schools, Miami, FL.

The course outline has been prepared as a guide to assist the instructor to plan systematically and to present meaningful lessons programmed to meet the necessary training needed by the machine shop student who has completed an introductory course in machine tool technology. The five blocks of instruction contained in this outline are designed to…

The Linux operating system: An introduction

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1995-01-01

Linux is a Unix-like operating system for Intel 386/486/Pentium based IBM-PCs and compatibles. The kernel of this operating system was written from scratch by Linus Torvalds and, although copyrighted by the author, may be freely distributed. A world-wide group has collaborated in developing Linux on the Internet. Linux can run the powerful set of compilers and programming tools of the Free Software Foundation, and XFree86, a port of the X Window System from MIT. Most capabilities associated with high performance workstations, such as networking, shared file systems, electronic mail, TeX, LaTeX, etc. are freely available for Linux. It can thus transform cheap IBM-PC compatible machines into Unix workstations with considerable capabilities. The author explains how Linux may be obtained, installed and networked. He also describes some interesting applications for Linux that are freely available. The enormous consumer market for IBM-PC compatible machines continually drives down prices of CPU chips, memory, hard disks, CDROMs, etc. Linux can convert such machines into powerful workstations that can be used for teaching, research and software development. For professionals who use Unix based workstations at work, Linux permits virtually identical working environments on their personal home machines. For cost conscious educational institutions Linux can create world-class computing environments from cheap, easily maintained, PC clones. Finally, for university students, it provides an essentially cost-free path away from DOS into the world of Unix and X Windows.

[The effects of work in an air-conditioned cabin and stay in a resting chamber on blood pressure and heart rate of operators employed in deep copper mines].

PubMed

Borodulin-Nadzieja, L; Janocha, A; Pietraszkiewicz, T; Salomon, E; Stańda, M

2001-01-01

This paper is part of a wider comparative study of the heart rate, blood pressure, external and core temperature in operators of self-propelled mining machines with and without air-conditioning cabins. Two groups, each of ten operators, characterised by the similar age and duration of employment, stayed for 20 min a specially prepared resting chamber with much more advantageous microclimatic conditions. The results of our examinations (Holter heart rate and continuous blood pressure recordings, external and core temperature measurements) revealed that during the work (particularly during the increased work-load) all parameters recorded were significantly lower in air-conditioning cabins as compared with the group working without air-condition. In both groups, a complete restitution of the heart rate and blood pressure was observed after a 20-min stay in the resting chamber. During the work, a statistically significant increase in the external temperature was found in both groups of operators, whereas the increase in the core temperature was observed only in operators working without air-condition. After a 20-min stay in the resting chamber, a complete return to the normal temperature was noted only in operators working in air-conditioned cabins.

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.

The effect of social demographic factors, snack consumption and vending machine use on oral health of children living in London.

PubMed

Maliderou, M; Reeves, S; Noble, C

2006-10-07

To investigate the effect of socio-economic status, sugar, snack consumption and vending machine use on the prevalence and severity of caries (DMF) in children. An observational study was carried out in a dental practice in inner city London. Sixty children were asked to complete a questionnaire and a three day food and drink diary. After a dental examination the number of decayed (D), missing (M) or filled (F) teeth provided a DMF score. Anova and Pearsons correlations were used to analyse the data statistically. Children from social groups I and II consumed significantly less (P < 0.05) sugar, confectionery, crisps and used a vending machine less often than children from other social groups. Children from Social groups I, II and III had significantly lower DMF scores. The average DMF from social group I children was 0.5 +/- 0.6, whilst group IV children had the greatest incidence and a DMF of 4.6 +/- 0.8. Significant correlations were identified between DMF and sugar, confectionery and crisp consumption and vending machine use, and a negative correlation between DMF and vegetable consumption. Socio-economic status and access to vending machines were found to have a significant effect on sugar intakes, foods choices, and dental health. The removal of vending machines from schools or at least installing 'healthy' vending machines is recommended. Health promotion programmes that account for social groups and snacking habits that are cost effective are required.

OCCUPATIONAL EDUCATION AND TRAINING FOR TOMORROW'S WORLD OF WORK. NUMBER 1, SQUARE PEGS AND ROUND HOLES.

ERIC Educational Resources Information Center

HORNER, JAMES T.; PETERSON, EVERETT E.

A MAJOR PROBLEM OF AMERICAN YOUTH TODAY IS THAT OF QUALIFYING FOR AND HOLDING A JOB. GENERAL EDUCATION IS NOT ENOUGH FOR THE GREAT MAJORITY OF PEOPLE WHO MUST OPERATE FARMS, MACHINES, SHOPS, AND OFFICES AND PROVIDE SERVICES. YOUTH FACE INCREASED JOB COMPETITION BECAUSE OF THE INCREASED SIZE OF THE 14- TO 24-YEAR AGE GROUP. UNEMPLOYMENT AMONG YOUNG…

Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science

NASA Astrophysics Data System (ADS)

Riedel, Morris; Ramachandran, Rahul; Baumann, Peter

2014-05-01

The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.

Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science

NASA Technical Reports Server (NTRS)

Riedel, Morris; Ramachandran, Rahul; Baumann, Peter

2014-01-01

The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.

A T-Type Capacitive Sensor Capable of Measuring 5-DOF Error Motions of Precision Spindles

PubMed Central

Xiang, Kui; Qiu, Rongbo; Mei, Deqing; Chen, Zichen

2017-01-01

The precision spindle is a core component of high-precision machine tools, and the accurate measurement of its error motions is important for improving its rotation accuracy as well as the work performance of the machine. This paper presents a T-type capacitive sensor (T-type CS) with an integrated structure. The proposed sensor can measure the 5-degree-of-freedom (5-DOF) error motions of a spindle in-situ and simultaneously by integrating electrode groups in the cylindrical bore of the stator and the outer end face of its flange, respectively. Simulation analysis and experimental results show that the sensing electrode groups with differential measurement configuration have near-linear output for the different types of rotor displacements. What’s more, the additional capacitance generated by fringe effects has been reduced about 90% with the sensing electrode groups fabricated based on flexible printed circuit board (FPCB) and related processing technologies. The improved signal processing circuit has also been increased one times in the measuring performance and makes the measured differential output capacitance up to 93% of the theoretical values. PMID:28846631

76 FR 5832 - International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-02

... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-74,554] International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA, San Jose, CA; Notice of... determination of the TAA petition filed on behalf of workers at International Business Machines (IBM), Software...

Improving Energy Efficiency in CNC Machining

NASA Astrophysics Data System (ADS)

Pavanaskar, Sushrut S.

We present our work on analyzing and improving the energy efficiency of multi-axis CNC milling process. Due to the differences in energy consumption behavior, we treat 3- and 5-axis CNC machines separately in our work. For 3-axis CNC machines, we first propose an energy model that estimates the energy requirement for machining a component on a specified 3-axis CNC milling machine. Our model makes machine-specific predictions of energy requirements while also considering the geometric aspects of the machining toolpath. Our model - and the associated software tool - facilitate direct comparison of various alternative toolpath strategies based on their energy-consumption performance. Further, we identify key factors in toolpath planning that affect energy consumption in CNC machining. We then use this knowledge to propose and demonstrate a novel toolpath planning strategy that may be used to generate new toolpaths that are inherently energy-efficient, inspired by research on digital micrography -- a form of computational art. For 5-axis CNC machines, the process planning problem consists of several sub-problems that researchers have traditionally solved separately to obtain an approximate solution. After illustrating the need to solve all sub-problems simultaneously for a truly optimal solution, we propose a unified formulation based on configuration space theory. We apply our formulation to solve a problem variant that retains key characteristics of the full problem but has lower dimensionality, allowing visualization in 2D. Given the complexity of the full 5-axis toolpath planning problem, our unified formulation represents an important step towards obtaining a truly optimal solution. With this work on the two types of CNC machines, we demonstrate that without changing the current infrastructure or business practices, machine-specific, geometry-based, customized toolpath planning can save energy in CNC machining.

Evaluation and selection of refrigeration systems for lunar surface and space applications

NASA Technical Reports Server (NTRS)

Copeland, R. J.; Blount, T. D.; Williams, J. L.

1971-01-01

Evaluated are the various refrigeration machines which could be used to provide heat rejection in environmental control systems for lunar surface and spacecraft applications, in order to select the best refrigeration machine for satisfying each individual application and the best refrigeration machine for satisfying all of the applications. The refrigeration machine considered include: (1) vapor comparison cycle (work-driven); (2) vapor adsorption cycle (heat-driven); (3) vapor absorption cycle (heat-driven); (4) thermoelectric (electrically-driven); (5) gas cycle (work driven); (6) steam-jet (heat-driven).

Application of Elements of TPM Strategy for Operation Analysis of Mining Machine

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Total Productive Maintenance (TPM) strategy includes group of activities and actions in order to maintenance machines in failure-free state and without breakdowns thanks to tending limitation of failures, non-planned shutdowns, lacks and non-planned service of machines. These actions are ordered to increase effectiveness of utilization of possessed devices and machines in company. Very significant element of this strategy is connection of technical actions with changes in their perception by employees. Whereas fundamental aim of introduction this strategy is improvement of economic efficiency of enterprise. Increasing competition and necessity of reduction of production costs causes that also mining enterprises are forced to introduce this strategy. In the paper examples of use of OEE model for quantitative evaluation of selected mining devices were presented. OEE model is quantitative tool of TPM strategy and can be the base for further works connected with its introduction. OEE indicator is the product of three components which include availability and performance of the studied machine and the quality of the obtained product. The paper presents the results of the effectiveness analysis of the use of a set of mining machines included in the longwall system, which is the first and most important link in the technological line of coal production. The set of analyzed machines included the longwall shearer, armored face conveyor and cruscher. From a reliability point of view, the analyzed set of machines is a system that is characterized by the serial structure. The analysis was based on data recorded by the industrial automation system used in the mines. This method of data acquisition ensured their high credibility and a full time synchronization. Conclusions from the research and analyses should be used to reduce breakdowns, failures and unplanned downtime, increase performance and improve production quality.

A time-shared machine repair problem with mixed spares under N-policy

NASA Astrophysics Data System (ADS)

Jain, Madhu; Shekhar, Chandra; Shukla, Shalini

2016-06-01

The present investigation deals with a machine repair problem consisting of cold and warm standby machines. The machines are subject to breakdown and are repaired by the permanent repairman operating under N-policy. There is provision of one additional removable repairman who is called upon when the work load of failed machines crosses a certain threshold level and is removed as soon as the work load again ceases to that level. Both repairmen recover the failed machines by following the time sharing concept which means that the repairmen share their repair job simultaneously among all the failed machines that have joined the system for repair. Markovian model has been developed by considering the queue dependent rates and solved analytically using the recursive technique. Various performance indices are derived which are further used to obtain the cost function. By taking illustration, numerical simulation and sensitivity analysis have been provided.

Non-equilibrium quantum heat machines

NASA Astrophysics Data System (ADS)

Alicki, Robert; Gelbwaser-Klimovsky, David

2015-11-01

Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound.

Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress

PubMed Central

Fu, Longwen; Liu, Zuoyi

2018-01-01

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented. PMID:29849612

Machining of Fibre Reinforced Plastic Composite Materials.

PubMed

Caggiano, Alessandra

2018-03-18

Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented.

Machining of Fibre Reinforced Plastic Composite Materials

PubMed Central

2018-01-01

Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented. PMID:29562635

Ex Vivo Machine Perfusion in VCA with a Novel Oxygen Carrier System to Enhance Graft Preservation and Immunologic Outcomes

DTIC Science & Technology

2016-12-01

studies 2. Ex Vivo Study Group (n=4) Machine Perfusion 4 VRAM grafts preserved for 14 hours with MP at 21°C Study group – developments for machine...period. The VRAM grafts were inspected daily and punch biopsies were performed on days 2, 4 and 7. The end- study necropsy was conducted on post ...TNF- α in the MP group, showing the beneficial impact of effective ex -vivo oxygenation in this group (Figure 6). Previous clinical studies in

Trends of Occupational Fatalities Involving Machines, United States, 1992–2010

PubMed Central

Marsh, Suzanne M.; Fosbroke, David E.

2016-01-01

Background This paper describes trends of occupational machine-related fatalities from 1992–2010. We examine temporal patterns by worker demographics, machine types (e.g., stationary, mobile), and industries. Methods We analyzed fatalities from Census of Fatal Occupational Injuries data provided by the Bureau of Labor Statistics to the National Institute for Occupational Safety and Health. We used injury source to identify machine-related incidents and Poisson regression to assess trends over the 19-year period. Results There was an average annual decrease of 2.8% in overall machine-related fatality rates from 1992 through 2010. Mobile machine-related fatality rates decreased an average of 2.6% annually and stationary machine-related rates decreased an average of 3.5% annually. Groups that continued to be at high risk included older workers; self-employed; and workers in agriculture/forestry/fishing, construction, and mining. Conclusion Addressing dangers posed by tractors, excavators, and other mobile machines needs to continue. High-risk worker groups should receive targeted information on machine safety. PMID:26358658

49 CFR 214.341 - Roadway maintenance machines.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Roadway maintenance machines. 214.341 Section 214... Roadway maintenance machines. (a) Each employer shall include in its on-track safety program specific provisions for the safety of roadway workers who operate or work near roadway maintenance machines. Those...

8. VIEW OF COMBINATION GEAR HOBBING MACHINE (Gould & Eberhardt, ...

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

8. VIEW OF COMBINATION GEAR HOBBING MACHINE (Gould & Eberhardt, Newark, New Jersey. Patented No. 2103) AND LATHE (W.E. Shipley Machiner Co. Metal Working Machinery, Philadelphia, Pennsylvania, 1913). - Juniata Shops, Machine Shop No. 1, East of Fourth Avenue at Third Street, Altoona, Blair County, PA

Freeform diamond machining of complex monolithic metal optics for integral field systems

NASA Astrophysics Data System (ADS)

Dubbeldam, Cornelis M.; Robertson, David J.; Preuss, Werner

2004-09-01

Implementation of the optical designs of image slicing Integral Field Systems requires accurate alignment of a large number of small (and therefore difficult to manipulate) optical components. In order to facilitate the integration of these complex systems, the Astronomical Instrumentation Group (AIG) of the University of Durham, in collaboration with the Labor für Mikrozerspanung (Laboratory for Precision Machining - LFM) of the University of Bremen, have developed a technique for fabricating monolithic multi-faceted mirror arrays using freeform diamond machining. Using this technique, the inherent accuracy of the diamond machining equipment is exploited to achieve the required relative alignment accuracy of the facets, as well as an excellent optical surface quality for each individual facet. Monolithic arrays manufactured using this freeform diamond machining technique were successfully applied in the Integral Field Unit for the GEMINI Near-InfraRed Spectrograph (GNIRS IFU), which was recently installed at GEMINI South. Details of their fabrication process and optical performance are presented in this paper. In addition, the direction of current development work, conducted under the auspices of the Durham Instrumentation R&D Program supported by the UK Particle Physics and Astronomy Research Council (PPARC), will be discussed. The main emphasis of this research is to improve further the optical performance of diamond machined components, as well as to streamline the production and quality control processes with a view to making this technique suitable for multi-IFU instruments such as KMOS etc., which require series production of large quantities of optical components.

A review of supervised machine learning applied to ageing research.

PubMed

Fabris, Fabio; Magalhães, João Pedro de; Freitas, Alex A

2017-04-01

Broadly speaking, supervised machine learning is the computational task of learning correlations between variables in annotated data (the training set), and using this information to create a predictive model capable of inferring annotations for new data, whose annotations are not known. Ageing is a complex process that affects nearly all animal species. This process can be studied at several levels of abstraction, in different organisms and with different objectives in mind. Not surprisingly, the diversity of the supervised machine learning algorithms applied to answer biological questions reflects the complexities of the underlying ageing processes being studied. Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to review these works, to discuss their main findings and weaknesses. In summary, the main findings of the reviewed papers are: the link between specific types of DNA repair and ageing; ageing-related proteins tend to be highly connected and seem to play a central role in molecular pathways; ageing/longevity is linked with autophagy and apoptosis, nutrient receptor genes, and copper and iron ion transport. Additionally, several biomarkers of ageing were found by machine learning. Despite some interesting machine learning results, we also identified a weakness of current works on this topic: only one of the reviewed papers has corroborated the computational results of machine learning algorithms through wet-lab experiments. In conclusion, supervised machine learning has contributed to advance our knowledge and has provided novel insights on ageing, yet future work should have a greater emphasis in validating the predictions.

Development of an Eco-Friendly Electrical Discharge Machine (E-EDM) Using TRIZ Approach

NASA Astrophysics Data System (ADS)

Sreebalaji, V. S.; Saravanan, R.

Electrical Discharge Machine (EDM) is one of the non-traditional machining processes. EDM process is based on thermoelectric energy between the work and an electrode. A pulse discharge occurs in a small gap between the work piece and the electrode and removes the unwanted material from the parent metal through melting and vaporization. The electrode and the work piece must have an electrical conductivity in order to generate the spark. Dielectric fluid acts as a spark conductor, concentrating the energy to a very narrow region. There are various types of products can be produced and finished using EDM such as Moulds, Dies, Parts of Aerodynamics, Automotives and Surgical components. This research work reveals how an Eco friendly EDM (E-EDM) can be modeled to replace die electric fluid and introducing ozonised oxygen in to EDM to eliminate harmful effects generated while machining by using dielectric, to make pollution free machining environment through a new design of EEDM using TRIZ (a Russian acronym for Theory of Inventive Problem Solving) approach, since Eco friendly design is the need of the hour.

Assessing the role of syringe dispensing machines and mobile van outlets in reaching hard-to-reach and high-risk groups of injecting drug users (IDUs): a review

PubMed Central

Islam, Md Mofizul; Conigrave, Katherine M

2007-01-01

Reaching hard-to-reach and high-risk injecting drug users (IDUs) is one of the most important challenges for contemporary needle syringe programs (NSPs). The aim of this review is to examine, based upon the available international experience, the effectiveness of syringe vending machines and mobile van/bus based NSPs in making services more accessible to these hard-to-reach and high-risk groups of IDUs. A literature search revealed 40 papers/reports, of which 18 were on dispensing machines (including vending and exchange machines) and 22 on mobile vans. The findings demonstrate that syringe dispensing machines and mobile vans are promising modalities of NSPs, which can make services more accessible to the target group and in particular to the harder-to-reach and higher-risk groups of IDUs. Their anonymous and confidential approaches make services attractive, accessible and acceptable to these groups. These two outlets were found to be complementary to each other and to other modes of NSPs. Services through dispensing machines and mobile vans in strategically important sites are crucial elements in continuing efforts in reducing the spread of HIV and other blood borne viruses among IDUs. PMID:17958894

Increasing energy efficiency level of building production based on applying modern mechanization facilities

NASA Astrophysics Data System (ADS)

Prokhorov, Sergey

2017-10-01

Building industry in a present day going through the hard times. Machine and mechanism exploitation cost, on a field of construction and installation works, takes a substantial part in total building construction expenses. There is a necessity to elaborate high efficient method, which allows not only to increase production, but also to reduce direct costs during machine fleet exploitation, and to increase its energy efficiency. In order to achieve the goal we plan to use modern methods of work production, hi-tech and energy saving machine tools and technologies, and use of optimal mechanization sets. As the optimization criteria there are exploitation prime cost and set efficiency. During actual task-solving process we made a conclusion, which shows that mechanization works, energy audit with production juxtaposition, prime prices and costs for energy resources allow to make complex machine fleet supply, improve ecological level and increase construction and installation work quality.

Control system for, and a method of, heating an operator station of a work machine

DOEpatents

Baker, Thomas M.; Hoff, Brian D.; Akasam, Sivaprasad

2005-04-05

There are situations in which an operator remains in an operator station of a work machine when an engine of the work machine is inactive. The present invention includes a control system for, and a method of, heating the operator station when the engine is inactive. A heating system of the work machine includes an electrically-powered coolant pump, a power source, and at least one piece of warmed machinery. An operator heat controller is moveable between a first and a second position, and is operable to connect the electrically-powered coolant pump to the power source when the engine is inactive and the operator heat controller is in the first position. Thus, by deactivating the engine and then moving the operator heat controller to the first position, the operator may supply electrical energy to the electrically-powered coolant pump, which is operably coupled to heat the operator station.

National Aspects of Creating and Using MARC/RECON Records.

ERIC Educational Resources Information Center

Rather, John C., Ed.; Avram, Henriette D., Ed.

The Retrospective Conversion (RECON) Working Task Force investigated the problems of converting retrospective catalog records to machine readable form. The major conclusions and recommendations of the Task Force cover five areas: the level of machine-readable records, conversion of other machine-readable data bases, a machine-readable National…

30 CFR 70.220 - Status change reports.

Code of Federal Regulations, 2014 CFR

2014-07-01

... to all miners expected to wear a CPDM. The training shall be completed prior to a miner wearing a... cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section blasting off the solid. On the loading machine operator...

Calculating Synchronous Inductive Reactances of Contactless Machines When Magnetic Circuit is Saturated and of Machines with Superconducting Excitation Windings,

DTIC Science & Technology

The work studies the effect of magnetic circuit saturation on the synchronous inductive reactance of the armature. A practical method is given for...calculating synchronized parameters in saturating synchronized machines with additional clearances and machines with superconducting excitation windings.

GlycoRDF: an ontology to standardize glycomics data in RDF

PubMed Central

Ranzinger, Rene; Aoki-Kinoshita, Kiyoko F.; Campbell, Matthew P.; Kawano, Shin; Lütteke, Thomas; Okuda, Shujiro; Shinmachi, Daisuke; Shikanai, Toshihide; Sawaki, Hiromichi; Toukach, Philip; Matsubara, Masaaki; Yamada, Issaku; Narimatsu, Hisashi

2015-01-01

Motivation: Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. Results: An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. Availability and implementation: The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/). Contact: rene@ccrc.uga.edu or kkiyoko@soka.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25388145

GlycoRDF: an ontology to standardize glycomics data in RDF.

PubMed

Ranzinger, Rene; Aoki-Kinoshita, Kiyoko F; Campbell, Matthew P; Kawano, Shin; Lütteke, Thomas; Okuda, Shujiro; Shinmachi, Daisuke; Shikanai, Toshihide; Sawaki, Hiromichi; Toukach, Philip; Matsubara, Masaaki; Yamada, Issaku; Narimatsu, Hisashi

2015-03-15

Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/). © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Investigation of approximate models of experimental temperature characteristics of machines

NASA Astrophysics Data System (ADS)

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

2018-05-01

This work is devoted to the investigation of various approaches to the approximation of experimental data and the creation of simulation mathematical models of thermal processes in machines with the aim of finding ways to reduce the time of their field tests and reducing the temperature error of the treatments. The main methods of research which the authors used in this work are: the full-scale thermal testing of machines; realization of various approaches at approximation of experimental temperature characteristics of machine tools by polynomial models; analysis and evaluation of modelling results (model quality) of the temperature characteristics of machines and their derivatives up to the third order in time. As a result of the performed researches, rational methods, type, parameters and complexity of simulation mathematical models of thermal processes in machine tools are proposed.

The Evaluation of Efficiency of the Use of Machine Working Time in the Industrial Company - Case Study

NASA Astrophysics Data System (ADS)

Kardas, Edyta; Brožova, Silvie; Pustějovská, Pavlína; Jursová, Simona

2017-12-01

In the paper the evaluation of efficiency of the use of machines in the selected production company was presented. The OEE method (Overall Equipment Effectiveness) was used for the analysis. The selected company deals with the production of tapered roller bearings. The analysis of effectiveness was done for 17 automatic grinding lines working in the department of grinding rollers. Low level of efficiency of machines was affected by problems with the availability of machines and devices. The causes of machine downtime on these lines was also analyzed. Three basic causes of downtime were identified: no kanban card, diamonding, no operator. Ways to improve the use of these machines were suggested. The analysis takes into account the actual results from the production process and covers the period of one calendar year.

Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.

PubMed

Shouval, Roni; Labopin, Myriam; Bondi, Ori; Mishan-Shamay, Hila; Shimoni, Avichai; Ciceri, Fabio; Esteve, Jordi; Giebel, Sebastian; Gorin, Norbert C; Schmid, Christoph; Polge, Emmanuelle; Aljurf, Mahmoud; Kroger, Nicolaus; Craddock, Charles; Bacigalupo, Andrea; Cornelissen, Jan J; Baron, Frederic; Unger, Ron; Nagler, Arnon; Mohty, Mohamad

2015-10-01

Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplantation-related mortality risk prediction. This work is a retrospective DM study on a cohort of 28,236 adult HSCT recipients from the AL registry of the European Group for Blood and Marrow Transplantation. The primary objective was prediction of overall mortality (OM) at 100 days after HSCT. Secondary objectives were estimation of nonrelapse mortality, leukemia-free survival, and overall survival at 2 years. Donor, recipient, and procedural characteristics were analyzed. The alternating decision tree machine learning algorithm was applied for model development on 70% of the data set and validated on the remaining data. OM prevalence at day 100 was 13.9% (n=3,936). Of the 20 variables considered, 10 were selected by the model for OM prediction, and several interactions were discovered. By using a logistic transformation function, the crude score was transformed into individual probabilities for 100-day OM (range, 3% to 68%). The model's discrimination for the primary objective performed better than the European Group for Blood and Marrow Transplantation score (area under the receiver operating characteristics curve, 0.701 v 0.646; P<.001). Calibration was excellent. Scores assigned were also predictive of secondary objectives. The alternating decision tree model provides a robust tool for risk evaluation of patients with AL before HSCT, and is available online (http://bioinfo.lnx.biu.ac.il/∼bondi/web1.html). It is presented as a continuous probabilistic score for the prediction of day 100 OM, extending prediction to 2 years. The DM method has proved useful for clinical prediction in HSCT. © 2015 by American Society of Clinical Oncology.

Determinants of dust exposure in tunnel construction work.

PubMed

Bakke, Berit; Stewart, Patricia; Eduard, Wijnand

2002-11-01

In tunnel construction work, dust is generated from rock drilling, rock bolting, grinding, scaling, and transport operations. Other important dust-generating activities are blasting rock and spraying wet concrete on tunnel walls for strength and finishing work. The aim of this study was to identify determinants of dust exposure in tunnel construction work and to propose control measures. Personal exposures to total dust, respirable dust, and alpha-quartz were measured among 209 construction workers who were divided into 8 job groups performing similar tasks: drill and blast workers, shaft drilling workers, tunnel boring machine workers, shotcreting operators, support workers, concrete workers, outdoor concrete workers, and electricians. Information on determinants was obtained from interviewing the workers, observation by the industrial hygienist responsible for the sampling, and the job site superintendent. Multivariate regression models were used to identify determinants associated with the dust exposures within the job groups. The geometric mean exposure to total dust, respirable dust, and alpha-quartz for all tunnel workers was 3.5 mg/m(3) (GSD = 2.6), 1.2 mg/m(3) (GSD = 2.4), and 0.035 mg/m(3) (GSD = 5.0), respectively. A total of 15 percent of the total dust measurements, 5 percent of the respirable dust, and 21 percent of the alpha-quartz exceeded the Norwegian OELs of 10 mg/m(3), 5 mg/m(3), and 0.1 mg/m(3), respectively. Job groups with highest geometric mean total dust exposure were shotcreting operators (6.8 mg/m(3)), tunnel boring machine workers (6.2 mg/m(3)), and shaft drilling workers (6.1 mg/m(3)). The lowest exposed groups to total dust were outdoor concrete workers (1.0 mg/m(3)), electricians (1.4 mg/m(3)), and support workers (1.9 mg/m(3)). Important determinants of exposure were job group, job site, certain tasks (e.g., drilling and scaling), the presence of a cab, and breakthrough of the tunnel. The use of ventilated, closed cabs appeared to be the single most important control measure for lowering exposures.

Determinants of wood dust exposure in the Danish furniture industry.

PubMed

Mikkelsen, Anders B; Schlunssen, Vivi; Sigsgaard, Torben; Schaumburg, Inger

2002-11-01

This paper investigates the relation between wood dust exposure in the furniture industry and occupational hygiene variables. During the winter 1997-98 54 factories were visited and 2362 personal, passive inhalable dust samples were obtained; the geometric mean was 0.95 mg/m(3) and the geometric standard deviation was 2.08. In a first measuring round 1685 dust concentrations were obtained. For some of the workers repeated measurements were carried out 1 (351) and 2 weeks (326) after the first measurement. Hygiene variables like job, exhaust ventilation, cleaning procedures, etc., were documented. A multivariate analysis based on mixed effects models was used with hygiene variables being fixed effects and worker, machine, department and factory being random effects. A modified stepwise strategy of model making was adopted taking into account the hierarchically structured variables and making possible the exclusion of non-influential random as well as fixed effects. For woodworking, the following determinants of exposure increase the dust concentration: manual and automatic sanding and use of compressed air with fully automatic and semi-automatic machines and for cleaning of work pieces. Decreased dust exposure resulted from the use of compressed air with manual machines, working at fully automatic or semi-automatic machines, functioning exhaust ventilation, work on the night shift, daily cleaning of rooms, cleaning of work pieces with a brush, vacuum cleaning of machines, supplementary fresh air intake and safety representative elected within the last 2 yr. For handling and assembling, increased exposure results from work at automatic machines and presence of wood dust on the workpieces. Work on the evening shift, supplementary fresh air intake, work in a chair factory and special cleaning staff produced decreased exposure to wood dust. The implications of the results for the prevention of wood dust exposure are discussed.

Deep Learning Online Course

DTIC Science & Technology

2016-11-01

The instructor was Prof. Fei-Fei Li, who is well known and is a leader in the computer vision community. All of the course materials were made...Systems Center Pacific (SSC Pacific). The machine learning community began organizing itself in 2012, which inspired a group of people to study an online...labor for the participants to study the material alongside their project work. This report documents the activities of the course along with some

Job Grading Standard for Machinist, WG 3414.

ERIC Educational Resources Information Center

Civil Service Commission, Washington, DC. Bureau of Policies and Standards.

The standard covers nonsupervisory work involved in the manufacture and repair of parts and items of equipment which require the use of various types of standard and special machine tools and their attachments to machine metals, metal alloys, and other materials. The work requires skills ranging from initial planning of necessary work sequences to…

Report from the MPP Working Group to the NASA Associate Administrator for Space Science and Applications

NASA Technical Reports Server (NTRS)

Fischer, James R.; Grosch, Chester; Mcanulty, Michael; Odonnell, John; Storey, Owen

1987-01-01

NASA's Office of Space Science and Applications (OSSA) gave a select group of scientists the opportunity to test and implement their computational algorithms on the Massively Parallel Processor (MPP) located at Goddard Space Flight Center, beginning in late 1985. One year later, the Working Group presented its report, which addressed the following: algorithms, programming languages, architecture, programming environments, the way theory relates, and performance measured. The findings point to a number of demonstrated computational techniques for which the MPP architecture is ideally suited. For example, besides executing much faster on the MPP than on conventional computers, systolic VLSI simulation (where distances are short), lattice simulation, neural network simulation, and image problems were found to be easier to program on the MPP's architecture than on a CYBER 205 or even a VAX. The report also makes technical recommendations covering all aspects of MPP use, and recommendations concerning the future of the MPP and machines based on similar architectures, expansion of the Working Group, and study of the role of future parallel processors for space station, EOS, and the Great Observatories era.

USSR Report, Kommunist, No. 13, September 1986.

DTIC Science & Technology

1987-01-07

all-union) program for specialization of NPO and industrial enterprises and their scientific research institutes and design bureaus could play a major...machine tools with numerical programming (ChPU), processing centers, automatic machines and groups of automatic machines controlled by computers, and...automatic lines, computer- controlled groups of equipment, comprehensively automated shops and sections) is the most important feature of high technical

[A field study on the work load and muscle fatigue at neck-shoulder in female sewing machine operators by using surface electromyography].

PubMed

Zhang, Fei-ruo; Wang, Sheng; He, Li-hua; Zhang, Ying; Wu, Shan-shan; Li, Jing-yun; Hu, Guang-yi; Ye, Kang-ping

2011-03-01

To study neck and shoulder work-related muscle fatigue of female sewing machine operators. 18 health female sewing machine operators without musculoskeletal disorders work in Beijing garment industry factory as volunteers in participate of this study. The maximal voluntary contraction (MVC) and 20% MVC of bilateral upper trapezium and cervical erectors spinae was tested before sewing operations, then the whole 20 time windows (1 time window = 10 min) sewing machine operations was monitored and the surface electromyography (sEMG) signals simultaneously was recorded after monitoring the 20%MVC was tested. Use amplitude analysis method to reduction recorded EMG signals. During work, the median load for the left cervical erector spinae (LCES), right cervical erector spinae (RCES), left upper trapezium (LUT) and right upper trapezium (RUT) respectively was 6.78 ± 1.05, 6.94 ± 1.12, 5.68 ± 2.56 and 6.47 ± 3.22, work load of right is higher than the left; static load analysis indicated the value of RMS(20%MVC) before work was higher than that value after work, the increase of right CES and UT RMS(20%MVC) was more; the largest 20%MVE of bilateral CES occurred at 20th time window, and that of bilateral UT happened at 16th. The work load of female sewing machine operators is sustained "static" load, and work load of right neck-shoulder is higher than left, right neck-shoulder muscle is more fatigable and much serious once fatigued.

Failure mode and effects analysis of the universal anaesthesia machine in two tertiary care hospitals in Sierra Leone

PubMed Central

Rosen, M. A.; Sampson, J. B.; Jackson, E. V.; Koka, R.; Chima, A. M.; Ogbuagu, O. U.; Marx, M. K.; Koroma, M.; Lee, B. H.

2014-01-01

Background Anaesthesia care in developed countries involves sophisticated technology and experienced providers. However, advanced machines may be inoperable or fail frequently when placed into the austere medical environment of a developing country. Failure mode and effects analysis (FMEA) is a method for engaging local staff in identifying real or potential breakdowns in processes or work systems and to develop strategies to mitigate risks. Methods Nurse anaesthetists from the two tertiary care hospitals in Freetown, Sierra Leone, participated in three sessions moderated by a human factors specialist and an anaesthesiologist. Sessions were audio recorded, and group discussion graphically mapped by the session facilitator for analysis and commentary. These sessions sought to identify potential barriers to implementing an anaesthesia machine designed for austere medical environments—the universal anaesthesia machine (UAM)—and also engaging local nurse anaesthetists in identifying potential solutions to these barriers. Results Participating Sierra Leonean clinicians identified five main categories of failure modes (resource availability, environmental issues, staff knowledge and attitudes, and workload and staffing issues) and four categories of mitigation strategies (resource management plans, engaging and educating stakeholders, peer support for new machine use, and collectively advocating for needed resources). Conclusions We identified factors that may limit the impact of a UAM and devised likely effective strategies for mitigating those risks. PMID:24833727

Variability in the skin exposure of machine operators exposed to cutting fluids.

PubMed

Wassenius, O; Järvholm, B; Engström, T; Lillienberg, L; Meding, B

1998-04-01

This study describes a new technique for measuring skin exposure to cutting fluids and evaluates the variability of skin exposure among machine operators performing cyclic (repetitive) work. The technique is based on video recording and subsequent analysis of the video tape by means of computer-synchronized video equipment. The time intervals at which the machine operator's hand was exposed to fluid were registered, and the total wet time of the skin was calculated by assuming different evaporation times for the fluid. The exposure of 12 operators with different work methods was analyzed in 6 different workshops, which included a range of machine types, from highly automated metal cutting machines (ie, actual cutting and chip removal machines) requiring operator supervision to conventional metal cutting machines, where the operator was required to maneuver the machine and manually exchange products. The relative wet time varied between 0% and 100%. A significant association between short cycle time and high relative wet time was noted. However, there was no relationship between the degree of automatization of the metal cutting machines and wet time. The study shows that skin exposure to cutting fluids can vary considerably between machine operators involved in manufacturing processes using different types of metal cutting machines. The machine type was not associated with dermal wetness. The technique appears to give objective information about dermal wetness.

Metalworking and machining fluids

DOEpatents

Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

2010-10-12

Improved boron-based metal working and machining fluids. Boric acid and boron-based additives that, when mixed with certain carrier fluids, such as water, cellulose and/or cellulose derivatives, polyhydric alcohol, polyalkylene glycol, polyvinyl alcohol, starch, dextrin, in solid and/or solvated forms result in improved metalworking and machining of metallic work pieces. Fluids manufactured with boric acid or boron-based additives effectively reduce friction, prevent galling and severe wear problems on cutting and forming tools.

Hazard perception and occupational injuries in the welders and lathe machine operators of Rawalpindi and Islamabad.

PubMed

Shaikh, M A

2001-02-01

To study the prevalence of occupational injuries in the welders and lathe machine operators and their hazard perception. This study was conducted in the welders and lathe machine operators working in the welding and metal working shops in Rawalpindi and Islamabad. A cross-sectional survey was conducted by two trained health interviewers using uniform questionnaire with both close and open-ended questions. Two hundred and eight welders and 104 lathe machine operators were interviewed. Thirty nine (18.7%) welders and 27 (26%) lathe machine operators reported an injury in the past three months, while 63 (30.3%) welders and 76 (73.8%) lathe machine operators reported sustaining an injury in the past twelve months. However, only half of the welders and 31 (29.8%) lathe machine operators believed that their occupation was hazardous for health. For effective public health policy there is a need preventive education and enforcement of safety regulations for the informal occupational sector in Pakistan.

A deviation based assessment methodology for multiple machine health patterns classification and fault detection

NASA Astrophysics Data System (ADS)

Jia, Xiaodong; Jin, Chao; Buzza, Matt; Di, Yuan; Siegel, David; Lee, Jay

2018-01-01

Successful applications of Diffusion Map (DM) in machine failure detection and diagnosis have been reported in several recent studies. DM provides an efficient way to visualize the high-dimensional, complex and nonlinear machine data, and thus suggests more knowledge about the machine under monitoring. In this paper, a DM based methodology named as DM-EVD is proposed for machine degradation assessment, abnormality detection and diagnosis in an online fashion. Several limitations and challenges of using DM for machine health monitoring have been analyzed and addressed. Based on the proposed DM-EVD, a deviation based methodology is then proposed to include more dimension reduction methods. In this work, the incorporation of Laplacian Eigen-map and Principal Component Analysis (PCA) are explored, and the latter algorithm is named as PCA-Dev and is validated in the case study. To show the successful application of the proposed methodology, case studies from diverse fields are presented and investigated in this work. Improved results are reported by benchmarking with other machine learning algorithms.

Research in Chinese-English Machine Translation. Final Report.

ERIC Educational Resources Information Center

Wang, William S-Y.; And Others

This report documents results of a two-year effort toward the study and investigation of the design of a prototype system for Chinese-English machine translation in the general area of physics. Previous work in Chinese-English machine translation is reviewed. Grammatical considerations in machine translation are discussed and detailed aspects of…

18. Photocopy of Photograph (From Bethlehem Shipbuilding Ltd., New York, ...

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

18. Photocopy of Photograph (From Bethlehem Shipbuilding Ltd., New York, New York, 1919) C.1918 PHOTOGRAPH OF CONSTRUCTION WORK IN PROGRESS WITH MACHINE SHOP IN BACKGROUND - Union Iron Works Turbine Machine Shop, 2200 Webster Street, Alameda, Alameda County, CA

Influence of non-edible vegetable based oil as cutting fluid on chip, surface roughness and cutting force during drilling operation of Mild Steel

NASA Astrophysics Data System (ADS)

Susmitha, M.; Sharan, P.; Jyothi, P. N.

2016-09-01

Friction between work piece-cutting tool-chip generates heat in the machining zone. The heat generated reduces the tool life, increases surface roughness and decreases the dimensional sensitiveness of work material. This can be overcome by using cutting fluids during machining. They are used to provide lubrication and cooling effects between cutting tool and work piece and cutting tool and chip during machining operation. As a result, important benefits would be achieved such longer tool life, easy chip flow and higher machining quality in the machining processes. Non-edible vegetable oils have received considerable research attention in the last decades owing to their remarkable improved tribological characteristics and due to increasing attention to environmental issues, have driven the lubricant industry toward eco friendly products from renewable sources. In the present work, different non-edible vegetable oils are used as cutting fluid during drilling of Mild steel work piece. Non-edible vegetable oils, used are Karanja oil (Honge), Neem oil and blend of these two oils. The effect of these cutting fluids on chip formation, surface roughness and cutting force are investigated and the results obtained are compared with results obtained with petroleum based cutting fluids and dry conditions.

Machine safety: proper safeguarding techniques.

PubMed

Martin, K J

1992-06-01

1. OSHA mandates certain safeguarding of machinery to prevent accidents and protect machine operators. OSHA specifies moving parts that must be guarded and sets criteria for the guards. 2. A 1989 OSHA standard for lockout/tagout requires locking the energy source during maintenance, periodically inspecting for power transmission, and training maintenance workers. 3. In an amputation emergency, first aid for cardiopulmonary resuscitation, shock, and bleeding are the first considerations. The amputated part should be wrapped in moist gauze, placed in a sealed plastic bag, and placed in a container of 50% water and 50% ice for transport. 4. The role of the occupational health nurse in machine safety is to conduct worksite analyses to identify proper safeguarding and to communicate deficiencies to appropriate personnel; to train workers in safe work practices and observe compliance in the use of machine guards; to provide care to workers injured by machines; and to reinforce safe work practices among machine operators.

IPv6 Security

NASA Astrophysics Data System (ADS)

Babik, M.; Chudoba, J.; Dewhurst, A.; Finnern, T.; Froy, T.; Grigoras, C.; Hafeez, K.; Hoeft, B.; Idiculla, T.; Kelsey, D. P.; López Muñoz, F.; Martelli, E.; Nandakumar, R.; Ohrenberg, K.; Prelz, F.; Rand, D.; Sciabà, A.; Tigerstedt, U.; Traynor, D.; Wartel, R.

2017-10-01

IPv4 network addresses are running out and the deployment of IPv6 networking in many places is now well underway. Following the work of the HEPiX IPv6 Working Group, a growing number of sites in the Worldwide Large Hadron Collider Computing Grid (WLCG) are deploying dual-stack IPv6/IPv4 services. The aim of this is to support the use of IPv6-only clients, i.e. worker nodes, virtual machines or containers. The IPv6 networking protocols while they do contain features aimed at improving security also bring new challenges for operational IT security. The lack of maturity of IPv6 implementations together with the increased complexity of some of the protocol standards raise many new issues for operational security teams. The HEPiX IPv6 Working Group is producing guidance on best practices in this area. This paper considers some of the security concerns for WLCG in an IPv6 world and presents the HEPiX IPv6 working group guidance for the system administrators who manage IT services on the WLCG distributed infrastructure, for their related site security and networking teams and for developers and software engineers working on WLCG applications.

The production deployment of IPv6 on WLCG

NASA Astrophysics Data System (ADS)

Bernier, J.; Campana, S.; Chadwick, K.; Chudoba, J.; Dewhurst, A.; Eliáš, M.; Fayer, S.; Finnern, T.; Grigoras, C.; Hartmann, T.; Hoeft, B.; Idiculla, T.; Kelsey, D. P.; López Muñoz, F.; Macmahon, E.; Martelli, E.; Millar, A. P.; Nandakumar, R.; Ohrenberg, K.; Prelz, F.; Rand, D.; Sciabà, A.; Tigerstedt, U.; Voicu, R.; Walker, C. J.; Wildish, T.

2015-12-01

The world is rapidly running out of IPv4 addresses; the number of IPv6 end systems connected to the internet is increasing; WLCG and the LHC experiments may soon have access to worker nodes and/or virtual machines (VMs) possessing only an IPv6 routable address. The HEPiX IPv6 Working Group has been investigating, testing and planning for dual-stack services on WLCG for several years. Following feedback from our working group, many of the storage technologies in use on WLCG have recently been made IPv6-capable. This paper presents the IPv6 requirements, tests and plans of the LHC experiments together with the tests performed on the group's IPv6 test-bed. This is primarily aimed at IPv6-only worker nodes or VMs accessing several different implementations of a global dual-stack federated storage service. Finally the plans for deployment of production dual-stack WLCG services are presented.

Investigating the impact of a LEGO(TM)-based, engineering-oriented curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines

NASA Astrophysics Data System (ADS)

Marulcu, Ismail

This mixed method study examined the impact of a LEGO-based, engineering-oriented curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. This study takes a social constructivist theoretical stance that science learning involves learning scientific concepts and their relations to each other. From this perspective, students are active participants, and they construct their conceptual understanding through the guidance of their teacher. With the goal of better understanding the use of engineering education materials in classrooms the National Academy of Engineering and National Research Council in the book "Engineering in K-12 Education" conducted an in-depth review of the potential benefits of including engineering in K--12 schools as (a) improved learning and achievement in science and mathematics, (b) increased awareness of engineering and the work of engineers, (c) understanding of and the ability to engage in engineering design, (d) interest in pursuing engineering as a career, and (e) increased technological literacy (Katehi, Pearson, & Feder, 2009). However, they also noted a lack of reliable data and rigorous research to support these assertions. Data sources included identical written tests and interviews, classroom observations and videos, teacher interviews, and classroom artifacts. To investigate the impact of the design-based simple machines curriculum compared to the scientific inquiry-based simple machines curriculum on student learning outcomes, I compared the control and the experimental groups' scores on the tests and interviews by using ANCOVA. To analyze and characterize the classroom observation videotapes, I used Jordan and Henderson's (1995) method and divide them into episodes. My 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' content learning. I also found that students in the engineering group outperformed students in the control group in regards to their ability to answer open-ended questions when interviewed. Implications for students' science content learning and teachers' professional development are discussed.

Application of Electro Chemical Machining for materials used in extreme conditions

NASA Astrophysics Data System (ADS)

Pandilov, Z.

2018-03-01

Electro-Chemical Machining (ECM) is the generic term for a variety of electrochemical processes. ECM is used to machine work pieces from metal and metal alloys irrespective of their hardness, strength or thermal properties, through the anodic dissolution, in aerospace, automotive, construction, medical equipment, micro-systems and power supply industries. The Electro Chemical Machining is extremely suitable for machining of materials used in extreme conditions. General overview of the Electro-Chemical Machining and its application for different materials used in extreme conditions is presented.

Effects of retrofit emission controls and work practices on perchloroethylene exposures in small dry-cleaning shops.

PubMed

Ewers, Lynda M; Ruder, Avima M; Petersen, Martin R; Earnest, G Scott; Goldenhar, Linda M

2002-02-01

The effectiveness of commercially available interventions for reducing workers' perchloroethylene exposures in three small dry-cleaning shops was evaluated. Depending upon machine configuration, the intervention consisted of the addition of either a refrigerated condenser or a closed-loop carbon adsorber to the existing dry-cleaning machine. These relatively inexpensive (less than $5000) engineering controls were designed to reduce perchloroethylene emissions when dry-cleaning machine doors were opened for loading or unloading. Effectiveness of the interventions was judged by comparing pre- and postintervention perchloroethylene exposures using three types of measurements in each shop: (1) full-shift, personal breathing zone, air monitoring, (2) next-morning, end-exhaled worker breath concentrations of perchloroethylene, and (3) differences in the end-exhaled breath perchloroethylene concentrations before and after opening the dry-cleaning machine door. In general, measurements supported the hypothesis that machine operators' exposures to perchloroethylene can be reduced. However, work practices, especially maintenance practices, influenced exposures more than was originally anticipated. Only owners of dry-cleaning machines in good repair, with few leaks, should consider retrofitting them, and only after consultation with their machine's manufacturer. If machines are in poor condition, a new machine or alternative technology should be considered. Shop owners and employees should never circumvent safety features on dry-cleaning machines.

Using Trained Pixel Classifiers to Select Images of Interest

NASA Technical Reports Server (NTRS)

Mazzoni, D.; Wagstaff, K.; Castano, R.

2004-01-01

We present a machine-learning-based approach to ranking images based on learned priorities. Unlike previous methods for image evaluation, which typically assess the value of each image based on the presence of predetermined specific features, this method involves using two levels of machine-learning classifiers: one level is used to classify each pixel as belonging to one of a group of rather generic classes, and another level is used to rank the images based on these pixel classifications, given some example rankings from a scientist as a guide. Initial results indicate that the technique works well, producing new rankings that match the scientist's rankings significantly better than would be expected by chance. The method is demonstrated for a set of images collected by a Mars field-test rover.

A field study of exposure to whole-body vibration due to agricultural machines in a full-time rice farmer over one year.

PubMed

Tsujimura, Hiroji; Taoda, Kazushi; Kitahara, Teruyo

2015-01-01

The aims of this study were to clarify in detail the levels of whole-body vibration (WBV) exposure from a variety of agricultural machines in a rice farmer over one year, and to evaluate the daily level of exposure compared with European and Japanese threshold limits. The subject was a full-time, male rice farmer. We measured vibration accelerations on the seat pan and at the seat base of four tractors with various implements attached, one rice-planting machine, two combine harvesters, produced by the same manufacturer, and one truck used for transportation of agricultural machines. The position and velocity of the machines were recorded in parallel with WBV measurements. In addition, during the year starting in April 2010, the subject completed a questionnaire regarding his work (date, place, content, hours worked, machines used). We calculated the daily exposure to WBV, A(8), on all the days on which the subject used the agricultural machines. The WBV magnitude in farm fields was relatively high during tasks with high velocity and heavy mechanical load on the machine, and had no dominant axis. The subject worked for 159 days using the agricultural machines during the year, and the proportion of days on which A(8) values exceeded the thresholds was 90% for the Japan occupational exposure limit and 24% for the EU exposure action value. Our findings emphasize the need for rice farmers to have health management strategies suited to the farming seasons and measures to reduce WBV exposure during each farm task.

Diesel Engine Technician

ERIC Educational Resources Information Center

Tech Directions, 2010

2010-01-01

Diesel engine technicians maintain and repair the engines that power transportation equipment such as heavy trucks, trains, buses, and locomotives. Some technicians work mainly on farm machines, ships, compressors, and pumps. Others work mostly on construction equipment such as cranes, power shovels, bulldozers, and paving machines. This article…

Wire electric-discharge machining and other fabrication techniques

NASA Technical Reports Server (NTRS)

Morgan, W. H.

1983-01-01

Wire electric discharge machining and extrude honing were used to fabricate a two dimensional wing for cryogenic wind tunnel testing. Electric-discharge cutting is done with a moving wire electrode. The cut track is controlled by means of a punched-tape program and the cutting feed is regulated according to the progress of the work. Electric-discharge machining involves no contact with the work piece, and no mechanical force is exerted. Extrude hone is a process for honing finish-machined surfaces by the extrusion of an abrasive material (silly putty), which is forced through a restrictive fixture. The fabrication steps are described and production times are given.

Machine Learning Based Malware Detection

DTIC Science & Technology

2015-05-18

A TRIDENT SCHOLAR PROJECT REPORT NO. 440 Machine Learning Based Malware Detection by Midshipman 1/C Zane A. Markel, USN...COVERED (From - To) 4. TITLE AND SUBTITLE Machine Learning Based Malware Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...suitably be projected into realistic performance. This work explores several aspects of machine learning based malware detection . First, we

29 CFR 570.55 - Occupations involved in the operation of power-driven woodworking machines (Order 5).

Code of Federal Regulations, 2011 CFR

2011-07-01

... woodworking machines (Order 5). 570.55 Section 570.55 Labor Regulations Relating to Labor (Continued) WAGE AND... woodworking machines (Order 5). (a) Finding and declaration of fact. The following occupations involved in the operation of power-driven wood-working machines are particularly hazardous for minors between 16 and 18...

Stochastic subset selection for learning with kernel machines.

PubMed

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Evaluating Effects of Heat Stress on Cognitive Function among Workers in a Hot Industry.

PubMed

Mazloumi, Adel; Golbabaei, Farideh; Mahmood Khani, Somayeh; Kazemi, Zeinab; Hosseini, Mostafa; Abbasinia, Marzieh; Farhang Dehghan, Somayeh

2014-01-01

Heat stress, as one of the most common occupational health problems, can impair operators' cognitive processes. The aim of this study was to evaluate the impact of thermal stress on cognitive function among workers in a hot industry. In this cross-sectional study conducted in Malibel Saipa Company in 2013, workers were assigned into two groups: one group were exposed to heat stress (n=35), working in casting unit and the other group working in machining unit (n=35) with a normal air conditioning. Wet Bulb Globe Temperature was measured at three heights of ankle, abdomen, and head. In order to evaluate the effects of heat stress on attention and reaction time, Stroop tests 1, 2, and 3 were conducted before starting the work and during the work. A significant positive correlation was observed between WBGT and test duration (P=0.01) and reaction time of Stroop test 3 (P=0.047), and between number of errors in Stroop tests 1, 2, and 3, during the work (P= 0.001). Moreover, Stroop test 3 showed a significant higher score for both test duration and reaction time of workers in case group. RESULTS of the present study, conducted in a real work environment, confirmed the impairment of cognitive functions, including selective attention and reaction time, under heat stress conditions.

Identifying ecological "sweet spots" underlying cyanobacteria functional group dynamics from long-term observations using a statistical machine learning approach

NASA Astrophysics Data System (ADS)

Nelson, N.; Munoz-Carpena, R.; Phlips, E. J.

2017-12-01

Diversity in the eco-physiological adaptations of cyanobacteria genera creates challenges for water managers who are tasked with developing appropriate actions for controlling not only the intensity and frequency of cyanobacteria blooms, but also reducing the potential for blooms of harmful taxa (e.g., toxin producers, N2 fixers). Compounding these challenges, the efficacy of nutrient management strategies (phosphorus-only versus nitrogen-and-phosphorus) for cyanobacteria bloom abatement is the subject of an ongoing debate, which increases uncertainty associated with bloom mitigation decision-making. In this work, we analyze a unique long-term (17-year) dataset composed of monthly observations of cyanobacteria genera abundances, zooplankton abundances, water quality, and flow from Lake George, a bloom-impacted flow-through lake of the St. Johns River (FL, USA). Using the Random Forests machine learning algorithm, an assumption-free ensemble modeling approach, the dataset was evaluated to quantify and characterize relationships between environmental conditions and seven cyanobacteria groupings: five genera (Anabaena, Cylindrospermopsis, Lyngbya, Microcystis, and Oscillatoria) and two functional groups (N2 fixers and non-fixers). Results highlight the selectivity of nitrogen in describing genera and functional group dynamics, and potential for physical effects to limit the efficacy of nutrient management as a mechanism for cyanobacteria bloom mitigation.

The Relationship between Injury and Socioeconomic Status in Reference to the Fourth Korean National Health and Nutrition Examination Survey

PubMed Central

2014-01-01

Objectives This study aims to investigate the relationship between the total injury experience rate and socioeconomic status based on the fourth Korea National Health and Nutrition Examination Survey (KNHANES). Methods By analyzing data from the fourth KNHANES conducted from 2007 to 2009, we estimated the injury experience rate according to socioeconomic status, including the occupational characteristics of 11,837 subjects. Setting the injury experience rate as a dependent variable and socioeconomic status as an independent variable, we performed logistic regression to calculate odds ratios reflecting the likelihood of injury according to socioeconomic status while controlling for relevant covariates. Results In 797 subjects who had injury experience over the past 1 year, 290 persons (36.4%) had a work-related injury. As their income, home value, and educational status increased, their injury experiences decreased. Among occupational groups, the craft, equipment, machine operating, and assembling workers showed the highest rate (10.6%) of injury experience, and the lowest rate (5.7%) was found in the unemployed group. After adjusting for the confounding variables, the experience of injury was significantly related to several socioeconomic factors: high income (OR = 0.54; 95% CI: 0.34-0.86), high home value (OR = 0.65; 95% CI: 0.43-0.96), low education status (OR = 1.28; 95% CI: 1.07-1.52), and specific occupations such as craft, equipment, machine operating, and assembling work (OR = 1.99; 95% CI: 1.60-2.47), skilled agriculture, forestry and fishery work (OR = 1.43; 95% CI: 1.02-2.01), and simple labor (OR = 1.38; 95% CI: 1.04-1.82). Conclusions The injury experience rate differed depending on the socioeconomic status. A negative correlation was found between the injury experience rate and income, low home value, and education level. Moreover, a higher rate of injury experience was found in occupation groups and physical worker groups in comparison to the unemployed group and white-collar worker groups. This study would be useful in selecting appropriate priorities for injury management in Korea. PMID:24472308

Learning of perceptual grouping for object segmentation on RGB-D data☆

PubMed Central

Richtsfeld, Andreas; Mörwald, Thomas; Prankl, Johann; Zillich, Michael; Vincze, Markus

2014-01-01

Object segmentation of unknown objects with arbitrary shape in cluttered scenes is an ambitious goal in computer vision and became a great impulse with the introduction of cheap and powerful RGB-D sensors. We introduce a framework for segmenting RGB-D images where data is processed in a hierarchical fashion. After pre-clustering on pixel level parametric surface patches are estimated. Different relations between patch-pairs are calculated, which we derive from perceptual grouping principles, and support vector machine classification is employed to learn Perceptual Grouping. Finally, we show that object hypotheses generation with Graph-Cut finds a globally optimal solution and prevents wrong grouping. Our framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. We also tackle the problem of segmenting objects when they are partially occluded. The work is evaluated on publicly available object segmentation databases and also compared with state-of-the-art work of object segmentation. PMID:24478571

Open NASA Earth Exchange (OpenNEX): Strategies for enabling cross organization collaboration in the earth sciences

NASA Astrophysics Data System (ADS)

Michaelis, A.; Ganguly, S.; Nemani, R. R.; Votava, P.; Wang, W.; Lee, T. J.; Dungan, J. L.

2014-12-01

Sharing community-valued codes, intermediary datasets and results from individual efforts with others that are not in a direct funded collaboration can be a challenge. Cross organization collaboration is often impeded due to infrastructure security constraints, rigid financial controls, bureaucracy, and workforce nationalities, etc., which can force groups to work in a segmented fashion and/or through awkward and suboptimal web services. We show how a focused community may come together, share modeling and analysis codes, computing configurations, scientific results, knowledge and expertise on a public cloud platform; diverse groups of researchers working together at "arms length". Through the OpenNEX experimental workshop, users can view short technical "how-to" videos and explore encapsulated working environment. Workshop participants can easily instantiate Amazon Machine Images (AMI) or launch full cluster and data processing configurations within minutes. Enabling users to instantiate computing environments from configuration templates on large public cloud infrastructures, such as Amazon Web Services, may provide a mechanism for groups to easily use each others work and collaborate indirectly. Moreover, using the public cloud for this workshop allowed a single group to host a large read only data archive, making datasets of interest to the community widely available on the public cloud, enabling other groups to directly connect to the data and reduce the costs of the collaborative work by freeing other individual groups from redundantly retrieving, integrating or financing the storage of the datasets of interest.

Performance of solar refrigerant ejector refrigerating machine

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

Al-Khalidy, N.A.H.

1997-12-31

In this work a detailed analysis for the ideal, theoretical, and experimental performance of a solar refrigerant ejector refrigerating machine is presented. A comparison of five refrigerants to select a desirable one for the system is made. The theoretical analysis showed that refrigerant R-113 is more suitable for use in the system. The influence of the boiler, condenser, and evaporator temperatures on system performance is investigated experimentally in a refrigerant ejector refrigerating machine using R-113 as a working refrigerant.

KSC-2012-3081

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3076

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3080

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3079

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

Quantify work load and muscle functional activation patterns in neck-shoulder muscles of female sewing machine operators using surface electromyogram.

PubMed

Zhang, Fei-Ruo; He, Li-Hua; Wu, Shan-Shan; Li, Jing-Yun; Ye, Kang-Pin; Wang, Sheng

2011-11-01

Work-related musculoskeletal disorders (WMSDs) have high prevalence in sewing machine operators employed in the garment industry. Long work duration, sustained low level work and precise hand work are the main risk factors of neck-shoulder disorders for sewing machine operators. Surface electromyogram (sEMG) offers a valuable tool to determine muscle activity (internal exposure) and quantify muscular load (external exposure). During sustained and/or repetitive muscle contractions, typical changes of muscle fatigue in sEMG, as an increase in amplitude or a decrease as a shift in spectrum towards lower frequencies, can be observed. In this paper, we measured and quantified the muscle load and muscular activity patterns of neck-shoulder muscles in female sewing machine operators during sustained sewing machine operating tasks using sEMG. A total of 18 healthy women sewing machine operators volunteered to participate in this study. Before their daily sewing machine operating task, we measured the maximal voluntary contractions (MVC) and 20%MVC of bilateral cervical erector spinae (CES) and upper trapezius (UT) respectively, then the sEMG signals of bilateral UT and CES were monitored and recorded continuously during 200 minutes of sustained sewing machine operating simultaneously which equals to 20 time windows with 10 minutes as one time window. After 200 minutes' work, we retest 20%MVC of four neck-shoulder muscles and recorded the sEMG signals. Linear analysis, including amplitude probability distribution frequency (APDF), amplitude analysis parameters such as roof mean square (RMS) and spectrum analysis parameter as median frequency (MF), were used to calculate and indicate muscle load and muscular activity of bilateral CES and UT. During 200 minutes of sewing machine operating, the median load for the left cervical erector spinae (LCES), right cervical erector spinae (RCES), left upper trapezius (LUT) and right upper trapezius (RUT) were 6.78%MVE, 6.94%MVE, 6.47%MVE and 5.68%MVE, respectively. Work load of right muscles are significantly higher than that of the left muscles (P < 0.05); sEMG signal analysis of isometric contractions indicated that the amplitude value before operating was significantly higher than that of after work (P < 0.01), and the spectrum value of bilateral CES and UT were significantly lower than those of after work (P < 0.01); according to the sEMG signal data of 20 time windows, with operating time pass by, the muscle activity patterns of bilateral CES and UT showed dynamic changes, the maximal amplitude of LCES, RCES, LUT occurred at the 20th time window, RUT at 16th time window, spectrum analysis showed that the lower value happened at 7th, 16th, 20th time windows. Female sewing machine operators were exposed to high sustained static load on bilateral neck-shoulder muscles; left neck and shoulder muscles were held in more static positions; the 7th, 16th, and 20th time windows were muscle fatigue period that ergonomics intervention can protocol at these periods.

Feature selection and classification of protein-protein complexes based on their binding affinities using machine learning approaches.

PubMed

Yugandhar, K; Gromiha, M Michael

2014-09-01

Protein-protein interactions are intrinsic to virtually every cellular process. Predicting the binding affinity of protein-protein complexes is one of the challenging problems in computational and molecular biology. In this work, we related sequence features of protein-protein complexes with their binding affinities using machine learning approaches. We set up a database of 185 protein-protein complexes for which the interacting pairs are heterodimers and their experimental binding affinities are available. On the other hand, we have developed a set of 610 features from the sequences of protein complexes and utilized Ranker search method, which is the combination of Attribute evaluator and Ranker method for selecting specific features. We have analyzed several machine learning algorithms to discriminate protein-protein complexes into high and low affinity groups based on their Kd values. Our results showed a 10-fold cross-validation accuracy of 76.1% with the combination of nine features using support vector machines. Further, we observed accuracy of 83.3% on an independent test set of 30 complexes. We suggest that our method would serve as an effective tool for identifying the interacting partners in protein-protein interaction networks and human-pathogen interactions based on the strength of interactions. © 2014 Wiley Periodicals, Inc.

29 CFR 570.55 - Occupations involved in the operation of power-driven woodworking machines (Order 5).

Code of Federal Regulations, 2010 CFR

2010-07-01

... woodworking machines (Order 5). 570.55 Section 570.55 Labor Regulations Relating to Labor (Continued) WAGE AND... woodworking machines (Order 5). Link to an amendment published at 75 FR 28455, May 20, 2010. (a) Finding and declaration of fact. The following occupations involved in the operation of power-driven wood-working machines...

49 CFR 214.341 - Roadway maintenance machines.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD WORKPLACE SAFETY Roadway Worker Protection § 214.341 Roadway maintenance machines. (a) Each employer shall include in its on-track safety program specific provisions for the safety of roadway workers who operate or work near roadway maintenance machines. Those...

100. COBBLER SHOP AFT LOOKING FORWARD VISIBLE ARE ...

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

100. COBBLER SHOP - AFT LOOKING FORWARD - VISIBLE ARE THE FINISHING MACHINE, DAVIS STITCHING MACHINE, SINGER SEWING MACHINE FROM TAILOR SHOP, STORAGE SHELVES, WORK BENCH AND SHOE TREE STAND. - U.S.S. HORNET, Puget Sound Naval Shipyard, Sinclair Inlet, Bremerton, Kitsap County, WA

Verification and validation of a Work Domain Analysis with turing machine task analysis.

PubMed

Rechard, J; Bignon, A; Berruet, P; Morineau, T

2015-03-01

While the use of Work Domain Analysis as a methodological framework in cognitive engineering is increasing rapidly, verification and validation of work domain models produced by this method are becoming a significant issue. In this article, we propose the use of a method based on Turing machine formalism named "Turing Machine Task Analysis" to verify and validate work domain models. The application of this method on two work domain analyses, one of car driving which is an "intentional" domain, and the other of a ship water system which is a "causal domain" showed the possibility of highlighting improvements needed by these models. More precisely, the step by step analysis of a degraded task scenario in each work domain model pointed out unsatisfactory aspects in the first modelling, like overspecification, underspecification, omission of work domain affordances, or unsuitable inclusion of objects in the work domain model. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Eclipse prediction on the ancient Greek astronomical calculating machine known as the Antikythera Mechanism.

PubMed

Freeth, Tony

2014-01-01

The ancient Greek astronomical calculating machine, known as the Antikythera Mechanism, predicted eclipses, based on the 223-lunar month Saros cycle. Eclipses are indicated on a four-turn spiral Saros Dial by glyphs, which describe type and time of eclipse and include alphabetical index letters, referring to solar eclipse inscriptions. These include Index Letter Groups, describing shared eclipse characteristics. The grouping and ordering of the index letters, the organization of the inscriptions and the eclipse times have previously been unsolved. A new reading and interpretation of data from the back plate of the Antikythera Mechanism, including the glyphs, the index letters and the eclipse inscriptions, has resulted in substantial changes to previously published work. Based on these new readings, two arithmetical models are presented here that explain the complete eclipse prediction scheme. The first model solves the glyph distribution, the grouping and anomalous ordering of the index letters and the structure of the inscriptions. It also implies the existence of lost lunar eclipse inscriptions. The second model closely matches the glyph times and explains the four-turn spiral of the Saros Dial. Together, these models imply a surprisingly early epoch for the Antikythera Mechanism. The ancient Greeks built a machine that can predict, for many years ahead, not only eclipses but also a remarkable array of their characteristics, such as directions of obscuration, magnitude, colour, angular diameter of the Moon, relationship with the Moon's node and eclipse time. It was not entirely accurate, but it was an astonishing achievement for its era.

Eclipse Prediction on the Ancient Greek Astronomical Calculating Machine Known as the Antikythera Mechanism

PubMed Central

Freeth, Tony

2014-01-01

The ancient Greek astronomical calculating machine, known as the Antikythera Mechanism, predicted eclipses, based on the 223-lunar month Saros cycle. Eclipses are indicated on a four-turn spiral Saros Dial by glyphs, which describe type and time of eclipse and include alphabetical index letters, referring to solar eclipse inscriptions. These include Index Letter Groups, describing shared eclipse characteristics. The grouping and ordering of the index letters, the organization of the inscriptions and the eclipse times have previously been unsolved. A new reading and interpretation of data from the back plate of the Antikythera Mechanism, including the glyphs, the index letters and the eclipse inscriptions, has resulted in substantial changes to previously published work. Based on these new readings, two arithmetical models are presented here that explain the complete eclipse prediction scheme. The first model solves the glyph distribution, the grouping and anomalous ordering of the index letters and the structure of the inscriptions. It also implies the existence of lost lunar eclipse inscriptions. The second model closely matches the glyph times and explains the four-turn spiral of the Saros Dial. Together, these models imply a surprisingly early epoch for the Antikythera Mechanism. The ancient Greeks built a machine that can predict, for many years ahead, not only eclipses but also a remarkable array of their characteristics, such as directions of obscuration, magnitude, colour, angular diameter of the Moon, relationship with the Moon’s node and eclipse time. It was not entirely accurate, but it was an astonishing achievement for its era. PMID:25075747

Conversion of Mass Storage Hierarchy in an IBM Computer Network

DTIC Science & Technology

1989-03-01

storage devices GUIDE IBM users’ group for DOS operating systems IBM International Business Machines IBM 370/145 CPU introduced in 1970 IBM 370/168 CPU...February 12, 1985, Information Systems Group, International Business Machines Corporation. "IBM 3090 Processor Complex" and 񓼪 Mass Storage System...34 Mainframe Journal, pp. 15-26, 64-65, Dallas, Texas, September-October 1987. 3. International Business Machines Corporation, Introduction to IBM 3S80 Storage

A New Approach to Geoengineering: Manna From Heaven

NASA Astrophysics Data System (ADS)

Ellery, Alex

2015-04-01

Geo-engineering, although controversial, has become an emerging factor in coping with climate change. Although most are terrestrial-based technologies, I focus on a space-based approach implemented through a solar shield system. I present several new elements that essentially render the high-cost criticism moot. Of special relevance are two seemingly unrelated technologies - the Resource Prospector Mission (RPM) to the Moon in 2018 that shall implement a technology demonstration of simple material resource extraction from lunar regolith, and the emergence of multi-material 3D printing technology that promises unprecedented robotic manufacturing capabilities. My research group has begun theoretical and experimentation work in developing the concept of a 3D printed electric motor system from lunar-type resources. The electric motor underlies every universal mechanical machine. Together with 3D printed electronics, I submit that this would enable self-replicating machines to be realised. A detailed exposition on how this may be achieved will be outlined. Such self-replicating machines could construct the spacecraft required to implement a solar shield and solar power satellites in large numbers from lunar resources with the same underlying technologies at extremely low cost.

Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

PubMed

Kebschull, Moritz; Papapanou, Panos N

2017-01-01

Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional patterns, beyond the mere identification of lists of features that differ between groups.Here, we demonstrate the utility of (1) supervised classification algorithms in class validation, and (2) unsupervised clustering in class discovery. We use data from our previous work that described the transcriptional profiles of gingival tissue samples obtained from subjects suffering from chronic or aggressive periodontitis (1) to test whether the two diagnostic entities were also characterized by differences on the molecular level, and (2) to search for a novel, alternative classification of periodontitis based on the tissue transcriptomes.Using machine learning technology, we provide evidence for diagnostic imprecision in the currently accepted classification of periodontitis, and demonstrate that a novel, alternative classification based on differences in gingival tissue transcriptomes is feasible. The outlined procedures allow for the unbiased interrogation of high-dimensional datasets for characteristic underlying classes, and are applicable to a broad range of -omics data.

Millwright Apprenticeship. Related Training Modules. 5.1-5.16 Drafting.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet, part of the instructional materials for the Oregon apprenticeship program for millwright training, contains 16 modules covering drafting. The modules provide information on the following topics: types of drawing and views, sketching, blueprint reading/working drawings, working drawings for machines and welding, machine and welding…

Classification of older adults with/without a fall history using machine learning methods.

PubMed

Lin Zhang; Ou Ma; Fabre, Jennifer M; Wood, Robert H; Garcia, Stephanie U; Ivey, Kayla M; McCann, Evan D

2015-01-01

Falling is a serious problem in an aged society such that assessment of the risk of falls for individuals is imperative for the research and practice of falls prevention. This paper introduces an application of several machine learning methods for training a classifier which is capable of classifying individual older adults into a high risk group and a low risk group (distinguished by whether or not the members of the group have a recent history of falls). Using a 3D motion capture system, significant gait features related to falls risk are extracted. By training these features, classification hypotheses are obtained based on machine learning techniques (K Nearest-neighbour, Naive Bayes, Logistic Regression, Neural Network, and Support Vector Machine). Training and test accuracies with sensitivity and specificity of each of these techniques are assessed. The feature adjustment and tuning of the machine learning algorithms are discussed. The outcome of the study will benefit the prediction and prevention of falls.

WEST END OF SOUTH FACADE OF MACHINE SHOP No. 1. ...

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

WEST END OF SOUTH FACADE OF MACHINE SHOP No. 1. BRICK SECTION ON THE LEFT IS THE FORMER OFFICE OF THE ARMOR PLATE DIVISION BUILT IN 1899 - U.S. Steel Homestead Works, Machine Shop No. 1, Along Monongahela River, Homestead, Allegheny County, PA

Machine Learning for the Knowledge Plane

DTIC Science & Technology

2006-06-01

this idea is to combine techniques from machine learning with new architectural concepts in networking to make the internet self-aware and self...work on the machine learning portion of the Knowledge Plane. This consisted of three components: (a) we wrote a document formulating the various

Machine Trades Lab Management Guide.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Instructional Materials Lab.

This manual was developed to guide machine trades instructors and vocational supervisors in sequencing laboratory instruction and controlling the flow of work for a 2-year machine trades training program. The first part of the guide provides information on program management (program description, safety concerns, academic issues, implementation…

6. VIEW OF LATHE OF EAST END OF MACHINE SHOP ...

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

6. VIEW OF LATHE OF EAST END OF MACHINE SHOP No. 2 ADDITION. THE 78 1/2' X 100 LATHE BORES OUT CENTERS, OR TREPANNS, OF FORGING. - U.S. Steel Homestead Works, Machine Shop No. 2, Along Monongahela River, Homestead, Allegheny County, PA

Machine vision 1992-1996: technology program to promote research and its utilization in industry

NASA Astrophysics Data System (ADS)

Soini, Antti J.

1994-10-01

Machine vision technology has got a strong interest in Finnish research organizations, which is resulting in many innovative products to industry. Despite this end users were very skeptical towards machine vision and its robustness for harsh industrial environments. Therefore Technology Development Centre, TEKES, who funds technology related research and development projects in universities and individual companies, decided to start a national technology program, Machine Vision 1992 - 1996. Led by industry the program boosts research in machine vision technology and seeks to put the research results to work in practical industrial applications. The emphasis is in nationally important, demanding applications. The program will create new industry and business for machine vision producers and encourage the process and manufacturing industry to take advantage of this new technology. So far 60 companies and all major universities and research centers are working on our forty different projects. The key themes that we have are process control, robot vision and quality control.

Machine Learning

NASA Astrophysics Data System (ADS)

Hoffmann, Achim; Mahidadia, Ashesh

The purpose of this chapter is to present fundamental ideas and techniques of machine learning suitable for the field of this book, i.e., for automated scientific discovery. The chapter focuses on those symbolic machine learning methods, which produce results that are suitable to be interpreted and understood by humans. This is particularly important in the context of automated scientific discovery as the scientific theories to be produced by machines are usually meant to be interpreted by humans. This chapter contains some of the most influential ideas and concepts in machine learning research to give the reader a basic insight into the field. After the introduction in Sect. 1, general ideas of how learning problems can be framed are given in Sect. 2. The section provides useful perspectives to better understand what learning algorithms actually do. Section 3 presents the Version space model which is an early learning algorithm as well as a conceptual framework, that provides important insight into the general mechanisms behind most learning algorithms. In section 4, a family of learning algorithms, the AQ family for learning classification rules is presented. The AQ family belongs to the early approaches in machine learning. The next, Sect. 5 presents the basic principles of decision tree learners. Decision tree learners belong to the most influential class of inductive learning algorithms today. Finally, a more recent group of learning systems are presented in Sect. 6, which learn relational concepts within the framework of logic programming. This is a particularly interesting group of learning systems since the framework allows also to incorporate background knowledge which may assist in generalisation. Section 7 discusses Association Rules - a technique that comes from the related field of Data mining. Section 8 presents the basic idea of the Naive Bayesian Classifier. While this is a very popular learning technique, the learning result is not well suited for human comprehension as it is essentially a large collection of probability values. In Sect. 9, we present a generic method for improving accuracy of a given learner by generatingmultiple classifiers using variations of the training data. While this works well in most cases, the resulting classifiers have significantly increased complexity and, hence, tend to destroy the human readability of the learning result that a single learner may produce. Section 10 contains a summary, mentions briefly other techniques not discussed in this chapter and presents outlook on the potential of machine learning in the future.

On-Line Scheduling of Parallel Machines

DTIC Science & Technology

1990-11-01

machine without losing any work; this is referred to as the preemptive model. In contrast to the nonpreemptive model which we have considered in this paper...that there exists no schedule of length d. The 2-relaxed decision procedure is as follows. Put each job into the queue of the slowest machine Mk such...in their queues . If a machine’s queue is empty it takes jobs to process from the queue of the first machine that is slower than it and that has a

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

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.

Special Machines; Apparel Manufacturing: 9377.10.

ERIC Educational Resources Information Center

Dade County Public Schools, Miami, FL.

This course allows students who are interested in careers in apparel manufacturing to learn the techniques for operating the various types of special machines used for finishing garments professionally and for specialty work. Course content includes goals, specific objectives, orientation, safety practices, special machines, assembling a child's…

12. TOOL ROOM SHOWING LANDIS MACHINE CO. BOL/T THREADER (L), ...

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

12. TOOL ROOM SHOWING LANDIS MACHINE CO. BOL/T THREADER (L), OSTER MANUFACTURING CO. PIPE MASTER (R), AND OLDMAN KINK, A SHOP-MADE WELDING STRENGTH TESTER (L, BACKGROUND). VIEW NORTHEAST - Oldman Boiler Works, Office/Machine Shop, 32 Illinois Street, Buffalo, Erie County, NY

1. EAST END OF MACHINE SHOP No. 2. THE TALL ...

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

1. EAST END OF MACHINE SHOP No. 2. THE TALL STRUCTURE IS THE VERTICAL FURNACE BUILDING, AND THE TWO-STORY BRICK BUILDING WAS THE HEAT TREATING AND FORGING OFFICE. - U.S. Steel Homestead Works, Machine Shop No. 2, Along Monongahela River, Homestead, Allegheny County, PA

10. INTERIOR OF THE VERTICAL FURNACE BUILDING OF MACHINE SHOP ...

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

10. INTERIOR OF THE VERTICAL FURNACE BUILDING OF MACHINE SHOP No. 2. STRUCTURE IN THE FOREGROUND IS THE UPENDER. THE QUENCH TOWER AND FURNACES ARE IN THE BACKGROUND. - U.S. Steel Homestead Works, Machine Shop No. 2, Along Monongahela River, Homestead, Allegheny County, PA

34. INTERIOR VIEW, SAME AS ABOVE WITH THE FEEDER ROD ...

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

34. INTERIOR VIEW, SAME AS ABOVE WITH THE FEEDER ROD BEING OFFERED INTO THE MACHINE; UNLIKE THE OTHER NAIL CUTTING MACHINES, THE NAIL PLATE MUST BE HAND FLIPPED AND HAND FED WITH THIS MACHINE - LaBelle Iron Works, Thirtieth & Wood Streets, Wheeling, Ohio County, WV

Hypothermic machine perfusion permits extended cold ischemia times with improved early graft function.

PubMed

Guy, Alison; McGrogan, Damian; Inston, Nicholas; Ready, Andrew

2015-04-01

The logistics of deceased-donor renal transplants are largely affected by cold ischemia time. However, to attain successful outcomes, other issues must be considered. Extending cold ischemia time to accommodate these issues would be valuable. We investigated the role of hypothermic machine perfusion to extend cold ischaemia time. Deceased-donor kidneys were allocated to a storage method, depending on predicted time to operation. Kidneys to be transplanted from 8:00 AM to 8:00 PM in the transplant room remained in static cold storage. If predicted operating time was out of hours, the kidney was transferred to hypothermic machine perfusion and transplanted at the earliest opportunity on the dedicated transplant list. There were 74 kidneys transplanted from hypothermic machine perfusion and 101 kidneys from static cold storage. Median cold ischemia time was 23.85 hours in the hypothermic machine perfusion group, compared with 13 hours in the static cold storage group (P ≤ .0001). There were 20 kidneys (27%) from hypothermic machine perfusion that had delayed graft function, compared with 47 kidneys (47%) in the static cold storage group (P = .012). There were no other significant differences in graft or postoperative complications. This study demonstrated that improved early graft outcomes can be achieved following longer cold ischemia time by using hypothermic machine perfusion rather than static cold storage. This effect is likely multifactorial including the inherent effects of hypothermic machine perfusion, improved recipient preparation, and possibly better perioperative conditions.

Pattern Activity Clustering and Evaluation (PACE)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Banas, Christopher; Paul, Michael; Bussjager, Becky; Seetharaman, Guna

2012-06-01

With the vast amount of network information available on activities of people (i.e. motions, transportation routes, and site visits) there is a need to explore the salient properties of data that detect and discriminate the behavior of individuals. Recent machine learning approaches include methods of data mining, statistical analysis, clustering, and estimation that support activity-based intelligence. We seek to explore contemporary methods in activity analysis using machine learning techniques that discover and characterize behaviors that enable grouping, anomaly detection, and adversarial intent prediction. To evaluate these methods, we describe the mathematics and potential information theory metrics to characterize behavior. A scenario is presented to demonstrate the concept and metrics that could be useful for layered sensing behavior pattern learning and analysis. We leverage work on group tracking, learning and clustering approaches; as well as utilize information theoretical metrics for classification, behavioral and event pattern recognition, and activity and entity analysis. The performance evaluation of activity analysis supports high-level information fusion of user alerts, data queries and sensor management for data extraction, relations discovery, and situation analysis of existing data.

Machinability of Green Powder Metallurgy Components: Part I. Characterization of the Influence of Tool Wear

NASA Astrophysics Data System (ADS)

Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

2007-06-01

The green machining process is an interesting approach for solving the mediocre machining behavior of high-performance powder metallurgy (PM) steels. This process appears as a promising method for extending tool life and reducing machining costs. Recent improvements in binder/lubricant technologies have led to high green strength systems that enable green machining. So far, tool wear has been considered negligible when characterizing the machinability of green PM specimens. This inaccurate assumption may lead to the selection of suboptimum cutting conditions. The first part of this study involves the optimization of the machining parameters to minimize the effects of tool wear on the machinability in turning of green PM components. The second part of our work compares the sintered mechanical properties of components machined in green state with other machined after sintering.

Generation Mechanism of Work Hardened Surface Layer in Metal Cutting

NASA Astrophysics Data System (ADS)

Hikiji, Rikio; Kondo, Eiji; Kawagoishi, Norio; Arai, Minoru

Finish machining used to be carried out in grinding, but it is being replaced by cutting with very small undeformed chip thickness. In ultra precision process, the effects of the cutting conditions and the complicated factors on the machined surface integrity are the serious problems. In this research, work hardened surface layer was dealt with as an evaluation of the machined surface integrity and the effect of the mechanical factors on work hardening was investigated experimentally in orthogonal cutting. As a result, it was found that work hardened surface layer was affected not only by the shear angle varied under the cutting conditions and the thrust force of cutting resistance, but also by the thrust force acting point, the coefficient of the thrust force and the compressive stress equivalent to the bulk hardness. Furthermore, these mechanical factors acting on the depth of the work hardened surface layer were investigated with the calculation model.

Creating and connecting recommended practices for reproducible research through collaborative culture and consensus in the Research Data Alliance

NASA Astrophysics Data System (ADS)

Parsons, M. A.; Yarmey, L.; Dillo, I.

2017-12-01

Data are the foundation of a robust, efficient, and reproducible scientific enterprise. The Research Data Alliance (RDA) is a community-driven, action-oriented, virtual organization committed to enabling open sharing and reuse of data by building social and technical bridges. The international RDA community includes almost 6000 members bringing diverse perspectives, domain knowledge, and expertise to a common table for identification of common challenges and holistic solutions. RDA members work together to identify common interests and form exploratory Interest Groups and outcome-oriented Working Groups. Participants exchange knowledge, share discoveries, discuss barriers and potential solutions, articulate policies, and align standards to enhance and facilitate global data sharing within and across domains and communities. With activities defined and led by members, RDA groups have organically been addressing issues across the full research cycle with community-ratified Recommendations and other outputs that begin to create the components of a global, data-sharing infrastructure. This paper examines how multiple RDA Recommendations can be implemented together to improve data and information discoverability, accessibility, and interconnection by both people and machines. For instance, the Persistent Identifier Types can support moving data across platforms through the Data Description Registry Interoperability framework following the RDA/WDS Publishing Data Workflows model. The Scholix initiative connects scholarly literature and data across numerous stakeholders can draw on the Practical Policy best practices for machine-actionable data policies. Where appropriate, we use a case study approach built around several flagship data sets from the Deep Carbon Observatory to examine how multiple RDA Recommendations can be implemented in actual practice.

Ergonomic risk factor identification for sewing machine operators through supervised occupational therapy fieldwork in Bangladesh: A case study.

PubMed

Habib, Md Monjurul

2015-01-01

Many sewing machine operators are working with high risk factors for musculoskeletal health in the garments industries in Bangladesh. To identify the physical risk factors among sewing machine operators in a Bangladeshi garments factory. Sewing machine operators (327, 83% female), were evaluated. The mean age of the participants was 25.25 years. Six ergonomic risk factors were determined using the Musculoskeletal Disorders risk assessment. Data collection included measurements of sewing machine table and chair heights; this data was combined with information from informal interviews. Significant ergonomic risk factors found included the combination of awkward postures of the neck and back, repetitive hand and arm movements, poor ergonomic workstations and prolonged working hours without adequate breaks; these risk factors resulted in musculoskeletal complaints, sick leave, and switching jobs. One aspect of improving worker health in garment factories includes addressing musculoskeletal risk factors through ergonomic interventions.

Quantum machine learning.

PubMed

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Quantum machine learning

NASA Astrophysics Data System (ADS)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-01

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Modeling and Analysis of CNC Milling Process Parameters on Al3030 based Composite

NASA Astrophysics Data System (ADS)

Gupta, Anand; Soni, P. K.; Krishna, C. M.

2018-04-01

The machining of Al3030 based composites on Computer Numerical Control (CNC) high speed milling machine have assumed importance because of their wide application in aerospace industries, marine industries and automotive industries etc. Industries mainly focus on surface irregularities; material removal rate (MRR) and tool wear rate (TWR) which usually depends on input process parameters namely cutting speed, feed in mm/min, depth of cut and step over ratio. Many researchers have carried out researches in this area but very few have taken step over ratio or radial depth of cut also as one of the input variables. In this research work, the study of characteristics of Al3030 is carried out at high speed CNC milling machine over the speed range of 3000 to 5000 r.p.m. Step over ratio, depth of cut and feed rate are other input variables taken into consideration in this research work. A total nine experiments are conducted according to Taguchi L9 orthogonal array. The machining is carried out on high speed CNC milling machine using flat end mill of diameter 10mm. Flatness, MRR and TWR are taken as output parameters. Flatness has been measured using portable Coordinate Measuring Machine (CMM). Linear regression models have been developed using Minitab 18 software and result are validated by conducting selected additional set of experiments. Selection of input process parameters in order to get best machining outputs is the key contributions of this research work.

Analysis and design of asymmetrical reluctance machine

NASA Astrophysics Data System (ADS)

Harianto, Cahya A.

Over the past few decades the induction machine has been chosen for many applications due to its structural simplicity and low manufacturing cost. However, modest torque density and control challenges have motivated researchers to find alternative machines. The permanent magnet synchronous machine has been viewed as one of the alternatives because it features higher torque density for a given loss than the induction machine. However, the assembly and permanent magnet material cost, along with safety under fault conditions, have been concerns for this class of machine. An alternative machine type, namely the asymmetrical reluctance machine, is proposed in this work. Since the proposed machine is of the reluctance machine type, it possesses desirable feature, such as near absence of rotor losses, low assembly cost, low no-load rotational losses, modest torque ripple, and rather benign fault conditions. Through theoretical analysis performed herein, it is shown that this machine has a higher torque density for a given loss than typical reluctance machines, although not as high as the permanent magnet machines. Thus, the asymmetrical reluctance machine is a viable and advantageous machine alternative where the use of permanent magnet machines are undesirable.

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2011 CFR

2011-07-01

... air will be used to determine the average concentration for that mechanized mining unit. (e) Unless... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section...

Machine Shop Projects. Instructor Guide. General Information.

ERIC Educational Resources Information Center

Westbrook, Raymond E.

Developed in Georgia, this manual contains 101 projects for use in machine shop courses, arranged according to a suggested machine shop curriculum. Each project, included in a student workbook, contains complete drawings and instructions for implementation. Tasks are listed under the broad headings of measuring, layout, bench work, saws, drilling,…

Toward Usable Interactive Analytics: Coupling Cognition and Computation

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

Endert, Alexander; North, Chris; Chang, Remco

Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analyticsmore » that will ultimately increase the effectiveness for both humans and computers to produce insights.« less

Global Positioning System (GPS) and Geographic Information System (GIS) analysis of mobile harvesting equipment and sediment delivery to streams during forest harvest operations on steep terrain: Experimental design

Treesearch

Daniel Bowker; Jeff Stringer; Chris Barton; Songlin Fei

2011-01-01

Sediment mobilized by forest harvest machine traffic contributes substantially to the degradation of headwater stream systems. This study monitored forest harvest machine traffic to analyze how it affects sediment delivery to stream channels. Harvest machines were outfitted with global positioning system (GPS) dataloggers, recording machine movements and working status...

Machine Learning for Medical Imaging

PubMed Central

Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L.

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. ©RSNA, 2017 PMID:28212054

Machine Learning for Medical Imaging.

PubMed

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

Machine intelligence and robotics: Report of the NASA study group

NASA Technical Reports Server (NTRS)

1980-01-01

Opportunities for the application of machine intelligence and robotics in NASA missions and systems were identified. The benefits of successful adoption of machine intelligence and robotics techniques were estimated and forecasts were prepared to show their growth potential. Program options for research, advanced development, and implementation of machine intelligence and robot technology for use in program planning are presented.

A Guide for Planning Facilities for Occupational Preparation Programs in the Machine Trades. Interim Report. Research 24.

ERIC Educational Resources Information Center

Larson, Milton E.

This guide is designed for use by any person or groups of persons responsible for planning occupational programs in the machine trades. Its major purpose is to elicit the necessary information for the writing of educational specifications for facilities to house needed vocational programs in machine tool operation, machine shop, and tool and die…

Integral habitat transport system

NASA Technical Reports Server (NTRS)

Elliott, Bill; Frazer, Scott; Higgs, Joey; Huff, Jason; Milam, Tigree

1994-01-01

In the 1993 Fall quarter, the ME 4182 design class was sponsored to study various scenarios that needed to be studied for Martian travel. The class was sponsored by NASA and there were several different design projects. The design that group three chose was an integral transport system for a Martian habitat. An integral transport system means the design had to be one that was attached to the habitat. There were several criteria that the design had to meet. Group three performed an in depth study of the Martian environment and looked at several different design ideas. The concept group three developed involved the use of kinematic linkages and the use of Martian gravity to move the habitat. The various design concepts, the criteria matrices and all other aspects that helped group three develop their design can be found in their 1993 ME 4182 design report. Now it is Winter quarter 1994 and group three is faced with another problem. The problem is building a working prototype of their Fall design. The limitations this quarter were the parts. The group had to make the prototype work with existing manufactured parts or make the parts themselves in a machine shop. The prototype was scaled down roughly about twelve times smaller than the original design. The following report describes the actions taken by group three to build a working model.

Laser Machining of Melt Infiltrated Ceramic Matrix Composite

NASA Technical Reports Server (NTRS)

Jarmon, D. C.; Ojard, G.; Brewer, D.

2012-01-01

As interest grows in considering the use of ceramic matrix composites for critical components, the effects of different machining techniques, and the resulting machined surfaces, on strength need to be understood. This work presents the characterization of a Melt Infiltrated SiC/SiC composite material system machined by different methods. While a range of machining approaches were initially considered, only diamond grinding and laser machining were investigated on a series of tensile coupons. The coupons were tested for residual tensile strength, after a stressed steam exposure cycle. The data clearly differentiated the laser machined coupons as having better capability for the samples tested. These results, along with micro-structural characterization, will be presented.

Needs of ergonomic design at control units in production industries.

PubMed

Levchuk, I; Schäfer, A; Lang, K-H; Gebhardt, Hj; Klussmann, A

2012-01-01

During the last decades, an increasing use of innovative technologies in manufacturing areas was monitored. A huge amount of physical workload was replaced by the change from conventional machine tools to computer-controlled units. CNC systems spread in current production processes. Because of this, machine operators today mostly have an observational function. This caused increasing of static work (e.g., standing, sitting) and cognitive demands (e.g., process observation). Machine operators have a high responsibility, because mistakes may lead to human injuries as well as to product losses - and in consequence may lead to high monetary losses (for the company) as well. Being usable often means for a CNC machine being efficient. An intuitive usability and an ergonomic organization of CNC workplaces can be an essential basis to reduce the risk of failures in operation as well as physical complaints (e.g. pain or diseases because of bad body posture during work). In contrast to conventional machines, CNC machines are equipped both with hardware and software. An intuitive and clear-sighted operating of CNC systems is a requirement for quick learning of new systems. Within this study, a survey was carried out among trainees learning the operation of CNC machines.

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

PubMed Central

2011-01-01

Background Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. Results This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. Conclusions AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements. PMID:21798025

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment.

PubMed

Stålring, Jonna C; Carlsson, Lars A; Almeida, Pedro; Boyer, Scott

2011-07-28

Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements.

Determinants explaining the variability of hand-transmitted vibration emissions from two different work tasks: grinding and cutting using angle grinders.

PubMed

Liljelind, Ingrid; Pettersson, Hans; Nilsson, Leif; Wahlström, Jens; Toomingas, Allan; Lundström, Ronnie; Burström, Lage

2013-10-01

There are numerous factors including physical, biomechanical, and individual that influence exposure to hand-transmitted vibration (HTV) and cause variability in the exposure measurements. Knowledge of exposure variability and determinants of exposure could be used to improve working conditions. We performed a quasi-experimental study, where operators performed routine work tasks in order to obtain estimates of the variance components and to evaluate the effect of determinants, such as machine-wheel combinations and individual operator characteristics. Two pre-defined simulated work tasks were performed by 11 operators: removal of a weld puddle of mild steel and cutting of a square steel pipe. In both tasks, four angle grinders were used, two running on compressed air and two electrically driven. Two brands of both grinding and cutting wheels were used. Each operator performed both tasks twice in a random order with each grinder and wheel and the time to complete each task was recorded. Vibration emission values were collected and the wheel wear was measured as loss of weight. Operators' characteristics collected were as follows: age, body height and weight, length and volume of their hands, maximum hand grip force, and length of work experience with grinding machines (years). The tasks were also performed by one operator who used four machines of the same brand. Mixed and random effects models were used in the statistical evaluation. The statistical evaluation was performed for grinding and cutting separately and we used a measure referring to the sum of the 1-s r.m.s. average frequency-weighted acceleration over time for completing the work task (a(sa)). Within each work task, there was a significant effect as a result of the determinants 'the machine used', 'wheel wear', and 'time taken to complete the task'. For cutting, 'the brand of wheel' used also had a significant effect. More than 90% of the inherent variability in the data was explained by the determinants. The two electrically powered machines had a mean a(sa) that was 2.6 times higher than the two air-driven machines. For cutting, the effect of the brand of wheel on a(sa) was ~0.1 times. The a(sa) increased both with increasing wheel wear and with time taken to complete the work task. However, there were also a number of interaction effects which, to a minor extent, modified the a(sa). Only a minor part (1%) of the total variability was attributed to the operator: for cutting, the volume of the hands, maximum grip force, and body weight were significant, while for grinding, it was the maximum grip force. There was no clear difference in a(sa) between the four copies of the same brand of each machine. By including determinants that were attributed to the brand of both machine and wheel used as well as the time taken to complete the work task, we were able to explain >90% of the variability. The dominating determinant was the brand of the machine. Little variability was found between operators, indicating that the overall effect as due to the operator was small.

FSW of Aluminum Tailor Welded Blanks across Machine Platforms

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

Hovanski, Yuri; Upadhyay, Piyush; Carlson, Blair

2015-02-16

Development and characterization of friction stir welded aluminum tailor welded blanks was successfully carried out on three separate machine platforms. Each was a commercially available, gantry style, multi-axis machine designed specifically for friction stir welding. Weld parameters were developed to support high volume production of dissimilar thickness aluminum tailor welded blanks at speeds of 3 m/min and greater. Parameters originally developed on an ultra-high stiffness servo driven machine where first transferred to a high stiffness servo-hydraulic friction stir welding machine, and subsequently transferred to a purpose built machine designed to accommodate thin sheet aluminum welding. The inherent beam stiffness, bearingmore » compliance, and control system for each machine were distinctly unique, which posed specific challenges in transferring welding parameters across machine platforms. This work documents the challenges imposed by successfully transferring weld parameters from machine to machine, produced from different manufacturers and with unique control systems and interfaces.« less

[Research on infrared safety protection system for machine tool].

PubMed

Zhang, Shuan-Ji; Zhang, Zhi-Ling; Yan, Hui-Ying; Wang, Song-De

2008-04-01

In order to ensure personal safety and prevent injury accident in machine tool operation, an infrared machine tool safety system was designed with infrared transmitting-receiving module, memory self-locked relay and voice recording-playing module. When the operator does not enter the danger area, the system has no response. Once the operator's whole or part of body enters the danger area and shades the infrared beam, the system will alarm and output an control signal to the machine tool executive element, and at the same time, the system makes the machine tool emergency stop to prevent equipment damaged and person injured. The system has a module framework, and has many advantages including safety, reliability, common use, circuit simplicity, maintenance convenience, low power consumption, low costs, working stability, easy debugging, vibration resistance and interference resistance. It is suitable for being installed and used in different machine tools such as punch machine, pour plastic machine, digital control machine, armor plate cutting machine, pipe bending machine, oil pressure machine etc.

Interior of building 16 section, view north of machine shop, ...

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

Interior of building 16 section, view north of machine shop, showing shrink-fitting a bearing sleeve onto a section of the propeller shaft for the aircraft carrier John F. Kennedy. The lathe on the extreme left of the photograph was used to machine bearing sleeves to final dimensions. This work, in August 1994, was the final major machine shop job done for the U.S. Navy. Photograph by Robert Stewart, August 1994. - Naval Base Philadelphia-Philadelphia Naval Shipyard, Machine Shops, League Island, Philadelphia, Philadelphia County, PA

Highly Productive Tools For Turning And Milling

NASA Astrophysics Data System (ADS)

Vasilko, Karol

2015-12-01

Beside cutting speed, shift is another important parameter of machining. Its considerable influence is shown mainly in the workpiece machined surface microgeometry. In practice, mainly its combination with the radius of cutting tool tip rounding is used. Options to further increase machining productivity and machined surface quality are hidden in this approach. The paper presents variations of the design of productive cutting tools for lathe work and milling on the base of the use of the laws of the relationship among the highest reached uneveness of machined surface, tool tip radius and shift.

Lecture Notes on a Machine Independent Compiler for ATLAS (MICA).

DTIC Science & Technology

1980-10-01

1 w E-- - --SUMARY.. The memorandum is in essence the text of a lecture given to the Industrial Liaison Group of the Defence Automatic Test Equipment...Steering Committee, on 10 September 1980 at RSRE Malvern. The purpose of the lecture was to convey to industry the results of research work performed...TO INDUSTRY 2.1 overview of ATLAS 2.2 What is MICA 2.3 What can be made available to industry 2.4 What can not be made available to industry 3 TALK 2

A randomized controlled trial of chair interventions on back and hip pain among sewing machine operators: the los angeles garment study.

PubMed

Wang, Pin-Chieh; Ritz, Beate R; Janowitz, Ira; Harrison, Robert J; Yu, Fei; Chan, Jacqueline; Rempel, David M

2008-03-01

Determine whether an adjustable chair with a curved or a flat seat pan improved monthly back and hip pain scores in sewing machine operators. This 4-month intervention study randomized 293 sewing machine operators with back and hip pain. The participants in the control group received a placebo intervention, and participants in the intervention groups received the placebo intervention and one of the two intervention chairs. Compared with the control group, mean pain improvement for the flat chair intervention was 0.43 points (95% CI = 0.34, 0.51) per month, and mean pain improvement for the curved chair intervention was 0.25 points (95% CI = 0.16, 0.34) per month. A height-adjustable task chair with a swivel function can reduce back and hip pain in sewing machine operators. The findings may be relevant to workers who perform visual- and hand-intensive manufacturing jobs.

A Comparison of Machine Learning Approaches for Corn Yield Estimation

NASA Astrophysics Data System (ADS)

Kim, N.; Lee, Y. W.

2017-12-01

Machine learning is an efficient empirical method for classification and prediction, and it is another approach to crop yield estimation. The objective of this study is to estimate corn yield in the Midwestern United States by employing the machine learning approaches such as the support vector machine (SVM), random forest (RF), and deep neural networks (DNN), and to perform the comprehensive comparison for their results. We constructed the database using satellite images from MODIS, the climate data of PRISM climate group, and GLDAS soil moisture data. In addition, to examine the seasonal sensitivities of corn yields, two period groups were set up: May to September (MJJAS) and July and August (JA). In overall, the DNN showed the highest accuracies in term of the correlation coefficient for the two period groups. The differences between our predictions and USDA yield statistics were about 10-11 %.

Intensification of the Students' Self-Development Process When Performing Design and Settlement Works on the "Machine Parts" Course

ERIC Educational Resources Information Center

Timerbaev, Rais Mingalievich; Muhutdinov, Rafis Habreevich; Danilov, Valeriy Fedorovich

2015-01-01

The article addresses issues related to the methodology of intensifying self-development process when performing design and settlement works on the "Machine Parts" course for the students studying in such areas of training as "Technology" and "Vocational Education" with the use of computer technologies. At the same…

Apprentice Machinist (AFSC 53130), Volumes 1-4, and Change Supplement (AFSC 42730).

ERIC Educational Resources Information Center

Air Univ., Gunter AFS, Ala. Extension Course Inst.

This four-volume student learning package is designed for use by Air Force personnel enrolled in a self-study extension course for apprentice machinists. The package consists of four volumes of instructional text and four workbooks. Covered in the individual volumes are machine shop fundamentals, lathe work, shaper and contour machine work, and…

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

Feature Discovery by Competitive Learning.

DTIC Science & Technology

1984-06-01

Probably the first such attempt occurred in 1951 when Dean Edmonds and Marvin Minsky built their learning machine. The flavor of this machine and...Bernstein, J. (1961). Profiles: Al, Marvin Minsky . The New Yorker. 57, 50-126. Bienenstock, E. L., Cooper, L. N., & Munro, P. W. (1982). Theory for the...This machine actually worked and was so fascinating to watch that Minsky remembers: We sort of quit science for awhile to watch the machine. We were

New developments in operator protection for forest machines

Treesearch

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

2003-01-01

Mechanization of forest operations ha greatly improved saftey of woods work. However, increasing use of machines has introduced new hazards that must be addressed. Two of these hazards are rollover of swing-type forestry machines (currently excluded from standard protection) and the hazard of thrown objects from cutting devices. Ongoing research projects are developing...

Learn about Physical Science: Simple Machines. [CD-ROM].

ERIC Educational Resources Information Center

2000

This CD-ROM, designed for students in grades K-2, explores the world of simple machines. It allows students to delve into the mechanical world and learn the ways in which simple machines make work easier. Animated demonstrations are provided of the lever, pulley, wheel, screw, wedge, and inclined plane. Activities include practical matching and…

Orientation to Machine Shop. Safety, Machine Identification, Metal Identification.

ERIC Educational Resources Information Center

Engelbrecht, Nancy; And Others

These instructional materials provide an orientation to the machine shop for use at the postsecondary level. The first of three sections discusses four important areas of safety: (1) personal safety; (2) safety procedures; (3) safe work practices; and (4) fire prevention. The second section identifies and describes the general purposes of 12…

40 CFR Table 9 to Subpart Wwww of... - Initial Compliance With Work Practice Standards

Code of Federal Regulations, 2014 CFR

2014-07-01

... compression/injection molding uncover, unwrap or expose only one charge per mold cycle per compression/injection molding machine. For machines with multiple molds, one charge means sufficient material to fill... cycle per compression/injection molding machine, or prior to the loader, hoppers are closed except when...

Science 101: Q--What Is the Physics behind Simple Machines?

ERIC Educational Resources Information Center

Robertson, Bill

2013-01-01

Bill Robertson thinks that questioning the physics behind simple machines is a great idea because when he encounters the subject of simple machines in textbooks, activities, and classrooms, he seldom encounters, a scientific explanation of how they work. Instead, what one often sees is a discussion of load, effort, fulcrum, actual mechanical…

48 CFR 6105.502 - Request for decision [Rule 502].

Code of Federal Regulations, 2014 CFR

2014-10-01

...) Include— (A) The name, address, telephone number, facsimile machine number, and e-mail address, if available, of the official making the request; (B) The name, address, telephone number, facsimile machine... Clerk's facsimile machine number is: (202) 606-0019. The Board's working hours are 8:00 a.m. to 4:30 p.m...

48 CFR 6105.502 - Request for decision [Rule 502].

Code of Federal Regulations, 2012 CFR

2012-10-01

...) Include— (A) The name, address, telephone number, facsimile machine number, and e-mail address, if available, of the official making the request; (B) The name, address, telephone number, facsimile machine... Clerk's facsimile machine number is: (202) 606-0019. The Board's working hours are 8:00 a.m. to 4:30 p.m...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

48 CFR 6104.402 - Filing claims [Rule 402].

Code of Federal Regulations, 2010 CFR

2010-10-01

... number, and facsimile machine number, if available, of the claimant; (ii) The name, address, telephone number, and facsimile machine number, if available, of the agency employee who denied the claim; (iii) A... Clerk's facsimile machine number is: (202) 606-0019. The Board's working hours are 8:00 a.m. to 4:30 p.m...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

Abrasives and Grinding Machines; Machine Shop Work--Advanced: 9557.02.

ERIC Educational Resources Information Center

Dade County Public Schools, Miami, FL.

The course outline has been prepared as a guide to assist the instructor in systematically planning and presenting a variety of meaningful lessons to facilitate the necessary training for the machine shop student. The material contained in the outline is designed to enable the student to learn the manipulative skills and related knowledge…

Process Monitoring Evaluation and Implementation for the Wood Abrasive Machining Process

PubMed Central

Saloni, Daniel E.; Lemaster, Richard L.; Jackson, Steven D.

2010-01-01

Wood processing industries have continuously developed and improved technologies and processes to transform wood to obtain better final product quality and thus increase profits. Abrasive machining is one of the most important of these processes and therefore merits special attention and study. The objective of this work was to evaluate and demonstrate a process monitoring system for use in the abrasive machining of wood and wood based products. The system developed increases the life of the belt by detecting (using process monitoring sensors) and removing (by cleaning) the abrasive loading during the machining process. This study focused on abrasive belt machining processes and included substantial background work, which provided a solid base for understanding the behavior of the abrasive, and the different ways that the abrasive machining process can be monitored. In addition, the background research showed that abrasive belts can effectively be cleaned by the appropriate cleaning technique. The process monitoring system developed included acoustic emission sensors which tended to be sensitive to belt wear, as well as platen vibration, but not loading, and optical sensors which were sensitive to abrasive loading. PMID:22163477

Research on axisymmetric aspheric surface numerical design and manufacturing technology

NASA Astrophysics Data System (ADS)

Wang, Zhen-zhong; Guo, Yin-biao; Lin, Zheng

2006-02-01

The key technology for aspheric machining offers exact machining path and machining aspheric lens with high accuracy and efficiency, in spite of the development of traditional manual manufacturing into nowadays numerical control (NC) machining. This paper presents a mathematical model between virtual cone and aspheric surface equations, and discusses the technology of uniform wear of grinding wheel and error compensation in aspheric machining. Finally, a software system for high precision aspheric surface manufacturing is designed and realized, based on the mentioned above. This software system can work out grinding wheel path according to input parameters and generate machining NC programs of aspheric surfaces.

Zooniverse: Combining Human and Machine Classifiers for the Big Survey Era

NASA Astrophysics Data System (ADS)

Fortson, Lucy; Wright, Darryl; Beck, Melanie; Lintott, Chris; Scarlata, Claudia; Dickinson, Hugh; Trouille, Laura; Willi, Marco; Laraia, Michael; Boyer, Amy; Veldhuis, Marten; Zooniverse

2018-01-01

Many analyses of astronomical data sets, ranging from morphological classification of galaxies to identification of supernova candidates, have relied on humans to classify data into distinct categories. Crowdsourced galaxy classifications via the Galaxy Zoo project provided a solution that scaled visual classification for extant surveys by harnessing the combined power of thousands of volunteers. However, the much larger data sets anticipated from upcoming surveys will require a different approach. Automated classifiers using supervised machine learning have improved considerably over the past decade but their increasing sophistication comes at the expense of needing ever more training data. Crowdsourced classification by human volunteers is a critical technique for obtaining these training data. But several improvements can be made on this zeroth order solution. Efficiency gains can be achieved by implementing a “cascade filtering” approach whereby the task structure is reduced to a set of binary questions that are more suited to simpler machines while demanding lower cognitive loads for humans.Intelligent subject retirement based on quantitative metrics of volunteer skill and subject label reliability also leads to dramatic improvements in efficiency. We note that human and machine classifiers may retire subjects differently leading to trade-offs in performance space. Drawing on work with several Zooniverse projects including Galaxy Zoo and Supernova Hunter, we will present recent findings from experiments that combine cohorts of human and machine classifiers. We show that the most efficient system results when appropriate subsets of the data are intelligently assigned to each group according to their particular capabilities.With sufficient online training, simple machines can quickly classify “easy” subjects, leaving more difficult (and discovery-oriented) tasks for volunteers. We also find humans achieve higher classification purity while samples produced by machines are typically more complete. These findings set the stage for further investigations, with the ultimate goal of efficiently and accurately labeling the wide range of data classes that will arise from the planned large astronomical surveys.

Estimating the mass of the Local Group using machine learning applied to numerical simulations

NASA Astrophysics Data System (ADS)

McLeod, M.; Libeskind, N.; Lahav, O.; Hoffman, Y.

2017-12-01

We present a new approach to calculating the combined mass of the Milky Way (MW) and Andromeda (M31), which together account for the bulk of the mass of the Local Group (LG). We base our work on an ensemble of 30,190 halo pairs from the Small MultiDark simulation, assuming a ΛCDM (Cosmological Constant and Cold Dark Matter) cosmology. This is used in conjunction with machine learning methods (artificial neural networks, ANN) to investigate the relationship between the mass and selected parameters characterising the orbit and local environment of the binary. ANN are employed to take account of additional physics arising from interactions with larger structures or dynamical effects which are not analytically well understood. Results from the ANN are most successful when the velocity shear is provided, which demonstrates the flexibility of machine learning to model physical phenomena and readily incorporate new information. The resulting estimate for the Local Group mass, when shear information is included, is 4.9×1012Msolar, with an error of ±0.8×1012Msolar from the 68% uncertainty in observables, and a r.m.s. scatter interval of +1.7‑1.3×1012Msolar estimated scatter from the differences between the model estimates and simulation masses for a testing sample of halo pairs. We also consider a recently reported large relative transverse velocity of M31 and the Milky Way, and produce an alternative mass estimate of 3.6±0.3+2.1‑1.3×1012Msolar. Although the methods used predict similar values for the most likely mass of the LG, application of ANN compared to the traditional Timing Argument reduces the scatter in the log mass by approximately half when tested on samples from the simulation.

Hand-arm vibration disorder among grass-cutter workers in Malaysia.

PubMed

Azmir, Nor Azali; Ghazali, Mohd Imran; Yahya, Musli Nizam; Ali, Mohamad Hanafi

2016-09-01

Prolonged exposure to hand-transmitted vibration from grass-cutting machines has been associated with increasing occurrences of symptoms and signs of occupational diseases related to hand-arm vibration syndrome (HAVS). A cross-sectional study was carried out using an adopted HAVS questionnaire on hand-arm vibration exposure and symptoms distributed to 168 male workers from the grass and turf maintenance industry who use hand-held grass-cutting machines as part of their work. The prevalence ratio and symptom correlation to HAVS between high and low-moderate exposure risk groups were evaluated. There were positive HAVS symptoms relationships between the low-moderate exposure group and the high exposure group among hand-held grass-cutting workers. The prevalence ratio was considered high because there were indicators that fingers turned white and felt numb, 3.63, 95% CI [1.41, 9.39] and 4.24, 95% CI [2.18, 8.27], respectively. Less than 14.3% of workers stated that they were aware of the occupational hand-arm vibration, and it seemed to be related to the finger blanching and numbness. The results suggest that HAVS is under-diagnosed in Malaysia, especially in the agricultural sectors. More information related to safety and health awareness programmes for HAVS exposure is required among hand-held grass-cutting workers.

Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.

PubMed

Chen, Lili; Hao, Yaru

2017-01-01

Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT) and extreme learning machine (ELM). For each sample, each channel was decomposed into a set of intrinsic mode functions (IMFs) using empirical mode decomposition (EMD). Then, the Hilbert transform was applied to IMF to obtain analytic function. The maximum amplitude of analytic function was extracted as feature. The identification model was constructed based on ELM. Experimental results reveal that the best classification performance of the proposed method can reach an accuracy of 88.00%, a sensitivity of 91.30%, and a specificity of 85.19%. The area under receiver operating characteristic (ROC) curve is 0.88. Finally, experimental results indicate that the method developed in this work could be effective in the classification of EHG between pregnancy and labour group.

[Occupational differences in exposure to hazardous work conditions].

PubMed

Marinacci, Chiara; d'Errico, A; Cardano, M; Perini, F; Costa, G

2005-01-01

Few studies have been aimed at describing organizational and psychosocial conditions of the Italian workforce by occupational group, and they have been mainly conducted within specific occupations. The present study aimed at identifying specific groups of occupations which have unfavourable profiles from the point of view of exposure to specific organizational factors and psychosocial risks, and to physical, chemical and ergonomic risks, and analyzing their distribution by worker age. The analysis was conducted on a sample of 4,195 workers in the Piedmont Region who were members of the CGIL Trade Union (Italian General Confederation of Labour), who answered a self-administered questionnaire in 2000, aimed at assessing chemical, physical, and ergonomic risks, accidents, and psychosocial factors connected with work organization and work tasks. Psychosocial risks were assessed via three scales aimed at measuring the degree of control, psychophysical demands, and worker satisfaction. The proportion of workers exposed to the above mentioned risks was analysed according to occupational group. This group was then compared with all other groups taken together, according to prevalence of high strain condition (combination of high demand and low control) and HSUR condition (High Strain Unfairly Rewarded; combination of high strain and low satisfaction). Among males aged 25-44 years, restricted to the occupation groups with more than ten workers in high strain condition, significantly higher proportions of stress were observed in leather workers and shoemakers, paper factory workers, rubber workers, crane and bridge crane operators, plastic workers, painters, transport drivers and carpenters. For many of these groups, excesses were confirmed for the HSUR condition. Among subjects aged over 44 years, a higher risk for high strain was confirmed in rubber workers, transport drivers and carpenters. In addition, machine tool operators, assembly line and mechanical workers in this age group were exposed to higher risk of stress. In younger women there was a significantly higher risk of both high strain and HSUR conditions in workers employed in the rubber, plastic and the food industries, and in machine tool workers. Such excess risk was confirmed in the latter three categories also among older women. In general, the proportion of male workers classified as working in high strain conditions decreased as age increased, while in women it remained stable. The study allowed evaluation of the differential impact of exposure to physical, chemical, and psychosocial risk factors among occupational groups, thus contributing to the identification and classification of exhausting jobs. The results further showed, particularly among men, a smaller proportion of older workers, compared to younger ones, exposed to harmful physical, chemical, ergonomic and psychosocial conditions, indicating a possible propensity of companies to adapt workplace conditions, organization and internal mobility to worker age.

Integration of the virtual 3D model of a control system with the virtual controller

NASA Astrophysics Data System (ADS)

Herbuś, K.; Ociepka, P.

2015-11-01

Nowadays the design process includes simulation analysis of different components of a constructed object. It involves the need for integration of different virtual object to simulate the whole investigated technical system. The paper presents the issues related to the integration of a virtual 3D model of a chosen control system of with a virtual controller. The goal of integration is to verify the operation of an adopted object of in accordance with the established control program. The object of the simulation work is the drive system of a tunneling machine for trenchless work. In the first stage of work was created an interactive visualization of functioning of the 3D virtual model of a tunneling machine. For this purpose, the software of the VR (Virtual Reality) class was applied. In the elaborated interactive application were created adequate procedures allowing controlling the drive system of a translatory motion, a rotary motion and the drive system of a manipulator. Additionally was created the procedure of turning on and off the output crushing head, mounted on the last element of the manipulator. In the elaborated interactive application have been established procedures for receiving input data from external software, on the basis of the dynamic data exchange (DDE), which allow controlling actuators of particular control systems of the considered machine. In the next stage of work, the program on a virtual driver, in the ladder diagram (LD) language, was created. The control program was developed on the basis of the adopted work cycle of the tunneling machine. The element integrating the virtual model of the tunneling machine for trenchless work with the virtual controller is the application written in a high level language (Visual Basic). In the developed application was created procedures responsible for collecting data from the running, in a simulation mode, virtual controller and transferring them to the interactive application, in which is verified the operation of the adopted research object. The carried out work allowed foot the integration of the virtual model of the control system of the tunneling machine with the virtual controller, enabling the verification of its operation.

A Brief Description of My Projects

NASA Technical Reports Server (NTRS)

Barnes, Tobin

2016-01-01

My internship was in the IDC which consist of a machine shop and an array of design space. During my tour I worked on a wide variety of projects some of which included design, research, machining and fabrication. I gained further knowledge on some machines that I have had prior experience on such as the lathe and Hurco CNC machines. The first thing we did was complete our checkout in the machine shop which went pretty well, since I was already familiar with most of the machines. I also did a couple of practice parts on some of the machines, I made a name block on the CNC machine and I also used the vertical milling machine to complete this project. One of the other projects that I did was machine a hammer with my initials with the use of the lathe and CNC machine, this project took much longer since I had to set up a cylindrical piece on the CNC machine. The first project that I began work on was the Systems Engineering & Management Advancement Program (SEPMAP) Hexacopter project and helped them to assemble and modify one of their particle capture doors on their boxes. After a while we ended up helping them make a hinge and holes to reduce the weight of their design. We helped the NASA Extreme Environment Mission Operations (NEEMO) team a bit with some of their name tags and assembly of some of their underwater parts. One of the more challenging projects was a rail that came in with a rather weirdly drawn part. The biggest project that I worked on was the solar array project. Which consisted of a variety of machining and 3D printing and it took me about 3 different times of re-designing to come up with a final prototype. Along with this project I also had to complete a project in which I had to modify a thermos. This was rather simple since I just had to draw up a part and print it out on the 3D printer. I also learned how to use Pro E/Creo parametric to design a square block and print it on the 3D Printer. All of these projects increased my experience on all of the machines and equipment that I used. I also got to tweak my design skills and better understand how to modify my designs and how to improve those specific designs.

Principle and design of small-sized and high-definition x-ray machine

NASA Astrophysics Data System (ADS)

Zhao, Anqing

2010-10-01

The paper discusses the circuit design and working principles of VMOS PWM type 75KV10mA high frequency X-ray machine. The system mainly consists of silicon controlled rectifier, VMOS tube PWM type high-frequency and highvoltage inverter circuit, filament inverter circuit, high-voltage rectifier filter circuit and as X-ray tube. The working process can be carried out under the control of a single-chip microcomputer. Due to the small size and high resolution in imaging, the X-ray machine is mostly adopted for emergent medical diagnosis and specific circumstances where nondestructive tests are conducted.

Design of robotic cells based on relative handling modules with use of SolidWorks system

NASA Astrophysics Data System (ADS)

Gaponenko, E. V.; Anciferov, S. I.

2018-05-01

The article presents a diagramed engineering solution for a robotic cell with six degrees of freedom for machining of complex details, consisting of the base with a tool installation module and a detail machining module made as parallel structure mechanisms. The output links of the detail machining module and the tool installation module can move along X-Y-Z coordinate axes each. A 3D-model of the complex is designed in the SolidWorks system. It will be used further for carrying out engineering calculations and mathematical analysis and obtaining all required documentation.

Assessment of various supervised learning algorithms using different performance metrics

NASA Astrophysics Data System (ADS)

Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

Neck pain combined with arm pain among professional drivers of forest machines and the association with whole-body vibration exposure.

PubMed

Rehn, B; Nilsson, T; Lundström, R; Hagberg, M; Burström, L

2009-10-01

The purpose of this study was to investigate the existence of neck pain and arm pain among professional forest machine drivers and to find out if pain were related to their whole-body vibration (WBV) exposure. A self-administered questionnaire was sent to 529 forest machine drivers in northern Sweden and the response was 63%. Two pain groups were formed; 1) neck pain; 2) neck pain combined with arm pain. From WBV exposure data (recent measurements made according to ISO 2631-1, available information from reports) and from the self-administered questionnaire, 14 various WBV exposure/dose measures were calculated for each driver. The prevalence of neck pain reported both for the previous 12 months and for the previous 7 d was 34% and more than half of them reported neck pain combined with pain in one or both arms. Analysis showed no significant association between neck pain and high WBV exposure; however, cases with neck pain more often experienced shocks and jolts in the vehicle as uncomfortable. There was no significant association between the 14 WBV measures and type of neck pain (neck pain vs. neck pain combined with arm pain). It seems as if characteristics of WBV exposure can explain neither existence nor the type of neck pain amongst professional drivers of forest machines. The logging industry is important for several industrialised countries. Drivers of forest machines frequently report neuromusculoskeletal pain from the neck. The type of neck pain is important for the decision of treatment modality and may be associated with exposure characteristics at work.

Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

NASA Astrophysics Data System (ADS)

Fachrurrozi, Muhammad; Saparudin; Erwin

2017-04-01

Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

Learning atoms for materials discovery.

PubMed

Zhou, Quan; Tang, Peizhe; Liu, Shenxiu; Pan, Jinbo; Yan, Qimin; Zhang, Shou-Cheng

2018-06-26

Exciting advances have been made in artificial intelligence (AI) during recent decades. Among them, applications of machine learning (ML) and deep learning techniques brought human-competitive performances in various tasks of fields, including image recognition, speech recognition, and natural language understanding. Even in Go, the ancient game of profound complexity, the AI player has already beat human world champions convincingly with and without learning from the human. In this work, we show that our unsupervised machines (Atom2Vec) can learn the basic properties of atoms by themselves from the extensive database of known compounds and materials. These learned properties are represented in terms of high-dimensional vectors, and clustering of atoms in vector space classifies them into meaningful groups consistent with human knowledge. We use the atom vectors as basic input units for neural networks and other ML models designed and trained to predict materials properties, which demonstrate significant accuracy. Copyright © 2018 the Author(s). Published by PNAS.

Bridging the gap between the technological singularity and mainstream medicine: highlighting a course on technology and the future of medicine.

PubMed

Solez, Kim; Bernier, Ashlyn; Crichton, Joel; Graves, Heather; Kuttikat, Preeti; Lockwood, Ross; Marovitz, William F; Monroe, Damon; Pallen, Mark; Pandya, Shawna; Pearce, David; Saleh, Abdullah; Sandhu, Neelam; Sergi, Consolato; Tuszynski, Jack; Waugh, Earle; White, Jonathan; Woodside, Michael; Wyndham, Roger; Zaiane, Osmar; Zakus, David

2013-09-09

The "technological singularity" is defined as that putative point in time forecasted to occur in the mid twenty-first century when machines will become smarter than humans, leading humans and machines to merge. It is hypothesized that this event will have a profound influence on medicine and population health. This work describes a new course on Technology and the Future of Medicine developed by a diverse, multi-disciplinary group of faculty members at a Canadian university. The course began as a continuous professional learning course and was later established as a recognized graduate course. We describe the philosophy of the course, the barriers encountered in course development, and some of the idiosyncratic solutions that were developed to overcome these, including the use of YouTube audience retention analytics. We hope that this report might provide a useful template for other institutions attempting to set up similar programs.

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

PubMed Central

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

PubMed

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

Thermodynamic work from operational principles

NASA Astrophysics Data System (ADS)

Gallego, R.; Eisert, J.; Wilming, H.

2016-10-01

In recent years we have witnessed a concentrated effort to make sense of thermodynamics for small-scale systems. One of the main difficulties is to capture a suitable notion of work that models realistically the purpose of quantum machines, in an analogous way to the role played, for macroscopic machines, by the energy stored in the idealisation of a lifted weight. Despite several attempts to resolve this issue by putting forward specific models, these are far from realistically capturing the transitions that a quantum machine is expected to perform. In this work, we adopt a novel strategy by considering arbitrary kinds of systems that one can attach to a quantum thermal machine and defining work quantifiers. These are functions that measure the value of a transition and generalise the concept of work beyond those models familiar from phenomenological thermodynamics. We do so by imposing simple operational axioms that any reasonable work quantifier must fulfil and by deriving from them stringent mathematical condition with a clear physical interpretation. Our approach allows us to derive much of the structure of the theory of thermodynamics without taking the definition of work as a primitive. We can derive, for any work quantifier, a quantitative second law in the sense of bounding the work that can be performed using some non-equilibrium resource by the work that is needed to create it. We also discuss in detail the role of reversibility and correlations in connection with the second law. Furthermore, we recover the usual identification of work with energy in degrees of freedom with vanishing entropy as a particular case of our formalism. Our mathematical results can be formulated abstractly and are general enough to carry over to other resource theories than quantum thermodynamics.

Visualization of anthropometric measures of workers in computer 3D modeling of work place.

PubMed

Mijović, B; Ujević, D; Baksa, S

2001-12-01

In this work, 3D visualization of a work place by means of a computer-made 3D-machine model and computer animation of a worker have been performed. By visualization of 3D characters in inverse kinematic and dynamic relation with the operating part of a machine, the biomechanic characteristics of worker's body have been determined. The dimensions of a machine have been determined by an inspection of technical documentation as well as by direct measurements and recordings of the machine by camera. On the basis of measured body height of workers all relevant anthropometric measures have been determined by a computer program developed by the authors. By knowing the anthropometric measures, the vision fields and the scope zones while forming work places, exact postures of workers while performing technological procedures were determined. The minimal and maximal rotation angles and the translation of upper and lower arm which are basis for the analysis of worker burdening were analyzed. The dimensions of the seized space of a body are obtained by computer anthropometric analysis of movement, e.g. range of arms, position of legs, head, back. The influence of forming of a work place on correct postures of workers during work has been reconsidered and thus the consumption of energy and fatigue can be reduced to a minimum.

High-pressure coolant effect on the surface integrity of machining titanium alloy Ti-6Al-4V: a review

NASA Astrophysics Data System (ADS)

Liu, Wentao; Liu, Zhanqiang

2018-03-01

Machinability improvement of titanium alloy Ti-6Al-4V is a challenging work in academic and industrial applications owing to its low thermal conductivity, low elasticity modulus and high chemical affinity at high temperatures. Surface integrity of titanium alloys Ti-6Al-4V is prominent in estimating the quality of machined components. The surface topography (surface defects and surface roughness) and the residual stress induced by machining Ti-6Al-4V occupy pivotal roles for the sustainability of Ti-6Al-4V components. High-pressure coolant (HPC) is a potential choice in meeting the requirements for the manufacture and application of Ti-6Al-4V. This paper reviews the progress towards the improvements of Ti-6Al4V surface integrity under HPC. Various researches of surface integrity characteristics have been reported. In particularly, surface roughness, surface defects, residual stress as well as work hardening are investigated in order to evaluate the machined surface qualities. Several coolant parameters (including coolant type, coolant pressure and the injection position) deserve investigating to provide the guidance for a satisfied machined surface. The review also provides a clear roadmap for applications of HPC in machining Ti-6Al4V. Experimental studies and analysis are reviewed to better understand the surface integrity under HPC machining process. A distinct discussion has been presented regarding the limitations and highlights of the prospective for machining Ti-6Al4V under HPC.

Analysis of Work Design in Rubber Processing Plant

NASA Astrophysics Data System (ADS)

Wahyuni, Dini; Nasution, Harmein; Budiman, Irwan; Wijaya, Khairini

2018-02-01

The work design illustrates how structured jobs, tasks, and roles are defined and modified and their impact on individuals, groups, and organizations. If the work is not designed well, the company must pay greater costs for workers' health, longer production processes or even penalties for not being able to meet the delivery schedule. This is visible to the condition in a rubber processing factory in North Sumatra. Work design aspects such as layouts, machinery and equipment, worker's physical working environment, work methods, and organizational policies have not been well-organized. Coagulum grinding machines into sheets are often damaged, resulting in 4 times the delay of product delivery in 2016, the presence of complaints of heat exposure submitted by workers, and workstation that has not been properly arranged is an indication of the need for work design. The research data will be collected through field observation, and distribution of questionnaires related aspects of work design. The result of the analysis depends on the respondent's answer from the distributed questionnaire regarding the 6 aspects studied.

Comparison of corneal endothelial changes following phacoemulsification with transversal and torsional phacoemulsification machines

PubMed Central

Ataş, Mustafa; Demircan, Süleyman; Karatepe Haşhaş, Arzu Seyhan; Gülhan, Ahmet; Zararsız, Gökmen

2014-01-01

AIM To compare and evaluate the phacoemulsification parameters and postoperative endothelial cell changes of two different phacoemulsification machines, each with different modes, but also to assess the relationship between postoperative endothelial cell loss and the phacoemulsification parameters, as well as the other factors in both groups. METHODS This prospective observational study was comprised of consecutive eligible cataract patients operated with phacoemulsification technique performed by the same surgeon using either a WHITESTAR Signature Ellips FX (transversal, group 1) or Infiniti OZil IP (torsional, group 2) machine. RESULTS The study included 86 patients. Baseline characteristics in the groups were similar. The median nuclear sclerosis grade was 3 (2-4) in the first group and 2 (2-4) in the second group (P=0.265). Both groups had similar phacoemulsification needle times (group 1: 60.63±36 s; group 2: 55.98±30 s; P=0.789). The percentage of endothelial cell loss 30d after surgery ranged from 3% to 15% with a median of 7% in group 1, and from 2% to 13% with a median of 6% in group 2; however, there was no statistically significant difference between the groups (P=0.407). Hexagonality (P=0.794) and the coefficient of variation (CV; P=0.142) did not differ significantly between the groups before and 30d after surgery. A significant positive correlation was found between the endothelial cell loss and nuclear sclerosis grade (group 1: P<0.001; group 2: P<0.001) and between the endothelial cell loss and average phacoemulsification power (group 1: P=0.007; group 2: P=0.008). CONCLUSION Both of these machines were efficient, with similar endothelial cell loss. This endothelial cell loss was related to the increased nuclear sclerosis grade and increased phacoemulsification power. PMID:25349800

Comparison of corneal endothelial changes following phacoemulsification with transversal and torsional phacoemulsification machines.

PubMed

Ataş, Mustafa; Demircan, Süleyman; Karatepe Haşhaş, Arzu Seyhan; Gülhan, Ahmet; Zararsız, Gökmen

2014-01-01

To compare and evaluate the phacoemulsification parameters and postoperative endothelial cell changes of two different phacoemulsification machines, each with different modes, but also to assess the relationship between postoperative endothelial cell loss and the phacoemulsification parameters, as well as the other factors in both groups. This prospective observational study was comprised of consecutive eligible cataract patients operated with phacoemulsification technique performed by the same surgeon using either a WHITESTAR Signature Ellips FX (transversal, group 1) or Infiniti OZil IP (torsional, group 2) machine. The study included 86 patients. Baseline characteristics in the groups were similar. The median nuclear sclerosis grade was 3 (2-4) in the first group and 2 (2-4) in the second group (P=0.265). Both groups had similar phacoemulsification needle times (group 1: 60.63±36 s; group 2: 55.98±30 s; P=0.789). The percentage of endothelial cell loss 30d after surgery ranged from 3% to 15% with a median of 7% in group 1, and from 2% to 13% with a median of 6% in group 2; however, there was no statistically significant difference between the groups (P=0.407). Hexagonality (P=0.794) and the coefficient of variation (CV; P=0.142) did not differ significantly between the groups before and 30d after surgery. A significant positive correlation was found between the endothelial cell loss and nuclear sclerosis grade (group 1: P<0.001; group 2: P<0.001) and between the endothelial cell loss and average phacoemulsification power (group 1: P=0.007; group 2: P=0.008). Both of these machines were efficient, with similar endothelial cell loss. This endothelial cell loss was related to the increased nuclear sclerosis grade and increased phacoemulsification power.

Flexible Conformable Clamps for a Machining Cell with Applications to Turbine Blade Machining.

DTIC Science & Technology

1983-05-01

PERIOD COVERED * FLEXIBLE CONFORMABLE CLAMPS FOR A MACHINING CELL Interim WITH APPLICATIONS TO TURBINE BLADE MACHINING 6. PERFORMING ORG. REPORT NUMBER...7. AuTmbR(s) 6. CONTRACT OR GRANT NUMBER(a) Eiki Kurokawa 3. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELE%4NTPROJECT. TASK Carnegie-Mellon...University AREA a WORK UhIT NUMBERS The Robotics Institute Pittsburgh, PA. 15213 II. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE May 1983. 13

An investigation of chatter and tool wear when machining titanium

NASA Technical Reports Server (NTRS)

Sutherland, I. A.

1974-01-01

The low thermal conductivity of titanium, together with the low contact area between chip and tool and the unusually high chip velocities, gives rise to high tool tip temperatures and accelerated tool wear. Machining speeds have to be considerably reduced to avoid these high temperatures with a consequential loss of productivity. Restoring this lost productivity involves increasing other machining variables, such as feed and depth-of-cut, and can lead to another machining problem commonly known as chatter. This work is to acquaint users with these problems, to examine the variables that may be encountered when machining a material like titanium, and to advise the machine tool user on how to maximize the output from the machines and tooling available to him. Recommendations are made on ways of improving tolerances, reducing machine tool instability or chatter, and improving productivity. New tool materials, tool coatings, and coolants are reviewed and their relevance examined when machining titanium.

Charging machine

DOEpatents

Medlin, John B.

1976-05-25

A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine.

The ultrastructural characteristics of porcine hepatocytes donated after cardiac death and preserved with warm machine perfusion preservation.

PubMed

Bochimoto, Hiroki; Matsuno, Naoto; Ishihara, Yo; Shonaka, Tatsuya; Koga, Daisuke; Hira, Yoshiki; Nishikawa, Yuji; Furukawa, Hiroyuki; Watanabe, Tsuyoshi

2017-01-01

The effects of warm machine perfusion preservation of liver grafts donated after cardiac death on the intracellular three-dimensional ultrastructure of the organelles in hepatocytes remain unclear. Here we analyzed comparatively the ultrastructure of the endomembrane systems in porcine hepatocytes under warm ischemia and successive hypothermic and midthermic machine perfusion preservation, a type of the warm machine perfusion. Porcine liver grafts which had a warm ischemia time of 60 minutes were perfused for 4 hours with modified University of Wisconsin gluconate solution. Group A grafts were preserved with hypothermic machine perfusion preservation at 8°C constantly for 4 hours. Group B grafts were preserved with rewarming up to 22°C by warm machine perfusion preservation for 4 hours. An analysis of hepatocytes after 60 minutes of warm ischemia by scanning electron microscope revealed the appearance of abnormal vacuoles and invagination of mitochondria. In the hepatocytes preserved by subsequent hypothermic machine perfusion preservation, strongly swollen mitochondria were observed. In contrast, the warm machine perfusion preservation could preserve the functional appearance of mitochondria in hepatocytes. Furthermore, abundant vacuoles and membranous structures sequestrating cellular organelles like autophagic vacuoles were frequently observed in hepatocytes after warm machine perfusion preservation. In conclusion, the ultrastructure of the endomembrane systems in the hepatocytes of liver grafts changed in accordance with the temperature conditions of machine perfusion preservation. In addition, temperature condition of the machine perfusion preservation may also affect the condition of the hepatic graft attributed to autophagy systems, and consequently alleviate the damage of the hepatocytes.

Learning as a Machine: Crossovers between Humans and Machines

ERIC Educational Resources Information Center

Hildebrandt, Mireille

2017-01-01

This article is a revised version of the keynote presented at LAK '16 in Edinburgh. The article investigates some of the assumptions of learning analytics, notably those related to behaviourism. Building on the work of Ivan Pavlov, Herbert Simon, and James Gibson as ways of "learning as a machine," the article then develops two levels of…

20. MACHINE SHOP, LOOKING SOUTH. SHOP IS EQUIPPED WITH A ...

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

20. MACHINE SHOP, LOOKING SOUTH. SHOP IS EQUIPPED WITH A 25-TON SHAW CRANE TO HANDLE PARTS FROM RAIL CARS INTO THE SHOP. MACHINE SHOP HANDLES ALL NECESSARY REPAIR WORK ON THE DOCK MACHINERY. - Pennsylvania Railway Ore Dock, Lake Erie at Whiskey Island, approximately 1.5 miles west of Public Square, Cleveland, Cuyahoga County, OH

30 CFR 48.27 - Training of miners assigned to a task in which they have had no previous experience; minimum...

Code of Federal Regulations, 2012 CFR

2012-07-01

..., drilling machine operators, haulage and conveyor systems operators, ground control machine operators, AMS... practice in the assigned tasks, and the performance of work duties at times or places where production is..., while under direct and immediate supervision and production is in progress, operation of the machine or...

30 CFR 48.27 - Training of miners assigned to a task in which they have had no previous experience; minimum...

Code of Federal Regulations, 2011 CFR

2011-07-01

..., drilling machine operators, haulage and conveyor systems operators, ground control machine operators, AMS... practice in the assigned tasks, and the performance of work duties at times or places where production is..., while under direct and immediate supervision and production is in progress, operation of the machine or...

30 CFR 48.27 - Training of miners assigned to a task in which they have had no previous experience; minimum...

Code of Federal Regulations, 2014 CFR

2014-07-01

..., drilling machine operators, haulage and conveyor systems operators, ground control machine operators, AMS... practice in the assigned tasks, and the performance of work duties at times or places where production is..., while under direct and immediate supervision and production is in progress, operation of the machine or...

30 CFR 48.27 - Training of miners assigned to a task in which they have had no previous experience; minimum...

Code of Federal Regulations, 2013 CFR

2013-07-01

..., drilling machine operators, haulage and conveyor systems operators, ground control machine operators, AMS... practice in the assigned tasks, and the performance of work duties at times or places where production is..., while under direct and immediate supervision and production is in progress, operation of the machine or...

40 CFR 63.463 - Batch vapor and in-line cleaning machine standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... described in § 63.463(e)(2)(ii). (2) Each cleaning machine shall have a freeboard ratio of 0.75 or greater... of 1.0, superheated vapor. 2 Freeboard refrigeration device, superheated vapor. 3 Working-mode cover...) or (2) of this section as appropriate. The owner or operator of a continuous web cleaning machine...

The Machine Scoring of Writing

ERIC Educational Resources Information Center

McCurry, Doug

2010-01-01

This article provides an introduction to the kind of computer software that is used to score student writing in some high stakes testing programs, and that is being promoted as a teaching and learning tool to schools. It sketches the state of play with machines for the scoring of writing, and describes how these machines work and what they do.…

Learning Activity Packets for Grinding Machines. Unit I--Grinding Machines.

ERIC Educational Resources Information Center

Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This learning activity packet (LAP) is one of three that accompany the curriculum guide on grinding machines. It outlines the study activities and performance tasks for the first unit of this curriculum guide. Its purpose is to aid the student in attaining a working knowledge of this area of training and in achieving a skilled or moderately…

Introduction to Machine Tool Technology, Machine Shop Work--Intermediate: 9555.01.

ERIC Educational Resources Information Center

Dade County Public Schools, Miami, FL.

The course outline has been prepared as a guide to assist the instructor to plan systematically and to present meaningful lessons programmed to meet the necessary training needed by the machine shop student. A beginning course, the four blocks of instruction contained in the outline are designed to enable the student to obtain the manipulative…

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

Effect of surface anodization on stability of orthodontic microimplant

PubMed Central

Karmarker, Sanket; Yu, Wonjae

2012-01-01

Objective To determine the effect of surface anodization on the interfacial strength between an orthodontic microimplant (MI) and the rabbit tibial bone, particularly in the initial phase after placement. Methods A total of 36 MIs were driven into the tibias of 3 mature rabbits by using the self-drilling method and then removed after 6 weeks. Half the MIs were as-machined (n = 18; machined group), while the remaining had anodized surfaces (n = 18; anodized group). The peak insertion torque (PIT) and the peak removal torque (PRT) values were measured for the 2 groups of MIs. These values were then used to calculate the interfacial shear strength between the MI and cortical bone. Results There were no statistical differences in terms of PIT between the 2 groups. However, mean PRT was significantly greater for the anodized implants (3.79 ± 1.39 Ncm) than for the machined ones (2.05 ± 1.07 Ncm) (p < 0.01). The interfacial strengths, converted from PRT, were calculated at 10.6 MPa and 5.74 MPa for the anodized and machined group implants, respectively. Conclusions Anodization of orthodontic MIs may enhance their early-phase retention capability, thereby ensuring a more reliable source of absolute anchorage. PMID:23112925

A self-contained quantum harmonic engine

NASA Astrophysics Data System (ADS)

Reid, B.; Pigeon, S.; Antezza, M.; De Chiara, G.

2017-12-01

We propose a system made of three quantum harmonic oscillators as a compact quantum engine for producing mechanical work. The three oscillators play respectively the role of the hot bath, the working medium and the cold bath. The working medium performs an Otto cycle during which its frequency is changed and it is sequentially coupled to each of the two other oscillators. As the two environments are finite, the lifetime of the machine is finite and after a number of cycles it stops working and needs to be reset. Remarkably, we show that this machine can extract more than 90% of the available energy during 70 cycles. Differently from usually investigated infinite-reservoir configurations, this machine allows the protection of induced quantum correlations and we analyse the entanglement and quantum discord generated during the strokes. Interestingly, we show that high work generation is always accompanied by large quantum correlations. Our predictions can be useful for energy management at the nanoscale, and can be relevant for experiments with trapped ions and experiments with light in integrated optical circuits.

Intelligent Machines in the 21st Century: Automating the Processes of Inference and Inquiry

NASA Technical Reports Server (NTRS)

Knuth, Kevin H.

2003-01-01

The last century saw the application of Boolean algebra toward the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines. in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. However, modern intelligent machines work by inferring knowledge using only their pre-programmed prior knowledge and the data provided. They lack the ability to ask questions, or request data that would aid their inferences. Recent advances in understanding the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we identified the algebra of questions as the free distributive algebra, which now allows us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper we describe this logic of inference and inquiry using the mathematics of partially ordered sets and the scaffolding of lattice theory, discuss the far-reaching implications of the methodology, and demonstrate its application with current examples in machine learning. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them to not only make inferences from data, but also decide which question to ask, experiment to perform, or measurement to take given what they have learned and what they are designed to understand.

Predictive Surface Roughness Model for End Milling of Machinable Glass Ceramic

NASA Astrophysics Data System (ADS)

Mohan Reddy, M.; Gorin, Alexander; Abou-El-Hossein, K. A.

2011-02-01

Advanced ceramics of Machinable glass ceramic is attractive material to produce high accuracy miniaturized components for many applications in various industries such as aerospace, electronics, biomedical, automotive and environmental communications due to their wear resistance, high hardness, high compressive strength, good corrosion resistance and excellent high temperature properties. Many research works have been conducted in the last few years to investigate the performance of different machining operations when processing various advanced ceramics. Micro end-milling is one of the machining methods to meet the demand of micro parts. Selecting proper machining parameters are important to obtain good surface finish during machining of Machinable glass ceramic. Therefore, this paper describes the development of predictive model for the surface roughness of Machinable glass ceramic in terms of speed, feed rate by using micro end-milling operation.

Proceedings of the IMOG (Interagency Manufacturing Operations Group) Numerical Systems Group. 62nd Meeting

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

Maes, G.J.

1993-10-01

This document contains the proceedings of the 62nd Interagency Manufacturing Operations Group (IMOG) Numerical Systems Group. Included are the minutes of the 61st meeting and the agenda for the 62nd meeting. Presentations at the meeting are provided in the appendices to this document. Presentations were: 1992 NSG Annual Report to IMOG Steering Committee; Charter for the IMOG Numerical Systems Group; Y-12 Coordinate Measuring Machine Training Project; IBH NC Controller; Automatically Programmed Metrology Update; Certification of Anvil-5000 for Production Use at the Y-12 Plant; Accord Project; Sandia National Laboratories {open_quotes}Accord{close_quotes}; Demo/Anvil Tool Path Generation 5-Axis; Demo/Video Machine/Robot Animation Dynamics; Demo/Certification ofmore » Anvil Tool Path Generation; Tour of the M-60 Inspection Machine; Distributed Numerical Control Certification; Spline Usage Method; Y-12 NC Engineering Status; and Y-12 Manufacturing CAD Systems.« less

X-Ray Backscatter Machine Support Frame

NASA Technical Reports Server (NTRS)

Cannon, Brooke

2010-01-01

This summer at Kennedy Space Center, I spent 10 weeks as an intern working at the Prototype Development Lab. During this time I learned about the design and machining done here at NASA. I became familiar with the process from where a design begins in Pro/Engineer and finishes at the hands of the machinists. As an intern I was given various small jobs to do and then one project of my own. My personal project was a job for the Applied Physics Lab; in their work they use an X-Ray Backscatter machine. Previously it was resting atop a temporary frame that limited the use of the machine. My job was to design a frame for the machine to rest upon that would allow a full range of sample sizes. The frame was required to support the machine and provide a strain relief for the cords attached to the machine as it moved in the x and y directions. Calculations also had to be done to be sure the design would be able to withstand any loads or outside sources of stress. After the calculations proved the design to be ready to withstand the requirements, the parts were ordered or fabricated, as required. This helped me understand the full process of jobs sent to the Prototype Development Lab.

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.

Controlling the type and the form of chip when machining steel

NASA Astrophysics Data System (ADS)

Gruby, S. V.; Lasukov, A. A.; Nekrasov, R. Yu; Politsinsky, E. V.; Arkhipova, D. A.

2016-08-01

The type of the chip produced in the process of machining influences many factors of production process. Controlling the type of chip when cutting metals is important for producing swarf chips and for easing its utilization as well as for protecting the machined surface, cutting tool and the worker. In the given work we provide the experimental data on machining structural steel with implanted tool. The authors show that it is possible to control the chip formation process to produce the required type of chip by selecting the material for machining the tool surface.

Multicutter machining of compound parametric surfaces

NASA Astrophysics Data System (ADS)

Hatna, Abdelmadjid; Grieve, R. J.; Broomhead, P.

2000-10-01

Parametric free forms are used in industries as disparate as footwear, toys, sporting goods, ceramics, digital content creation, and conceptual design. Optimizing tool path patterns and minimizing the total machining time is a primordial issue in numerically controlled (NC) machining of free form surfaces. We demonstrate in the present work that multi-cutter machining can achieve as much as 60% reduction in total machining time for compound sculptured surfaces. The given approach is based upon the pre-processing as opposed to the usual post-processing of surfaces for the detection and removal of interference followed by precise tracking of unmachined areas.

The Altar Machine in the Church Mother of Gangi (Palermo, Italy). Interpretation of the past uses, scientific investigation and preservation challenge

PubMed Central

2012-01-01

Background The aim of this work was to study the Altar Machine in the Church Mother of Gangi, a little town near Palermo (Italy) regarding the history, the technical manufacture, the constitutive materials and the state of preservation. The Altar Machine was dated back to the second half of the 18th century; it is constituted by carved and painted wood, a complex system of winch and pulleys allows move various statues and parts of the Machine in accordance with the baroque scenography machineries. Results The observation and survey of the mechanisms allowed formulate hypothesis on a more ancient mode of operation of the Altar Machine. Laboratory analysis revealed the presence of many superimposed layers constituted by several different materials (protein binders, siccative oils, natural terpene resins, shellac, calcium carbonate, gypsum, lead white, brass, zinc white, iron oxides) and different wood species employed for the original and restoration elements of the Machine. This is due to a continuous usage of the object that has got a demo-ethno-anthropological significance. Microclimate monitoring (relative humidity RH and temperature T) put in evidence that most of the data fall outside the tolerance intervals, i.e. the RH and T limits defined by the international standards. In particular, T values were generally high (out of the tolerance range) but they appeared to be quite constant; on the other hand RH values fell almost always inside the tolerance area but they often exhibited dangerous variations. Conclusions The characterization of the constitutive materials provided useful information both to support the dating of the Machine proposed by the inscription and to obtain a base of data for a possible conservation work. The microclimate monitoring put in evidence that the temperature and relative humidity values are not always suitable to correctly preserve the artefact. The careful in situ investigation confirmed an on-going climate induced damage to the Altar Machine that, associated to the deterioration caused by its usage, may have dramatic consequences on this unique and peculiar work of art. The results of this work will have potential implications in the near future regarding a probable conservation project on the Machine. PMID:22616574

Method and system for providing work machine multi-functional user interface

DOEpatents

Hoff, Brian D [Peoria, IL; Akasam, Sivaprasad [Peoria, IL; Baker, Thomas M [Peoria, IL

2007-07-10

A method is performed to provide a multi-functional user interface on a work machine for displaying suggested corrective action. The process includes receiving status information associated with the work machine and analyzing the status information to determine an abnormal condition. The process also includes displaying a warning message on the display device indicating the abnormal condition and determining one or more corrective actions to handle the abnormal condition. Further, the process includes determining an appropriate corrective action among the one or more corrective actions and displaying a recommendation message on the display device reflecting the appropriate corrective action. The process may also include displaying a list including the remaining one or more corrective actions on the display device to provide alternative actions to an operator.

A Vision for MSSP

NASA Astrophysics Data System (ADS)

Mottershead, John E.

2015-05-01

MSSP is our journal. It developed out of the research community and in that sense is owned by us, its readers and authors. It was started by a small group, all international leaders in System Identification, Measurement and Signal Processing, Modal Analysis, Machine and Structural Diagnostics etc., several of whom still provide invaluable advice and guidance through their work on the Editorial Board. Most importantly, Simon's leadership for almost three decades has been inspirational, dedicated and energetic. So, it is a great honour for me to have been invited to assume the editorial leadership of MSSP and continue the work of serving a new generation of researchers in the broad and evolving field of Mechanical Systems and Signal Processing.

Handling knowledge via Concept Maps: a space weather use case

NASA Astrophysics Data System (ADS)

Messerotti, Mauro; Fox, Peter

Concept Maps (Cmaps) are powerful means for knowledge coding in graphical form. As flexible software tools exist to manipulate the knowledge embedded in Cmaps in machine-readable form, such complex entities are suitable candidates not only for the representation of ontologies and semantics in Virtual Observatory (VO) architectures, but also for knowledge handling and knowledge discovery. In this work, we present a use case relevant to space weather applications and we elaborate on its possible implementation and adavanced use in Semantic Virtual Observatories dedicated to Sun-Earth Connections. This analysis was carried out in the framework of the Electronic Geophysical Year (eGY) and represents an achievement synergized by the eGY Virtual Observatories Working Group.

Effects of the sliding rehabilitation machine on balance and gait in chronic stroke patients - a controlled clinical trial.

PubMed

Byun, Seung-Deuk; Jung, Tae-Du; Kim, Chul-Hyun; Lee, Yang-Soo

2011-05-01

To investigate the effects of a sliding rehabilitation machine on balance and gait in chronic stroke patients. A non-randomized crossover design. Inpatient rehabilitation in a general hospital. Thirty patients with chronic stroke who had medium or high falling risk as determined by the Berg Balance Scale. Participants were divided into two groups and underwent four weeks of training. Group A (n = 15) underwent training with the sliding rehabilitation machine for two weeks with concurrent conventional training, followed by conventional training only for another two weeks. Group B (n = 15) underwent the same training in reverse order. The effect of the experimental period was defined as the sum of changes during training with sliding rehabilitation machine in each group, and the effect of the control period was defined as those during the conventional training only in each group. Functional Ambulation Category, Berg Balance Scale, Six-Minute Walk Test, Timed Up and Go Test, Korean Modified Barthel Index, Modified Ashworth Scale and Manual Muscle Test. Statistically significant improvements were observed in all parameters except Modified Ashworth Scale in the experimental period, but only in Six-Minute Walk Test (P < 0.01) in the control period. There were also statistically significant differences in the degree of change in all parameters in the experimental period as compared to the control period. The sliding rehabilitation machine may be a useful tool for the improvement of balance and gait abilities in chronic stroke patients.

Monitoring the tobacco use epidemic II. The Agent: Current and Emerging Tobacco Products

PubMed Central

Stellman, Steven D.; Djordjevic, Mirjana V.

2009-01-01

Objective This Agent paper summarizes the findings and recommendations of the Agent (product) Working Group of the November, 2002, National Tobacco Monitoring, Research and Evaluation Workshop. Methods The Agent Working Group evaluated the need to develop new surveillance systems for quantifying ingredients and emissions of tobacco and tobacco smoke and to improve methods to assess uptake and metabolism of these constituents taking into account variability in human smoking behavior. Results The toxic properties of numerous tobacco and tobacco smoke constituents are well known, yet systematic monitoring of tobacco products has historically been limited to tar, nicotine, and CO in mainstream cigarette smoke using a machine-smoking protocol that does not reflect human smoking behavior. Toxicity of smokeless tobacco products has not been regularly monitored. Tobacco products are constantly changing and untested products are introduced into the marketplace with great frequency, including potential reduced-exposure products (PREPs). The public health impact of new or modified tobacco products is unknown. Conclusions Systematic surveillance is recommended for mainstream smoke constituents such as polycyclic aromatic hydrocarbons (PAH), tobacco-specific nitrosamines (TSNA), total and free-base nicotine, volatile organic compounds, aromatic amines, and metals; and design attributes including tobacco blend, additives, and filter ventilation. Research on smoking topography is recommended to help define machine-smoking protocols for monitoring emissions reflective of human smoking behavior. Recommendations are made for marketplace product sampling and for population monitoring of smoking topography, emissions of toxic constituents, biomarkers of exposure and, eventually, risk of tobacco-related diseases. PMID:18848577

Draftsmen at Work during Construction of the Aircraft Engine Research Laboratory

NASA Image and Video Library

1942-09-21

The National Advisory Committee for Aeronautics (NACA) Aircraft Engine Research Laboratory was designed by a group of engineers at the Langley Memorial Aeronautical Laboratory in late 1940 and 1941. Under the guidance of Ernest Whitney, the men worked on drawings and calculations in a room above Langley’s Structural Research Laboratory. The main Aircraft Engine Research Laboratory design group originally consisted of approximately 30 engineers and draftsmen, but there were smaller groups working separately on specific facilities. The new engine lab would have six principal buildings: the Engine Research Building, hangar, Fuels and Lubricants Building, Administration Building, Propeller Test Stand, and Altitude Wind Tunnel. In December 1941 most of those working on the project transferred to Cleveland from Langley. Harrison Underwood and Charles Egan led 18 architectural, 26 machine equipment, 3 structural and 10 mechanical draftsmen. Initially these staff members were housed in temporary offices in the hangar. As sections of the four-acre Engine Research Building were completed in the summer of 1942, the design team began relocating there. The Engine Research Building contained a variety of test cells and laboratories to address virtually every aspect of piston engine research. It also contained a two-story office wing, seen in this photograph that would later house many of the powerplant research engineers.

Metaphorical constructions of hypertension among three ethnic groups in the Netherlands.

PubMed

Schuster, John; Beune, Erik; Stronks, Karien

2011-12-01

This article examines the various metaphors used by hypertensive patients from different ethnic groups in multi-ethnic and multicultural Netherlands. The choice for the study of metaphors is based on the need of people to use metaphors, analogies and symbols to make sense of and express their illness experiences. Given the high prevalence of hypertension in Western countries, such as the Netherlands, and the fact that hypertension is also a major risk factor for cardiovascular disease among immigrants makes it necessary to study the various metaphors these groups use when speaking about the causes and consequences of their hypertension. This can contribute to a shared understanding and communication about this illness. Discursive analysis of the metaphorical constructions of the causes and consequences of hypertension 55 participants of Creole, (White) Dutch and Hindustani descent employed in-depth interviews. The findings illustrate that the participants use several metaphors to 'live' their hypertension. The metaphors some of the participants employed to explain the origins of their hypertension construct the human body and its organs as machines or parts of machines. When speaking about the possible consequences the participants used metaphors that represented of hypertension as an unknown enemy, they feared because of its silent, invisible and uncontrollable character and the way it abruptly makes itself known. Metaphors people employ to speak about their hypertension open up a space for patients to explain how they understand their hypertension and how they want to live with it even if it means resisting recommendations put forward by their doctors. It is therefore necessary to find metaphors that can work for health care providers and patients that work the best for communication about hypertension and its medical treatment.

Toward Harnessing User Feedback For Machine Learning

DTIC Science & Technology

2006-10-02

machine learning systems. If this resource-the users themselves-could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved and the users? understanding and trust of the system could improve as well. We conducted a think-aloud study to see how willing users were to provide feedback and to understand what kinds of feedback users could give. Users were shown explanations of machine learning predictions and asked to provide feedback to improve the predictions. We found that users

Intelligible machine learning with malibu.

PubMed

Langlois, Robert E; Lu, Hui

2008-01-01

malibu is an open-source machine learning work-bench developed in C/C++ for high-performance real-world applications, namely bioinformatics and medical informatics. It leverages third-party machine learning implementations for more robust bug-free software. This workbench handles several well-studied supervised machine learning problems including classification, regression, importance-weighted classification and multiple-instance learning. The malibu interface was designed to create reproducible experiments ideally run in a remote and/or command line environment. The software can be found at: http://proteomics.bioengr. uic.edu/malibu/index.html.

The infrared camera application for calculating the impact of the feed screw thermal expansion on machining accuracy

NASA Astrophysics Data System (ADS)

Matras, A.

2017-08-01

The paper discusses the impact of the feed screw heating on the machining accuracy. The test stand was built based on HASS Mini Mill 2 CNC milling machine and a Flir SC620 infrared camera. Measurements of workpiece were performed on Talysurf Intra 50 Taylor Hobson profilometer. The research proved that the intensive work of the milling machine lasted 60 minutes, causing thermal expansion of the feed screw what influence on the dimension error of the workpiece.

Three-point compound sine plate offers cost and weight savings

NASA Technical Reports Server (NTRS)

Barras, A. P.

1972-01-01

Work piece adjustment fixture reduces size, weight and set-up complexity of alignment platforms used in metal blank machining. Design benefits designers and manufacturers of machine tools and measuring equipment.

2. GENERAL VIEW LOOKING NORTHEAST, SHOWING COKE MACHINE (CENTER), INTERMEDIATE ...

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

2. GENERAL VIEW LOOKING NORTHEAST, SHOWING COKE MACHINE (CENTER), INTERMEDIATE TIPPLE (RIGHT), AND OVENS - Shoaf Mine & Coke Works, East side of Shoaf, off Township Route 472, Shoaf, Fayette County, PA

122. BENCH SHOP, SOUTHWEST CORNER SHOWING WOOD BORING MACHINE. DOOR ...

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

122. BENCH SHOP, SOUTHWEST CORNER SHOWING WOOD BORING MACHINE. DOOR TO WOODSHOP ON RIGHT. - Gruber Wagon Works, Pennsylvania Route 183 & State Hill Road at Red Bridge Park, Bernville, Berks County, PA

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.

An epidemiological study of low back pain in professional drivers

NASA Astrophysics Data System (ADS)

Bovenzi, Massimo; Rui, Francesca; Negro, Corrado; D'Agostin, Flavia; Angotzi, Giuliano; Bianchi, Sandra; Bramanti, Lucia; Festa, GianLuca; Gatti, Silvana; Pinto, Iole; Rondina, Livia; Stacchini, Nicola

2006-12-01

The prevalence of low back pain (LBP) was investigated in 598 Italian professional drivers exposed to whole-body vibration (WBV) and ergonomic risk factors (drivers of earth moving machines, fork-lift truck drivers, truck drivers, bus drivers). The control group consisted of a small sample of 30 fire inspectors not exposed to WBV. Personal, occupational and health histories were collected by means of a structured questionnaire. Vibration measurements were performed on representative samples of the machines and vehicles used by the driver groups. From the vibration magnitudes and exposure durations, alternative measures of vibration dose were estimated for each subject. Daily vibration exposure, expressed in terms of 8-h energy-equivalent frequency-weighted acceleration, A(8), averaged 0.28-0.61 (range 0.10-1.18) m s -2 rms in the driver groups. Duration of exposure to WBV ranged between 1 and 41 years. The 7-day and 12-month prevalence of LBP was greater in the driver groups than in the controls. In the professional drivers, the occurrence of 12-month LBP, high intensity of LBP (Von Korff pain scale score ⩾5), and LBP disability (Roland & Morris disability scale score ⩾12) significantly increased with increasing cumulative vibration exposure. Even though several alternative measures of vibration exposure were associated with LBP outcomes, nevertheless a more regular trend of association with LBP was found for vibration dose expressed as ∑ a vit i (m s -2 h), in which the frequency-weighted acceleration, a v, and lifetime exposure duration, t, were given equal weight. In multivariate data analysis, individual characteristics (e.g. age, body mass index) and a physical load index (derived from combining manual materials handling and awkward postures) were significantly associated with LBP outcomes, while psychosocial work factors (e.g. job decision, job support) showed a marginal relation to LBP. This study tends to confirm that professional driving in industry is associated with an increased risk of work-related LBP. Exposure to WBV and physical loading factors at work are important components of the multifactorial origin of LBP in professional drivers.

The Role of Automata and Machine Theory in School and College Mathematics Syllabuses.

ERIC Educational Resources Information Center

Holcombe, M.

1981-01-01

The introduction of certain topics in the theory of machines and languages into school and college mathematics courses in place of the more usual discussion of groups and formal logic is proposed. Examples of machines and languages and their interconnections suitable for such courses are outlined. (MP)

Development of a 3-D X-ray system

NASA Astrophysics Data System (ADS)

Evans, James Paul Owain

The interpretation of standard two-dimensional x-ray images by humans is often very difficult. This is due to the lack of visual cues to depth in an image which has been produced by transmitted radiation. The solution put forward in this research is to introduce binocular parallax, a powerful physiological depth cue, into the resultant shadowgraph x-ray image. This has been achieved by developing a binocular stereoscopic x-ray imaging technique, which can be used for both visual inspection by human observers and also for the extraction of three-dimensional co-ordinate information. The technique is implemented in the design and development of two experimental x-ray systems and also the development of measurement algorithms. The first experimental machine is based on standard linear x-ray detector arrays and was designed as an optimum configuration for visual inspection by human observers. However, it was felt that a combination of the 3-D visual inspection capability together with a measurement facility would enhance the usefulness of the technique. Therefore, both a theoretical and an empirical analysis of the co-ordinate measurement capability of the machine has been carried out. The measurement is based on close-range photogrammetric techniques. The accuracy of the measurement has been found to be of the order of 4mm in x, 3mm in y and 6mm in z. A second experimental machine was developed and based on the same technique as that used for the first machine. However, a major departure has been the introduction of a dual energy linear x-ray detector array which will allow, in general, the discrimination between organic and inorganic substances. The second design is a compromise between ease of visual inspection for human observers and optimum three-dimensional co-ordinate measurement capability. The system is part of an on going research programme into the possibility of introducing psychological depth cues into the resultant x-ray images. The research presented in this thesis was initiated to enhance the visual interpretation of complex x-ray images, specifically in response to problems encountered in the routine screening of freight by HM. Customs and Excise. This phase of the work culminated in the development of the first experimental machine. During this work the security industry was starting to adopt a new type of x-ray detector, namely the dual energy x-ray sensor. The Department of Transport made available funding to the Police Scientific Development Branch (P.S.D.B.), part of The Home Office Science and Technology Group, to investigate the possibility of utilising the dual energy sensor in a 3-D x-ray screening system. This phase of the work culminated in the development of the second experimental machine.

Heat transfer head for a Stirling cycle machine

NASA Technical Reports Server (NTRS)

Emigh, Stuart G. (Inventor); Noble, Jack E. (Inventor); Lehmann, Gregory A. (Inventor)

1991-01-01

A common heat acceptor is provided between opposed displacers in a Stirling cycle machine. It includes two sets of open channels in separate fluid communications with the expansion spaces of the receptive cyclinders. The channels confine movement of working fluid in separate paths that extend between the expansion space of one cylinder and the compression space of the other. The method for operating the machine involves alternatively directing working fluid from the expansion space of each cylinder in a fluid path leading to the compression space of the other cylinder and from the compression space of each cylinder in a fluid path leading to the expansion space of the other cylinder.

Paradigms for Realizing Machine Learning Algorithms.

PubMed

Agneeswaran, Vijay Srinivas; Tonpay, Pranay; Tiwary, Jayati

2013-12-01

The article explains the three generations of machine learning algorithms-with all three trying to operate on big data. The first generation tools are SAS, SPSS, etc., while second generation realizations include Mahout and RapidMiner (that work over Hadoop), and the third generation paradigms include Spark and GraphLab, among others. The essence of the article is that for a number of machine learning algorithms, it is important to look beyond the Hadoop's Map-Reduce paradigm in order to make them work on big data. A number of promising contenders have emerged in the third generation that can be exploited to realize deep analytics on big data.

Machine Learning in the Presence of an Adversary: Attacking and Defending the SpamBayes Spam Filter

DTIC Science & Technology

2008-05-20

Machine learning techniques are often used for decision making in security critical applications such as intrusion detection and spam filtering...filter. The defenses shown in this thesis are able to work against the attacks developed against SpamBayes and are sufficiently generic to be easily extended into other statistical machine learning algorithms.

Method of fabricating a micro machine

DOEpatents

Stalford, Harold L

2014-11-11

A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

Methods and systems for micro machines

DOEpatents

Stalford, Harold L.

2018-03-06

A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

Methods and systems for micro machines

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

Stalford, Harold L.

2017-04-11

A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

Methods and systems for micro machines

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

Stalford, Harold L.

A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

Color line-scan technology in industrial applications

NASA Astrophysics Data System (ADS)

Lemstrom, Guy F.

1995-10-01

Color machine vision opens new possibilities for industrial on-line quality control applications. With color machine vision it's possible to detect different colors and shades, make color separation, spectroscopic applications and at the same time do measurements in the same way as with gray scale technology. These can be geometrical measurements such as dimensions, shape, texture etc. By combining these technologies in a color line scan camera, it brings the machine vision to new dimensions of realizing new applications and new areas in the machine vision business. Quality and process control requirements in the industry get more demanding every day. Color machine vision can be the solution for many simple tasks that haven't been realized with gray scale technology. The lack of detecting or measuring colors has been one reason why machine vision has not been used in quality control as much as it could have been. Color machine vision has shown a growing enthusiasm in the industrial machine vision applications. Potential areas of the industry include food, wood, mining and minerals, printing, paper, glass, plastic, recycling etc. Tasks are from simple measuring to total process and quality control. The color machine vision is not only for measuring colors. It can also be for contrast enhancement, object detection, background removing, structure detection and measuring. Color or spectral separation can be used in many different ways for working out machine vision application than before. It's only a question of how to use the benefits of having two or more data per measured pixel, instead of having only one as in case with traditional gray scale technology. There are plenty of potential applications already today that can be realized with color vision and it's going to give more performance to many traditional gray scale applications in the near future. But the most important feature is that color machine vision offers a new way of working out applications, where machine vision hasn't been applied before.

Machine Learning Techniques in Clinical Vision Sciences.

PubMed

Caixinha, Miguel; Nunes, Sandrina

2017-01-01

This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration, and diabetic retinopathy, these ocular pathologies being the major causes of irreversible visual impairment.

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

PubMed

Zhou, Jing; Wu, Xiao-ming; Zeng, Wei-jie

2015-12-01

Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of the electroencephalogram (EEG) signals. The purpose of this study is to find a novel and simpler method for detecting apnea patients and to quantify nonlinear characteristics of the sleep apnea. 30 min EEG scaling exponents that quantify power-law correlations were computed using detrended fluctuation analysis (DFA) and compared between six SAS and six healthy subjects during sleep. The mean scaling exponents were calculated every 30 s and 360 control values and 360 apnea values were obtained. These values were compared between the two groups and support vector machine (SVM) was used to classify apnea patients. Significant difference was found between EEG scaling exponents of the two groups (p < 0.001). SVM was used and obtained high and consistent recognition rate: average classification accuracy reached 95.1% corresponding to the sensitivity 93.2% and specificity 98.6%. DFA of EEG is an efficient and practicable method and is helpful clinically in diagnosis of sleep apnea.

Achieving Small Structures in Thin NiTi Sheets for Medical Applications with Water Jet and Micro Machining: A Comparison

NASA Astrophysics Data System (ADS)

Frotscher, M.; Kahleyss, F.; Simon, T.; Biermann, D.; Eggeler, G.

2011-07-01

NiTi shape memory alloys (SMA) are used for a variety of applications including medical implants and tools as well as actuators, making use of their unique properties. However, due to the hardness and strength, in combination with the high elasticity of the material, the machining of components can be challenging. The most common machining techniques used today are laser cutting and electrical discharge machining (EDM). In this study, we report on the machining of small structures into binary NiTi sheets, applying alternative processing methods being well-established for other metallic materials. Our results indicate that water jet machining and micro milling can be used to machine delicate structures, even in very thin NiTi sheets. Further work is required to optimize the cut quality and the machining speed in order to increase the cost-effectiveness and to make both methods more competitive.

Support vector machine in machine condition monitoring and fault diagnosis

NASA Astrophysics Data System (ADS)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

Looking west inside of the machine/forge shop at chargin door ...

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

Looking west inside of the machine/forge shop at chargin door of the forging furnace. - U.S. Steel Edgar Thomson Works, Auxiliary Buildings & Shops, Along Monongahela River, Braddock, Allegheny County, PA

19. SECOND FLOOR, CARDING MACHINE, BY 'CARDING SPECIALISTS, CO., LTD., ...

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

19. SECOND FLOOR, CARDING MACHINE, BY 'CARDING SPECIALISTS, CO., LTD., PELLON LAND WORKS, HALIFAX, ENGLAND, SN #M2983 14 (EST. DATE 1940'S+). - Bamberg Cotton Mill, Main Street, Bamberg, Bamberg County, SC

3. INTERIOR VIEW LOOKING SOUTH SHOWING PUNCH AND SHEAR MACHINE ...

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

3. INTERIOR VIEW LOOKING SOUTH SHOWING PUNCH AND SHEAR MACHINE (manufactured by Cleveland Punch and Shear Works Company, USA) - Cambria & Indiana Railroad, Blacksmith Shop, .25 miles northwest of Colver, Colver, Cambria County, PA

Training on automated machine guidance.

DOT National Transportation Integrated Search

2009-05-01

"Beginning in 2006, WisDOT and the Construction Materials Support Center (CMSC) at UW-Madison worked together : to develop the specifications and the QA/QC procedures for GPS machine guidance on highway grading projects. These : specifications and pr...

Incidence of MSDs and neck and back pain among logging machine operators in the southern U.S.

PubMed

Lynch, S M; Smidt, M F; Merrill, P D; Sesek, R F

2014-07-01

There are limited data about the incidence and prevalence of musculoskeletal disorders (MSDs) among loggers in the southern U.S. despite the risk factors associated with these occupations. Risk factors are both personal (age, body mass index, etc.) and job-related (awkward postures, repetitive hand and foot movements, vibration, etc.). A survey was conducted to estimate the incidence of self-reported pain and diagnosed MSDs and to study the relationship with known risk factors. Respondents were loggers attending training and continuing education classes. Respondents were asked to identify personal attributes, machine use, awkward postures, repetitive movements, and recent incidence of pain and medical diagnoses. All were male with an average age of 44 (range of 19-67) and an average body mass index of 31.3. Most were machine operators (97%) who have worked in the logging industry for an average of 22.9 years. Most machines identified were manufactured within the past ten years (average machine age 6.7 years). For machine operators, 10.5% (16) reported an MSD diagnosis, 74.3% (113) reported at least mild back pain, and 71.7% (109) reported at least mild neck pain over the past year. Further analysis attempted to identify an association between personal attributes, machine use, posture, and pain. Risk factors related to machine use may be biased since most survey respondents had considerable choice or control in working conditions, as they were firm owners and/or supervisors.

EMCORE - Emotional Cooperative Groupware

NASA Astrophysics Data System (ADS)

Fasoli, N.; Messina, A.

In the last years considerable effort has been spent to develop groupware applications. Despite this, no general consenus has been met by groupware applications in computer field. Interdisciplinary approach could prove very useful to overcome these difficulties. A workgroup is not simply a set of people gathered together, working for a common goal. It can also be thought as a strong, hard mental reality. Actually, sociological and psychological definitions of group differ considerably. At sociological level a group is generally described in the view of the activities and events occurring inside the group itself. On the other hand, the psychological group approach considers not only the actions occurring inside the group, but also all the mental activities originated by belonging to the group, be they emotional or rational nature. Since early '60 simple work group (i.e. discussion group) has been analyzed in his psychological behavior. EMCORE is a prototype which aims to support computer science methods with psychological approach. The tool has been developed for a discussion group supported by heterogeneous distributed systems and has been implemented according to the CORBA abstraction augmented by the machine independent JAVA language. The tool allows all the common activities of a discussion group: discussion by voice or by chatting board if multimedia device are not present; discussion and elaboration of a shared document by text and/or graphic editor. At the same time, tools are provided for the psychoanalytic approach, according to a specific methodology.

Medical, personal, and occupational outcomes for work-related amputations in Minnesota.

PubMed

Boyle, D; Larson, C; Parker, D; Pessoa-Brandão, L

2000-05-01

The Minnesota Sentinel Event Notification System for Occupational Risks (SENSOR) surveillance system has collected data on the medical, personal, and occupational outcomes associated with work-related amputations since 1992. SENSOR defined amputations as any finger amputation or the loss of any other body part; 832 workers were identified as having amputation injuries between 1994 and 1995 and 72% of these workers completed a telephone interview. Twenty percent of those injured required overnight hospitalization. Ninety-one percent of the cases reported having missed work, with 56% reporting missing ten or more days. Individuals working on their usual jobs at the time of injury were more likely to report less serious medical and occupational outcomes. Severe injuries were significantly associated with worse medical, personal, and occupational outcomes. Two groups of machines, material handling, and powered handtools were associated with a higher proportion of severe injuries. Copyright 2000 Wiley-Liss, Inc.

Security Aspects of Smart Cards vs. Embedded Security in Machine-to-Machine (M2M) Advanced Mobile Network Applications

NASA Astrophysics Data System (ADS)

Meyerstein, Mike; Cha, Inhyok; Shah, Yogendra

The Third Generation Partnership Project (3GPP) standardisation group currently discusses advanced applications of mobile networks such as Machine-to-Machine (M2M) communication. Several security issues arise in these contexts which warrant a fresh look at mobile networks’ security foundations, resting on smart cards. This paper contributes a security/efficiency analysis to this discussion and highlights the role of trusted platform technology to approach these issues.

Dynamics of the process boom machine working equipment under the real law of the hydraulic distributor electric spool control

NASA Astrophysics Data System (ADS)

Tarasov, V. N.; Boyarkina, I. V.

2017-06-01

Analytical calculation methods of dynamic processes of the self-propelled boom hydraulic machines working equipment are more preferable in comparison with numerical methods. The analytical research method of dynamic processes of the boom hydraulic machines working equipment by means of differential equations of acceleration and braking of the working equipment is proposed. The real control law of a hydraulic distributor electric spool is considered containing the linear law of the electric spool activation and stepped law of the electric spool deactivation. Dependences of dynamic processes of the working equipment on reduced mass, stiffness of hydraulic power cylinder, viscous drag coefficient, piston acceleration, pressure in hydraulic cylinders, inertia force are obtained. Definite recommendations relative to the reduction of dynamic loads, appearing during the working equipment control are considered as the research result. The nature and rate of parameter variations of the speed and piston acceleration dynamic process depend on the law of the ports opening and closure of the hydraulic distributor electric spool. Dynamic loads in the working equipment are decreased during a smooth linear activation of the hydraulic distributor electric spool.

Experimental Realization of a Quantum Support Vector Machine

NASA Astrophysics Data System (ADS)

Li, Zhaokai; Liu, Xiaomei; Xu, Nanyang; Du, Jiangfeng

2015-04-01

The fundamental principle of artificial intelligence is the ability of machines to learn from previous experience and do future work accordingly. In the age of big data, classical learning machines often require huge computational resources in many practical cases. Quantum machine learning algorithms, on the other hand, could be exponentially faster than their classical counterparts by utilizing quantum parallelism. Here, we demonstrate a quantum machine learning algorithm to implement handwriting recognition on a four-qubit NMR test bench. The quantum machine learns standard character fonts and then recognizes handwritten characters from a set with two candidates. Because of the wide spread importance of artificial intelligence and its tremendous consumption of computational resources, quantum speedup would be extremely attractive against the challenges of big data.

Machinability of Stellite 6 hardfacing

NASA Astrophysics Data System (ADS)

Benghersallah, M.; Boulanouar, L.; Le Coz, G.; Devillez, A.; Dudzinski, D.

2010-06-01

This paper reports some experimental findings concerning the machinability at high cutting speed of nickel-base weld-deposited hardfacings for the manufacture of hot tooling. The forging work involves extreme impacts, forces, stresses and temperatures. Thus, mould dies must be extremely resistant. The aim of the project is to create a rapid prototyping process answering to forging conditions integrating a Stellite 6 hardfacing deposed PTA process. This study talks about the dry machining of the hardfacing, using a two tips machining tool and a high speed milling machine equipped by a power consumption recorder Wattpilote. The aim is to show the machinability of the hardfacing, measuring the power and the tip wear by optical microscope and white light interferometer, using different strategies and cutting conditions.

Cost of unreliability method to estimate loss of revenue based on unreliability data: Case study of Printing Company

NASA Astrophysics Data System (ADS)

alhilman, Judi

2017-12-01

In the production line process of the printing office, the reliability of the printing machine plays a very important role, if the machine fail it can disrupt production target so that the company will suffer huge financial loss. One method to calculate the financial loss cause by machine failure is use the Cost of Unreliability(COUR) method. COUR method works based on down time machine and costs associated with unreliability data. Based on the calculation of COUR method, so the sum of cost due to unreliability printing machine during active repair time and downtime is 1003,747.00.

Soft electroactive actuators and hard ratchet-wheels enable unidirectional locomotion of hybrid machine

NASA Astrophysics Data System (ADS)

Sun, Wenjie; Liu, Fan; Ma, Ziqi; Li, Chenghai; Zhou, Jinxiong

2017-01-01

Combining synergistically the muscle-like actuation of soft materials and load-carrying and locomotive capability of hard mechanical components results in hybrid soft machines that can exhibit specific functions. Here, we describe the design, fabrication, modeling and experiment of a hybrid soft machine enabled by marrying unidirectionally actuated dielectric elastomer (DE) membrane-spring system and ratchet wheels. Subjected to an applied voltage 8.2 kV at ramping velocity 820 V/s, the hybrid machine prototype exhibits monotonic uniaxial locomotion with an averaged velocity 0.5mm/s. The underlying physics and working mechanisms of the soft machine are verified and elucidated by finite element simulation.

The Effect of Different Non-Metallic Inclusions on the Machinability of Steels.

PubMed

Ånmark, Niclas; Karasev, Andrey; Jönsson, Pär Göran

2015-02-16

Considerable research has been conducted over recent decades on the role of non‑metallic inclusions and their link to the machinability of different steels. The present work reviews the mechanisms of steel fractures during different mechanical machining operations and the behavior of various non-metallic inclusions in a cutting zone. More specifically, the effects of composition, size, number and morphology of inclusions on machinability factors (such as cutting tool wear, power consumption, etc .) are discussed and summarized. Finally, some methods for modification of non-metallic inclusions in the liquid steel are considered to obtain a desired balance between mechanical properties and machinability of various steel grades.

Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

NASA Astrophysics Data System (ADS)

Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

2018-04-01

The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

A SUGGESTED CURRICULUM GUIDE FOR ELECTRO-MECHANICAL TECHNOLOGY ORIENTED SPECIFICALLY TO THE COMPUTER AND BUSINESS MACHINE FIELDS. INTERIM REPORT.

ERIC Educational Resources Information Center

LESCARBEAU, ROLAND F.; AND OTHERS

A SUGGESTED POST-SECONDARY CURRICULUM GUIDE FOR ELECTRO-MECHANICAL TECHNOLOGY ORIENTED SPECIFICALLY TO THE COMPUTER AND BUSINESS MACHINE FIELDS WAS DEVELOPED BY A GROUP OF COOPERATING INSTITUTIONS, NOW INCORPORATED AS TECHNICAL EDUCATION CONSORTIUM, INCORPORATED. SPECIFIC NEEDS OF THE COMPUTER AND BUSINESS MACHINE INDUSTRY WERE DETERMINED FROM…

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 and Evaluation of Heartbeat: A Machine Perfusion Heart Preservation System.

PubMed

Li, Yongnan; Zeng, Qingdong; Liu, Gang; Du, Junzhe; Gao, Bingren; Wang, Wei; Zheng, Zhe; Hu, Shengshou; Ji, Bingyang

2017-11-01

Static cold storage is accompanied with a partial safe ischemic interval for donor hearts. In this current study, a machine perfusion system was built to provide a better preservation for the donor heart and assessment for myocardial function. Chinese mini-swine (weight 30-35 kg, n = 16) were randomly divided into HTK, Celsior, and Heartbeat groups. All donor hearts were respectively preserved for 8 hours under static cold storage or machine perfusion. The perfusion solution is aimed to maintain its homeostasis based on monitoring the Heartbeat group. The ultrastructure of myocardium suggests better myocardial protection in the Heartbeat group compared with HTK or Celsior-preserved hearts. The myocardial and coronary artery structural and functional integrity was evaluated by immunofluorescence and Western blots in the Heartbeat. In the Heartbeat group, donor hearts maintained a high adenosine triphosphate level. Bcl-2 and Beclin-1 protein demonstrates high expression in the Celsior group. The Heartbeat system can be used to preserve donor hearts, and it could guarantee the myocardial and endothelial function of hearts during machine perfusion. Translating Heartbeat into clinical practice, it is such as to impact on donor heart preservation for cardiac transplantation. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Nanocomposites for Machining Tools

PubMed Central

Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

2017-01-01

Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance. PMID:29027926

20. SECOND FLOOR, CARDING MACHINE, BY 'CARDING SPECIALISTS, CO., LTD., ...

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

20. SECOND FLOOR, CARDING MACHINE, BY 'CARDING SPECIALISTS, CO., LTD., PELLON LAND WORKS, HALIFAX, ENGLAND, SN #M2983 14 (EST. DATE 1940'S+), OPPOSITE END - Bamberg Cotton Mill, Main Street, Bamberg, Bamberg County, SC

30 CFR 75.1719-1 - Illumination in working places.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., hydraulic, pneumatic, or mechanical power supplied by a source located on the machine or transmitted to the machine by cables, ropes, or chains. (c) The lighting prescribed in this section shall be in addition to...

30 CFR 75.1719-1 - Illumination in working places.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., hydraulic, pneumatic, or mechanical power supplied by a source located on the machine or transmitted to the machine by cables, ropes, or chains. (c) The lighting prescribed in this section shall be in addition to...

Noether symmetries and the Swinging Atwood Machine

NASA Astrophysics Data System (ADS)

Moreira, I. C.; Almeida, M. A.

1991-07-01

In this work we apply the Noether theorem with generalised symmetries for discussing the integrability of the Swinging Atwood Machine (SAM) model. We analyse also the limitations of this procedure and compare it with the Yoshida method.

Proceedings of the NATO-Advanced Study Institute on Computer Aided Analysis of Rigid and Flexible Mechanical Systems Held in Troia, Portugal on June 27-July 9, 1993. Volume 1. Main Lectures

DTIC Science & Technology

1993-07-09

real-time simulation capabilities, highly non -linear control devices, work space path planing, active control of machine flexibilities and reliability...P.M., "The Information Capacity of the Human Motor System in Controlling the Amplitude of Movement," Journal of Experimental Psychology, Vol 47, No...driven many research groups in the challenging problem of flexible sy,;tems with an increasing interaction with finite element methodologies. Basic

Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers.

PubMed

García-Massó, X; Serra-Añó, P; Gonzalez, L M; Ye-Lin, Y; Prats-Boluda, G; Garcia-Casado, J

2015-10-01

This was a cross-sectional study. The main objective of this study was to develop and test classification algorithms based on machine learning using accelerometers to identify the activity type performed by manual wheelchair users with spinal cord injury (SCI). The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia. A total of 20 volunteers were asked to perform 10 physical activities, lying down, body transfers, moving items, mopping, working on a computer, watching TV, arm-ergometer exercises, passive propulsion, slow propulsion and fast propulsion, while fitted with four accelerometers placed on both wrists, chest and waist. The activities were grouped into five categories: sedentary, locomotion, housework, body transfers and moderate physical activity. Different machine learning algorithms were used to develop individual and group activity classifiers from the acceleration data for different combinations of number and position of the accelerometers. We found that although the accuracy of the classifiers for individual activities was moderate (55-72%), with higher values for a greater number of accelerometers, grouped activities were correctly classified in a high percentage of cases (83.2-93.6%). With only two accelerometers and the quadratic discriminant analysis algorithm we achieved a reasonably accurate group activity recognition system (>90%). Such a system with the minimum of intervention would be a valuable tool for studying physical activity in individuals with SCI.

Design of electric control system for automatic vegetable bundling machine

NASA Astrophysics Data System (ADS)

Bao, Yan

2017-06-01

A design can meet the requirements of automatic bale food structure and has the advantages of simple circuit, and the volume is easy to enhance the electric control system of machine carrying bunch of dishes and low cost. The bundle of vegetable machine should meet the sensor to detect and control, in order to meet the control requirements; binding force can be adjusted by the button to achieve; strapping speed also can be adjusted, by the keys to set; sensors and mechanical line connection, convenient operation; can be directly connected with the plug, the 220V power supply can be connected to a power source; if, can work, by the transmission signal sensor, MCU to control the motor, drive and control procedures for small motor. The working principle of LED control circuit and temperature control circuit is described. The design of electric control system of automatic dish machine.

Biomorphic architectures for autonomous Nanosat designs

NASA Technical Reports Server (NTRS)

Hasslacher, Brosl; Tilden, Mark W.

1995-01-01

Modern space tool design is the science of making a machine both massively complex while at the same time extremely robust and dependable. We propose a novel nonlinear control technique that produces capable, self-organizing, micron-scale space machines at low cost and in large numbers by parallel silicon assembly. Experiments using biomorphic architectures (with ideal space attributes) have produced a wide spectrum of survival-oriented machines that are reliably domesticated for work applications in specific environments. In particular, several one-chip satellite prototypes show interesting control properties that can be turned into numerous application-specific machines for autonomous, disposable space tasks. We believe that the real power of these architectures lies in their potential to self-assemble into larger, robust, loosely coupled structures. Assembly takes place at hierarchical space scales, with different attendant properties, allowing for inexpensive solutions to many daunting work tasks. The nature of biomorphic control, design, engineering options, and applications are discussed.

The Effect of Hierarchical Micro/Nanotextured Titanium Implants on Osseointegration Immediately After Tooth Extraction in Beagle Dogs.

PubMed

Fu, Qian; Bellare, Anuj; Cui, Yajun; Cheng, Bingkun; Xu, Shanshan; Kong, Liang

2017-06-01

Owing to simplify the operation and shorten the overall duration of treatment, immediate implantation earned much satisfactory from patients and dentists. The results of immediate implantation determined by osseointegration, we fabricated a micro/nanotextured titanium implants to improve osseointegration immediately after tooth extraction. The aim of this study was to investigate the effect of hierarchical micro/nanotextured titanium implant on osseointegration immediately after tooth extraction. The micro/nanotextured titanium implants were fabricated by etching with 0.5 wt% hydrofluoric (HF) acid followed by anodization in HF electrolytes. Implants with a machined surface as well as implants a microtextured surface prepared by 0.5 wt% HF etching served as control groups. The machined, microtextured, and micro/nanotextured implants were inserted into fresh sockets immediately after tooth extraction in beagle dogs. Twelve weeks after implantation, the animals were sacrificed for micro-CT scanning, histological analysis and biomechanical test. The micro-CT imaging revealed that the bone volume/total volume (BV/TV) and trabecular thickness (Tb.Th) in the micro/nanotextured group was significantly higher than that in the machined group and microtextured group, and the trabecular separation (Tb.Sp) in the micro/nanotextured group was significantly lower than that in the other groups. For the histological analysis, the bone-to-implant contact in the machined, micro and micro/nanotextured groups were 47.13 ± 6.2%, 54.29 ± 4.18%, and 63.38 ± 7.63%, respectively, and the differences significant. The maximum pull-out force in the machined, micro, and micro/nanotextured groups were 216.58 ± 38.71 N, 259.42 ± 28.93 N, and 284.73 ± 47.09 N, respectively. The results indicated that implants with a hierarchical micro/nanotextured can promote osseointegration immediately after tooth extraction. © 2016 Wiley Periodicals, Inc.

Does providing nutrition information at vending machines reduce calories per item sold?

PubMed

Dingman, Deirdre A; Schulz, Mark R; Wyrick, David L; Bibeau, Daniel L; Gupta, Sat N

2015-02-01

In 2010, the United States (US) enacted a restaurant menu labeling law. The law also applied to vending machine companies selling food. Research suggested that providing nutrition information on menus in restaurants might reduce the number of calories purchased. We tested the effect of providing nutrition information and 'healthy' designations to consumers where vending machines were located in college residence halls. We conducted our study at one university in Southeast US (October-November 2012). We randomly assigned 18 vending machines locations (residence halls) to an intervention or control group. For the intervention we posted nutrition information, interpretive signage, and sent a promotional email to residents of the hall. For the control group we did nothing. We tracked sales over 4 weeks before and 4 weeks after we introduced the intervention. Our intervention did not change what the residents bought. We recommend additional research about providing nutrition information where vending machines are located, including testing formats used to present information.

Monitoring Temperature and Fan Speed Using Ganglia and Winbond Chips

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

McCaffrey, Cattie; /SLAC

2006-09-27

Effective monitoring is essential to keep a large group of machines, like the ones at Stanford Linear Accelerator Center (SLAC), up and running. SLAC currently uses Ganglia Monitoring System to observe about 2000 machines, analyzing metrics like CPU usage and I/O rate. However, metrics essential to machine hardware health, such as temperature and fan speed, are not being monitored. Many machines have a Winbond w83782d chip which monitors three temperatures, two of which come from dual CPUs, and returns the information when the sensor command is invoked. Ganglia also provides a feature, gmetric, that allows the users to monitor theirmore » own metrics and incorporate them into the monitoring system. The programming language Perl is chosen to implement a script that invokes the sensors command, extracts the temperature and fan speed information, and calls gmetric with the appropriate arguments. Two machines were used to test the script; the two CPUs on each machine run at about 65 Celsius, which is well within the operating temperature range (The maximum safe temperature range is 77-82 Celsius for the Pentium III processors being used). Installing the script on all machines with a Winbond w83782d chip allows the SLAC Scientific Computing and Computing Services group (SCCS) to better evaluate current cooling methods.« less

Chlorophyll fluorescence as a tool for nutrient status identification in rapeseed plants.

PubMed

Kalaji, Hazem M; Bąba, Wojciech; Gediga, Krzysztof; Goltsev, Vasilij; Samborska, Izabela A; Cetner, Magdalena D; Dimitrova, Stella; Piszcz, Urszula; Bielecki, Krzysztof; Karmowska, Kamila; Dankov, Kolyo; Kompała-Bąba, Agnieszka

2018-06-01

In natural conditions, plants growth and development depends on environmental conditions, including the availability of micro- and macroelements in the soil. Nutrient status should thus be examined not by establishing the effects of single nutrient deficiencies on the physiological state of the plant but by combinations of them. Differences in the nutrient content significantly affect the photochemical process of photosynthesis therefore playing a crucial role in plants growth and development. In this work, an attempt was made to find a connection between element content in (i) different soils, (ii) plant leaves, grown on these soils and (iii) changes in selected chlorophyll a fluorescence parameters, in order to find a method for early detection of plant stress resulting from the combination of nutrient status in natural conditions. To achieve this goal, a mathematical procedure was used which combines principal component analysis (a tool for the reduction of data complexity), hierarchical k-means (a classification method) and a machine-learning method-super-organising maps. Differences in the mineral content of soil and plant leaves resulted in functional changes in the photosynthetic machinery that can be measured by chlorophyll a fluorescent signals. Five groups of patterns in the chlorophyll fluorescent parameters were established: the 'no deficiency', Fe-specific deficiency, slight, moderate and strong deficiency. Unfavourable development in groups with nutrient deficiency of any kind was reflected by a strong increase in F o and ΔV/Δt 0 and decline in φ Po , φ Eo δ Ro and φ Ro . The strong deficiency group showed the suboptimal development of the photosynthetic machinery, which affects both PSII and PSI. The nutrient-deficient groups also differed in antenna complex organisation. Thus, our work suggests that the chlorophyll fluorescent method combined with machine-learning methods can be highly informative and in some cases, it can replace much more expensive and time-consuming procedures such as chemometric analyses.

An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice

PubMed Central

Özdemir, Ahmet Turan

2016-01-01

Wearable devices for fall detection have received attention in academia and industry, because falls are very dangerous, especially for elderly people, and if immediate aid is not provided, it may result in death. However, some predictive devices are not easily worn by elderly people. In this work, a huge dataset, including 2520 tests, is employed to determine the best sensor placement location on the body and to reduce the number of sensor nodes for device ergonomics. During the tests, the volunteer’s movements are recorded with six groups of sensors each with a triaxial (accelerometer, gyroscope and magnetometer) sensor, which is placed tightly on different parts of the body with special straps: head, chest, waist, right-wrist, right-thigh and right-ankle. The accuracy of individual sensor groups with their location is investigated with six machine learning techniques, namely the k-nearest neighbor (k-NN) classifier, Bayesian decision making (BDM), support vector machines (SVM), least squares method (LSM), dynamic time warping (DTW) and artificial neural networks (ANNs). Each technique is applied to single, double, triple, quadruple, quintuple and sextuple sensor configurations. These configurations create 63 different combinations, and for six machine learning techniques, a total of 63 × 6 = 378 combinations is investigated. As a result, the waist region is found to be the most suitable location for sensor placement on the body with 99.96% fall detection sensitivity by using the k-NN classifier, whereas the best sensitivity achieved by the wrist sensor is 97.37%, despite this location being highly preferred for today’s wearable applications. PMID:27463719

An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice.

PubMed

Özdemir, Ahmet Turan

2016-07-25

Wearable devices for fall detection have received attention in academia and industry, because falls are very dangerous, especially for elderly people, and if immediate aid is not provided, it may result in death. However, some predictive devices are not easily worn by elderly people. In this work, a huge dataset, including 2520 tests, is employed to determine the best sensor placement location on the body and to reduce the number of sensor nodes for device ergonomics. During the tests, the volunteer's movements are recorded with six groups of sensors each with a triaxial (accelerometer, gyroscope and magnetometer) sensor, which is placed tightly on different parts of the body with special straps: head, chest, waist, right-wrist, right-thigh and right-ankle. The accuracy of individual sensor groups with their location is investigated with six machine learning techniques, namely the k-nearest neighbor (k-NN) classifier, Bayesian decision making (BDM), support vector machines (SVM), least squares method (LSM), dynamic time warping (DTW) and artificial neural networks (ANNs). Each technique is applied to single, double, triple, quadruple, quintuple and sextuple sensor configurations. These configurations create 63 different combinations, and for six machine learning techniques, a total of 63 × 6 = 378 combinations is investigated. As a result, the waist region is found to be the most suitable location for sensor placement on the body with 99.96% fall detection sensitivity by using the k-NN classifier, whereas the best sensitivity achieved by the wrist sensor is 97.37%, despite this location being highly preferred for today's wearable applications.

Performance and Surface Integrity of Ti6Al4V After Sinking EDM with Special Graphite Electrodes

NASA Astrophysics Data System (ADS)

Amorim, Fred L.; Stedile, Leandro J.; Torres, Ricardo D.; Soares, Paulo C.; Henning Laurindo, Carlos A.

2014-04-01

Titanium and its alloys have high chemical reactivity with most of the cutting tools. This makes it difficult to work with these alloys using conventional machining processes. Electrical discharge machining (EDM) emerges as an alternative technique to machining these materials. In this work, it is investigated the performance of three special grades of graphite as electrodes when ED-Machining Ti6Al4V samples under three different regimes. The main influences of electrical parameters are discussed for the samples material removal rate, volumetric relative wear and surface roughness. The samples surfaces were evaluated using SEM images, microhardness measurements, and x-ray diffraction. It was found that the best results for samples material removal rate, surface roughness, and volumetric relative wear were obtained for the graphite electrode with 10-μm particle size and negative polarity. For all samples machined by EDM and characterized by x-ray (XRD), it was identified the presence of titanium carbides. For the finish EDM regimes, the recast layer presents an increased amount of titanium carbides compared to semi-finish and rough regimes.

Prevalence of Hand-transmitted Vibration Exposure among Grass-cutting Workers using Objective and Subjective Measures

NASA Astrophysics Data System (ADS)

Azmir, N. A.; Yahya, M. N.

2017-01-01

Extended exposure to hand-transmitted vibration from vibrating machine is associated with an increased occurrence of symptoms of occupational disease related to hand disorder. The present case study is to determine the prevalence and correlation of significant subjective as well as objective variables that induce to hand arm vibration syndrome (HAVS) among hand-held grass-cutting workers in Malaysia. Thus, recommendations are made for grass-cutting workers and grass maintenance service management based on findings. A cross sectional study using adopted subjective Hand Arm Vibration Exposure Risk Assessment (HAVERA) questionnaire from Vibration Injury Network on hand disorder signs and symptoms was distributed to a sample of one hundred and sixty eight male workers from grass and turf maintenance industry that use vibrating machine as part of their work. For objective measure, hand-transmitted vibration measurement was collected on site during operation by the following ISO 5349-1, 2001. Two groups were identified in this research comprising of high exposure group and low-moderate exposure group. Workers also gave information about their personal identification, social history, workers’ health, occupational history and machine safety inspection. There was positive HAVS symptoms relationship between the low-moderate exposure group and high exposure group among hand-held grass-cutting workers. The prevalence ratio (PR) was considered high for experiencing white colour change at fingers and fingers go numb which are 3.63 (1.41 to 9.39) and 4.24 (2.18 to 8.27), respectively. The estimated daily vibration exposure, A(8) differs between 2.1 to 20.7 ms-2 for right hand while 2.7 to 29.1 ms-2 for left hand. The subjects claimed that the feel of numbness at left hand is much stronger compared to right hand. The results suggest that HAVS is diagnosed in Malaysia especially in agriculture sector. The A(8) indicates that the exposure value is more than exposure limit value which is 5 ms-2. Thus, control measure such as engineering and administrative control should be implemented to reduce the severity of hand-transmitted vibration hazard.

Development of thermal model to analyze thermal flux distribution in thermally enhanced machining of high chrome white cast iron

NASA Astrophysics Data System (ADS)

Ravi, A. M.; Murigendrappa, S. M.

2018-04-01

In recent times, thermally enhanced machining (TEM) slowly gearing up to cut hard metals like high chrome white cast iron (HCWCI) which were impossible in conventional procedures. Also setting up of suitable cutting parameters and positioning of the heat source against the work appears to be critical in order to enhance the machinability characteristics of the work material. In this research work, the Oxy - LPG flame was used as the heat source and HCWCI as the workpiece. ANSYS-CFD-Flow software was used to develop the transient thermal model to analyze the thermal flux distribution on the work surface during TEM of HCWCI using Cubic boron nitride (CBN) tools. Non-contact type Infrared thermo sensor was used to measure the surface temperature continuously at different positions, and is validated with the thermal model results. The result confirms thermal model is a better predictive tool for thermal flux distribution analysis in TEM process.

Morbidity ranking of U.S. workers employed in 206 occupations: the National Health Interview Survey (NHIS) 1986-1994.

PubMed

Lee, David J; Fleming, Lora E; Gómez-Marín, Orlando; LeBlanc, William G; Arheart, Kristopher L; Caban, Alberto J; Christ, Sharon L; Chung-Bridges, Katherine; Pitman, Terry

2006-02-01

The objective of this study was to rank U.S. occupations by worker morbidity. From 1986 through 1994, morbidity information was collected on over 410,000 U.S. workers who participated in the National Health Interview Survey, an annual household survey representative of the U.S. civilian noninstitutionalized population. A multivariate adjusted logistic regression morbidity summary score was created for each worker group based on seven indicators: days of restricted activity, bedrest, and missed work in the previous 2 weeks; doctor visits and hospitalizations in the previous 12 months; reported health conditions; and health status. Worker groups reporting the greatest morbidity included social workers, inspectors, postal clerks, psychologists, and grinding machine operators; worker groups reporting the least morbidity included dentists, pilots, physicians, pharmacists, and dietitians. These findings aid in the identification of worker groups that require increased attention for morbidity research and prevention.

The engine maintenance scheduling by using reliability centered maintenance method and the identification of 5S application in PT. XYZ

NASA Astrophysics Data System (ADS)

Sembiring, N.; Panjaitan, N.; Saragih, A. F.

2018-02-01

PT. XYZ is a manufacturing company that produces fresh fruit bunches (FFB) to Crude Palm Oil (CPO) and Palm Kernel Oil (PKO). PT. XYZ consists of six work stations: receipt station, sterilizing station, thressing station, pressing station, clarification station, and kernelery station. So far, the company is still implementing corrective maintenance maintenance system for production machines where the machine repair is done after damage occurs. Problems at PT. XYZ is the absence of scheduling engine maintenance in a planned manner resulting in the engine often damaged which can disrupt the smooth production. Another factor that is the problem in this research is the kernel station environment that becomes less convenient for operators such as there are machines and equipment not used in the production area, slippery, muddy, scattered fibers, incomplete use of PPE, and lack of employee discipline. The most commonly damaged machine is in the seed processing station (kernel station) which is cake breaker conveyor machine. The solution of this problem is to propose a schedule plan for maintenance of the machine by using the method of reliability centered maintenance and also the application of 5S. The result of the application of Reliability Centered maintenance method is obtained four components that must be treated scheduled (time directed), namely: for bearing component is 37 days, gearbox component is 97 days, CBC pen component is 35 days and conveyor pedal component is 32 days While after identification the application of 5S obtained the proposed corporate environmental improvement measures in accordance with the principles of 5S where unused goods will be moved from the production area, grouping goods based on their use, determining the procedure of cleaning the production area, conducting inspection in the use of PPE, and making 5S slogans.

Design Study for a Free-piston Vuilleumier Cycle Heat Pump

NASA Astrophysics Data System (ADS)

Matsue, Junji; Hoshino, Norimasa; Ikumi, Yonezou; Shirai, Hiroyuki

Conceptual design for a free-piston Vuilleumier cycle heat pump machine was proposed. The machine was designed based upon the numerical results of a dynamic analysis method. The method included the effect of self excitation vibration with dissipation caused by the flow friction of an oscillating working gas flow and solid friction of seals. It was found that the design values of reciprocating masses and spring constants proposed in published papers related to this study were suitable for practical use. The fundamental effects of heat exchanger elements on dynamic behaviors of the machine were clarified. It has been pointed out that some improvements were required for thermodynamic analysis of heat exchangers and working spaces.

Parametric Optimization of Wire Electrical Discharge Machining of Powder Metallurgical Cold Worked Tool Steel using Taguchi Method

NASA Astrophysics Data System (ADS)

Sudhakara, Dara; Prasanthi, Guvvala

2017-04-01

Wire Cut EDM is an unconventional machining process used to build components of complex shape. The current work mainly deals with optimization of surface roughness while machining P/M CW TOOL STEEL by Wire cut EDM using Taguchi method. The process parameters of the Wire Cut EDM is ON, OFF, IP, SV, WT, and WP. L27 OA is used for to design of the experiments for conducting experimentation. In order to find out the effecting parameters on the surface roughness, ANOVA analysis is engaged. The optimum levels for getting minimum surface roughness is ON = 108 µs, OFF = 63 µs, IP = 11 A, SV = 68 V and WT = 8 g.

Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine

PubMed Central

Mourão-Miranda, Janaina; Hardoon, David R.; Hahn, Tim; Marquand, Andre F.; Williams, Steve C.R.; Shawe-Taylor, John; Brammer, Michael

2011-01-01

Pattern recognition approaches, such as the Support Vector Machine (SVM), have been successfully used to classify groups of individuals based on their patterns of brain activity or structure. However these approaches focus on finding group differences and are not applicable to situations where one is interested in accessing deviations from a specific class or population. In the present work we propose an application of the one-class SVM (OC-SVM) to investigate if patterns of fMRI response to sad facial expressions in depressed patients would be classified as outliers in relation to patterns of healthy control subjects. We defined features based on whole brain voxels and anatomical regions. In both cases we found a significant correlation between the OC-SVM predictions and the patients' Hamilton Rating Scale for Depression (HRSD), i.e. the more depressed the patients were the more of an outlier they were. In addition the OC-SVM split the patient groups into two subgroups whose membership was associated with future response to treatment. When applied to region-based features the OC-SVM classified 52% of patients as outliers. However among the patients classified as outliers 70% did not respond to treatment and among those classified as non-outliers 89% responded to treatment. In addition 89% of the healthy controls were classified as non-outliers. PMID:21723950

Health Effects of Electromagnetic Fields on Reproductive-Age Female Operators of Plastic Welding Machines in Fuzhou, China.

PubMed

Xu, Youqiong; Zhang, Xiaoyang; Chen, Yu; Ren, Nan; Lin, Wei; Zhang, Qunwei

2016-02-01

The aim of this study was to investigate the health effects of electromagnetic fields (EMFs) among female operators of plastic welding machines. We examined 180 female operators in shoe factories as the exposed group, and 349 female workers from nearby supermarkets as the unexposed group. The mean radiation levels in the vicinity of the welding machines ranged from 51.3 to 368.9 V/m. The prevalence of neurovegetative symptoms increased with higher EMFs exposures (P < 0.05). The prevalence of menstrual disorder was 12.0% in the unexposed group, but was 26.8% and 33.8% in low and high-exposure groups, respectively (P < 0.01). Exposure-response relationships were found between cumulate exposure and neurovegetative symptoms and menstrual disorder (P < 0.05). Serum progesterone (P4) was significantly lower in the exposed groups (P < 0.01). EMFs exposure was associated with adverse health effects, including neurovegetative symptoms, menstrual disorder, and low level of P4.

Machining of AISI D2 Tool Steel with Multiple Hole Electrodes by EDM Process

NASA Astrophysics Data System (ADS)

Prasad Prathipati, R.; Devuri, Venkateswarlu; Cheepu, Muralimohan; Gudimetla, Kondaiah; Uzwal Kiran, R.

2018-03-01

In recent years, with the increasing of technology the demand for machining processes is increasing for the newly developed materials. The conventional machining processes are not adequate to meet the accuracy of the machining of these materials. The non-conventional machining processes of electrical discharge machining is one of the most efficient machining processes is being widely used to machining of high accuracy products of various industries. The optimum selection of process parameters is very important in machining processes as that of an electrical discharge machining as they determine surface quality and dimensional precision of the obtained parts, even though time consumption rate is higher for machining of large dimension features. In this work, D2 high carbon and chromium tool steel has been machined using electrical discharge machining with the multiple hole electrode technique. The D2 steel has several applications such as forming dies, extrusion dies and thread rolling. But the machining of this tool steel is very hard because of it shard alloyed elements of V, Cr and Mo which enhance its strength and wear properties. However, the machining is possible by using electrical discharge machining process and the present study implemented a new technique to reduce the machining time using a multiple hole copper electrode. In this technique, while machining with multiple holes electrode, fin like projections are obtained, which can be removed easily by chipping. Then the finishing is done by using solid electrode. The machining time is reduced to around 50% while using multiple hole electrode technique for electrical discharge machining.

Ergonomic evaluation of conventional and improved methods of aonla pricking with women workers.

PubMed

Rai, Arpana; Gandhi, Sudesh; Sharma, D K

2012-01-01

Conventional and improved methods of aonla pricking were evaluated ergonomically on an experiment conducted for 20 minute with women workers. The working heart rate, energy expenditure rate, total cardiac cost of work and physiological cost of work with conventional tools varied from 93-102 beats.min-1, 6-7.5 kJ.min-1, 285-470 beats, 14 -23 beats.min-1 while with machine varied from 96-105 beats.min-1, 6.5-8 kJ.min-1 , 336-540 beats, 16-27 beats.min-1 respectively. OWAS score for conventional method was 2 indicating corrective measures in near future while with machine was 1 indicating no corrective measures. Result of Nordic Musculoskeletal Questionnaire revealed that subjects complaint of pain in back, neck, right shoulder and right hand due to unnatural body posture and repetitive movement with hand tool. Moreover pricking was carried out in improper lighting conditions (200-300 lux) resulting into finger injuries from sharp edges of hand tool, whereas with machine no such problems were observed. Output with machine increased thrice than hand pricking in a given time. Machine was found useful in terms of saving time, increased productivity, enhanced safety and comfort as involved improved posture, was easy to handle and operate, thus increasing efficiency of the worker leading to better quality of life.

A randomized, controlled intervention of machine guarding and related safety programs in small metal-fabrication businesses.

PubMed

Parker, David L; Brosseau, Lisa M; Samant, Yogindra; Xi, Min; Pan, Wei; Haugan, David

2009-01-01

Metal fabrication employs an estimated 3.1 million workers in the United States. The absence of machine guarding and related programs such as lockout/tagout may result in serious injury or death. The purpose of this study was to improve machine-related safety in small metal-fabrication businesses. We used a randomized trial with two groups: management only and management-employee. We evaluated businesses for the adequacy of machine guarding (machine scorecard) and related safety programs (safety audit). We provided all businesses with a report outlining deficiencies and prioritizing their remediation. In addition, the management-employee group received four one-hour interactive training sessions from a peer educator. We evaluated 40 metal-fabrication businesses at baseline and 37 (93%) one year later. Of the three nonparticipants, two had gone out of business. More than 40% of devices required for adequate guarding were missing or inadequate, and 35% of required safety programs and practices were absent at baseline. Both measures improved significantly during the course of the intervention. No significant differences in changes occurred between the two intervention groups. Machine-guarding practices and programs improved by up to 13% and safety audit scores by up to 23%. Businesses that added safety committees or those that started with the lowest baseline measures showed the greatest improvements. Simple and easy-to-use assessment tools allowed businesses to significantly improve their safety practices, and safety committees facilitated this process.

Suicide by occupation: systematic review and meta-analysis.

PubMed

Milner, Allison; Spittal, Matthew J; Pirkis, Jane; LaMontagne, Anthony D

2013-12-01

Previous research has shown that those employed in certain occupations, such as doctors and farmers, have an elevated risk of suicide, yet little research has sought to synthesise these findings across working-age populations. To summarise published research in this area through systematic review and meta-analysis. Random effects meta-analyses were used to calculate a pooled risk of suicide across occupational skill-level groups. Thirty-four studies were included in the meta-analysis. Elementary professions (e.g. labourers and cleaners) were at elevated risk compared with the working-age population (rate ratio (RR) = 1.84, 95% CI 1.46-2.33), followed by machine operators and deck crew (RR = 1.78, 95% CI 1.22-2.60) and agricultural workers (RR = 1.64, 95% CI 1.19-2.28). Results suggested a stepwise gradient in risk, with the lowest skilled occupations being at greater risk of suicide than the highest skill-level group. This is the first comprehensive meta-analytical review of suicide and occupation. There is a need for future studies to investigate explanations for the observed skill-level differences, particularly in people employed in lower skill-level groups.

Dose reduction and cost-benefit analysis at Japan`s Tokai No. 2 Plant

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

Humamoto, Hisao; Suzuki, Seishiro; Taniguchi, Kazufumi

1995-03-01

In the Tokai No. 2 power plant of the Japan Atomic Power Company, about 80% of the annual dose equivalent is received during periodic maintenance outages. A project group for dose reduction was organized at the company`s headquarters in 1986; in 1988, they proposed a five-year program to reduce by half the collective dose of 4 person-Sv per normal outage work. To achieve the target dose value, some dose-reduction measures were undertaken, namely, permanent radiation shielding, decontamination, automatic, operating machines, and ALARA organization. As the result, the collective dose from normal outage work was 1.6 person-Sv in 1992, which wasmore » less than the initial target value.« less

Effect of cutting parameters on surface finish and machinability of graphite reinforced Al-8011 matrix composite

NASA Astrophysics Data System (ADS)

Anil, K. C.; Vikas, M. G.; Shanmukha Teja, B.; Sreenivas Rao, K. V.

2017-04-01

Many materials such as alloys, composites find their applications on the basis of machinability, cost and availability. In the present work, graphite (Grp) reinforced Aluminium 8011 is synthesized by convention stir casting process and Surface finish & machinability of prepared composite is examined by using lathe tool dynamometer attached with BANKA Lathe by varying the machining parameters like spindle speed, Depth of cut and Feed rate in 3 levels. Also, Roughness Average (Ra) of machined surfaces is measured by using Surface Roughness Tester (Mitutoyo SJ201). From the studies it is cleared that mechanical properties of a composites increases with addition of Grp and The cutting force were decreased with the reinforcement percentage and thus increases the machinability of composites and also results in increased surface finish.

'To quarterback behind the scenes, third-party efforts': the tobacco industry and the Tea Party.

PubMed

Fallin, Amanda; Grana, Rachel; Glantz, Stanton A

2014-07-01

The Tea Party, which gained prominence in the USA in 2009, advocates limited government and low taxes. Tea Party organisations, particularly Americans for Prosperity and FreedomWorks, oppose smoke-free laws and tobacco taxes. We used the Legacy Tobacco Documents Library, the Wayback Machine, Google, LexisNexis, the Center for Media and Democracy and the Center for Responsive Politics (opensecrets.org) to examine the tobacco companies' connections to the Tea Party. Starting in the 1980s, tobacco companies worked to create the appearance of broad opposition to tobacco control policies by attempting to create a grassroots smokers' rights movement. Simultaneously, they funded and worked through third-party groups, such as Citizens for a Sound Economy, the predecessor of AFP and FreedomWorks, to accomplish their economic and political agenda. There has been continuity of some key players, strategies and messages from these groups to Tea Party organisations. As of 2012, the Tea Party was beginning to spread internationally. Rather than being a purely grassroots movement that spontaneously developed in 2009, the Tea Party has developed over time, in part through decades of work by the tobacco industry and other corporate interests. It is important for tobacco control advocates in the USA and internationally, to anticipate and counter Tea Party opposition to tobacco control policies and ensure that policymakers, the media and the public understand the longstanding connection between the tobacco industry, the Tea Party and its associated organisations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Fatigue Life Variability in Large Aluminum Forgings with Residual Stress

DTIC Science & Technology

2011-07-01

been conducted. A detailed finite element analysis of the forge/ quench /coldwork/machine process was performed in order to predict the bulk residual...forge/ quench /coldwork/machine process was performed in order to predict the bulk residual stresses in a fictitious aluminum bulkhead. The residual...continues to develop the capability for computational simulation of the forge, quench , cold work and machining processes. In order to handle the

Pellet to Part Manufacturing System for CNCs

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

Roschli, Alex C.; Love, Lonnie J.; Post, Brian K.

Oak Ridge National Laboratory’s Manufacturing Demonstration Facility worked with Hybrid Manufacturing Technologies to develop a compact prototype composite additive manufacturing head that can effectively extrude injection molding pellets. The head interfaces with conventional CNC machine tools enabling rapid conversion of conventional machine tools to additive manufacturing tools. The intent was to enable wider adoption of Big Area Additive Manufacturing (BAAM) technology and combine BAAM technology with conventional machining systems.

Dual scan CT image recovery from truncated projections

NASA Astrophysics Data System (ADS)

Sarkar, Shubhabrata; Wahi, Pankaj; Munshi, Prabhat

2017-12-01

There are computerized tomography (CT) scanners available commercially for imaging small objects and they are often categorized as mini-CT X-ray machines. One major limitation of these machines is their inability to scan large objects with good image quality because of the truncation of projection data. An algorithm is proposed in this work which enables such machines to scan large objects while maintaining the quality of the recovered image.

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.

Harmony search optimization in dimensional accuracy of die sinking EDM process using SS316L stainless steel

NASA Astrophysics Data System (ADS)

Deris, A. M.; Zain, A. M.; Sallehuddin, R.; Sharif, S.

2017-09-01

Electric discharge machine (EDM) is one of the widely used nonconventional machining processes for hard and difficult to machine materials. Due to the large number of machining parameters in EDM and its complicated structural, the selection of the optimal solution of machining parameters for obtaining minimum machining performance is remain as a challenging task to the researchers. This paper proposed experimental investigation and optimization of machining parameters for EDM process on stainless steel 316L work piece using Harmony Search (HS) algorithm. The mathematical model was developed based on regression approach with four input parameters which are pulse on time, peak current, servo voltage and servo speed to the output response which is dimensional accuracy (DA). The optimal result of HS approach was compared with regression analysis and it was found HS gave better result y giving the most minimum DA value compared with regression approach.

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.

Entanglement-Based Machine Learning on a Quantum Computer

NASA Astrophysics Data System (ADS)

Cai, X.-D.; Wu, D.; Su, Z.-E.; Chen, M.-C.; Wang, X.-L.; Li, Li; Liu, N.-L.; Lu, C.-Y.; Pan, J.-W.

2015-03-01

Machine learning, a branch of artificial intelligence, learns from previous experience to optimize performance, which is ubiquitous in various fields such as computer sciences, financial analysis, robotics, and bioinformatics. A challenge is that machine learning with the rapidly growing "big data" could become intractable for classical computers. Recently, quantum machine learning algorithms [Lloyd, Mohseni, and Rebentrost, arXiv.1307.0411] were proposed which could offer an exponential speedup over classical algorithms. Here, we report the first experimental entanglement-based classification of two-, four-, and eight-dimensional vectors to different clusters using a small-scale photonic quantum computer, which are then used to implement supervised and unsupervised machine learning. The results demonstrate the working principle of using quantum computers to manipulate and classify high-dimensional vectors, the core mathematical routine in machine learning. The method can, in principle, be scaled to larger numbers of qubits, and may provide a new route to accelerate machine learning.

Dynamic State Estimation for Multi-Machine Power System by Unscented Kalman Filter With Enhanced Numerical Stability

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

Qi, Junjian; Sun, Kai; Wang, Jianhui

In this paper, in order to enhance the numerical stability of the unscented Kalman filter (UKF) used for power system dynamic state estimation, a new UKF with guaranteed positive semidifinite estimation error covariance (UKFGPS) is proposed and compared with five existing approaches, including UKFschol, UKF-kappa, UKFmodified, UKF-Delta Q, and the squareroot UKF (SRUKF). These methods and the extended Kalman filter (EKF) are tested by performing dynamic state estimation on WSCC 3-machine 9-bus system and NPCC 48-machine 140-bus system. For WSCC system, all methods obtain good estimates. However, for NPCC system, both EKF and the classic UKF fail. It is foundmore » that UKFschol, UKF-kappa, and UKF-Delta Q do not work well in some estimations while UKFGPS works well in most cases. UKFmodified and SRUKF can always work well, indicating their better scalability mainly due to the enhanced numerical stability.« less

The Effect of Different Non-Metallic Inclusions on the Machinability of Steels

PubMed Central

Ånmark, Niclas; Karasev, Andrey; Jönsson, Pär Göran

2015-01-01

Considerable research has been conducted over recent decades on the role of non-metallic inclusions and their link to the machinability of different steels. The present work reviews the mechanisms of steel fractures during different mechanical machining operations and the behavior of various non-metallic inclusions in a cutting zone. More specifically, the effects of composition, size, number and morphology of inclusions on machinability factors (such as cutting tool wear, power consumption, etc.) are discussed and summarized. Finally, some methods for modification of non-metallic inclusions in the liquid steel are considered to obtain a desired balance between mechanical properties and machinability of various steel grades. PMID:28787969

Critical Speed of The Glass Glue Machine's Creep and Influence Factors Analysis

NASA Astrophysics Data System (ADS)

Yang, Jianxi; Huang, Jian; Wang, Liying; Shi, Jintai

When automatic glass glue machine works, two questions of the machine starting vibrating and stick-slip motion are existing. These problems should be solved. According to these questions, a glue machine's model for studying stick-slip is established. Based on the dynamics system describing of the model, mathematical expression is presented. The creep critical speed expression is constructed referring to existing research achievement and a new conclusion is found. The influencing factors of stiffness, dampness, mass, velocity, difference of static and kinetic coefficient of friction are analyzed through Matlab simulation. Research shows that reasonable choice of influence parameters can improve the creep phenomenon. These all supply the theory evidence for improving the machine's motion stability.

Machine learning and medicine: book review and commentary.

PubMed

Koprowski, Robert; Foster, Kenneth R

2018-02-01

This article is a review of the book "Master machine learning algorithms, discover how they work and implement them from scratch" (ISBN: not available, 37 USD, 163 pages) edited by Jason Brownlee published by the Author, edition, v1.10 http://MachineLearningMastery.com . An accompanying commentary discusses some of the issues that are involved with use of machine learning and data mining techniques to develop predictive models for diagnosis or prognosis of disease, and to call attention to additional requirements for developing diagnostic and prognostic algorithms that are generally useful in medicine. Appendix provides examples that illustrate potential problems with machine learning that are not addressed in the reviewed book.

Looking north at the threading machine of the no. 1 ...

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

Looking north at the threading machine of the no. 1 seamless line in bay 11 of the main pipe mill building - U.S. Steel National Tube Works, Main Pipe Mill Building, Along Monongahela River, McKeesport, Allegheny County, PA

Office Requirements in the Portland Standard Metropolitan Area

ERIC Educational Resources Information Center

Robertson, Leonard

1975-01-01

The findings evolved from questionnaires received from 204 firms pertaining to needed skills in spelling, typewriting, automatic typewriting, calculating machines, transcription machines, shorthand, and work processing, as well as to attributes of job attendance, cooperation, courtesy, telephone personality and appearance. (Author)

Parental attitudes towards soft drink vending machines in high schools.

PubMed

Hendel-Paterson, Maia; French, Simone A; Story, Mary

2004-10-01

Soft drink vending machines are available in 98% of US high schools. However, few data are available about parents' opinions regarding the availability of soft drink vending machines in schools. Six focus groups with 33 parents at three suburban high schools were conducted to describe the perspectives of parents regarding soft drink vending machines in their children's high school. Parents viewed the issue of soft drink vending machines as a matter of their children's personal choice more than as an issue of a healthful school environment. However, parents were unaware of many important details about the soft drink vending machines in their children's school, such as the number and location of machines, hours of operation, types of beverages available, or whether the school had contracts with soft drink companies. Parents need more information about the number of soft drink vending machines at their children's school, the beverages available, the revenue generated by soft drink vending machine sales, and the terms of any contracts between the school and soft drink companies.

Detecting Dementia Through Interactive Computer Avatars

PubMed Central

Adachi, Hiroyoshi; Ukita, Norimichi; Ikeda, Manabu; Kazui, Hiroaki; Kudo, Takashi; Nakamura, Satoshi

2017-01-01

This paper proposes a new approach to automatically detect dementia. Even though some works have detected dementia from speech and language attributes, most have applied detection using picture descriptions, narratives, and cognitive tasks. In this paper, we propose a new computer avatar with spoken dialog functionalities that produces spoken queries based on the mini-mental state examination, the Wechsler memory scale-revised, and other related neuropsychological questions. We recorded the interactive data of spoken dialogues from 29 participants (14 dementia and 15 healthy controls) and extracted various audiovisual features. We tried to predict dementia using audiovisual features and two machine learning algorithms (support vector machines and logistic regression). Here, we show that the support vector machines outperformed logistic regression, and by using the extracted features they classified the participants into two groups with 0.93 detection performance, as measured by the areas under the receiver operating characteristic curve. We also newly identified some contributing features, e.g., gap before speaking, the variations of fundamental frequency, voice quality, and the ratio of smiling. We concluded that our system has the potential to detect dementia through spoken dialog systems and that the system can assist health care workers. In addition, these findings could help medical personnel detect signs of dementia. PMID:29018636

Informing the Human Plasma Protein Binding of ...

EPA Pesticide Factsheets

The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data is scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict Fub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18 Fub. The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0

Women, work and pregnancy outcome.

PubMed

Huffman, S

1988-01-01

In developing countries, 1/3 of infants are born weighing less than 2500 grams. A study conducted in Ethiopia among women consuming about 1600 kcal/day, those who were very physically active during pregnancy bore smaller babies, and gained less weight during pregnancy, than those who were not so active. Average birth weight was 3068 grams for the 1st group, 3270 grams for the less active. The active group of women gained an average of 6.5 kilograms, and the less active 9.2 kilograms. Women who did not engage in heavy work during pregnancy, although they were undernourished, apparently did not bear growth-retarded babies. Indirect evidence for the effect of physical activity on pregnancy outcome comes from studies conducted in Taiwan, and the Gambia. These studies, and others from Malawi, Burkina Faso, and Kenya have shown that women's energy expenditures vary greatly with the agricultural season. Daily housekeeping tasks, however, also consume a lot of women's energy. Technologies that allow women to reduce energy expenditure can have beneficial effects, if they do not simultaneously reduce their incomes. For instance, programs improving water or fuel availability, or reducing fuel needs, reduce women's energy expenditures. Food processing mills can help too if women have access to them, and are thus not in danger of being displaced from their jobs and losing necessary income. Examples of technology improving women's tasks are pedal drying machines for nice in Bangladesh, using a greater and pressing machine to prepare gari in Ghana; but growing thicker rice stalks in Indonesia displaced women workers and reduced income.

Relations between work and entropy production for general information-driven, finite-state engines

NASA Astrophysics Data System (ADS)

Merhav, Neri

2017-02-01

We consider a system model of a general finite-state machine (ratchet) that simultaneously interacts with three kinds of reservoirs: a heat reservoir, a work reservoir, and an information reservoir, the latter being taken to be a running digital tape whose symbols interact sequentially with the machine. As has been shown in earlier work, this finite-state machine can act as a demon (with memory), which creates a net flow of energy from the heat reservoir into the work reservoir (thus extracting useful work) at the price of increasing the entropy of the information reservoir. Under very few assumptions, we propose a simple derivation of a family of inequalities that relate the work extraction with the entropy production. These inequalities can be seen as either upper bounds on the extractable work or as lower bounds on the entropy production, depending on the point of view. Many of these bounds are relatively easy to calculate and they are tight in the sense that equality can be approached arbitrarily closely. In their basic forms, these inequalities are applicable to any finite number of cycles (and not only asymptotically), and for a general input information sequence (possibly correlated), which is not necessarily assumed even stationary. Several known results are obtained as special cases.

The effects of subcutaneous injection of nicotine on osseointegration of machined and anodized implants in rabbits.

PubMed

Linden, Maria Salete Sandini; Bittencourt, Marcos Eugênio de; Carli, João Paulo De; Miyagaki, Daniela Cristina; Santos, Pâmela Letícia Dos; Paranhos, Luiz Renato; Groppo, Francisco Carlos; Ramacciato, Juliana Cama

2018-01-01

To evaluate the influence of subcutaneous injection nicotine in osseointegration process on different implant surfaces. Twenty-two male rabbits were distributed into two groups according to the subcutaneous injections: (1) nicotine 3 mg/day/kg and (2) 0.9 % NaCI 3 mL/day/kg, three times a day; subgroups were then designated-machined and anodized implants were placed in the right and left tibia bones, respectively. The animals were submitted euthanasia after periods of eight weeks to determine nicotine and cotinine levels, alkaline phosphatase and biomechanical analysis. The plasmatic levels of nicotine and cotinine were 0.5 ± 0.28 ng/mL and 9.5 ± 6.51 ng/mL, respectively. The alkaline phosphatase analyses in blood levels in control group were observed 40.8 ± 11.88 UI/L and 40.75 ± 12.46 UI/L, for the surfaces machined and anodized, respectively. In the test group was observed levels 37.9 ± 4.84 UI/L, for both implant surfaces. No significant differences were observed between control and test groups and between the implant surfaces regarding alkaline phosphatase blood levels. For biomechanics, no significant differences were observed in control group between the machined (25±8.46 Ncm) or anodized (31.2 ± 6.76 Ncm) implants. However, the treatment with nicotine induced higher torque than control in both machined (38.3 ± 13.52 Ncm) and anodized (35.5 ± 14.17 Ncm) implants, with p = 0.0024 and p = 0.0121, respectively. Subcutaneous injection of nicotine following implant insertion didn't have effect on osseointegration, independently from the implant surface.

The scheme machine: A case study in progress in design derivation at system levels

NASA Technical Reports Server (NTRS)

Johnson, Steven D.

1995-01-01

The Scheme Machine is one of several design projects of the Digital Design Derivation group at Indiana University. It differs from the other projects in its focus on issues of system design and its connection to surrounding research in programming language semantics, compiler construction, and programming methodology underway at Indiana and elsewhere. The genesis of the project dates to the early 1980's, when digital design derivation research branched from the surrounding research effort in programming languages. Both branches have continued to develop in parallel, with this particular project serving as a bridge. However, by 1990 there remained little real interaction between the branches and recently we have undertaken to reintegrate them. On the software side, researchers have refined a mathematically rigorous (but not mechanized) treatment starting with the fully abstract semantic definition of Scheme and resulting in an efficient implementation consisting of a compiler and virtual machine model, the latter typically realized with a general purpose microprocessor. The derivation includes a number of sophisticated factorizations and representations and is also deep example of the underlying engineering methodology. The hardware research has created a mechanized algebra supporting the tedious and massive transformations often seen at lower levels of design. This work has progressed to the point that large scale devices, such as processors, can be derived from first-order finite state machine specifications. This is roughly where the language oriented research stops; thus, together, the two efforts establish a thread from the highest levels of abstract specification to detailed digital implementation. The Scheme Machine project challenges hardware derivation research in several ways, although the individual components of the system are of a similar scale to those we have worked with before. The machine has a custom dual-ported memory to support garbage collection. It consists of four tightly coupled processes--processor, collector, allocator, memory--with a very non-trivial synchronization relationship. Finally, there are deep issues of representation for the run-time objects of a symbolic processing language. The research centers on verification through integrated formal reasoning systems, but is also involved with modeling and prototyping environments. Since the derivation algebra is basd on an executable modeling language, there is opportunity to incorporate design animation in the design process. We are looking for ways to move smoothly and incrementally from executable specifications into hardware realization. For example, we can run the garbage collector specification, a Scheme program, directly against the physical memory prototype, and similarly, the instruction processor model against the heap implementation.

Non-symmetric approach to single-screw expander and compressor modeling

NASA Astrophysics Data System (ADS)

Ziviani, Davide; Groll, Eckhard A.; Braun, James E.; Horton, W. Travis; De Paepe, M.; van den Broek, M.

2017-08-01

Single-screw type volumetric machines are employed both as compressors in refrigeration systems and, more recently, as expanders in organic Rankine cycle (ORC) applications. The single-screw machine is characterized by having a central grooved rotor and two mating toothed starwheels that isolate the working chambers. One of the main features of such machine is related to the simultaneous occurrence of the compression or expansion processes on both sides of the main rotor which results in a more balanced loading on the main shaft bearings with respect to twin-screw machines. However, the meshing between starwheels and main rotor is a critical aspect as it heavily affects the volumetric performance of the machine. To allow flow interactions between the two sides of the rotor, a non-symmetric modelling approach has been established to obtain a more comprehensive model of the single-screw machine. The resulting mechanistic model includes in-chamber governing equations, leakage flow models, heat transfer mechanisms, viscous and mechanical losses. Forces and moments balances are used to estimate the loads on the main shaft bearings as well as on the starwheel bearings. An 11 kWe single-screw expander (SSE) adapted from an air compressor operating with R245fa as working fluid is used to validate the model. A total of 60 steady-steady points at four different rotational speeds have been collected to characterize the performance of the machine. The maximum electrical power output and overall isentropic efficiency measured were 7.31 kW and 51.91%, respectively.

A hybrid least squares support vector machines and GMDH approach for river flow forecasting

NASA Astrophysics Data System (ADS)

Samsudin, R.; Saad, P.; Shabri, A.

2010-06-01

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

Artificial muscles driven by the cooperative actuation of electrochemical molecular machines. Persistent discrepancies and challenges

NASA Astrophysics Data System (ADS)

Otero

2017-10-01

Here we review the persisting conceptual discrepancies between different research groups working on artificial muscles based on conducting polymers and other electroactive material. The basic question is if they can be treated as traditional electro-mechanical (physical) actuators driven by electric fields and described by some adaptation of their physical models or if, replicating natural muscles, they are electro-chemo-mechanical actuators driven by electrochemical reaction of the constitutive molecular machines: the polymeric chains. In that case the charge consumed by the reaction will control the volume variation of the muscular material and the motor displacement, following the basic and single Faraday's laws: the charge consumed by the reaction determines the number of exchanged ions and solvent, the film volume variation to lodge/expel them and the amplitude of the movement. Deviations from the linear relationships are due to the osmotic exchange of solvent and to the presence of parallel reactions from the electrolyte, which originate creeping effects. Challenges and limitations are underlined.

A note on resource allocation scheduling with group technology and learning effects on a single machine

NASA Astrophysics Data System (ADS)

Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu

2017-09-01

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.

Implementation of GPS Machine Controlled Grading - Phase III (2008) and Technical Training

DOT National Transportation Integrated Search

2009-02-01

Beginning in 2006, WisDOT and the Construction Material and Support Center (CMSC) at UW-Madison worked together to develop the specifications and the QA/QC procedures for GPS machine guidance on highway grading projects. These specifications and proc...

ClearTK 2.0: Design Patterns for Machine Learning in UIMA

PubMed Central

Bethard, Steven; Ogren, Philip; Becker, Lee

2014-01-01

ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework. PMID:29104966

ClearTK 2.0: Design Patterns for Machine Learning in UIMA.

PubMed

Bethard, Steven; Ogren, Philip; Becker, Lee

2014-05-01

ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework.

Waste Minimization Program. Air Force Plant 6.

DTIC Science & Technology

1986-02-01

coolant’s life, it can cause the formation of gummy residues on machines and parts and cause corrosion of the machine and work tools . i 3-91e 0 _ b-4 LA...2-9 3.0 Waste Minimization Program, AFP 6 3-1 3.1 Machine Coolant Waste 3-1 3.2 Engine Oil and Hydraulic Fluid Waste 3-12 3.3 Paint Sludge 3-14 3.4...Incineration 3-54 LIST OF FIGURES Figure Page 3-1 Annual Machine Coolant Use 3-5 n 3-2 oily Industrial Waste Treatment System 3-7 3-3 Schematic of Paint

Efficiency of autonomous soft nanomachines at maximum power.

PubMed

Seifert, Udo

2011-01-14

We consider nanosized artificial or biological machines working in steady state enforced by imposing nonequilibrium concentrations of solutes or by applying external forces, torques, or electric fields. For unicyclic and strongly coupled multicyclic machines, efficiency at maximum power is not bounded by the linear response value 1/2. For strong driving, it can even approach the thermodynamic limit 1. Quite generally, such machines fall into three different classes characterized, respectively, as "strong and efficient," "strong and inefficient," and "balanced." For weakly coupled multicyclic machines, efficiency at maximum power has lost any universality even in the linear response regime.

Teleoperators - Manual/automatic system requirements.

NASA Technical Reports Server (NTRS)

Janow, C.; Malone, T. B.

1973-01-01

The teleoperator is defined as a remotely controlled, cybernetic, man-machine system designed to extend and augment man's sensory, manipulative, and cognitive capabilities. The teleoperator system incorporates the decision making, adaptive intelligence without requiring its presence. The man and the machine work as a team, each contributing unique and significant capabilities, and each depending on the other to achieve a common goal. Some of the more significant requirements associated with the development of teleoperator systems technology for space, industry, and medicine are examined. Emphasis is placed on the requirement to more effectively use the man and the machine in any man-machine system.

Lunar regolith bagging system

NASA Technical Reports Server (NTRS)

Cannon, Reuben; Henninger, Scott; Levandoski, Mark; Perkins, Jim; Pitchon, Jack; Swats, Robin; Wessels, Roger

1990-01-01

A design of a lunar regolith bag and bagging system is described. The bags of regolith are to be used for construction applications on the lunar surface. The machine is designed to be used in conjunction with the lunar SKITTER currently under development. The bags for this system are 1 cu ft volume and are made from a fiberglass composite weave. The machinery is constructed mostly from a boron/aluminum composite. The machine can fill 120 bags per hour and work for 8 hours a day. The man hours to machine hours ratio to operate the machine is .5/8.

[Present-day metal-cutting tools and working conditions].

PubMed

Kondratiuk, V P

1990-01-01

Polyfunctional machine-tools of a processing centre type are characterized by a set of hygienic advantages as compared to universal machine-tools. But low degree of mechanization and automation of some auxiliary processes, and constructional defects which decrease the ergonomic characteristics of the tools, involve labour intensity in multi-machine processing. The article specifies techniques of allowable noise level assessment, and proposes hygienic recommendations, some of which have been introduced into practice.

Can the job content questionnaire be used to assess structural and organizational properties of the work environment?

PubMed

Persson, Roger; Hansen, Åse Marie; Garde, Anne Helene; Kristiansen, Jesper; Nordander, Catarina; Balogh, Istvan; Ohlsson, Kerstina; Ostergren, Per-Olof; Ørbæk, Palle

2012-01-01

The theory behind the Job Content Questionnaire (JCQ) presumes that the "objective" social environment is measurable via self-report inventories such as the JCQ. Hence, it is expected that workers in identical work will respond highly similar. However, since no studies have evaluated this basic assumption, we decided to investigate whether workers performing highly similar work also responded similarly to the JCQ. JCQ data from a rubber-manufacturing (RM: n = 95) and a mechanical assembly company (MA: n = 119) were examined. On each worksite, men and women performed identical machine-paced job tasks. A population sample (n = 8,542) served as a reference group. In both the RM and MA groups, the job support questions were rated most similar. Yet, there was a substantial variation as regards choosing to agree or disagree with single JCQ items. The variation was also reflected in the scale scores. In the RM and MA groups, the variance of job demand and job control scores was 64-87% of that of the population sample. For job support scores, the corresponding variation was 42-87%. Conducting highly similar work does not lead to highly similar reports in the JCQ. In view of the large response variation, it seems that the attempt to avoid personal influence by minimizing the self-reflexive component in the questions asked, and using response alternative that indicates degree of agreement, does not seem to work as intended.

Modification of working conditions based on ergo THK reducing workload, muscle tension, and fatigue of rice milling workers in J village

NASA Astrophysics Data System (ADS)

Ruliati, L. P.; Adiputra, N.; Sutjana, I. D. P.; Sutajaya, I. M.

2017-11-01

Rice mill is one of the businesses in informal sector. From the rice milling process, ergonomic problems arise when employees work with bent position that done repeatedly to lift grain sacks to be transferred to peeler machine. This situation will affect the comfort of work, thus increasing the workload, muscle tension, and fatigue. The consequence will certainly affect the health and productivity of workers. In this study introduces ergo Tri Hita Karana (ergo THK) as an ergonomics intervention model which solves ergonomics problems of the cultural aspects of THK. The study aim is to determine the modification of working conditions based Ergo THK to reduce workload, muscle tension and fatigue. This research uses Randomized Pretest and Posttest Control Group Design experimental design. The subjects were 30 male rice mill workers with an age range of 16 until 56 years, and then divided into 15 subjects in the control group and 15 subjects in the treatment group. The results showed that the average posttest workloads in the control group are 136.950 more less 0.297 and in the treatment group are 107.60 more less 0.396. Significance analysis showed that after the two groups done their activities, the average workload significantly different p less than 0.005. The amount of reduction in the workload between the two groups was 21.43 percent. In muscle tension posttest showed that the mean score of the muscle tension in the control group was 62.67 more less 7.31 and the treatment group was 20.96 more less 2.96. Significance analysis showed that both groups mean muscle-tension results were significantly different p less than 0.005. The amount of reduction in tension between the control group and the treatment group while working was 66.55 percent. At fatigue posttest showed that the mean score of fatigue in the control group was 76.40 more less 13.51 and the treatment group was 55.53 more less 9.51. Significant analysis showed that the mean fatigue of both groups significantly different p less than 0.005. The amount of reduction in fatigue between the control group and the treatment group while working was 27.31 percent. From this study it can be concluded that the modification of the working conditions based on Ergo THK can reduce the workload by 21.43 percent, muscle tension by 66.55 percent and fatigue by 27.31 percent.

Coordinated joint motion control system with position error correction

DOEpatents

Danko, George [Reno, NV

2011-11-22

Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two-joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.

Coordinated joint motion control system with position error correction

DOEpatents

Danko, George L.

2016-04-05

Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.

Radiator debris removing apparatus and work machine using same

DOEpatents

Martin, Kevin L [Washburn, IL; Elliott, Dwight E [Chillicothe, IL

2008-09-02

A radiator assembly includes a finned radiator core and a debris removing apparatus having a compressed air inlet and at least one compressed air outlet configured to direct compressed air through the radiator core. A work machine such as a wheel loader includes a radiator and a debris removing apparatus coupled with on-board compressed air and having at least one pressurized gas outlet configured to direct a gas toward the face of the radiator.

Scheduling a Medium-Sized Manufacturing Shop: A Simulation Study

DTIC Science & Technology

1993-09-01

distinction, elements of work order data include: the minimum machine type required for a work order, as well as the prgramming , set-up, and machining... prevent this from happening. Such a mechanism could take the form of a reprioritization function that is executed after a specified period of time...system for a very long time unless some mechanism is used to prevent this from happening. The jobs left in the system will be the ones that have very

Mi Primer Libro de Maquinas Simples: Trabajo y Fuerza. Escuela Intermedia Grados 7, 8 y 9 (My First Book of Simple Machines: Work and Force. Intermediate School Grades 7, 8, and 9).

ERIC Educational Resources Information Center

Alvarado, Patricio R.; Montalvo, Luis

This is the first book in a five-book physical science series on simple machines. The books are designed for Spanish-speaking junior high school students. This volume defines force and work by suggesting experiments and posing questions concerning drawings in the book which illustrate scientific principles. Answers to the questions are provided;…

Ball Machine Usage in Tennis: Movement Initiation and Swing Timing While Returning Balls from a Ball Machine and from a Real Server

PubMed Central

Carboch, Jan; Süss, Vladimir; Kocib, Tomas

2014-01-01

Practicing with the use of a ball machine could handicap a player compared to playing against an actual opponent. Recent studies have shown some differences in swing timing and movement coordination, when a player faces a ball projection machine as opposed to a human opponent. We focused on the time of movement initiation and on stroke timing during returning tennis serves (simulated by a ball machine or by a real server). Receivers’ movements were measured on a tennis court. In spite of using a serving ball speed from 90 kph to 135 kph, results showed significant differences in movement initiation and backswing duration between serves received from a ball machine and serves received from a real server. Players had shorter movement initiation when they faced a ball machine. Backswing duration was longer for the group using a ball machine. That demonstrates different movement timing of tennis returns when players face a ball machine. Use of ball machines in tennis practice should be limited as it may disrupt stroke timing. Key points Players have shorter initial move time when they are facing the ball machine. Using the ball machine results in different swing timing and movement coordination. The use of the ball machine should be limited. PMID:24790483

Ball machine usage in tennis: movement initiation and swing timing while returning balls from a ball machine and from a real server.

PubMed

Carboch, Jan; Süss, Vladimir; Kocib, Tomas

2014-05-01

Practicing with the use of a ball machine could handicap a player compared to playing against an actual opponent. Recent studies have shown some differences in swing timing and movement coordination, when a player faces a ball projection machine as opposed to a human opponent. We focused on the time of movement initiation and on stroke timing during returning tennis serves (simulated by a ball machine or by a real server). Receivers' movements were measured on a tennis court. In spite of using a serving ball speed from 90 kph to 135 kph, results showed significant differences in movement initiation and backswing duration between serves received from a ball machine and serves received from a real server. Players had shorter movement initiation when they faced a ball machine. Backswing duration was longer for the group using a ball machine. That demonstrates different movement timing of tennis returns when players face a ball machine. Use of ball machines in tennis practice should be limited as it may disrupt stroke timing. Key pointsPlayers have shorter initial move time when they are facing the ball machine.Using the ball machine results in different swing timing and movement coordination.The use of the ball machine should be limited.

Contributions a la caracterisation et a l'amelioration de l'usinabilite de pieces d'acier elaborees par metallurgie des poudres

NASA Astrophysics Data System (ADS)

Boilard, Patrick

Even though powder metallurgy (P/M) is a near net shape process, a large number of parts still require one or more machining operations during the course of their elaboration and/or their finishing. The main objectives of the work presented in this thesis are centered on the elaboration of blends with enhanced machinability, as well as helping with the definition and in the characterization of the machinability of P/M parts. Enhancing machinability can be done in various ways, through the use of machinability additives and by decreasing the amount of porosity of the parts. These different ways of enhancing machinability have been investigated thoroughly, by systematically planning and preparing series of samples in order to obtain valid and repeatable results leading to meaningful conclusions relevant to the P/M domain. Results obtained during the course of the work are divided into three main chapters: (1) the effect of machining parameters on machinability, (2) the effect of additives on machinability, and (3) the development and the characterization of high density parts obtained by liquid phase sintering. Regarding the effect of machining parameters on machinability, studies were performed on parameters such as rotating speed, feed, tool position and diameter of the tool. Optimal cutting parameters are found for drilling operations performed on a standard FC-0208 blend, for different machinability criteria. Moreover, study of material removal rates shows the sensitivity of the machinability criteria for different machining parameters and indicates that thrust force is more regular than tool wear and slope of the drillability curve in the characterization of machinability. The chapter discussing the effect of various additives on machinability reveals many interesting results. First, work carried out on MoS2 additions reveals the dissociation of this additive and the creation of metallic sulphides (namely CuxS sulphides) when copper is present. Results also show that it is possible to reduce the amount of MoS2 in the blend so as to lower the dimensional change and the cost (blend Mo8A), while enhancing machinability and keeping hardness values within the same range (70 HRB). Second, adding enstatite (MgO·SiO2) permits the observation of the mechanisms occurring with the use of this additive. It is found that the stability of enstatite limits the diffusion of graphite during sintering, leading to the presence of free graphite in the pores, thus enhancing machinability. Furthermore, a lower amount of graphite in the matrix leads to a lower hardness, which is also beneficial to machinability. It is also found that the presence of copper enhances the diffusion of graphite, through the formation of a liquid phase during sintering. With the objective of improving machinability by reaching higher densities, blends were developed for densification through liquid phase sintering. High density samples are obtained (>7.5 g/cm3) for blends prepared with Fe-C-P constituents, namely with 0.5%P and 2.4%C. By systematically studying the effect of different parameters, the importance of the chemical composition (mainly the carbon content) and the importance of the sintering cycle (particularly the cooling rate) are demonstrated. Moreover, various heat treatments studied illustrate the different microstructures achievable for this system, showing various amounts of cementite, pearlite and free graphite. Although the machinability is limited for samples containing large amounts of cementite, it can be greatly improved with very slow cooling, leading to graphitization of the carbon in presence of phosphorus. Adequate control of the sintering cycle on samples made from FGS1625 powder leads to the obtention of high density (≥7.0 g/cm 3) microstructures containing various amounts of pearlite, ferrite and free graphite. Obtaining ferritic microstructures with free graphite designed for very high machinability (tool wear <1.0%) or fine pearlitic microstructures with excellent mechanical properties (transverse rupture strength >1600 MPa) is therefore possible. These results show that improvement of machinability through higher densities is limited by microstructure. Indeed, for the studied samples, microstructure is dominant in the determination of machinability, far more important than density, judging by the influence of cementite or of the volume fraction of free graphite on machinability for example. (Abstract shortened by UMI.)

Research on intelligent machine self-perception method based on LSTM

NASA Astrophysics Data System (ADS)

Wang, Qiang; Cheng, Tao

2018-05-01

In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

Tomography and generative training with quantum Boltzmann machines

NASA Astrophysics Data System (ADS)

Kieferová, Mária; Wiebe, Nathan

2017-12-01

The promise of quantum neural nets, which utilize quantum effects to model complex data sets, has made their development an aspirational goal for quantum machine learning and quantum computing in general. Here we provide methods of training quantum Boltzmann machines. Our work generalizes existing methods and provides additional approaches for training quantum neural networks that compare favorably to existing methods. We further demonstrate that quantum Boltzmann machines enable a form of partial quantum state tomography that further provides a generative model for the input quantum state. Classical Boltzmann machines are incapable of this. This verifies the long-conjectured connection between tomography and quantum machine learning. Finally, we prove that classical computers cannot simulate our training process in general unless BQP=BPP , provide lower bounds on the complexity of the training procedures and numerically investigate training for small nonstoquastic Hamiltonians.

Selection of Wire Electrical Discharge Machining Process Parameters on Stainless Steel AISI Grade-304 using Design of Experiments Approach

NASA Astrophysics Data System (ADS)

Lingadurai, K.; Nagasivamuni, B.; Muthu Kamatchi, M.; Palavesam, J.

2012-06-01

Wire electrical discharge machining (WEDM) is a specialized thermal machining process capable of accurately machining parts of hard materials with complex shapes. Parts having sharp edges that pose difficulties to be machined by the main stream machining processes can be easily machined by WEDM process. Design of Experiments approach (DOE) has been reported in this work for stainless steel AISI grade-304 which is used in cryogenic vessels, evaporators, hospital surgical equipment, marine equipment, fasteners, nuclear vessels, feed water tubing, valves, refrigeration equipment, etc., is machined by WEDM with brass wire electrode. The DOE method is used to formulate the experimental layout, to analyze the effect of each parameter on the machining characteristics, and to predict the optimal choice for each WEDM parameter such as voltage, pulse ON, pulse OFF and wire feed. It is found that these parameters have a significant influence on machining characteristic such as metal removal rate (MRR), kerf width and surface roughness (SR). The analysis of the DOE reveals that, in general the pulse ON time significantly affects the kerf width and the wire feed rate affects SR, while, the input voltage mainly affects the MRR.

The rise of machine consciousness: studying consciousness with computational models.

PubMed

Reggia, James A

2013-08-01

Efforts to create computational models of consciousness have accelerated over the last two decades, creating a field that has become known as artificial consciousness. There have been two main motivations for this controversial work: to develop a better scientific understanding of the nature of human/animal consciousness and to produce machines that genuinely exhibit conscious awareness. This review begins by briefly explaining some of the concepts and terminology used by investigators working on machine consciousness, and summarizes key neurobiological correlates of human consciousness that are particularly relevant to past computational studies. Models of consciousness developed over the last twenty years are then surveyed. These models are largely found to fall into five categories based on the fundamental issue that their developers have selected as being most central to consciousness: a global workspace, information integration, an internal self-model, higher-level representations, or attention mechanisms. For each of these five categories, an overview of past work is given, a representative example is presented in some detail to illustrate the approach, and comments are provided on the contributions and limitations of the methodology. Three conclusions are offered about the state of the field based on this review: (1) computational modeling has become an effective and accepted methodology for the scientific study of consciousness, (2) existing computational models have successfully captured a number of neurobiological, cognitive, and behavioral correlates of conscious information processing as machine simulations, and (3) no existing approach to artificial consciousness has presented a compelling demonstration of phenomenal machine consciousness, or even clear evidence that artificial phenomenal consciousness will eventually be possible. The paper concludes by discussing the importance of continuing work in this area, considering the ethical issues it raises, and making predictions concerning future developments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Review on CNC-Rapid Prototyping

NASA Astrophysics Data System (ADS)

Z, M. Nafis O.; Y, Nafrizuan M.; A, Munira M.; J, Kartina

2012-09-01

This article reviewed developments of Computerized Numerical Control (CNC) technology in rapid prototyping process. Rapid prototyping (RP) can be classified into three major groups; subtractive, additive and virtual. CNC rapid prototyping is grouped under the subtractive category which involves material removal from the workpiece that is larger than the final part. Richard Wysk established the use of CNC machines for rapid prototyping using sets of 2½-D tool paths from various orientations about a rotary axis to machine parts without refixturing. Since then, there are few developments on this process mainly aimed to optimized the operation and increase the process capabilities to stand equal with common additive type of RP. These developments include the integration between machining and deposition process (hybrid RP), adoption of RP to the conventional machine and optimization of the CNC rapid prototyping process based on controlled parameters. The article ended by concluding that the CNC rapid prototyping research area has a vast space for improvement as in the conventional machining processes. Further developments and findings will enhance the usage of this method and minimize the limitation of current approach in building a prototype.

Verification of operation of the actuator control system using the integration the B&R Automation Studio software with a virtual model of the actuator system

NASA Astrophysics Data System (ADS)

Herbuś, K.; Ociepka, P.

2017-08-01

In the work is analysed a sequential control system of a machine for separating and grouping work pieces for processing. Whereas, the area of the considered problem is related with verification of operation of an actuator system of an electro-pneumatic control system equipped with a PLC controller. Wherein to verification is subjected the way of operation of actuators in view of logic relationships assumed in the control system. The actuators of the considered control system were three drives of linear motion (pneumatic cylinders). And the logical structure of the system of operation of the control system is based on the signals flow graph. The tested logical structure of operation of the electro-pneumatic control system was implemented in the Automation Studio software of B&R company. This software is used to create programs for the PLC controllers. Next, in the FluidSIM software was created the model of the actuator system of the control system of a machine. To verify the created program for the PLC controller, simulating the operation of the created model, it was utilized the approach of integration these two programs using the tool for data exchange in the form of the OPC server.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

NASA Astrophysics Data System (ADS)

Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

Learning clinically useful information from images: Past, present and future.

PubMed

Rueckert, Daniel; Glocker, Ben; Kainz, Bernhard

2016-10-01

Over the last decade, research in medical imaging has made significant progress in addressing challenging tasks such as image registration and image segmentation. In particular, the use of model-based approaches has been key in numerous, successful advances in methodology. The advantage of model-based approaches is that they allow the incorporation of prior knowledge acting as a regularisation that favours plausible solutions over implausible ones. More recently, medical imaging has moved away from hand-crafted, and often explicitly designed models towards data-driven, implicit models that are constructed using machine learning techniques. This has led to major improvements in all stages of the medical imaging pipeline, from acquisition and reconstruction to analysis and interpretation. As more and more imaging data is becoming available, e.g., from large population studies, this trend is likely to continue and accelerate. At the same time new developments in machine learning, e.g., deep learning, as well as significant improvements in computing power, e.g., parallelisation on graphics hardware, offer new potential for data-driven, semantic and intelligent medical imaging. This article outlines the work of the BioMedIA group in this area and highlights some of the challenges and opportunities for future work. Copyright © 2016 Elsevier B.V. All rights reserved.

The ergonomics of vertical turret lathe operation.

PubMed

Pratt, F M; Corlett, E N

1970-12-01

A study of the work load of 14 vertical turret lathe operators engaged on different work tasks in two factories is reported. For eight of these workers continuous heart rate recordings were made throughout the day. It was shown that in four cases improved technology was unlikely to lead to higher output and certain aspects of posture and equipment manipulation were major contributors to the limitations on increased output. The role of the work-rest schedule in increasing work loads was also demonstrated. Improvements in technology and methods to reduce the extent of certain work loads to enable heavy work to be done in shorter periods followed by light work or rest periods are given as means to modify and improve the output of these machines. Finally, the direction for the development of a predictive model for man-machine matching is introduced.

Relationships Between the External and Internal Training Load in Professional Soccer: What Can We Learn From Machine Learning?

PubMed

Jaspers, Arne; De Beéck, Tim Op; Brink, Michel S; Frencken, Wouter G P; Staes, Filip; Davis, Jesse J; Helsen, Werner F

2018-05-01

Machine learning may contribute to understanding the relationship between the external load and internal load in professional soccer. Therefore, the relationship between external load indicators (ELIs) and the rating of perceived exertion (RPE) was examined using machine learning techniques on a group and individual level. Training data were collected from 38 professional soccer players over 2 seasons. The external load was measured using global positioning system technology and accelerometry. The internal load was obtained using the RPE. Predictive models were constructed using 2 machine learning techniques, artificial neural networks and least absolute shrinkage and selection operator (LASSO) models, and 1 naive baseline method. The predictions were based on a large set of ELIs. Using each technique, 1 group model involving all players and 1 individual model for each player were constructed. These models' performance on predicting the reported RPE values for future training sessions was compared with the naive baseline's performance. Both the artificial neural network and LASSO models outperformed the baseline. In addition, the LASSO model made more accurate predictions for the RPE than did the artificial neural network model. Furthermore, decelerations were identified as important ELIs. Regardless of the applied machine learning technique, the group models resulted in equivalent or better predictions for the reported RPE values than the individual models. Machine learning techniques may have added value in predicting RPE for future sessions to optimize training design and evaluation. These techniques may also be used in conjunction with expert knowledge to select key ELIs for load monitoring.

A general purpose subroutine for fast fourier transform on a distributed memory parallel machine

NASA Technical Reports Server (NTRS)

Dubey, A.; Zubair, M.; Grosch, C. E.

1992-01-01

One issue which is central in developing a general purpose Fast Fourier Transform (FFT) subroutine on a distributed memory parallel machine is the data distribution. It is possible that different users would like to use the FFT routine with different data distributions. Thus, there is a need to design FFT schemes on distributed memory parallel machines which can support a variety of data distributions. An FFT implementation on a distributed memory parallel machine which works for a number of data distributions commonly encountered in scientific applications is presented. The problem of rearranging the data after computing the FFT is also addressed. The performance of the implementation on a distributed memory parallel machine Intel iPSC/860 is evaluated.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

PubMed Central

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

A field programmable gate array-based reconfigurable smart-sensor network for wireless monitoring of new generation computer numerically controlled machines.

PubMed

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; Romero-Troncoso, Rene de Jesus

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node.

[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.

In Praise of Robots

ERIC Educational Resources Information Center

Sagan, Carl

1975-01-01

The author of this article believes that human survival depends upon the ability to develop and work with machines of high artificial intelligence. He lists uses of such machines, including terrestrial mining, outer space exploration, and other tasks too dangerous, too expensive, or too boring for human beings. (MA)

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.

Evolving autonomous learning in cognitive networks.

PubMed

Sheneman, Leigh; Hintze, Arend

2017-12-01

There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

Agile Machining and Inspection Non-Nuclear Report (NNR) Project

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

Lazarus, Lloyd

This report is a high level summary of the eight major projects funded by the Agile Machining and Inspection Non-Nuclear Readiness (NNR) project (FY06.0422.3.04.R1). The largest project of the group is the Rapid Response project in which the six major sub categories are summarized. This project focused on the operations of the machining departments that will comprise Special Applications Machining (SAM) in the Kansas City Responsive Infrastructure Manufacturing & Sourcing (KCRIMS) project. This project was aimed at upgrading older machine tools, developing new inspection tools, eliminating Classified Removable Electronic Media (CREM) in the handling of classified Numerical Control (NC) programsmore » by installing the CRONOS network, and developing methods to automatically load Coordinated-Measuring Machine (CMM) inspection data into bomb books and product score cards. Finally, the project personnel leaned perations of some of the machine tool cells, and now have the model to continue this activity.« less

Radiographic evaluation of marginal bone level around implants with different neck designs after 1 year.

PubMed

Shin, Young-Kyu; Han, Chong-Hyun; Heo, Seong-Joo; Kim, Sunjai; Chun, Heoung-Jae

2006-01-01

To evaluate the influence of macro- and microstructure of the implant surface at the marginal bone level after functional loading. Sixty-eight patients were randomly assigned to 1 of 3 groups. The first group received 35 implants with a machined neck (Ankylos); the second group, 34 implants with a rough-surfaced neck (Stage 1); and the third, 38 implants with a rough-surfaced neck with microthreads (Oneplant). Clinical and radiographic examinations were conducted at baseline (implant loading) and 3, 6, and 12 months postloading. Two-way repeated analysis of variance (ANOVA) was used to test the significance of marginal bone change of each tested group at baseline, 3, 6, and 12 month follow-ups and 1-way ANOVA was also used to compare the bone loss of each time interval within the same implant group (P < .05). At 12 months, significant differences were noted in the amount of alveolar bone loss recorded for the 3 groups (P < .05). The group with the rough-surfaced microthreaded neck had a mean crestal bone loss of 0.18 +/- 0.16 mm; the group with the rough-surfaced neck, 0.76 +/- 0.21 mm; and the group with the machined neck, 1.32 +/- 0.27 mm. In the rough-surfaced group and the rough-surfaced microthreaded group, no statistically significant changes were observed after 3 months, whereas the machined-surface group showed significant bone loss for every interval (P < .05). To minimize marginal bone loss, in addition to the use of a rough surface at the marginal bone level, a macroscopic modification such as the addition of microthreads could be recommended. A rough surface and microthreads at the implant neck not only reduce crestal bone loss but also help with early biomechanical adaptation against loading in comparison to the machined neck design. A rough surface with microthreads at the implant neck was the most effective design to maintain the marginal bone level against functional loading.

Cost Analysis of a Home-Based Nurse Care Coordination Program

PubMed Central

Marek, Karen Dorman; Stetzer, Frank; Adams, Scott J; Bub, Linda Denison; Schlidt, Andrea; Colorafi, Karen Jiggins

2014-01-01

Objectives To determine whether a home-based care coordination program focused on medication self-management would affect the cost of care to the Medicare program and whether the addition of technology, a medication-dispensing machine, would further reduce cost. Design Randomized, controlled, three-arm longitudinal study. Setting Participant homes in a large Midwestern urban area. Participants Older adults identified as having difficulty managing their medications at discharge from Medicare Home Health Care (N = 414). Intervention A team consisting of advanced practice nurses (APNs) and registered nurses (RNs) coordinated care for two groups: home-based nurse care coordination (NCC) plus a pill organizer group and NCC plus a medication-dispensing machine group. Measurements To measure cost, participant claims data from 2005 to 2011 were retrieved from Medicare Part A and B Standard Analytical Files. Results Ordinary least squares regression with covariate adjustment was used to estimate monthly dollar savings. Total Medicare costs were $447 per month lower in the NCC plus pill organizer group (P = .11) than in a control group that received usual care. For participants in the study at least 3 months, total Medicare costs were $491 lower per month in the NCC plus pill organizer group (P = .06) than in the control group. The cost of the NCC plus pill organizer intervention was $151 per month, yielding a net savings of $296 per month or $3,552 per year. The cost of the NCC plus medication-dispensing machine intervention was $251 per month, and total Medicare costs were $409 higher per month than in the NCC plus pill organizer group. Conclusion Nurse care coordination plus a pill organizer is a cost-effective intervention for frail elderly Medicare beneficiaries. The addition of the medication machine did not enhance the cost effectiveness of the intervention. PMID:25482242

Chip breaking system for automated machine tool

DOEpatents

Arehart, Theodore A.; Carey, Donald O.

1987-01-01

The invention is a rotary selectively directional valve assembly for use in an automated turret lathe for directing a stream of high pressure liquid machining coolant to the interface of a machine tool and workpiece for breaking up ribbon-shaped chips during the formation thereof so as to inhibit scratching or other marring of the machined surfaces by these ribbon-shaped chips. The valve assembly is provided by a manifold arrangement having a plurality of circumferentially spaced apart ports each coupled to a machine tool. The manifold is rotatable with the turret when the turret is positioned for alignment of a machine tool in a machining relationship with the workpiece. The manifold is connected to a non-rotational header having a single passageway therethrough which conveys the high pressure coolant to only the port in the manifold which is in registry with the tool disposed in a working relationship with the workpiece. To position the machine tools the turret is rotated and one of the tools is placed in a material-removing relationship of the workpiece. The passageway in the header and one of the ports in the manifold arrangement are then automatically aligned to supply the machining coolant to the machine tool workpiece interface for breaking up of the chips as well as cooling the tool and workpiece during the machining operation.

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.

Experimental investigation into effect of cutting parameters on surface integrity of hardened tool steel

NASA Astrophysics Data System (ADS)

Bashir, K.; Alkali, A. U.; Elmunafi, M. H. S.; Yusof, N. M.

2018-04-01

Recent trend in turning hardened materials have gained popularity because of its immense machinability benefits. However, several machining processes like thermal assisted machining and cryogenic machining have reveal superior machinability benefits over conventional dry turning of hardened materials. Various engineering materials have been studied. However, investigations on AISI O1 tool steel have not been widely reported. In this paper, surface finish and surface integrity dominant when hard turning AISI O1 tool steel is analysed. The study is focused on the performance of wiper coated ceramic tool with respect to surface roughness and surface integrity of hardened tool steel. Hard turned tool steel was machined at varying cutting speed of 100, 155 and 210 m/min and feed rate of 0.05, 0.125 and 0.20mm/rev. The depth of cut of 0.2mm was maintained constant throughout the machining trials. Machining was conducted using dry turning on 200E-axis CNC lathe. The experimental study revealed that the surface finish is relatively superior at higher cutting speed of 210m/min. The surface finish increases when cutting speed increases whereas surface finish is generally better at lower feed rate of 0.05mm/rev. The experimental study conducted have revealed that phenomena such as work piece vibration due to poor or improper mounting on the spindle also contributed to higher surface roughness value of 0.66Ra during turning at 0.2mm/rev. Traces of white layer was observed when viewed with optical microscope which shows evidence of cutting effects on the turned work material at feed rate of 0.2 rev/min

A translator and simulator for the Burroughs D machine

NASA Technical Reports Server (NTRS)

Roberts, J.

1972-01-01

The D Machine is described as a small user microprogrammable computer designed to be a versatile building block for such diverse functions as: disk file controllers, I/O controllers, and emulators. TRANSLANG is an ALGOL-like language, which allows D Machine users to write microprograms in an English-like format as opposed to creating binary bit pattern maps. The TRANSLANG translator parses TRANSLANG programs into D Machine microinstruction bit patterns which can be executed on the D Machine simulator. In addition to simulation and translation, the two programs also offer several debugging tools, such as: a full set of diagnostic error messages, register dumps, simulated memory dumps, traces on instructions and groups of instructions, and breakpoints.

Development of a non-piston MR suspension rod for variable mass systems

NASA Astrophysics Data System (ADS)

Deng, Huaxia; Han, Guanghui; Zhang, Jin; Wang, Mingxian; Ma, Mengchao; Zhong, Xiang; Yu, Liandong

2018-06-01

The semi-active suspension systems for variable mass systems require long work stroke and variable damping, while the currently piston structure limits the work stroke for the magnetorheological (MR) dampers. The main work of this paper is to design a semi-active non-piston MR (NPMR) suspension rod for the reduction of the vibration of an automatic impeller washing machine, which is a typical variable mass system. The designed suspension rod locates in the suspension system that links the internal tub to the washing machine cabinet. The NPMR suspension rod includes a MR part and a air part. The MR part can provide low initial damping force and the unlimited work stroke compared with the piston MR damper. The hysteretic response tests and vibration performance evaluation with different loadings are conducted to verify the dynamic performance for the designed rod. The measured damping force of the MR part varies from 5 to 20 N. Studies of dehydration mode experiments of the washing machine indicate that its vibration acceleration with the NPMR suspension rods can reduce to half of the original passive ones in certain conditions.

Improved equivalent magnetic network modeling for analyzing working points of PMs in interior permanent magnet machine

NASA Astrophysics Data System (ADS)

Guo, Liyan; Xia, Changliang; Wang, Huimin; Wang, Zhiqiang; Shi, Tingna

2018-05-01

As is well known, the armature current will be ahead of the back electromotive force (back-EMF) under load condition of the interior permanent magnet (PM) machine. This kind of advanced armature current will produce a demagnetizing field, which may make irreversible demagnetization appeared in PMs easily. To estimate the working points of PMs more accurately and take demagnetization under consideration in the early design stage of a machine, an improved equivalent magnetic network model is established in this paper. Each PM under each magnetic pole is segmented, and the networks in the rotor pole shoe are refined, which makes a more precise model of the flux path in the rotor pole shoe possible. The working point of each PM under each magnetic pole can be calculated accurately by the established improved equivalent magnetic network model. Meanwhile, the calculated results are compared with those calculated by FEM. And the effects of d-axis component and q-axis component of armature current, air-gap length and flux barrier size on working points of PMs are analyzed by the improved equivalent magnetic network model.

The use of physical and virtual manipulatives in an undergraduate mechanical engineering (Dynamics) course

NASA Astrophysics Data System (ADS)

Pan, Edward A.

Science, technology, engineering, and mathematics (STEM) education is a national focus. Engineering education, as part of STEM education, needs to adapt to meet the needs of the nation in a rapidly changing world. Using computer-based visualization tools and corresponding 3D printed physical objects may help nontraditional students succeed in engineering classes. This dissertation investigated how adding physical or virtual learning objects (called manipulatives) to courses that require mental visualization of mechanical systems can aid student performance. Dynamics is one such course, and tends to be taught using lecture and textbooks with static diagrams of moving systems. Students often fail to solve the problems correctly and an inability to mentally visualize the system can contribute to student difficulties. This study found no differences between treatment groups on quantitative measures of spatial ability and conceptual knowledge. There were differences between treatments on measures of mechanical reasoning ability, in favor of the use of physical and virtual manipulatives over static diagrams alone. There were no major differences in student performance between the use of physical and virtual manipulatives. Students used the physical and virtual manipulatives to test their theories about how the machines worked, however their actual time handling the manipulatives was extremely limited relative to the amount of time they spent working on the problems. Students used the physical and virtual manipulatives as visual aids when communicating about the problem with their partners, and this behavior was also seen with Traditional group students who had to use the static diagrams and gesture instead. The explanations students gave for how the machines worked provided evidence of mental simulation; however, their causal chain analyses were often flawed, probably due to attempts to decrease cognitive load. Student opinions about the static diagrams and dynamic models varied by type of model (static, physical, virtual), but were generally favorable. The Traditional group students, however, indicated that the lack of adequate representation of motion in the static diagrams was a problem, and wished they had access to the physical and virtual models.

Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder.

PubMed

Schnyer, David M; Clasen, Peter C; Gonzalez, Christopher; Beevers, Christopher G

2017-06-30

Using MRI to diagnose mental disorders has been a long-term goal. Despite this, the vast majority of prior neuroimaging work has been descriptive rather than predictive. The current study applies support vector machine (SVM) learning to MRI measures of brain white matter to classify adults with Major Depressive Disorder (MDD) and healthy controls. In a precisely matched group of individuals with MDD (n =25) and healthy controls (n =25), SVM learning accurately (74%) classified patients and controls across a brain map of white matter fractional anisotropy values (FA). The study revealed three main findings: 1) SVM applied to DTI derived FA maps can accurately classify MDD vs. healthy controls; 2) prediction is strongest when only right hemisphere white matter is examined; and 3) removing FA values from a region identified by univariate contrast as significantly different between MDD and healthy controls does not change the SVM accuracy. These results indicate that SVM learning applied to neuroimaging data can classify the presence versus absence of MDD and that predictive information is distributed across brain networks rather than being highly localized. Finally, MDD group differences revealed through typical univariate contrasts do not necessarily reveal patterns that provide accurate predictive information. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Neonatal blood cultures: effect of delayed entry into the blood culture machine and bacterial concentration on the time to positive growth in a simulated model.

PubMed

Jardine, Luke Anthony; Sturgess, Barbara Ruth; Inglis, Garry Donald Trevor; Davies, Mark William

2009-04-01

To determine if: time from blood culture inoculation to positive growth (total time to positive) and time from blood culture machine entry to positive growth (machine time to positive) is altered by delayed entry into the automated blood culture machine, and if the total time to positive differs by the concentration of organisms inoculated into blood culture bottles. Staphylococcus epidermidis, Escherichia coli and group B beta-haemolytic streptococci were chosen as clinically significant representative organisms. Two concentrations (> or =10 colony-forming units per millilitre and <1 colony-forming units per millilitre) were inoculated into PEDS BacT/Alert blood culture bottles and randomly allocated to one of three delayed automated blood culture machine entry times (30 min/8.5 h/15.5 h). For all organisms at all concentrations, except the Staphylococcus epidermidis, the machine time to positive was significantly decreased by delayed entry. For all organisms at all concentrations, the mean total time to positive significantly increased with increasing delayed entry into the blood culture machine. Higher concentrations of group B beta-haemolytic streptococci and Escherichia coli grew significantly faster than lower concentrations. Bacterial growth in inoculated bottles, stored at room temperature, continues although at a slower rate than in those blood culture bottles immediately entered into the machine. If a blood culture specimen has been stored at room temperature for greater than 15.5 h, the currently allowed safety margin of 36 h (before declaring a result negative) may be insufficient.

Work hours, weight status, and weight-related behaviors: a study of metro transit workers.

PubMed

Escoto, Kamisha H; French, Simone A; Harnack, Lisa J; Toomey, Traci L; Hannan, Peter J; Mitchell, Nathan R

2010-12-20

Associations between hours worked per week and Body Mass Index (BMI), food intake, physical activity, and perceptions of eating healthy at work were examined in a sample of transit workers. Survey data were collected from 1086 transit workers. Participants reported hours worked per week, food choices, leisure-time physical activity and perceptions of the work environment with regard to healthy eating. Height and weight were measured for each participant. Multivariate linear and logistic regressions were conducted to examine associations between work hours and behavioral variables. Associations were examined in the full sample and stratified by gender. Transit workers working in the highest work hour categories had higher BMI and poorer dietary habits, with results differing by gender. Working 50 or more hours per week was associated with higher BMI among men but not women. Additionally, working 50 or more hours per week was significantly associated with higher frequency of accessing cold beverage, cold food, and snack vending machines among men. Working 40 or more hours per week was associated with higher frequency of accessing cold food vending machines among women. Reported frequency of fruit and vegetable intake was highest among women working 50 or more hours per week. Intake of sweets, sugar sweetened beverages, and fast food did not vary with work hours in men or women. Physical activity and perception of ease of eating healthy at work were not associated with work hours in men or women. Long work hours were associated with more frequent use of garage vending machines and higher BMI in transit workers, with associations found primarily among men. Long work hours may increase dependence upon food availability at the worksite, which highlights the importance of availability of healthy food choices.

Work hours, weight status, and weight-related behaviors: a study of metro transit workers

PubMed Central

2010-01-01

Background Associations between hours worked per week and Body Mass Index (BMI), food intake, physical activity, and perceptions of eating healthy at work were examined in a sample of transit workers. Methods Survey data were collected from 1086 transit workers. Participants reported hours worked per week, food choices, leisure-time physical activity and perceptions of the work environment with regard to healthy eating. Height and weight were measured for each participant. Multivariate linear and logistic regressions were conducted to examine associations between work hours and behavioral variables. Associations were examined in the full sample and stratified by gender. Results Transit workers working in the highest work hour categories had higher BMI and poorer dietary habits, with results differing by gender. Working 50 or more hours per week was associated with higher BMI among men but not women. Additionally, working 50 or more hours per week was significantly associated with higher frequency of accessing cold beverage, cold food, and snack vending machines among men. Working 40 or more hours per week was associated with higher frequency of accessing cold food vending machines among women. Reported frequency of fruit and vegetable intake was highest among women working 50 or more hours per week. Intake of sweets, sugar sweetened beverages, and fast food did not vary with work hours in men or women. Physical activity and perception of ease of eating healthy at work were not associated with work hours in men or women. Conclusions Long work hours were associated with more frequent use of garage vending machines and higher BMI in transit workers, with associations found primarily among men. Long work hours may increase dependence upon food availability at the worksite, which highlights the importance of availability of healthy food choices. PMID:21172014

SEGMAG Machines for Marine Electrical Propulsion Systems

DTIC Science & Technology

1978-09-13

78-9B2-SYSTA-Rj P4 SIG•(AG MACHINES VOR MARINE ELECTRICAL PROPULSION SYSTBILS Final Report Submitted to Office of Naval Research R.A. Feranchak, R. B...MACHINES FOR MARINE ELECTRICAL PROPULSION SYSTEMS Final Technical Report Submitted to Office of Naval Research Contract N00014-.77-C-0307 Feranchak, R. A...OF0ANI ZATION NAME AND ADDRESS 0., PROGRAM ELtEMNT.PROJECT, TASK~~.i~ckev ~eiAREA & WORK UNIT NUMBERS Westinghouse Research & Develepment Center 1310

Effect of cutting parameters on strain hardening of nickel–titanium shape memory alloy

NASA Astrophysics Data System (ADS)

Wang, Guijie; Liu, Zhanqiang; Ai, Xing; Huang, Weimin; Niu, Jintao

2018-07-01

Nickel–titanium shape memory alloy (SMA) has been widely used as implant materials due to its good biocompatibility, shape memory property and super-elasticity. However, the severe strain hardening is a main challenge due to cutting force and temperature caused by machining. An orthogonal experiment of nickel–titanium SMA with different milling parameters conditions was conducted in this paper. On the one hand, the effect of cutting parameters on work hardening is obtained. It is found that the cutting speed has the most important effect on work hardening. The depth of machining induced layer and the degree of hardening become smaller with the increase of cutting speed when the cutting speed is less than 200 m min‑1 and then get larger with further increase of cutting speed. The relative intensity of diffraction peak increases as the cutting speed increase. In addition, all of the depth of machining induced layer, the degree of hardening and the relative intensity of diffraction peak increase when the feed rate increases. On the other hand, it is found that the depth of machining induced layer is closely related with the degree of hardening and phase transition. The higher the content of austenite in the machined surface is, the higher the degree of hardening will be. The depth of the machining induced layer increases with the degree of hardening increasing.

Nocturnal 6-hydroxymelatonin sulfate excretion in female workers exposed to magnetic fields

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

Juutilainen, J; Stevens, Richard G.; Anderson, Larry E.

The objective of this study was to determine whether daytime occupational exposure to extremely low frequency magnetic fields (MFs) suppresses nocturnal melatonin production. Sixty female volunteers were recruited. Thirty-nine worked in a garment factory, and 21 office workers served as a reference group. Exposure assessment was based on the type of sewing machine used and MF measurements around each type of machine. Eye-level MF flux density was used to classify the operators to higher (> 1 microT) and lower (0.3-1 microT) exposure categories. A third group of factory workers had diverse MF exposures from other sources. The reference group hadmore » average exposure of about 0.15 microT. Urine samples were collected on Friday and Monday for three consecutive weeks. Melatonin production was assessed as urinary 6-hydroxymelatonin sulfate (6-OHMS) excretion. The ratio of Friday morning/Monday morning 6-OHMS was used to test the hypothesis that melatonin production is suppressed after 4 days of occupational MF exposure with significant recovery during the weekend. Possible chronic suppression of melatonin production was evaluated by studying exposure-related differences in the Friday values by multivariate regression analysis. The Monday/Friday ratios were close to 1.0, suggesting that there is no increase in melatonin production over the weekend. The average 6-OHMS excretion on Friday was lower among the factory workers than in the reference group, but no monotonous dose-response was observed. Multivariate regression analysis identified MF exposure, smoking, and age as significant explanatory variables associated with decreased 6-OHMS excretion.« less

Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

NASA Astrophysics Data System (ADS)

Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

2018-03-01

The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

Recent advances in the development and transfer of machine vision technologies for space

NASA Technical Reports Server (NTRS)

Defigueiredo, Rui J. P.; Pendleton, Thomas

1991-01-01

Recent work concerned with real-time machine vision is briefly reviewed. This work includes methodologies and techniques for optimal illumination, shape-from-shading of general (non-Lambertian) 3D surfaces, laser vision devices and technology, high level vision, sensor fusion, real-time computing, artificial neural network design and use, and motion estimation. Two new methods that are currently being developed for object recognition in clutter and for 3D attitude tracking based on line correspondence are discussed.

Methodology of selecting dozers for lignite open pit mines in Serbia

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

Stojanovic, D.; Ignjatovic, D.; Kovacevic, S.

1996-12-31

Apart from the main production processes (coal and overburden mining, rail conveyors transportation and storage of excavated masses) performed by great-capacity mechanization at open pit mines, numerous and different auxiliary works, that often have crucial influence on both the work efficiency of main equipment and the maintenance of optimum technical conditions of machines and plants covering technological system of open pit, are present. Successful realization of work indispensably requires a proper and adequate selection of auxiliary machines according to their type quantity, capacity, power etc. thus highly respecting specific conditions existing at each and every open pit mine. A dozermore » is certainly the most important and representative auxiliary machine at single open pit mine. It is widely used in numerous works that, in fact, are preconditions for successful work of the main mechanization and consequently the very selection of a dozer ranges among the most important operations when selecting mechanization. This paper presents the methodology of dozers selection when lignite open pit mines are concerned. A mathematical model defining the volume of work required for dozers to perform at open pit mines and consequently the number of necessary dozers was designed. The model underwent testing in practice at big open pit mines and can be used in design of future open pits mines.« less

Producibility Engineering and Planning (PEP)

DTIC Science & Technology

1977-01-01

Materiel System, May 1976. c. Cesare Raimondi, "Estimating Drafting Time - Art , Science , Guess- work", Machine Design, 7 September 1972. d. Current Wage...Comprehensive 8 16 24 32 40 86 45 70 90 80 1/ Cesare Raimondi, "Estimating Drafting Time- Art , Science , Guesswork," Machine Design, September

17. Photocopy of Photograph (From Bethlehem Shipbuilding Ltd., New York, ...

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

17. Photocopy of Photograph (From Bethlehem Shipbuilding Ltd., New York, New York, 1919) COMPOSITE PHOTOGRAPH SHOWING AN EXTERIOR AND INTERIOR VIEW OF THE MACHINE SHOP AND AN INSET OF THE GENERAL MANAGER - Union Iron Works Turbine Machine Shop, 2200 Webster Street, Alameda, Alameda County, CA

V-TECS Guide for Machine Shop (Machinist).

ERIC Educational Resources Information Center

Gregory, Margaret R.; Benson, Robert T.

This curriculum guide is intended to train trade and industrial education students in the hands-on aspects of the occupation of machinist. Included in the guide are course outlines that deal with the following topics: following safety procedures; performing mathematical calculations; designing and planning machine work; performing precision…

Position feedback control system

DOEpatents

Bieg, Lothar F.; Jokiel, Jr., Bernhard; Ensz, Mark T.; Watson, Robert D.

2003-01-01

Disclosed is a system and method for independently evaluating the spatial positional performance of a machine having a movable member, comprising an articulated coordinate measuring machine comprising: a first revolute joint; a probe arm, having a proximal end rigidly attached to the first joint, and having a distal end with a probe tip attached thereto, wherein the probe tip is pivotally mounted to the movable machine member; a second revolute joint; a first support arm serially connecting the first joint to the second joint; and coordinate processing means, operatively connected to the first and second revolute joints, for calculating the spatial coordinates of the probe tip; means for kinematically constraining the articulated coordinate measuring machine to a working surface; and comparator means, in operative association with the coordinate processing means and with the movable machine, for comparing the true position of the movable machine member, as measured by the true position of the probe tip, with the desired position of the movable machine member.

Application of Fuzzy TOPSIS for evaluating machining techniques using sustainability metrics

NASA Astrophysics Data System (ADS)

Digalwar, Abhijeet K.

2018-04-01

Sustainable processes and techniques are getting increased attention over the last few decades due to rising concerns over the environment, improved focus on productivity and stringency in environmental as well as occupational health and safety norms. The present work analyzes the research on sustainable machining techniques and identifies techniques and parameters on which sustainability of a process is evaluated. Based on the analysis these parameters are then adopted as criteria’s to evaluate different sustainable machining techniques such as Cryogenic Machining, Dry Machining, Minimum Quantity Lubrication (MQL) and High Pressure Jet Assisted Machining (HPJAM) using a fuzzy TOPSIS framework. In order to facilitate easy arithmetic, the linguistic variables represented by fuzzy numbers are transformed into crisp numbers based on graded mean representation. Cryogenic machining was found to be the best alternative sustainable technique as per the fuzzy TOPSIS framework adopted. The paper provides a method to deal with multi criteria decision making problems in a complex and linguistic environment.

What makes an automated teller machine usable by blind users?

PubMed

Manzke, J M; Egan, D H; Felix, D; Krueger, H

1998-07-01

Fifteen blind and sighted subjects, who featured as a control group for acceptance, were asked for their requirements for automated teller machines (ATMs). Both groups also tested the usability of a partially operational ATM mock-up. This machine was based on an existing cash dispenser, providing natural speech output, different function menus and different key arrangements. Performance and subjective evaluation data of blind and sighted subjects were collected. All blind subjects were able to operate the ATM successfully. The implemented speech output was the main usability factor for them. The different interface designs did not significantly affect performance and subjective evaluation. Nevertheless, design recommendations can be derived from the requirement assessment. The sighted subjects were rather open for design modifications, especially the implementation of speech output. However, there was also a mismatch of the requirements of the two subject groups, mainly concerning the key arrangement.

Survey and comparison of sleep quality among fixed and changing shift staff in a steel factory in Tehran, Iran.

PubMed

Mohammadian, Farugh; Abbasinia, Marzieh; Rahmani, Abdolrasoul; Monazzam, Mohammad Reza; Asghari, Mehdi; Ahmadnezhad, Iman; Asadi, Ali

2013-01-01

Given the hazardous nature of the work in steel factories and that the staff has to deal with hazardous equipment and machines, improper sleep quality and drowsiness among the works tackles performance and boosts rate of job accidents. This study is aimed to survey the quality of sleep and sleepiness status and the pertinent factors among the workers in a rolling mill and a steel production company in Tehran, Iran. In a Cross-Sectional study 2011, 180 workers were selected randomly from a rolling mill and a steel production company in Tehran. A questionnaire was designed to collect demographic data and variables of work condition. Pitersborg's sleep quality questionnaire was used to survey quality and problems of Participants' sleep. Epworth Sleepiness questionnaire was used to deals with sleepiness during work, studying, watching TV, or during time spent in public. Average score of sleep quality for the fixed shift staff and changing shift staff were 7.5±2.82 and 8.49±2.95 respectively. Surveys of sleep quality for the two groups of the participants based on T-test showed a significant difference between the two groups so that the changing shift staff group suffered poorer sleep quality (p=0.03). Comparison of average drowsiness scores between the two groups of participants based on Mann-Whitney test showed no significant difference (p>0.005). Chi square test showed a significant difference between severity of drowsiness and type of working shift (p =0.028 and 0.009). Staff in revolving shifts suffers poor sleep quality comparing with staff with fixed working shift. Moreover, type of working shift greatly affects severity of drowsiness as staff at different work shift experienced different level of sleepiness. It is essential to survey sleep disorder of the staff in the industry and pay more emphasis on sleep disorder epidemic in other fields of industry.

Protocol Design Challenges in the Detection of Awareness in Aware Subjects Using EEG Signals.

PubMed

Henriques, J; Gabriel, D; Grigoryeva, L; Haffen, E; Moulin, T; Aubry, R; Pazart, L; Ortega, J-P

2016-10-01

Recent studies have evidenced serious difficulties in detecting covert awareness with electroencephalography-based techniques both in unresponsive patients and in healthy control subjects. This work reproduces the protocol design in two recent mental imagery studies with a larger group comprising 20 healthy volunteers. The main goal is assessing if modifications in the signal extraction techniques, training-testing/cross-validation routines, and hypotheses evoked in the statistical analysis, can provide solutions to the serious difficulties documented in the literature. The lack of robustness in the results advises for further search of alternative protocols more suitable for machine learning classification and of better performing signal treatment techniques. Specific recommendations are made using the findings in this work. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Multi-parameter monitoring of electrical machines using integrated fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Fabian, Matthias; Hind, David; Gerada, Chris; Sun, Tong; Grattan, Kenneth T. V.

2017-04-01

In this paper a sensor system for multi-parameter electrical machine condition monitoring is reported. The proposed FBG-based system allows for the simultaneous monitoring of machine vibration, rotor speed and position, torque, spinning direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution reduces the component count of conventional sensor systems, i.e., all 48 sensing elements are contained within the machine operated by a single sensing interrogation unit. In this work, the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

Impact resistance of guards on grinding machines.

PubMed

Mewes, Detlef; Mewes, Olaf; Herbst, Peter

2011-01-01

Guards on machine tools are meant to protect persons from injuries caused by parts ejected with high kinetic energy from the machine's working zone. With respect to stationary grinding machines, Standard No. EN 13218:2002, therefore, specifies minimum wall thicknesses for guards. These values are mainly based on estimations and experience instead of systematic experimental investigations. This paper shows to what extent simple impact tests with standardizable projectiles can be used as basis for the evaluation of the impact resistance of guards, provided that not only the kinetic energy of the projectiles used but also, among others, their geometry corresponds to the abrasive product fragments to be expected.

Neck-Shoulder Pain and Work Status among Former Sewing Machine Operators: A 14-year Follow-up Study.

PubMed

Jakobsen, Emma Lise Thorlund; Biering, Karin; Kærgaard, Anette; Andersen, Johan Hviid

2018-03-01

Purpose A total of 243 Danish female sewing machine operators lost their jobs in 1996 because of outsourcing. The aim was to investigate the employment status during follow-up from 1996 to 2008, and to estimate to what extent former neck-shoulder pain had an impact on later work participation. Methods Assessment of neck-shoulder pain was based on questionnaires completed in 1994. The Danish Register-Based Evaluation of Marginalization (DREAM) register was used to describe employment status during the follow-up period. Register data were explored by sequence analyses and graphics, and the association between neck-shoulder pain and work participation was analyzed by logistic regression analysis. Results In all, 987 working years were lost during follow-up, and a sequence index plot revealed interrupted and heterogeneous courses of incomes. The odds ratio between neck and shoulder pain and a work participation score less than 75% was 1.49 (95% CI 0.84-2.67). Conclusions After outsourcing of the textile industry, the former sewing machine operators had decreased work participation and frequent transitions between different income types. Previous neck-shoulder pain tended to be associated with poor work participation. The results suggest that increased attention should be to given to dismissed workers from other industries that become outsourced, especially unskilled workers with similar work-related health limitations. Additionally, we concluded that time-to-event measures in research involving employment status are insufficient because of the many transitions that take place in working life.

Verbal messages strengthen bench press efficacy.

PubMed

Wise, James B; Posner, Amy E; Walker, Gretchen L

2004-02-01

This study examined the effects of verbal messages on bench press efficacy: the confidence to lift progressively heavier weights for 1 repetition. Thirty-two women who had not bench pressed within the previous 18 months were assigned to 1 of 2 groups and exposed to 2 sources of efficacy information. First, subjects in both groups performed 10 repetitions on a fixed movement, vertical bench press machine and completed the bench press efficacy scale. Next, each group received 1 of 2 possible verbal messages. Both messages included the speaker's strength training qualifications. In addition, one message conveyed specific performance feedback while the other contained more general information. Then efficacy was measured again. Results indicated both messages strengthened efficacy. Strength professionals who work one-on-one with novice women should: (a) make sure lifters are aware of their professional qualifications, (b) provide specific feedback, and (c) profess their beliefs in the lifters' abilities to perform the exercises.

Culture cultivating culture: the four products of the meaning-made world.

PubMed

Carriere, Kevin R

2014-09-01

Culture, in a semiotic cultural psychology, is defined from the viewpoint of cultivation--the meaning making processes that give meaning to the world (Valsiner 2000, 2007a). However, the individual is not simply a process-machine in an empty world--there are both the external outcomes of meaning making (individual and group based) as well as the collective influence on the cultivation process. I argue to examine the cultivation process more completely, one must look at these external influences that catalyze future cultivation processes. By examining the power of the external (environmental Umwelten) and group-internal (myths, morals), a much greater understanding of the behavior of individuals can be accomplished beyond examining the individual's process of meaning making. Further work into examining the objects that affectively activate the individual as well as group action and meaning making is called for and examples of such studies are given.

Contemporary machine learning: techniques for practitioners in the physical sciences

NASA Astrophysics Data System (ADS)

Spears, Brian

2017-10-01

Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Mechanization for Optimal Landscape Reclamation

NASA Astrophysics Data System (ADS)

Vondráčková, Terezie; Voštová, Věra; Kraus, Michal

2017-12-01

Reclamation is a method of ultimate utilization of land adversely affected by mining or other industrial activity. The paper explains the types of reclamation and the term “optimal reclamation”. Technological options of the long-lasting process of mine dumps reclamation starting with the removal of overlying rocks, transport and backfilling up to the follow-up remodelling of the mine dumps terrain. Technological units and equipment for stripping flow division. Stripping flow solution with respect to optimal reclamation. We recommend that the application of logistic chains and mining simulation with follow-up reclamation to open-pit mines be used for the implementation of optimal reclamation. In addition to a database of local heterogeneities of the stripped soil and reclaimed land, the flow of earths should be resolved in a manner allowing the most suitable soil substrate to be created for the restoration of agricultural and forest land on mine dumps. The methodology under development for the solution of a number of problems, including the geological survey of overlying rocks, extraction of stripping, their transport and backfilling in specified locations with the follow-up deployment of goal-directed reclamation. It will make possible to reduce the financial resources needed for the complex process chain by utilizing GIS, GPS and DGPS technologies, logistic tools and synergistic effects. When selecting machines for transport, moving and spreading of earths, various points of view and aspects must be taken into account. Among such aspects are e.g. the kind of earth to be operated by the respective construction machine, the kind of work activities to be performed, the machine’s capacity, the option to control the machine’s implement and economic aspects and clients’ requirements. All these points of view must be considered in the decision-making process so that the selected machine is capable of executing the required activity and that the use of an unsuitable machine is eliminated as it would result in a delay and increase in the project costs. Therefore, reclamation always includes extensive earth-moving work activities restoring the required relief of the land being reclaimed. Using the earth-moving machine capacity, the kind of soil in mine dumps, the kind of the work activity performed and the machine design, a SW application has been developed that allows the most suitable machine for the respective work technology to be selected with a view to preparing the land intended for reclamation.

AC Loss Analysis of MgB2-Based Fully Superconducting Machines

NASA Astrophysics Data System (ADS)

Feddersen, M.; Haran, K. S.; Berg, F.

2017-12-01

Superconducting electric machines have shown potential for significant increase in power density, making them attractive for size and weight sensitive applications such as offshore wind generation, marine propulsion, and hybrid-electric aircraft propulsion. Superconductors exhibit no loss under dc conditions, though ac current and field produce considerable losses due to hysteresis, eddy currents, and coupling mechanisms. For this reason, many present machines are designed to be partially superconducting, meaning that the dc field components are superconducting while the ac armature coils are conventional conductors. Fully superconducting designs can provide increases in power density with significantly higher armature current; however, a good estimate of ac losses is required to determine the feasibility under the machines intended operating conditions. This paper aims to characterize the expected losses in a fully superconducting machine targeted towards aircraft, based on an actively-shielded, partially superconducting machine from prior work. Various factors are examined such as magnet strength, operating frequency, and machine load to produce a model for the loss in the superconducting components of the machine. This model is then used to optimize the design of the machine for minimal ac loss while maximizing power density. Important observations from the study are discussed.

Operation of micro and molecular machines: a new concept with its origins in interface science.

PubMed

Ariga, Katsuhiko; Ishihara, Shinsuke; Izawa, Hironori; Xia, Hong; Hill, Jonathan P

2011-03-21

A landmark accomplishment of nanotechnology would be successful fabrication of ultrasmall machines that can work like tweezers, motors, or even computing devices. Now we must consider how operation of micro- and molecular machines might be implemented for a wide range of applications. If these machines function only under limited conditions and/or require specialized apparatus then they are useless for practical applications. Therefore, it is important to carefully consider the access of functionality of the molecular or nanoscale systems by conventional stimuli at the macroscopic level. In this perspective, we will outline the position of micro- and molecular machines in current science and technology. Most of these machines are operated by light irradiation, application of electrical or magnetic fields, chemical reactions, and thermal fluctuations, which cannot always be applied in remote machine operation. We also propose strategies for molecular machine operation using the most conventional of stimuli, that of macroscopic mechanical force, achieved through mechanical operation of molecular machines located at an air-water interface. The crucial roles of the characteristics of an interfacial environment, i.e. connection between macroscopic dimension and nanoscopic function, and contact of media with different dielectric natures, are also described.

The Birth of Lepton Colliders in Italy and the United States

NASA Astrophysics Data System (ADS)

Paris, Elizabeth

2003-04-01

In 1960 the highest center-of-mass energies in particle physics were being achieved via proton synchrotrons utilizing stationary targets. However, efforts were already underway to challenge this hegemony. In addition to Soviet work in Novosibirsk, groups at Stanford University in California and at the Frascati National Laboratories near Rome each had begun original investigation towards one particular type of challenger: colliding beam storage rings. For the group in California, the accomplishment involved creating the potential for feasible experiments. The energetic advantages of the colliding beam configuration had long been accepted - together with its impossibility for realization. The builders of the Princeton-Stanford machine feel that creating usable beams and a reasonable reaction rate is what stood between this concept and its glorious future. For the European builders of AdA, however, the beauty emerges from recognizing the enormous potential inherent in electron-positron annihilations. At least as important for the rise of electron-positron colliders, though, is the role of both of these projects as cultural firsts -- as places where particular sets of physicists got their feet wet associating with beams and beam problems and with the many individuals who were addressing beam problems. The Princeton-Stanford Collider provided experience which its builders would use to move on, functioning as both a technological and political platform for creating what would eventually become SPEAR. For the Roman group, the pursuit of AdA encouraged investigation which applied equally well to their next machine, Adone.

Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning.

PubMed

Davatzikos, Christos

2016-10-01

The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain parcellation, voxel-based morphometric analyses, and multivariate pattern analyses using machine learning approaches. The evolution of these 3 types of analyses over the years has overcome many challenges. We present the evolution of our work in these 3 directions, which largely follows the evolution of this field. We discuss the progression from single-atlas, single-registration brain parcellation work to current ensemble-based parcellation; from relatively basic mass-univariate t-tests to optimized regional pattern analyses combining deformations and residuals; and from basic application of support vector machines to generative-discriminative formulations of multivariate pattern analyses, and to methods dealing with heterogeneity of neuroanatomical patterns. We conclude with discussion of some of the future directions and challenges. Copyright © 2016. Published by Elsevier B.V.

Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning

PubMed Central

Davatzikos, Christos

2017-01-01

The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain parcellation, voxel-based morphometric analyses, and multivariate pattern analyses using machine learning approaches. The evolution of these 3 types of analyses over the years has overcome many challenges. We present the evolution of our work in these 3 directions, which largely follows the evolution of this field. We discuss the progression from single-atlas, single-registration brain parcellation work to current ensemble-based parcellation; from relatively basic mass-univariate t-tests to optimized regional pattern analyses combining deformations and residuals; and from basic application of support vector machines to generative-discriminative formulations of multivariate pattern analyses, and to methods dealing with heterogeneity of neuroanatomical patterns. We conclude with discussion of some of the future directions and challenges. PMID:27514582

Learning algorithms for human-machine interfaces.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2009-05-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore-Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction.

Learning Algorithms for Human–Machine Interfaces

PubMed Central

Fishbach, Alon; Mussa-Ivaldi, Ferdinando A.

2012-01-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore–Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction. PMID:19203886

Finite element analysis of chip formation usingale method

NASA Astrophysics Data System (ADS)

Jayaprakash, V.

2017-05-01

In recent times, many studies made in FEM on plain isotropic metal plate formulation. The stress analysis plays the significant role in the stability of structural safety and system. The stress and distortion estimation is very helpful for designing and manufacturing product well. Usually the residual stress and plastic strain determine the fatigue life of structure, it also plays the significant role in designing and choosing material. When the load magnitude increases the crack starts to form, decreasing the work load and the residual stress reduces the damage of the metal. The manufacturing process is a key parameter in process and forming the part of any system. However, machining operation involves complex thing like hot development, material property and other estimates based on transition of the plastic strain and residual stress. The reduction of residual stress plays the complexity role in the finite element study. This paper deals with the manufacturing process with less residual stress and strain. The results shows that, by applying the ALE method in machining we can reduce the load on the work piece hence the life type of the work piece can be increased. We also investigate the cutting tool wear and there efficiency since it is a essential machine member in fabrication technology. ABAQUS platform used to solve the machining operation

Noise characteristics of grass-trimming machine engines and their effect on operators.

PubMed

Mallick, Zulquernain; Badruddin, Irfan Anjum; Khaleed Hussain, M T; Salman Ahmed, N J; Kanesan, Jeevan

2009-01-01

Over the last few years, interaction of humans with noisy power-driven agricultural tools and its possible adverse after effects have been realized. Grass-trimmer engine is the primary source of noise and the use of motorized cutter, spinning at high speed, is the secondary source of noise to which operators are exposed. In the present study, investigation was carried out to determine the effect of two types of grass-trimming machine engines (SUM 328 SE and BG 328) noise on the operators in real working environment. It was found that BG-328 and SUM-328 SE produced high levels of noise, of the order of 100 and 105 dB(A), respectively, to which operators are exposed while working. It was also observed that situation aggravates when a number of operators simultaneously operate resulting in still higher levels of noise. Operators should be separated 15 meters from each other in order to avoid the combined level of noise exposure while working with these machines. It was found that SPL, of the grass-trimmer machine engines (BG-328 and SUM-328 SE), were higher than the limit of noise recommended by ISO, NIOSH, and OSHA for an 8-hour workday. Such a high level of noise exposure may cause physiological and psychological problems to the operators in long run.

Machine Learning Techniques for Stellar Light Curve Classification

NASA Astrophysics Data System (ADS)

Hinners, Trisha A.; Tat, Kevin; Thorp, Rachel

2018-07-01

We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB of Kepler light curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature engineering approaches. Studies using machine learning in the field have been primarily done on simulated data, making our study one of the first to use real light-curve data for machine learning approaches. We tuned our data using previous work with simulated data as a template and achieved mixed results between the two approaches. Representation learning using a long short-term memory recurrent neural network produced no successful predictions, but our work with feature engineering was successful for both classification and regression. In particular, we were able to achieve values for stellar density, stellar radius, and effective temperature with low error (∼2%–4%) and good accuracy (∼75%) for classifying the number of transits for a given star. The results show promise for improvement for both approaches upon using larger data sets with a larger minority class. This work has the potential to provide a foundation for future tools and techniques to aid in the analysis of astrophysical data.

Task-Oriented, Naturally Elicited Speech (TONE) Database for the Force Requirements Expert System, Hawaii (FRESH)

DTIC Science & Technology

1988-09-01

Group Subgroup Command and control; Computational linguistics; expert system voice recognition; man- machine interface; U.S. Government 19 Abstract...simulates the characteristics of FRESH on a smaller scale. This study assisted NOSC in developing a voice-recognition, man- machine interface that could...scale. This study assisted NOSC in developing a voice-recogni- tion, man- machine interface that could be used with TONE and upgraded at a later date

Design of conveyor type machine with numerical control for manufacturing of extrusion thermoplastic thread

NASA Astrophysics Data System (ADS)

Gorbunova, T. N.; Koltunov, I. I.; Tumanova, M. B.

2018-05-01

The article is devoted to the development of a model and control program for a 3D printer working based on extrusion technology. The article contains descriptions of all components of the machine and blocks of the interface of the control program.

Mixed-Initiative Clustering

ERIC Educational Resources Information Center

Huang, Yifen

2010-01-01

Mixed-initiative clustering is a task where a user and a machine work collaboratively to analyze a large set of documents. We hypothesize that a user and a machine can both learn better clustering models through enriched communication and interactive learning from each other. The first contribution or this thesis is providing a framework of…

Spin Cycle

ERIC Educational Resources Information Center

Casey, Dick

2005-01-01

Laundry equipment is an investment, and the investment should be protected. To keep laundry equipment working at an optimum level, schools must maintain their machines. This article offers preventive-maintenance tips for washing machines and dryers. To prevent faucets from binding up, close and reopen the water faucets. This also is a great way to…

CPAP Machines: Tips for Avoiding 10 Common Problems

MedlinePlus

... closed and reduce the air leak if you wear a nasal mask. A full-face-mask-style device that covers your mouth and nose also may work well for you. A CPAP-heated humidifier that attaches to the air pressure machine also may help. It's normal to sometimes wake ...

Development of German-English Machine Translation System.

ERIC Educational Resources Information Center

Lehmann, Winifred P.; Stachowitz, Rolf

This report documents efforts over a five-month period toward completion of a pilot system for machine translation of German scientific and technical literature into English. The report is divided into three areas: grammar formalism, programming, and linguistics. Work on grammar formalism concentrated mainly on increasing the power of the…

MACHINE TRANSLATION RESEARCH DURING THE PAST TWO YEARS.

ERIC Educational Resources Information Center

LEHMANN, W.P.

THE AUTHOR RECOUNTS THE RISE IN IMPORTANCE OF MACHINE TRANSLATION, WHICH TOGETHER WITH LANGUAGE LEARNING AND TEACHING COMPRISE THE MAJOR FIELDS OF APPLIED LINGUISTICS. MUCH OF THE RECENT THEORETICAL WORK ON LANGUAGE DEALS WITH THE PROBLEM OF THE RELATIONSHIP BETWEEN THE SURFACE SYNTACTIC STRUCTURE OF LANGUAGE AND THE UNDERLYING STRUCTURE. THE…

National Apprenticeship and Training Standards for Vending Machine Mechanics.

ERIC Educational Resources Information Center

Employment and Training Administration (DOL), Washington, DC.

This booklet contains national standards for apprentices in vending machine mechanics. The main topic of the booklet, Provisions of Standards, includes the following: definitions of terms used in the booklet, apprenticeship qualifications, a statement on equal opportunity employment, explanation of probation, hours of work, credit for previous…

Machine Shop I. Oklahoma Trade and Industrial Education.

ERIC Educational Resources Information Center

Dunn, James

Designed to provide the basic knowledge and hands-on skills necessary to prepare job-ready machinist trainees, these instructional materials focus on the following areas of trade and industrial education: orientation, basic and related technology, hand and bench work, and power saws and drilling machines. Suitable for use in secondary,…

The Factory of the Future

NASA Technical Reports Server (NTRS)

Byman, J. E.

1985-01-01

A brief history of aircraft production techniques is given. A flexible machining cell is then described. It is a computer controlled system capable of performing 4-axis machining part cleaning, dimensional inspection and materials handling functions in an unmanned environment. The cell was designed to: allow processing of similar and dissimilar parts in random order without disrupting production; allow serial (one-shipset-at-a-time) manufacturing; reduce work-in-process inventory; maximize machine utilization through remote set-up; maximize throughput and minimize labor.

High Speed Turbo-Generator: Test Stand Simulator Including Turbine Engine Emulator

DTIC Science & Technology

2010-07-30

15% Shaft Power 4% 8% Our model of the six-phase synchronous machine was based on work by Schiferl and Ong [1]. The six-phase synchronous machine is...develop and submit to ONR a follow-on proposal to address these open issues. 27 REFERENCES [1] R. F. Schiferl and C. M. Ong, "Six phase...at 32 References [Al] R. F. Schiferl and C. M. Ong, "Six phase synchronous machine with ac and dc stator connections, Part I: Equivalent Circuit

Unorganized machines for seasonal streamflow series forecasting.

PubMed

Siqueira, Hugo; Boccato, Levy; Attux, Romis; Lyra, Christiano

2014-05-01

Modern unorganized machines--extreme learning machines and echo state networks--provide an elegant balance between processing capability and mathematical simplicity, circumventing the difficulties associated with the conventional training approaches of feedforward/recurrent neural networks (FNNs/RNNs). This work performs a detailed investigation of the applicability of unorganized architectures to the problem of seasonal streamflow series forecasting, considering scenarios associated with four Brazilian hydroelectric plants and four distinct prediction horizons. Experimental results indicate the pertinence of these models to the focused task.

Volumetric Verification of Multiaxis Machine Tool Using Laser Tracker

PubMed Central

Aguilar, Juan José

2014-01-01

This paper aims to present a method of volumetric verification in machine tools with linear and rotary axes using a laser tracker. Beyond a method for a particular machine, it presents a methodology that can be used in any machine type. Along this paper, the schema and kinematic model of a machine with three axes of movement, two linear and one rotational axes, including the measurement system and the nominal rotation matrix of the rotational axis are presented. Using this, the machine tool volumetric error is obtained and nonlinear optimization techniques are employed to improve the accuracy of the machine tool. The verification provides a mathematical, not physical, compensation, in less time than other methods of verification by means of the indirect measurement of geometric errors of the machine from the linear and rotary axes. This paper presents an extensive study about the appropriateness and drawbacks of the regression function employed depending on the types of movement of the axes of any machine. In the same way, strengths and weaknesses of measurement methods and optimization techniques depending on the space available to place the measurement system are presented. These studies provide the most appropriate strategies to verify each machine tool taking into consideration its configuration and its available work space. PMID:25202744