Hybrid machining processes perspectives on machining and finishing

CERN Document Server

Gupta, Kapil; Laubscher, R F

2016-01-01

This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

The Hegelian Notion of Progress and its Applicability in Critical Philosophy

DEFF Research Database (Denmark)

Hansen, Ejvind

2009-01-01

In this paper I discuss the relevance of the Hegelian notion of progress in relation to problems in present-day discussions of critical theory. I discuss Honneth’s attempt to maintain the Hegelian notion of progress without subscribing to its metaphysical foundations. I argue that Honneth’s strat...... solving conflicts....

Big Data Analytics and Machine Intelligence Capability Development at NASA Langley Research Center: Strategy, Roadmap, and Progress

Science.gov (United States)

Ambur, Manjula Y.; Yagle, Jeremy J.; Reith, William; McLarney, Edward

2016-01-01

In 2014, a team of researchers, engineers and information technology specialists at NASA Langley Research Center developed a Big Data Analytics and Machine Intelligence Strategy and Roadmap as part of Langley's Comprehensive Digital Transformation Initiative, with the goal of identifying the goals, objectives, initiatives, and recommendations need to develop near-, mid- and long-term capabilities for data analytics and machine intelligence in aerospace domains. Since that time, significant progress has been made in developing pilots and projects in several research, engineering, and scientific domains by following the original strategy of collaboration between mission support organizations, mission organizations, and external partners from universities and industry. This report summarizes the work to date in Data Intensive Scientific Discovery, Deep Content Analytics, and Deep Q&A projects, as well as the progress made in collaboration, outreach, and education. Recommendations for continuing this success into future phases of the initiative are also made.

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

Science.gov (United States)

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential.

Science.gov (United States)

Bogdan, Ryan; Salmeron, Betty Jo; Carey, Caitlin E; Agrawal, Arpana; Calhoun, Vince D; Garavan, Hugh; Hariri, Ahmad R; Heinz, Andreas; Hill, Matthew N; Holmes, Andrew; Kalin, Ned H; Goldman, David

2017-08-01

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology. Copyright © 2017 Society of Biological Psychiatry. All rights reserved.

The influence of critical thinking skills on performance and progression in a pre-registration nursing program.

Science.gov (United States)

Pitt, Victoria; Powis, David; Levett-Jones, Tracy; Hunter, Sharyn

2015-01-01

The importance of developing critical thinking skills in preregistration nursing students is recognized worldwide. Yet, there has been limited exploration of how students' critical thinking skill scores on entry to pre-registration nursing education influence their academic and clinical performance and progression. The aim of this study was to: i) describe entry and exit critical thinking scores of nursing students enrolled in a three year bachelor of nursing program in Australia in comparison to norm scores; ii) explore entry critical thinking scores in relation to demographic characteristics, students' performance and progression. This longitudinal correlational study used the Health Sciences Reasoning Test (HSRT) to measure critical thinking skills in a sample (n=134) of students, at entry and exit (three years later). A one sample t-test was used to determine if differences existed between matched student critical thinking scores between entry and exit points. Academic performance, clinical performance and progression data were collected and correlations with entry critical thinking scores were examined. There was a significant relationship between critical thinking scores, academic performance and students' risk of failing, especially in the first semester of study. Critical thinking scores were predictive of program completion within three years. The increase in critical thinking scores from entry to exit was significant for the 28 students measured. In comparison to norm scores, entry level critical thinking scores were significantly lower, but exit scores were comparable. Critical thinking scores had no significant relationship to clinical performance. Entry critical thinking scores significantly correlate to academic performance and predict students risk of course failure and ability to complete a nursing degree in three years. Students' critical thinking scores are an important determinant of their success and as such can inform curriculum development and

A survey on queues in machining system: Progress from 2010 to 2017

Directory of Open Access Journals (Sweden)

Shekhar C.

2017-01-01

Full Text Available The aim of the present article is to give a historical survey of some important research works related to queues in machining system since 2010. Queues of failed machines in machine repairing problem occur due to the failure of machines at random in the manufacturing industries, where different jobs are performed on machining stations. Machines are subject to failure what may result in significant loss of production, revenue, or goodwill. In addition to the references on queues in machining system, which is also called `Machine Repair Problem' (MRP or `Machine Interference Problem' (MIP, a meticulous list of books and survey papers is also prepared so as to provide a detailed catalog for understanding the research in queueing domain. We have classified the relevant literature according to a year of publishing, methodological, and modeling aspects. The author(s hope that this survey paper could be of help to learners contemplating research on queueing domain.

Advances in Machine Technology.

Science.gov (United States)

Clark, William R; Villa, Gianluca; Neri, Mauro; Ronco, Claudio

2018-01-01

Continuous renal replacement therapy (CRRT) machines have evolved into devices specifically designed for critically ill over the past 40 years. In this chapter, a brief history of this evolution is first provided, with emphasis on the manner in which changes have been made to address the specific needs of the critically ill patient with acute kidney injury. Subsequently, specific examples of technology developments for CRRT machines are discussed, including the user interface, pumps, pressure monitoring, safety features, and anticoagulation capabilities. © 2018 S. Karger AG, Basel.

Machine Translation in Post-Contemporary Era

Science.gov (United States)

Lin, Grace Hui Chin

2010-01-01

This article focusing on translating techniques via personal computer or laptop reports updated artificial intelligence progresses before 2010. Based on interpretations and information for field of MT [Machine Translation] by Yorick Wilks' book, "Machine Translation, Its scope and limits," this paper displays understandable theoretical frameworks…

A Peer-Reviewed Journal about Machine Research

OpenAIRE

Cox, G; Ganesh, MI; Gil-Fournier, A; Herrie, MB; Hill, J; House, B; Jones, N; Skinner, S; Young, D; Anon

2017-01-01

Edited by Christian Ulrik Andersen and Geoff Cox This publication is about MACHINE RESEARCH – research on machines, research with machines, and research as a machine. It thus explores machinic perspectives to suggest a situation where the humanities are put into a critical perspective by machine driven ecologies, ontologies and epistemologies of thinking and acting. It aims to engage research and artistic practice that takes into account the new materialist conditions implied by nonhuman t...

Human-machine cooperation: a solution for life-critical systems?

Science.gov (United States)

Millot, Patrick; Boy, Guy A

2012-01-01

Decision-making plays an important role in life-critical systems. It entails cognitive functions such as monitoring, as well as fault prevention and recovery. Three kinds of objectives are typically considered: safety, efficiency and comfort. People involved in the control and management of such systems provide two kinds of contributions: positive with their unique involvement and capacity to deal with the unexpected; and negative with their ability to make errors. In the negative view, people are the problem and need to be supervised by regulatory systems in the form of operational constraints or by design. In the positive view, people are the solution and lead the game; they are decision-makers. The former view also deals with error resistance, and the latter with error tolerance, which, for example, enables cooperation between people and decision support systems (DSS). In the real life, both views should be considered with respect to appropriate situational factors, such as time constraints and very dangerous environments. This is known as function allocation between people and systems. This paper presents a possibility to reconcile both approaches into a joint human-machine organization, where the main dimensioning factors are safety and complexity. A framework for cooperative and fault tolerant systems is proposed, and illustrated by an example in Air Traffic Control.

Investigation of the Machining Stability of a Milling Machine with Hybrid Guideway Systems

Directory of Open Access Journals (Sweden)

Jui-Pin Hung

2016-03-01

Full Text Available This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

Histone Demethylase RBP2 Is Critical for Breast Cancer Progression and Metastasis

Directory of Open Access Journals (Sweden)

Jian Cao

2014-03-01

Full Text Available Metastasis is a major clinical challenge for cancer treatment. Emerging evidence suggests that aberrant epigenetic modifications contribute significantly to tumor formation and progression. However, the drivers and roles of such epigenetic changes in tumor metastasis are still poorly understood. Using bioinformatic analysis of human breast cancer gene-expression data sets, we identified histone demethylase RBP2 as a putative mediator of metastatic progression. By using both human breast cancer cells and genetically engineered mice, we demonstrated that RBP2 is critical for breast cancer metastasis to the lung in multiple in vivo models. Mechanistically, RBP2 promotes metastasis as a pleiotropic positive regulator of many metastasis genes, including TNC. In addition, RBP2 loss suppresses tumor formation in MMTV-neu transgenic mice. These results suggest that therapeutic targeting of RBP2 is a potential strategy for inhibition of tumor progression and metastasis.

Research on the proficient machine system. Theoretical part; Jukutatsu machine system no chosa kenkyu. Rironhen

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-03-01

The basic theory of the proficient machine system to be developed was studied. Important proficient techniques in manufacturing industries are becoming extinct because of insufficient succession to next generation. The proficient machine system was proposed to cope with such situation. This machine system includes the mechanism for progress and evolution of techniques and sensibilities to be adaptable to environmental changes by learning and recognizing various motions such as work and process. Consequently, the basic research fields are composed of thought, learning, perception and action. This machine requires not only deigned fixed functions but also introduction of the same proficient concept as human being to be adaptable to changes in situation, purpose, time and machine`s complexity. This report explains in detail the basic concept, system principle, approaching procedure and practical elemental technologies of the proficient machine system, and also describes the future prospect. 133 refs., 110 figs., 7 tabs.

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

Science.gov (United States)

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

An Exploratory Study of the Critical Factors Affecting the Acceptability of Automated Teller Machine (ATM) in Nigeria

OpenAIRE

Olusegun Folorunso; Oluwafunmilayo Ayobami Ateji; Gabriel Oludare Awe

2010-01-01

This paper uses the Technology Acceptance Model (TAM) as a basis for studying critical factors that affects the acceptability of Automated Teller Machine (ATM) in Nigeria. Questionnaire approach was used with the respondents predominantly between 20-29 years old. Factor analysis was used to test which of the factors are the main factors affecting the adoption of the technology in Nigeria. It was discovered that the major factors affecting people’s intention to accept ATM are the security issu...

Brain-Machine Interface control of a robot arm using actor-critic rainforcement learning.

Science.gov (United States)

Pohlmeyer, Eric A; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline; Sanchez, Justin C

2012-01-01

Here we demonstrate how a marmoset monkey can use a reinforcement learning (RL) Brain-Machine Interface (BMI) to effectively control the movements of a robot arm for a reaching task. In this work, an actor-critic RL algorithm used neural ensemble activity in the monkey's motor cortext to control the robot movements during a two-target decision task. This novel approach to decoding offers unique advantages for BMI control applications. Compared to supervised learning decoding methods, the actor-critic RL algorithm does not require an explicit set of training data to create a static control model, but rather it incrementally adapts the model parameters according to its current performance, in this case requiring only a very basic feedback signal. We show how this algorithm achieved high performance when mapping the monkey's neural states (94%) to robot actions, and only needed to experience a few trials before obtaining accurate real-time control of the robot arm. Since RL methods responsively adapt and adjust their parameters, they can provide a method to create BMIs that are robust against perturbations caused by changes in either the neural input space or the output actions they generate under different task requirements or goals.

Machine-to-machine communications architectures, technology, standards, and applications

CERN Document Server

Misic, Vojislav B

2014-01-01

With the number of machine-to-machine (M2M)-enabled devices projected to reach 20 to 50 billion by 2020, there is a critical need to understand the demands imposed by such systems. Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications offers rigorous treatment of the many facets of M2M communication, including its integration with current technology.Presenting the work of a different group of international experts in each chapter, the book begins by supplying an overview of M2M technology. It considers proposed standards, cutting-edge applications, architectures, and traffic modeling and includes case studies that highlight the differences between traditional and M2M communications technology.Details a practical scheme for the forward error correction code designInvestigates the effectiveness of the IEEE 802.15.4 low data rate wireless personal area network standard for use in M2M communicationsIdentifies algorithms that will ensure functionality, performance, reliability, ...

Improving the reliability of stator insulation system in rotating machines

International Nuclear Information System (INIS)

Gupta, G.K.; Sedding, H.G.; Culbert, I.M.

1997-01-01

Reliable performance of rotating machines, especially generators and primary heat transport pump motors, is critical to the efficient operation on nuclear stations. A significant number of premature machine failures have been attributed to the stator insulation problems. Ontario Hydro has attempted to assure the long term reliability of the insulation system in critical rotating machines through proper specifications and quality assurance tests for new machines and periodic on-line and off-line diagnostic tests on machines in service. The experience gained over the last twenty years is presented in this paper. Functional specifications have been developed for the insulation system in critical rotating machines based on engineering considerations and our past experience. These specifications include insulation stress, insulation resistance and polarization index, partial discharge levels, dissipation factor and tip up, AC and DC hipot tests. Voltage endurance tests are specified for groundwall insulation system of full size production coils and bars. For machines with multi-turn coils, turn insulation strength for fast fronted surges in specified and verified through tests on all coils in the factory and on samples of finished coils in the laboratory. Periodic on-line and off-line diagnostic tests were performed to assess the condition of the stator insulation system in machines in service. Partial discharges are measured on-line using several techniques to detect any excessive degradation of the insulation system in critical machines. Novel sensors have been developed and installed in several machines to facilitate measurements of partial discharges on operating machines. Several off-line tests are performed either to confirm the problems indicated by the on-line test or to assess the insulation system in machines which cannot be easily tested on-line. Experience with these tests, including their capabilities and limitations, are presented. (author)

Machine learning & artificial intelligence in the quantum domain: a review of recent progress.

Science.gov (United States)

Dunjko, Vedran; Briegel, Hans J

2018-03-05

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and

An Exploratory Study of the Critical Factors Affecting the Acceptability of Automated Teller Machine (ATM in Nigeria

Directory of Open Access Journals (Sweden)

Olusegun Folorunso

2010-01-01

Full Text Available This paper uses the Technology Acceptance Model (TAM as a basis for studying critical factors that affects the acceptability of Automated Teller Machine (ATM in Nigeria. Questionnaire approach was used with the respondents predominantly between 20-29 years old. Factor analysis was used to test which of the factors are the main factors affecting the adoption of the technology in Nigeria. It was discovered that the major factors affecting people’s intention to accept ATM are the security issues and poor internet connectivity.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

Machine learning of the reactor core loading pattern critical parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2007-01-01

The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employed a recently introduced machine learning technique, Support Vector Regression (SVR), which has a strong theoretical background in statistical learning theory. Superior empirical performance of the method has been reported on difficult regression problems in different fields of science and technology. SVR is a data driven, kernel based, nonlinear modelling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modelling. The starting set of experimental data for training and testing of the machine learning algorithm was obtained using a two-dimensional diffusion theory reactor physics computer code. We illustrate the performance of the solution and discuss its applicability, i.e., complexity, speed and accuracy, with a projection to a more realistic scenario involving machine learning from the results of more accurate and time consuming three-dimensional core modelling code. (author)

Aqueous cutting fluid for machining fissionable materials

Science.gov (United States)

Duerksen, Walter K.; Googin, John M.; Napier, Jr., Bradley

1984-01-01

The present invention is directed to a cutting fluid for machining fissionable material. The cutting fluid is formed of glycol, water and boron compound in an adequate concentration for effective neutron attenuation so as to inhibit criticality incidents during machining.

LHC Report: machine development

CERN Multimedia

Rogelio Tomás García for the LHC team

2015-01-01

Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

Machine-Learning Research

OpenAIRE

Dietterich, Thomas G.

1997-01-01

Machine-learning research has been making great progress in many directions. This article summarizes four of these directions and discusses some current open problems. The four directions are (1) the improvement of classification accuracy by learning ensembles of classifiers, (2) methods for scaling up supervised learning algorithms, (3) reinforcement learning, and (4) the learning of complex stochastic models.

Protein-Injection Machines in Bacteria.

Science.gov (United States)

Galán, Jorge E; Waksman, Gabriel

2018-03-08

Many bacteria have evolved specialized nanomachines with the remarkable ability to inject multiple bacterially encoded effector proteins into eukaryotic or prokaryotic cells. Known as type III, type IV, and type VI secretion systems, these machines play a central role in the pathogenic or symbiotic interactions between multiple bacteria and their eukaryotic hosts, or in the establishment of bacterial communities in a diversity of environments. Here we focus on recent progress elucidating the structure and assembly pathways of these machines. As many of the interactions shaped by these machines are of medical importance, they provide an opportunity to develop novel therapeutic approaches to combat important human diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

Progress in computational toxicology.

Science.gov (United States)

Ekins, Sean

2014-01-01

Computational methods have been widely applied to toxicology across pharmaceutical, consumer product and environmental fields over the past decade. Progress in computational toxicology is now reviewed. A literature review was performed on computational models for hepatotoxicity (e.g. for drug-induced liver injury (DILI)), cardiotoxicity, renal toxicity and genotoxicity. In addition various publications have been highlighted that use machine learning methods. Several computational toxicology model datasets from past publications were used to compare Bayesian and Support Vector Machine (SVM) learning methods. The increasing amounts of data for defined toxicology endpoints have enabled machine learning models that have been increasingly used for predictions. It is shown that across many different models Bayesian and SVM perform similarly based on cross validation data. Considerable progress has been made in computational toxicology in a decade in both model development and availability of larger scale or 'big data' models. The future efforts in toxicology data generation will likely provide us with hundreds of thousands of compounds that are readily accessible for machine learning models. These models will cover relevant chemistry space for pharmaceutical, consumer product and environmental applications. Copyright © 2013 Elsevier Inc. All rights reserved.

Progress report on Freeform Calibrations on Coordinate Measureing Machines

DEFF Research Database (Denmark)

Savio, Enrico; Meneghello, R.; De Chiffre, Leonardo

This report is made as a part of the project Easytrac, an EU project under the programme: Competitive and Sustainable Growth: Contract No: G6RD-CT-2000-00188, coordinated by UNIMETRIK S.A. (Spain). The project is concerned with low uncertainty calibrations on coordinate measuring machines...

Quantum cloning machines and the applications

Energy Technology Data Exchange (ETDEWEB)

Fan, Heng, E-mail: hfan@iphy.ac.cn [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Collaborative Innovation Center of Quantum Matter, Beijing 100190 (China); Wang, Yi-Nan; Jing, Li [School of Physics, Peking University, Beijing 100871 (China); Yue, Jie-Dong [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu [School of Physics, Peking University, Beijing 100871 (China)

2014-11-20

No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results.

Quantum cloning machines and the applications

International Nuclear Information System (INIS)

Fan, Heng; Wang, Yi-Nan; Jing, Li; Yue, Jie-Dong; Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu

2014-01-01

No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results

Engineered Surface Properties of Porous Tungsten from Cryogenic Machining

Science.gov (United States)

Schoop, Julius Malte

Porous tungsten is used to manufacture dispenser cathodes due to it refractory properties. Surface porosity is critical to functional performance of dispenser cathodes because it allows for an impregnated ceramic compound to migrate to the emitting surface, lowering its work function. Likewise, surface roughness is important because it is necessary to ensure uniform wetting of the molten impregnate during high temperature service. Current industry practice to achieve surface roughness and surface porosity requirements involves the use of a plastic infiltrant during machining. After machining, the infiltrant is baked and the cathode pellet is impregnated. In this context, cryogenic machining is investigated as a substitutionary process for the current plastic infiltration process. Along with significant reductions in cycle time and resource use, surface quality of cryogenically machined un-infiltrated (as-sintered) porous tungsten has been shown to significantly outperform dry machining. The present study is focused on examining the relationship between machining parameters and cooling condition on the as-machined surface integrity of porous tungsten. The effects of cryogenic pre-cooling, rake angle, cutting speed, depth of cut and feed are all taken into consideration with respect to machining-induced surface morphology. Cermet and Polycrystalline diamond (PCD) cutting tools are used to develop high performance cryogenic machining of porous tungsten. Dry and pre-heated machining were investigated as a means to allow for ductile mode machining, yet severe tool-wear and undesirable smearing limited the feasibility of these approaches. By using modified PCD cutting tools, high speed machining of porous tungsten at cutting speeds up to 400 m/min is achieved for the first time. Beyond a critical speed, brittle fracture and built-up edge are eliminated as the result of a brittle to ductile transition. A model of critical chip thickness ( hc ) effects based on cutting

Supporting Multiprocessors in the Icecap Safety-Critical Java Run-Time Environment

DEFF Research Database (Denmark)

Zhao, Shuai; Wellings, Andy; Korsholm, Stephan Erbs

The current version of the Safety Critical Java (SCJ) specification defines three compliance levels. Level 0 targets single processor programs while Level 1 and 2 can support multiprocessor platforms. Level 1 programs must be fully partitioned but Level 2 programs can also be more globally...... scheduled. As of yet, there is no official Reference Implementation for SCJ. However, the icecap project has produced a Safety-Critical Java Run-time Environment based on the Hardware-near Virtual Machine (HVM). This supports SCJ at all compliance levels and provides an implementation of the safety......-critical Java (javax.safetycritical) package. This is still work-in-progress and lacks certain key features. Among these is the ability to support multiprocessor platforms. In this paper, we explore two possible options to adding multiprocessor support to this environment: the “green thread” and the “native...

The research progress of perforating gun inner wall blind hole machining method

Science.gov (United States)

Wang, Zhe; Shen, Hongbing

2018-04-01

Blind hole processing method has been a concerned technical problem in oil, electronics, aviation and other fields. This paper introduces different methods for blind hole machining, focus on machining method for perforating gun inner wall blind hole processing. Besides, the advantages and disadvantages of different methods are also discussed, and the development trend of blind hole processing were introduced significantly.

Making molecular machines work

NARCIS (Netherlands)

Browne, Wesley R.; Feringa, Ben L.

2006-01-01

In this review we chart recent advances in what is at once an old and very new field of endeavour the achievement of control of motion at the molecular level including solid-state and surface-mounted rotors, and its natural progression to the development of synthetic molecular machines. Besides a

Biomarkers in critical illness: have we made progress?

Directory of Open Access Journals (Sweden)

Honore PM

2016-10-01

Full Text Available Patrick M Honore,1 Rita Jacobs,1 Inne Hendrickx,1 Elisabeth De Waele,1 Viola Van Gorp,1 Olivier Joannes-Boyau,2 Jouke De Regt,1 Willem Boer,3 Herbert D Spapen1 1Intensive Care Unit, Universitair Ziekenhuis Brussel, VUB University, Brussels, Belgium; 2Intensive Care Unit, Hopital Haut Leveque, University of Bordeaux 2, Bordeaux, France; 3Intensive Care Unit, Ziekenhuis Oost-Limburg, Genk, Belgium Abstract: Biomarkers have emerged as exemplary key players in translational medicine. Many have been assessed for timely recognition, early treatment, and adequate follow-up for a variety of pathologies. Biomarker sensitivity has improved considerably over the last years but specificity remains poor, in particular when two “marker-sensitive” conditions overlap in one patient. Biomarker research holds an enormous potential for diagnostic and prognostic purposes in postoperative and critically ill patients who present varying degrees of inflammation, infection, and concomitant (subacute organ dysfunction or failure. Despite a remarkable progress in development and testing, biomarkers are not yet ready for routine use at the bedside. Keywords: biomarkers, acute kidney injury, sepsis, ARDS

Critical feature analysis of a radiotherapy machine

International Nuclear Information System (INIS)

Rae, Andrew; Jackson, Daniel; Ramanan, Prasad; Flanz, Jay; Leyman, Didier

2005-01-01

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An 'assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code

Plac8 Links Oncogenic Mutations to Regulation of Autophagy and Is Critical to Pancreatic Cancer Progression

Directory of Open Access Journals (Sweden)

Conan Kinsey

2014-05-01

Full Text Available Mutations in p53 and RAS potently cooperate in oncogenic transformation, and correspondingly, these genetic alterations frequently coexist in pancreatic ductal adenocarcinoma (PDA and other human cancers. Previously, we identified a set of genes synergistically activated by combined RAS and p53 mutations as frequent downstream mediators of tumorigenesis. Here, we show that the synergistically activated gene Plac8 is critical for pancreatic cancer growth. Silencing of Plac8 in cell lines suppresses tumor formation by blocking autophagy, a process essential for maintaining metabolic homeostasis in PDA, and genetic inactivation in an engineered mouse model inhibits PDA progression. We show that Plac8 is a critical regulator of the autophagic machinery, localizing to the lysosomal compartment and facilitating lysosome-autophagosome fusion. Plac8 thus provides a mechanistic link between primary oncogenic mutations and the induction of autophagy, a central mechanism of metabolic reprogramming, during PDA progression.

A confidence metric for using neurobiological feedback in actor-critic reinforcement learning based brain-machine interfaces

Directory of Open Access Journals (Sweden)

Noeline Wilhelmina Prins

2014-05-01

Full Text Available Brain-Machine Interfaces (BMIs can be used to restore function in people living with paralysis. Current BMIs require extensive calibration that increase the set-up times and external inputs for decoder training that may be difficult to produce in paralyzed individuals. Both these factors have presented challenges in transitioning the technology from research environments to activities of daily living (ADL. For BMIs to be seamlessly used in ADL, these issues should be handled with minimal external input thus reducing the need for a technician/caregiver to calibrate the system. Reinforcement Learning (RL based BMIs are a good tool to be used when there is no external training signal and can provide an adaptive modality to train BMI decoders. However, RL based BMIs are sensitive to the feedback provided to adapt the BMI. In actor-critic BMIs, this feedback is provided by the critic and the overall system performance is limited by the critic accuracy. In this work, we developed an adaptive BMI that could handle inaccuracies in the critic feedback in an effort to produce more accurate RL based BMIs. We developed a confidence measure, which indicated how appropriate the feedback is for updating the decoding parameters of the actor. The results show that with the new update formulation, the critic accuracy is no longer a limiting factor for the overall performance. We tested and validated the system on three different data sets: synthetic data generated by an Izhikevich neural spiking model, synthetic data with a Gaussian noise distribution, and data collected from a non-human primate engaged in a reaching task. All results indicated that the system with the critic confidence built in always outperformed the system without the critic confidence. Results of this study suggest the potential application of the technique in developing an autonomous BMI that does not need an external signal for training or extensive calibration.

Control processes and machine protection on ASDEX Upgrade

International Nuclear Information System (INIS)

Raupp, G.; Treutterer, W.; Mertens, V.; Neu, G.; Sips, A.; Zasche, D.; Zehetbauer, Th.

2007-01-01

Safe operation of ASDEX Upgrade is guaranteed by a conventional hierarchy of simple and robust hard-wired systems for personnel and machine protection featuring standardized switch-off procedures. Machine protection and handling of off-normal events is further enhanced and peak and lifetime stress minimized through the plasma control system. Based on a real-time process model supporting safety critical applications with data quality tagging, process self-monitoring, watchdog monitoring and alarm propagation, processes detect complex and critical failures and reliably perform case-sensitive counter measures. Intelligent real-time failure handling is done with hardware or software redundancy and performance degradation, or modification of reference values to continue or terminate discharges with reduced machine stress. Examples implemented so far on ASDEX Upgrade are given, such as recovery from measurement failures, switch-over of redundant actuators, handling of actuator limitations, detection of plasma instabilities, plasma state dependent soft landing, or handling of failed switch-off procedures through breakers disconnecting the machine from grid

Marketing and vending machine; Marketing to jido hanbaiki

Energy Technology Data Exchange (ETDEWEB)

Onzo, N. [Waseda University, Tokyo (Japan)

1999-08-10

Vending machines in Japan have made original progress and have developed into big business. Annual sales by vending machines are 6 trillion 700 billion yen, which exceeds 6 trillion 100 billion yen sales by convenience stores. Research on vending machines may have advanced on the technical side but almost none on the marketing. In a vending machine that made an appearance in 1980 with the feature of a lottery, the winning probability was approximately one in fifty. In addition to a simple vending function, these machines have a promotion function. Some other machines have an electrical display of a commercial for products inside the machine for the purpose of attracting attention of passersby. This is an advertising function of the machines. In other words, one vending machine is capable of various marketing functions. This precisely means the subjects are numerous in the marketing research on vending machines. In contrast to the present century in which technical innovations have been made for vending machines, the coming 21st century may turn out to be the one in which marketing innovations are the mainstream for them. (NEDO)

Building machine learning systems with Python

CERN Document Server

Richert, Willi

2013-01-01

This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro

The Bearingless Electrical Machine

Science.gov (United States)

Bichsel, J.

1992-01-01

Electromagnetic bearings allow the suspension of solids. For rotary applications, the most important physical effect is the force of a magnetic circuit to a high permeable armature, called the MAXWELL force. Contrary to the commonly used MAXWELL bearings, the bearingless electrical machine will take advantage of the reaction force of a conductor carrying a current in a magnetic field. This kind of force, called Lorentz force, generates the torque in direct current, asynchronous and synchronous machines. The magnetic field, which already exists in electrical machines and helps to build up the torque, can also be used for the suspension of the rotor. Besides the normal winding of the stator, a special winding was added, which generates forces for levitation. So a radial bearing, which is integrated directly in the active part of the machine, and the motor use the laminated core simultaneously. The winding was constructed for the levitating forces in a special way so that commercially available standard ac inverters for drives can be used. Besides wholly magnetic suspended machines, there is a wide range of applications for normal drives with ball bearings. Resonances of the rotor, especially critical speeds, can be damped actively.

Investigation of permanent magnet machines for downhole applications: Design, prototype and testing of a flux-switching permanent magnet machine

Energy Technology Data Exchange (ETDEWEB)

Chen, Anyuan

2011-01-15

The current standard electrical downhole machine is the induction machine which is relatively inefficient. Permanent magnet (PM) machines, having higher efficiencies, higher torque densities and smaller volumes, have widely employed in industrial applications to replace conventional machines, but few have been developed for downhole applications due to the high ambient temperatures in deep wells and the low temperature stability of PM materials over time. Today, with the development of variable speed drives and the applications of high temperature magnet materials, it is increasingly interesting for oil and gas industries to develop PM machines for downhole applications. Recently, some PM machines applications have been presented for downhole applications, which are normally addressed on certain specific downhole case. In this thesis the focus has been put on the performance investigation of different PM machines for general downhole cases, in which the machine outer diameter is limited to be small by well size, while the machine axial length may be relatively long. The machine reliability is the most critical requirement while high torque density and high efficiency are also desirable. The purpose is to understand how the special constraints in downhole condition affect the performances of different machines. First of all, three basic machine concepts, which are the radial, axial and transverse flux machines, are studied in details by analytical method. Their torque density, efficiency, power factor and power capability are investigated with respect to the machine axial length and pole number. The presented critical performance comparisons of the machines provide an indication of machines best suitable with respect to performance and size for downhole applications. Conventional radial flux permanent magnet (RFPM) machines with the PMs on the rotor can provide high torque density and high efficiency. This type of machine has been suggested for several different

Motor proteins and molecular motors: how to operate machines at the nanoscale

International Nuclear Information System (INIS)

Kolomeisky, Anatoly B

2013-01-01

Several classes of biological molecules that transform chemical energy into mechanical work are known as motor proteins or molecular motors. These nanometer-sized machines operate in noisy stochastic isothermal environments, strongly supporting fundamental cellular processes such as the transfer of genetic information, transport, organization and functioning. In the past two decades motor proteins have become a subject of intense research efforts, aimed at uncovering the fundamental principles and mechanisms of molecular motor dynamics. In this review, we critically discuss recent progress in experimental and theoretical studies on motor proteins. Our focus is on analyzing fundamental concepts and ideas that have been utilized to explain the non-equilibrium nature and mechanisms of molecular motors. (topical review)

Consuming a Machinic Servicescape

OpenAIRE

Hietanen, Joel; Andéhn, Mikael; Iddon, Thom; Denny, Iain; Ehnhage, Anna

2016-01-01

Consumer encounters with servicescapes tend to emphasize the harmonic tendency of their value-creating potential. We contest this assumption from a critical non-representational perspective that foregrounds the machinic and repressive potentiality of such con- sumption contexts. We offer the airport servicescape as an illustrative example. 

Machine learning: Trends, perspectives, and prospects.

Science.gov (United States)

Jordan, M I; Mitchell, T M

2015-07-17

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.

Evolution of Machine Reliability and Life and Economics of Operational Use

Directory of Open Access Journals (Sweden)

Młynarski Stanisław

2016-12-01

Full Text Available The article presents new assumptions for reliability and life of machines, resulting from the development of technology. The innovative approach to reliability and life design as well as warranty duration planning is presented on an example of vehicle reliability characteristics. A new algorithm is proposed for the replacement of repairable objects costs by the price of life and reliability of new unrepairable ones. For the planning of the life of innovative machines, an effective method of technical progress rate determination is proposed. In conclusion, necessary modifications of machine and vehicle use systems, resulting from technology evolution and technical progress, are indicated. Finally, recommendations and directions of indispensable research in engineering and management of technical means of production are formulated.

Machine Maintenance Scheduling with Reliability Engineering Method and Maintenance Value Stream Mapping

Science.gov (United States)

Sembiring, N.; Nasution, A. H.

2018-02-01

Corrective maintenance i.e replacing or repairing the machine component after machine break down always done in a manufacturing company. It causes the production process must be stopped. Production time will decrease due to the maintenance team must replace or repair the damage machine component. This paper proposes a preventive maintenance’s schedule for a critical component of a critical machine of an crude palm oil and kernel company due to increase maintenance efficiency. The Reliability Engineering & Maintenance Value Stream Mapping is used as a method and a tool to analize the reliability of the component and reduce the wastage in any process by segregating value added and non value added activities.

Machine Learning of the Reactor Core Loading Pattern Critical Parameters

Directory of Open Access Journals (Sweden)

Krešimir Trontl

2008-01-01

Full Text Available The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR, which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

Machine Learning of the Reactor Core Loading Pattern Critical Parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2008-01-01

The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy

Beam interlock system and safe machine parameters system 2010 and beyond

CERN Document Server

Todd, B

2010-01-01

The Beam Interlock System (BIS) and Safe Machine Parameters (SMP) system are central to the protection of the Large Hadron Collider (LHC) machine. The BIS has been critical for the safe operation of LHC from the first day of operation. It has been installed and commissioned, only minor enhancements are required in order to accommodate all future LHC machine protection requirements. At reduced intensity, the SMP system is less critical for LHC operation. As such, the current system satisfies the 2010 operational requirements. Further developments are required, both at the SMP Controller level, and at the system level, in order to accommodate the requirements of the LHC beyond 2010.

An active role for machine learning in drug development

Science.gov (United States)

Murphy, Robert F.

2014-01-01

Due to the complexity of biological systems, cutting-edge machine-learning methods will be critical for future drug development. In particular, machine-vision methods to extract detailed information from imaging assays and active-learning methods to guide experimentation will be required to overcome the dimensionality problem in drug development. PMID:21587249

Wire electric-discharge machining and other fabrication techniques

Science.gov (United States)

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.

A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)

Science.gov (United States)

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon

1990-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

Future developments in brain-machine interface research.

Science.gov (United States)

Lebedev, Mikhail A; Tate, Andrew J; Hanson, Timothy L; Li, Zheng; O'Doherty, Joseph E; Winans, Jesse A; Ifft, Peter J; Zhuang, Katie Z; Fitzsimmons, Nathan A; Schwarz, David A; Fuller, Andrew M; An, Je Hi; Nicolelis, Miguel A L

2011-01-01

Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL) Center for Neuroprosthetics, to bring this new technology to clinical fruition.

Future developments in brain-machine interface research

Directory of Open Access Journals (Sweden)

Mikhail A. Lebedev

2011-01-01

Full Text Available Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL Center for Neuroprosthetics, to bring this new technology to clinical fruition.

In silico machine learning methods in drug development.

Science.gov (United States)

Dobchev, Dimitar A; Pillai, Girinath G; Karelson, Mati

2014-01-01

Machine learning (ML) computational methods for predicting compounds with pharmacological activity, specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties are being increasingly applied in drug discovery and evaluation. Recently, machine learning techniques such as artificial neural networks, support vector machines and genetic programming have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic targets. These methods are particularly useful for screening compound libraries of diverse chemical structures, "noisy" and high-dimensional data to complement QSAR methods, and in cases of unavailable receptor 3D structure to complement structure-based methods. A variety of studies have demonstrated the potential of machine-learning methods for predicting compounds as potential drug candidates. The present review is intended to give an overview of the strategies and current progress in using machine learning methods for drug design and the potential of the respective model development tools. We also regard a number of applications of the machine learning algorithms based on common classes of diseases.

A critical survey of live virtual machine migration techniques

Directory of Open Access Journals (Sweden)

Anita Choudhary

2017-11-01

Full Text Available Abstract Virtualization techniques effectively handle the growing demand for computing, storage, and communication resources in large-scale Cloud Data Centers (CDC. It helps to achieve different resource management objectives like load balancing, online system maintenance, proactive fault tolerance, power management, and resource sharing through Virtual Machine (VM migration. VM migration is a resource-intensive procedure as VM’s continuously demand appropriate CPU cycles, cache memory, memory capacity, and communication bandwidth. Therefore, this process degrades the performance of running applications and adversely affects efficiency of the data centers, particularly when Service Level Agreements (SLA and critical business objectives are to be met. Live VM migration is frequently used because it allows the availability of application service, while migration is performed. In this paper, we make an exhaustive survey of the literature on live VM migration and analyze the various proposed mechanisms. We first classify the types of Live VM migration (single, multiple and hybrid. Next, we categorize VM migration techniques based on duplication mechanisms (replication, de-duplication, redundancy, and compression and awareness of context (dependency, soft page, dirty page, and page fault and evaluate the various Live VM migration techniques. We discuss various performance metrics like application service downtime, total migration time and amount of data transferred. CPU, memory and storage data is transferred during the process of VM migration and we identify the category of data that needs to be transferred in each case. We present a brief discussion on security threats in live VM migration and categories them in three different classes (control plane, data plane, and migration module. We also explain the security requirements and existing solutions to mitigate possible attacks. Specific gaps are identified and the research challenges in improving

Progress toward a unified kJ-machine CANDY

International Nuclear Information System (INIS)

Kitagawa, Yoneyoshi; Mori, Yoshitaka; Komeda, Osamu; Hanayama, Ryohei; Ishii, Katsuhiro; Okihara, Shinichiro; Fujita, Kazuhisa; Nakayama, Suisei; Sekine, Takashi; Sato, Nakahiro; Kurita, Takashi; Kawashima, Toshiyuki; Watari, Takeshi; Kan, Hirofumi; Nakamura, Naoki; Kondo, Takuya; Fujine, Manabu; Azuma, Hirozumi; Motohiro, Tomoyoshi; Hioki, Tatsumi

2016-01-01

To construct a unified experimental machine CANDY using a kJ DPSSL driver in the fast-ignition scheme, the Laser for Fast Ignition Experiment (LFEX) at Osaka is used, showing that the laser-driven ions heat the preimploded core of a deuterated polystyrene (CD) shell target from 0.8 keV to 2 keV, resulting in 5 x 10 8 DD neutrons best ever obtained in the scheme. 4-J/10-Hz DPSSL laser HAMA is for the first time applied to the CD shell implosion- core heating experiments in the fast ignition scheme to yield neutrons and also to a continuous target injection, which yields neutrons of 3 x 10 5 n/4πsr n/shot. (paper)

Making and Operating Molecular Machines: A Multidisciplinary Challenge.

Science.gov (United States)

Baroncini, Massimo; Casimiro, Lorenzo; de Vet, Christiaan; Groppi, Jessica; Silvi, Serena; Credi, Alberto

2018-02-01

Movement is one of the central attributes of life, and a key feature in many technological processes. While artificial motion is typically provided by macroscopic engines powered by internal combustion or electrical energy, movement in living organisms is produced by machines and motors of molecular size that typically exploit the energy of chemical fuels at ambient temperature to generate forces and ultimately execute functions. The progress in several areas of chemistry, together with an improved understanding of biomolecular machines, has led to the development of a large variety of wholly synthetic molecular machines. These systems have the potential to bring about radical innovations in several areas of technology and medicine. In this Minireview, we discuss, with the help of a few examples, the multidisciplinary aspects of research on artificial molecular machines and highlight its translational character.

The phaco machine: analysing new technology.

Science.gov (United States)

Fishkind, William J

2013-01-01

The phaco machine is frequently overlooked as the crucial surgical instrument it is. Understanding how to set parameters is initiated by understanding fundamental concepts of machine function. This study analyses the critical concepts of partial occlusion phaco, occlusion phaco and pump technology. In addition, phaco energy categories as well as variations of phaco energy production are explored. Contemporary power modulations and pump controls allow for the enhancement of partial occlusion phacoemulsification. These significant changes in the anterior chamber dynamics produce a balanced environment for phaco; less complications; and improved patient outcomes.

Machine Translation Tools - Tools of The Translator's Trade

DEFF Research Database (Denmark)

Kastberg, Peter

2012-01-01

In this article three of the more common types of translation tools are presented, discussed and critically evaluated. The types of translation tools dealt with in this article are: Fully Automated Machine Translation (or FAMT), Human Aided Machine Translation (or HAMT) and Machine Aided Human...... Translation (or MAHT). The strengths and weaknesses of the different types of tools are discussed and evaluated by means of a number of examples. The article aims at two things: at presenting a sort of state of the art of what is commonly referred to as “machine translation” as well as at providing the reader...... with a sound basis for considering what translation tool (if any) is the most appropriate in order to meet his or her specific translation needs....

55th International Conference of Machine Design Departments 2014

CERN Document Server

Berka, Ondrej; Petr, Karel; Lopot, František; Dub, Martin

2016-01-01

This book is based on the 55th International Conference of Machine Design Departments 2014 (ICMD 2014) which was hosted by the Czech Technical University in September 2014. It features scientific articles which solve progressive themes from the field of machine design. The book addresses a broad range of themes including tribology, hydraulics, materials science, product innovation and experimental methods. It presents the latest interdisciplinary high-tech work. People with an interest in the latest research results in the field of machine design and manufacturing engineering will value this book with contributions of leading academic scientists and experts from all around the world.

Economic lifetime of a drilling machine:a case study on mining industry

OpenAIRE

Hamodi, Hussan; Lundberg, Jan; Jonsson, Adam

2013-01-01

Underground mines use many different types of machinery duringthe drift mining processes of drilling, charging, blasting, loading, scaling andbolting. Drilling machines play a critical role in the mineral extraction processand thus are important economically. However, as the machines age, theirefficiency and effectiveness decrease, negatively affecting productivity andprofitability and increasing total cost. Hence, the economic replacementlifetime of the machine is a key performance indicator...

A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)

Science.gov (United States)

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

1992-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

The expressive stance: intentionality, expression, and machine art

OpenAIRE

Linson, Adam

2013-01-01

This paper proposes a new interpretive stance for interpreting artistic works and performances that is relevant to artificial intelligence research but also has broader implications. Termed the expressive stance, this stance makes intelligible a critical distinction between present-day machine art and human art, but allows for the possibility that future machine art could find a place alongside our own. The expressive stance is elaborated as a response to Daniel Dennett's notion of the intent...

Group program procedure for machining seal rings of steam turbines on digital computer controlled machines

International Nuclear Information System (INIS)

Glukhikh, V.K.; Skvortsov, S.B.; Sidorov, V.A.

1982-01-01

Developed is a group program procedure for turning machining of seal rings, including the use of new progressive high-accuracy equipment, universal device for securing of all nomenclature of treated seal rings, necessary cutting tools and program control of the process of treatment. Introduction of a new technological process permitted to improve the quality of treated seal rings; to reduce the labour consumption in 30...40% [ru

Complex analysis of electromagnetic machines for vibro-impact technologies

Science.gov (United States)

Neyman, L. A.; Neyman, V. Yu

2017-10-01

For the implementation of high-energy impulse technologies of mechanical shock methods of secondary rock destruction, electromagnetic machines of vibro-impact action are of particular interest. Linear synchronous electromagnetic impact machine designs as a part of progress trend are considered where the head reciprocal motion is synchronized with 50 Hz power source pulses frequency applied to a winding or a system of windings. On the basis of identified differences of the head forced mechanical oscillation processes, merits and demerits of the work cycles of single or two-winding synchronous machine design variants are analyzed. Synchronous electromagnetic machines of a new design and principles of their control in a work cycle are presented. The specific half-wave interleaving of voltages applied to the windings allows reducing current amplitude and the influence of the impact drive on the power grid. To improve forced oscillation mode stability and precision, the new engineering solutions improving machines performances and exploitation conditions are proposed.

Los Alamos Critical Experiments Facility

International Nuclear Information System (INIS)

Malenfant, R.E.

1991-01-01

The Critical Experiments Facility of the Los Alamos National Laboratory has been in existence for 45 years. In that period of time, thousands of measurements have been made on assemblies containing every fissionable material in various configurations that included bare metal and compounds of the nitrate, sulfate, fluoride, carbide, and oxide. Techniques developed or applied include Rossi-α, source-jerk, rod oscillator, and replacement measurements. Many of the original measurements of delay neutrons were performed at the site, and a replica of the Hiroshima weapon was operated at steady state to assist in evaluating the relative biological effectiveness (RBE) of neutrons. Solid, liquid, and gas fissioning systems were run at critical. Operation of this original critical facility has demonstrated the margin of safety that can be obtained through remote operation. Eight accidental excursions have occurred on the site, ranging from 1.5 x 10 16 to 1.2 x 10 17 fissions, with no significant exposure to personnel or damage to the facility beyond the machines themselves -- and in only one case was the machine damaged beyond further use. The present status of the facility, operating procedures, and complement of machines will be described in the context of programmatic activity. New programs will focus on training, validation of criticality alarm systems, experimental safety assessment of process applications, and dosimetry. Special emphasis will be placed on the incorporation of experience from 45 years of operation into present procedures and programs. 3 refs

IQ Tests Are Not for Machines, Yet

Science.gov (United States)

Dowe, David L.; Hernandez-Orallo, Jose

2012-01-01

Complex, but specific, tasks--such as chess or "Jeopardy!"--are popularly seen as milestones for artificial intelligence (AI). However, they are not appropriate for evaluating the intelligence of machines or measuring the progress in AI. Aware of this delusion, Detterman has recently raised a challenge prompting AI researchers to evaluate their…

Critical Criminological Understandings of Adult Pornography and Woman Abuse: New Progressive Directions in Research and Theory

Directory of Open Access Journals (Sweden)

Walter DeKeseredy

2015-12-01

Full Text Available There is a small, but growing, social scientific literature on the racist and violent nature of contemporary adult pornography. However, considerably more empirical and theoretical work needs to be done to advance a critical criminological understanding of how such hurtful sexual media contribute to various forms of woman abuse in intimate relationships. The main objective of this article is to briefly review the relevant literature and to suggest a few new progressive empirical and theoretical directions.

The machine intelligence Hex project

Science.gov (United States)

Chalup, Stephan K.; Mellor, Drew; Rosamond, Fran

2005-12-01

Hex is a challenging strategy board game for two players. To enhance students’ progress in acquiring understanding and practical experience with complex machine intelligence and programming concepts we developed the Machine Intelligence Hex (MIHex) project. The associated undergraduate student assignment is about designing and implementing Hex players and evaluating them in an automated tournament of all programs developed by the class. This article surveys educational aspects of the MIHex project. Additionally, fundamental techniques for game programming as well as specific concepts for Hex board evaluation are reviewed. The MIHex game server and possibilities of tournament organisation are described. We summarise and discuss our experiences from running the MIHex project assignment over four consecutive years. The impact on student motivation and learning benefits are evaluated using questionnaires and interviews.

Analysis of machining and machine tools

CERN Document Server

Liang, Steven Y

2016-01-01

This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

Machine Learning Approaches for Clinical Psychology and Psychiatry.

Science.gov (United States)

Dwyer, Dominic B; Falkai, Peter; Koutsouleris, Nikolaos

2018-05-07

Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.

Amplification macroscopique de mouvements nanométriques induits par des machines moléculaires

OpenAIRE

Goujon , Antoine

2016-01-01

The last twenty years have seen tremendous progresses in the design and synthesis of complex molecular machines, often inspired by the beauty of the machinery found in biological systems. However, amplification of the molecular machines motion over several orders of magnitude above their typical length scale is still an ambitious challenge. This work describes how self-organization of molecular machines or motors allows for the synthesis of materials translating the motions of their component...

Design of a Three-Axis Machine Tool Module

National Research Council Canada - National Science Library

Childers, Marshal

2003-01-01

This report documents the design improvement process of the components in a tool module for a three-axis machine tool, which occurred during the period of March-April 2002 in support of a critical U.S...

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

Science.gov (United States)

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.

Recent developments in man-machine systems

International Nuclear Information System (INIS)

Johannsen, G.

1987-01-01

The field of man-machine systems is introduced with its subareas and a short outline of its history of 45 years. Three current lines of development in university and industrial research are emphasized. Today, the human problem solving activities are experimentally investigated and analytically described more vigorously than the control activities. Further, improved information presentations and decision support are made possible through new technologies of computer graphics and expert systems. At last, work on a general design methodology for man-machine systems is in progress. The aim is to better support human operators of dynamic technological systems as well as designers of graphics for visual display units and of dialogue styles. Thereby, safety and availability of the complete system can be increased. (orig.) [de

Jet joint undertaking progress report 1988 volume I

International Nuclear Information System (INIS)

1989-06-01

The 1988 progress report of the Joint European Torus (JET) is presented. It covers the fifth year of JET's operation and provides an overview of the scientific and technical advances made on JET. The JET most important articles, published during 1988, are included. The background of JET project, the main objectives and design aspects of the machine are summarized. Most of 1988 was devoted to machine operations: the number of pulses was 4673. The introduction, commissioning and operation of the JET second beam injector is reported. Planned developments on enhancements in the machine for future operations are included

A Year of Progress: NASA's Space Launch System Approaches Critical Design Review

Science.gov (United States)

Askins, Bruce; Robinson, Kimberly

2015-01-01

NASA's Space Launch System (SLS) made significant progress on the manufacturing floor and on the test stand in 2014 and positioned itself for a successful Critical Design Review in mid-2015. SLS, the world's only exploration-class heavy lift rocket, has the capability to dramatically increase the mass and volume of human and robotic exploration. Additionally, it will decrease overall mission risk, increase safety, and simplify ground and mission operations - all significant considerations for crewed missions and unique high-value national payloads. Development now is focused on configuration with 70 metric tons (t) of payload to low Earth orbit (LEO), more than double the payload of the retired Space Shuttle program or current operational vehicles. This "Block 1" design will launch NASA's Orion Multi-Purpose Crew Vehicle (MPCV) on an uncrewed flight beyond the Moon and back and the first crewed flight around the Moon. The current design has a direct evolutionary path to a vehicle with a 130t lift capability that offers even more flexibility to reduce planetary trip times, simplify payload design cycles, and provide new capabilities such as planetary sample returns. Every major element of SLS has successfully completed its Critical Design Review and now has hardware in production or testing. In fact, the SLS MPCV-to-Stage-Adapter (MSA) flew successfully on the Exploration Flight Test (EFT) 1 launch of a Delta IV and Orion spacecraft in December 2014. The SLS Program is currently working toward vehicle Critical Design Review in mid-2015. This paper will discuss these and other technical and programmatic successes and challenges over the past year and provide a preview of work ahead before the first flight of this new capability.

Machine learning for micro-tomography

Science.gov (United States)

Parkinson, Dilworth Y.; Pelt, Daniël. M.; Perciano, Talita; Ushizima, Daniela; Krishnan, Harinarayan; Barnard, Harold S.; MacDowell, Alastair A.; Sethian, James

2017-09-01

Machine learning has revolutionized a number of fields, but many micro-tomography users have never used it for their work. The micro-tomography beamline at the Advanced Light Source (ALS), in collaboration with the Center for Applied Mathematics for Energy Research Applications (CAMERA) at Lawrence Berkeley National Laboratory, has now deployed a series of tools to automate data processing for ALS users using machine learning. This includes new reconstruction algorithms, feature extraction tools, and image classification and recommen- dation systems for scientific image. Some of these tools are either in automated pipelines that operate on data as it is collected or as stand-alone software. Others are deployed on computing resources at Berkeley Lab-from workstations to supercomputers-and made accessible to users through either scripting or easy-to-use graphical interfaces. This paper presents a progress report on this work.

Underground roadway drivage with heading machines in Indian coal industry

Energy Technology Data Exchange (ETDEWEB)

Mukherjee, T.K.

1983-03-01

Heading machines have assumed a very important place in underground roadway drivage. They are not only a compromise between ''drill-and-blast'' technique and full-face machines, but are also an economic and versatile form of mechanised roadway drivage. Since the advantages gained by heading machines are considerable, the use of these machines is becoming popular in underground roadway drivage. Experience with continuous miner and heading machines in Indian coal mines is very limited compared to that of Western countries. In 1964-65, for the first time, two units of Lee Norse Miner were used at Kunostoria Colliery of Bengal Coal Company. In 1966, two units of Joy Continuous Miner were introduced at Chalkari Colliery of National Coal Development Corporation, but had to be adandoned because of heavy make of water at the installation site. A Russian PK-3 heading machine was used limitedly during the development of Banki Colliery, Madhya Pradesh. A Demag Unicorn VS-1 machine operated for the development of roadways at Jitpur and Chasnala Collieries of IISCO between 1967-70. With this machine, progress of 7 m per day was attained in level roadways and of about 2 m per day in steep raises.

Machine learning for epigenetics and future medical applications

OpenAIRE

Holder, Lawrence B.; Haque, M. Muksitul; Skinner, Michael K.

2017-01-01

ABSTRACT Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems w...

Progress report for a research program in computational physics: Progress report, January 1, 1988-December 31, 1988

International Nuclear Information System (INIS)

Guralnik, G.S.

1988-01-01

The project of this progress report are all ultimately concerned with various aspects of numerical simulations of lattice gauge theories. These aspects include algorithms, machines, theoretical studies and actual simulations. We made progress in four general areas: studies of new algorithms, determination of the SU(3) β-function, studies of the finite temperature QCD phase transition in the presence of fermions, and the calculation of hadronic matrix elements. We will describe each of these in turn. 7 refs

Reliability Centred Maintenance (RCM) Analysis of Laser Machine in Filling Lithos at PT X

Science.gov (United States)

Suryono, M. A. E.; Rosyidi, C. N.

2018-03-01

PT. X used automated machines which work for sixteen hours per day. Therefore, the machines should be maintained to keep the availability of the machines. The aim of this research is to determine maintenance tasks according to the cause of component’s failure using Reliability Centred Maintenance (RCM) and determine the amount of optimal inspection frequency which must be performed to the machine at filling lithos process. In this research, RCM is used as an analysis tool to determine the critical component and find optimal inspection frequencies to maximize machine’s reliability. From the analysis, we found that the critical machine in filling lithos process is laser machine in Line 2. Then we proceed to determine the cause of machine’s failure. Lastube component has the highest Risk Priority Number (RPN) among other components such as power supply, lens, chiller, laser siren, encoder, conveyor, and mirror galvo. Most of the components have operational consequences and the others have hidden failure consequences and safety consequences. Time-directed life-renewal task, failure finding task, and servicing task can be used to overcome these consequences. The results of data analysis show that the inspection must be performed once a month for laser machine in the form of preventive maintenance to lowering the downtime.

Neutron shielding and its impact on the ITER machine design

International Nuclear Information System (INIS)

Daenner, W.; El Guebaly, L.; Sawan, M.; Gohar, Y.; Maki, K.; Rado, V.; Schchipakin, O.; Zimin, S.

1991-01-01

This paper describes the efforts made in the frame of the ITER project to analyze the shielding of the superconducting magnets. First, the radiation limits to be achieved are specified as well as the neutron source in terms of wall loading on the first wall of the machine. Then the general shield concept is explained, including the most essential details of the various shield components. A brief section is devoted to the calculational tools, the data base, and the safety factors to be applied to the results obtained. The neutronics models of four different configurations are summarized as they were used to study the most critical parts of the machine. This section is followed by a presentation of the most important results from one-, two- and three-dimensional calculations. They are given for both the reference design and an improved one in which the critical regions are reinforced with respect to their shielding capability. It is concluded that the ITER shield layout just marginally meets the stated limits provided that some tungsten is included in the critical regions. A slight revision of the overall machine dimensions with the aim to achieve a less complex shield and a higher margin with respect to the limits is, however, seen the better solution. (orig.)

Some new machine projects studied at LNS

International Nuclear Information System (INIS)

Tkatchenko, A.

1983-01-01

In front of the increasing interest for the synchrotron radiation uses, the electron storage rings have been gradually transformed in light sources. Yet, those machines had not been optimized for this use. So, in the last 10 years, numerous optimized machines have been defined and destinated to sole synchrotron light production up to the X domain. In the French domain, several projects have been elaborated, to satisfy the national needs in far UV and X radiation. - SUPER-ACO project (0,8 GeV) from Orsay. Its realisation is in progress. - SIREM project (1,2 GeV) from Grenoble CEN. - European ESRF project (5 GeV) optimized for X radiation, and for which a work group has been installed at CERN. - A X radiation national machine project (3 or 4 GeV) derived from the ESRF one. - At last, the Mars project, concerning a X radiation source storage ring aimed to a industrial use: the microlithographie [fr

Modelling, Construction, and Testing of a Simple HTS Machine Demonstrator

DEFF Research Database (Denmark)

Jensen, Bogi Bech; Abrahamsen, Asger Bech

2011-01-01

This paper describes the construction, modeling and experimental testing of a high temperature superconducting (HTS) machine prototype employing second generation (2G) coated conductors in the field winding. The prototype is constructed in a simple way, with the purpose of having an inexpensive way...... of validating finite element (FE) simulations and gaining a better understanding of HTS machines. 3D FE simulations of the machine are compared to measured current vs. voltage (IV) curves for the tape on its own. It is validated that this method can be used to predict the critical current of the HTS tape...... installed in the machine. The measured torque as a function of rotor position is also reproduced by the 3D FE model....

Machine rates for selected forest harvesting machines

Science.gov (United States)

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

Using Machine Learning to Predict MCNP Bias

Energy Technology Data Exchange (ETDEWEB)

Grechanuk, Pavel Aleksandrovi [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2018-01-09

For many real-world applications in radiation transport where simulations are compared to experimental measurements, like in nuclear criticality safety, the bias (simulated - experimental k_eff) in the calculation is an extremely important quantity used for code validation. The objective of this project is to accurately predict the bias of MCNP6 [1] criticality calculations using machine learning (ML) algorithms, with the intention of creating a tool that can complement the current nuclear criticality safety methods. In the latest release of MCNP6, the Whisper tool is available for criticality safety analysts and includes a large catalogue of experimental benchmarks, sensitivity profiles, and nuclear data covariance matrices. This data, coming from 1100+ benchmark cases, is used in this study of ML algorithms for criticality safety bias predictions.

Molecular machines open cell membranes.

Science.gov (United States)

García-López, Víctor; Chen, Fang; Nilewski, Lizanne G; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B; Robinson, Jacob T; Wang, Gufeng; Pal, Robert; Tour, James M

2017-08-30

Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

Molecular machines open cell membranes

Science.gov (United States)

García-López, Víctor; Chen, Fang; Nilewski, Lizanne G.; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B.; Robinson, Jacob T.; Wang, Gufeng; Pal, Robert; Tour, James M.

2017-08-01

Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

Empirical model for estimating the surface roughness of machined ...

African Journals Online (AJOL)

Empirical model for estimating the surface roughness of machined ... as well as surface finish is one of the most critical quality measure in mechanical products. ... various cutting speed have been developed using regression analysis software.

Dynamic Resource Allocation and Access Class Barring Scheme for Delay-Sensitive Devices in Machine to Machine (M2M) Communications.

Science.gov (United States)

Li, Ning; Cao, Chao; Wang, Cong

2017-06-15

Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine (M2M) communications, in which Delay-Sensitive (DS) devices coexist with Delay-Tolerant (DT) ones. In M2M communications, since delay-sensitive devices share random access resources with delay-tolerant devices, reducing the resources consumed by delay-sensitive devices means that there will be more resources available to delay-tolerant ones. Our goal is to optimize the random access scheme, which can not only satisfy the requirements of delay-sensitive devices, but also take the communication quality of delay-tolerant ones into consideration. We discuss this problem from the perspective of delay-sensitive services by adjusting the resource allocation and ACB scheme for these devices dynamically. Simulation results show that our proposed scheme realizes good performance in satisfying the delay-sensitive services as well as increasing the utilization rate of the random access resources allocated to them.

Progress Report on the US Critical Zone Observatory Program

Science.gov (United States)

Barrera, E. C.

2014-12-01

The Critical Zone Observatory (CZO) program supported by the National Science Foundation originated from the recommendation of the Earth Science community published in the National Research Council report "Basic Research Opportunities in Earth Sciences" (2001) to establish natural laboratories to study processes and systems of the Critical Zone - the surface and near-surface environment sustaining nearly all terrestrial life. After a number of critical zone community workshops to develop a science plan, the CZO program was initiated in 2007 with three sites and has now grown to 10 sites and a National Office, which coordinates research, education and outreach activities of the network. Several of the CZO sites are collocated with sites supported by the US Long Term Ecological Research (LTER) and the Long Term Agricultural Research (LTAR) programs, and the National Ecological Observatory Network (NEON). Future collaboration with additional sites of these networks will add to the potential to answer questions in a more comprehensive manner and in a larger regional scale about the critical zone form and function. At the international level, CZOs have been established in many countries and strong collaborations with the US program have been in place for many years. The next step is the development of a coordinated international program of critical zone research. The success of the CZO network of sites can be measured in transformative results that elucidate properties and processes controlling the critical zone and how the critical zone structure, stores and fluxes respond to climate and land use change. This understanding of the critical zone can be used to enhance resilience and sustainability, and restore ecosystem function. Thus, CZO science can address major societal challenges. The US CZO network is a facility open to research of the critical zone community at large. Scientific data and information about the US program are available at www.criticalzone.org.

Advances Towards Synthetic Machines at the Molecular and Nanoscale Level

Directory of Open Access Journals (Sweden)

Kristina Konstas

2010-06-01

Full Text Available The fabrication of increasingly smaller machines to the nanometer scale can be achieved by either a “top-down” or “bottom-up” approach. While the former is reaching its limits of resolution, the latter is showing promise for the assembly of molecular components, in a comparable approach to natural systems, to produce functioning ensembles in a controlled and predetermined manner. In this review we focus on recent progress in molecular systems that act as molecular machine prototypes such as switches, motors, vehicles and logic operators.

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

Science.gov (United States)

Iwasaki, N

2001-06-01

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

Modelling injection moulding machines for micro manufacture applications through functional analysis

DEFF Research Database (Denmark)

Fantoni, G.; Tosello, Guido; Gabelloni, D.

2012-01-01

The paper presents the analysis of an injection moulding machine using functional analysis to identify both its critical components and possible working problems when such a machine is employed for the production of polymer-based micro products. The step-by-step procedure starts from the study...... of the process phases of a machine and then it employs functional analysis to decompose the phases and attributes functions to part features. Part features are subsequently analyzed to understand the causal chains bringing either to the desired behaviour or to failures to avoid. The assessment of the design...... solution is finally performed by gathering quantitative data from experiments. The case study investigates the design motivations and functional drivers of a micro injection moulding machine. The analysis allows identifying the correlations between failures and advantages with the design of the machine...

Manufacturing progress on the first sector and lower ports for ITER vacuum vessel

Energy Technology Data Exchange (ETDEWEB)

Ahn, H.J., E-mail: hjahn@nfri.re.kr [National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of); Kim, H.S.; Kim, G.H.; Park, C.K.; Hong, G.H.; Jin, S.W.; Lee, H.G.; Jung, K.J. [National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of); Lee, J.S.; Kim, T.S.; Won, J.G.; Roh, B.R.; Park, K.H. [Hyundai Heavy Industries Co. Ltd., Ulsan 682-792 (Korea, Republic of); Sa, J.W.; Choi, C.H.; Sborchia, C. [ITER Organization, Route de Vinon sur Verdon, 13115 Saint Paul-lez-Durance (France)

2016-11-01

Highlights: • All manufacturing drawings of the first sector of VV have been completed. • Full scale mock-ups have been constructed to verify fabrication procedure. • Qualifications for welding and forming are done and for NDE are ongoing. • Manufacturing progress is around 40% for the sector and LPSE up to the end of 2015. - Abstract: Manufacturing design of Korean sectors and ports for the ITER Vacuum Vessel (VV) has been developed to comply with the tight tolerance and severe inspection requirements. The first VV sector and lower ports are being fabricated slowly under strict regulations after verification using several real scale mock-ups and qualifications for welding, forming and NDE. During three years after start of fabrication, manufacturing progress on four poloidal segments of the first sector is that (1) all inner shells were welded, (2) forgings for complicate components have been machined, (3) port stubs and poloidal T-ribs were assembled, and (4) machined components are welded on the inner shells by narrow-gap TIG welding and electron beam welding. The progress of lower ports is that (1) inner shells of stub extensions were bent and treated with heat, (2) T-ribs were fabricated and examined by qualified phased array UT, (3) supporting pads and gussets have been machined, and (4) inner shells are assembled with T-ribs and machined forgings. The progress rate of manufacturing is around 40% up to the end of 2015 for the first sector and lower port stub extensions.

A Critical Role of TET1/2 Proteins in Cell-Cycle Progression of Trophoblast Stem Cells

Directory of Open Access Journals (Sweden)

Stephanie Chrysanthou

2018-04-01

Full Text Available Summary: The ten-eleven translocation (TET proteins are well known for their role in maintaining naive pluripotency of embryonic stem cells. Here, we demonstrate that, jointly, TET1 and TET2 also safeguard the self-renewal potential of trophoblast stem cells (TSCs and have partially redundant roles in maintaining the epithelial integrity of TSCs. For the more abundantly expressed TET1, we show that this is achieved by binding to critical epithelial genes, notably E-cadherin, which becomes hyper-methylated and downregulated in the absence of TET1. The epithelial-to-mesenchymal transition phenotype of mutant TSCs is accompanied by centrosome duplication and separation defects. Moreover, we identify a role of TET1 in maintaining cyclin B1 stability, thereby acting as facilitator of mitotic cell-cycle progression. As a result, Tet1/2 mutant TSCs are prone to undergo endoreduplicative cell cycles leading to the formation of polyploid trophoblast giant cells. Taken together, our data reveal essential functions of TET proteins in the trophoblast lineage. : TET proteins are well known for their role in pluripotency. Here, Hemberger and colleagues show that TET1 and TET2 are also critical for maintaining the epithelial integrity of trophoblast stem cells. TET1/2 ensure mitotic cell-cycle progression by stabilizing cyclin B1 and by regulating centrosome organization. These insights reveal the importance of TET proteins beyond their role in epigenome remodeling. Keywords: TET proteins, trophoblast stem cells, cell cycle, endoreduplication, self-renewal, mitosis, trophoblast giant cells, differentiation

Overview of engineering design, manufacturing and assembly of JT-60SA machine

Energy Technology Data Exchange (ETDEWEB)

Di Pietro, Enrico, E-mail: enrico.dipietro@jt60sa.org [JT-60SA EU Home Team, Fusion for Energy, Boltzmannstrasse 2, Garching 85748 (Germany); Barabaschi, Pietro [JT-60SA EU Home Team, Fusion for Energy, Boltzmannstrasse 2, Garching 85748 (Germany); Kamada, Yutaka [JT-60SA JA Home Team, Japan Atomic Energy Agency, 801-1 Mukoyama, Naka, Ibaraki 311-0193 (Japan); Ishida, Shinichi [JT-60SA JA Project Team, Japan Atomic Energy Agency, 801-1 Mukoyama, Naka, Ibaraki 311-0193 (Japan)

2014-10-15

The JT-60SA experiment is one of the three projects to be undertaken in Japan as part of the Broader Approach Agreement, conducted jointly by Europe and Japan, and complementing the construction of ITER in Europe. The JT-60SA device is a fully superconducting tokamak capable of confining break-even equivalent deuterium plasmas with equilibria covering high plasma shaping with a low aspect ratio at a maximum plasma current of I{sub p} = 5.5 MA. This makes JT-60SA capable to support and complement ITER in all the major areas of fusion plasma development necessary to decide DEMO reactor construction. After a complex start-up phase due to the necessity to carry out a re-baselining effort with the purpose to fit in the original budget while aiming to retain the machine mission, performance, and experimental flexibility, in 2009 detailed design could start. With the majority of time-critical industrial contracts in place, in 2012, it was possible to establish a credible time plan, and now, the project is progressing on schedule towards the first plasma in March 2019. After careful and focused R and D and qualification tests, the procurement of the major components and plant is now well advanced in manufacturing design and/or fabrication. In the meantime the disassembly of the JT-60U machine has been completed and the engineering of the JT-60SA assembly process has been developed. The actual assembly of JT-60SA started in January 2013 with the installation of the cryostat base. The paper gives an overview of the present status of the engineering design, manufacturing and assembly of the JT-60SA machine.

Quantitative assessment of the enamel machinability in tooth preparation with dental diamond burs.

Science.gov (United States)

Song, Xiao-Fei; Jin, Chen-Xin; Yin, Ling

2015-01-01

Enamel cutting using dental handpieces is a critical process in tooth preparation for dental restorations and treatment but the machinability of enamel is poorly understood. This paper reports on the first quantitative assessment of the enamel machinability using computer-assisted numerical control, high-speed data acquisition, and force sensing systems. The enamel machinability in terms of cutting forces, force ratio, cutting torque, cutting speed and specific cutting energy were characterized in relation to enamel surface orientation, specific material removal rate and diamond bur grit size. The results show that enamel surface orientation, specific material removal rate and diamond bur grit size critically affected the enamel cutting capability. Cutting buccal/lingual surfaces resulted in significantly higher tangential and normal forces, torques and specific energy (pmachinability for clinical dental practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mechanical properties of JT-60 tokamak machine in power tests

International Nuclear Information System (INIS)

Takatsu, Hideyuki; Ohkubo, Minoru; Yamamoto, Masahiro; Ohta, Mitsuru

1986-01-01

JT-60 power tests were carried out from Dec. 10, 1984 to Feb. 20, 1985 to demonstrate, in advance of actual plasma operation, satisfactory performance of tokamak machine, power suppliers and control system in combination. The tests began with low power test of individual coil systems and progressed to full power tests. The coil current was raised step by step, monitoring the mechanical, thermal, electrical and vacuum data. Power tests were concluded with successful results. All of the coil systems were raised up to full power operation in combination and system performance was verified including the structural integrity of tokamak machine. Measured strain and deflection showed good agreements with those predicted in the design, which was an evidence that electromagnetic forces were supported as expected in the design. A few limitations to machine operation was made clear quantitatively. And it was found that existing detectors were insufficient to monitor machine integrity and two kinds of detector were proposed to be installed. (author)

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Science.gov (United States)

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

What is the machine learning?

Science.gov (United States)

Chang, Spencer; Cohen, Timothy; Ostdiek, Bryan

2018-03-01

Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. To address this concern, we explore a data planing procedure for identifying combinations of variables—aided by physical intuition—that can discriminate signal from background. Weights are introduced to smooth away the features in a given variable(s). New networks are then trained on this modified data. Observed decreases in sensitivity diagnose the variable's discriminating power. Planing also allows the investigation of the linear versus nonlinear nature of the boundaries between signal and background. We demonstrate the efficacy of this approach using a toy example, followed by an application to an idealized heavy resonance scenario at the Large Hadron Collider. By unpacking the information being utilized by these algorithms, this method puts in context what it means for a machine to learn.

Reactor technology. Progress report, January--March 1978

International Nuclear Information System (INIS)

Warren, J.L.

1978-07-01

Progress is reported in eight program areas. The nuclear Space Electric Power Supply Program examined safety questions in the aftermath of the COSMOS 954 incident, examined the use of thermoelectric converters, examined the neutronic effectiveness of various reflecting materials, examined ways of connecting heat pipes to one another, studied the consequences of the failure of one heat pipe in the reactor core, and did conceptual design work on heat radiators for various power supplies. The Heat Pipe Program reported progress in the design of ceramic heat pipes, new application of heat pipes to solar collectors, and final performance tests of two pipes for HEDL applications. Under the Nuclear Process Heat Program, work continues on computer codes to model a pebble bed high-temperature gas-cooled reactor, adaptation of a set of German reactor calculation codes to use on U.S. computers, and a parametric study of a certain resonance integral required in reactor studies. Under the Nonproliferation Alternative Sources Assessment Program LASL has undertaken an evaluation of a study of gaseous core reactors by Southern Science Applications, Inc. Independently LASL has developed a proposal for a comprehensive study of gaseous uranium-fueled reactor technology. The Plasma Core Reactor Program has concentrated on restacking the beryllium reflector and redesigning the nuclear control system. The status of and experiments on four critical assemblies, SKUA, Godiva IV, Big Ten, and Flattop, are reported. The Nuclear Criticality Safety Program carried out several tasks including conducting a course, doing several annual safety reviews and evaluating the safety of two Nevada test devices. During the quarter one of the groups involved in reactor technology has acquired responsibility for the operation of a Cockroft-Walton accelerator. The present report contains information on the use of machine and improvements being made in its operation

A reliability-based preventive maintenance methodology for the projection spot welding machine

Directory of Open Access Journals (Sweden)

Fayzimatov Ulugbek

2018-06-01

Full Text Available An effective operations of a projection spot welding (PSW machine is closely related to the effec-tiveness of the maintenance. Timely maintenance can prevent failures and improve reliability and maintainability of the machine. Therefore, establishing the maintenance frequency for the welding machine is one of the most important tasks for plant engineers. In this regard, reliability analysis of the welding machine can be used to establish preventive maintenance intervals (PMI and to identify the critical parts of the system. In this reliability and maintainability study, analysis of the PSW machine was carried out. The failure and repair data for analysis were obtained from automobile manufacturing company located in Uzbekistan. The machine was divided into three main sub-systems: electrical, pneumatic and hydraulic. Different distributions functions for all sub-systems was tested and their parameters tabulated. Based on estimated parameters of the analyzed distribu-tions, PMI for the PSW machines sub-systems at different reliability levels was calculated. Finally, preventive measures for enhancing the reliability of the PSW machine sub-systems are suggested.

MoleculeNet: a benchmark for molecular machine learning.

Science.gov (United States)

Wu, Zhenqin; Ramsundar, Bharath; Feinberg, Evan N; Gomes, Joseph; Geniesse, Caleb; Pappu, Aneesh S; Leswing, Karl; Pande, Vijay

2018-01-14

Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However, algorithmic progress has been limited due to the lack of a standard benchmark to compare the efficacy of proposed methods; most new algorithms are benchmarked on different datasets making it challenging to gauge the quality of proposed methods. This work introduces MoleculeNet, a large scale benchmark for molecular machine learning. MoleculeNet curates multiple public datasets, establishes metrics for evaluation, and offers high quality open-source implementations of multiple previously proposed molecular featurization and learning algorithms (released as part of the DeepChem open source library). MoleculeNet benchmarks demonstrate that learnable representations are powerful tools for molecular machine learning and broadly offer the best performance. However, this result comes with caveats. Learnable representations still struggle to deal with complex tasks under data scarcity and highly imbalanced classification. For quantum mechanical and biophysical datasets, the use of physics-aware featurizations can be more important than choice of particular learning algorithm.

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics

Directory of Open Access Journals (Sweden)

Haejoon Jung

2018-01-01

Full Text Available As an intrinsic part of the Internet of Things (IoT ecosystem, machine-to-machine (M2M communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics.

Science.gov (United States)

Jung, Haejoon; Lee, In-Ho

2018-01-12

As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

A review on progress of man-machine interface system designs for Japanese PWRs

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Yamamoto, Yoshihiro; Magari, Takayuki.

1994-01-01

Historical development of Instrumentation and Control (I and C) system designing for the PWR plants in Kansai Electric Co. Ltd is firstly reviewed with respect to the conventional PWRs in the past, brand-new PWRs (Ohi 3/4 units) and advanced PWRs (APWR) in Japan. The major features of the APWR I and C system design are extensive application of digital computer control technology and advanced man-machine interface in order to enhance safety and reliability of total I and C system and to improve human factors in nuclear power plant operation. Comparative study of the APWR's I and C system design with the EPRI's User Requirement Definitions (URD) resulted in that the current Japanese APWR I and C system design meets generally with the EPRI URD conditions except for those items mainly set by the present national regulatory guidelines. The remaining problems in the current I and C system design are discussed which include the issues on future direction of man-machine interface development. (author)

Identification of Technological Parameters of Ni-Alloys When Machining by Monolithic Ceramic Milling Tool

Science.gov (United States)

Czán, Andrej; Kubala, Ondrej; Danis, Igor; Czánová, Tatiana; Holubják, Jozef; Mikloš, Matej

2017-12-01

The ever-increasing production and the usage of hard-to-machine progressive materials are the main cause of continual finding of new ways and methods of machining. One of these ways is the ceramic milling tool, which combines the pros of conventional ceramic cutting materials and pros of conventional coating steel-based insert. These properties allow to improve cutting conditions and so increase the productivity with preserved quality known from conventional tools usage. In this paper, there is made the identification of properties and possibilities of this tool when machining of hard-to-machine materials such as nickel alloys using in airplanes engines. This article is focused on the analysis and evaluation ordinary technological parameters and surface quality, mainly roughness of surface and quality of machined surface and tool wearing.

The Machine within the Machine

CERN Multimedia

Katarina Anthony

2014-01-01

Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

Hydraulic stud-tensioning machines in reactor technology

International Nuclear Information System (INIS)

Lachner, H.

1978-01-01

Hydraulic multiple stud tensioner (MST) for the simultaneous prestressing of all the stud bolts is make it possible to achieve highly accurate prestress levels in the highly stressed bolts holding down the top head of reactor pressure vessels. These machines can remove and replace the nuts and studs, and can rotate these components upwards and downwards, during the operation of opening and closing the reactor pressure vessel. In order to reduce the radiation exposure of the service personnel, and also to reduce the time required for this work which may lie in the critical path of the refuelling time schedule, it is desirable to achieve complete mechanisation of these machines, including remote control and remote monitoring. The devices and components required for this purpose are without precedent in machine construction with respect to their functions and to the load range involved. The reported operating experience therefore also covers some points of general interest while the data on maintenance reflect the known status of the technology. (orig.) [de

Council-supported condom vending machines: are they acceptable to rural communities?

Science.gov (United States)

Tomnay, Jane E; Hatch, Beth

2013-11-01

Twenty-four hour access to condoms for young people living in rural Victoria is problematic for many reasons, including the fact that condom vending machines are often located in venues and places they cannot access. We partnered with three rural councils to install condom vending machines in locations that provided improved access to condoms for local young people. Councils regularly checked the machines, refilled the condoms and retrieved the money. They also managed the maintenance of the machine and provided monthly data. In total, 1153 condoms were purchased over 12 months, with 924 (80%) obtained from male toilets and 69% (801 out of 1153) purchased in the second half of the study. Revenue of $2626.10 (AUD) was generated and no negative feedback from residents was received by any council nor was there any negative reporting by local media. Vandalism, tampering or damage occurred at all sites; however, only two significant episodes of damage required a machine to be sent away for repairs. Condom vending machines installed in rural towns in north-east Victoria are accessible to young people after business hours, are cost-effective for councils and have not generated any complaints from residents. The machines have not suffered unrepairable damage and were used more frequently as the study progressed.

THE GARDEN AND THE MACHINE

DEFF Research Database (Denmark)

Clemmensen, Thomas Juel

2012-01-01

The aim of this paper is to explore how the concepts of garden and machine might inform our understanding of the complex relationship between infrastructure and nature. The garden is introduced as a third nature and used to shed a critical light on the promotion of landscape as infrastructure...... in relation to the environmental problems being addressed, and that we need gardens of reflection, interrogation and doubt, in order to engage with the deeper complexities of territorial transformations....

The Garden and the Machine

DEFF Research Database (Denmark)

Clemmensen, Thomas Juel

2014-01-01

The aim of this paper is to explore how the concepts of garden and machine might inform our understanding of the complex relationship between infrastructure and nature. The garden is introduced as a third nature and used to shed a critical light on the promotion of landscape ‘as’ infrastructure...... in relation to the environmental problems being addressed, and that we need gardens of reflection, interrogation and doubt, in order to engage with the deeper complexities of territorial transformations....

A Systematic Approach to Analyse Critical Tribological Parameters in an Industrial Case Study of Progressive Die Sequence Production

DEFF Research Database (Denmark)

Üstünyagiz, Esmeray; Nielsen, Chris V.; Bay, Niels

the tribologically critical parameters in an industrial production line in which a progressive tool sequence is used. The current industrial case is based on multistage deep drawing followed by an ironing operation. Severe reduction in the ironing stage leads to high interface temperature and pressure. As a result......, subsequent lubricant film breakdown in the production line occurs. The methodology combines finite element simulations and experimental measurements to determine tribological parameters which will later be used in laboratory testing of possible tribology systems....

Effect of Machining Velocity in Nanoscale Machining Operations

International Nuclear Information System (INIS)

Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

2015-01-01

The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

Benchmark assemblies of the Los Alamos critical assemblies facility

International Nuclear Information System (INIS)

Dowdy, E.J.

1986-01-01

Several critical assemblies of precisely known materials composition and easily calculated and reproducible geometries have been constructed at the Los Alamos National Laboratory. Some of these machines, notably Jezebel, Flattop, Big Ten, and Godiva, have been used as benchmark assemblies for the comparison of the results of experimental measurements and computation of certain nuclear reaction parameters. These experiments are used to validate both the input nuclear data and the computational methods. The machines and the applications of these machines for integral nuclear data checks are described. (author)

Benchmark assemblies of the Los Alamos Critical Assemblies Facility

International Nuclear Information System (INIS)

Dowdy, E.J.

1985-01-01

Several critical assemblies of precisely known materials composition and easily calculated and reproducible geometries have been constructed at the Los Alamos National Laboratory. Some of these machines, notably Jezebel, Flattop, Big Ten, and Godiva, have been used as benchmark assemblies for the comparison of the results of experimental measurements and computation of certain nuclear reaction parameters. These experiments are used to validate both the input nuclear data and the computational methods. The machines and the applications of these machines for integral nuclear data checks are described

Benchmark assemblies of the Los Alamos critical assemblies facility

International Nuclear Information System (INIS)

Dowdy, E.J.

1985-01-01

Several critical assemblies of precisely known materials composition and easily calculated and reproducible geometries have been constructed at the Los Alamos National Laboratory. Some of these machines, notably Jezebel, Flattop, Big Ten, and Godiva, have been used as benchmark assemblies for the comparison of the results of experimental measurements and computation of certain nuclear reaction parameters. These experiments are used to validate both the input nuclear data and the computational methods. The machines and the applications of these machines for integral nuclear data checks are described

ISABELLE: a progress report

Energy Technology Data Exchange (ETDEWEB)

Hahn, H

1980-01-01

This paper discusses the ISABELLE project, which has the objective of constructing a high-energy proton colliding beam facility at Brookhaven National Laboratory. The major technical features of the intersecting storage accelerators with their projected performance are described. Application of over 1000 superconducting magnets in the two rings represents the salient characteristic of the machine. The status of the entire project, the technical progress made so far, and difficulties encountered are reviewed.

ISABELLE: a progress report

International Nuclear Information System (INIS)

Hahn, H.

1980-01-01

This paper discusses the ISABELLE project, which has the objective of constructing a high-energy proton colliding beam facility at Brookhaven National Laboratory. The major technical features of the intersecting storage accelerators with their projected performance are described. Application of over 1000 superconducting magnets in the two rings represents the salient characteristic of the machine. The status of the entire project, the technical progress made so far, and difficulties encountered are reviewed

Biological formal counterparts of logical machines

Energy Technology Data Exchange (ETDEWEB)

Moreno-diaz, R; Hernandez Guarch, F

1983-01-01

The significance of the McCulloch-Pitts formal neural net theory (1943) is still nowadays frequently misunderstood, and their basic units are wrongly considered as factual models for neurons. As a consequence, the whole original theory and its later addenda are unreasonably criticized for their simplicity. But, as it was proved then and since, the theory is after the modular neurophysiological counterpart of logical machines, so that it actually provides biologically plausible models for automata, turing machines, etc., and not vice versa. In its true context, no theory has surpassed its proposals. In McCulloch and Pitts memoriam and for the sake of future theoretical research, the authors stress this important historical point, including also some recent results on the neurophysiological counterparts of modular arbitrary probabilistic automata. 16 references.

Building machines that learn and think like people.

Science.gov (United States)

Lake, Brenden M; Ullman, Tomer D; Tenenbaum, Joshua B; Gershman, Samuel J

2017-01-01

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.

Machine Learning of Multi-Modal Influences on Airport Delays, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We build machine learning capabilities that enables improved prediction of off-block times and wheels up times which are critical inputs to NAS stakeholders. NextGen...

25 CFR 542.13 - What are the minimum internal control standards for gaming machines?

Science.gov (United States)

2010-04-01

... system shall be appropriately documented. (2) [Reserved] (k) In-house progressive gaming machine... provide positive ID for cash withdrawal transactions at the cashier stations. (p) Smart cards. All smart...

Molecular and metabolic pattern classification for detection of brain glioma progression

Energy Technology Data Exchange (ETDEWEB)

Imani, Farzin, E-mail: imanif@upmc.edu [Department of Radiology, University of Pittsburgh Medical Center, PA (United States); Boada, Fernando E. [Department of Radiology, University of Pittsburgh Medical Center, PA (United States); Lieberman, Frank S. [Department of Neurology, University of Pittsburgh Medical Center, PA (United States); Davis, Denise K.; Mountz, James M. [Department of Radiology, University of Pittsburgh Medical Center, PA (United States)

2014-02-15

Objectives: The ability to differentiate between brain tumor progression and radiation therapy induced necrosis is critical for appropriate patient management. In order to improve the differential diagnosis, we combined fluorine-18 2-fluoro-deoxyglucose positron emission tomography ({sup 18}F-FDG PET), proton magnetic resonance spectroscopy ({sup 1}H MRS) and histological data to develop a multi-parametric machine-learning model. Methods: We enrolled twelve post-therapy patients with grade 2 and 3 gliomas that were suspicious of tumor progression. All patients underwent {sup 18}F-FDG PET and {sup 1}H MRS. Maximal standardized uptake value (SUVmax) of the tumors and reference regions were obtained. Multiple 2D maps of choline (Cho), creatine (Cr), and N-acetylaspartate (NAA) of the tumors were generated. A support vector machine (SVM) learning model was established to take imaging biomarkers and histological data as input vectors. A combination of clinical follow-up and multiple sequential MRI studies served as the basis for assessing the clinical outcome. All vector combinations were evaluated for diagnostic accuracy and cross validation. The optimal cutoff value of individual parameters was calculated using Receiver operating characteristic (ROC) plots. Results: The SVM and ROC analyses both demonstrated that SUVmax of the lesion was the most significant single diagnostic parameter (75% accuracy) followed by Cho concentration (67% accuracy). SVM analysis of all paired parameters showed SUVmax and Cho concentration in combination could achieve 83% accuracy. SUVmax of the lesion paired with SUVmax of the white matter as well as the tumor Cho paired with the tumor Cr both showed 83% accuracy. These were the most significant paired diagnostic parameters of either modality. Combining all four parameters did not improve the results. However, addition of two more parameters, Cho and Cr of brain parenchyma contralateral to the tumor, increased the accuracy to 92

Applications of machine learning in cancer prediction and prognosis.

Science.gov (United States)

Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

Directory of Open Access Journals (Sweden)

Cai Wingfield

2017-09-01

Full Text Available There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG, generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.

Man-machine interface requirements - advanced technology

Science.gov (United States)

Remington, R. W.; Wiener, E. L.

1984-01-01

Research issues and areas are identified where increased understanding of the human operator and the interaction between the operator and the avionics could lead to improvements in the performance of current and proposed helicopters. Both current and advanced helicopter systems and avionics are considered. Areas critical to man-machine interface requirements include: (1) artificial intelligence; (2) visual displays; (3) voice technology; (4) cockpit integration; and (5) pilot work loads and performance.

Robotic refueling machine

International Nuclear Information System (INIS)

Challberg, R.C.; Jones, C.R.

1996-01-01

One of the longest critical path operations performed during the outage is removing and replacing the fuel. A design is currently under development for a refueling machine which would allow faster, fully automated operation and would also allow the handling of two fuel assemblies at the same time. This design is different from current designs, (a) because of its lighter weight, making increased acceleration and speed possible, (b) because of its control system which makes locating the fuel assembly more dependable and faster, and (c) because of its dual handling system allowing simultaneous fuel movements. The new design uses two robotic arms to span a designated area of the vessel and the fuel storage area. Attached to the end of each robotic arm is a lightweight telescoping mast with a pendant attached to the end of each mast. The pendant acts as the base unit, allowing attachment of any number of end effectors depending on the servicing or inspection operation. Housed within the pendant are two television cameras used for the positioning control system. The control system is adapted from the robotics field using the technology known as machine vision, which provides both object and character recognition techniques to enable relative position control rather than absolute position control as in past designs. The pendant also contains thrusters that are used for fast, short distance, precise positioning. The new refueling machine system design is capable of a complete off load and reload of an 872 element core in about 5.3 days compared to 13 days for a conventional system

Scaling of the critical free length for progressive unfolding of self-bonded graphene

Energy Technology Data Exchange (ETDEWEB)

Kwan, Kenny; Cranford, Steven W., E-mail: s.cranford@neu.edu [Laboratory of Nanotechnology in Civil Engineering (NICE), Department of Civil and Environmental Engineering, Northeastern University, 400 Snell Engineering, 360 Huntington Avenue, Boston, Massachusetts 02115 (United States)

2014-05-19

Like filled pasta, rolled or folded graphene can form a large nanocapsule surrounding a hollow interior. Use as a molecular carrier, however, requires understanding of the opening of such vessels. Here, we investigate a monolayer sheet of graphene as a theoretical trial platform for such a nanocapsule. The graphene is bonded to itself via aligned disulfide (S-S) bonds. Through theoretical analysis and atomistic modeling, we probe the critical nonbonded length (free length, L{sub crit}) that induces fracture-like progressive unfolding as a function of folding radius (R{sub i}). We show a clear linear scaling relationship between the length and radius, which can be used to determine the necessary bond density to predict mechanical opening/closing. However, stochastic dissipated energy limits any exact elastic formulation, and the required energy far exceeds the dissociation energy of the S-S bond. We account for the necessary dissipated kinetic energy through a simple scaling factor (Ω), which agrees well with computational results.

Advancing Critical Learning and Public Good in progressive education

DEFF Research Database (Denmark)

Svensson, Christian Franklin

A problem-oriented approach presents challenges for some students not previously trained in thinking critically. However, when dealing with actual social challenges it becomes clear for most that there are no simple solutions, and therefore developing social indignation and a critical edge...

Machine for development impact tests in sports seats and similar

International Nuclear Information System (INIS)

Gonçalves, R M

2015-01-01

This paper describes the stages of development of a machine to perform impact tests in sport seats, seats for spectators and multiple seats. This includes reviews and recommendations for testing laboratories that have needs similar to the laboratory where unfolded this process.The machine was originally developed seeking to meet certain impact tests in accordance with the NBR15925 standards; 15878 and 16031. The process initially included the study of the rules and the election of the tests for which the machine could be developed and yet all reports and outcome of interaction with service providers and raw materials.For operating facility, it was necessary to set entirely the machine control, which included the concept of dialogue with operator, the design of the menu screens and the procedures for submission and registration of results. To ensure reliability in the process, the machine has been successfully calibrated according to the requirements of the Brazilian network of calibration.The criticism to this enterprise covers the technical and economic aspects involved and points out the main obstacles that were needed to overcome. (paper)

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

CERN: LHC progress

International Nuclear Information System (INIS)

Anon.

1993-01-01

The push for CERN's next major project, the LHC proton collider to be built in the 27-kilometre LEP tunnel, is advancing on a wide front. For the machine itself, there has been considerable progress in the detailed design. While the main thrust is for proton-proton collisions, heavy ions are also on the LHC collision menu. On the experimental side, proposals are coming into sharper focus. For the machine, the main aim is for the highest possible proton collision energies and collision rates in the confines of the existing LEP tunnel, and the original base design looked to achieve these goals in three collision regions. Early discussions on the experimental programme quickly established that the most probable configuration would have two collision regions rather than three. This, combined with hints that the electronics of several detectors would have to handle several bunch crossings at a time, raised the question whether the originally specified bunch spacing of 15 ns was still optimal

The use of holographic and diffractive optics for optimized machine vision illumination for critical dimension inspection

Science.gov (United States)

Lizotte, Todd E.; Ohar, Orest

2004-02-01

Illuminators used in machine vision applications typically produce non-uniform illumination onto the targeted surface being observed, causing a variety of problems with machine vision alignment or measurement. In most circumstances the light source is broad spectrum, leading to further problems with image quality when viewed through a CCD camera. Configured with a simple light bulb and a mirrored reflector and/or frosted glass plates, these general illuminators are appropriate for only macro applications. Over the last 5 years newer illuminators have hit the market including circular or rectangular arrays of high intensity light emitting diodes. These diode arrays are used to create monochromatic flood illumination of a surface that is to be inspected. The problem with these illumination techniques is that most of the light does not illuminate the desired areas, but broadly spreads across the surface, or when integrated with diffuser elements, tend to create similar shadowing effects to the broad spectrum light sources. In many cases a user will try to increase the performance of these illuminators by adding several of these assemblies together, increasing the intensity or by moving the illumination source closer or farther from the surface being inspected. In this case these non-uniform techniques can lead to machine vision errors, where the computer machine vision may read false information, such as interpreting non-uniform lighting or shadowing effects as defects. This paper will cover a technique involving the use of holographic / diffractive hybrid optical elements that are integrated into standard and customized light sources used in the machine vision industry. The bulk of the paper will describe the function and fabrication of the holographic/diffractive optics and how they can be tailored to improve illuminator design. Further information will be provided a specific design and examples of it in operation will be disclosed.

Advanced Turbine Systems (ATS) program conceptual design and product development. Quarterly progress report, December 1, 1995--February 29, 1996

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-06-01

This report describes the overall program status of the General Electric Advanced Gas Turbine Development program, and reports progress on three main task areas. The program is focused on two specific products: (1) a 70-MW class industrial gas turbine based on the GE90 core technology, utilizing a new air cooling methodology; and (2) a 200-MW class utility gas turbine based on an advanced GE heavy-duty machine, utilizing advanced cooling and enhancement in component efficiency. The emphasis for the industrial system is placed on cycle design and low emission combustion. For the utility system, the focus is on developing a technology base for advanced turbine cooling while achieving low emission combustion. The three tasks included in this progress report are on: conversion to a coal-fueled advanced turbine system, integrated program plan, and design and test of critical components. 13 figs., 1 tab.

Pelletron progress report, July 1 1978 - June 30 1979

International Nuclear Information System (INIS)

1979-01-01

Progress is reported in research by the University of Melbourne Pelletron Accelerator Group. Areas covered include lifetime determination of nuclear states, reaction studies and nuclear astrophysics, elemental microanalysis and depth profiling and a report on the pelletron machine

Environmentally Friendly Machining

CERN Document Server

Dixit, U S; Davim, J Paulo

2012-01-01

Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

Relevance as a metric for evaluating machine learning algorithms

NARCIS (Netherlands)

Kota Gopalakrishna, A.; Ozcelebi, T.; Liotta, A.; Lukkien, J.J.

2013-01-01

In machine learning, the choice of a learning algorithm that is suitable for the application domain is critical. The performance metric used to compare different algorithms must also reflect the concerns of users in the application domain under consideration. In this work, we propose a novel

A Critical Review on the Effect of Docosahexaenoic Acid (DHA) on Cancer Cell Cycle Progression.

Science.gov (United States)

Newell, Marnie; Baker, Kristi; Postovit, Lynne M; Field, Catherine J

2017-08-17

Globally, there were 14.1 million new cancer diagnoses and 8.2 million cancer deaths in 2012. For many cancers, conventional therapies are limited in their successes and an improved understanding of disease progression is needed in conjunction with exploration of alternative therapies. The long chain polyunsaturated fatty acid, docosahexaenoic acid (DHA), has been shown to enhance many cellular responses that reduce cancer cell viability and decrease proliferation both in vitro and in vivo. A small number of studies suggest that DHA improves chemotherapy outcomes in cancer patients. It is readily incorporated into cancer cell membranes and, as a result there has been considerable research regarding cell membrane initiated events. For example, DHA has been shown to mediate the induction of apoptosis/reduction of proliferation in vitro and in vivo. However, there is limited research into the effect of DHA on cell cycle regulation in cancer cells and the mechanism(s) by which DHA acts are not fully understood. The purpose of the current review is to provide a critical examination of the literature investigating the ability of DHA to stall progression during different cell cycle phases in cancer cells, as well as the consequences that these changes may have on tumour growth, independently and in conjunction with chemotherapy.

Informatics and machine learning to define the phenotype.

Science.gov (United States)

Basile, Anna Okula; Ritchie, Marylyn DeRiggi

2018-03-01

For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.

Support vector machine for automatic pain recognition

Science.gov (United States)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

A survey on Barrett's esophagus analysis using machine learning.

Science.gov (United States)

de Souza, Luis A; Palm, Christoph; Mendel, Robert; Hook, Christian; Ebigbo, Alanna; Probst, Andreas; Messmann, Helmut; Weber, Silke; Papa, João P

2018-05-01

This work presents a systematic review concerning recent studies and technologies of machine learning for Barrett's esophagus (BE) diagnosis and treatment. The use of artificial intelligence is a brand new and promising way to evaluate such disease. We compile some works published at some well-established databases, such as Science Direct, IEEEXplore, PubMed, Plos One, Multidisciplinary Digital Publishing Institute (MDPI), Association for Computing Machinery (ACM), Springer, and Hindawi Publishing Corporation. Each selected work has been analyzed to present its objective, methodology, and results. The BE progression to dysplasia or adenocarcinoma shows a complex pattern to be detected during endoscopic surveillance. Therefore, it is valuable to assist its diagnosis and automatic identification using computer analysis. The evaluation of the BE dysplasia can be performed through manual or automated segmentation through machine learning techniques. Finally, in this survey, we reviewed recent studies focused on the automatic detection of the neoplastic region for classification purposes using machine learning methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Machine learning for epigenetics and future medical applications.

Science.gov (United States)

Holder, Lawrence B; Haque, M Muksitul; Skinner, Michael K

2017-07-03

Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review.

Materiality of a simulation: Scratch reading machine, 1931

Directory of Open Access Journals (Sweden)

Craig Saper

2009-12-01

Full Text Available Using Bob Brown's reading machine and the prepared texts for his machine, called readies, both designed in 1930, as an example of scratch turntablist techniques, suggests an alternative to narrow definitions of literacy and new ways to appreciate the history of scratch techniques. Brown's machine resembles the turntablist’s ability to rapidly shift reading (its direction, speed, and repetition rather than slowly flipping the pages of a book. Punctuation marks, in the readies, become visual analogies. For movement we see em-dashes (— that also, by definition, indicate that the sentence was interrupted or cut short. The old uses of punctuation, such as employment of periods to mark the end of a sentence, disappear. The result looks like a script for a turntablist’s performance, and dj Herc starts to sound like a reading teacher. An online simulation of Brown's machine, http://www.readies.org, reproduce, or approximate, the motion, scratch, jerking, flickering, and visual effects produced or illuminated with the machine. Those supplemental aspects of reading are always already part of reading. The supplement (movement, visuality, mechanicity to traditional notions of literacy usually remain part of an implicate process. The reading machine and scratch techniques are not simply a new conduit for the same supposedly natural process. The scratch reading highlights what Jacques Derrida calls the "virtual multimedia" (of reading print on paper. The increasing prevalence, even omnipresent and [to some critics] epidemic, use of text(ing machines, something outside or beside traditional literacy, the scratch-meaning becomes foregrounded. Brown's machine puts the natural process of reading under erasure or scratch (simply by adjusting the speed, direction, and layout. dj Herc did the same for music.

Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques

Science.gov (United States)

Tellaeche, A.; Arana, R.; Ibarguren, A.; Martínez-Otzeta, J. M.

The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

Applications of Machine Learning in Cancer Prediction and Prognosis

Directory of Open Access Journals (Sweden)

Joseph A. Cruz

2006-01-01

Full Text Available Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25% improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Boosting Economic Growth Through Advanced Machine Vision

OpenAIRE

MAAD, Soha; GARBAYA, Samir; AYADI, Nizar; BOUAKAZ, Saida

2012-01-01

In this chapter, we overview the potential of machine vision and related technologies in various application domains of critical importance for economic growth and prospect. Considered domains include healthcare, energy and environment, finance, and industrial innovation. Visibility technologies considered encompass augmented and virtual reality, 3D technologies, and media content authoring tools and technologies. We overview the main challenges facing the application domains and discuss the ...

Machine Learning-based Transient Brokers for Real-time Classification of the LSST Alert Stream

Science.gov (United States)

Narayan, Gautham; Zaidi, Tayeb; Soraisam, Monika; ANTARES Collaboration

2018-01-01

The number of transient events discovered by wide-field time-domain surveys already far outstrips the combined followup resources of the astronomical community. This number will only increase as we progress towards the commissioning of the Large Synoptic Survey Telescope (LSST), breaking the community's current followup paradigm. Transient brokers - software to sift through, characterize, annotate and prioritize events for followup - will be a critical tool for managing alert streams in the LSST era. Developing the algorithms that underlie the brokers, and obtaining simulated LSST-like datasets prior to LSST commissioning, to train and test these algorithms are formidable, though not insurmountable challenges. The Arizona-NOAO Temporal Analysis and Response to Events System (ANTARES) is a joint project of the National Optical Astronomy Observatory and the Department of Computer Science at the University of Arizona. We have been developing completely automated methods to characterize and classify variable and transient events from their multiband optical photometry. We describe the hierarchical ensemble machine learning algorithm we are developing, and test its performance on sparse, unevenly sampled, heteroskedastic data from various existing observational campaigns, as well as our progress towards incorporating these into a real-time event broker working on live alert streams from time-domain surveys.

Survey of the problems posed by the man-machine interface, as seen from the angle of facility operators

International Nuclear Information System (INIS)

Heinbuch, R.

1995-01-01

The man-machine interface in nuclear power plants is an area very much influenced by the vigorous progress in computer technology. The paper describes the causes underlying the innovative power in this field and its impacts on the man-machine interface in nuclear power plants. The benefits brought by the advanced computer systems in the design of the man-machine interface as well as the problems posed through application in practice to safety-relevant plant systems are discussed, and examples are given showing the experience accumulated so far, and the significant changes effected in the man-machine interface. (orig.) [de

Towards freeform curved blazed gratings using diamond machining

Science.gov (United States)

Bourgenot, C.; Robertson, D. J.; Stelter, D.; Eikenberry, S.

2016-07-01

Concave blazed gratings greatly simplify the architecture of spectrographs by reducing the number of optical components. The production of these gratings using diamond-machining offers practically no limits in the design of the grating substrate shape, with the possibility of making large sag freeform surfaces unlike the alternative and traditional method of holography and ion etching. In this paper, we report on the technological challenges and progress in the making of these curved blazed gratings using an ultra-high precision 5 axes Moore-Nanotech machine. We describe their implementation in an integral field unit prototype called IGIS (Integrated Grating Imaging Spectrograph) where freeform curved gratings are used as pupil mirrors. The goal is to develop the technologies for the production of the next generation of low-cost, compact, high performance integral field unit spectrometers.

Risk management for operations of the LANL Critical Experiments Facility

International Nuclear Information System (INIS)

Paternoster, R.; Butterfield, K.

1998-01-01

The Los Alamos Critical Experiments Facility (LACEF) currently operates two burst reactors (Godiva-IV and Skua), one solution assembly [the Solution High-Energy Burst Assembly (SHEBA)], two fast-spectrum benchmark assemblies (Flattop and Big Ten), and five general-purpose remote assembly machines that may be configured with nuclear materials and assembled by remote control. Special nuclear materials storage vaults support these and other operations at the site. With this diverse set of operations, several approaches are possible in the analysis and management of risk. The most conservative approach would be to write a safety analysis report (SAR) for each assembly and experiment. A more cost-effective approach is to analyze the probability and consequences of several classes of operations representative of operations on each critical assembly machine and envelope the bounding case accidents. Although the neutron physics of these machines varies widely, the operations performed at LACEF fall into four operational modes: steady-state mode, approach-to-critical mode, prompt burst mode, and nuclear material operations, which can include critical assembly fuel loading. The operational sequences of each mode are very nearly identical, whether operated on one assembly machine or another. The use of an envelope approach to accident analysis is facilitated by the use of classes of operations and the use of bounding case consequence analysis. A simple fault tree analysis of operational modes helps resolve which operations are sensitive to human error and which are initiated by hardware of software failures. Where possible, these errors and failures are blocked by TSR LCOs. Future work will determine the probability of accidents with various initiators

Machine learning in cardiovascular medicine: are we there yet?

Science.gov (United States)

Shameer, Khader; Johnson, Kipp W; Glicksberg, Benjamin S; Dudley, Joel T; Sengupta, Partho P

2018-01-19

Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encompassing several terms like machine learning, cognitive learning, deep learning and reinforcement learning-based methods that can be used to integrate and interpret complex biomedical and healthcare data in scenarios where traditional statistical methods may not be able to perform. In this review article, we discuss the basics of machine learning algorithms and what potential data sources exist; evaluate the need for machine learning; and examine the potential limitations and challenges of implementing machine in the context of cardiovascular medicine. The most promising avenues for AI in medicine are the development of automated risk prediction algorithms which can be used to guide clinical care; use of unsupervised learning techniques to more precisely phenotype complex disease; and the implementation of reinforcement learning algorithms to intelligently augment healthcare providers. The utility of a machine learning-based predictive model will depend on factors including data heterogeneity, data depth, data breadth, nature of modelling task, choice of machine learning and feature selection algorithms, and orthogonal evidence. A critical understanding of the strength and limitations of various methods and tasks amenable to machine learning is vital. By leveraging the growing corpus of big data in medicine, we detail pathways by which machine learning may facilitate optimal development of patient-specific models for improving diagnoses, intervention and outcome in cardiovascular medicine. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Risk management for operations of the Los Alamos critical experiments facility

International Nuclear Information System (INIS)

Paternoster, R.; Butterfield, K.

1998-01-01

The Los Alamos Critical Experiments Facility (LACEF) currently operates two burst reactors (Godiva-IV and Skua), one solution assembly (SHEBA 2--Solution high-Energy Burst Assembly), two fast-spectrum benchmark assemblies (Flattop and Big Ten), and five general-purpose remote assembly machines which may be configured with nuclear materials and assembled by remote control. SNM storage vaults support these and other operations at the site. With this diverse set of operations, several approaches are possible in the analysis and management of risk. The most conservative approach would be to write a safety analysis report (SAR) for each assembly and experiment. A more cost-effective approach is to analyze the probability and consequences of several classes of operations representative of operations on each critical assembly machine and envelope the bounding case accidents. Although the neutron physics of these machines varies widely, the operations performed at LACEF fall into four operational modes: steady-state mode, approach-to-critical mode, prompt burst mode, and nuclear material operations which can include critical assembly fuel loading. The operational sequences of each mode are very nearly the same, whether operated on one assembly machine or another. The use of an envelope approach to accident analysis is facilitated by the use of classes of operations and the use of bounding case consequence analysis. A simple fault tree analysis of operational modes helps resolve which operations are sensitive to human error and which are initiated by hardware of software failures. Where possible, these errors and failures are blocked by TSR LCOs

Assessing Progress in Mastery of Counseling Communication Skills

NARCIS (Netherlands)

A.J. Kuntze (Jeroen)

2009-01-01

textabstractDuring the last century the attention paid in higher education to the development of professional skills has progressively increased. In the first half of the last century the term ‘skill’ mainly referred to motor or technical actions, for instance driving a car or operating a machine

Machine learning applications in cancer prognosis and prediction.

Science.gov (United States)

Kourou, Konstantina; Exarchos, Themis P; Exarchos, Konstantinos P; Karamouzis, Michalis V; Fotiadis, Dimitrios I

2015-01-01

Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of machine learning (ML) methods. Therefore, these techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. In addition, the ability of ML tools to detect key features from complex datasets reveals their importance. A variety of these techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) have been widely applied in cancer research for the development of predictive models, resulting in effective and accurate decision making. Even though it is evident that the use of ML methods can improve our understanding of cancer progression, an appropriate level of validation is needed in order for these methods to be considered in the everyday clinical practice. In this work, we present a review of recent ML approaches employed in the modeling of cancer progression. The predictive models discussed here are based on various supervised ML techniques as well as on different input features and data samples. Given the growing trend on the application of ML methods in cancer research, we present here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes.

Engineering artificial machines from designable DNA materials for biomedical applications.

Science.gov (United States)

Qi, Hao; Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng; Wang, Lin

2015-06-01

Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications.

JT-60 power tests from mechanical and thermal viewpoints of tokamak machine

International Nuclear Information System (INIS)

Takatsu, H.; Yamamoto, M.; Ohkubo, M.

1986-01-01

JT-60 power tests were carried out, to demonstrate, in advance of actual plasma operation, satisfactory performance of the tokamak machine, power suppliers and control system in combination. The tests began with low power ones of individual coil systems, progressed to full power ones and concluded successfully. The present paper describes the principal results of JT-60 power tests from mechanical and thermal viewpoints of tokamak machine. All of the coil systems were raised up to full power operation in combination and system performance was verified including thermal and mechanical integrity of tokamak machine. Measured strain and displacement showed good agreements with those predicted in the design, which was an evidence that electromagnetic loads were supported adequately as expected in the design. Vibration of the vacuum vessel was found to be large up to 48 m/s/sup 2/ and caused excessive vibration of the lateral port gate-valves. A few limitations to machine operation were also made clear quantatively

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

Science.gov (United States)

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

2018-03-01

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

University of Florida, University research program in robotics. Annual technical progress report

International Nuclear Information System (INIS)

Crane, C.D. III; Tulenko, J.S.

1994-05-01

Progress is reported in the areas of environmental hardening, database, world modeling, vision, man-machine interface, advanced liquid metal reactor inspection robot, and articulated transporter/manipulator system (ATMS) development

University of Florida, University research program in robotics. Annual technical progress report

Energy Technology Data Exchange (ETDEWEB)

Crane, C.D. III; Tulenko, J.S.

1994-05-01

Progress is reported in the areas of environmental hardening, database, world modeling, vision, man-machine interface, advanced liquid metal reactor inspection robot, and articulated transporter/manipulator system (ATMS) development.

Protection of Mission-Critical Applications from Untrusted Execution Environment: Resource Efficient Replication and Migration of Virtual Machines

Science.gov (United States)

2015-09-28

in the same LAN ; this setup resembles the typical setup in a virtualized datacenter where protected and backup hosts are connected by an internal LAN ... Virtual Machines 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-10-1-0393 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Kang G. Shin 5d. PROJECT...Distribution A - Approved for Public Release 13. SUPPLEMENTARY NOTES None 14. ABSTRACT Continuous replication and live migration of Virtual Machines (VMs

Machine terms dictionary

Energy Technology Data Exchange (ETDEWEB)

NONE

1979-04-15

This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

JET Joint Undertaking. Progress report 1991 - volume 1

International Nuclear Information System (INIS)

1992-04-01

The ninth JET Progress Report provides an overview summary and puts into context the scientific and technical advances made on JET during 1991. The report contains a brief summary of the background to the project, and describes the basic objectives of JET and the principal design aspects of the machine

Intellectual Control System of Processing on CNC Machines

OpenAIRE

Nekrasov, R. Y.; Lasukov, Aleksandr Aleksandrovich; Starikov, A. I.; Soloviev, I. V.; Bekareva, O. V.

2016-01-01

Scientific and technical progress makes great demands for quality of engineering production. The priority is to ensure metalworking equipment with required dimensional accuracy during the entire period of operation at minimum manufacturing costs. In article considered the problem of increasing of accuracy of processing products on CNC. The authors offers a solution to the problem by providing compensating adjustment in the trajectory of the cutting tool and machining mode. The necessity of cr...

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

Science.gov (United States)

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.

Design of Smooth Ramp Feedrate for Machining Complex NURBS Paths

Science.gov (United States)

Sekar, M.; Suresha, B.; Kantharaj, I.

2017-10-01

The feedrate scheduling algorithms proposed in this work permit the complex NURBS tool paths to be traversed quickly in those areas not limited by dynamic constraints, but slowdown in critical areas just enough to keep the machine within its dynamic limits and the specified tolerance zone. Due to the typically improved path tracking performance, surface finish can improve greatly, reducing the need for secondary finishing operations such as polishing. This work implements the Acceleration Deceleration Before Interpolation (ADBI) approach which is desired in modern CNC controller design and high speed machining of complex micro profiles common in Aerospace applications.

The Machine as Art (in the 20th Century: An Introduction

Directory of Open Access Journals (Sweden)

Juliette Bessette

2018-01-01

Full Text Available The machine, over the course of the 20th century, progressively integrated itself into all fields of human activity, including artistic creation; and indeed, with the first decades of that century having established a surprisingly vital and wide-ranging series of perspectives on the relationship between art and the machine, certain artists in the wake of the Second World War no longer felt compelled to treat the machine as a mere theme or source of inspiration: the machine itself becomes art—unless it is art which seeks to become mechanical? The artist mutates into “artist-engineer”; and this transition, resonating within a specific historical context, leads not only to a questioning of the nature of the work itself, but also to a broader questioning which places us within the realm of anthropology: what is this art telling us about the actual conditions of contemporary human society, and what is it telling us about the future to which we aspire? It is the goal of this special issue of Arts to stimulate an historically conscious, protean, and global (rethinking of the cultural relationship between man and machine; and to this end, we welcome contributions falling anywhere within the nearly infinite spectrum represented by the prismatic period during the middle of the last century in which the machine became a legitimate artistic medium.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Science.gov (United States)

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Directory of Open Access Journals (Sweden)

Cai Huang

Full Text Available Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM algorithm combined with a standard recursive feature elimination (RFE approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60. The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

Some relations between quantum Turing machines and Turing machines

OpenAIRE

Sicard, Andrés; Vélez, Mario

1999-01-01

For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

SEAMLESS TECHNOLOGY ON CIRCULAR KNITTING MACHINES

Directory of Open Access Journals (Sweden)

CRETU Viorica

2014-05-01

Full Text Available With industrial progress, the advancements in garment manufacturing have evolved from cut & sew to complete garment knitting, which produces one entire garment without sewing or linking process. Seamless knitting technology is similar to sock manufacture, the specialized circular knitting machines producing 3 dimensional garments with no side seams, with the waistband integrated with body of the garment and with knitted washing instructions and logos. The paper starts by presenting the main advantages of seamless garments but also some limitations because the technology. Because for a seamless garment, which is realized as a knitted tub, is very important to ensure the required final chest size, it was presented the main components involved: the knitting machine, the garment design and the yarns used. The knitting machines, beside the values of diameters and gauges with a great impact on the chest size, are characterized by a very innovative and complex construction. The design of a seamless garment is fundamental different compared to garments produced on a traditional way because the designer must to work backwards from a finished garment to create the knitting programme that will ultimately give the correct finished size. On the end of the paper it was presented some of the applications of the seamless products that cover intimate apparel and other bodywear, outwear, activewear and functional sportswear, upholstery, industrial, automotive and medical textiles.

When Progressive Disease Does Not Mean Treatment Failure: Reconsidering the Criteria for Progression

Science.gov (United States)

2012-01-01

Although progression-based endpoints, such as progression-free survival, are often key clinical trial endpoints for anticancer agents, the clinical meaning of “objective progression” is much less certain. As scrutiny of progression-based endpoints in clinical trials increases, it should be remembered that the Response Evaluation Criteria In Solid Tumors (RECIST) progression criteria were not developed as a surrogate for survival. Now that progression-free survival has come to be an increasingly important trial endpoint, the criteria that define progression deserve critical evaluation to determine whether alternate definitions of progression might facilitate the development of stronger surrogate endpoints and more meaningful trial results. In this commentary, we review the genesis of the criteria for progression, highlight recent data that question their value as a marker of treatment failure, and advocate for several research strategies that could lay the groundwork for a clinically validated definition of disease progression in solid tumor oncology. PMID:22927506

ANALYSIS OF PARAMETERS AFFECTING THE QUALITY OF A CUTTING MACHINE

Directory of Open Access Journals (Sweden)

Iveta Onderová

2014-02-01

Full Text Available The quality of cutting machines is affected by several factors that can be directly or indirectly influenced by manufacturers, technicians and users of machine tools. The most critical qualitative evaluation parameters of machine tools include accuracy and stability. Investigations of accuracy and repeatable positioning accuracy were essential for the research presented in this paper. The aim was to develop and experimentally verify the design of a methodology for cutting centers aimed at achieving the desired working precision. Before working on the topic described here, it was necessary to make several scientific analyses, which are summarized in this paper. We can build on the initial working hypothesis that by improving the technological parameters (e.g. by increasing the working speed of the machine, or by improving the precision of the positioning the quality of the cutting machine will also be improved. For the purposes of our study, several investigated parameters were set affecting positioning accuracy, such as rigidity, positioning speed, etc. First, the stiffness of the portal structure of the cutting machine was analyzed. FEM analysis was used to investigate several alternative structures of the cutting machine, and also an innovative solution for beam mounting. The second step was to integrate two types of drives into the design of the cutting machine. The first drive is a classic rack and pinion drive for cutting machines. To increase (improve the working speed of the machine, linear motors were designed as an alternative drive. The portal of the cutting machine was designed for a working speed of 260mmin−1 and acceleration of 25 m. s−2. The third step was based on the results of the analysis. In collaboration with Microstep, an experimental cutting machine in a portal version was produced using linear synchronous motors driving the portal on both sides, and with direct linear metering of its position. In the fourth step, an

Model-based setup assistant for progressive tools

Science.gov (United States)

Springer, Robert; Gräler, Manuel; Homberg, Werner; Henke, Christian; Trächtler, Ansgar

2018-05-01

In the field of production systems, globalization and technological progress lead to increasing requirements regarding part quality, delivery time and costs. Hence, today's production is challenged much more than a few years ago: it has to be very flexible and produce economically small batch sizes to satisfy consumer's demands and avoid unnecessary stock. Furthermore, a trend towards increasing functional integration continues to lead to an ongoing miniaturization of sheet metal components. In the industry of electric connectivity for example, the miniaturized connectors are manufactured by progressive tools, which are usually used for very large batches. These tools are installed in mechanical presses and then set up by a technician, who has to manually adjust a wide range of punch-bending operations. Disturbances like material thickness, temperatures, lubrication or tool wear complicate the setup procedure. In prospect of the increasing demand of production flexibility, this time-consuming process has to be handled more and more often. In this paper, a new approach for a model-based setup assistant is proposed as a solution, which is exemplarily applied in combination with a progressive tool. First, progressive tools, more specifically, their setup process is described and based on that, the challenges are pointed out. As a result, a systematic process to set up the machines is introduced. Following, the process is investigated with an FE-Analysis regarding the effects of the disturbances. In the next step, design of experiments is used to systematically develop a regression model of the system's behaviour. This model is integrated within an optimization in order to calculate optimal machine parameters and the following necessary adjustment of the progressive tool due to the disturbances. Finally, the assistant is tested in a production environment and the results are discussed.

Progress report of the critical equipment monitoring system

International Nuclear Information System (INIS)

Pantis, M.J.

1984-01-01

The Philadelphia Electric Company has contracted with Energy Data Systems to develop a Critical Equipment Monitoring System for its Peach Bottom Nuclear Plant. This computerized system is designed to acquire and maintain accurate and timely status information on plant equipment. It will provide auditable record of plant and equipment transactions. Positive equipment identification and location will be provided. Errors in complex logical checking will be minimized. This system should reduce operator loading and improve operator communicatin with the plant personnel. Phase I of this system was installed at Peach Bottom Nuclear Station May 1982. It provides the necessary hardware and software to do check-off lists on critical plant systems. This paper describes some of the start-up and operational problems encountered

High productivity machining of holes in Inconel 718 with SiAlON tools

Science.gov (United States)

Agirreurreta, Aitor Arruti; Pelegay, Jose Angel; Arrazola, Pedro Jose; Ørskov, Klaus Bonde

2016-10-01

Inconel 718 is often employed in aerospace engines and power generation turbines. Numerous researches have proven the enhanced productivity when turning with ceramic tools compared to carbide ones, however there is considerably less information with regard to milling. Moreover, no knowledge has been published about machining holes with this type of tools. Additional research on different machining techniques, like for instance circular ramping, is critical to expand the productivity improvements that ceramics can offer. In this a 3D model of the machining and a number of experiments with SiAlON round inserts have been carried out in order to evaluate the effect of the cutting speed and pitch on the tool wear and chip generation. The results of this analysis show that three different types of chips are generated and also that there are three potential wear zones. Top slice wear is identified as the most critical wear type followed by the notch wear as a secondary wear mechanism. Flank wear and adhesion are also found in most of the tests.

Support vector machine in machine condition monitoring and fault diagnosis

Science.gov (United States)

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.

The position of Ghana on the progressive map of positive mental health: A critical perspective.

Science.gov (United States)

Wilson, Angelina; Somhlaba, Nceba Z

2017-05-01

According to the World Health Organisation (WHO), mental health is a state of well-being and not just the absence of diseases. With this definition, there has been a surge of mental health research, albeit still predominantly in Western countries, which is reflected in contemporary theories on positive mental health that include 'flourishing mental health', 'salutogenesis', and 'fortigenesis'. However, in low- and middle-income countries (LMICs), mental health research is slowly receiving scholarly attention. The aim of this paper was twofold: Firstly, to highlight progress that had been made in some LMICs, giving consideration to research across different settings and populations as a basis to argue for more research on positive mental health in the Ghanaian context. Secondly, to present a critical perspective on the current mental health research trends in Ghana, thus discussing important recommendations for future research.

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

Science.gov (United States)

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Study and implementation high speed operating of induced magnetization machines; Etude et mise en oeuvre de machines a aimantation induite fonctionnant a haute vitesse

Energy Technology Data Exchange (ETDEWEB)

Alhassoun, Y.

2005-05-15

Actually, electromechanical machines are characterized by their low cost and reduced maintenance. Therefore, new types of magnetic materials such as soft magnetic composites (SMC), have to be considered not only for multiple applications (small motors for automotive) for cost reduction, but also when considering other special requirements such as high speed drive (aircraft and space applications). Our report of thesis is articulated around four chapters: The first chapter show the various types of magnetic interactions used in the electromagnetic actuators. The second chapter is devoted to the modelling of the induced magnetic machines by analytical resolution of equations of the field in two dimensions. The third chapter presents the four configurations prototypes of switched reluctance machine which mix the exploitation of laminated materials and the soft magnetic powders. The fourth chapter discusses the critical conditions of this machines operating at high speed. We conclude, insisting on the efforts carried out in term of analytical modelling of the induced magnetization machines for their dimensions and exploited in this same structure, the soft magnetic composite materials. The results show the potential of soft magnetic powders when considering in particular the high frequency losses and their ability to favour the heat dissipation in this structure. (author)

Beam Loss Monitoring for LHC Machine Protection

Science.gov (United States)

Holzer, Eva Barbara; Dehning, Bernd; Effnger, Ewald; Emery, Jonathan; Grishin, Viatcheslav; Hajdu, Csaba; Jackson, Stephen; Kurfuerst, Christoph; Marsili, Aurelien; Misiowiec, Marek; Nagel, Markus; Busto, Eduardo Nebot Del; Nordt, Annika; Roderick, Chris; Sapinski, Mariusz; Zamantzas, Christos

The energy stored in the nominal LHC beams is two times 362 MJ, 100 times the energy of the Tevatron. As little as 1 mJ/cm3 deposited energy quenches a magnet at 7 TeV and 1 J/cm3 causes magnet damage. The beam dumps are the only places to safely dispose of this beam. One of the key systems for machine protection is the beam loss monitoring (BLM) system. About 3600 ionization chambers are installed at likely or critical loss locations around the LHC ring. The losses are integrated in 12 time intervals ranging from 40 μs to 84 s and compared to threshold values defined in 32 energy ranges. A beam abort is requested when potentially dangerous losses are detected or when any of the numerous internal system validation tests fails. In addition, loss data are used for machine set-up and operational verifications. The collimation system for example uses the loss data for set-up and regular performance verification. Commissioning and operational experience of the BLM are presented: The machine protection functionality of the BLM system has been fully reliable; the LHC availability has not been compromised by false beam aborts.

Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

OpenAIRE

Qiu, Daowen

2005-01-01

As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing ma...

Machine Learning for ATLAS DDM Network Metrics

CERN Document Server

Lassnig, Mario; The ATLAS collaboration; Vamosi, Ralf

2016-01-01

The increasing volume of physics data is posing a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from our ongoing automation efforts. First, we describe our framework for distributed data management and network metrics, automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

Critical experiments supporting underwater storage of tightly packed configurations of spent fuel pins. Technical progress report, January 1-March 31, 1981

International Nuclear Information System (INIS)

Hoovler, G.S.; Baldwin, M.N.

1981-04-01

Critical experiments are in progress on arrays of 2 1/2% enriched UO 2 fuel pins simulating underwater pin storage of spent power reactor fuel. Pin storage refers to a spent fuel storage concept in which the fuel assemblies are dismantled and the fuel pins are tightly packed into specially designed canisters. These experiments are providing benchmark data with which to validate nuclear codes used to design spent fuel pin storage racks

LHC Report: machine commissioning - looking good

CERN Document Server

CERN Bulletin

2016-01-01

Since first beam was injected on Friday, 25 March, the recommissioning of the LHC has made good progress.   An event display showing the first collisions after the 2015 year-end technical stop as seen by the CMS experiment. At present, work is being performed with either probe bunches (around 1010 protons per bunch) or single nominal bunches (1.1 x 1011 protons per bunch). This procedure is intended to ensure safe operation before full qualification of the machine protection set-up. Beam has been taken up the ramp to 6.5 TeV and through the squeeze to the planned 2016 operating scenario. The optics (i.e. the global focusing properties of the whole ring) have been measured and corrected to an unprecedented level: there is now excellent agreement between the machine model and the actual LHC. Some preliminary measurements of the global aperture have been performed and there are no apparent bottlenecks. The position of the ULO (Unidentified Lying Object) had been probed and it is in a similar positio...

The analysis of today situation on the market of the agricultural machines

Directory of Open Access Journals (Sweden)

Šárka Stojarová

2007-01-01

Full Text Available The paper is dealing with the analysis of the market of agricultural machines in the Czech Republic. The part of the article is focused on export and import development of agricultural machines between Czech Republic, EU countries and the other countries of the world. The trade balance progress of agricultural machines is analyzed for Czech market as well. In the article the possible opportunities for the Czech exporters, which concern Danish, Spanish, and Polish market, are also emphasized. The part of the analysis is also focused on the area of subsidy policy for Czech agricultural subjects. The analysis of subsidies deals with the opportunity of financial supports by the Czech government and by the European Union. The difference in subsidy policy for Czech Republic before and after the entering the European Union is also mentioned.

Machine tool structures

CERN Document Server

Koenigsberger, F

1970-01-01

Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

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

Directory of Open Access Journals (Sweden)

Mo Yang

2018-03-01

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

High critical temperature superconductors: Progress achieved after two years

International Nuclear Information System (INIS)

Maillard, J.M.; Rammal, R.; Vittorge, M.C.

1989-01-01

Progress concerning the theory of high temperature superconductors and activity of laboratories of the CNRS (France) are reviewed and news on strategy, budgets, theoretical research, materials characterization, fabrication process technology transfers, commercialisation, uses and data bases are given [fr

Studies on Nb3Sn field coils for superconducting machine

International Nuclear Information System (INIS)

Fujino, H.; Nose, S.

1981-01-01

This paper describes experimental studies on several coils wound with multifilamentary (MF) Nb 3 Sn cables with reinforcing strip for superconducting rotating machine application. To use a Nb 3 Sn superconductor to field winding of a rotating machine, several coil performances of pre-reacted, bronze processed and stranded MF Nb 3 Sn cables were investigated, mainly in relation to stress effect. Bending strain up to 0.64% in strand and winding stress of 5 kg/mm 2 have resulted in nondegradation in coil performance. A pair of impregnated race-track coils designed for a 30 MVA synchronous condenser was energized successfully up to 80% of critical current without quench. 8 refs

Cohort: critical science

Science.gov (United States)

Digney, Bruce L.

2007-04-01

Unmanned vehicle systems is an attractive technology for the military, but whose promises have remained largely undelivered. There currently exist fielded remote controlled UGVs and high altitude UAV whose benefits are based on standoff in low complexity environments with sufficiently low control reaction time requirements to allow for teleoperation. While effective within there limited operational niche such systems do not meet with the vision of future military UxV scenarios. Such scenarios envision unmanned vehicles operating effectively in complex environments and situations with high levels of independence and effective coordination with other machines and humans pursing high level, changing and sometimes conflicting goals. While these aims are clearly ambitious they do provide necessary targets and inspiration with hopes of fielding near term useful semi-autonomous unmanned systems. Autonomy involves many fields of research including machine vision, artificial intelligence, control theory, machine learning and distributed systems all of which are intertwined and have goals of creating more versatile broadly applicable algorithms. Cohort is a major Applied Research Program (ARP) led by Defence R&D Canada (DRDC) Suffield and its aim is to develop coordinated teams of unmanned vehicles (UxVs) for urban environments. This paper will discuss the critical science being addressed by DRDC developing semi-autonomous systems.

Electricity of machine tool

International Nuclear Information System (INIS)

Gijeon media editorial department

1977-10-01

This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

Machine medical ethics

CERN Document Server

Pontier, Matthijs

2015-01-01

The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

Routine human-competitive machine intelligence by means of genetic programming

Science.gov (United States)

Koza, John R.; Streeter, Matthew J.; Keane, Martin

2004-01-01

Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Science.gov (United States)

Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

2018-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Machine learning of network metrics in ATLAS Distributed Data Management

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00218873; The ATLAS collaboration; Toler, Wesley; Vamosi, Ralf; Bogado Garcia, Joaquin Ignacio

2017-01-01

The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our m...

Process capability improvement through DMAIC for aluminum alloy wheel machining

Science.gov (United States)

Sharma, G. V. S. S.; Rao, P. Srinivasa; Babu, B. Surendra

2017-07-01

This paper first enlists the generic problems of alloy wheel machining and subsequently details on the process improvement of the identified critical-to-quality machining characteristic of A356 aluminum alloy wheel machining process. The causal factors are traced using the Ishikawa diagram and prioritization of corrective actions is done through process failure modes and effects analysis. Process monitoring charts are employed for improving the process capability index of the process, at the industrial benchmark of four sigma level, which is equal to the value of 1.33. The procedure adopted for improving the process capability levels is the define-measure-analyze-improve-control (DMAIC) approach. By following the DMAIC approach, the C p, C pk and C pm showed signs of improvement from an initial value of 0.66, -0.24 and 0.27, to a final value of 4.19, 3.24 and 1.41, respectively.

Machine learning of network metrics in ATLAS Distributed Data Management

Science.gov (United States)

Lassnig, Mario; Toler, Wesley; Vamosi, Ralf; Bogado, Joaquin; ATLAS Collaboration

2017-10-01

The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for networkaware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

An ensemble machine learning approach to predict survival in breast cancer.

Science.gov (United States)

Djebbari, Amira; Liu, Ziying; Phan, Sieu; Famili, Fazel

2008-01-01

Current breast cancer predictive signatures are not unique. Can we use this fact to our advantage to improve prediction? From the machine learning perspective, it is well known that combining multiple classifiers can improve classification performance. We propose an ensemble machine learning approach which consists of choosing feature subsets and learning predictive models from them. We then combine models based on certain model fusion criteria and we also introduce a tuning parameter to control sensitivity. Our method significantly improves classification performance with a particular emphasis on sensitivity which is critical to avoid misclassifying poor prognosis patients as good prognosis.

Progressive Propaganda Critics and the Magic Bullet Myth.

Science.gov (United States)

Sproule, J. Michael

1989-01-01

Examines the development and historical inaccuracies of the "magic bullet" interpretation of American propaganda studies, which asserts that propaganda critics between the world wars treated messages as "magic bullets" directly and powerfully infused into passive receivers. Considers why this misconception of the progressive…

Code-expanded radio access protocol for machine-to-machine communications

DEFF Research Database (Denmark)

Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

2013-01-01

The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated b...... subframes and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the massive support of Machine-Type Communication users that is beyond the reach of current systems.......The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated...... by the random access method employed in LTE, which significantly increases the amount of contention resources without increasing the system resources, such as contention subframes and preambles. This is accomplished by a logical, rather than physical, extension of the access method in which the available system...

Design, fabrication and evaluation of fish meal pelletizing machine ...

African Journals Online (AJOL)

A 113.1kg/h fish meal pellet processing machine which produced 4mm diameter pellet, with an average length of 6mm was designed and fabricated. Design values of 210 was used for the maximum angle that the hopper wall formed with the vertical in the discharge zone, a critical stress of 1.3kPa of the ground particulate ...

Effect of changing polarity of graphite tool/ Hadfield steel workpiece couple on machining performances in die sinking EDM

Directory of Open Access Journals (Sweden)

Özerkan Haci Bekir

2017-01-01

Full Text Available In this study, machining performance ouput parameters such as machined surface roughness (SR, material removal rate (MRR, tool wear rate (TWR, were experimentally examined and analyzed with the diversifying and changing machining parameters in (EDM. The processing parameters (input par. of this research are stated as tool material, peak current (I, pulse duration (ton and pulse interval (toff. The experimental machinings were put into practice by using Hadfield steel workpiece (prismatic and cylindrical graphite electrodes with kerosene dielectric at different machining current, polarity and pulse time settings. The experiments have shown that the type of tool material, polarity (direct polarity forms higher MRR, SR and TWR, current (high current lowers TWR and enhances MRR, TWR and pulse on time (ton=48□s is critical threshold value for MRR and TWR were influential on machining performance in electrical discharge machining.

Realism in nuclear criticality safety

International Nuclear Information System (INIS)

McLaughlin, T. P.

2009-01-01

Commercial nuclear power plant operation and regulation have made remarkable progress since the Three Mile Island Accident. This is attributed largely to a heavy dose of introspection and self-regulation by the industry and to a significant infusion of risk-informed and performance-based regulation by the Nuclear Regulatory Commission. This truly represents reality in action both by the plant operators and the regulators. On the other hand, the implementation of nuclear criticality safety in ex-reactor operations involving significant quantities of fissile material has not progressed, but, tragically, it has regressed. Not only is the practice of the discipline in excess of a factor of ten more expensive than decades ago; the trend continues. This unfortunate reality is attributed to a lack of coordination within the industry (as contrasted to what occurred in the reactor operations sector), and to a lack of implementation of risk-informed and performance-based regulation by the NRC While the criticality safety discipline is orders of magnitude smaller than the reactor safety discipline, both operators and regulators must learn from the progress made in reactor safety and apply it to the former to reduce the waste, inefficiency and potentially increased accident risks associated with current practices. Only when these changes are made will there be progress made toward putting realism back into nuclear criticality safety. (authors)

Smart Cutting Tools and Smart Machining: Development Approaches, and Their Implementation and Application Perspectives

Science.gov (United States)

Cheng, Kai; Niu, Zhi-Chao; Wang, Robin C.; Rakowski, Richard; Bateman, Richard

2017-09-01

Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo (FTS) and smart collets for ultraprecision and micro manufacturing purposes. Implementation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation techniques are presented focusing on: (a) plug-and-produce design principle and the associated smart control algorithms, (b) piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, (c) critical cutting temperature control in real-time machining, (d) in-process calibration through machining trials, (e) FE-based design and analysis of smart cutting tools, and (f) application exemplars on adaptive smart machining.

Ductile and brittle transition behavior of titanium alloys in ultra-precision machining.

Science.gov (United States)

Yip, W S; To, S

2018-03-02

Titanium alloys are extensively applied in biomedical industries due to their excellent material properties. However, they are recognized as difficult to cut materials due to their low thermal conductivity, which induces a complexity to their deformation mechanisms and restricts precise productions. This paper presents a new observation about the removal regime of titanium alloys. The experimental results, including the chip formation, thrust force signal and surface profile, showed that there was a critical cutting distance to achieve better surface integrity of machined surface. The machined areas with better surface roughness were located before the clear transition point, defining as the ductile to brittle transition. The machined area at the brittle region displayed the fracture deformation which showed cracks on the surface edge. The relationship between depth of cut and the ductile to brittle transaction behavior of titanium alloys in ultra-precision machining(UPM) was also revealed in this study, it showed that the ductile to brittle transaction behavior of titanium alloys occurred mainly at relatively small depth of cut. The study firstly defines the ductile to brittle transition behavior of titanium alloys in UPM, contributing the information of ductile machining as an optimal machining condition for precise productions of titanium alloys.

Simple machines

CERN Document Server

Graybill, George

2007-01-01

Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

Uterine NK cells are critical in shaping DC immunogenic functions compatible with pregnancy progression.

Directory of Open Access Journals (Sweden)

Irene Tirado-González

Full Text Available Dendritic cell (DC and natural killer (NK cell interactions are important for the regulation of innate and adaptive immunity, but their relevance during early pregnancy remains elusive. Using two different strategies to manipulate the frequency of NK cells and DC during gestation, we investigated their relative impact on the decidualization process and on angiogenic responses that characterize murine implantation. Manipulation of the frequency of NK cells, DC or both lead to a defective decidual response characterized by decreased proliferation and differentiation of stromal cells. Whereas no detrimental effects were evident upon expansion of DC, NK cell ablation in such expanded DC mice severely compromised decidual development and led to early pregnancy loss. Pregnancy failure in these mice was associated with an unbalanced production of anti-angiogenic signals and most notably, with increased expression of genes related to inflammation and immunogenic activation of DC. Thus, NK cells appear to play an important role counteracting potential anomalies raised by DC expansion and overactivity in the decidua, becoming critical for normal pregnancy progression.

Uterine NK cells are critical in shaping DC immunogenic functions compatible with pregnancy progression.

Science.gov (United States)

Tirado-González, Irene; González, Irene Tirado; Barrientos, Gabriela; Freitag, Nancy; Otto, Teresa; Thijssen, Victor L J L; Moschansky, Petra; von Kwiatkowski, Petra; Klapp, Burghard F; Winterhager, Elke; Bauersachs, Stefan; Blois, Sandra M

2012-01-01

Dendritic cell (DC) and natural killer (NK) cell interactions are important for the regulation of innate and adaptive immunity, but their relevance during early pregnancy remains elusive. Using two different strategies to manipulate the frequency of NK cells and DC during gestation, we investigated their relative impact on the decidualization process and on angiogenic responses that characterize murine implantation. Manipulation of the frequency of NK cells, DC or both lead to a defective decidual response characterized by decreased proliferation and differentiation of stromal cells. Whereas no detrimental effects were evident upon expansion of DC, NK cell ablation in such expanded DC mice severely compromised decidual development and led to early pregnancy loss. Pregnancy failure in these mice was associated with an unbalanced production of anti-angiogenic signals and most notably, with increased expression of genes related to inflammation and immunogenic activation of DC. Thus, NK cells appear to play an important role counteracting potential anomalies raised by DC expansion and overactivity in the decidua, becoming critical for normal pregnancy progression.

Machine performance assessment and enhancement for a hexapod machine

Energy Technology Data Exchange (ETDEWEB)

Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

1998-03-19

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective.

Science.gov (United States)

Kim, Yong-Ku; Na, Kyoung-Sae

2018-01-03

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future. Copyright �

Superconducting rotating machines

International Nuclear Information System (INIS)

Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

1975-01-01

The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

Sustainable machining

CERN Document Server

2017-01-01

This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

Man-machine systems research at the OECD Halden reactor project

International Nuclear Information System (INIS)

Owre, F.; Bjorlo, T.J.; Haugset, K.

1994-01-01

The OECD Halden Reactor Project is a jointly financed research programme under the auspices of the OECD - Nuclear Energy Agency with fifteen participating countries. One of the main research topics focuses on man-machine systems. Particular attention is paid to the operator's tasks in the reactor control room environment. The overall objective of the research in this field is to provide a basis for improving today's control rooms through the introduction of computer-based solutions for the effective and safe execution of surveillance and control functions in normal as well as off-normal plant situations. The programme comprises four main activities: the verification and validation of safety critical software systems; man-machine interaction research emphasizing improvements in man-machine interfaces on the basis of human factors studies; computerised operator support systems assisting the operator in fault detection/diagnosis and planning of control actions; and control room development providing a basis for retrofitting of existing control rooms and for the design of advanced concepts

Machine-Checked Sequencer for Critical Embedded Code Generator

Science.gov (United States)

Izerrouken, Nassima; Pantel, Marc; Thirioux, Xavier

This paper presents the development of a correct-by-construction block sequencer for GeneAuto a qualifiable (according to DO178B/ED12B recommendation) automatic code generator. It transforms Simulink models to MISRA C code for safety critical systems. Our approach which combines classical development process and formal specification and verification using proof-assistants, led to preliminary fruitful exchanges with certification authorities. We present parts of the classical user and tools requirements and derived formal specifications, implementation and verification for the correctness and termination of the block sequencer. This sequencer has been successfully applied to real-size industrial use cases from various transportation domain partners and led to requirement errors detection and a correct-by-construction implementation.

Looking from Within: Prospects and Challenges for Progressive Education in Indonesia

Science.gov (United States)

Zulfikar, Teuku

2013-01-01

Many Indonesian scholars (Azra, 2002; Darmaningtyas, 2004; Yunus, 2004), have attempted to bring progressive education to their country. They believe that progressive practices such as critical thinking, critical dialogue and child-centered instruction will help students learn better. However, this implementation is resisted because of cultural…

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

Directory of Open Access Journals (Sweden)

Ming Cheng

2015-09-01

Full Text Available The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs. Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG. Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

Asynchronized synchronous machines

CERN Document Server

Botvinnik, M M

1964-01-01

Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

Machine Shop Lathes.

Science.gov (United States)

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

Machine learning application in online lending risk prediction

OpenAIRE

Yu, Xiaojiao

2017-01-01

Online leading has disrupted the traditional consumer banking sector with more effective loan processing. Risk prediction and monitoring is critical for the success of the business model. Traditional credit score models fall short in applying big data technology in building risk model. In this manuscript, data with various format and size were collected from public website, third-parties and assembled with client's loan application information data. Ensemble machine learning models, random fo...

Correlation between use time of machine and decline curve for emerging enterprise information systems

Science.gov (United States)

Chang, Yao-Chung; Lai, Chin-Feng; Chuang, Chi-Cheng; Hou, Cheng-Yu

2018-04-01

With the progress of science and technology, more and more machines are adpot to help human life better and more convenient. When the machines have been used for a longer period of time so that the machine components are getting old, the amount of power comsumption will increase and easily cause the machine to overheat. This also causes a waste of invisible resources. If the Internet of Everything (IoE) technologies are able to be applied into the enterprise information systems for monitoring the machines use time, it can not only make energy can be effectively used, but aslo create a safer living environment. To solve the above problem, the correlation predict model is established to collect the data of power consumption converted into power eigenvalues. This study takes the power eigenvalue as the independent variable and use time as the dependent variable in order to establish the decline curve. Ultimately, the scoring and estimation modules are employed to seek the best power eigenvalue as the independent variable. To predict use time, the correlation is discussed between the use time and the decline curve to improve the entire behavioural analysis of the facilitate recognition of the use time of machines.

Machinability of titanium metal matrix composites (Ti-MMCs)

Science.gov (United States)

Aramesh, Maryam

Titanium metal matrix composites (Ti-MMCs), as a new generation of materials, have various potential applications in aerospace and automotive industries. The presence of ceramic particles enhances the physical and mechanical properties of the alloy matrix. However, the hard and abrasive nature of these particles causes various issues in the field of their machinability. Severe tool wear and short tool life are the most important drawbacks of machining this class of materials. There is very limited work in the literature regarding the machinability of this class of materials especially in the area of tool life estimation and tool wear. By far, polycrystalline diamond (PCD) tools appear to be the best choice for machining MMCs from researchers' point of view. However, due to their high cost, economical alternatives are sought. Cubic boron nitride (CBN) inserts, as the second hardest available tools, show superior characteristics such as great wear resistance, high hardness at elevated temperatures, a low coefficient of friction and a high melting point. Yet, so far CBN tools have not been studied during machining of Ti-MMCs. In this study, a comprehensive study has been performed to explore the tool wear mechanisms of CBN inserts during turning of Ti-MMCs. The unique morphology of the worn faces of the tools was investigated for the first time, which led to new insights in the identification of chemical wear mechanisms during machining of Ti-MMCs. Utilizing the full tool life capacity of cutting tools is also very crucial, due to the considerable costs associated with suboptimal replacement of tools. This strongly motivates development of a reliable model for tool life estimation under any cutting conditions. In this study, a novel model based on the survival analysis methodology is developed to estimate the progressive states of tool wear under any cutting conditions during machining of Ti-MMCs. This statistical model takes into account the machining time in

Classification for Safety-Critical Car-Cyclist Scenarios Using Machine Learning

NARCIS (Netherlands)

Cara, I.; Gelder, E.D.

2015-01-01

The number of fatal car-cyclist accidents is increasing. Advanced Driver Assistance Systems (ADAS) can improve the safety of cyclists, but they need to be tested with realistic safety-critical car-cyclist scenarios. In order to store only relevant scenarios, an online classification algorithm is

Reactor noise in critical and accelerator driven sub-critical systems

International Nuclear Information System (INIS)

Degweker, S.B.; Rana, Y.S.

2007-01-01

Noise methods have long been used for reactor kinetics parameters measurement and as diagnostic tools for monitoring the health of a nuclear power plant. It is conceivable that noise techniques would find similar applications in ADS. Measurement/monitoring the degree of sub-criticality of an ADS is one such application for which noise based methods are being considered, among others such as the pulsed source method. For this reason, theoretical studies on ADS noise have appeared since the late nineties. The principal difference between critical reactor noise and ADS noise is due to the statistical properties of the source. Unlike the source due to radioactive decay present in ordinary reactors, the machine produced ADS source cannot be assumed to be a Poisson process. In addition the source is pulsed. All this requires a new theoretical approach to the subject. In a number of papers (beginning in 2000) such a theoretical approach has been developed in BARC. Over the years, our approach has received general acceptance. The paper gives a description of the subject of reactor noise and its applications in critical reactors. The theory of noise in ADS is then outlined, highlighting the differences in approach and results from that of critical reactors. (author)

Mining the Kepler Data using Machine Learning

Science.gov (United States)

Walkowicz, Lucianne; Howe, A. R.; Nayar, R.; Turner, E. L.; Scargle, J.; Meadows, V.; Zee, A.

2014-01-01

Kepler's high cadence and incredible precision has provided an unprecedented view into stars and their planetary companions, revealing both expected and novel phenomena and systems. Due to the large number of Kepler lightcurves, the discovery of novel phenomena in particular has often been serendipitous in the course of searching for known forms of variability (for example, the discovery of the doubly pulsating elliptical binary KOI-54, originally identified by the transiting planet search pipeline). In this talk, we discuss progress on mining the Kepler data through both supervised and unsupervised machine learning, intended to both systematically search the Kepler lightcurves for rare or anomalous variability, and to create a variability catalog for community use. Mining the dataset in this way also allows for a quantitative identification of anomalous variability, and so may also be used as a signal-agnostic form of optical SETI. As the Kepler data are exceptionally rich, they provide an interesting counterpoint to machine learning efforts typically performed on sparser and/or noisier survey data, and will inform similar characterization carried out on future survey datasets.

Machining of Machine Elements Made of Polymer Composite Materials

Science.gov (United States)

Baurova, N. I.; Makarov, K. A.

2017-12-01

The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

Science.gov (United States)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

The achievements of the Z-machine; Les exploits de la Z-machine

Energy Technology Data Exchange (ETDEWEB)

Larousserie, D

2008-03-15

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Paradigm shifts in critical care medicine: the progress we have made.

Science.gov (United States)

Vincent, Jean-Louis; Creteur, Jacques

2015-01-01

There have really been no single, major, advances in critical care medicine since the specialty came into existence. There has, however, been a gradual, continuous improvement in the process of care over the years, which has resulted in improved patient outcomes. Here, we will highlight just a few of the paradigm shifts we have seen in processes of critical care, including the move from small, closed units to larger, more open ICUs; from a paternal "dictatorship" to more "democratic" team-work; from intermittent to continuous, invasive to less-invasive monitoring; from "more" interventions to "less" thus reducing iatrogenicity; from consideration of critical illness as a single event to realization that it is just one part of a trajectory; and from "four walls" to "no walls" as we take intensive care outside the physical ICU. These and other paradigm shifts have resulted in improvements in the whole approach to patient management, leading to more holistic, humane care for patients and their families. As critical care medicine continues to develop, further paradigm shifts in processes of care are inevitable and must be embraced if we are to continue to provide the best possible care for all critically ill patients.

Paradigm shifts in critical care medicine: the progress we have made

Science.gov (United States)

2015-01-01

There have really been no single, major, advances in critical care medicine since the specialty came into existence. There has, however, been a gradual, continuous improvement in the process of care over the years, which has resulted in improved patient outcomes. Here, we will highlight just a few of the paradigm shifts we have seen in processes of critical care, including the move from small, closed units to larger, more open ICUs; from a paternal "dictatorship" to more "democratic" team-work; from intermittent to continuous, invasive to less-invasive monitoring; from "more" interventions to "less" thus reducing iatrogenicity; from consideration of critical illness as a single event to realization that it is just one part of a trajectory; and from "four walls" to "no walls" as we take intensive care outside the physical ICU. These and other paradigm shifts have resulted in improvements in the whole approach to patient management, leading to more holistic, humane care for patients and their families. As critical care medicine continues to develop, further paradigm shifts in processes of care are inevitable and must be embraced if we are to continue to provide the best possible care for all critically ill patients. PMID:26728199

Quantum machine learning.

Science.gov (United States)

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.

Scientific instruments, scientific progress and the cyclotron

International Nuclear Information System (INIS)

Baird, David; Faust, Thomas

1990-01-01

Philosophers speak of science in terms of theory and experiment, yet when they speak of the progress of scientific knowledge they speak in terms of theory alone. In this article it is claimed that scientific knowledge consists of, among other things, scientific instruments and instrumental techniques and not simply of some kind of justified beliefs. It is argued that one aspect of scientific progress can be characterized relatively straightforwardly - the accumulation of new scientific instruments. The development of the cyclotron is taken to illustrate this point. Eight different activities which promoted the successful completion of the cyclotron are recognised. The importance is in the machine rather than the experiments which could be run on it and the focus is on how the cyclotron came into being, not how it was subsequently used. The completed instrument is seen as a useful unit of scientific progress in its own right. (UK)

Machine protection systems

CERN Document Server

Macpherson, A L

2010-01-01

A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

Preliminary Test of Upgraded Conventional Milling Machine into PC Based CNC Milling Machine

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

CNC (Computerized Numerical Control) milling machine yields a challenge to make an innovation in the field of machining. With an action job is machining quality equivalent to CNC milling machine, the conventional milling machine ability was improved to be based on PC CNC milling machine. Mechanically and instrumentally change. As a control replacing was conducted by servo drive and proximity were used. Computer programme was constructed to give instruction into milling machine. The program structure of consists GUI model and ladder diagram. Program was put on programming systems called RTX software. The result of up-grade is computer programming and CNC instruction job. The result was beginning step and it will be continued in next time. With upgrading ability milling machine becomes user can be done safe and optimal from accident risk. By improving performance of milling machine, the user will be more working optimal and safely against accident risk. (author)

ASCERTAINMENT OF THE EQUIVALENT CIRCUIT PARAMETERS OF THE ASYNCHRONOUS MACHINE

Directory of Open Access Journals (Sweden)

V. S. Safaryan

2015-01-01

Full Text Available The article considers experimental and analytical determination of the asynchronous machine equivalent-circuit parameters with application of the reference data. Transient processes investigation of the asynchronous machines necessitates the equivalent circuit parameters (resistance impedance, inductances and coefficient of the stator-rotor contours mutual inductance that help form the transitory-process mathematical simulation model. The reference books do not provide those parameters; they instead give the rated ones (active power, voltage, slide, coefficient of performance and capacity coefficient as well as the ratio of starting and nominal currents and torques. The noted studies on the asynchronous machine equivalent-circuits parametrization fail to solve the problems ad finem or solve them with admissions. The paper presents experimental and analytical determinations of the asynchronous machine equivalent-circuit parameters: the experimental one based on the results of two measurements and the analytical one where the problem boils down to solving a system of nonlineal algebraic equations. The authors investigate the equivalent asynchronous machine input-resistance properties and adduce the dependence curvatures of the input-resistances on the slide. They present a symbolic model for analytical parameterization of the asynchronous machine equivalent-circuit that represents a system of nonlineal equations and requires one of the rotor-parameters arbitrary assignment. The article demonstrates that for the asynchronous machine equivalent-circuit experimental parameterization the measures are to be conducted of the stator-circuit voltage, current and active power with two different slides and arbitrary assignment of one of the rotor parameters. The paper substantiates the fact that additional measurement does not discard the rotor-parameter choice arbitrariness. The authors establish that in motoring mode there is a critical slide by which the

Systematic Poisoning Attacks on and Defenses for Machine Learning in Healthcare.

Science.gov (United States)

Mozaffari-Kermani, Mehran; Sur-Kolay, Susmita; Raghunathan, Anand; Jha, Niraj K

2015-11-01

Machine learning is being used in a wide range of application domains to discover patterns in large datasets. Increasingly, the results of machine learning drive critical decisions in applications related to healthcare and biomedicine. Such health-related applications are often sensitive, and thus, any security breach would be catastrophic. Naturally, the integrity of the results computed by machine learning is of great importance. Recent research has shown that some machine-learning algorithms can be compromised by augmenting their training datasets with malicious data, leading to a new class of attacks called poisoning attacks. Hindrance of a diagnosis may have life-threatening consequences and could cause distrust. On the other hand, not only may a false diagnosis prompt users to distrust the machine-learning algorithm and even abandon the entire system but also such a false positive classification may cause patient distress. In this paper, we present a systematic, algorithm-independent approach for mounting poisoning attacks across a wide range of machine-learning algorithms and healthcare datasets. The proposed attack procedure generates input data, which, when added to the training set, can either cause the results of machine learning to have targeted errors (e.g., increase the likelihood of classification into a specific class), or simply introduce arbitrary errors (incorrect classification). These attacks may be applied to both fixed and evolving datasets. They can be applied even when only statistics of the training dataset are available or, in some cases, even without access to the training dataset, although at a lower efficacy. We establish the effectiveness of the proposed attacks using a suite of six machine-learning algorithms and five healthcare datasets. Finally, we present countermeasures against the proposed generic attacks that are based on tracking and detecting deviations in various accuracy metrics, and benchmark their effectiveness.

Man-machine interface versus full automation

International Nuclear Information System (INIS)

Hatton, V.

1984-01-01

As accelerators grow in size and complexity of operation there is an increasing economical as well as an operational incentive for the controls and operations teams to use computers to help the man-machine interface. At first the computer network replaced the traditional controls racks filled with knobs, buttons and digital displays of voltages and potentiometer readings. The computer system provided the operator with the extension of his hands and eyes. It was quickly found that much more could be achieved. Where previously it was necessary for the human operator to decide the order of the actions to be executed by the computer as a result of a visual indication of malfunctioning of the accelerator, now the operation is becoming more and more under the direct control of the computer system. Expert knowledge is programmed into the system to help the non-specialist make decision and to safeguard the equipment. Machine physics concepts have been incorporated and critical machine parameters can be optimised easily by the physicists or operators without any detailed knowledge of the intervening medium or of the equipment being controlled. As confidence grows and reliability improves, more and more automation can be added. How far can this process of automation replace the skilled operator. Can the accelerators of tomorrow be run like the ever increasing robotic assembly plants of today. How is the role of the operator changing in this new environment

Study of on-machine error identification and compensation methods for micro machine tools

International Nuclear Information System (INIS)

Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

2016-01-01

Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

Cardiac imaging: working towards fully-automated machine analysis & interpretation.

Science.gov (United States)

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-03-01

Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke.

Science.gov (United States)

McConnell, Alistair C; Moioli, Renan C; Brasil, Fabricio L; Vallejo, Marta; Corne, David W; Vargas, Patricia A; Stokes, Adam A

2017-06-28

To review the state of the art of robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain-machine interfaces. Each patient has a unique clinical history and, in response to personalized treatment needs, research into individualized and at-home treatment options has expanded rapidly in recent years. This has resulted in the development of many devices and design strategies for use in stroke rehabilitation. The development progression of robotic-aided hand physiotherapy devices and brain-machine interface systems is outlined, focussing on those with mechanisms and control strategies designed to improve recovery outcomes of the hand post-stroke. A total of 110 commercial and non-commercial hand and wrist devices, spanning the 2 major core designs: end-effector and exoskeleton are reviewed. The growing body of evidence on the efficacy and relevance of incorporating brain-machine interfaces in stroke rehabilitation is summarized. The challenges involved in integrating robotic rehabilitation into the healthcare system are discussed. This review provides novel insights into the use of robotics in physiotherapy practice, and may help system designers to develop new devices.

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

Quarterly progress report on the evaluation of critical materials for photovoltaic cells

Energy Technology Data Exchange (ETDEWEB)

Watts, R.L.; Pawlewicz, W.W.; Gurwell, W.E.; Jamieson, W.M.; Long, L.W.; Smith, S.A.; Teeter, R.R.

1979-09-01

The scope of the activities included in this program are as follows: (1) characterize new and improved photovoltaic cell designs and production processes for subsequent analysis; (2) review or screen these designs for potential material shortages or other constraints; (3) carry out investigations of the probable costs of new sources of materials potentially in short supply, concentrating on gallium and indium; and (4) identify options for coping with or mitigating the problems identified. The methodology and data base used in the CMAP (Critical Material Analysis Program) computer program were developed as part of a broad scale DOE program to review the potential material constraints of all solar programs. The photovoltaic report screened 13 cells in 15 systems and assumed 100% material utilization (process efficiency) in producing the photovoltaic cells. This study emphasizes the availability of cell fabrication feedstock materials and the effects of process efficiencies on material availability by adding characterizations of photovoltaic production processes. This quarterly report presents the results of work with emphasis on Task I, the characterization of photovoltaic cells and their production processes. Task IIA, CMAP Modification, Data Base Development and Operation has been initiated. Task IIB, Review, Integration, Interpretation and Analysis of Screening will begin once the baseline screening has been completed in Task IIA. Work on Task IIIA, the Assessment of Future Costs and Supplies of Gallium and Indium and Task IIIB, Economics of Coal Derived PV Materials have been initiated. Progress and initial results are reported. (WHK)

Electrochemical machining of burn-resistant Ti40 alloy

Directory of Open Access Journals (Sweden)

Xu Zhengyang

2015-08-01

Full Text Available This study investigates the feasibility of using electrochemical machining (ECM to produce critical aeroengine components from a new burn-resistant titanium alloy (Ti40, thereby reducing costs and improving efficiency relative to conventional mechanical machining. Through this, it is found that an aqueous mix of sodium chloride and potassium bromide provides the optimal electrolyte and that the surface quality of the Ti40 workpiece is improved by using a pulsed current of 1 kHz rather than a direct current. Furthermore, the quality of cavities produced by ECM and the overall material removal rate are determined to be dependent on a combination of operating voltage, electrolyte inlet pressure, cathode feeding rate and electrolyte concentration. By optimizing these parameters, a surface roughness of 0.371 μm has been achieved in conjunction with a specific removal rate of more than 3.1 mm3/A·min.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

2014-08-15

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

International Nuclear Information System (INIS)

Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

2014-01-01

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

THE ANALYSIS OF MACHINES FOR THE FOOTWEAR PULL ON BOOT TREE

Directory of Open Access Journals (Sweden)

I. Pascari

2011-01-01

Full Text Available The ways of manufacturing of footwear have undergone a long evolutionary way, beginning with the manual work and finishing with the automated. The first sewing machine that had come to help the manappeared in ХVIII century. The Industrial progress of development and of the equipment it is possible to divide conditionally into three stages: from 60 till 90th years where it is attempt the two-operational power engine; from 90 till 2000 two machines were applied to an inhaling; and the modern period when inhaling processallows using less machines. The new machines had new patented system that allows the operator to put the position for preparation of the top of footwear according to the design of model that is applied to each size of footwear. The system provides an automatic centering of a narrow site of footwear that by means of a followingbeam of light the operator could guarantee each time exact width of capture of a long edge in beam parts ofpreparation of top. In a similar way the system provides exact positioning of the sample in toe cap footwear parts. Except the equipment by the modern electronic devices, the new machines have fashionable design, in particular, the polished black panel and the automated tray for the footwear, covered with genuine leather. Theappointment of these machines is universal: on them it is possible to carry out process of an inhaling for various types of footwear (boots, low shoes, shoes, etc. both as daily socks as model sports. Thus the footwear can be various groups of people– man, female, and children.

Antibiotic Residues in Milk from Three Popular Kenyan Milk Vending Machines.

Science.gov (United States)

Kosgey, Amos; Shitandi, Anakalo; Marion, Jason W

2018-05-01

Milk vending machines (MVMs) are growing in popularity in Kenya and worldwide. Milk vending machines dispense varying quantities of locally sourced, pasteurized milk. The Kenya Dairy Board has a regulatory framework, but surveillance is weak because of several factors. Milk vending machines' milk is not routinely screened for antibiotics, thereby increasing potential for antibiotic misuse. To investigate, a total of 80 milk samples from four commercial providers ( N = 25), street vendors ( N = 21), and three MVMs ( N = 34) were collected and screened in Eldoret, Kenya. Antibiotic residue surveillance occurred during December 2016 and January 2017 using Idexx SNAP ® tests for tetracyclines, sulfamethazine, beta-lactams, and gentamicin. Overall, 24% of MVM samples and 24% of street vendor samples were presumably positive for at least one antibiotic. No commercial samples were positive. Research into cost-effective screening methods and increased monitoring by food safety agencies are needed to uphold hazard analysis and critical control point for improving antibiotic stewardship throughout the Kenyan private dairy industry.

Los Alamos Critical Assemblies Facility

International Nuclear Information System (INIS)

Malenfant, R.E.

1981-06-01

The Critical Assemblies Facility of the Los Alamos National Laboratory has been in existence for thirty-five years. In that period, many thousands of measurements have been made on assemblies of 235 U, 233 U, and 239 Pu in various configurations, including the nitrate, sulfate, fluoride, carbide, and oxide chemical compositions and the solid, liquid, and gaseous states. The present complex of eleven operating machines is described, and typical applications are presented

Advances in and prospects for development of high-temperature superconductor rotating machines at Siemens

International Nuclear Information System (INIS)

Neumueller, H W; Nick, W; Wacker, B; Frank, M; Nerowski, G; Frauenhofer, J; Rzadki, W; Hartig, R

2006-01-01

We report on the successful manufacture and testing of the Siemens 400 kVA HTS synchronous motor, which has been in operation for over 3 years, and on the progress of the 4 MVA synchronous motor/generator, which has been manufactured and is now in a phase of extended testing. Furthermore, the benefits of HTS machines will be discussed with emphasis on applications in ships. The development of future marketable products will be strongly dependent on the progress of secondary technologies, such as wire performance and efficient cost-effective refrigerators

Mechanical and thermal characteristics of JT-60 tokamak machine demonstrated in its power tests

International Nuclear Information System (INIS)

Takatsu, Hideyuki; Yamamoto, Masahiro; Ohkubo, Minoru

1985-09-01

JT-60 power tests were carried out from Dec. 10, 1984 to Feb. 20, 1985 to demonstrate, in advance of actual plasma operation, satisfactory performance of tokamak machine, power suppliers and control system in combination. The tests began with low power test of individual coil systems and progressed to full power tests. Power tests were successfully concluded with the following conclusions. (1) All of the coil systems were raised up to full power operation in combination and system performance was verified including thermal and structural integrity of tokamak machine. (2) Measured strain and deflection showed good agreements with those predicted in the design, which was an evidence that electromagnetic loads were supported adequately as expected in the design. (3) Vibration of lateral port was found to be large up to 50 m/s 2 and caused excessive vibration of gate-valves. (4) A few limitations to machine operation were made clear quantatively. (5) It was found that the existing detectors were insufficient to monitor the machine integrity and a few kinds of detectors were necessary to be installed. (author)

Penentuan Critical Parts Alat Bantu Pemeras Santan Menggunakan Quality Function Deployment Fase Kedua

Directory of Open Access Journals (Sweden)

Yuswono Hadi

2017-08-01

Full Text Available Some previous studies used QFD first phase method to obtain customer satisfaction of coconut milk squeezer machines, as follows: accelerates extortion process, reduces fatigue, easy to use, optimizes the output, strong construction, rustproof materials, compact design, easy to move, and hygienic. Study developing of the squeezer machine of coconut milk is required to deploy customer satisfaction into two parts including specifications and critical parts by using QFD second phase. There are 15 part specifications that obtained by discussing and interviewing with the experts. Then, 4 part specifications such as motor, pressing mechanism, production step, pressing strength, and volume of the cylinder were selected as main part to be used for QFD second phase. While there were 10 critical parts was derived from selected part specification such as pressure strength, hydraulic system, ON/OFF push button, cylinder clamps, the power and voltage that used for the machine,  the piston holder material, and its diameter.

Progress on alternative energy resources

Science.gov (United States)

Couch, H. T.

1982-03-01

Progress in the year 1981 toward the development of energy systems suitable for replacing petroleum products combustion and growing in use to fulfill a near term expansion in energy use is reviewed. Coal is noted to be a potentially heavy pollution source, and the presence of environmentally acceptable methods of use such as fluidized-bed combustion and gasification and liquefaction reached the prototype stage in 1981, MHD power generation was achieved in two U.S. plants, with severe corrosion problems remaining unsolved for the electrodes. Solar flat plate collectors sales amounted to 20 million sq ft in 1981, and solar thermal electric conversion systems with central receivers neared completion. Solar cells are progressing toward DOE goals of $.70/peak W by 1986, while wind energy conversion sales were 2000 machines in 1981, and the industry is regarded as maturing. Finally, geothermal, OTEC, and fusion systems are reviewed.

Investigations on the performance of ultrasonic drilling process with special reference to precision machining of advanced ceramics

International Nuclear Information System (INIS)

Adithan, M.; Laroiya, S.C.

1997-01-01

Advanced ceramics are assuming an important role in modern industrial technology. The applications and advantages of using advanced ceramics are many. There are several reasons why we should go in for machining of advanced ceramics after their compacting and sintering. These are discussed in this paper. However, precision machining of advanced ceramics must be economical. Critical technological issues to be addressed in cost effective machining of ceramics include design of machine tools, tooling arrangements, improved yield and precision, relationship of part dimensions and finish specifications to functional performance, and on-line inspection. Considering the above ultrasonic drilling is an important process used for the precision machining of advanced ceramics. Extensive studies on tool wear occurring in the ultrasonic machining of advanced ceramics have been carried out. In addition, production accuracy of holes drilled, surface finish obtained and surface integrity aspects in the machining of advanced ceramics have also been investigated. Some specific findings with reference to surface integrity are: a) there were no cracks or micro-cracks developed during or after ultrasonic machining of advanced ceramics, b) while machining Hexoloy alpha silicon carbide a recast layer is formed as a result of ultrasonic machining. This is attributed to the viscous heating resulting from high energy impacts during ultrasonic machining. While machining all other types of ceramics no such formation of recast layer was observed, and , c) there is no change in the microstructure of the advanced ceramics as a result of ultrasonic machining

Electrical machines & drives

CERN Document Server

Hammond, P

1985-01-01

Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

Machine translation

Energy Technology Data Exchange (ETDEWEB)

Nagao, M

1982-04-01

Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

Vibration transmitted to operator’s back by machines with back-pack power unit: a case study on blower and spraying machines

Directory of Open Access Journals (Sweden)

Roberto Deboli

2013-09-01

Full Text Available To correctly evaluate the vibration transmitted to the operators, it is necessary to consider each body’s point interested by the vibratory stimulus produced by machines. All the body’s part in contact to the vibration, when a portable device with internal combustion engine is used, are: hands, back and shoulders. Some information for wholebody vibration are available in the ISO 2631-1997 standard, which otherwise refers to a seated operator. ‘C’ type standards for the vibration analysis exist for some portable machines with an internal combustion engine which is comprehensive in the machine (chainsaw, brush-cutter, blower. If the engine is not inside the machine, but it is on the operator’s back, ‘C’ type standards on vibration measurements are quite incomplete. The IMAMOTER institute of CNR, the DISAFA Department (University of Turin and the Occupational Medicine Department of the University of Catania started some tests to verify the vibration levels transmitted to an operator working with backed engine devices. Two machines have been examined: a blower and a spraying machine. Two operative conditions have been considered during all the tests: idling and full load. Three operators have been involved and each test has been repeated three times. The spraying machine has been tested both with the empty tank and with 10 litres of water, to simulate the load to be caused by the presence of liquid inside the tank. In this work the comfort condition of ISO 2631-1 standard was considered, using the frequency weighting Wc curve with the weighting factor 0.8 for X axis (back-ventral direction and the Wd curve for Y and Z axis (shoulder - shoulder and buttocks - head with weighting factors 0.5 and 0.4 (respectively for Y and Z axis. Data were examined using IBM SPSS Statistics 20 software package. The statistical analysis underlined that the running condition is the main factor to condition the vibration levels transmitted to the operator�

Engineering electrodynamics electric machine, transformer, and power equipment design

CERN Document Server

Turowski, Janusz

2013-01-01

Due to a huge concentration of electromagnetic fields and eddy currents, large power equipment and systems are prone to crushing forces, overheating, and overloading. Luckily, power failures due to disturbances like these can be predicted and/or prevented.Based on the success of internationally acclaimed computer programs, such as the authors' own RNM-3D, Engineering Electrodynamics: Electric Machine, Transformer, and Power Equipment Design explains how to implement industry-proven modeling and design techniques to solve complex electromagnetic phenomena. Considering recent progress in magneti

What is the machine learning.

CERN Multimedia

CERN. Geneva

2018-01-01

Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. In this talk, I explore a procedure for identifying combinations of variables -- aided by physical intuition -- that can discriminate signal from background. Weights are introduced to smooth away the features in a given variable(s). New networks are then trained on this modified data. Observed decreases in sensitivity diagnose the variable's discriminating power. Planing also allows the investigation of the linear versus non-linear nature of the boundaries between signal and background. I will demonstrate these features in both an easy to understand toy model and an idealized LHC resonance scenario.

Induction machine handbook

CERN Document Server

Boldea, Ion

2002-01-01

Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

Chaotic Boltzmann machines

Science.gov (United States)

Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

2013-01-01

The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

Rotating electrical machines

CERN Document Server

Le Doeuff, René

2013-01-01

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

1985. Annual progress report

International Nuclear Information System (INIS)

1986-01-01

This annual progress report of the CEA Protection and Nuclear Safety Institut outlines a description of the progress made in each sections of the Institut Research activities of the different departments include: reactor safety analysis, fuel cycle facilities analysis; and associated safety research programs (criticality, sites, transport ...), radioecology and environmental radioprotection techniques; data acquisition on radioactive waste storage sites; radiation effects on man, studies on radioprotection techniques; nuclear material security including security of facilities, security of nuclear material transport, and monitoring of nuclear material management; nuclear facility decommissioning; and finally the public information [fr

Your Sewing Machine.

Science.gov (United States)

Peacock, Marion E.

The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

Process acceptance and adjustment techniques for Swiss automatic screw machine parts. Final report

International Nuclear Information System (INIS)

Robb, J.M.

1976-01-01

Product tolerance requirements for small, cylindrical, piece parts produced on swiss automatic screw machines have progressed to the reliability limits of inspection equipment. The miniature size, configuration, and tolerance requirements (plus or minus 0.0001 in.) (0.00254 mm) of these parts preclude the use of screening techniques to accept product or adjust processes during setup and production runs; therefore, existing means of product acceptance and process adjustment must be refined or new techniques must be developed. The purpose of this endeavor has been to determine benefits gained through the implementation of a process acceptance technique (PAT) to swiss automatic screw machine processes. PAT is a statistical approach developed for the purpose of accepting product and centering processes for parts produced by selected, controlled processes. Through this endeavor a determination has been made of the conditions under which PAT can benefit a controlled process and some specific types of screw machine processes upon which PAT could be applied. However, it was also determined that PAT, if used indiscriminately, may become a record keeping burden when applied to more than one dimension at a given machining operation

Kernel methods for interpretable machine learning of order parameters

Science.gov (United States)

Ponte, Pedro; Melko, Roger G.

2017-11-01

Machine learning is capable of discriminating phases of matter, and finding associated phase transitions, directly from large data sets of raw state configurations. In the context of condensed matter physics, most progress in the field of supervised learning has come from employing neural networks as classifiers. Although very powerful, such algorithms suffer from a lack of interpretability, which is usually desired in scientific applications in order to associate learned features with physical phenomena. In this paper, we explore support vector machines (SVMs), which are a class of supervised kernel methods that provide interpretable decision functions. We find that SVMs can learn the mathematical form of physical discriminators, such as order parameters and Hamiltonian constraints, for a set of two-dimensional spin models: the ferromagnetic Ising model, a conserved-order-parameter Ising model, and the Ising gauge theory. The ability of SVMs to provide interpretable classification highlights their potential for automating feature detection in both synthetic and experimental data sets for condensed matter and other many-body systems.

Stagnant zone formation on diamond cutting tools during machining

International Nuclear Information System (INIS)

Izman, S.; Tamin, M.N.; Mon, T.T.; Venkatesh, V.C.; Shaharoun, A.M.

2007-01-01

Formation of an intact region on the rake face of cutting tool during machining is quite common phenomenon but its significance in maintaining tool edge sharpness has not been recognized by many researchers. This region is sometimes called stagnant zone. It is believed that when an intact zone present on the rake face, it delays the crater wear progress and hence maintaining the tool edge sharpness longer. This paper investigates the effect of edge radius, surface roughness of the rake face and cutting parameters on the formation of stagnant zone on two different type of diamond tools i.e. polycrystalline diamond PCD-KD100 and diamond-coated inserts when machining titanium alloy. The used inserta and post-processed chips were examined under FESEM and optical microscope after cutting at three different conditions. Experimental results show that the speed and feel, the tool edge radius, and the tool rake surface roughness significantly affect the stagnant zone formation. (author)

Introduction to AC machine design

CERN Document Server

Lipo, Thomas A

2018-01-01

AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

Precision machining commercialization

International Nuclear Information System (INIS)

1978-01-01

To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

Are there intelligent Turing machines?

OpenAIRE

Bátfai, Norbert

2015-01-01

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

Technology Time Machine 2012

DEFF Research Database (Denmark)

Lehner, Wolfgang; Fettweis, Gerhard; Fitzek, Frank

2013-01-01

The IEEE Technology Time Machine (TTM) is a unique event for industry leaders, academics, and decision making government officials who direct R&D activities, plan research programs or manage portfolios of research activities. This report covers the main topics of the 2nd Symposium of future...... technologies. The Symposium brought together world renowned experts to discuss the evolutionary and revolutionary advances in technology landscapes as we look towards 2020 and beyond. TTM facilitated informal discussions among the participants and speakers thus providing an excellent opportunity for informal...... interaction between attendees, senior business leaders, world-renowned innovators, and the press. The goal of the Symposium is to discover key critical innovations across technologies which will alter the research and application space of the future. Topics covered the future of Wireless Technology, Smart...

Improved Saturated Hydraulic Conductivity Pedotransfer Functions Using Machine Learning Methods

Science.gov (United States)

Araya, S. N.; Ghezzehei, T. A.

2017-12-01

Saturated hydraulic conductivity (Ks) is one of the fundamental hydraulic properties of soils. Its measurement, however, is cumbersome and instead pedotransfer functions (PTFs) are often used to estimate it. Despite a lot of progress over the years, generic PTFs that estimate hydraulic conductivity generally don't have a good performance. We develop significantly improved PTFs by applying state of the art machine learning techniques coupled with high-performance computing on a large database of over 20,000 soils—USKSAT and the Florida Soil Characterization databases. We compared the performance of four machine learning algorithms (k-nearest neighbors, gradient boosted model, support vector machine, and relevance vector machine) and evaluated the relative importance of several soil properties in explaining Ks. An attempt is also made to better account for soil structural properties; we evaluated the importance of variables derived from transformations of soil water retention characteristics and other soil properties. The gradient boosted models gave the best performance with root mean square errors less than 0.7 and mean errors in the order of 0.01 on a log scale of Ks [cm/h]. The effective particle size, D10, was found to be the single most important predictor. Other important predictors included percent clay, bulk density, organic carbon percent, coefficient of uniformity and values derived from water retention characteristics. Model performances were consistently better for Ks values greater than 10 cm/h. This study maximizes the extraction of information from a large database to develop generic machine learning based PTFs to estimate Ks. The study also evaluates the importance of various soil properties and their transformations in explaining Ks.

Control and interpretation of criticality experiments on metallic assemblies

International Nuclear Information System (INIS)

Long, J.J.

1984-01-01

This paper deals with the principle of criticality experiment control with approach machines; to follow the reactivity evolution, one uses the classical method of the inverses of counting rates, then one shows how it is possible to extrapolate the approach curves that have been obtained [fr

Machine learning algorithms to classify spinal muscular atrophy subtypes.

Science.gov (United States)

Srivastava, Tuhin; Darras, Basil T; Wu, Jim S; Rutkove, Seward B

2012-07-24

The development of better biomarkers for disease assessment remains an ongoing effort across the spectrum of neurologic illnesses. One approach for refining biomarkers is based on the concept of machine learning, in which individual, unrelated biomarkers are simultaneously evaluated. In this cross-sectional study, we assess the possibility of using machine learning, incorporating both quantitative muscle ultrasound (QMU) and electrical impedance myography (EIM) data, for classification of muscles affected by spinal muscular atrophy (SMA). Twenty-one normal subjects, 15 subjects with SMA type 2, and 10 subjects with SMA type 3 underwent EIM and QMU measurements of unilateral biceps, wrist extensors, quadriceps, and tibialis anterior. EIM and QMU parameters were then applied in combination using a support vector machine (SVM), a type of machine learning, in an attempt to accurately categorize 165 individual muscles. For all 3 classification problems, normal vs SMA, normal vs SMA 3, and SMA 2 vs SMA 3, use of SVM provided the greatest accuracy in discrimination, surpassing both EIM and QMU individually. For example, the accuracy, as measured by the receiver operating characteristic area under the curve (ROC-AUC) for the SVM discriminating SMA 2 muscles from SMA 3 muscles was 0.928; in comparison, the ROC-AUCs for EIM and QMU parameters alone were only 0.877 (p < 0.05) and 0.627 (p < 0.05), respectively. Combining EIM and QMU data categorizes individual SMA-affected muscles with very high accuracy. Further investigation of this approach for classifying and for following the progression of neuromuscular illness is warranted.

Coldness production and heat revalorization: particular machines; Production de froid et revalorisation de la chaleur: machines particulieres

Energy Technology Data Exchange (ETDEWEB)

Feidt, M. [Universite Henri Poincare - Nancy-1, 54 - Nancy (France)

2003-10-01

The machines presented in this article are not the common reverse cycle machines. They use some systems based on different physical principles which have some consequences on the analysis of cycles: 1 - permanent gas machines (thermal separators, pulse gas tube, thermal-acoustic machines); 2 - phase change machines (mechanical vapor compression machines, absorption machines, ejection machines, adsorption machines); 3 - thermoelectric machines (thermoelectric effects, thermodynamic model of a thermoelectric machine). (J.S.)

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

Science.gov (United States)

Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

‘Machinic Trajectories’: Appropriated Devices as Post-Digital Drawing Machines

Directory of Open Access Journals (Sweden)

Andres Wanner

2014-12-01

Full Text Available This article presents a series of works called Machinic Trajectories, consisting of domestic devices appropriated as mechanical drawing machines. These are contextualized within the post-digital discourse, which integrates messy analog conditions into the digital realm. The role of eliciting and examining glitches for investigating a technology is pointed out. Glitches are defined as short-lived, unpremeditated aesthetic results of a failure; they are mostly known as digital phenomena, but I argue that the concept is equally applicable to the output of mechanical machines. Three drawing machines will be presented: The Opener, The Mixer and The Ventilator. In analyzing their drawings, emergent patterns consisting of unpremeditated visual artifacts will be identified and connected to irregularities of the specific technologies. Several other artists who work with mechanical and robotic drawing machines are introduced, to situate the presented works and reflections in a larger context of practice and to investigate how glitch concepts are applicable to such mechanical systems. 

Anarchism & Educational Policy Studies; A Marxist View of Joel Spring's "The Sorting Machine."

Science.gov (United States)

Berlowitz, Marvin J.

A critical analysis and interpretation of "The Sorting Machine" by Joel H. Spring is presented. The book, which uses a historical revisionist approach to trace the development and impact of the corporate-government-foundation network on the ideological orientation of the American educational system, makes its greatest contribution by…

Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke

OpenAIRE

McConnell, Alistair C; Moioli, Renan C; Brasil, Fabricio L; Vallejo, Marta; Corne, David W; Vargas, Patricia A; Stokes, Adam A

2017-01-01

OBJECTIVE: To review the state of the art of robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain-machine interfaces. Each patient has a unique clinical history and, in response to personalized treatment needs, research into individualized and at-home treatment options has expanded rapidly in recent years. This has resulted in the development of many devices and design strategies for use in stroke rehabilitation.METHODS: The development progression of ro...

Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

Science.gov (United States)

Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-Ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R; Eils, Roland; Grabe, Niels

2017-04-25

Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ductal carcinoma in situ (DCIS). Using a machine learning system, we succeeded in classifying the four histological types with 90.9% accuracy. Electron microscopy observations suggested that the activity of typical myoepithelial cells in DCIS was lowered. Through these observations as well as meta-analytic database analyses, we developed a paracrine cross-talk-based biological mechanism of DCIS progressing to invasive cancer. Our observations support novel approaches in clinical computational diagnostics as well as in therapy development against progression.

Self-Improving CNC Milling Machine

OpenAIRE

Spilling, Torjus

2014-01-01

This thesis is a study of the ability of a CNC milling machine to create parts for itself, and an evaluation of whether or not the machine is able to improve itself by creating new machine parts. This will be explored by using off-the-shelf parts to build an initial machine, using 3D printing/rapid prototyping to create any special parts needed for the initial build. After an initial working machine is completed, the design of the machine parts will be adjusted so that the machine can start p...

Machine Learning.

Science.gov (United States)

Kirrane, Diane E.

1990-01-01

As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

Machining of Metal Matrix Composites

CERN Document Server

2012-01-01

Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

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

OpenAIRE

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

2018-01-01

Low critical rotary speed and large vibration in the metal drive-line system of heavy-duty machine tool affect the machining precision seriously. Replacing metal drive-line with the CFRP drive-line can effectively solve this problem. Based on the composite laminated theory and the transfer matrix method (TMM), this paper puts forward a modified TMM to analyze dynamic characteristics of CFRP drive-line system. With this modified TMM, the CFRP drive-line of a heavy vertical miller is analyzed. ...

Machine technology: a survey

International Nuclear Information System (INIS)

Barbier, M.M.

1981-01-01

An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available

Development of iFab (Instant Foundry Adaptive Through Bits) Manufacturing Process and Machine Library

Science.gov (United States)

2012-08-01

input shaft , pump, gearbox, rack & pinion… Wheel assy wheel, tire, drive hub, lug, spindle , bearing… Braking brake disc/drum, caliper, friction...processes and associated machines is provided. Progress with respect to Task 3 (to design and develop the Manufacturing Capability Modeling Environment...of Military Ground Vehicle Design , Materials, and Processes ............... 4 4.2 Task 2 Manufacturing Knowledge Characterization

The man, the machine and the sacred: when the virtual reality reenchants the world

Directory of Open Access Journals (Sweden)

Olivier NANNIPIERI

2011-01-01

Full Text Available The rationality associated with the technical progress were able to let believe that the world became disillusioned. Now, far from disillusioning the world, certain technical devices reveal the sacred dimension inherent to any human activity. Indeed, paradoxically, we shall show that the human-machine interaction producing virtual environments is an experience of the sacred.

Strength analysis of refueling machine for large PWR in nuclear power plant

International Nuclear Information System (INIS)

Jia Xiaofeng; Zhou Guofeng; Bi Xiangjun; Ji Shunying

2010-01-01

The refueling machine of PWR plays important roles in nuclear power plant operation,and the dynamic analysis and strength assessment should be carried out to check its safety. In this paper, the finite element model (FEM) was established with the software ANSYS 12 for the refueling machine structure of large 1 000 MW PWR. The dynamic computations were performed under three work conditions, i.e. normal (cart starting and braking), abnormal (OBE) and accident(SSE) conditions, respectively. The structure responses (internal force and stress) of refueling machine under earthquake response spectrum in three directions were combined with the method of square root of square sum (SRSS). Moreover, the static response under gravity was also considered to construct the most critical conditions. With the simulated results, the strength of main structure, bold and weld joint,and the stability of landing leg for additional crane were assessed based on the RCCM code. At last, the local stress analysis of finger-form hook, which function is to take fuel assemblies, was also analyzed, while its strength was also assessed. The results show that the strengths of the refueling machine under various working conditions can meet the safety requirements. (authors)

Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

Science.gov (United States)

Boissoneault, Jeff; Sevel, Landrew; Letzen, Janelle; Robinson, Michael; Staud, Roland

2017-01-01

Chronic musculoskeletal pain condition often shows poor correlations between tissue abnormalities and clinical pain. Therefore, classification of pain conditions like chronic low back pain, osteoarthritis, and fibromyalgia depends mostly on self report and less on objective findings like X-ray or magnetic resonance imaging (MRI) changes. However, recent advances in structural and functional brain imaging have identified brain abnormalities in chronic pain conditions that can be used for illness classification. Because the analysis of complex and multivariate brain imaging data is challenging, machine learning techniques have been increasingly utilized for this purpose. The goal of machine learning is to train specific classifiers to best identify variables of interest on brain MRIs (i.e., biomarkers). This report describes classification techniques capable of separating MRI-based brain biomarkers of chronic pain patients from healthy controls with high accuracy (70-92%) using machine learning, as well as critical scientific, practical, and ethical considerations related to their potential clinical application. Although self-report remains the gold standard for pain assessment, machine learning may aid in the classification of chronic pain disorders like chronic back pain and fibromyalgia as well as provide mechanistic information regarding their neural correlates.

Progress in abrasive and grinding technology

CERN Document Server

Xu, Xipeng

2009-01-01

The grinding and abrasive processing of materials are machining techniques which use bonded or loose abrasives to remove material from workpieces. Due to the well-known advantages of grinding and abrasive processes, advances in abrasive and grinding technology are always of great import in enhancing both productivity and component quality. In order to highlight the recent progress made in this field, the editor invited 21 world-wide contributions with the aim of gathering together all of the achievements of leading researchers into a single publication. The authors of the 21 invited papers, of

Characteristics of laser assisted machining for silicon nitride ceramic according to machining parameters

International Nuclear Information System (INIS)

Kim, Jong Do; Lee, Su Jin; Suh, Jeong

2011-01-01

This paper describes the Laser Assisted Machining (LAM) that cuts and removes softened parts by locally heating the ceramic with laser. Silicon nitride ceramics can be machined with general machining tools as well, because YSiAlON, which was made up ceramics, is soften at about 1,000 .deg. C. In particular, the laser, which concentrates on highly dense energy, can locally heat materials and very effectively control the temperature of the heated part of specimen. Therefore, this paper intends to propose an efficient machining method of ceramic by deducing the machining governing factors of laser assisted machining and understanding its mechanism. While laser power is the machining factor that controls the temperature, the CBN cutting tool could cut the material more easily as the material gets deteriorated from the temperature increase by increasing the laser power, but excessive oxidation can negatively affect the quality of the material surface after machining. As the feed rate and cutting depth increase, the cutting force increases and tool lifespan decreases, but surface oxidation also decreases. In this experiment, the material can be cut to 3 mm of cutting depth. And based on the results of the experiment, the laser assisted machining mechanism is clarified

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

Directory of Open Access Journals (Sweden)

Ying Zhang

2018-01-01

Full Text Available With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks.

Science.gov (United States)

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-08

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

Science.gov (United States)

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-01

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms. PMID:29316702

Optimizing the way kinematical feed chains with great distance between slides are chosen for CNC machine tools

Science.gov (United States)

Lucian, P.; Gheorghe, S.

2017-08-01

This paper presents a new method, based on FRISCO formula, for optimizing the choice of the best control system for kinematical feed chains with great distance between slides used in computer numerical controlled machine tools. Such machines are usually, but not limited to, used for machining large and complex parts (mostly in the aviation industry) or complex casting molds. For such machine tools the kinematic feed chains are arranged in a dual-parallel drive structure that allows the mobile element to be moved by the two kinematical branches and their related control systems. Such an arrangement allows for high speed and high rigidity (a critical requirement for precision machining) during the machining process. A significant issue for such an arrangement it’s the ability of the two parallel control systems to follow the same trajectory accurately in order to address this issue it is necessary to achieve synchronous motion control for the two kinematical branches ensuring that the correct perpendicular position it’s kept by the mobile element during its motion on the two slides.

Quantitative criticism of literary relationships.

Science.gov (United States)

Dexter, Joseph P; Katz, Theodore; Tripuraneni, Nilesh; Dasgupta, Tathagata; Kannan, Ajay; Brofos, James A; Bonilla Lopez, Jorge A; Schroeder, Lea A; Casarez, Adriana; Rabinovich, Maxim; Haimson Lushkov, Ayelet; Chaudhuri, Pramit

2017-04-18

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships ("intertextuality") and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term "quantitative criticism," focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca's main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions.

Progress in Titanium Metal Powder Injection Molding

Directory of Open Access Journals (Sweden)

Randall M. German

2013-08-01

Full Text Available Metal powder injection molding is a shaping technology that has achieved solid scientific underpinnings. It is from this science base that recent progress has occurred in titanium powder injection molding. Much of the progress awaited development of the required particles with specific characteristics of particle size, particle shape, and purity. The production of titanium components by injection molding is stabilized by a good understanding of how each process variable impacts density and impurity level. As summarized here, recent research has isolated the four critical success factors in titanium metal powder injection molding (Ti-MIM that must be simultaneously satisfied—density, purity, alloying, and microstructure. The critical role of density and impurities, and the inability to remove impurities with sintering, compels attention to starting Ti-MIM with high quality alloy powders. This article addresses the four critical success factors to rationalize Ti-MIM processing conditions to the requirements for demanding applications in aerospace and medical fields. Based on extensive research, a baseline process is identified and reported here with attention to linking mechanical properties to the four critical success factors.

Real-time spot size camera for pulsed high-energy radiographic machines

International Nuclear Information System (INIS)

Watson, S.A.

1993-01-01

The focal spot size of an x-ray source is a critical parameter which degrades resolution in a flash radiograph. For best results, a small round focal spot is required. Therefore, a fast and accurate measurement of the spot size is highly desirable to facilitate machine tuning. This paper describes two systems developed for Los Alamos National Laboratory's Pulsed High-Energy Radiographic Machine Emitting X-rays (PHERMEX) facility. The first uses a CCD camera combined with high-brightness floors, while the second utilizes phosphor storage screens. Other techniques typically record only the line spread function on radiographic film, while systems in this paper measure the more general two-dimensional point-spread function and associated modulation transfer function in real time for shot-to-shot comparison

Energy-efficient electrical machines by new materials. Superconductivity in large electrical machines

International Nuclear Information System (INIS)

Frauenhofer, Joachim; Arndt, Tabea; Grundmann, Joern

2013-01-01

The implementation of superconducting materials in high-power electrical machines results in significant advantages regarding efficiency, size and dynamic behavior when compared to conventional machines. The application of HTS (high-temperature superconductors) in electrical machines allows significantly higher power densities to be achieved for synchronous machines. In order to gain experience with the new technology, Siemens carried out a series of development projects. A 400 kW model motor for the verification of a concept for the new technology was followed by a 4000 kV A generator as highspeed machine - as well as a low-speed 4000 kW propeller motor with high torque. The 4000 kVA generator is still employed to carry out long-term tests and to check components. Superconducting machines have significantly lower weight and envelope dimensions compared to conventional machines, and for this reason alone, they utilize resources better. At the same time, operating losses are slashed to about half and the efficiency increases. Beyond this, they set themselves apart as a result of their special features in operation, such as high overload capability, stiff alternating load behavior and low noise. HTS machines provide significant advantages where the reduction of footprint, weight and losses or the improved dynamic behavior results in significant improvements of the overall system. Propeller motors and generators,for ships, offshore plants, in wind turbine and hydroelectric plants and in large power stations are just some examples. HTS machines can therefore play a significant role when it comes to efficiently using resources and energy as well as reducing the CO 2 emissions.

Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.

Science.gov (United States)

Thabtah, Fadi

2018-02-13

Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of linguistic, communication, cognitive, and social skills and abilities. Despite being diagnosed with ASD, some individuals exhibit outstanding scholastic, non-academic, and artistic capabilities, in such cases posing a challenging task for scientists to provide answers. In the last few years, ASD has been investigated by social and computational intelligence scientists utilizing advanced technologies such as machine learning to improve diagnostic timing, precision, and quality. Machine learning is a multidisciplinary research topic that employs intelligent techniques to discover useful concealed patterns, which are utilized in prediction to improve decision making. Machine learning techniques such as support vector machines, decision trees, logistic regressions, and others, have been applied to datasets related to autism in order to construct predictive models. These models claim to enhance the ability of clinicians to provide robust diagnoses and prognoses of ASD. However, studies concerning the use of machine learning in ASD diagnosis and treatment suffer from conceptual, implementation, and data issues such as the way diagnostic codes are used, the type of feature selection employed, the evaluation measures chosen, and class imbalances in data among others. A more serious claim in recent studies is the development of a new method for ASD diagnoses based on machine learning. This article critically analyses these recent investigative studies on autism, not only articulating the aforementioned issues in these studies but also recommending paths forward that enhance machine learning use in ASD with respect to conceptualization, implementation, and data. Future studies concerning machine learning in autism research are greatly benefitted by such proposals.

Environmental assessment for consolidation of certain materials and machines for nuclear criticality experiments and training

International Nuclear Information System (INIS)

1996-01-01

In support of its assigned missions and because of the importance of avoiding nuclear criticality accidents, DOE has adopted a policy to reduce identifiable nuclear criticality safety risks and to protect the public, workers, government property and essential operations from the effects of a criticality accident. In support of this policy, the Los Alamos Critical Experiments Facility (LACEF) at the Los Alamos National Laboratory (LANL) Technical Area (TA) 18, provides a program of general purpose critical experiments. This program, the only remaining one of its kind in the United States, seeks to maintain a sound basis of information for criticality control in those physical situations that DOE will encounter in handling and storing fissionable material in the future, and ensuring the presence of a community of individuals competent in practicing this control

A future of living machines?: International trends and prospects in biomimetic and biohybrid systems

Science.gov (United States)

Prescott, Tony J.; Lepora, Nathan; Vershure, Paul F. M. J.

2014-03-01

Research in the fields of biomimetic and biohybrid systems is developing at an accelerating rate. Biomimetics can be understood as the development of new technologies using principles abstracted from the study of biological systems, however, biomimetics can also be viewed from an alternate perspective as an important methodology for improving our understanding of the world we live in and of ourselves as biological organisms. A biohybrid entity comprises at least one artificial (engineered) component combined with a biological one. With technologies such as microscale mobile computing, prosthetics and implants, humankind is moving towards a more biohybrid future in which biomimetics helps us to engineer biocompatible technologies. This paper reviews recent progress in the development of biomimetic and biohybrid systems focusing particularly on technologies that emulate living organisms—living machines. Based on our recent bibliographic analysis [1] we examine how biomimetics is already creating life-like robots and identify some key unresolved challenges that constitute bottlenecks for the field. Drawing on our recent research in biomimetic mammalian robots, including humanoids, we review the future prospects for such machines and consider some of their likely impacts on society, including the existential risk of creating artifacts with significant autonomy that could come to match or exceed humankind in intelligence. We conclude that living machines are more likely to be a benefit than a threat but that we should also ensure that progress in biomimetics and biohybrid systems is made with broad societal consent.

COMPARISION OF FUZZY PERT APPROACHES IN MACHINE PRODUCTION PROCESS

Directory of Open Access Journals (Sweden)

İRFAN ERTUĞRUL

2013-06-01

Full Text Available In traditional PERT (Program Evaluation and Review Technique activity durations are represented as crisp numbers and assumed that they are drawn from beta distribution. However, in real life the duration of the activities are usually difficult to estimate precisely.  In order to overcome this difficulty, there are studies in the literature that combine fuzzy set theory and PERT method. In this study, two fuzzy PERT approaches proposed by different authors are employed to find the degrees of criticality of each path in the network and comparison of these two methods is also given. Furthermore, by the help of these methods the criticality of the activities in the marble machine production process of a company that manufactures machinery is determined and results are compared.

VIRTUAL MACHINES IN EDUCATION – CNC MILLING MACHINE WITH SINUMERIK 840D CONTROL SYSTEM

Directory of Open Access Journals (Sweden)

Ireneusz Zagórski

2014-11-01

Full Text Available Machining process nowadays could not be conducted without its inseparable element: cutting edge and frequently numerically controlled milling machines. Milling and lathe machining centres comprise standard equipment in many companies of the machinery industry, e.g. automotive or aircraft. It is for that reason that tertiary education should account for this rising demand. This entails the introduction into the curricula the forms which enable visualisation of machining, milling process and virtual production as well as virtual machining centres simulation. Siemens Virtual Machine (Virtual Workshop sets an example of such software, whose high functionality offers a range of learning experience, such as: learning the design of machine tools, their configuration, basic operation functions as well as basics of CNC.

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

Science.gov (United States)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

Nonplanar machines

International Nuclear Information System (INIS)

Ritson, D.

1989-05-01

This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

Ultraprecision machining. Cho seimitsu kako

Energy Technology Data Exchange (ETDEWEB)

Suga, T [The Univ. of Tokyo, Tokyo (Japan). Research Center for Advanced Science and Technology

1992-10-05

It is said that the image of ultraprecision improved from 0.1[mu]m to 0.01[mu]m within recent years. Ultraprecision machining is a production technology which forms what is called nanotechnology with ultraprecision measuring and ultraprecision control. Accuracy means average machined sizes close to a required value, namely the deflection errors are small; precision means the scattered errors of machined sizes agree very closely. The errors of machining are related to both of the above errors and ultraprecision means the combined errors are very small. In the present ultraprecision machining, the relative precision to the size of a machined object is said to be in the order of 10[sup -6]. The flatness of silicon wafers is usually less than 0.5[mu]m. It is the fact that the appearance of atomic scale machining is awaited as the limit of ultraprecision machining. The machining of removing and adding atomic units using scanning probe microscopes are expected to reach the limit actually. 2 refs.

Theory and practice in machining systems

CERN Document Server

Ito, Yoshimi

2017-01-01

This book describes machining technology from a wider perspective by considering it within the machining space. Machining technology is one of the metal removal activities that occur at the machining point within the machining space. The machining space consists of structural configuration entities, e.g., the main spindle, the turret head and attachments such the chuck and mandrel, and also the form-generating movement of the machine tool itself. The book describes fundamental topics, including the form-generating movement of the machine tool and the important roles of the attachments, before moving on to consider the supply of raw materials into the machining space, and the discharge of swarf from it, and then machining technology itself. Building on the latest research findings “Theory and Practice in Machining System” discusses current challenges in machining. Thus, with the inclusion of introductory and advanced topics, the book can be used as a guide and survey of machining technology for students an...

Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review.

Science.gov (United States)

Orrù, Graziella; Pettersson-Yeo, William; Marquand, Andre F; Sartori, Giuseppe; Mechelli, Andrea

2012-04-01

Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical and functional differences between healthy individuals and patients suffering a wide range of neurological and psychiatric disorders. Significant only at group level however these findings have had limited clinical translation, and recent attention has turned toward alternative forms of analysis, including Support-Vector-Machine (SVM). A type of machine learning, SVM allows categorisation of an individual's previously unseen data into a predefined group using a classification algorithm, developed on a training data set. In recent years, SVM has been successfully applied in the context of disease diagnosis, transition prediction and treatment prognosis, using both structural and functional neuroimaging data. Here we provide a brief overview of the method and review those studies that applied it to the investigation of Alzheimer's disease, schizophrenia, major depression, bipolar disorder, presymptomatic Huntington's disease, Parkinson's disease and autistic spectrum disorder. We conclude by discussing the main theoretical and practical challenges associated with the implementation of this method into the clinic and possible future directions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Machine learning in jet physics

CERN Multimedia

CERN. Geneva

2018-01-01

High energy collider experiments produce several petabytes of data every year. Given the magnitude and complexity of the raw data, machine learning algorithms provide the best available platform to transform and analyse these data to obtain valuable insights to understand Standard Model and Beyond Standard Model theories. These collider experiments produce both quark and gluon initiated hadronic jets as the core components. Deep learning techniques enable us to classify quark/gluon jets through image recognition and help us to differentiate signals and backgrounds in Beyond Standard Model searches at LHC. We are currently working on quark/gluon jet classification and progressing in our studies to find the bias between event generators using domain adversarial neural networks (DANN). We also plan to investigate top tagging, weak supervision on mixed samples in high energy physics, utilizing transfer learning from simulated data to real experimental data.

Face machines

Energy Technology Data Exchange (ETDEWEB)

Hindle, D.

1999-06-01

The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.

Dynamic balancing of super-critical rotating structures using slow-speed data via parametric excitation

Science.gov (United States)

Tresser, Shachar; Dolev, Amit; Bucher, Izhak

2018-02-01

High-speed machinery is often designed to pass several "critical speeds", where vibration levels can be very high. To reduce vibrations, rotors usually undergo a mass balancing process, where the machine is rotated at its full speed range, during which the dynamic response near critical speeds can be measured. High sensitivity, which is required for a successful balancing process, is achieved near the critical speeds, where a single deflection mode shape becomes dominant, and is excited by the projection of the imbalance on it. The requirement to rotate the machine at high speeds is an obstacle in many cases, where it is impossible to perform measurements at high speeds, due to harsh conditions such as high temperatures and inaccessibility (e.g., jet engines). This paper proposes a novel balancing method of flexible rotors, which does not require the machine to be rotated at high speeds. With this method, the rotor is spun at low speeds, while subjecting it to a set of externally controlled forces. The external forces comprise a set of tuned, response dependent, parametric excitations, and nonlinear stiffness terms. The parametric excitation can isolate any desired mode, while keeping the response directly linked to the imbalance. A software controlled nonlinear stiffness term limits the response, hence preventing the rotor to become unstable. These forces warrant sufficient sensitivity required to detect the projection of the imbalance on any desired mode without rotating the machine at high speeds. Analytical, numerical and experimental results are shown to validate and demonstrate the method.

Machine Learning Classification of Buildings for Map Generalization

Directory of Open Access Journals (Sweden)

Jaeeun Lee

2017-10-01

Full Text Available A critical problem in mapping data is the frequent updating of large data sets. To solve this problem, the updating of small-scale data based on large-scale data is very effective. Various map generalization techniques, such as simplification, displacement, typification, elimination, and aggregation, must therefore be applied. In this study, we focused on the elimination and aggregation of the building layer, for which each building in a large scale was classified as “0-eliminated,” “1-retained,” or “2-aggregated.” Machine-learning classification algorithms were then used for classifying the buildings. The data of 1:1000 scale and 1:25,000 scale digital maps obtained from the National Geographic Information Institute were used. We applied to these data various machine-learning classification algorithms, including naive Bayes (NB, decision tree (DT, k-nearest neighbor (k-NN, and support vector machine (SVM. The overall accuracies of each algorithm were satisfactory: DT, 88.96%; k-NN, 88.27%; SVM, 87.57%; and NB, 79.50%. Although elimination is a direct part of the proposed process, generalization operations, such as simplification and aggregation of polygons, must still be performed for buildings classified as retained and aggregated. Thus, these algorithms can be used for building classification and can serve as preparatory steps for building generalization.

Tattoo machines, needles and utilities.

Science.gov (United States)

Rosenkilde, Frank

2015-01-01

Starting out as a professional tattooist back in 1977 in Copenhagen, Denmark, Frank Rosenkilde has personally experienced the remarkable development of tattoo machines, needles and utilities: all the way from home-made equipment to industrial products of substantially improved quality. Machines can be constructed like the traditional dual-coil and single-coil machines or can be e-coil, rotary and hybrid machines, with the more convenient and precise rotary machines being the recent trend. This development has resulted in disposable needles and utilities. Newer machines are more easily kept clean and protected with foil to prevent crosscontaminations and infections. The machines and the tattooists' knowledge and awareness about prevention of infection have developed hand-in-hand. For decades, Frank Rosenkilde has been collecting tattoo machines. Part of his collection is presented here, supplemented by his personal notes. © 2015 S. Karger AG, Basel.

Design of rotating electrical machines

CERN Document Server

Pyrhonen , Juha; Hrabovcova , Valeria

2013-01-01

In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

Directory of Open Access Journals (Sweden)

POPESCU Adrian

2015-11-01

Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

MITS machine operations

International Nuclear Information System (INIS)

Flinchem, J.

1980-01-01

This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility

Coordinate measuring machines

DEFF Research Database (Denmark)

De Chiffre, Leonardo

This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...... and uncertainty during coordinate measurements, 3) Digitalisation and Reverse Engineering. This document contains a short description of each step in the exercise and schemes with room for taking notes of the results.......This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceability...

Multi-response optimization of machining characteristics in ultrasonic machining of WC-Co composite through Taguchi method and grey-fuzzy logic

Directory of Open Access Journals (Sweden)

Ravi Pratap Singh

2018-01-01

Full Text Available This article addresses the application of grey based fuzzy logic coupled with Taguchi’s approach for optimization of multi performance characteristics in ultrasonic machining of WC-Co composite material. The Taguchi’s L-36 array has been employed to conduct the experimentation and also to observe the influence of different process variables (power rating, cobalt content, tool geometry, thickness of work piece, tool material, abrasive grit size on machining characteristics. Grey relational fuzzy grade has been computed by converting the multiple responses, i.e., material removal rate and tool wear rate obtained from Taguchi’s approach into a single performance characteristic using grey based fuzzy logic. In addition, analysis of variance (ANOVA has also been attempted in a view to identify the significant parameters. Results revealed grit size and power rating as leading parameters for optimization of multi performance characteristics. From the microstructure analysis, the mode of material deformation has been observed and the critical parameters (i.e., work material properties, grit size, and power rating for the deformation mode have been established.

Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.

Science.gov (United States)

Janssen, Ronald J; Mourão-Miranda, Janaina; Schnack, Hugo G

2018-04-22

Psychiatric prognosis is a difficult problem. Making a prognosis requires looking far into the future, as opposed to making a diagnosis, which is concerned with the current state. During the follow-up period, many factors will influence the course of the disease. Combined with the usually scarcer longitudinal data and the variability in the definition of outcomes/transition, this makes prognostic predictions a challenging endeavor. Employing neuroimaging data in this endeavor introduces the additional hurdle of high dimensionality. Machine-learning techniques are especially suited to tackle this challenging problem. This review starts with a brief introduction to machine learning in the context of its application to clinical neuroimaging data. We highlight a few issues that are especially relevant for prediction of outcome and transition using neuroimaging. We then review the literature that discusses the application of machine learning for this purpose. Critical examination of the studies and their results with respect to the relevant issues revealed the following: 1) there is growing evidence for the prognostic capability of machine-learning-based models using neuroimaging; and 2) reported accuracies may be too optimistic owing to small sample sizes and the lack of independent test samples. Finally, we discuss options to improve the reliability of (prognostic) prediction models. These include new methodologies and multimodal modeling. Paramount, however, is our conclusion that future work will need to provide properly (cross-)validated accuracy estimates of models trained on sufficiently large datasets. Nevertheless, with the technological advances enabling acquisition of large databases of patients and healthy subjects, machine learning represents a powerful tool in the search for psychiatric biomarkers. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Electric machine

Science.gov (United States)

El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

2012-07-17

An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

Design and realization on function of pre-forming and continuous winding for HT-7U special winding machine

International Nuclear Information System (INIS)

Yu Jie; Gao Daming; Wen Jun; Zhu Wenhua; Cheng Leping; Tao Yuming

2000-05-01

The winding machine is one of the critical facilities for R and D of HT-7U construction. The machine mainly consists of five parts, CICC pay-off spool, a four-rollers straightening assembly, a four-roller forming/bending assembly, continuous winding structure and CNC control system with three-axis CNC control. The facility is needed for CICC magnet fabrication of HT-7U. The main requirements of the winding machine are: continuous winding to reduce number of joints inside the coils; pre-forming CICC conductor to avoid winding with tension; suitable for all TF and PF coils within the scope of various coil shape and dimension limit; improving the configuration tolerance, specially flatness of the CICC conductor. The author emphasizes on the design and realization on function of Pre-forming and Continuous Winding for HT-7U special winding machine. The winding machine with high accuracy has just been developed and applied to the construction of HT-7U model coils

Machine Learning and Radiology

Science.gov (United States)

Wang, Shijun; Summers, Ronald M.

2012-01-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

Tribology in machine design

CERN Document Server

Stolarski, Tadeusz

1999-01-01

""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

Summary session B: more observations at existing accelerators and concerns for future machines

International Nuclear Information System (INIS)

Harkay, K.

2004-01-01

Beginning with the International Workshop on Multibunch Instabilities in Tsukuba (KEK, 1997) (1), and continuing with special Electron Cloud workshops in Santa Fe (LANL/ANL, 2000) (2), Tsukuba (KEK, 2001) (3), Geneva (CERN, 2002) (4) and the present workshop, it is remarkable that new observations of electron cloud effects continue to be reported, spreading from proton rings to positron and electron rings to heavy-ion linacs and rings. This paper summarizes a rich collection of recent observations, as well as issues for future machines, presented in Session B. An attempt is also made to summarize conclusions and questions raised by the presenters. Efforts at several proton, positron, electron (colliders), and ion rings and linacs continue to characterize and finetune our understanding of electron cloud effects and the generation and suppression of electron clouds. An incomplete outline of the topics presented and related machines follows: (1) EC suppression - (a) Scrubbing (SPS, RHIC); (b) Solenoid (PEPII, KEKB, KEK-PS, RHIC, PSR); (c) TiN, NEG (PEPII, PSR, RHIC, SPS, others); and (d) EC Collectors (HCX, KEK-PS); (2) EC vs. pressure (RHIC, SPS, KEKB, PEPII); (3) Bunch length effect (SPS, RHIC); (4) Memory effect and EC lifetime (PSR, KEKB, KEKPS, SPS); and (5) New EC diagnostics - (a) RFA in quads (SPS, PSR (planned)); (b) EC sweeper (PSR, KEK-PS); (c) HCX GESD: electron and gas emission rates; (d) Microwave TE (more work needed). Significant progress has been made in identifying and quantifying those surface parameters most critical in the accurate prediction of electron cloud effects. A strong focus of experimental efforts is in benchmarking analytical and numerical modeling with measured data, and some consistency is emerging, although work remains to be done.

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

Directory of Open Access Journals (Sweden)

Woong-Kirl Choi

2018-01-01

Full Text Available Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks.

A Universal Reactive Machine

DEFF Research Database (Denmark)

Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

1997-01-01

Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...

Intellectual Control System of Processing on CNC Machines

Science.gov (United States)

Nekrasov, R. Y.; Lasukov, A. A.; Starikov, A. I.; Soloviev, I. V.; Bekareva, O. V.

2016-04-01

Scientific and technical progress makes great demands for quality of engineering production. The priority is to ensure metalworking equipment with required dimensional accuracy during the entire period of operation at minimum manufacturing costs. In article considered the problem of increasing of accuracy of processing products on CNC. The authors offers a solution to the problem by providing compensating adjustment in the trajectory of the cutting tool and machining mode. The necessity of creation of mathematical models of processes behavior in an automated technological system operations (OATS). Based on the research, authors have proposed a generalized diagram of diagnosis and input operative correction and approximate mathematical models of individual processes of diagnosis.

Consequences of heavy machining vis à vis the machine structure – typical applications

International Nuclear Information System (INIS)

Leuch, M

2011-01-01

StarragHeckert has built 5 axis machines since the middle of the 80s for heavy duty milling. The STC-Centres are predominantly utilised in the aerospace industry, especially for milling structural workpieces, casings or Impellers made out of titanium and steel. StarragHeckert has a history of building machines for high performance milling. The machining of these components includes high forces thus spreading the wheat from the chaff. Although FEM calculations and multi-body simulations are carried out in the early stages of development, this paper will illustrate how the real process stability with modal analysis and cutting trials is determined. The experiment observes chatter stability to identify if the machine devices are adequate for the application or if the design has to be improved. Machining parameters of industrial applications are demonstrating the process stability for five axis heavy duties milling of StarragHeckert machine.

Cancer classification through filtering progressive transductive support vector machine based on gene expression data

Science.gov (United States)

Lu, Xinguo; Chen, Dan

2017-08-01

Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

Classifying cognitive profiles using machine learning with privileged information in Mild Cognitive Impairment

Directory of Open Access Journals (Sweden)

Hanin Hamdan Alahmadi

2016-11-01

Full Text Available Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalised Matrix Learning Vector Quantization (GMLVQ classifiers to discriminate patients with Mild Cognitive Impairment (MCI from healthy controls based on their cognitive skills. Further, we adopted a ``Learning with privileged information'' approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants.MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls based on the learning performance and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on the learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1 when overall fMRI signal for structured stimuli is

Virtual Machine in Automation Projects

OpenAIRE

Xing, Xiaoyuan

2010-01-01

Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper is to examine how to better utilize virtual machine for the automation projects. This paper designs different project scenarios using virtual machine. It analyzes installability, performance and stability of virtual machine from the test results. Technical solutions concerning virtual machine are discussed such as the conversion with physical...

The Buttonhole Machine. Module 13.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the bottonhole machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers two topics: performing special operations on the buttonhole machine (parts and purpose) and performing special operations on the buttonhole machine (gauged buttonholes). For each topic these components are…

Introduction to machine learning.

Science.gov (United States)

Baştanlar, Yalin; Ozuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

Machine learning-enabled discovery and design of membrane-active peptides.

Science.gov (United States)

Lee, Ernest Y; Wong, Gerard C L; Ferguson, Andrew L

2017-07-08

Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen sequence space and guide experiment towards promising candidates with high putative activity. In this mini-review, we provide an introduction to antimicrobial peptides and summarize recent advances in machine learning-enabled antimicrobial peptide discovery and design with a focus on a recent work Lee et al. Proc. Natl. Acad. Sci. USA 2016;113(48):13588-13593. This study reports the development of a support vector machine classifier to aid in the design of membrane active peptides. We use this model to discover membrane activity as a multiplexed function in diverse peptide families and provide interpretable understanding of the physicochemical properties and mechanisms governing membrane activity. Experimental validation of the classifier reveals it to have learned membrane activity as a unifying signature of antimicrobial peptides with diverse modes of action. Some of the discriminating rules by which it performs classification are in line with existing "human learned" understanding, but it also unveils new previously unknown determinants and multidimensional couplings governing membrane activity. Integrating machine learning with targeted experimentation can guide both antimicrobial peptide discovery and design and new understanding of the properties and mechanisms underpinning their modes of action. Copyright © 2017 Elsevier Ltd. All rights reserved.

MCNP Progress & Performance Improvements

Energy Technology Data Exchange (ETDEWEB)

Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bull, Jeffrey S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rising, Michael Evan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-04-14

Twenty-eight slides give information about the work of the US DOE/NNSA Nuclear Criticality Safety Program on MCNP6 under the following headings: MCNP6.1.1 Release, with ENDF/B-VII.1; Verification/Validation; User Support & Training; Performance Improvements; and Work in Progress. Whisper methodology will be incorporated into the code, and run speed should be increased.

Applied machining technology

CERN Document Server

Tschätsch, Heinz

2010-01-01

Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

Machine Learning Interface for Medical Image Analysis.

Science.gov (United States)

Zhang, Yi C; Kagen, Alexander C

2017-10-01

TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

Deformation-phase transformation coupling mechanism of white layer formation in high speed machining of FGH95 Ni-based superalloy

Energy Technology Data Exchange (ETDEWEB)

Du, Jin [School of Mechanical and Automotive Engineering, Qilu University of Technology, Jinan, Shandong 250353 (China); Liu, Zhanqiang, E-mail: melius@sdu.edu.cn [School of Mechanical Engineering, Shandong University, Jinan, Shandong 250061 (China); Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Shandong University, Ministry of Education, Shandong (China); Lv, Shaoyu [School of Mechanical Engineering, Shandong University, Jinan, Shandong 250061 (China)

2014-02-15

Ni-based superalloy represents a significant metal portion of the aircraft critical structural and engine components. When these critical structural components in aerospace industry are manufactured with the objective to reach high reliability levels and excellent service performance, surface integrity is one of the most relevant parameter used for evaluating the quality of finish machined surfaces. In the study of surface integrity, the formation white layer is a very important research topic. The formation of white layer on the Ni-based superalloy machined surface will reduce the machined parts service performance and fatigue life. This paper was conducted to determine the effects of cutting speed on white layer formation in high speed machining of FGH95 Ni-based superalloy. Optical microscope, scanning electron microscope and X-ray diffraction were employed to analyze the elements and microstructures of white layer and bulk materials. The statistical analysis for grain numbers was executed to study the influence of cutting speed on the grain refinement in the machined surface. The investigation results showed that white layer exhibits significantly different microstructures with the bulk materials. It shows densification, no obvious structural features characteristic. The microstructure and phase of Ni-based solid solution changed during cutting process. The increase of cutting speed causes the increase of white layer thickness when the cutting speed is less than 2000 m/min. However, white layer thickness reduces with the cutting speed further increase. The higher the cutting speed, the more serious grains refinement in machined surface. 2-D FEM for machining FGH95 were carried out to simulate the cutting process and obtained the cutting temperature field, cutting strain field and strain rate field. The impact mechanisms of cutting temperature, cutting strain and strain rates on white layer formation were analyzed. At last, deformation-phase transformation

Defect detection and classification of machined surfaces under multiple illuminant directions

Science.gov (United States)

Liao, Yi; Weng, Xin; Swonger, C. W.; Ni, Jun

2010-08-01

Continuous improvement of product quality is crucial to the successful and competitive automotive manufacturing industry in the 21st century. The presence of surface porosity located on flat machined surfaces such as cylinder heads/blocks and transmission cases may allow leaks of coolant, oil, or combustion gas between critical mating surfaces, thus causing damage to the engine or transmission. Therefore 100% inline inspection plays an important role for improving product quality. Although the techniques of image processing and machine vision have been applied to machined surface inspection and well improved in the past 20 years, in today's automotive industry, surface porosity inspection is still done by skilled humans, which is costly, tedious, time consuming and not capable of reliably detecting small defects. In our study, an automated defect detection and classification system for flat machined surfaces has been designed and constructed. In this paper, the importance of the illuminant direction in a machine vision system was first emphasized and then the surface defect inspection system under multiple directional illuminations was designed and constructed. After that, image processing algorithms were developed to realize 5 types of 2D or 3D surface defects (pore, 2D blemish, residue dirt, scratch, and gouge) detection and classification. The steps of image processing include: (1) image acquisition and contrast enhancement (2) defect segmentation and feature extraction (3) defect classification. An artificial machined surface and an actual automotive part: cylinder head surface were tested and, as a result, microscopic surface defects can be accurately detected and assigned to a surface defect class. The cycle time of this system can be sufficiently fast that implementation of 100% inline inspection is feasible. The field of view of this system is 150mm×225mm and the surfaces larger than the field of view can be stitched together in software.

Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

2017-04-21

The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

Machine Protection

International Nuclear Information System (INIS)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

Machine Protection

Energy Technology Data Exchange (ETDEWEB)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)

2012-07-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Machine Protection

CERN Document Server

Zerlauth, Markus; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Development of a Crush and Mix Machine for Composite Brick Fabrication

International Nuclear Information System (INIS)

Sothea, Kruy; Fazli, Nik; Hamdi, M.; Aoyama, Hideki

2011-01-01

Currently, people are more and more concerned about the environmental protection. Municipal solid wastes (MSW) have bad effect on the environment and also human health. In addition, the amounts of municipal solid wastes are increasing due to the economic development, density of population, especially in the developing countries and they are recycled in a little percentage. To address this problem, the composite brick forming machine was designed and developed to make brick using combination of MSW and mortar. The machine consists of two independent parts, crusher and mixer part, and molding part. This paper explores the design of crusher and mixer part. The crusher has ability to cut MSW such as wood, paper and plastic into small size. There are two mixers; one is used for making mortar and other use for making slurry. FEA analyses were carried out to address the suitable strength of the critical parts of the crusher which ensures that crusher can run properly with high efficiency. The experimentation of the crusher shows that it has high performance for cutting MSW. The mixers also work very well in high efficiency. The results of composite brick testing have been shown that ability of the machine can performance well. This is the innovation of crush and mix machine which is portable and economic by using MSW in replacement of sand.

Dictionary of machine terms

International Nuclear Information System (INIS)

1990-06-01

This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.

HTS machine laboratory prototype

DEFF Research Database (Denmark)

machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

2011-01-01

Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

A new machine for continuous renal replacement therapy: from development to clinical testing.

Science.gov (United States)

Ricci, Zaccaria; Salvatori, Gabriella; Bonello, Monica; Ratanarat, Ranistha; Andrikos, Emilios; Dan, Maurizio; Piccinni, Pasquale; Ronco, Claudio

2005-01-01

A new continuous renal replacement therapy machine has been designed to fulfill the expectations of nephrologists and intensivists operating in the common ground of critical care nephrology. The new equipment is called Prismaflex and it is the natural evolution of the PRISMA machine that has been utilized worldwide for continuous renal replacement therapy in the last 10 years. The authors performed a preliminary alpha-trial to establish the usability, flexibility and reliability of the new device. Accuracy was also tested by recording various operational parameters during different intermittent and continuous renal replacement modalities during 62 treatments. This article will describe our first experience with this new device and touch upon the historic and technologic background leading to its development.

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

OpenAIRE

Parker, David L.; Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardize...

Machine vision systems using machine learning for industrial product inspection

Science.gov (United States)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Machine Directional Register System Modeling for Shaft-Less Drive Gravure Printing Machines

Directory of Open Access Journals (Sweden)

Shanhui Liu

2013-01-01

Full Text Available In the latest type of gravure printing machines referred to as the shaft-less drive system, each gravure printing roller is driven by an individual servo motor, and all motors are electrically synchronized. The register error is regulated by a speed difference between the adjacent printing rollers. In order to improve the control accuracy of register system, an accurate mathematical model of the register system should be investigated for the latest machines. Therefore, the mathematical model of the machine directional register (MDR system is studied for the multicolor gravure printing machines in this paper. According to the definition of the MDR error, the model is derived, and then it is validated by the numerical simulation and experiments carried out in the experimental setup of the four-color gravure printing machines. The results show that the established MDR system model is accurate and reliable.

Soft Material-Enabled, Flexible Hybrid Electronics for Medicine, Healthcare, and Human-Machine Interfaces.

Science.gov (United States)

Herbert, Robert; Kim, Jong-Hoon; Kim, Yun Soung; Lee, Hye Moon; Yeo, Woon-Hong

2018-01-24

Flexible hybrid electronics (FHE), designed in wearable and implantable configurations, have enormous applications in advanced healthcare, rapid disease diagnostics, and persistent human-machine interfaces. Soft, contoured geometries and time-dynamic deformation of the targeted tissues require high flexibility and stretchability of the integrated bioelectronics. Recent progress in developing and engineering soft materials has provided a unique opportunity to design various types of mechanically compliant and deformable systems. Here, we summarize the required properties of soft materials and their characteristics for configuring sensing and substrate components in wearable and implantable devices and systems. Details of functionality and sensitivity of the recently developed FHE are discussed with the application areas in medicine, healthcare, and machine interactions. This review concludes with a discussion on limitations of current materials, key requirements for next generation materials, and new application areas.

Machine learning and radiology.

Science.gov (United States)

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Guest Editorial Electric Machines in Renewable Energy Applications

Energy Technology Data Exchange (ETDEWEB)

Aliprantis, Dionysios; El-Sharkawi, Mohamed; Muljadi, Eduard; Brown, Ian; Chiba, Akira; Dorrell, David; Erlich, Istvan; Kerszenbaum, Isidor Izzy; Levi, Emil; Mayor, Kevin; Mohammed, Osama; Papathanassiou, Stavros; Popescu, Mircea; Qiao, Wei; Wu, Dezheng

2015-12-01

The main objective of this special issue is to collect and disseminate publications that highlight recent advances and breakthroughs in the area of renewable energy resources. The use of these resources for production of electricity is increasing rapidly worldwide. As of 2015, a majority of countries have set renewable electricity targets in the 10%-40% range to be achieved by 2020-2030, with a few notable exceptions aiming for 100% generation by renewables. We are experiencing a truly unprecedented transition away from fossil fuels, driven by environmental, energy security, and socio-economic factors.Electric machines can be found in a wide range of renewable energy applications, such as wind turbines, hydropower and hydrokinetic systems, flywheel energy storage devices, and low-power energy harvesting systems. Hence, the design of reliable, efficient, cost-effective, and controllable electric machines is crucial in enabling even higher penetrations of renewable energy systems in the smart grid of the future. In addition, power electronic converter design and control is critical, as they provide essential controllability, flexibility, grid interface, and integration functions.

Ultrasound for critical care physicians: ghost in the machine

Directory of Open Access Journals (Sweden)

Davidson R

2018-02-01

Full Text Available No abstract available. Article truncated after 150 words. A 53-year-old woman presented to the emergency department after a sudden cardiac arrest at home. The patient had a history of asthma and tracheal stenosis and had progressive shortness of breath over the previous days. The patient’s family noticed a “thump” sound from the patient’s room, and found her apneic. They called 911 and began cardiopulmonary resuscitation. Paramedics arrived on the scene, found an initial rhythm of pulseless electrical activity. The patient eventually achieved return of spontaneous circulation and was transported to the hospital. On arrival the patient was in normal sinus rhythm, with a heart rate of 110 beats per minute. Blood pressure was 80/45 mmHg, on an epinephrine infusion. The patient was afebrile, endotracheally intubated, unresponsive and ventilated at 30 breaths per minute. An initial chest radiograph was compatible with aspiration pneumonitis and a small pneumothorax. Initial electrocardiogram on arrival had 1mm ST-segment depressions in leads V4 to …

EXPERIMENTAL STUDY OF THE DYNAMICS OF CENTRIFUGAL CASTING MACHINES FOR PRODUCTION OF MILL ROLLS

Directory of Open Access Journals (Sweden)

P. G. Anofriev

2017-06-01

Full Text Available Purpose. The main purpose of experimental studies is to establish the adequacy of the developed mathematical models of machine fluctuations and the actual parameters of machine vibration. Almost all casting machines for the production of mill rolls have a unique design and performances. The additional aim of this work is to compare the vibration level of the casting machine with the requirements of the current vibration standards for new technological machines. Frequency analysis of the oscillations allows establishing defects in workmanship, errors of rotating parts installation and their influence on the dynamics of the machine. Methodology. Measurement of vibration parameters was performed on the moving parts of roller bearings of the machine. To measure the amplitudes of accelerations in three mutually perpendicular directions piezoelectric sensors with magnetic mount were used. Electrical signals from the sensors were recorded on magnetic tape. Further analysis of the oscillations was carried out and visualized using specialized frequency analyzer. The frequency analyzer implements the algorithm of fast Fourier transformation and/or integration of sensor input signal. After the first integration the data for plotting the vibration velocity spectrogram were obtained and as a result of the second integration there are the data of vibration displacements spectrogram of the machine supports. Findings. The results of experimental studies of centrifugal casting machine vibrations for the production of two-layer rolls were presented. There were obtained and analyzed the spectrograms of accelerations, velocities and displacements of moving parts of the upper and lower roller supports. The work of the machine is associated with the calculated values passing of critical frequencies and the short-term development of resonance oscillations of the rotor and roller bearings. Originality. For the first time the author obtained the frequency spectra of

Coordinate measurement machines as an alignment tool

International Nuclear Information System (INIS)

Wand, B.T.

1991-03-01

In February of 1990 the Stanford Linear Accelerator Center (SLAC) purchased a LEITZ PM 12-10-6 CMM (Coordinate measurement machine). The machine is shared by the Quality Control Team and the Alignment Team. One of the alignment tasks in positioning beamline components in a particle accelerator is to define the component's magnetic centerline relative to external fiducials. This procedure, called fiducialization, is critical to the overall positioning tolerance of a magnet. It involves the definition of the magnetic center line with respect to the mechanical centerline and the transfer of the mechanical centerline to the external fiducials. To perform the latter a magnet coordinate system has to be established. This means defining an origin and the three rotation angles of the magnet. The datum definition can be done by either optical tooling techniques or with a CMM. As optical tooling measurements are very time consuming, not automated and are prone to errors, it is desirable to use the CMM fiducialization method instead. The establishment of a magnet coordinate system based on the mechanical center and the transfer to external fiducials will be discussed and presented with 2 examples from the Stanford Linear Collider (SLC). 7 figs

Machining with abrasives

CERN Document Server

Jackson, Mark J

2011-01-01

Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

The Knife Machine. Module 15.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

Florida Progress Corporation 1991 annual report

International Nuclear Information System (INIS)

Anon.

1992-01-01

Florida Progress Corporation is a utility holding company with assets of 5 billion dollars. Its principal subsidiary is the Florida Power Corporation; others are the Electric Fuels Corporation, the Mid-Continent Life Assurance Company, the Talquin Corporation, the Progress Credit Corporation and Advanced Separation Technologies Incorporated. The annual report describes achievements during the year. To meet growing energy demand Florida Power is building new peaking and base-load generating units, purchasing power from neighbouring utilities and cogenerators, and building more bulk power transmission line capacity in the state. Emphasis has been placed on meeting load growth by demand-site management. Attention is given to balancing energy needs with concerns for the environment, and there is an award-winning recycling program. The Electric Fuels Corporation major area of business is coal mining and transportation services. Advanced Separation Technologies has sold several of its patented ion separation machines. The report includes consolidated financial statements for the year ended 31 December 1991

Restrictions of process machine retooling at machine-building enterprises

Directory of Open Access Journals (Sweden)

Kuznetsova Elena

2017-01-01

Full Text Available The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of up-to-date equipment, and drop in its use efficiency. The article investigates and classifies the main restrictions of the manufacturing equipment renewal process, such as regulatory and legislative, financial, organizational, competency-based. The economic consequences of the revealed restrictions influence on the machine-building enterprises activity are shown.

Mechanical design of machine components

CERN Document Server

Ugural, Ansel C

2015-01-01

Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

Static Measurements on HTS Coils of Fully Superconducting AC Electric Machines for Aircraft Electric Propulsion System

Science.gov (United States)

Choi, Benjamin B.; Hunker, Keith R.; Hartwig, Jason; Brown, Gerald V.

2017-01-01

The NASA Glenn Research Center (GRC) has been developing the high efficiency and high-power density superconducting (SC) electric machines in full support of electrified aircraft propulsion (EAP) systems for a future electric aircraft. A SC coil test rig has been designed and built to perform static and AC measurements on BSCCO, (RE)BCO, and YBCO high temperature superconducting (HTS) wire and coils at liquid nitrogen (LN2) temperature. In this paper, DC measurements on five SC coil configurations of various geometry in zero external magnetic field are measured to develop good measurement technique and to determine the critical current (Ic) and the sharpness (n value) of the super-to-normal transition. Also, standard procedures for coil design, fabrication, coil mounting, micro-volt measurement, cryogenic testing, current control, and data acquisition technique were established. Experimentally measured critical currents are compared with theoretical predicted values based on an electric-field criterion (Ec). Data here are essential to quantify the SC electric machine operation limits where the SC begins to exhibit non-zero resistance. All test data will be utilized to assess the feasibility of using HTS coils for the fully superconducting AC electric machine development for an aircraft electric propulsion system.

Mankind, machines and people

Energy Technology Data Exchange (ETDEWEB)

Hugli, A

1984-01-01

The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.

1000–ton testing machine for cyclic fatigue tests of materials at liquid nitrogen temperatures

Energy Technology Data Exchange (ETDEWEB)

Khitruk, A. A.; Klimchenko, Yu. A.; Kovalchuk, O. A.; Marushin, E. L.; Mednikov, A. A.; Nasluzov, S. N.; Privalova, E. K.; Rodin, I. Yu.; Stepanov, D. B.; Sukhanova, M. V. [The D.V. Efremov Scientific Research Institute of Electrophysical Apparatus (NIIEFA), 3 Doroga na Metallostroy, Metallostroy, Saint Petersburg 196641 (Russian Federation)

2014-01-29

One of the main tasks of superconductive magnets R and D is to determine the mechanical and fatigue properties of structural materials and the critical design elements in the cryogenic temperature range. This paper describes a new facility built based on the industrial 1000-ton (10 MN) testing machine Schenk PC10.0S. Special equipment was developed to provide the mechanical and cyclic tensile fatigue tests of large-scale samples at the liquid nitrogen temperature and in a given load range. The main feature of the developed testing machine is the cryostat, in which the device converting a standard compression force of the testing machine to the tensile force affected at the test object is placed. The control system provides the remote control of the test and obtaining, processing and presentation of test data. As an example of the testing machine operation the test program and test results of the cyclic tensile fatigue tests of fullscale helium inlet sample of the PF1 coil ITER are presented.

1000–ton testing machine for cyclic fatigue tests of materials at liquid nitrogen temperatures

International Nuclear Information System (INIS)

Khitruk, A. A.; Klimchenko, Yu. A.; Kovalchuk, O. A.; Marushin, E. L.; Mednikov, A. A.; Nasluzov, S. N.; Privalova, E. K.; Rodin, I. Yu.; Stepanov, D. B.; Sukhanova, M. V.

2014-01-01

One of the main tasks of superconductive magnets R and D is to determine the mechanical and fatigue properties of structural materials and the critical design elements in the cryogenic temperature range. This paper describes a new facility built based on the industrial 1000-ton (10 MN) testing machine Schenk PC10.0S. Special equipment was developed to provide the mechanical and cyclic tensile fatigue tests of large-scale samples at the liquid nitrogen temperature and in a given load range. The main feature of the developed testing machine is the cryostat, in which the device converting a standard compression force of the testing machine to the tensile force affected at the test object is placed. The control system provides the remote control of the test and obtaining, processing and presentation of test data. As an example of the testing machine operation the test program and test results of the cyclic tensile fatigue tests of fullscale helium inlet sample of the PF1 coil ITER are presented

A Concrete Framework for Environment Machines

DEFF Research Database (Denmark)

Biernacka, Malgorzata; Danvy, Olivier

2007-01-01

calculus with explicit substitutions), we extend it minimally so that it can also express one-step reduction strategies, and we methodically derive a series of environment machines from the specification of two one-step reduction strategies for the lambda-calculus: normal order and applicative order....... The derivation extends Danvy and Nielsen’s refocusing-based construction of abstract machines with two new steps: one for coalescing two successive transitions into one, and the other for unfolding a closure into a term and an environment in the resulting abstract machine. The resulting environment machines...... include both the Krivine machine and the original version of Krivine’s machine, Felleisen et al.’s CEK machine, and Leroy’s Zinc abstract machine....

Findings From the National Machine Guarding Program-A Small Business Intervention: Machine Safety.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Xi, Min; Brosseau, Lisa M; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2016-09-01

The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P increase in LOTO program scores (P < 0.0001). Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees.

Progress In Transverse Feedbacks and Related Diagnostics for Hadron Machines

CERN Document Server

Hofle, W

2013-01-01

Today Hadron Accelerators with high intensity and high brightness beams increasingly rely on transverse feedback systems for the control of instabilities and the preservation of the transverse emittance. With particular emphasis, but not limited to, the CERN Hadron Accelerator Chain, the progress made in recent years, and the performances achieved are reviewed. Hadron colliders such as the LHC represent a particular challenge as they ask for low noise electronic systems in these feedbacks for acceptable emittance growth. Achievements of the LHC transverse feedback system used for damping injection oscillations and to provide stability throughout the cycle are summarized. This includes its use for abort gap and injection cleaning as well as transverse blow-up for diagnostics purposes. Beyond systems already in operation, advances in technology and modern digital signal processing with increasingly higher digitization rates have made systems conceivable to cure intra-bunch motion. With its capabilities to both ...

A Simulation Model for Machine Efficiency Improvement Using Reliability Centered Maintenance: Case Study of Semiconductor Factory

Directory of Open Access Journals (Sweden)

Srisawat Supsomboon

2014-01-01

Full Text Available The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA, calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.

A Design for Life: A Consideration of the Learning Legacy of P.H. Pearse's "The Murder Machine"

Science.gov (United States)

Cronin, James G. R.

2016-01-01

In the centenary of the death of Patrick Henry Pearse--one of the leaders of Ireland's 1916 Rebellion--it is interesting to reflect on the relevance of his writing for contemporary approaches to lifelong and lifewide learning. Pearse's essay "The Murder Machine" was forged within the tradition of progressive education movements in the…

Machining of uranium and uranium alloys

International Nuclear Information System (INIS)

Morris, T.O.

1981-01-01

Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures

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

Science.gov (United States)

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.

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

OpenAIRE

Ming Cheng; Le Sun; Giuseppe Buja; Lihua Song

2015-01-01

The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs). Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator perm...

Advice taking from humans and machines: an fMRI and effective connectivity study

Directory of Open Access Journals (Sweden)

Kimberly Goodyear

2016-11-01

Full Text Available With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate. We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction and interoception (posterior insula. We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines.

The QCD Critical Point and Related Observables

Energy Technology Data Exchange (ETDEWEB)

Nahrgang, Marlene

2016-12-15

The search for the critical point of QCD in heavy-ion collision experiments has sparked enormous interest with the completion of phase I of the RHIC beam energy scan. Here, I review the basics of the thermodynamics of the QCD phase transition and its implications for experimental multiplicity fluctuations in heavy-ion collisions. Several sources of noncritical fluctuations impact the observables and need to be understood in addition to the critical phenomena. Recent progress has been made in dynamical modeling of critical fluctuations, which ultimately is indispensable to understand potential signals of the QCD critical point in heavy-ion collision.

Recent progress in material technology on RE-Ba-Cu-O bulk superconductors

International Nuclear Information System (INIS)

Teshima, Hidekazu; Morita, Mitsuru

2011-01-01

The current status of large-grained RE-Ba-Cu-O (RE: Y or rare earth elements) bulk superconductors with excellent superconducting properties is described. Gd-Ba-Cu-O bulk superconductors can trap a very high magnetic field even if they are melt-processed in air. Although the electromagnetic force caused by the trapped field is larger for a larger sample and may break the sample, a large sample of Gd-Ba-Cu-O 46 mm in diameter has the potential of trapped magnetic fields greater than 10 T at around 40 K. In addition, single-grained bulk superconductors as large as 150 mm can be obtained using the RE compositional gradient method. Dy-Ba-Cu-O is an ideal material for current leads because it has low thermal conductivity and high critical current density at 77 K in high magnetic fields. Eu-Ba-Cu-O has low magnetic permeability, and is therefore suitable for bulk NMR applications. Progress in machining technology has made possible various bulk superconductors with complicated shapes such as coils, leading to small and strong electromagnets by stacking several coil-shaped bulk superconductors together. (author)

Modal analysis of spindle of grinder machine based on ANSYS

OpenAIRE

HE Chaocong; LIU Peipei; YAN Chunfei; WANG Muhuan; LIN Jun

2015-01-01

The object of research is to a certain type grinding wheel spindle for which a 3D model of the spindle is established by SolidWorks software and ANSYS software is imported for model analysis.Natural frequency,vibration type and critical speed of the spindle model are obtained and the resulting data are scientifically analyzed.The results show that the spindle structure is reasonable,the machining accuracy can be ensured and the position where the most severe deformation and the main shaft fat...

The Necessity of Machine Learning and Epistemology in the Development of Categorization Theories: A Case Study in Prototype-Exemplar Debate

Science.gov (United States)

Gagliardi, Francesco

In the present paper we discuss some aspects of the development of categorization theories concerning cognitive psychology and machine learning. We consider the thirty-year debate between prototype-theory and exemplar-theory in the studies of cognitive psychology regarding the categorization processes. We propose this debate is ill-posed, because it neglects some theoretical and empirical results of machine learning about the bias-variance theorem and the existence of some instance-based classifiers which can embed models subsuming both prototype and exemplar theories. Moreover this debate lies on a epistemological error of pursuing a, so called, experimentum crucis. Then we present how an interdisciplinary approach, based on synthetic method for cognitive modelling, can be useful to progress both the fields of cognitive psychology and machine learning.

How To Save the World: Through Critical Thinking.

Science.gov (United States)

Hanford, George H.

Education is the best hope for peace and progress in the world, and because education is best given and received when infused with critical thinking, critical thinking can save the world. Some of the most serious problems facing humankind are overpopulation and famine. The problems of ethnicity, colonialism, and religion further complicate matters…

Findings from the National Machine Guarding Program–A Small Business Intervention: Machine Safety

Science.gov (United States)

Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 – 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of OSHA citations and may result in serious traumatic injury. Methods Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits and a twelve-month follow-up evaluation. Results The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10-percentage point increase in business-level machine scores (p< 0.0001) and a 33-percentage point increase in LOTO program scores (p <0.0001). Conclusions Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:26716850

CERN, World's largest particle physics lab, selects Progress SonicMQ

CERN Document Server

2007-01-01

"Progress Software Corporation (NADAQ: PRGS), a global supplier of application insfrastructure software used to develop, deploy, integrate and manage business applications, today announced that CERN the world's largest physis laboratory and particle accelerator, has chosen Progress® SonicMQ® for mission-critical message delivery." (1 page)

Machine Tool Software

Science.gov (United States)

1988-01-01

A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

Machine Ethics: Creating an Ethical Intelligent Agent

OpenAIRE

Anderson, Michael; Anderson, Susan Leigh

2007-01-01

The newly emerging field of machine ethics (Anderson and Anderson 2006) is concerned with adding an ethical dimension to machines. Unlike computer ethics -- which has traditionally focused on ethical issues surrounding humans' use of machines -- machine ethics is concerned with ensuring that the behavior of machines toward human users, and perhaps other machines as well, is ethically acceptable. In this article we discuss the importance of machine ethics, the need for machines that represent ...

Nanocomposites for Machining Tools

Directory of Open Access Journals (Sweden)

Daria Sidorenko

2017-10-01

Full Text Available 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.

Machine learning with R

CERN Document Server

Lantz, Brett

2013-01-01

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

Restrictions of process machine retooling at machine-building enterprises

OpenAIRE

Kuznetsova Elena; Tipner Ludmila; Ershov Alexey

2017-01-01

The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of...

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

Science.gov (United States)

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.

Pattern recognition & machine learning

CERN Document Server

Anzai, Y

1992-01-01

This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?

Science.gov (United States)

Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W

2018-03-01

The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.

Use of Machine-Learning Approaches to Predict Clinical Deterioration in Critically Ill Patients: A Systematic Review

Directory of Open Access Journals (Sweden)

Tadashi Kamio

2017-06-01

Full Text Available Introduction: Early identification of patients with unexpected clinical deterioration is a matter of serious concern. Previous studies have shown that early intervention on a patient whose health is deteriorating improves the patient outcome, and machine-learning-based approaches to predict clinical deterioration may contribute to precision improvement. To date, however, no systematic review in this area is available. Methods: We completed a search on PubMed on January 22, 2017 as well as a review of the articles identified by study authors involved in this area of research following the preferred reporting items for systematic reviews and meta-analyses (PRISMA guidelines for systematic reviews. Results: Twelve articles were selected for the current study from 273 articles initially obtained from the PubMed searches. Eleven of the 12 studies were retrospective studies, and no randomized controlled trials were performed. Although the artificial neural network techniques were the most frequently used and provided high precision and accuracy, we failed to identify articles that showed improvement in the patient outcome. Limitations were reported related to generalizability, complexity of models, and technical knowledge. Conclusions: This review shows that machine-learning approaches can improve prediction of clinical deterioration compared with traditional methods. However, these techniques will require further external validation before widespread clinical acceptance can be achieved.

The Insulation for Machines Having a High Lifespan Expectancy, Design, Tests and Acceptance Criteria Issues

Directory of Open Access Journals (Sweden)

Olivier Barré

2017-02-01

Full Text Available The windings insulation of electrical machines will remain a topic that is updated frequently. The criteria severity requested by the electrical machine applications increases continuously. Manufacturers and designers are always confronted with new requirements or new criteria with enhanced performances. The most problematic requirements that will be investigated here are the extremely long lifespan coupled to critical operating conditions (overload, supply grid instabilities, and critical operating environments. Increasing lifespan does not have a considerable benefit because the purchasing price of usual machines has to be compared to the purchasing price and maintenance price of long lifespan machines. A machine having a 40-year lifespan will cost more than twice the usual price of a 20-year lifetime machine. Systems which need a long lifetime are systems which are crucial for a country, and those for which outage costs are exorbitant. Nuclear power stations are such systems. It is certain that the used technologies have evolved since the first nuclear power plant, but they cannot evolve as quickly as in other sectors of activities. No-one wants to use an immature technology in such power plants. Even if the electrical machines have exceeded 100 years of age, their improvements are linked to a patient and continuous work. Nowadays, the windings insulation systems have a well-established structure, especially high voltage windings. Unfortunately, a high life span is not only linked to this result. Several manufacturers’ improvements induced by many years of experiment have led to the writing of standards that help the customers and the manufacturers to regularly enhance the insulation specifications or qualifications. Hence, in this publication, the authors will give a step by step exhaustive review of one insulation layout and will take time to give a detailed report on the standards that are linked to insulation systems. No standard can

Applying Fuzzy Possibilistic Methods on Critical Objects

DEFF Research Database (Denmark)

Yazdani, Hossein; Ortiz-Arroyo, Daniel; Choros, Kazimierz

2016-01-01

Providing a flexible environment to process data objects is a desirable goal of machine learning algorithms. In fuzzy and possibilistic methods, the relevance of data objects is evaluated and a membership degree is assigned. However, some critical objects objects have the potential ability to affect...... the performance of the clustering algorithms if they remain in a specific cluster or they are moved into another. In this paper we analyze and compare how critical objects affect the behaviour of fuzzy possibilistic methods in several data sets. The comparison is based on the accuracy and ability of learning...... methods to provide a proper searching space for data objects. The membership functions used by each method when dealing with critical objects is also evaluated. Our results show that relaxing the conditions of participation for data objects in as many partitions as they can, is beneficial....

Parallel-Machine Scheduling with Time-Dependent and Machine Availability Constraints

Directory of Open Access Journals (Sweden)

Cuixia Miao

2015-01-01

Full Text Available We consider the parallel-machine scheduling problem in which the machines have availability constraints and the processing time of each job is simple linear increasing function of its starting times. For the makespan minimization problem, which is NP-hard in the strong sense, we discuss the Longest Deteriorating Rate algorithm and List Scheduling algorithm; we also provide a lower bound of any optimal schedule. For the total completion time minimization problem, we analyze the strong NP-hardness, and we present a dynamic programming algorithm and a fully polynomial time approximation scheme for the two-machine problem. Furthermore, we extended the dynamic programming algorithm to the total weighted completion time minimization problem.

试论机修钳工与机械修理一体化%On the Integration of Machine Repairing Bench Worker and Machine Repairing

Institute of Scientific and Technical Information of China (English)

吴壮

2015-01-01

With the continuous development and progress of machine repairing in China, the demand of society for high level mechanical machine repairing bench workers has increased year by year. The machine tool repairing needs a lot of theory as the support foundation, and it also needs the sufficient curriculum practice to master the technology. All of these need the machine repairing bench workers fully combine the theory and practice in the personnel training activities. The personnel training method of combining machine repairing bench workers and machine repairing can effectively promote the theoretical study of the workers further implement the reasonable grasp of practical skills. This method can help them utilize the theory of knowledge to the specific practice, and also help them further understanding and master the theoretical knowledge in actual practice.%随着我国机修事业的不断发展与进步，使得社会对于高素质水平机修钳工的需求也逐年增多。机床的修理工作不仅需要借助大量的理论来作为基础支撑，同时也需要进行充分的课程实践来实现技术的有效掌握，这就要求其在钳工的人才培养活动中，必须实现理论与实践的充分结合。机修钳工与机械修理一体化的人才培养方法，能够有效促使钳工在理论学习的同时，也进一步的实现实践技能的合理掌握，不仅能够帮助其将所学的理论知识充分的运用到具体的实践活动中，也能进一步帮助其在实际的实践活动中来对理论知识进行更加深入的理解与掌握。

The Hooey Machine.

Science.gov (United States)

Scarnati, James T.; Tice, Craig J.

1992-01-01

Describes how students can make and use Hooey Machines to learn how mechanical energy can be transferred from one object to another within a system. The Hooey Machine is made using a pencil, eight thumbtacks, one pushpin, tape, scissors, graph paper, and a plastic lid. (PR)

A Review of Current Machine Learning Methods Used for Cancer Recurrence Modeling and Prediction

Energy Technology Data Exchange (ETDEWEB)

Hemphill, Geralyn M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-27

Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type has become a necessity in cancer research. A major challenge in cancer management is the classification of patients into appropriate risk groups for better treatment and follow-up. Such risk assessment is critically important in order to optimize the patient’s health and the use of medical resources, as well as to avoid cancer recurrence. This paper focuses on the application of machine learning methods for predicting the likelihood of a recurrence of cancer. It is not meant to be an extensive review of the literature on the subject of machine learning techniques for cancer recurrence modeling. Other recent papers have performed such a review, and I will rely heavily on the results and outcomes from these papers. The electronic databases that were used for this review include PubMed, Google, and Google Scholar. Query terms used include “cancer recurrence modeling”, “cancer recurrence and machine learning”, “cancer recurrence modeling and machine learning”, and “machine learning for cancer recurrence and prediction”. The most recent and most applicable papers to the topic of this review have been included in the references. It also includes a list of modeling and classification methods to predict cancer recurrence.

First operational experience with the LHC machine protection system when operating with beam energies beyond the 100MJ range

CERN Document Server

Assmann, R; Ferro-Luzzi, M; Goddard, B; Lamont, M; Schmidt, R; Siemko, A; Uythoven, J; Wenninger, J; Zerlauth, M

2012-01-01

The Large Hadron Collider (LHC) at CERN has made remarkable progress during 2011, surpassing its ambitious goal for the year in terms of luminosity delivered to the LHC experiments. This achievement was made possible by a progressive increase of beam intensities by more than 5 orders of magnitude during the first months of operation, reaching stored beam energies beyond the 100MJ range at the end of the year, less than a factor of 4 from the nominal design value. The correct functioning of the machine protection systems is vital during the different operational phases, for initial operation and even more when approaching nominal beam parameters where already a small fraction of the stored energy is sufficient to damage accelerator equipment or experiments in case of uncontrolled beam loss. Safe operation of the machine in presence of such high intensity proton beams is guaranteed by the interplay of many different systems: beam dumping system, beam interlocks, beam instrumentation, equipment monitoring, colli...

Machine Vision Handbook

CERN Document Server

2012-01-01

The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook  equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in insp...

Effect of the Machined Surfaces of AISI 4337 Steel to Cutting Conditions on Dry Machining Lathe

Science.gov (United States)

Rahim, Robbi; Napid, Suhardi; Hasibuan, Abdurrozzaq; Rahmah Sibuea, Siti; Yusmartato, Y.

2018-04-01

The objective of the research is to obtain a cutting condition which has a good chance of realizing dry machining concept on AISI 4337 steel material by studying surface roughness, microstructure and hardness of machining surface. The data generated from the experiment were then processed and analyzed using the standard Taguchi method L9 (34) orthogonal array. Testing of dry and wet machining used surface test and micro hardness test for each of 27 test specimens. The machining results of the experiments showed that average surface roughness (Raavg) was obtained at optimum cutting conditions when VB 0.1 μm, 0.3 μm and 0.6 μm respectively 1.467 μm, 2.133 μm and 2,800 μm fo r dry machining while which was carried out by wet machining the results obtained were 1,833 μm, 2,667 μm and 3,000 μm. It can be concluded that dry machining provides better surface quality of machinery results than wet machining. Therefore, dry machining is a good choice that may be realized in the manufacturing and automotive industries.

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

Science.gov (United States)

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.

Soft Material-Enabled, Flexible Hybrid Electronics for Medicine, Healthcare, and Human-Machine Interfaces

Science.gov (United States)

Herbert, Robert; Kim, Jong-Hoon; Kim, Yun Soung; Lee, Hye Moon

2018-01-01

Flexible hybrid electronics (FHE), designed in wearable and implantable configurations, have enormous applications in advanced healthcare, rapid disease diagnostics, and persistent human-machine interfaces. Soft, contoured geometries and time-dynamic deformation of the targeted tissues require high flexibility and stretchability of the integrated bioelectronics. Recent progress in developing and engineering soft materials has provided a unique opportunity to design various types of mechanically compliant and deformable systems. Here, we summarize the required properties of soft materials and their characteristics for configuring sensing and substrate components in wearable and implantable devices and systems. Details of functionality and sensitivity of the recently developed FHE are discussed with the application areas in medicine, healthcare, and machine interactions. This review concludes with a discussion on limitations of current materials, key requirements for next generation materials, and new application areas. PMID:29364861

Soft Material-Enabled, Flexible Hybrid Electronics for Medicine, Healthcare, and Human-Machine Interfaces

Directory of Open Access Journals (Sweden)

Robert Herbert

2018-01-01

Full Text Available Flexible hybrid electronics (FHE, designed in wearable and implantable configurations, have enormous applications in advanced healthcare, rapid disease diagnostics, and persistent human-machine interfaces. Soft, contoured geometries and time-dynamic deformation of the targeted tissues require high flexibility and stretchability of the integrated bioelectronics. Recent progress in developing and engineering soft materials has provided a unique opportunity to design various types of mechanically compliant and deformable systems. Here, we summarize the required properties of soft materials and their characteristics for configuring sensing and substrate components in wearable and implantable devices and systems. Details of functionality and sensitivity of the recently developed FHE are discussed with the application areas in medicine, healthcare, and machine interactions. This review concludes with a discussion on limitations of current materials, key requirements for next generation materials, and new application areas.

INFLUENCE OF MACHINING TECHNOLOGIES ON VALUES OF RESIDUAL STRESSES OF OXIDE CUTTING CERAMICS

Directory of Open Access Journals (Sweden)

Jakub Němeček

2017-07-01

Full Text Available Currently, the intensive development of engineering ceramic and effort to replace sintered carbides as cutting materials are in progress. With the development of the sintering technology it is now possible to produce compact ceramic cutting samples with very good mechanical properties. The advantage of these materials is their easy accessibility and low purchase price. In this work, the influence of the finishing machine technology on the values of surface residual stresses of cutting ceramic samples Al2O3+TiC were studying. The samples were supplied by Moscow State University of Technology STANKIN. Measurements made in the X-ray diffraction laboratory at the Department of solid state engineering were performed for both the phases. The influence of the parameters of machining to residual stresses was studied and the resulting values were compared with each other.

One approach to determining the optimal coefficient of slenderness scraping and tool materials when processing on a lathe for known machine

Directory of Open Access Journals (Sweden)

Pejović Branko B.

2014-01-01

Full Text Available Starting from the expression for the thrust in the field of full utilization cross section scrapings and tool life, an expression is derived for the maximum required thrust of universal machine. Then, using a working diagram the analysis of the main features of the simultaneous utilization of machines was performed and determined the optimal area of its utilization for given optimal diameter of treatment. Based on this, the well-known machine using its structural details and the corresponding function workability, derived relations to determine the optimal coefficient slenderness of scrapings suitable for practical use. In this case we think that is known critical material for work piece. Considering the critical and authoritative material of the work piece, based on the expression for the cutting speed was determined by the characteristic constant workability as the basis for establishing optimum tool material which is adequate for optimum regime. Both obtained relation can be considered as general model that can be applied directly to solving setting problems. Also, given the possibilities of practical application of the presented relations, especially in the case of other typical kinds of treatment. Finally, the model is verified on a one calculation example from practice for a Specific machine tool, where certain important characteristics of the optimal treatment are defined.

Machining a glass rod with a lathe-type electro-chemical discharge machine

International Nuclear Information System (INIS)

Furutani, Katsushi; Maeda, Hideaki

2008-01-01

This paper deals with the performance of electro-chemical discharge machining (ECDM) of a revolving glass rod. ECDM has been studied for machining insulating materials such as glass and ceramics. In conventional ECDM, an insulating workpiece is dipped in an electrolyte as a working fluid and a tool electrode is pressed on the surface with a small load. In the experiments, a workpiece was revolved to provide fresh working fluid into a gap between the tool electrode and the workpiece. A soda lime grass rod was machined with a thin tungsten rod in NaCl solution. The applied voltage was changed up to 40 V. The rotation speed was set to 0, 0.3, 3 and 30 min −1 . Discharge was observed over an applied voltage of 30 V. The width and depth of the machined grooves and the surface roughness of their bottom were increased with increase of the applied voltage. Although the depth of machining at 3 min −1 was the same as that at 30 min −1 , the width and roughness at 30 min −1 were smaller than those at 3 min −1 . Moreover, because the thickness of vaporization around the tool electrode was decreased with increase of the rotation speed, the width of the machined groove became smaller

Position error compensation via a variable reluctance sensor applied to a Hybrid Vehicle Electric machine.

Science.gov (United States)

Bucak, Ihsan Ömür

2010-01-01

In the automotive industry, electromagnetic variable reluctance (VR) sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV) system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion.

Study of the machining of uranium carbide rods obtained by continuous casting under electronic bombardment

International Nuclear Information System (INIS)

Rousset, P.; Accary, A.

1965-01-01

The authors consider the various methods of machining uranium mono-carbide and compare them critically in the case of their application to uranium carbide obtained by fusion under an electronic bombardment and continuous casting. This study leads them to propose two mechanical machining methods: cylindrical rectification and center-less rectification, preceded by a preliminary roughing out of a cylinder, the latter appearing more suitable. A study of the machining yields as a function of the diameter of the rough bars and of the diameter of the finished rods has shown that an optimum value of the rough bar diameter exists for each value of the finished rod diameter. It is found that the yield increases as the diameter itself increases, this yield rising from 45 per cent to around 70 per cent as the diameter of the rough bars increases from 25-26 mm to 37-38 mm. (authors) [fr

Position Error Compensation via a Variable Reluctance Sensor Applied to a Hybrid Vehicle Electric Machine

Directory of Open Access Journals (Sweden)

İhsan Ömür Bucak

2010-03-01

Full Text Available In the automotive industry, electromagnetic variable reluctance (VR sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion.

An HTS machine laboratory prototype

DEFF Research Database (Denmark)

Mijatovic, Nenad; Jensen, Bogi Bech; Træholt, Chresten

2012-01-01

This paper describes Superwind HTS machine laboratory setup which is a small scale HTS machine designed and build as a part of the efforts to identify and tackle some of the challenges the HTS machine design may face. One of the challenges of HTS machines is a Torque Transfer Element (TTE) which...... conduction compared to a shaft. The HTS machine was successfully cooled to 77K and tests have been performed. The IV curves of the HTS field winding employing 6 HTS coils indicate that two of the coils had been damaged. The maximal value of the torque during experiments of 78Nm was recorded. Loaded with 33...

Machine learning Z2 quantum spin liquids with quasiparticle statistics

Science.gov (United States)

Zhang, Yi; Melko, Roger G.; Kim, Eun-Ah

2017-12-01

After decades of progress and effort, obtaining a phase diagram for a strongly correlated topological system still remains a challenge. Although in principle one could turn to Wilson loops and long-range entanglement, evaluating these nonlocal observables at many points in phase space can be prohibitively costly. With growing excitement over topological quantum computation comes the need for an efficient approach for obtaining topological phase diagrams. Here we turn to machine learning using quantum loop topography (QLT), a notion we have recently introduced. Specifically, we propose a construction of QLT that is sensitive to quasiparticle statistics. We then use mutual statistics between the spinons and visons to detect a Z2 quantum spin liquid in a multiparameter phase space. We successfully obtain the quantum phase boundary between the topological and trivial phases using a simple feed-forward neural network. Furthermore, we demonstrate advantages of our approach for the evaluation of phase diagrams relating to speed and storage. Such statistics-based machine learning of topological phases opens new efficient routes to studying topological phase diagrams in strongly correlated systems.

Recent development work on PIM: a Blumlein driven IVA machine

International Nuclear Information System (INIS)

Phillips, Martin J.; Sinclair, Mark A.; Williamson, Mark C.; Clough, Stephen G.; Thomas, Kenneth J.; Smith, Ian Douglas; Bailey, Vernon Leslie; Johnson, David Lee; Corcoran, Patrick Allen; Kishi, Hiroshi J.; Maenchen, John Eric

2003-01-01

An IVA (inductive voltage adder) research programme at AWE began with the construction of a small scale IVA test bed named LINX and progressed to building PIM (Prototype IVA Module). The work on PIM is geared towards furnishing AWE with a range of machines operating at 1 to 4 MV that may eventually supersede, with an upgrade in performance, existing machines operating in that voltage range. PIM has a water dielectric Blumlein of 10 ohms charged by a Marx generator. This has been used to drive either one or two 1.5 MV inductive cavities and fitting a third cavity may be attempted in the future. The latest two cavity configuration is shown which requires a split oil coax to connect the two cavities in parallel. It also has a laser triggering system for initiating the Blumlein and the prepulse reduction system fitted to the output of the Blumlein. A short MITL (magnetically insulated transmission line) connects the cavities, via a vacuum pumping section, to a chamber containing an e-beam diode test load.

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

Science.gov (United States)

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

2017-12-01

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

Probability distribution of machining center failures

International Nuclear Information System (INIS)

Jia Yazhou; Wang Molin; Jia Zhixin

1995-01-01

Through field tracing research for 24 Chinese cutter-changeable CNC machine tools (machining centers) over a period of one year, a database of operation and maintenance for machining centers was built, the failure data was fitted to the Weibull distribution and the exponential distribution, the effectiveness was tested, and the failure distribution pattern of machining centers was found. Finally, the reliability characterizations for machining centers are proposed

Student Modeling and Machine Learning

OpenAIRE

Sison , Raymund; Shimura , Masamichi

1998-01-01

After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

The Newest Machine Material

International Nuclear Information System (INIS)

Seo, Yeong Seop; Choe, Byeong Do; Bang, Meong Sung

2005-08-01

This book gives descriptions of machine material with classification of machine material and selection of machine material, structure and connection of material, coagulation of metal and crystal structure, equilibrium diagram, properties of metal material, elasticity and plasticity, biopsy of metal, material test and nondestructive test. It also explains steel material such as heat treatment of steel, cast iron and cast steel, nonferrous metal materials, non metallic materials, and new materials.

Introduction to machine learning

OpenAIRE

Baştanlar, Yalın; Özuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning app...

Support vector machines applications

CERN Document Server

Guo, Guodong

2014-01-01

Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.

Machinability of advanced materials

CERN Document Server

Davim, J Paulo

2014-01-01

Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

Ergonomic requirements for the operation of machines and technical equipment

Directory of Open Access Journals (Sweden)

Górny Adam

2017-01-01

Full Text Available In order to operate machinery and equipment safely, it is critical for the solutions in place to conform to design-related and operating requirements. Design-related requirements are primarily the responsibility of machine designers/developers and manufacturers. Operating requirements should be satisfied by employers, who are responsible for ensuring safe working conditions for their employees. Under applicable laws, machinery and equipment should be designed, produced and then operated without placing excessive loads on workers and in keeping with machine functionality and intended use. One should also ensure that machinery and equipment can be maintained and adjusted without exposing their operators to hazards. Ergonomic criteria are an integral part of such requirements. They ensure that human users and operators of technical equipment are enabled to function properly. Design-related requirements are viewed as a priority safety consideration. While they facilitate the use of technical tools, the actual safety of employees ultimately depends on the satisfaction of specific requirements during operation.

Consequences attributed to kidney transplantation: critical incident technique

OpenAIRE

Santos,Bianca Pozza dos; Schwartz,Eda; Beuter,Margrid; Muniz,Rosani Manfrin; Echevarría-Guanilo,Maria Elena; Viegas,Aline da Costa

2015-01-01

This study aimed to describe the consequences experienced in the life of a person with kidney transplantation. This is a descriptive and qualitative approach, using the Critical Incident Technique, in which the interview content was analyzed, in an attempt to isolate the consequences of the kidney transplantation, showing positive and/or negative references. When confronted with what kidney transplantation provided to people's life, the independence from the hemodialysis machine, the existenc...

Nuclear reactor machine refuelling system

International Nuclear Information System (INIS)

Cashen, W.S.; Erwin, D.

1977-01-01

Part of an on-line fuelling machine for a CANDU pressure-tube reactor is described. The present invention provides a refuelling machine wherein the fuelling components, including the fuel carrier and the closure adapter, are positively positioned and retained within the machine magazine or positively secured to the machine charge tube head, and cannot be accidentally disengaged as in former practice. The positive positioning devices include an arcuate keeper plate. Simplified hooked fingers are used. (NDH)

Machine Translation Effect on Communication

DEFF Research Database (Denmark)

Jensen, Mika Yasuoka; Bjørn, Pernille

2011-01-01

Intercultural collaboration facilitated by machine translation has gradually spread in various settings. Still, little is known as for the practice of machine-translation mediated communication. This paper investigates how machine translation affects intercultural communication in practice. Based...... on communication in which multilingual communication system is applied, we identify four communication types and its’ influences on stakeholders’ communication process, especially focusing on establishment and maintenance of common ground. Different from our expectation that quality of machine translation results...

Machining of Complex Sculptured Surfaces

CERN Document Server

2012-01-01

The machining of complex sculptured surfaces is a global technological topic in modern manufacturing with relevance in both industrialized and emerging in countries particularly within the moulds and dies sector whose applications include highly technological industries such as the automotive and aircraft industry. Machining of Complex Sculptured Surfaces considers new approaches to the manufacture of moulds and dies within these industries. The traditional technology employed in the manufacture of moulds and dies combined conventional milling and electro-discharge machining (EDM) but this has been replaced with  high-speed milling (HSM) which has been applied in roughing, semi-finishing and finishing of moulds and dies with great success. Machining of Complex Sculptured Surfaces provides recent information on machining of complex sculptured surfaces including modern CAM systems and process planning for three and five axis machining as well as explanations of the advantages of HSM over traditional methods ra...

Formal modeling of virtual machines

Science.gov (United States)

Cremers, A. B.; Hibbard, T. N.

1978-01-01

Systematic software design can be based on the development of a 'hierarchy of virtual machines', each representing a 'level of abstraction' of the design process. The reported investigation presents the concept of 'data space' as a formal model for virtual machines. The presented model of a data space combines the notions of data type and mathematical machine to express the close interaction between data and control structures which takes place in a virtual machine. One of the main objectives of the investigation is to show that control-independent data type implementation is only of limited usefulness as an isolated tool of program development, and that the representation of data is generally dictated by the control context of a virtual machine. As a second objective, a better understanding is to be developed of virtual machine state structures than was heretofore provided by the view of the state space as a Cartesian product.

Design Control Systems of Human Machine Interface in the NTVS-2894 Seat Grinder Machine to Increase the Productivity

Science.gov (United States)

Ardi, S.; Ardyansyah, D.

2018-02-01

In the Manufacturing of automotive spare parts, increased sales of vehicles is resulted in increased demand for production of engine valve of the customer. To meet customer demand, we carry out improvement and overhaul of the NTVS-2894 seat grinder machine on a machining line. NTVS-2894 seat grinder machine has been decreased machine productivity, the amount of trouble, and the amount of downtime. To overcome these problems on overhaul the NTVS-2984 seat grinder machine include mechanical and programs, is to do the design and manufacture of HMI (Human Machine Interface) GP-4501T program. Because of the time prior to the overhaul, NTVS-2894 seat grinder machine does not have a backup HMI (Human Machine Interface) program. The goal of the design and manufacture in this program is to improve the achievement of production, and allows an operator to operate beside it easier to troubleshoot the NTVS-2894 seat grinder machine thereby reducing downtime on the NTVS-2894 seat grinder machine. The results after the design are HMI program successfully made it back, machine productivity increased by 34.8%, the amount of trouble, and downtime decreased 40% decrease from 3,160 minutes to 1,700 minutes. The implication of our design, it could facilitate the operator in operating machine and the technician easer to maintain and do the troubleshooting the machine problems.

Permutation parity machines for neural synchronization

International Nuclear Information System (INIS)

Reyes, O M; Kopitzke, I; Zimmermann, K-H

2009-01-01

Synchronization of neural networks has been studied in recent years as an alternative to cryptographic applications such as the realization of symmetric key exchange protocols. This paper presents a first view of the so-called permutation parity machine, an artificial neural network proposed as a binary variant of the tree parity machine. The dynamics of the synchronization process by mutual learning between permutation parity machines is analytically studied and the results are compared with those of tree parity machines. It will turn out that for neural synchronization, permutation parity machines form a viable alternative to tree parity machines

Manipulator for plasma-assisted machining of components made of materials with low machinability

International Nuclear Information System (INIS)

Lyaoshchukov, M.M.; Agadzhanyan, R.A.

1984-01-01

The All-Union Scientific-Research and Technological Institute of Pump Engineering developed, and the ''Uralgidromash'' Production Association has adopted, a manipulator with remote control for the plasma-assisted machining (PAM) of components made of materials with low machinability. The manipulator is distinguished by its universal design and can be used for machining both external and internal surfaces of the bodies of revolution and also end faces and various curvilinear surfaces

29 CFR 1910.218 - Forging machines.

Science.gov (United States)

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Forging machines. 1910.218 Section 1910.218 Labor... OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.218 Forging machines. (a... other identifier, for the forging machine which was inspected. (ii) Scheduling and recording the...

The achievements of the Z-machine

International Nuclear Information System (INIS)

Larousserie, D.

2008-01-01

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Vector control of induction machines

CERN Document Server

Robyns, Benoit

2012-01-01

After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, ""Vector Control of Induction Machines"" introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies. The use of causal ordering graphs allows systematization of the design stage, as well as standardization of the structure of control devices. ""Vector Control of Induction Machines"" suggests a unique approach aimed at reducing parameter sensitivity for

A Bayesian least-squares support vector machine method for predicting the remaining useful life of a microwave component

Directory of Open Access Journals (Sweden)

Fuqiang Sun

2017-01-01

Full Text Available Rapid and accurate lifetime prediction of critical components in a system is important to maintaining the system’s reliable operation. To this end, many lifetime prediction methods have been developed to handle various failure-related data collected in different situations. Among these methods, machine learning and Bayesian updating are the most popular ones. In this article, a Bayesian least-squares support vector machine method that combines least-squares support vector machine with Bayesian inference is developed for predicting the remaining useful life of a microwave component. A degradation model describing the change in the component’s power gain over time is developed, and the point and interval remaining useful life estimates are obtained considering a predefined failure threshold. In our case study, the radial basis function neural network approach is also implemented for comparison purposes. The results indicate that the Bayesian least-squares support vector machine method is more precise and stable in predicting the remaining useful life of this type of components.

The Chainstitch Machine. Module 18.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the chainstitch machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the chainstitch machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and…

Machine Shop Fundamentals: Part I.

Science.gov (United States)

Kelly, Michael G.; And Others

These instructional materials were developed and designed for secondary and adult limited English proficient students enrolled in machine tool technology courses. Part 1 includes 24 lessons covering introduction, safety and shop rules, basic machine tools, basic machine operations, measurement, basic blueprint reading, layout, and bench tools.…

Machining dynamics fundamentals, applications and practices

CERN Document Server

Cheng, Kai

2008-01-01

Machining dynamics are vital to the performance of machine tools and machining processes in manufacturing. This book discusses the state-of-the-art applications, practices and research in machining dynamics. It presents basic theory, analysis and control methodology. It is useful for manufacturing engineers, supervisors, engineers and designers.

Condom vending machines stir controversy.

Science.gov (United States)

1999-12-01

This article reports on the public debate on whether condoms should be made publicly available on the streets, in neighborhoods, and in schools, which could trigger discussions about sex in China. Condom vending machines have been installed in China since August 1999, and most regard the installations as a symbol of China's openness and progress, as well as an improvement in livelihood. However, some have objected to the public display and sale of condoms. Some teachers see it as damaging the reputation of the schools. Others suggest that they represent greater tolerance for premarital sex among youths, and a professor of sexual ethics stated that, while breaking the sex taboo is evidence of progress, condoms are a special type of commodity which should not be made available anywhere. In addition to the public debate concerning condoms, the banning of commercials featuring a condom-shaped cartoon character overcoming AIDS and sexually transmitted diseases touched off a debate between reproductive health advocates and government regulators. Reports indicate that the commercial was banned because it contravened the Advertisement Law, which provides that no sex product advertisement be aired or printed in the media. However, Zhang Konglai contended that condoms are not sex products but merely a means for preventing pregnancy and diseases and should be promoted actively. Moreover, Qui Renzong described the government's ban as a mistake and called on them to revise the law.

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

Science.gov (United States)

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

Electrical machining method of insulating ceramics

International Nuclear Information System (INIS)

Fukuzawa, Y.; Mohri, N.; Tani, T.

1999-01-01

This paper describes a new electrical discharge machining method for insulating ceramics using an assisting electrode with either a sinking electrical discharge machine or a wire electrical discharge machine. In this method, the metal sheet or mesh is attached to the ceramic surface as an assisting material for the discharge generation around the insulator surface. When the machining condition changes from the attached material to the workpiece, a cracked carbon layer is formed on the workpiece surface. As this layer has an electrical conductivity, electrical discharge occurs in working oil between the tool electrode and the surface of the workpiece. The carbon is formed from the working oil during this electrical discharge. Even after the material is machined, an electrical discharge occurs in the gap region between the tool electrode and the ceramic because an electrically conductive layer is generated continuously. Insulating ceramics can be machined by the electrical discharge machining method using the above mentioned surface modification phenomenon. In this paper the authors show a machined example demonstrating that the proposed method is available for machining a complex shape on insulating ceramics. Copyright (1999) AD-TECH - International Foundation for the Advancement of Technology Ltd

Overview of research in progress at the Center of Excellence

Science.gov (United States)

Wandell, Brian A.

1993-01-01

The Center of Excellence (COE) was created nine years ago to facilitate active collaboration between the scientists at Ames Research Center and the Stanford Psychology Department. Significant interchange of ideas and personnel continues between Stanford and participating groups at NASA-Ames; the COE serves its function well. This progress report is organized into sections divided by project. Each section contains a list of investigators, a background statement, progress report, and a proposal for work during the coming year. The projects are: Algorithms for development and calibration of visual systems, Visually optimized image compression, Evaluation of advanced piloting displays, Spectral representations of color, Perception of motion in man and machine, Automation and decision making, and Motion information used for navigation and control.

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning

Science.gov (United States)

Sutphin, George L.; Mahoney, J. Matthew; Sheppard, Keith; Walton, David O.; Korstanje, Ron

2016-01-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species—humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/. PMID:27812085