Design of Tools for Press-countersinking or Dimpling 0.040-inch-thick-24S-T Sheet

NASA Technical Reports Server (NTRS)

Templin, R L; Fogwell, J W

1942-01-01

A set of dimpling tools was designed for 0.040-inch 24S-T sheet and flush-type rivets 1/8 inch in diameter with 100 degree countersunk heads. The dimples produced under different conditions of pressure, sheet thickness, and drill diameter are presented as cross-sectional photographs magnified 20 times. The most satisfactory values for the dimpling tools were found to be: maximum punch diameter, 0.231 inch; maximum die diameter, 0.223 inch; maximum mandrel diameter, 0.128 inch; dimple angle, 100 degree; punch springback angle, 1 1/2 degree; and die springback angle, 2 degree.

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2011 CFR

2011-07-01

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

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

NASA Astrophysics Data System (ADS)

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.

Defect Detectability Improvement for Conventional Friction Stir Welds

NASA Technical Reports Server (NTRS)

Hill, Chris

2013-01-01

This research was conducted to evaluate the effects of defect detectability via phased array ultrasound technology in conventional friction stir welds by comparing conventionally prepped post weld surfaces to a machined surface finish. A machined surface is hypothesized to improve defect detectability and increase material strength.

The study on force, surface integrity, tool life and chip on laser assisted machining of inconel 718 using Nd:YAG laser source.

PubMed

Venkatesan, K

2017-07-01

Inconel 718, a high-temperature alloy, is a promising material for high-performance aerospace gas turbine engines components. However, the machining of the alloy is difficult owing to immense shear strength, rapid work hardening rate during turning, and less thermal conductivity. Hence, like ceramics and composites, the machining of this alloy is considered as difficult-to-turn materials. Laser assisted turning method has become a promising solution in recent years to lessen cutting stress when materials that are considered difficult-to-turn, such as Inconel 718 is employed. This study investigated the influence of input variables of laser assisted machining on the machinability aspect of the Inconel 718. The comparison of machining characteristics has been carried out to analyze the process benefits with the variation of laser machining variables. The laser assisted machining variables are cutting speeds of 60-150 m/min, feed rates of 0.05-0.125 mm/rev with a laser power between 1200 W and 1300 W. The various output characteristics such as force, roughness, tool life and geometrical characteristic of chip are investigated and compared with conventional machining without application of laser power. From experimental results, at a laser power of 1200 W, laser assisted turning outperforms conventional machining by 2.10 times lessening in cutting force, 46% reduction in surface roughness as well as 66% improvement in tool life when compared that of conventional machining. Compared to conventional machining, with the application of laser, the cutting speed of carbide tool has increased to a cutting condition of 150 m/min, 0.125 mm/rev. Microstructural analysis shows that no damage of the subsurface of the workpiece.

The semantics of Chemical Markup Language (CML): dictionaries and conventions.

PubMed

Murray-Rust, Peter; Townsend, Joe A; Adams, Sam E; Phadungsukanan, Weerapong; Thomas, Jens

2011-10-14

The semantic architecture of CML consists of conventions, dictionaries and units. The conventions conform to a top-level specification and each convention can constrain compliant documents through machine-processing (validation). Dictionaries conform to a dictionary specification which also imposes machine validation on the dictionaries. Each dictionary can also be used to validate data in a CML document, and provide human-readable descriptions. An additional set of conventions and dictionaries are used to support scientific units. All conventions, dictionaries and dictionary elements are identifiable and addressable through unique URIs.

The semantics of Chemical Markup Language (CML): dictionaries and conventions

PubMed Central

2011-01-01

The semantic architecture of CML consists of conventions, dictionaries and units. The conventions conform to a top-level specification and each convention can constrain compliant documents through machine-processing (validation). Dictionaries conform to a dictionary specification which also imposes machine validation on the dictionaries. Each dictionary can also be used to validate data in a CML document, and provide human-readable descriptions. An additional set of conventions and dictionaries are used to support scientific units. All conventions, dictionaries and dictionary elements are identifiable and addressable through unique URIs. PMID:21999509

CNC water-jet machining and cutting center

NASA Astrophysics Data System (ADS)

Bartlett, D. C.

1991-09-01

Computer Numerical Control (CNC) water-jet machining was investigated to determine the potential applications and cost-effectiveness that would result by establishing this capability in the engineering shops of Allied-Signal Inc., Kansas City Division (KCD). Both conductive and nonconductive samples were machined at KCD on conventional machining equipment (a three-axis conversational programmed mill and a wire electrical discharge machine) and on two current-technology water-jet machines at outside vendors. These samples were then inspected, photographed, and evaluated. The current-technology water-jet machines were not as accurate as the conventional equipment. The resolution of the water-jet equipment was only +/- 0.005 inch, as compared to +/- 0.0002 inch for the conventional equipment. The principal use for CNC water-jet machining would be as follows: Contouring to near finished shape those items made from 300 and 400 series stainless steels, titanium, Inconel, aluminum, glass, or any material whose fabrication tolerance is less than the machine resolution of +/- 0.005 inch; and contouring to finished shape those items made from Kevlar, rubber, fiberglass, foam, aluminum, or any material whose fabrication specifications allow the use of a machine with +/- 0.005 inch tolerance. Additional applications are possible because there is minimal force generated on the material being cut and because the water-jet cuts without generating dust.

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

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

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

2010-08-19

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

Hydraulic Fatigue-Testing Machine

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Investigations on high speed machining of EN-353 steel alloy under different machining environments

NASA Astrophysics Data System (ADS)

Venkata Vishnu, A.; Jamaleswara Kumar, P.

2018-03-01

The addition of Nano Particles into conventional cutting fluids enhances its cooling capabilities; in the present paper an attempt is made by adding nano sized particles into conventional cutting fluids. Taguchi Robust Design Methodology is employed in order to study the performance characteristics of different turning parameters i.e. cutting speed, feed rate, depth of cut and type of tool under different machining environments i.e. dry machining, machining with lubricant - SAE 40 and machining with mixture of nano sized particles of Boric acid and base fluid SAE 40. A series of turning operations were performed using L27 (3)13 orthogonal array, considering high cutting speeds and the other machining parameters to measure hardness. The results are compared among the different machining environments, and it is concluded that there is considerable improvement in the machining performance using lubricant SAE 40 and mixture of SAE 40 + boric acid compared with dry machining. The ANOVA suggests that the selected parameters and the interactions are significant and cutting speed has most significant effect on hardness.

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

NASA Astrophysics Data System (ADS)

Mehmood, Shahid; Shah, Masood; Pasha, Riffat Asim; Sultan, Amir

2017-10-01

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

Ship localization in Santa Barbara Channel using machine learning classifiers.

PubMed

Niu, Haiqiang; Ozanich, Emma; Gerstoft, Peter

2017-11-01

Machine learning classifiers are shown to outperform conventional matched field processing for a deep water (600 m depth) ocean acoustic-based ship range estimation problem in the Santa Barbara Channel Experiment when limited environmental information is known. Recordings of three different ships of opportunity on a vertical array were used as training and test data for the feed-forward neural network and support vector machine classifiers, demonstrating the feasibility of machine learning methods to locate unseen sources. The classifiers perform well up to 10 km range whereas the conventional matched field processing fails at about 4 km range without accurate environmental information.

Resistance characteristics of innovative eco-fitness equipment: a water buoyancy muscular machine.

PubMed

Chen, Wei-Han; Liu, Ya-Chen; Tai, Hsing-Hao; Liu, Chiang

2018-03-01

This paper propose innovative eco-fitness equipment-a water buoyancy muscular machine (WBM machine) in which resistance is generated by buoyancy and fluid resistance. The resistance characteristics during resistance adjustment and under isometric, concentric, eccentric and isokinetic conditions were investigated and compared to a conventional machine with metal weight plates. The results indicated that the isometric, concentric and eccentric resistances could be adjusted by varying the water volume; the maximum resistances under isometric, concentric and eccentric conditions were 163.8, 338.5 and 140.9 N, respectively. The isometric resistances at different positions remained constant in both machines; however the isometric resistance was lower for WBM machine when at a position corresponding to a 5% total displacement. The WBM machine has lower resistance under eccentric conditions and higher resistance under concentric conditions. Although the conventional machine has an identical trend, the variation was minor (within 4 N). In the WBM machine, the eccentric resistance was approximately 30-45% of the concentric resistance. Concentric resistances increased with an increase in velocity in both machines; however, the eccentric resistances decreased with an increase in velocity. In summary, the WBM machine, a piece of innovative eco-fitness equipment, has unique resistance characteristics and expansibility.

Machining of Fibre Reinforced Plastic Composite Materials.

PubMed

Caggiano, Alessandra

2018-03-18

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

Machining of Fibre Reinforced Plastic Composite Materials

PubMed Central

2018-01-01

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

30 CFR 70.220 - Status change reports.

Code of Federal Regulations, 2014 CFR

2014-07-01

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

Machine learning to predict the occurrence of bisphosphonate-related osteonecrosis of the jaw associated with dental extraction: A preliminary report.

PubMed

Kim, Dong Wook; Kim, Hwiyoung; Nam, Woong; Kim, Hyung Jun; Cha, In-Ho

2018-04-23

The aim of this study was to build and validate five types of machine learning models that can predict the occurrence of BRONJ associated with dental extraction in patients taking bisphosphonates for the management of osteoporosis. A retrospective review of the medical records was conducted to obtain cases and controls for the study. Total 125 patients consisting of 41 cases and 84 controls were selected for the study. Five machine learning prediction algorithms including multivariable logistic regression model, decision tree, support vector machine, artificial neural network, and random forest were implemented. The outputs of these models were compared with each other and also with conventional methods, such as serum CTX level. Area under the receiver operating characteristic (ROC) curve (AUC) was used to compare the results. The performance of machine learning models was significantly superior to conventional statistical methods and single predictors. The random forest model yielded the best performance (AUC = 0.973), followed by artificial neural network (AUC = 0.915), support vector machine (AUC = 0.882), logistic regression (AUC = 0.844), decision tree (AUC = 0.821), drug holiday alone (AUC = 0.810), and CTX level alone (AUC = 0.630). Machine learning methods showed superior performance in predicting BRONJ associated with dental extraction compared to conventional statistical methods using drug holiday and serum CTX level. Machine learning can thus be applied in a wide range of clinical studies. Copyright © 2017. Published by Elsevier Inc.

Development of Semi-Automatic Lathe by using Intelligent Soft Computing Technique

NASA Astrophysics Data System (ADS)

Sakthi, S.; Niresh, J.; Vignesh, K.; Anand Raj, G.

2018-03-01

This paper discusses the enhancement of conventional lathe machine to semi-automated lathe machine by implementing a soft computing method. In the present scenario, lathe machine plays a vital role in the engineering division of manufacturing industry. While the manual lathe machines are economical, the accuracy and efficiency are not up to the mark. On the other hand, CNC machine provide the desired accuracy and efficiency, but requires a huge capital. In order to over come this situation, a semi-automated approach towards the conventional lathe machine is developed by employing stepper motors to the horizontal and vertical drive, that can be controlled by Arduino UNO -microcontroller. Based on the input parameters of the lathe operation the arduino coding is been generated and transferred to the UNO board. Thus upgrading from manual to semi-automatic lathe machines can significantly increase the accuracy and efficiency while, at the same time, keeping a check on investment cost and consequently provide a much needed escalation to the manufacturing industry.

Non-conventional rule of making a periodically varying different-pole magnetic field in low-power alternating current electrical machines with using ring coils in multiphase armature winding

NASA Astrophysics Data System (ADS)

Plastun, A. T.; Tikhonova, O. V.; Malygin, I. V.

2018-02-01

The paper presents methods of making a periodically varying different-pole magnetic field in low-power electrical machines. Authors consider classical designs of electrical machines and machines with ring windings in armature, structural features and calculated parameters of magnetic circuit for these machines.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2012-01-01

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

Osteoporosis risk prediction using machine learning and conventional methods.

PubMed

Kim, Sung Kean; Yoo, Tae Keun; Oh, Ein; Kim, Deok Won

2013-01-01

A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women, and compared with the ability of a conventional clinical decision tool, osteoporosis self-assessment tool (OST). We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Surveys (KNHANES V-1). The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests (RF), artificial neural networks (ANN), and logistic regression (LR) based on various predictors associated with low bone density. The learning models were compared with OST. SVM had significantly better area under the curve (AUC) of the receiver operating characteristic (ROC) than ANN, LR, and OST. Validation on the test set showed that SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0%. We were the first to perform comparisons of the performance of osteoporosis prediction between the machine learning and conventional methods using population-based epidemiological data. The machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

Design of intelligent proximity detection zones to prevent striking and pinning fatalities around continuous mining machines.

PubMed

Bissert, P T; Carr, J L; DuCarme, J P; Smith, A K

2016-01-01

The continuous mining machine is a key piece of equipment used in underground coal mining operations. Over the past several decades these machines have been involved in a number of mine worker fatalities. Proximity detection systems have been developed to avert hazards associated with operating continuous mining machines. Incorporating intelligent design into proximity detection systems allows workers greater freedom to position themselves to see visual cues or avoid other hazards such as haulage equipment or unsupported roof or ribs. However, intelligent systems must be as safe as conventional proximity detection systems. An evaluation of the 39 fatal accidents for which the Mine Safety and Health Administration has published fatality investigation reports was conducted to determine whether the accident may have been prevented by conventional or intelligent proximity. Multiple zone configurations for the intelligent systems were studied to determine how system performance might be affected by the zone configuration. Researchers found that 32 of the 39 fatalities, or 82 percent, may have been prevented by both conventional and intelligent proximity systems. These results indicate that, by properly configuring the zones of an intelligent proximity detection system, equivalent protection to a conventional system is possible.

Operation of micro and molecular machines: a new concept with its origins in interface science.

PubMed

Ariga, Katsuhiko; Ishihara, Shinsuke; Izawa, Hironori; Xia, Hong; Hill, Jonathan P

2011-03-21

A landmark accomplishment of nanotechnology would be successful fabrication of ultrasmall machines that can work like tweezers, motors, or even computing devices. Now we must consider how operation of micro- and molecular machines might be implemented for a wide range of applications. If these machines function only under limited conditions and/or require specialized apparatus then they are useless for practical applications. Therefore, it is important to carefully consider the access of functionality of the molecular or nanoscale systems by conventional stimuli at the macroscopic level. In this perspective, we will outline the position of micro- and molecular machines in current science and technology. Most of these machines are operated by light irradiation, application of electrical or magnetic fields, chemical reactions, and thermal fluctuations, which cannot always be applied in remote machine operation. We also propose strategies for molecular machine operation using the most conventional of stimuli, that of macroscopic mechanical force, achieved through mechanical operation of molecular machines located at an air-water interface. The crucial roles of the characteristics of an interfacial environment, i.e. connection between macroscopic dimension and nanoscopic function, and contact of media with different dielectric natures, are also described.

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

A Review on High-Speed Machining of Titanium Alloys

NASA Astrophysics Data System (ADS)

Rahman, Mustafizur; Wang, Zhi-Gang; Wong, Yoke-San

Titanium alloys have been widely used in the aerospace, biomedical and automotive industries because of their good strength-to-weight ratio and superior corrosion resistance. However, it is very difficult to machine them due to their poor machinability. When machining titanium alloys with conventional tools, the tool wear rate progresses rapidly, and it is generally difficult to achieve a cutting speed of over 60m/min. Other types of tool materials, including ceramic, diamond, and cubic boron nitride (CBN), are highly reactive with titanium alloys at higher temperature. However, binder-less CBN (BCBN) tools, which do not have any binder, sintering agent or catalyst, have a remarkably longer tool life than conventional CBN inserts even at high cutting speeds. In order to get deeper understanding of high speed machining (HSM) of titanium alloys, the generation of mathematical models is essential. The models are also needed to predict the machining parameters for HSM. This paper aims to give an overview of recent developments in machining and HSM of titanium alloys, geometrical modeling of HSM, and cutting force models for HSM of titanium alloys.

Surface roughness analysis after laser assisted machining of hard to cut materials

NASA Astrophysics Data System (ADS)

Przestacki, D.; Jankowiak, M.

2014-03-01

Metal matrix composites and Si3N4 ceramics are very attractive materials for various industry applications due to extremely high hardness and abrasive wear resistance. However because of these features they are problematic for the conventional turning process. The machining on a classic lathe still requires special polycrystalline diamond (PCD) or cubic boron nitride (CBN) cutting inserts which are very expensive. In the paper an experimental surface roughness analysis of laser assisted machining (LAM) for two tapes of hard-to-cut materials was presented. In LAM, the surface of work piece is heated directly by a laser beam in order to facilitate, the decohesion of material. Surface analysis concentrates on the influence of laser assisted machining on the surface quality of the silicon nitride ceramic Si3N4 and metal matrix composite (MMC). The effect of the laser assisted machining was compared to the conventional machining. The machining parameters influence on surface roughness parameters was also investigated. The 3D surface topographies were measured using optical surface profiler. The analysis of power spectrum density (PSD) roughness profile were analyzed.

Bioactive calcium pyrophosphate glasses and glass-ceramics.

PubMed

Kasuga, Toshihiro

2005-01-01

Calcium phosphate glass-based materials in the pyrophosphate region are briefly reviewed. Calcium pyrophosphate glasses can be prepared by including a small amount of TiO(2) (

High speed turning of compacted graphite iron using controlled modulation

NASA Astrophysics Data System (ADS)

Stalbaum, Tyler Paul

Compacted graphite iron (CGI) is a material which emerged as a candidate material to replace cast iron (CI) in the automotive industry for engine block castings. Its thermal and mechanical properties allow the CGI-based engines to operate at higher cylinder pressures and temperatures than CI-based engines, allowing for lower fuel emissions and increased fuel economy. However, these same properties together with the thermomechanical wear mode in the CGI-CBN system result in poor machinability and inhibit CGI from seeing wide spread use in the automotive industry. In industry, machining of CGI is done only at low speeds, less than V = 200 m/min, to avoid encountering rapid wear of the cutting tools during cutting. Studies have suggested intermittent cutting operations such as milling suffer less severe tool wear than continuous cutting. Furthermore, evidence that a hard sulfide layer which forms over the cutting edge in machining CI at high speeds is absent during machining CGI is a major factor in the difference in machinability of these material systems. The present study addresses both of these issues by modification to the conventional machining process to allow intermittent continuous cutting. The application of controlled modulation superimposed onto the cutting process -- modulation-assisted machining (MAM) -- is shown to be quite effective in reducing the wear of cubic boron nitride (CBN) tools when machining CGI at high machining speeds (> 500 m/min). The tool life is at least 20 times greater than found in conventional machining of CGI. This significant reduction in wear is a consequence of reduction in the severity of the tool-work contact conditions with MAM. The propensity for thermochemical wear of CBN is thus reduced. It is found that higher cutting speed (> 700 m/min) leads to lower tool wear with MAM. The MAM configuration employing feed-direction modulation appears feasible for implementation at high speeds and offers a solution to this challenging class of industrial machining applications. This study's approach is by series of high speed turning tests of CGI with CBN tools, comparing conventional machining to MAM for similar parameters otherwise, by tool wear measurements and machinability observations.

Optical alignment of electrodes on electrical discharge machines

NASA Technical Reports Server (NTRS)

Boissevain, A. G.; Nelson, B. W.

1972-01-01

Shadowgraph system projects magnified image on screen so that alignment of small electrodes mounted on electrical discharge machines can be corrected and verified. Technique may be adapted to other machine tool equipment where physical contact cannot be made during inspection and access to tool limits conventional runout checking procedures.

Machinability of nickel based alloys using electrical discharge machining process

NASA Astrophysics Data System (ADS)

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.

Overview of nanofluid application through minimum quantity lubrication (MQL) in metal cutting process

NASA Astrophysics Data System (ADS)

Sharif, Safian; Sadiq, Ibrahim Ogu; Suhaimi, Mohd Azlan; Rahim, Shayfull Zamree Abd

2017-09-01

Pollution related activities in addition to handling cost of conventional cutting fluid application in metal cutting industry has generated a lot of concern over time. The desire for a green machining environment which will preserve the environment through reduction or elimination of machining related pollution, reduction in oil consumption and safety of the machine operators without compromising an efficient machining process led to search for alternatives to conventional cutting fluid. Amongst the alternatives of dry machining, cryogenic cooling, high pressure cooling, near dry or minimum quantity lubrication (MQL), MQL have shown remarkable performance in terms of cost, machining output, safety of environment and machine operators. However, the MQL under aggressive machining or very high speed machining pose certain restriction as the lubrication media cannot perform efficiently at elevated temperature. In compensating for the shortcomings of MQL technique, high thermal conductivity nanoparticles are introduced in cutting fluids for use in the MQL lubrication process. They have indicated enhanced performance of machining process and significant reduction of loads on the environment. The present work is aimed at evaluating the application and performance of nanofluid in metal cutting process through MQL lubrication technique highlighting their impacts and prospects as lubrication strategy in metal cutting process for sustainable green manufacturing. Enhanced performance of vegetable oil based nanofluids over mineral oil-based nanofluids have been reported and thus highlighted.

Needs of ergonomic design at control units in production industries.

PubMed

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

2012-01-01

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

The Invention Convention: Mind Meets Simple Machines.

ERIC Educational Resources Information Center

Hadi-Tabassum, Samina

1997-01-01

Describes an Earth Day celebration where students had to design an invention made of simple machines that could crush an empty aluminum can through 10 rapid mechanical movements using materials foraged from the students' homes. (JRH)

Dorsal slab fracture of the fourth carpal bone in a racing greyhound.

PubMed

Rutherford, Scott; Ness, Malcolm G

2012-11-01

To report the diagnosis and surgical management of a dorsal slab fracture of the fourth carpal bone in a racing greyhound. Clinical report. Three-year-old, male racing Greyhound. The fracture was not visible on orthogonal radiographs and the diagnosis was made by computed tomography. Open reduction and internal fixation with 2 countersunk 2.0-mm screws inserted in lag fashion was performed via a dorsal approach. Outcome was analyzed objectively by comparing preinjury and postsurgery racing performances. Internal fixation resulted in fracture healing and the dog returned to racing recording times similar to those before injury. Fractures of the fourth carpal bone may not be visible on standard orthogonal radiographic views and cross-sectional imaging may be required for more accurate identification. Surgical management was successful with the dog returning to preinjury levels of competition. © Copyright 2012 by The American College of Veterinary Surgeons.

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

NASA Astrophysics Data System (ADS)

Bachtiar, Ilham; Abdullah, Bualkar; Tahir, Dahlan

2018-03-01

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

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa

2012-01-01

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

Enhanced ultrasonically assisted turning of a β-titanium alloy.

PubMed

Maurotto, Agostino; Muhammad, Riaz; Roy, Anish; Silberschmidt, Vadim V

2013-09-01

Although titanium alloys have outstanding mechanical properties such as high hot hardness, a good strength-to-weight ratio and high corrosion resistance; their low thermal conductivity, high chemical affinity to tool materials severely impair their machinability. Ultrasonically assisted machining (UAM) is an advanced machining technique, which has been shown to improve machinability of a β-titanium alloy, namely, Ti-15-3-3-3, when compared to conventional turning processes. Copyright © 2013 Elsevier B.V. All rights reserved.

Pulsed Nd:YAG laser beam drilling: A review

NASA Astrophysics Data System (ADS)

Gautam, Girish Dutt; Pandey, Arun Kumar

2018-03-01

Laser beam drilling (LBD) is one of non contact type unconventional machining process that are employed in machining of stiff and high-strength materials, high strength temperature resistance materials such as; metal alloys, ceramics, composites and superalloys. Most of these materials are difficult-to-machine by using conventional machining methods. Also, the complex and precise holes may not be obtained by using the conventional machining processes which may be obtained by using unconventional machining processes. The laser beam drilling in one of the most important unconventional machining process that may be used for the machining of these materials with satisfactorily. In this paper, the attention is focused on the experimental and theoretical investigations on the pulsed Nd:YAG laser drilling of different categories of materials such as ferrous materials, non-ferrous materials, superalloys, composites and Ceramics. Moreover, the review has been emphasized by the use of pulsed Nd:YAG laser drilling of different materials in order to enhance productivity of this process without adverse effects on the drilled holes quality characteristics. Finally, the review is concluded with the possible scope in the area of pulsed Nd:YAG laser drilling. This review work may be very useful to the subsequent researchers in order to give an insight in the area of pulsed Nd:YAG laser drilling of different materials and research gaps available in this area.

High Energy Colliders

NASA Astrophysics Data System (ADS)

Palmer, R. B.; Gallardo, J. C.

INTRODUCTION PHYSICS CONSIDERATIONS GENERAL REQUIRED LUMINOSITY FOR LEPTON COLLIDERS THE EFFECTIVE PHYSICS ENERGIES OF HADRON COLLIDERS HADRON-HADRON MACHINES LUMINOSITY SIZE AND COST CIRCULAR e^{+}e^- MACHINES LUMINOSITY SIZE AND COST e^{+}e^- LINEAR COLLIDERS LUMINOSITY CONVENTIONAL RF SUPERCONDUCTING RF AT HIGHER ENERGIES γ - γ COLLIDERS μ ^{+} μ^- COLLIDERS ADVANTAGES AND DISADVANTAGES DESIGN STUDIES STATUS AND REQUIRED R AND D COMPARISION OF MACHINES CONCLUSIONS DISCUSSION

Effects of Process Parameters and Cryotreated Electrode on the Radial Overcut of Aisi 304 IN SiC Powder Mixed Edm

NASA Astrophysics Data System (ADS)

Bhaumik, Munmun; Maity, Kalipada

Powder mixed electro discharge machining (PMEDM) is further advancement of conventional electro discharge machining (EDM) where the powder particles are suspended in the dielectric medium to enhance the machining rate as well as surface finish. Cryogenic treatment is introduced in this process for improving the tool life and cutting tool properties. In the present investigation, the characterization of the cryotreated tempered electrode was performed. An attempt has been made to study the effect of cryotreated double tempered electrode on the radial overcut (ROC) when SiC powder is mixed in the kerosene dielectric during electro discharge machining of AISI 304. The process performance has been evaluated by means of ROC when peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameters and machining is performed by using tungsten carbide electrodes (untreated and double tempered electrodes). A regression analysis was performed to correlate the data between the response and the process parameters. Microstructural analysis was carried out on the machined surfaces. Least radial overcut was observed for conventional EDM as compared to powder mixed EDM. Cryotreated double tempered electrode significantly reduced the radial overcut than untreated electrode.

An Introduction to Database Structure and Database Machines.

ERIC Educational Resources Information Center

Detweiler, Karen

1984-01-01

Enumerates principal management objectives of database management systems (data independence, quality, security, multiuser access, central control) and criteria for comparison (response time, size, flexibility, other features). Conventional database management systems, relational databases, and database machines used for backend processing are…

Experimental Investigation Nano Particles Influence in NPMEDM to Machine Inconel 800 with Electrolyte Copper Electrode

NASA Astrophysics Data System (ADS)

Karunakaran, K.; Chandrasekaran, M.

2017-05-01

The recent technology of machining hard materials is Powder mix dielectric electrical Discharge Machining (PMEDM). This research investigates nano sized (about 5Nm) powders influence in machining Inconel 800 nickel based super alloy. This work is motivated for a practical need for a manufacturing industry, which processes various kinds of jobs of Inconel 800 material. The conventional EDM machining also considered for investigation for the measure of Nano powders performances. The aluminum, silicon and multi walled Carbon Nano tubes powders were considered in this investigation along with pulse on time, pulse of time and input current to analyze and optimize the responses of Material Removal Rate, Tool Wear Rate and surface roughness. The Taguchi general Full Factorial Design was used to design the experiments. The most advance equipments employed in conducting experiments and measuring equipments to improve the accuracy of the result. The MWCNT powder mix was out performs than other powders which reduce 22% to 50% of the tool wear rate, gives the surface roughness reduction from 29.62% to 41.64% and improved MRR 42.91% to 53.51% than conventional EDM.

Review on CNC-Rapid Prototyping

NASA Astrophysics Data System (ADS)

Z, M. Nafis O.; Y, Nafrizuan M.; A, Munira M.; J, Kartina

2012-09-01

This article reviewed developments of Computerized Numerical Control (CNC) technology in rapid prototyping process. Rapid prototyping (RP) can be classified into three major groups; subtractive, additive and virtual. CNC rapid prototyping is grouped under the subtractive category which involves material removal from the workpiece that is larger than the final part. Richard Wysk established the use of CNC machines for rapid prototyping using sets of 2½-D tool paths from various orientations about a rotary axis to machine parts without refixturing. Since then, there are few developments on this process mainly aimed to optimized the operation and increase the process capabilities to stand equal with common additive type of RP. These developments include the integration between machining and deposition process (hybrid RP), adoption of RP to the conventional machine and optimization of the CNC rapid prototyping process based on controlled parameters. The article ended by concluding that the CNC rapid prototyping research area has a vast space for improvement as in the conventional machining processes. Further developments and findings will enhance the usage of this method and minimize the limitation of current approach in building a prototype.

Practical aspects of the use of three-phase alternating current electric machines in electricity storage system

NASA Astrophysics Data System (ADS)

Ciucur, Violeta

2015-02-01

Of three-phase alternating current electric machines, it brings into question which of them is more advantageous to be used in electrical energy storage system by pumping water. The two major categories among which are given dispute are synchronous and the asynchronous machine. To consider the synchronous machine with permanent magnet configuration because it brings advantages compared with conventional synchronous machine, first by removing the necessary additional excitation winding. From the point of view of loss of the two types of machines, the optimal adjustment of the magnetic flux density is obtained to minimize the copper loss by hysteresis and eddy currents.

Micro- to Macroroughness of Additively Manufactured Titanium Implants in Terms of Coagulation and Contact Activation.

PubMed

Klingvall Ek, Rebecca; Hong, Jaan; Thor, Andreas; Bäckström, Mikael; Rännar, Lars-Erik

This study aimed to evaluate how as-built electron beam melting (EBM) surface properties affect the onset of blood coagulation. The properties of EBM-manufactured implant surfaces for placement have, until now, remained largely unexplored in literature. Implants with conventional designs and custom-made implants have been manufactured using EBM technology and later placed into the human body. Many of the conventional implants used today, such as dental implants, display modified surfaces to optimize bone ingrowth, whereas custom-made implants, by and large, have machined surfaces. However, titanium in itself demonstrates good material properties for the purpose of bone ingrowth. Specimens manufactured using EBM were selected according to their surface roughness and process parameters. EBM-produced specimens, conventional machined titanium surfaces, as well as PVC surfaces for control were evaluated using the slide chamber model. A significant increase in activation was found, in all factors evaluated, between the machined samples and EBM-manufactured samples. The results show that EBM-manufactured implants with as-built surfaces augment the thrombogenic properties. EBM that uses Ti6Al4V powder appears to be a good manufacturing solution for load-bearing implants with bone anchorage. The as-built surfaces can be used "as is" for direct bone contact, although any surface treatment available for conventional implants can be performed on EBM-manufactured implants with a conventional design.

Nozzles for Focusing Aerosol Particles

DTIC Science & Technology

2009-10-01

Fabrication of the nozzle with the desired shape was accomplished using EDM technology. First, a copper tungsten electrode was turned on a CNC lathe . The...small (0.9-mm diameter). The external portions of the nozzles were machined in a more conventional manner using computer numerical control ( CNC ... lathes and milling machines running programs written by computer aided machining (CAM) software. The close tolerance of concentricity of the two

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

PubMed

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

2011-05-01

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

Modelling of teeth of a gear transmission for modern manufacturing technologies

NASA Astrophysics Data System (ADS)

Monica, Z.; Banaś, W.; Ćwikla, G.; Topolska, S.

2017-08-01

The technological process of manufacturing of gear wheels is influenced by many factors. It is designated depending on the type of material from which the gear is to be produced, its heat treatment parameters, the required accuracy, the geometrical form and the modifications of the tooth. Therefor the parameters selection process is not easy and moreover it is unambiguous. Another important stage of the technological process is the selection of appropriate tools to properly machine teeth in the operations of both roughing and finishing. In the presented work the focus is put first of all on modern production methods of gears using technologically advanced instruments in comparison with conventional tools. Conventional processing tools such as gear hobbing cutters or Fellows gear-shaper cutters are used from the beginning of the machines for the production of gear wheels. With the development of technology and the creation of CNC machines designated for machining of gears wheel it was also developed the manufacturing technology as well as the design knowledge concerning the technological tools. Leading manufacturers of cutting tools extended the range of tools designated for machining of gears on the so-called hobbing cutters with inserted cemented carbide tips. The same have be introduced to Fellows gear-shaper cutters. The results of tests show that is advantaged to use hobbing cutters with inserted cemented carbide tips for milling gear wheels with a high number of teeth, where the time gains are very high, in relation to the use of conventional milling cutters.

Method for forming precision clockplate with pivot pins

DOEpatents

Wild, Ronald L [Albuquerque, NM

2010-06-01

Methods are disclosed for producing a precision clockplate with rotational bearing surfaces (e.g. pivot pins). The methods comprise providing an electrically conductive blank, conventionally machining oversize features comprising bearing surfaces into the blank, optionally machining of a relief on non-bearing surfaces, providing wire accesses adjacent to bearing surfaces, threading the wire of an electrical discharge machine through the accesses and finishing the bearing surfaces by wire electrical discharge machining. The methods have been shown to produce bearing surfaces of comparable dimension and tolerances as those produced by micro-machining methods such as LIGA, at reduced cost and complexity.

Support Vector Machines to improve physiologic hot flash measures: application to the ambulatory setting.

PubMed

Thurston, Rebecca C; Hernandez, Javier; Del Rio, Jose M; De La Torre, Fernando

2011-07-01

Most midlife women have hot flashes. The conventional criterion (≥2 μmho rise/30 s) for classifying hot flashes physiologically has shown poor performance. We improved this performance in the laboratory with Support Vector Machines (SVMs), a pattern classification method. We aimed to compare conventional to SVM methods to classify hot flashes in the ambulatory setting. Thirty-one women with hot flashes underwent 24 h of ambulatory sternal skin conductance monitoring. Hot flashes were quantified with conventional (≥2 μmho/30 s) and SVM methods. Conventional methods had low sensitivity (sensitivity=.57, specificity=.98, positive predictive value (PPV)=.91, negative predictive value (NPV)=.90, F1=.60), with performance lower with higher body mass index (BMI). SVMs improved this performance (sensitivity=.87, specificity=.97, PPV=.90, NPV=.96, F1=.88) and reduced BMI variation. SVMs can improve ambulatory physiologic hot flash measures. Copyright © 2010 Society for Psychophysiological Research.

An experimental investigation of pulsed laser-assisted machining of AISI 52100 steel

NASA Astrophysics Data System (ADS)

Panjehpour, Afshin; Soleymani Yazdi, Mohammad R.; Shoja-Razavi, Reza

2014-11-01

Grinding and hard turning are widely used for machining of hardened bearing steel parts. Laser-assisted machining (LAM) has emerged as an efficient alternative to grinding and hard turning for hardened steel parts. In most cases, continuous-wave lasers were used as a heat source to cause localized heating prior to material removal by a cutting tool. In this study, an experimental investigation of pulsed laser-assisted machining of AISI 52100 bearing steel was conducted. The effects of process parameters (i.e., laser mean power, pulse frequency, pulse energy, cutting speed and feed rate) on state variables (i.e., material removal temperature, specific cutting energy, surface roughness, microstructure, tool wear and chip formation) were investigated. At laser mean power of 425 W with frequency of 120 Hz and cutting speed of 70 m/min, the benefit of LAM was shown by 25% decrease in specific cutting energy and 18% improvement in surface roughness, as compared to those of the conventional machining. It was shown that at constant laser power, the increase of laser pulse energy causes the rapid increase in tool wear rate. Pulsed laser allowed efficient control of surface temperature and heat penetration in material removal region. Examination of the machined subsurface microstructure and microhardness profiles showed no change under LAM and conventional machining. Continuous chips with more uniform plastic deformation were produced in LAM.

Intense X-ray machine for penetrating radiography

NASA Astrophysics Data System (ADS)

Lucht, Roy A.; Eckhouse, Shimon

Penetrating radiography has been used for many years in the nuclear weapons research programs. Infrequently penetrating radiography has been used in conventional weapons research programs. For example the Los Alamos PHERMEX machine was used to view uranium rods penetrating steel for the GAU-8 program, and the Ector machine was used to see low density regions in forming metal jets. The armor/anti-armor program at Los Alamos has created a need for an intense flash X-ray machine that can be dedicated to conventional weapons research. The Balanced Technology Initiative, through DARPA, has funded the design and construction of such a machine at Los Alamos. It will be an 8- to 10-MeV diode machine capable of delivering a dose of 500 R at 1 m with a spot size of less than 5 mm. The machine used an 87.5-stage low inductance Marx generator that charges up a 7.4-(Omega), 32-ns water line. The water line is discharged through a self-breakdown oil switch into a 12.4-(Omega) water line that rings up the voltage into the high impendance X-ray diode. A long (233-cm) vacuum drift tube is used to separate the large diameter oil-insulated diode region from the X-ray source area that may be exposed to high overpressures by the explosive experiments. The electron beam is selffocused at the target area using a low pressure background gas.

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

NASA Astrophysics Data System (ADS)

Gohil, Vikas; Puri, YM

2018-04-01

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

Thermal-mechanical modeling of laser ablation hybrid machining

NASA Astrophysics Data System (ADS)

Matin, Mohammad Kaiser

2001-08-01

Hard, brittle and wear-resistant materials like ceramics pose a problem when being machined using conventional machining processes. Machining ceramics even with a diamond cutting tool is very difficult and costly. Near net-shape processes, like laser evaporation, produce micro-cracks that require extra finishing. Thus it is anticipated that ceramic machining will have to continue to be explored with new-sprung techniques before ceramic materials become commonplace. This numerical investigation results from the numerical simulations of the thermal and mechanical modeling of simultaneous material removal from hard-to-machine materials using both laser ablation and conventional tool cutting utilizing the finite element method. The model is formulated using a two dimensional, planar, computational domain. The process simulation acronymed, LAHM (Laser Ablation Hybrid Machining), uses laser energy for two purposes. The first purpose is to remove the material by ablation. The second purpose is to heat the unremoved material that lies below the ablated material in order to ``soften'' it. The softened material is then simultaneously removed by conventional machining processes. The complete solution determines the temperature distribution and stress contours within the material and tracks the moving boundary that occurs due to material ablation. The temperature distribution is used to determine the distance below the phase change surface where sufficient ``softening'' has occurred, so that a cutting tool may be used to remove additional material. The model incorporated for tracking the ablative surface does not assume an isothermal melt phase (e.g. Stefan problem) for laser ablation. Both surface absorption and volume absorption of laser energy as function of depth have been considered in the models. LAHM, from the thermal and mechanical point of view is a complex machining process involving large deformations at high strain rates, thermal effects of the laser, removal of materials and contact between workpiece and tool. The theoretical formulation associated with LAHM for solving the thermal-mechanical problem using the finite element method is presented. The thermal formulation is incorporated in the user defined subroutines called by ABAQUS/Standard. The mechanical portion is modeled using ABAQUS/Explicit's general capabilities of modeling interactions involving contact and separation. The results obtained from the FEA simulations showed that the cutting force decrease considerably in both LAEM Surface Absorption (LARM-SA) and LAHM volume absorption (LAHM-VA) models relative to LAM model. It was observed that the HAZ can be expanded or narrowed depending on the laser speed and power. The cutting force is minimal at the last extent of the HAZ. In both the models the laser ablates material thus reducing material stiffness as well as relaxing the thermal stress. The stress values obtained showed compressive yield stress just below the ablated surface and chip. The failure occurs by conventional cutting where tensile stress exceeds the tensile strength of the material at that temperature. In this hybrid machining process the advantages of both the individual machining processes were realized.

Laser assisted machining: a state of art review

NASA Astrophysics Data System (ADS)

Punugupati, Gurabvaiah; Kandi, Kishore Kumar; Bose, P. S. C.; Rao, C. S. P.

2016-09-01

Difficult-to-cut materials have increasing demand in aerospace and automobile industries due to their high yield stress, high strength to weight ratio, high toughness, high wear resistance, high creep, high corrosion resistivity, ability to retain high strength at high temperature, etc. The machinability of these advanced materials, using conventional methods of machining is typical due to the high temperature and pressure at the cutting zone and tool and properties such as low thermal conductivity, high cutting forces and cutting temperatures makes the materials difficult to machine. Laser assisted machining (LAM) is a new and innovative technique for machining the difficult-to-cut materials. This paper deals with a review on the advances in lasers, tools and the mechanism of machining using LAM and their effects.

Wax Reinforces Honeycomb During Machining

NASA Technical Reports Server (NTRS)

Towell, Timothy W.; Fahringer, David T.; Vasquez, Peter; Scheidegger, Alan P.

1995-01-01

Method of machining on conventional metal lathe devised for precise cutting of axisymmetric contours on honeycomb cores made of composite (matrix/fiber) materials. Wax filling reinforces honeycomb walls against bending and tearing while honeycomb being contoured on lathe. Innovative method of machining on lathe involves preparation in which honeycomb is placed in appropriate fixture and the fixture is then filled with molten water-soluble wax. Number of different commercial waxes have been tried.

Design and market considerations for axial flux superconducting electric machine design

NASA Astrophysics Data System (ADS)

Ainslie, M. D.; George, A.; Shaw, R.; Dawson, L.; Winfield, A.; Steketee, M.; Stockley, S.

2014-05-01

In this paper, the authors investigate a number of design and market considerations for an axial flux superconducting electric machine design that uses high temperature superconductors. The axial flux machine design is assumed to utilise high temperature superconductors in both wire (stator winding) and bulk (rotor field) forms, to operate over a temperature range of 65-77 K, and to have a power output in the range from 10s of kW up to 1 MW (typical for axial flux machines), with approximately 2-3 T as the peak trapped field in the bulk superconductors. The authors firstly investigate the applicability of this type of machine as a generator in small- and medium-sized wind turbines, including the current and forecasted market and pricing for conventional turbines. Next, a study is also carried out on the machine's applicability as an in-wheel hub motor for electric vehicles. Some recommendations for future applications are made based on the outcome of these two studies. Finally, the cost of YBCO-based superconducting (2G HTS) wire is analysed with respect to competing wire technologies and compared with current conventional material costs and current wire costs for both 1G and 2G HTS are still too great to be economically feasible for such superconducting devices.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Resistance Training using Low Cost Elastic Tubing is Equally Effective to Conventional Weight Machines in Middle-Aged to Older Healthy Adults: A Quasi-Randomized Controlled Clinical Trial.

PubMed

Lima, Fabiano F; Camillo, Carlos A; Gobbo, Luis A; Trevisan, Iara B; Nascimento, Wesley B B M; Silva, Bruna S A; Lima, Manoel C S; Ramos, Dionei; Ramos, Ercy M C

2018-03-01

The objectives of the study were to compare the effects of resistance training using either a low cost and portable elastic tubing or conventional weight machines on muscle force, functional exercise capacity, and health-related quality of life (HRQOL) in middle-aged to older healthy adults. In this clinical trial twenty-nine middle-aged to older healthy adults were randomly assigned to one of the three groups a priori defined: resistance training with elastic tubing (ETG; n = 10), conventional resistance training (weight machines) (CTG; n = 9) and control group (CG, n = 10). Both ETG and CTG followed a 12-week resistance training (3x/week - upper and lower limbs). Muscle force, functional exercise capacity and HRQOL were evaluated at baseline, 6 and 12 weeks. CG underwent the three evaluations with no formal intervention or activity counseling provided. ETG and CTG increased similarly and significantly muscle force (Δ16-44% in ETG and Δ25-46% in CTG, p < 0.05 for both), functional exercise capacity (ETG Δ4 ± 4% and CTG Δ6±8%; p < 0.05 for both). Improvement on "pain" domain of HRQOL could only be observed in the CTG (Δ21 ± 26% p = 0.037). CG showed no statistical improvement in any of the variables investigated. Resistance training using elastic tubing (a low cost and portable tool) and conventional resistance training using weight machines promoted similar positive effects on peripheral muscle force and functional exercise capacity in middle-aged to older healthy adults.

Diamond Machining of an Off-Axis Biconic Aspherical Mirror

NASA Technical Reports Server (NTRS)

Ohl, Raymond G.; Preuss, Werner; Sohn, Alex; MacKenty, John

2009-01-01

Two diamond-machining methods have been developed as part of an effort to design and fabricate an off-axis, biconic ellipsoidal, concave aluminum mirror for an infrared spectrometer at the Kitt Peak National Observatory. Beyond this initial application, the methods can be expected to enable satisfaction of requirements for future instrument mirrors having increasingly complex (including asymmetrical), precise shapes that, heretofore, could not readily be fabricated by diamond machining or, in some cases, could not be fabricated at all. In the initial application, the mirror is prescribed, in terms of Cartesian coordinates x and y, by aperture dimensions of 94 by 76 mm, placements of -2 mm off axis in x and 227 mm off axis in y, an x radius of curvature of 377 mm, a y radius of curvature of 407 mm, an x conic constant of 0.078, and a y conic constant of 0.127. The aspect ratio of the mirror blank is about 6. One common, "diamond machining" process uses single-point diamond turning (SPDT). However, it is impossible to generate the required off-axis, biconic ellipsoidal shape by conventional SPDT because (1) rotational symmetry is an essential element of conventional SPDT and (2) the present off-axis biconic mirror shape lacks rotational symmetry. Following conventional practice, it would be necessary to make this mirror from a glass blank by computer-controlled polishing, which costs more than diamond machining and yields a mirror that is more difficult to mount to a metal bench. One of the two present diamond machining methods involves the use of an SPDT machine equipped with a fast tool servo (FTS). The SPDT machine is programmed to follow the rotationally symmetric asphere that best fits the desired off-axis, biconic ellipsoidal surface. The FTS is actuated in synchronism with the rotation of the SPDT machine to generate the difference between the desired surface and the best-fit rotationally symmetric asphere. In order to minimize the required stroke of the FTS, the blanks were positioned at a large off-axis distance and angle, and the axis of the FTS was not parallel to the axis of the spindle of the SPDT machine. The spindle was rotated at a speed of 120 rpm, and the maximum FTS speed was 8.2 mm/s.

Selective hypertrophy of the quadriceps musculature after 14 weeks of isokinetic and conventional resistance training.

PubMed

Matta, Thiago Torres; Nascimento, Francisco Xavier; Trajano, Gabriel S; Simão, Roberto; Willardson, Jeffrey Michael; Oliveira, Liliam Fernandes

2017-03-01

One of the fundamental adaptations observed with resistance training (RT) is muscle hypertrophy. Conventional and isokinetic machines provide different forms of mechanical stress, and it is possible that these two training modes could promote differing degrees of hypertrophic adaptations. There is a lack of data comparing the selective hypertrophy of the quadriceps musculature after training with a conventional knee extension machine versus an isokinetic machine. The purpose of this study was to evaluate the selective hypertrophy of the quadriceps musculature and knee extension maximal isometric torque after 14 weeks of conventional versus isokinetic RT. Thirty-five men were assigned to three groups: control group and training groups (conventional and isokinetic) performed three sets of unilateral knee extensions per session with a progressive loading scheme twice a week. Prior to and following the intervention, maximal isometric knee extensor torque was measured using an isokinetic dynamometer, and muscle thickness (MT) of quadriceps femoris muscles was assessed via ultrasound. The results indicated non-uniform changes in MT between the muscles that comprise the quadriceps femoris group. For the conventional group, significantly greater increases in rectus femoris thickness were evident versus all other quadriceps muscles (14%). For the isokinetic group, increases in RF thickness (11%) were significantly greater in comparison with the vastus intermedius only. Although the muscle thickness did not increase for all the quadriceps femoris muscles, the relative rectus femoris adaptation suggested a selective hypertrophy favouring this portion. © 2015 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Design of Ultra-High-Power-Density Machine Optimized for Future Aircraft

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.

2004-01-01

The NASA Glenn Research Center's Structural Mechanics and Dynamics Branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more-electric" aircraft with specific power in the projected range of 50 hp/lb, whereas conventional electric machines generate usually 0.2 hp/lb. The use of such electric drives for propulsive fans or propellers depends on the successful development of ultra-high-power-density machines. One possible candidate for such ultra-high-power-density machines, a round-rotor synchronous machine with an engineering current density as high as 20,000 A/sq cm, was selected to investigate how much torque and power can be produced.

Machine learning for medical images analysis.

PubMed

Criminisi, A

2016-10-01

This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, K.; Ignasiak, B.; Pawlak, W.; Kulik, C.; Lebowitz, H.E.

1995-12-05

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other mineral particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal. 4 figs.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, Kazimierz; Ignasiak, Boleslaw; Pawlak, Wanda; Kulik, Conrad; Lebowitz, Howard E.

1995-01-01

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other minerals particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, K.; Ignasiak, B.; Pawlak, W.; Kulik, C.; Lebowitz, H.E.

1997-02-11

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other minerals particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal. 4 figs.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, Kazimierz; Ignasiak, Boleslaw; Pawlak, Wanda; Kulik, Conrad; Lebowitz, Howard E.

1997-01-01

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other minerals particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal.

Graphite fiber reinforced structure for supporting machine tools

DOEpatents

Knight, Jr., Charles E.; Kovach, Louis; Hurst, John S.

1978-01-01

Machine tools utilized in precision machine operations require tool support structures which exhibit minimal deflection, thermal expansion and vibration characteristics. The tool support structure of the present invention is a graphite fiber reinforced composite in which layers of the graphite fibers or yarn are disposed in a 0/90.degree. pattern and bonded together with an epoxy resin. The finished composite possesses a low coefficient of thermal expansion and a substantially greater elastic modulus, stiffness-to-weight ratio, and damping factor than a conventional steel tool support utilized in similar machining operations.

Robot based deposition of WC-Co HVOF coatings on HSS cutting tools as a substitution for solid cemented carbide cutting tools

NASA Astrophysics Data System (ADS)

Tillmann, W.; Schaak, C.; Biermann, D.; Aßmuth, R.; Goeke, S.

2017-03-01

Cemented carbide (hard metal) cutting tools are the first choice to machine hard materials or to conduct high performance cutting processes. Main advantages of cemented carbide cutting tools are their high wear resistance (hardness) and good high temperature strength. In contrast, cemented carbide cutting tools are characterized by a low toughness and generate higher production costs, especially due to limited resources. Usually, cemented carbide cutting tools are produced by means of powder metallurgical processes. Compared to conventional manufacturing routes, these processes are more expensive and only a limited number of geometries can be realized. Furthermore, post-processing and preparing the cutting edges in order to achieve high performance tools is often required. In the present paper, an alternative method to substitute solid cemented carbide cutting tools is presented. Cutting tools made of conventional high speed steels (HSS) were coated with thick WC-Co (88/12) layers by means of thermal spraying (HVOF). The challenge is to obtain a dense, homogenous, and near-net-shape coating on the flanks and the cutting edge. For this purpose, different coating strategies were realized using an industrial robot. The coating properties were subsequently investigated. After this initial step, the surfaces of the cutting tools were ground and selected cutting edges were prepared by means of wet abrasive jet machining to achieve a smooth and round micro shape. Machining tests were conducted with these coated, ground and prepared cutting tools. The occurring wear phenomena were analyzed and compared to conventional HSS cutting tools. Overall, the results of the experiments proved that the coating withstands mechanical stresses during machining. In the conducted experiments, the coated cutting tools showed less wear than conventional HSS cutting tools. With respect to the initial wear resistance, additional benefits can be obtained by preparing the cutting edge by means of wet abrasive jet machining.

Using ZWDOS to Communicate in Chinese on PC.

ERIC Educational Resources Information Center

Xie, Tianwei

1995-01-01

Describes the availability, installation, and use of the ZhonWen Disk Operating System (ZWDOS) to display, print, and transmit Chinese characters on conventional International Business Machines (IBM) personal computers and IBM-compatible machines. Also discussed is the use of ZWDOS to compose electronic mail messages, read newsgroups, and access…

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

EPA Science Inventory

Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

Microfiber Masses Recovered from Conventional Machine Washing of New or Aged Garments.

PubMed

Hartline, Niko L; Bruce, Nicholas J; Karba, Stephanie N; Ruff, Elizabeth O; Sonar, Shreya U; Holden, Patricia A

2016-11-01

Synthetic textiles can shed numerous microfibers during conventional washing, but evaluating environmental consequences as well as source-control strategies requires understanding mass releases. Polyester apparel accounts for a large proportion of the polyester market, and synthetic jackets represent the broadest range in apparel construction, allowing for potential changes in manufacturing as a mitigation measure to reduce microfiber release during laundering. Here, detergent-free washing experiments were conducted and replicated in both front- and top-load conventional home machines for five new and mechanically aged jackets or sweaters: four from one name-brand clothing manufacturer (three majority polyester fleece, and one nylon shell with nonwoven polyester insulation) and one off-brand (100% polyester fleece). Wash water was filtered to recover two size fractions (>333 μm and between 20 and 333 μm); filters were then imaged, and microfiber masses were calculated. Across all treatments, the recovered microfiber mass per garment ranged from approximately 0 to 2 g, or exceeding 0.3% of the unwashed garment mass. Microfiber masses from top-load machines were approximately 7 times those from front-load machines; garments mechanically aged via a 24 h continuous wash had increased mass release under the same wash protocol as new garments. When published wastewater treatment plant influent characterization and microfiber removal studies are considered, washing synthetic jackets or sweaters as per this study would account for most microfibers entering the environment.

Source localization in an ocean waveguide using supervised machine learning.

PubMed

Niu, Haiqiang; Reeves, Emma; Gerstoft, Peter

2017-09-01

Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data. The pressure received by a vertical linear array is preprocessed by constructing a normalized sample covariance matrix and used as the input for three machine learning methods: feed-forward neural networks (FNN), support vector machines (SVM), and random forests (RF). The range estimation problem is solved both as a classification problem and as a regression problem by these three machine learning algorithms. The results of range estimation for the Noise09 experiment are compared for FNN, SVM, RF, and conventional matched-field processing and demonstrate the potential of machine learning for underwater source localization.

Resistance Training using Low Cost Elastic Tubing is Equally Effective to Conventional Weight Machines in Middle-Aged to Older Healthy Adults: A Quasi-Randomized Controlled Clinical Trial

PubMed Central

Lima, Fabiano F.; Camillo, Carlos A.; Gobbo, Luis A.; Trevisan, Iara B.; Nascimento, Wesley B. B. M.; Silva, Bruna S. A.; Lima, Manoel C. S.; Ramos, Dionei; Ramos, Ercy M. C.

2018-01-01

The objectives of the study were to compare the effects of resistance training using either a low cost and portable elastic tubing or conventional weight machines on muscle force, functional exercise capacity, and health-related quality of life (HRQOL) in middle-aged to older healthy adults. In this clinical trial twenty-nine middle-aged to older healthy adults were randomly assigned to one of the three groups a priori defined: resistance training with elastic tubing (ETG; n = 10), conventional resistance training (weight machines) (CTG; n = 9) and control group (CG, n = 10). Both ETG and CTG followed a 12-week resistance training (3x/week - upper and lower limbs). Muscle force, functional exercise capacity and HRQOL were evaluated at baseline, 6 and 12 weeks. CG underwent the three evaluations with no formal intervention or activity counseling provided. ETG and CTG increased similarly and significantly muscle force (Δ16-44% in ETG and Δ25-46% in CTG, p < 0.05 for both), functional exercise capacity (ETG Δ4 ± 4% and CTG Δ6±8%; p < 0.05 for both). Improvement on “pain” domain of HRQOL could only be observed in the CTG (Δ21 ± 26% p = 0.037). CG showed no statistical improvement in any of the variables investigated. Resistance training using elastic tubing (a low cost and portable tool) and conventional resistance training using weight machines promoted similar positive effects on peripheral muscle force and functional exercise capacity in middle-aged to older healthy adults. Key points There is compeling evidence linking resistance training to health. Elastic resistance training improves the functionality of middle-aged to older healthy adults. Elastic resistance training was shown to be as effective as conventional resistence training in middle-aged to older healthy adults. PMID:29535589

Slide system for machine tools

DOEpatents

Douglass, S.S.; Green, W.L.

1980-06-12

The present invention relates to a machine tool which permits the machining of nonaxisymmetric surfaces on a workpiece while rotating the workpiece about a central axis of rotation. The machine tool comprises a conventional two-slide system (X-Y) with one of these slides being provided with a relatively short travel high-speed auxiliary slide which carries the material-removing tool. The auxiliary slide is synchronized with the spindle speed and the position of the other two slides and provides a high-speed reciprocating motion required for the displacement of the cutting tool for generating a nonaxisymmetric surface at a selected location on the workpiece.

Identifying product order with restricted Boltzmann machines

NASA Astrophysics Data System (ADS)

Rao, Wen-Jia; Li, Zhenyu; Zhu, Qiong; Luo, Mingxing; Wan, Xin

2018-03-01

Unsupervised machine learning via a restricted Boltzmann machine is a useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the two-dimensional Ashkin-Teller model, which features a partially ordered product phase. We train the neural network with spin configuration data generated by Monte Carlo simulations and show that distinct features of the product phase can be learned from nonergodic samples resulting from symmetry breaking. Careful analysis of the weight matrices inspires us to define a nontrivial machine-learning motivated quantity of the product form, which resembles the conventional product order parameter.

Slide system for machine tools

DOEpatents

Douglass, Spivey S.; Green, Walter L.

1982-01-01

The present invention relates to a machine tool which permits the machining of nonaxisymmetric surfaces on a workpiece while rotating the workpiece about a central axis of rotation. The machine tool comprises a conventional two-slide system (X-Y) with one of these slides being provided with a relatively short travel high-speed auxiliary slide which carries the material-removing tool. The auxiliary slide is synchronized with the spindle speed and the position of the other two slides and provides a high-speed reciprocating motion required for the displacement of the cutting tool for generating a nonaxisymmetric surface at a selected location on the workpiece.

Harvesting small trees for bio-energy

Treesearch

John Klepac; Robert Rummer; Jason Thompson

2011-01-01

A conventional whole-tree logging operation consisting of 4-wheeled and 3-wheeled saw-head feller-bunchers, two grapple skidders and a chipper that produces dirty chips was monitored across several stands and machine performance evaluated. Stands were inventoried to determine density, volume, and basal area per acre and will be used to relate machine performance to...

Improved Tensile Test for Ceramics

NASA Technical Reports Server (NTRS)

Osiecki, R. A.

1982-01-01

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

[Mechatronic in functional endoscopic sinus surgery. First experiences with the daVinci Telemanipulatory System].

PubMed

Strauss, G; Winkler, D; Jacobs, S; Trantakis, C; Dietz, A; Bootz, F; Meixensberger, J; Falk, V

2005-07-01

This study examines the advantages and disadvantages of a commercial telemanipulator system (daVinci, Intuitive Surgical, USA) with computer-guided instruments in functional endoscopic sinus surgery (FESS). We performed five different surgical FESS steps on 14 anatomical preparation and compared them with conventional FESS. A total of 140 procedures were examined taking into account the following parameters: degrees of freedom (DOF), duration , learning curve, force feedback, human-machine-interface. Telemanipulatory instruments have more DOF available then conventional instrumentation in FESS. The average time consumed by configuration of the telemanipulator is around 9+/-2 min. Missing force feedback is evaluated mainly as a disadvantage of the telemanipulator. Scaling was evaluated as helpful. The ergonomic concept seems to be better than the conventional solution. Computer guided instruments showed better results for the available DOF of the instruments. The human-machine-interface is more adaptable and variable then in conventional instrumentation. Motion scaling and indexing are characteristics of the telemanipulator concept which are helpful for FESS in our study.

Air Bearings Machined On Ultra Precision, Hydrostatic CNC-Lathe

NASA Astrophysics Data System (ADS)

Knol, Pierre H.; Szepesi, Denis; Deurwaarder, Jan M.

1987-01-01

Micromachining of precision elements requires an adequate machine concept to meet the high demand of surface finish, dimensional and shape accuracy. The Hembrug ultra precision lathes have been exclusively designed with hydrostatic principles for main spindle and guideways. This concept is to be explained with some major advantages of hydrostatics compared with aerostatics at universal micromachining applications. Hembrug has originally developed the conventional Mikroturn ultra precision facing lathes, for diamond turning of computer memory discs. This first generation of machines was followed by the advanced computer numerically controlled types for machining of complex precision workpieces. One of these parts, an aerostatic bearing component has been succesfully machined on the Super-Mikroturn CNC. A case study of airbearing machining confirms the statement that a good result of the micromachining does not depend on machine performance alone, but also on the technology applied.

Ultra precision machining

NASA Astrophysics Data System (ADS)

Debra, Daniel B.; Hesselink, Lambertus; Binford, Thomas

1990-05-01

There are a number of fields that require or can use to advantage very high precision in machining. For example, further development of high energy lasers and x ray astronomy depend critically on the manufacture of light weight reflecting metal optical components. To fabricate these optical components with machine tools they will be made of metal with mirror quality surface finish. By mirror quality surface finish, it is meant that the dimensions tolerances on the order of 0.02 microns and surface roughness of 0.07. These accuracy targets fall in the category of ultra precision machining. They cannot be achieved by a simple extension of conventional machining processes and techniques. They require single crystal diamond tools, special attention to vibration isolation, special isolation of machine metrology, and on line correction of imperfection in the motion of the machine carriages on their way.

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

NASA Astrophysics Data System (ADS)

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

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

Two High-Temperature Foil Journal Bearings

NASA Technical Reports Server (NTRS)

Zak, Michail

2006-01-01

An enlarged, high-temperature-compliant foil bearing has been built and tested to demonstrate the feasibility of such bearings for use in aircraft gas turbine engines. Foil bearings are attractive for use in some machines in which (1) speeds of rotation, temperatures, or both exceed maximum allowable values for rolling-element bearings; (2) conventional lubricants decompose at high operating temperatures; and/or (3) it is necessary or desirable not to rely on conventional lubrication systems. In a foil bearing, the lubricant is the working fluid (e.g., air or a mixture of combustion gases) in the space between the journal and the shaft in the machine in which the bearing is installed.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Machine learning phases of matter

NASA Astrophysics Data System (ADS)

Carrasquilla, Juan; Stoudenmire, Miles; Melko, Roger

We show how the technology that allows automatic teller machines read hand-written digits in cheques can be used to encode and recognize phases of matter and phase transitions in many-body systems. In particular, we analyze the (quasi-)order-disorder transitions in the classical Ising and XY models. Furthermore, we successfully use machine learning to study classical Z2 gauge theories that have important technological application in the coming wave of quantum information technologies and whose phase transitions have no conventional order parameter.

Unorganized machines for seasonal streamflow series forecasting.

PubMed

Siqueira, Hugo; Boccato, Levy; Attux, Romis; Lyra, Christiano

2014-05-01

Modern unorganized machines--extreme learning machines and echo state networks--provide an elegant balance between processing capability and mathematical simplicity, circumventing the difficulties associated with the conventional training approaches of feedforward/recurrent neural networks (FNNs/RNNs). This work performs a detailed investigation of the applicability of unorganized architectures to the problem of seasonal streamflow series forecasting, considering scenarios associated with four Brazilian hydroelectric plants and four distinct prediction horizons. Experimental results indicate the pertinence of these models to the focused task.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

PubMed

Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

2018-05-09

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

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

Hill, Mary Ann; Dombrowski, David E.; Clarke, Kester Diederik

U-10 wt. % Mo (U-10Mo) alloys are being developed as low enrichment monolithic fuel for the CONVERT program. Optimization of processing for the monolithic fuel is being pursued with the use of electrical discharge machining (EDM) under CONVERT HPRR WBS 1.2.4.5 Optimization of Coupon Preparation. The process is applicable to manufacturing experimental fuel plate specimens for the Mini-Plate-1 (MP-1) irradiation campaign. The benefits of EDM are reduced machining costs, ability to achieve higher tolerances, stress-free, burr-free surfaces eliminating the need for milling, and the ability to machine complex shapes. Kerf losses are much smaller with EDM (tenths of mm) comparedmore » to conventional machining (mm). Reliable repeatability is achievable with EDM due to its computer-generated machining programs.« less

Multi-parameter monitoring of electrical machines using integrated fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Fabian, Matthias; Hind, David; Gerada, Chris; Sun, Tong; Grattan, Kenneth T. V.

2017-04-01

In this paper a sensor system for multi-parameter electrical machine condition monitoring is reported. The proposed FBG-based system allows for the simultaneous monitoring of machine vibration, rotor speed and position, torque, spinning direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution reduces the component count of conventional sensor systems, i.e., all 48 sensing elements are contained within the machine operated by a single sensing interrogation unit. In this work, the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

Comparison of thin-film resistance heat-transfer gages with thin-skin transient calorimeter gages in conventional hypersonic wind tunnels

NASA Technical Reports Server (NTRS)

Miller, C. G., III

1981-01-01

Thin film gages deposited at the stagnation region of small (8.1-mm-diameter) hemispheres and gages mounted flush with the surface of a sharp-leading-edge flat plate were tested in the Langley continuous-flow hypersonic tunnel and in the Langley hypersonic CF4 tunnel. Two substrate materials were tested, quartz and a machinable glass-ceramic. Small hemispheres were also tested utilizing the thin-skin transient calorimeter technique usually employed in conventional tunnels. One transient calorimeter model was a thin shell of stainless steel, and the other was a thin-skin insert of stainless steel mounted into a hemisphere fabricated from a machinable-glass-ceramic. Measured heat-transfer rates from the various hemispheres were compared with one another and with predicted rates. The results demonstrate the feasibility and advantages of using-film resistance heat-transfer gages in conventional hypersonic wind tunnels over a wide range of conditions.

Vibration Damping Analysis of Lightweight Structures in Machine Tools

PubMed Central

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

2017-01-01

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

Experimental investigations on cryogenic cooling by liquid nitrogen in the end milling of hardened steel

NASA Astrophysics Data System (ADS)

Ravi, S.; Pradeep Kumar, M.

2011-09-01

Milling of hardened steel generates excessive heat during the chip formation process, which increases the temperature of cutting tool and accelerates tool wear. Application of conventional cutting fluid in milling process may not effectively control the heat generation also it has inherent health and environmental problems. To minimize health hazard and environmental problems caused by using conventional cutting fluid, a cryogenic cooling set up is developed to cool tool-chip interface using liquid nitrogen (LN 2). This paper presents results on the effect of LN 2 as a coolant on machinability of hardened AISI H13 tool steel for varying cutting speed in the range of 75-125 m/min during end milling with PVD TiAlN coated carbide inserts at a constant feed rate. The results show that machining with LN 2 lowers cutting temperature, tool flank wear, surface roughness and cutting forces as compared with dry and wet machining. With LN 2 cooling, it has been found that the cutting temperature was reduced by 57-60% and 37-42%; the tool flank wear was reduced by 29-34% and 10-12%; the surface roughness was decreased by 33-40% and 25-29% compared to dry and wet machining. The cutting forces also decreased moderately compared to dry and wet machining. This can be attributed to the fact that LN 2 machining provides better cooling and lubrication through substantial reduction in the cutting zone temperature.

Investigation of a tubular dual-stator flux-switching permanent-magnet linear generator for free-piston energy converter

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Tong, Chengde; Yu, Bin; Zhu, Shaohong; Zhu, Jianguo

2015-05-01

This paper describes a tubular dual-stator flux-switching permanent-magnet (PM) linear generator for free-piston energy converter. The operating principle, topology, and design considerations of the machine are investigated. Combining the motion characteristic of free-piston Stirling engine, a tubular dual-stator PM linear generator is designed by finite element method. Some major structural parameters, such as the outer and inner radii of the mover, PM thickness, mover tooth width, tooth width of the outer and inner stators, etc., are optimized to improve the machine performances like thrust capability and power density. In comparison with conventional single-stator PM machines like moving-magnet linear machine and flux-switching linear machine, the proposed dual-stator flux-switching PM machine shows advantages in higher mass power density, higher volume power density, and lighter mover.

A tubular hybrid Halbach/axially-magnetized permanent-magnet linear machine

NASA Astrophysics Data System (ADS)

Sui, Yi; Liu, Yong; Cheng, Luming; Liu, Jiaqi; Zheng, Ping

2017-05-01

A single-phase tubular permanent-magnet linear machine (PMLM) with hybrid Halbach/axially-magnetized PM arrays is proposed for free-piston Stirling power generation system. Machine topology and operating principle are elaborately illustrated. With the sinusoidal speed characteristic of the free-piston Stirling engine considered, the proposed machine is designed and calculated by finite-element analysis (FEA). The main structural parameters, such as outer radius of the mover, radial length of both the axially-magnetized PMs and ferromagnetic poles, axial length of both the middle and end radially-magnetized PMs, etc., are optimized to improve both the force capability and power density. Compared with the conventional PMLMs, the proposed machine features high mass and volume power density, and has the advantages of simple control and low converter cost. The proposed machine topology is applicable to tubular PMLMs with any phases.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Electronically commutated motors for vehicle applications

NASA Astrophysics Data System (ADS)

Echolds, E. F.

1980-02-01

Two permanent magnet electronically commutated motors for electric vehicle traction are discussed. One, based on existing technology, produces 23 kW (peak) at 26,000 rpm, and 11 kW continuous at 18,000 rpm. The motor has a conventional design: a four-pole permanent magnet rotor and a three-phase stator similar to those used on ordinary induction motors. The other, advanced technology motor, is rated at 27 kW (peak) at 14,000 rpm, and 11 kW continuous at 10,500 rpm. The machine employs a permanent magnet rotor and a novel ironless stator design in an axial air gap, homopolar configuration. Comparison of the new motors with conventional brush type machines indicates potential for substantial cost savings.

Development of Handcraft Exercise Courses that Bring Out Student's Creativity

NASA Astrophysics Data System (ADS)

Senda, Shinkoh; Yamamoto, Koji; Fukumori, Tutom; Matsuura, Hideo; Sato, Kazuo

We have developed a new type of handcraft exercise program that aims to stimulate student's creativity on the way of design and fabrication of the subject machines. Conventional handicraft exercise program used to aim at letting students learn procedures of machining operation in accordance with a designated manual. Students having experienced our conventional exercise did not fully satisfied at those programs because of the lack in a room for their idea and creativity. Authors, a group of both technical and academic staffs, have developed and started the new type of program since 2003 at the Creation Plaza in Nagoya University. Developed program is classified into grades according to the difference in technical contents required for students.

Ultrasonically assisted turning of aviation materials: simulations and experimental study.

PubMed

Babitsky, V I; Mitrofanov, A V; Silberschmidt, V V

2004-04-01

Ultrasonically assisted turning of modern aviation materials is conducted with ultrasonic vibration (frequency f approximately 20 kHz, amplitude a approximately 15 microm) superimposed on the cutting tool movement. An autoresonant control system is used to maintain the stable nonlinear resonant mode of vibration throughout the cutting process. Experimental comparison of roughness and roundness for workpieces machined conventionally and with the superimposed ultrasonic vibration, results of high-speed filming of the turning process and nanoindentation analyses of the microstructure of the machined material are presented. The suggested finite-element model provides numerical comparison between conventional and ultrasonic turning of Inconel 718 in terms of stress/strain state, cutting forces and contact conditions at the workpiece/tool interface.

Using methods from the data mining and machine learning literature for disease classification and prediction: A case study examining classification of heart failure sub-types

PubMed Central

Austin, Peter C.; Tu, Jack V.; Ho, Jennifer E.; Levy, Daniel; Lee, Douglas S.

2014-01-01

Objective Physicians classify patients into those with or without a specific disease. Furthermore, there is often interest in classifying patients according to disease etiology or subtype. Classification trees are frequently used to classify patients according to the presence or absence of a disease. However, classification trees can suffer from limited accuracy. In the data-mining and machine learning literature, alternate classification schemes have been developed. These include bootstrap aggregation (bagging), boosting, random forests, and support vector machines. Study design and Setting We compared the performance of these classification methods with those of conventional classification trees to classify patients with heart failure according to the following sub-types: heart failure with preserved ejection fraction (HFPEF) vs. heart failure with reduced ejection fraction (HFREF). We also compared the ability of these methods to predict the probability of the presence of HFPEF with that of conventional logistic regression. Results We found that modern, flexible tree-based methods from the data mining literature offer substantial improvement in prediction and classification of heart failure sub-type compared to conventional classification and regression trees. However, conventional logistic regression had superior performance for predicting the probability of the presence of HFPEF compared to the methods proposed in the data mining literature. Conclusion The use of tree-based methods offers superior performance over conventional classification and regression trees for predicting and classifying heart failure subtypes in a population-based sample of patients from Ontario. However, these methods do not offer substantial improvements over logistic regression for predicting the presence of HFPEF. PMID:23384592

Where tunneling equipment is heading

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

Singhal, R.K.

1984-02-01

A variety of equipment is being used for roadheading and tunneling in the mining industry. This includes hydraulic/rotary precussive drills for use in conventional drill and blast, drum-type continuous miners, roadheaders, mini-and midi-full facers for small size openings, soft rock shielded tunnel boring machines, and hard rock tunnel boring machines. The availability, performance, and specifications for tunneling equipment are discussed.

Electric vehicle traction motors - The development of an advanced motor concept

NASA Technical Reports Server (NTRS)

Campbell, P.

1980-01-01

An axial-field permanent magnet traction motor is described, similar to several advanced motors that are being developed in the United States. This type of machine has several advantages over conventional dc motors, particularly in the electric vehicle application. The rapidly changing cost of magnetic materials, particularly cobalt, makes it important to study the utilization of permanent magnet materials in such machines. The impact of different magnets on machine design is evaluated, and the advantages of using iron powder composites in the armature are assessed.

Automated planning for intelligent machines in energy-related applications

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

Weisbin, C.R.; de Saussure, G.; Barhen, J.

1984-01-01

This paper discusses the current activities of the Center for Engineering Systems Advanced Research (CESAR) program related to plan generation and execution by an intelligent machine. The system architecture for the CESAR mobile robot (named HERMIES-1) is described. The minimal cut-set approach is developed to reduce the tree search time of conventional backward chaining planning techniques. Finally, a real-time concept of an Intelligent Machine Operating System is presented in which planning and reasoning is embedded in a system for resource allocation and process management.

Energy efficient quantum machines

NASA Astrophysics Data System (ADS)

Abah, Obinna; Lutz, Eric

2017-05-01

We investigate the performance of a quantum thermal machine operating in finite time based on shortcut-to-adiabaticity techniques. We compute efficiency and power for a paradigmatic harmonic quantum Otto engine by taking the energetic cost of the shortcut driving explicitly into account. We demonstrate that shortcut-to-adiabaticity machines outperform conventional ones for fast cycles. We further derive generic upper bounds on both quantities, valid for any heat engine cycle, using the notion of quantum speed limit for driven systems. We establish that these quantum bounds are tighter than those stemming from the second law of thermodynamics.

Development of a rapid and sensitive one-step reverse transcription-nested polymerase chain reaction in a single tube using the droplet-polymerase chain reaction machine.

PubMed

Yamaguchi, Akemi; Matsuda, Kazuyuki; Sueki, Akane; Taira, Chiaki; Uehara, Masayuki; Saito, Yasunori; Honda, Takayuki

2015-08-25

Reverse transcription (RT)-nested polymerase chain reaction (PCR) is a time-consuming procedure because it has several handling steps and is associated with the risk of cross-contamination during each step. Therefore, a rapid and sensitive one-step RT-nested PCR was developed that could be performed in a single tube using a droplet-PCR machine. The K562 BCR-ABL mRNA-positive cell line as well as bone marrow aspirates from 5 patients with chronic myelogenous leukemia (CML) and 5 controls without CML were used. We evaluated one-step RT-nested PCR using the droplet-PCR machine. One-step RT-nested PCR performed in a single tube using the droplet-PCR machine enabled the detection of BCR-ABL mRNA within 40min, which was 10(3)-fold superior to conventional RT nested PCR using three steps in separate tubes. The sensitivity of the one-step RT-nested PCR was 0.001%, with sample reactivity comparable to that of the conventional assay. One-step RT-nested PCR was developed using the droplet-PCR machine, which enabled all reactions to be performed in a single tube accurately and rapidly and with high sensitivity. This one-step RT-nested PCR may be applicable to a wide spectrum of genetic tests in clinical laboratories. Copyright © 2015 Elsevier B.V. All rights reserved.

Wear of Cutting Tool with Excel Geometry in Turning Process of Hardened Steel

NASA Astrophysics Data System (ADS)

Samardžiová, Michaela

2016-09-01

This paper deals with hard turning using a cutting tool with Xcel geometry. This is one of the new geometries, and there is not any information about Xcel wear in comparison to the conventional geometry. It is already known from cutting tools producers that using the Xcel geometry leads to higher quality of machined surface, perticularly surface roughness. It is possible to achieve more than 4 times lower Ra and Rz values after turning than after using conventional geometry with radius. The workpiece material was 100Cr6 hardened steel with hardness of 60 ± 1 HRC. The machine used for the experiment was a lathe with counter spindle DMG CTX alpha 500, which is located in the Centre of Excellence of 5-axis Machining at the Faculty of Materials Science and Technology in Trnava. The cutting tools made by CBN were obtained from Sandvik COROMANT Company. The aim of this paper is to investigate the cutting tool wear in hard turning process by the Xcel cutting tool geometry.

Quantitative Evaluation of Heavy Duty Machine Tools Remanufacturing Based on Modified Catastrophe Progression Method

NASA Astrophysics Data System (ADS)

shunhe, Li; jianhua, Rao; lin, Gui; weimin, Zhang; degang, Liu

2017-11-01

The result of remanufacturing evaluation is the basis for judging whether the heavy duty machine tool can remanufacture in the EOL stage of the machine tool lifecycle management.The objectivity and accuracy of evaluation is the key to the evaluation method.In this paper, the catastrophe progression method is introduced into the quantitative evaluation of heavy duty machine tools’ remanufacturing,and the results are modified by the comprehensive adjustment method,which makes the evaluation results accord with the standard of human conventional thinking.Using the catastrophe progression method to establish the heavy duty machine tools’ quantitative evaluation model,to evaluate the retired TK6916 type CNC floor milling-boring machine’s remanufacturing.The evaluation process is simple,high quantification,the result is objective.

High-Strength Undiffused Brushless (HSUB) Machine

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

Hsu, John S; Tolbert, Leon M; Lee, Seong T

2007-01-01

This paper introduces a new high-strength undiffused brushless machine that transfers the stationary excitation magnetomotive force to the rotor without any brushes. For a conventional permanent magnet (PM) machine, the air gap flux density cannot be enhanced effectively but can be weakened. In the new machine, both the stationary excitation coil and the PM in the rotor produce an enhanced air gap flux. The PM in the rotor prevents magnetic flux diffusion between the poles and guides the reluctance flux path. The pole flux density in the air gap can be much higher than what the PM alone can produce.more » A high-strength machine is thus obtained. The air gap flux density can be weakened through the stationary excitation winding. This type of machine is particularly suitable for electric and hybrid-electric vehicle applications. Patents of this new technology are either granted or pending.« less

Knowledge-based load leveling and task allocation in human-machine systems

NASA Technical Reports Server (NTRS)

Chignell, M. H.; Hancock, P. A.

1986-01-01

Conventional human-machine systems use task allocation policies which are based on the premise of a flexible human operator. This individual is most often required to compensate for and augment the capabilities of the machine. The development of artificial intelligence and improved technologies have allowed for a wider range of task allocation strategies. In response to these issues a Knowledge Based Adaptive Mechanism (KBAM) is proposed for assigning tasks to human and machine in real time, using a load leveling policy. This mechanism employs an online workload assessment and compensation system which is responsive to variations in load through an intelligent interface. This interface consists of a loading strategy reasoner which has access to information about the current status of the human-machine system as well as a database of admissible human/machine loading strategies. Difficulties standing in the way of successful implementation of the load leveling strategy are examined.

Osteoporosis risk prediction for bone mineral density assessment of postmenopausal women using machine learning.

PubMed

Yoo, Tae Keun; Kim, Sung Kean; Kim, Deok Won; Choi, Joon Yul; Lee, Wan Hyung; Oh, Ein; Park, Eun-Cheol

2013-11-01

A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women compared to the ability of conventional clinical decision tools. We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Examination Surveys. The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests, artificial neural networks (ANN), and logistic regression (LR) based on simple surveys. The machine learning models were compared to four conventional clinical decision tools: osteoporosis self-assessment tool (OST), osteoporosis risk assessment instrument (ORAI), simple calculated osteoporosis risk estimation (SCORE), and osteoporosis index of risk (OSIRIS). SVM had significantly better area under the curve (AUC) of the receiver operating characteristic than ANN, LR, OST, ORAI, SCORE, and OSIRIS for the training set. SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0% at total hip, femoral neck, or lumbar spine for the testing set. The significant factors selected by SVM were age, height, weight, body mass index, duration of menopause, duration of breast feeding, estrogen therapy, hyperlipidemia, hypertension, osteoarthritis, and diabetes mellitus. Considering various predictors associated with low bone density, the machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

In vitro assessment of cutting efficiency and durability of zirconia removal diamond rotary instruments.

PubMed

Kim, Joon-Soo; Bae, Ji-Hyeon; Yun, Mi-Jung; Huh, Jung-Bo

2017-06-01

Recently, zirconia removal diamond rotary instruments have become commercially available for efficient cutting of zirconia. However, research of cutting efficiency and the cutting characteristics of zirconia removal diamond rotary instruments is limited. The purpose of this in vitro study was to assess and compare the cutting efficiency, durability, and diamond rotary instrument wear pattern of zirconia diamond removal rotary instruments with those of conventional diamond rotary instruments. In addition, the surface characteristics of the cut zirconia were assessed. Block specimens of 3 mol% yttrium cation-doped tetragonal zirconia polycrystal were machined 10 times for 1 minute each using a high-speed handpiece with 6 types of diamond rotary instrument from 2 manufacturers at a constant force of 2 N (n=5). An electronic scale was used to measure the lost weight after each cut in order to evaluate the cutting efficiency. Field emission scanning electron microscopy was used to evaluate diamond rotary instrument wear patterns and machined zirconia block surface characteristics. Data were statistically analyzed using the Kruskal-Wallis test, followed by the Mann-Whitney U test (α=.05). Zirconia removal fine grit diamond rotary instruments showed cutting efficiency that was reduced compared with conventional fine grit diamond rotary instruments. Diamond grit fracture was the most dominant diamond rotary instrument wear pattern in all groups. All machined zirconia surfaces were primarily subjected to plastic deformation, which is evidence of ductile cutting. Zirconia blocks machined with zirconia removal fine grit diamond rotary instruments showed the least incidence of surface flaws. Although zirconia removal diamond rotary instruments did not show improved cutting efficiency compared with conventional diamond rotary instruments, the machined zirconia surface showed smoother furrows of plastic deformation and fewer surface flaws. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Quantification of tooth wear: conventional vs new method using toolmakers microscope and a three-dimensional measuring technique.

PubMed

Al-Omiri, Mahmoud K; Harb, Rousan; Abu Hammad, Osama A; Lamey, Philip-John; Lynch, Edward; Clifford, Thomas J

2010-07-01

This study aimed to evaluate the reliability of a new CAD-CAM Laser scanning machine in detection of incisal tooth wear through a 6-month period and to compare the accuracy of using this new machine against measuring tooth wear using tool maker microscope and conventional tooth wear index. Twenty participants (11 males and 9 females, mean age=22.7 years, SD=2.0) were assessed for incisal tooth wear of lower anterior teeth using Smith and Knight clinical tooth wear index (TWI) on two occasions, the study baseline and 6 months later. Stone dies for each tooth were prepared and scanned using the CAD-CAM Laser Cercon System (Cercon Smart Ceramics, DeguDent, Germany). Scanned images were printed and examined under a toolmaker microscope (Stedall-Dowding Machine Tool Company, Optique et Mecanique de Precision, Marcel Aubert SA, Switzerland) to quantify tooth wear and then the dies were directly assessed under the microscope to measure tooth wear. The Wilcoxon Signed Ranks Test was used to analyse the data. TWI scores for incisal edges were 0, 1, and 2 and were similar at both occasions. Scores 3 and 4 were not detected. Wear values measured by directly assessing the dies under the tool maker microscope (range=517-656microm, mean=582microm, and SD=50) were significantly more than those measured from the Cercon digital machine images (range=132-193microm, mean =165microm, and SD=27) and both showed significant differences between the two occasions. Measuring images obtained with Cercon digital machine under tool maker microscope allowed detection of wear progression over the 6-month period. However, measuring the dies of worn dentition directly under the tool maker microscope enabled detection of wear progression more accurately. Conventional method was the least sensitive for tooth wear quantification and was unable to identify wear progression in most cases. Copyright 2010 Elsevier Ltd. All rights reserved.

Machine Learning Algorithms Outperform Conventional Regression Models in Predicting Development of Hepatocellular Carcinoma

PubMed Central

Singal, Amit G.; Mukherjee, Ashin; Elmunzer, B. Joseph; Higgins, Peter DR; Lok, Anna S.; Zhu, Ji; Marrero, Jorge A; Waljee, Akbar K

2015-01-01

Background Predictive models for hepatocellular carcinoma (HCC) have been limited by modest accuracy and lack of validation. Machine learning algorithms offer a novel methodology, which may improve HCC risk prognostication among patients with cirrhosis. Our study's aim was to develop and compare predictive models for HCC development among cirrhotic patients, using conventional regression analysis and machine learning algorithms. Methods We enrolled 442 patients with Child A or B cirrhosis at the University of Michigan between January 2004 and September 2006 (UM cohort) and prospectively followed them until HCC development, liver transplantation, death, or study termination. Regression analysis and machine learning algorithms were used to construct predictive models for HCC development, which were tested on an independent validation cohort from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial. Both models were also compared to the previously published HALT-C model. Discrimination was assessed using receiver operating characteristic curve analysis and diagnostic accuracy was assessed with net reclassification improvement and integrated discrimination improvement statistics. Results After a median follow-up of 3.5 years, 41 patients developed HCC. The UM regression model had a c-statistic of 0.61 (95%CI 0.56-0.67), whereas the machine learning algorithm had a c-statistic of 0.64 (95%CI 0.60–0.69) in the validation cohort. The machine learning algorithm had significantly better diagnostic accuracy as assessed by net reclassification improvement (p<0.001) and integrated discrimination improvement (p=0.04). The HALT-C model had a c-statistic of 0.60 (95%CI 0.50-0.70) in the validation cohort and was outperformed by the machine learning algorithm (p=0.047). Conclusion Machine learning algorithms improve the accuracy of risk stratifying patients with cirrhosis and can be used to accurately identify patients at high-risk for developing HCC. PMID:24169273

The Effects of Some Surface Irregularities on Wing Drag

NASA Technical Reports Server (NTRS)

Drag, Manley

1939-01-01

The N.A.C.A. has conducted tests to provide more complete data than were previously available for estimating the effects of common surface irregularities on wing drag. The irregularities investigated included: brazier-head and countersunk rivets, spot welds, several types of sheet-metal joints, and surface roughness. Tests were also conducted to determine the over-all effect of manufacturing irregularities incidental to riveted aluminum alloy and to spot-welded stainless-steel construction. The tests were made in the 8-foot high speed wind tunnel at Reynolds Numbers up to 18,000,000. The results show that any of the surface irregularities investigated may increase wing drag enough to have important adverse effects on high-speed performance and economy. A method of estimating increases in wing drag caused by brazier-head rivets and lapped joints under conditions outside the range of the tests is suggested. Estimated drag increases due to rivets and lapped joints under conditions outside the range of the tests is suggested. Estimated drag increases due to rivets and lapped joints on a wing of 20-foot chord flying at 250 miles per hour are shown.

Machine Learning and Radiology

PubMed Central

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

Influence of the Regime of Electropulsing-Assisted Machining on the Plastic Deformation of the Layer Being Cut.

PubMed

Hameed, Saqib; González Rojas, Hernán A; Perat Benavides, José I; Nápoles Alberro, Amelia; Sánchez Egea, Antonio J

2018-05-25

In this article, the influence of electropulsing on the machinability of steel S235 and aluminium 6060 has been studied during conventional and electropulsing-assisted turning processes. The machinability indices such as chip compression ratio ξ , shear plane angle ϕ and specific cutting energy (SCE) are investigated by using different cutting parameters such as cutting speed, cutting feed and depth of cut during electrically-assisted turning process. The results and analysis of this work indicated that the electrically-assisted turning process improves the machinability of steel S235, whereas the machinability of aluminium 6060 gets worse. Finally, due to electropluses (EPs), the chip compression ratio ξ increases with the increase in cutting speed during turning of aluminium 6060 and the SCE decreases during turning of steel S235.

Research on electrodischarge drilling of polycrystalline diamond with increased gap voltage

NASA Astrophysics Data System (ADS)

Skoczypiec, Sebastian; Bizoń, Wojciech; Żyra, Agnieszka

2018-05-01

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

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

NASA Astrophysics Data System (ADS)

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

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

A New Arbiter PUF for Enhancing Unpredictability on FPGA

PubMed Central

Machida, Takanori; Yamamoto, Dai; Iwamoto, Mitsugu; Sakiyama, Kazuo

2015-01-01

In general, conventional Arbiter-based Physically Unclonable Functions (PUFs) generate responses with low unpredictability. The N-XOR Arbiter PUF, proposed in 2007, is a well-known technique for improving this unpredictability. In this paper, we propose a novel design for Arbiter PUF, called Double Arbiter PUF, to enhance the unpredictability on field programmable gate arrays (FPGAs), and we compare our design to conventional N-XOR Arbiter PUFs. One metric for judging the unpredictability of responses is to measure their tolerance to machine-learning attacks. Although our previous work showed the superiority of Double Arbiter PUFs regarding unpredictability, its details were not clarified. We evaluate the dependency on the number of training samples for machine learning, and we discuss the reason why Double Arbiter PUFs are more tolerant than the N-XOR Arbiter PUFs by evaluating intrachip variation. Further, the conventional Arbiter PUFs and proposed Double Arbiter PUFs are evaluated according to other metrics, namely, their uniqueness, randomness, and steadiness. We demonstrate that 3-1 Double Arbiter PUF archives the best performance overall. PMID:26491720

Multichannel noninvasive human-machine interface via stretchable µm thick sEMG patches for robot manipulation

NASA Astrophysics Data System (ADS)

Zhou, Ying; Wang, Youhua; Liu, Runfeng; Xiao, Lin; Zhang, Qin; Huang, YongAn

2018-01-01

Epidermal electronics (e-skin) emerging in recent years offer the opportunity to noninvasively and wearably extract biosignals from human bodies. The conventional processes of e-skin based on standard microelectronic fabrication processes and a variety of transfer printing methods, nevertheless, unquestionably constrains the size of the devices, posing a serious challenge to collecting signals via skin, the largest organ in the human body. Herein we propose a multichannel noninvasive human-machine interface (HMI) using stretchable surface electromyography (sEMG) patches to realize a robot hand mimicking human gestures. Time-efficient processes are first developed to manufacture µm thick large-scale stretchable devices. With micron thickness, the stretchable µm thick sEMG patches show excellent conformability with human skin and consequently comparable electrical performance with conventional gel electrodes. Combined with the large-scale size, the multichannel noninvasive HMI via stretchable µm thick sEMG patches successfully manipulates the robot hand with eight different gestures, whose precision is as high as conventional gel electrodes array.

Improvement of the COP of the LiBr-Water Double-Effect Absorption Cycles

NASA Astrophysics Data System (ADS)

Shitara, Atsushi

Prevention of the global warming has called for a great necessity for energy saving. This applies to the improvement of the COP of absorption chiller-heaters. We started the development of the high efficiency gas-fired double-effect absorption chiller-heater using LiBr-H2O to achieve target performance in short or middle term. To maintain marketability, the volume of the high efficiency machine has been set below the equal to the conventional machine. The absorption cycle technology for improving the COP and the element technology for downsizing the machine is necessary in this development. In this study, the former is investigated. In this report, first of all the target performance has been set at cooling COP of 1.35(on HHV), which is 0.35 higher than the COP of 1.0 for conventional machines in the market. This COP of 1.35 is practically close to the maximum limit achievable by double-effect absorption chiller-heater. Next, the design condition of each element to achieve the target performance and the effect of each mean to improve the COP are investigated. Moreover, as a result of comparing the various flows(series, parallel, reverse)to which the each mean is applied, it has been found the optimum cycle is the parallel flow.

Line-drawing algorithms for parallel machines

NASA Technical Reports Server (NTRS)

Pang, Alex T.

1990-01-01

The fact that conventional line-drawing algorithms, when applied directly on parallel machines, can lead to very inefficient codes is addressed. It is suggested that instead of modifying an existing algorithm for a parallel machine, a more efficient implementation can be produced by going back to the invariants in the definition. Popular line-drawing algorithms are compared with two alternatives; distance to a line (a point is on the line if sufficiently close to it) and intersection with a line (a point on the line if an intersection point). For massively parallel single-instruction-multiple-data (SIMD) machines (with thousands of processors and up), the alternatives provide viable line-drawing algorithms. Because of the pixel-per-processor mapping, their performance is independent of the line length and orientation.

Grinding, Machining Morphological Studies on C/SiC Composites

NASA Astrophysics Data System (ADS)

Xiao, Chun-fang; Han, Bing

2018-05-01

C/SiC composite is a typical material difficult to machine. It is hard and brittle. In machining, the cutting force is large, the material removal rate is low, the edge is prone to collapse, and the tool wear is serious. In this paper, the grinding of C/Si composites material along the direction of fiber distribution is studied respectively. The surface microstructure and mechanical properties of C/SiC composites processed by ultrasonic machining were evaluated. The change of surface quality with the change of processing parameters has also been studied. By comparing the performances of conventional grinding and ultrasonic grinding, the surface roughness and functional characteristics of the material can be improved by optimizing the processing parameters.

Optimizing friction stir weld parameters of aluminum and copper using conventional milling machine

NASA Astrophysics Data System (ADS)

Manisegaran, Lohappriya V.; Ahmad, Nurainaa Ayuni; Nazri, Nurnadhirah; Noor, Amirul Syafiq Mohd; Ramachandran, Vignesh; Ismail, Muhammad Tarmizizulfika; Ahmad, Ku Zarina Ku; Daruis, Dian Darina Indah

2018-05-01

The joining of two of any particular materials through friction stir welding (FSW) are done by a rotating tool and the work piece material that generates heat which causes the region near the FSW tool to soften. This in return will mechanically intermix the work pieces. The first objective of this study is to join aluminum plates and copper plates by means of friction stir welding process using self-fabricated tools and conventional milling machine. This study also aims to investigate the optimum process parameters to produce the optimum mechanical properties of the welding joints for Aluminum plates and Copper plates. A suitable tool bit and a fixture is to be fabricated for the welding process. A conventional milling machine will be used to weld the aluminum and copper. The most important parameters to enable the process are speed and pressure of the tool (or tool design and alignment of the tool onto the work piece). The study showed that the best surface finish was produced from speed of 1150 rpm and tool bit tilted to 3°. For a 200mm × 100mm Aluminum 6061 with plate thickness of 2 mm at a speed of 1 mm/s, the time taken to complete the welding is only 200 seconds or equivalent to 3 minutes and 20 seconds. The Copper plates was successfully welded using FSW with tool rotation speed of 500 rpm, 700 rpm, 900 rpm, 1150 rpm and 1440 rpm and with welding traverse rate of 30 mm/min, 60 mm/min and 90 mm/min. As the conclusion, FSW using milling machine can be done on both Aluminum and Copper plates, however the weld parameters are different for the two types of plates.

AC Loss Analysis of MgB2-Based Fully Superconducting Machines

NASA Astrophysics Data System (ADS)

Feddersen, M.; Haran, K. S.; Berg, F.

2017-12-01

Superconducting electric machines have shown potential for significant increase in power density, making them attractive for size and weight sensitive applications such as offshore wind generation, marine propulsion, and hybrid-electric aircraft propulsion. Superconductors exhibit no loss under dc conditions, though ac current and field produce considerable losses due to hysteresis, eddy currents, and coupling mechanisms. For this reason, many present machines are designed to be partially superconducting, meaning that the dc field components are superconducting while the ac armature coils are conventional conductors. Fully superconducting designs can provide increases in power density with significantly higher armature current; however, a good estimate of ac losses is required to determine the feasibility under the machines intended operating conditions. This paper aims to characterize the expected losses in a fully superconducting machine targeted towards aircraft, based on an actively-shielded, partially superconducting machine from prior work. Various factors are examined such as magnet strength, operating frequency, and machine load to produce a model for the loss in the superconducting components of the machine. This model is then used to optimize the design of the machine for minimal ac loss while maximizing power density. Important observations from the study are discussed.

Hybrid micromachining using a nanosecond pulsed laser and micro EDM

NASA Astrophysics Data System (ADS)

Kim, Sanha; Kim, Bo Hyun; Chung, Do Kwan; Shin, Hong Shik; Chu, Chong Nam

2010-01-01

Micro electrical discharge machining (micro EDM) is a well-known precise machining process that achieves micro structures of excellent quality for any conductive material. However, the slow machining speed and high tool wear are main drawbacks of this process. Though the use of deionized water instead of kerosene as a dielectric fluid can reduce the tool wear and increase the machine speed, the material removal rate (MRR) is still low. In contrast, laser ablation using a nanosecond pulsed laser is a fast and non-wear machining process but achieves micro figures of rather low quality. Therefore, the integration of these two processes can overcome the respective disadvantages. This paper reports a hybrid process of a nanosecond pulsed laser and micro EDM for micromachining. A novel hybrid micromachining system that combines the two discrete machining processes is introduced. Then, the feasibility and characteristics of the hybrid machining process are investigated compared to conventional EDM and laser ablation. It is verified experimentally that the machining time can be effectively reduced in both EDM drilling and milling by rapid laser pre-machining prior to micro EDM. Finally, some examples of complicated 3D micro structures fabricated by the hybrid process are shown.

The electrical discharge machining of ceramics

NASA Astrophysics Data System (ADS)

Trueman, Christopher Stuart

This study introduces the concept of developing a novel and rapid rough-machining methodology for spark eroding suitable ceramic compositions based on material removal by thermal shock induced spalling, as opposed to conventional melting mechanisms. The principal materials studied were TiB2 dispersion toughened SiC, and Syalon501 - a commercially available TiN toughened sialon ceramic specifically designed for spark erosion. A preliminary study was also carried out on a range of SiC:B4C composites. Machinability and material performance were assessed where appropriate using machining parameters, material removal rate tests, surface analysis, four-point flexure testing, and tool wear. The machining technologies which supported the different mechanisms of material removal were identified, and each mechanism investigated by analysis of captured debris and sectioning of the workpiece. The SiC:B4C composites were found to be spark erodible only with B4C levels above 50% (by mass), and material removal was found to be solely by melting mechanisms. A SiC:TiB2 composition with the addition of 26.5% TiB2 (by mass) was found to be more machinable than a composition with 10% TiB2 (by mass), achieving greater material removal rates owing to its higher electrical conductivity. An in-depth study of the latter (10%TiB2) SiC composition and Syalon501 revealed surprisingly robust materials. Under conventional sparking (no arcing), material was removed by combined dissociation, melting and evaporation. Syalon501 in particular behaved with a high degree of predictability, and neither material could be made to spall under conventional sparking. However, by imposing conditions which deliberately induced arcing, both compositions spalled large flakes of material (up to several hundred microns across) in the localised region of the arc-strike. Examination of captured debris and fracture facets of the spall interface revealed the existence of small "penny cracks", each characterised by the presence of a dispersed particle (of greater thermal expansion) at its centre acting as a stress- raising nucleation point under the intense thermal loading of arcing. Sub-surface cracks in the near horizontal and near-vertical planes were discovered in line with published models based on the application of a hot-spot to brittle material, and evidence of discrete crack propagation under the thermally punctuated pulses of successive sparking was identified. Similar sub-surface cracking was also confirmed in Syalon501 which had been subjected to arcing. Sectioning of the workpiece revealed shallow sub-surface cracks which followed the profile of the machined surface in the near-horizontal plane, and which often limited the extent of near-vertical cracking to the layer of material above the crack, thereby offering the potential for a reliable and fast "planning" technique in which material would be removed in shallow layers. This research has shown that the possibility exists for increased material removal rates and improved process efficiency under a spalling-based machining regime, in which layers of material are released by thermal-shock induced fracture caused by arcing. The viability of developing a new rough-machining technology for ceramics, in which material is "planed" away prior to fine surface finishing by conventional spark erosion has, therefore, been successfully demonstrated.

High-throughput state-machine replication using software transactional memory.

PubMed

Zhao, Wenbing; Yang, William; Zhang, Honglei; Yang, Jack; Luo, Xiong; Zhu, Yueqin; Yang, Mary; Luo, Chaomin

2016-11-01

State-machine replication is a common way of constructing general purpose fault tolerance systems. To ensure replica consistency, requests must be executed sequentially according to some total order at all non-faulty replicas. Unfortunately, this could severely limit the system throughput. This issue has been partially addressed by identifying non-conflicting requests based on application semantics and executing these requests concurrently. However, identifying and tracking non-conflicting requests require intimate knowledge of application design and implementation, and a custom fault tolerance solution developed for one application cannot be easily adopted by other applications. Software transactional memory offers a new way of constructing concurrent programs. In this article, we present the mechanisms needed to retrofit existing concurrency control algorithms designed for software transactional memory for state-machine replication. The main benefit for using software transactional memory in state-machine replication is that general purpose concurrency control mechanisms can be designed without deep knowledge of application semantics. As such, new fault tolerance systems based on state-machine replications with excellent throughput can be easily designed and maintained. In this article, we introduce three different concurrency control mechanisms for state-machine replication using software transactional memory, namely, ordered strong strict two-phase locking, conventional timestamp-based multiversion concurrency control, and speculative timestamp-based multiversion concurrency control. Our experiments show that speculative timestamp-based multiversion concurrency control mechanism has the best performance in all types of workload, the conventional timestamp-based multiversion concurrency control offers the worst performance due to high abort rate in the presence of even moderate contention between transactions. The ordered strong strict two-phase locking mechanism offers the simplest solution with excellent performance in low contention workload, and fairly good performance in high contention workload.

High-throughput state-machine replication using software transactional memory

PubMed Central

Yang, William; Zhang, Honglei; Yang, Jack; Luo, Xiong; Zhu, Yueqin; Yang, Mary; Luo, Chaomin

2017-01-01

State-machine replication is a common way of constructing general purpose fault tolerance systems. To ensure replica consistency, requests must be executed sequentially according to some total order at all non-faulty replicas. Unfortunately, this could severely limit the system throughput. This issue has been partially addressed by identifying non-conflicting requests based on application semantics and executing these requests concurrently. However, identifying and tracking non-conflicting requests require intimate knowledge of application design and implementation, and a custom fault tolerance solution developed for one application cannot be easily adopted by other applications. Software transactional memory offers a new way of constructing concurrent programs. In this article, we present the mechanisms needed to retrofit existing concurrency control algorithms designed for software transactional memory for state-machine replication. The main benefit for using software transactional memory in state-machine replication is that general purpose concurrency control mechanisms can be designed without deep knowledge of application semantics. As such, new fault tolerance systems based on state-machine replications with excellent throughput can be easily designed and maintained. In this article, we introduce three different concurrency control mechanisms for state-machine replication using software transactional memory, namely, ordered strong strict two-phase locking, conventional timestamp-based multiversion concurrency control, and speculative timestamp-based multiversion concurrency control. Our experiments show that speculative timestamp-based multiversion concurrency control mechanism has the best performance in all types of workload, the conventional timestamp-based multiversion concurrency control offers the worst performance due to high abort rate in the presence of even moderate contention between transactions. The ordered strong strict two-phase locking mechanism offers the simplest solution with excellent performance in low contention workload, and fairly good performance in high contention workload. PMID:29075049

Value-Engineering Review for Numerical Control

NASA Technical Reports Server (NTRS)

Warner, J. L.

1984-01-01

Selecting parts for conversion from conventional machining to numerical control, value-engineering review performed for every part to identify potential changes to part design that result in increased production efficiency.

Quantum simulations with noisy quantum computers

NASA Astrophysics Data System (ADS)

Gambetta, Jay

Quantum computing is a new computational paradigm that is expected to lie beyond the standard model of computation. This implies a quantum computer can solve problems that can't be solved by a conventional computer with tractable overhead. To fully harness this power we need a universal fault-tolerant quantum computer. However the overhead in building such a machine is high and a full solution appears to be many years away. Nevertheless, we believe that we can build machines in the near term that cannot be emulated by a conventional computer. It is then interesting to ask what these can be used for. In this talk we will present our advances in simulating complex quantum systems with noisy quantum computers. We will show experimental implementations of this on some small quantum computers.

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

PubMed

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

1998-04-01

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

A simplified concept for controlling oxygen mixtures in the anaesthetic machine--better, cheaper and more user-friendly?

PubMed

Berge, J A; Gramstad, L; Grimnes, S

1995-05-01

Modern anaesthetic machines are equipped with several safety components to prevent delivery of hypoxic mixtures. However, such a technical development has increased the complexity of the equipment. We report a reconstructed anaesthetic machine in which a paramagnetic oxygen analyzer has provided the means to simplify the apparatus. The new machine is devoid of several components conventionally included to prevent hypoxic mixtures: oxygen failure protection device, reservoir O2 alarm, N2O/air selector, and proportioning system for oxygen/nitrous oxide delivery. These devices have been replaced by a simple safety system using a paramagnetic oxygen analyzer at the common gas outlet, which in a feed-back system cuts off the supply of nitrous oxide whenever the oxygen concentration falls below 25%. The simplified construction of the anaesthetic machine has important consequences for safety, cost and user-friendliness. Reducing the complexity of the construction also simplifies the pre-use checkout procedure, and an efficient 5-point check list is presented for the new machine.

Machine learning and data science in soft materials engineering

NASA Astrophysics Data System (ADS)

Ferguson, Andrew L.

2018-01-01

In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by ‘de-jargonizing’ data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

Machine learning and data science in soft materials engineering.

PubMed

Ferguson, Andrew L

2018-01-31

In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by 'de-jargonizing' data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

Development of hand rehabilitation system for paralysis patient - universal design using wire-driven mechanism.

PubMed

Yamaura, Hiroshi; Matsushita, Kojiro; Kato, Ryu; Yokoi, Hiroshi

2009-01-01

We have developed a hand rehabilitation system for patients suffering from paralysis or contracture. It consists of two components: a hand rehabilitation machine, which moves human finger joints with motors, and a data glove, which provides control of the movement of finger joints attached to the rehabilitation machine. The machine is based on the arm structure type of hand rehabilitation machine; a motor indirectly moves a finger joint via a closed four-link mechanism. We employ a wire-driven mechanism and develop a compact design that can control all three joints (i.e., PIP, DIP and MP ) of a finger and that offers a wider range of joint motion than conventional systems. Furthermore, we demonstrate the hand rehabilitation process, finger joints of the left hand attached to the machine are controlled by the finger joints of the right hand wearing the data glove.

High-Strength Undiffused Brushless (HSUB) Machine

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

Hsu, John S; Lee, Seong T; Tolbert, Leon M

2008-01-01

This paper introduces a new high-strength undiffused brushless machine that transfers the stationary excitation magnetomotive force to the rotor without any brushes. For a conventional permanent magnet (PM) machine, the air-gap flux density cannot be enhanced effectively but can be weakened. In the new machine, both the stationary excitation coil and the PM in the rotor produce an enhanced air-gap flux. The PM in the rotor prevents magnetic-flux diffusion between the poles and guides the reluctance flux path. The pole flux density in the air gap can be much higher than what the PM alone can produce. A high-strength machinemore » is thus obtained. The air-gap flux density can be weakened through the stationary excitation winding. This type of machine is particularly suitable for electric and hybrid-electric vehicle applications. Patents of this new technology are either granted or pending.« less

[Cyclic fatigue of Vita mark II machinable ceramics under Hertzian's contact].

PubMed

Liu, Wei-Cai; Zhang, Zhi-Shen; Huang, Cheng-Min; Chao, Yong-Lie; Wan, Qian-Bing

2006-08-01

To investigate the cyclic fatigue modes of Vita mark II machinable ceramics under Hertzian's contact. Hertzian's contact technique (WC spheres r = 3.18 mm) was used to investigate the cyclic fatigue of Vita mark II machinable ceramic. All specimens were fatigued by cyclic loading in moist environment, furthermore, surviving strength was examined by three point test and morphology damage observation. In homogeneous Vita mark II machinable ceramics, two fatigue damage modes existed after cyclic loading with spheres under moist environment, including conventional tensile-driven cone cracking (brittle mode) and shear-driven microdamage accumulation (quasi-plastic mode). The latter generated radial cracks and deeply penetrating secondary cone crack. Initial strength degradation were caused by the cone cracks, subsequent and much more deleterious loss was caused by radial cracks. Cyclic fatigue modes of Vita mark II machinable ceramics includes brittle and quasi-plastic mode.

Device for Extracting Flavors and Fragrances

NASA Technical Reports Server (NTRS)

Chang, F. R.

1986-01-01

Machine for making coffee and tea in weightless environment may prove even more valuable on Earth as general extraction apparatus. Zero-gravity beverage maker uses piston instead of gravity to move hot water and beverage from one chamber to other and dispense beverage. Machine functions like conventional coffeemaker during part of operating cycle and includes additional features that enable operation not only in zero gravity but also extraction under pressure in presence or absence of gravity.

Reversible micromachining locator

DOEpatents

Salzer, Leander J.; Foreman, Larry R.

1999-01-01

This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved.

LHCb experience with running jobs in virtual machines

NASA Astrophysics Data System (ADS)

McNab, A.; Stagni, F.; Luzzi, C.

2015-12-01

The LHCb experiment has been running production jobs in virtual machines since 2013 as part of its DIRAC-based infrastructure. We describe the architecture of these virtual machines and the steps taken to replicate the WLCG worker node environment expected by user and production jobs. This relies on the uCernVM system for providing root images for virtual machines. We use the CernVM-FS distributed filesystem to supply the root partition files, the LHCb software stack, and the bootstrapping scripts necessary to configure the virtual machines for us. Using this approach, we have been able to minimise the amount of contextualisation which must be provided by the virtual machine managers. We explain the process by which the virtual machine is able to receive payload jobs submitted to DIRAC by users and production managers, and how this differs from payloads executed within conventional DIRAC pilot jobs on batch queue based sites. We describe our operational experiences in running production on VM based sites managed using Vcycle/OpenStack, Vac, and HTCondor Vacuum. Finally we show how our use of these resources is monitored using Ganglia and DIRAC.

Personal manufacturing systems

NASA Astrophysics Data System (ADS)

Bailey, P.

1992-04-01

Personal Manufacturing Systems are the missing link in the automation of the design-to- manufacture process. A PMS will act as a CAD peripheral, closing the loop around the designer enabling him to directly produce models, short production runs or soft tooling with as little fuss as he might otherwise plot a drawing. Whereas conventional 5-axis CNC machines are based on orthogonal axes and simple incremental movements, the PMS is based on a geodetic structure and complex co-ordinated 'spline' movements. The software employs a novel 3D pixel technique for give itself 'spatial awareness' and an expert system to determine the optimum machining conditions. A completely automatic machining strategy can then be determined.

Applications of Support Vector Machines In Chemo And Bioinformatics

NASA Astrophysics Data System (ADS)

Jayaraman, V. K.; Sundararajan, V.

2010-10-01

Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.

Surgical Tooth Implants, Combat and Field.

DTIC Science & Technology

1979-12-01

conventional dental materials, usually gold. Roots are produced by grinding bisque fired alumina stock on a computer controlled milling machine. This...post and core and crown) are conventional dental materials, usually gold. Roots are produced by grinding bisque fired alumina stock on a computer...of dental implants have evolved. These devices are designed to be rigidly affixed by bone ingrowth and provide minimization of stress usually by

Stability Analysis of Radial Turning Process for Superalloys

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

A novel single-phase flux-switching permanent magnet linear generator used for free-piston Stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Ping; Sui, Yi; Tong, Chengde; Bai, Jingang; Yu, Bin; Lin, Fei

2014-05-01

This paper investigates a novel single-phase flux-switching permanent-magnet (PM) linear machine used for free-piston Stirling engines. The machine topology and operating principle are studied. A flux-switching PM linear machine is designed based on the quasi-sinusoidal speed characteristic of the resonant piston. Considering the performance of back electromotive force and thrust capability, some leading structural parameters, including the air gap length, the PM thickness, the ratio of the outer radius of mover to that of stator, the mover tooth width, the stator tooth width, etc., are optimized by finite element analysis. Compared with conventional three-phase moving-magnet linear machine, the proposed single-phase flux-switching topology shows advantages in less PM use, lighter mover, and higher volume power density.

A Novel Transverse Flux Machine for Vehicle Traction Applications

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

Wan, Zhao; Ahmed, Adeeb; Husain, Iqbal

2015-10-05

A novel transverse flux machine topology for electric vehicle traction application using ferrite magnets is presented in this paper. The proposed transverse flux topology utilizes novel magnet arrangements in the rotor that are similar to Halbach-array to boost flux linkage; on the stator side, cores are alternately arranged around a pair of ring windings in each phase to make use of the entire rotor flux that eliminates end windings. Analytical design considerations and finite element methods are used for an optimized design of a scooter in-wheel motor. Simulation results from Finite Element Analysis (FEA) show the motor achieved comparable torquemore » density to conventional rare-earth permanent magnet machines. This machine is a viable candidate for direct drive applications with low cost and high torque density.« less

Machine learning and radiology.

PubMed

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.

Stereotactic radiosurgery - CyberKnife

MedlinePlus

... slides into a machine that delivers radiation. A robotic arm controlled by a computer moves around you. ... people who are too high risk for conventional surgery. This may be due to age or other ...

Measured impacts of high efficiency domestic clothes washers in a community

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

Tomlinson, J.; Rizy, T.

1998-07-01

The US market for domestic clothes washers is currently dominated by conventional vertical-axis washers that typically require approximately 40 gallons of water for each wash load. Although the current market for high efficiency clothes washers that use much less water and energy is quite small, it is growing slowly as manufacturers make machines based on tumble action, horizontal-axis designs available and as information about the performance and benefits of such machines is developed and made available to consumers. To help build awareness of these benefits and to accelerate markets for high efficiency washers, the Department of Energy (DOE), under itsmore » ENERGY STAR{reg_sign} Program and in cooperation with a major manufacturers of high efficiency washers, conducted a field evaluation of high efficiency washers using Bern, Kansas as a test bed. Baseline washing machine performance data as well as consumer washing behavior were obtained from data collected on the existing machines of more than 100 participants in this instrumented study. Following a 2-month initial study period, all conventional machines were replaced by high efficiency, tumble-action washers, and the study continued for 3 months. Based on measured data from over 20,000 loads of laundry, the impact of the washer replacement on (1) individual customers` energy and water consumption, (2) customers` laundry habits and perceptions, and (3) the community`s water supply and waste water systems were determined. The study, its findings, and how information from the experiment was used to improve national awareness of high efficiency clothes washer benefits are described in this paper.« less

Training Scalable Restricted Boltzmann Machines Using a Quantum Annealer

NASA Astrophysics Data System (ADS)

Kumar, V.; Bass, G.; Dulny, J., III

2016-12-01

Machine learning and the optimization involved therein is of critical importance for commercial and military applications. Due to the computational complexity of many-variable optimization, the conventional approach is to employ meta-heuristic techniques to find suboptimal solutions. Quantum Annealing (QA) hardware offers a completely novel approach with the potential to obtain significantly better solutions with large speed-ups compared to traditional computing. In this presentation, we describe our development of new machine learning algorithms tailored for QA hardware. We are training restricted Boltzmann machines (RBMs) using QA hardware on large, high-dimensional commercial datasets. Traditional optimization heuristics such as contrastive divergence and other closely related techniques are slow to converge, especially on large datasets. Recent studies have indicated that QA hardware when used as a sampler provides better training performance compared to conventional approaches. Most of these studies have been limited to moderately-sized datasets due to the hardware restrictions imposed by exisitng QA devices, which make it difficult to solve real-world problems at scale. In this work we develop novel strategies to circumvent this issue. We discuss scale-up techniques such as enhanced embedding and partitioned RBMs which allow large commercial datasets to be learned using QA hardware. We present our initial results obtained by training an RBM as an autoencoder on an image dataset. The results obtained so far indicate that the convergence rates can be improved significantly by increasing RBM network connectivity. These ideas can be readily applied to generalized Boltzmann machines and we are currently investigating this in an ongoing project.

Lathe tool bit and holder for machining fiberglass materials

NASA Technical Reports Server (NTRS)

Winn, L. E. (Inventor)

1972-01-01

A lathe tool and holder combination for machining resin impregnated fiberglass cloth laminates is described. The tool holder and tool bit combination is designed to accommodate a conventional carbide-tipped, round shank router bit as the cutting medium, and provides an infinite number of cutting angles in order to produce a true and smooth surface in the fiberglass material workpiece with every pass of the tool bit. The technique utilizes damaged router bits which ordinarily would be discarded.

Influence of "in series" elastic resistance on muscular performance during a biceps-curl set on the cable machine.

PubMed

García-López, David; Herrero, Azael J; González-Calvo, Gustavo; Rhea, Matthew R; Marín, Pedro J

2010-09-01

This study aimed to investigate the role of elastic resistance (ER) applied "in series" to a pulley-cable (PC) machine on the number of repetitions performed, kinematics parameters, and perceived exertion during a biceps-curl set to failure with a submaximal load (70% of the 1 repetition maximum). Twenty-one undergraduate students (17 men and 4 women) performed, on 2 different days, 1 biceps-curl set on the PC machine. Subjects were randomly assigned to complete 2 experimental conditions in a cross-over fashion: conventional PC mode or ER + PC mode. Results indicate ER applied "in series" to a PC machine significantly reduces (p < 0.05) the maximal number of repetitions and results in a smooth and consistent decline in mean acceleration throughout the set, in comparison to the conventional PC mode. Although no significant differences were found concerning intrarepetition kinematics, the ER trended to reduce (18.6%) the peak acceleration of the load. With a more uniformly distributed external resistance, a greater average muscle tension could have been achieved throughout the range of movement, leading to greater fatigue that could explain the lower number of maximal repetitions achieved. The application of force in a smooth, consistent fashion during each repetition of an exercise, while avoiding active deceleration, is expected to enhance the benefits of the resistance exercise, especially for those seeking greater increases in muscular hypertrophy.

AE Monitoring of Diamond Turned Rapidly Soldified Aluminium 443

NASA Astrophysics Data System (ADS)

Onwuka, G.; Abou-El-Hossein, K.; Mkoko, Z.

2017-05-01

The fast replacement of conventional aluminium with rapidly solidified aluminium alloys has become a noticeable trend in the current manufacturing industries involved in the production of optics and optical molding inserts. This is as a result of the improved performance and durability of rapidly solidified aluminium alloys when compared to conventional aluminium. Melt spinning process is vital for manufacturing rapidly solidified aluminium alloys like RSA 905, RSA 6061 and RSA 443 which are common in the industries today. RSA 443 is a newly developed alloy with few research findings and huge research potential. There is no available literature focused on monitoring the machining of RSA 443 alloys. In this research, Acoustic Emission sensing technique was applied to monitor the single point diamond turning of RSA 443 on an ultrahigh precision lathe machine. The machining process was carried out after careful selection of feed, speed and depths of cut. The monitoring process was achieved with a high sampling data acquisition system using different tools while concurrent measurement of the surface roughness and tool wear were initiated after covering a total feed distance of 13km. An increasing trend of raw AE spikes and peak to peak signal were observed with an increase in the surface roughness and tool wear values. Hence, acoustic emission sensing technique proves to be an effective monitoring method for the machining of RSA 443 alloy.

Rapid Prototyping and the Human Factors Engineering Process

DTIC Science & Technology

2016-08-29

8217 without the effort and cost associated with conventional man -in-the-loop simulation. Advocates suggest that rapid prototyping is compatible with...use should be made of man -in-the loop simulation to supplement those analyses, but that such simulation is expensive and time consuming, precluding...conventional man -in-the- loop simulation. Rapid prototyping involves the construction and use of an executable model of a human-machine interface

Diamond Turning Of Infra-Red Components

NASA Astrophysics Data System (ADS)

Hodgson, B.; Lettington, A. H.; Stillwell, P. F. T. C.

1986-05-01

Single point diamond machining of infra-red optical components such as aluminium mirrors, germanium lenses and zinc sulphide domes is potentially the most cost effective method for their manufacture since components may be machined from the blanks to a high surface finish, requiring no subsequent polishing, in a few minutes. Machines for the production of flat surfaces are well established. Diamond turning lathes for curved surfaces however require a high capital investment which can be justified only for research purposes or high volume production. The present paper describes the development of a low cost production machine based on a Bryant Symons diamond turning lathe which is able to machine spherical components to the required form and finish. It employs two horizontal spindles one for the workpiece the other for the tool. The machined radius of curvature is set by the alignment of the axes and the radius of the tool motion, as in conventional generation. The diamond tool is always normal to the workpiece and does not need to be accurately profiled. There are two variants of this basic machine. For machining hemispherical domes the axes are at right angles while for lenses with positive or negative curvature these axes are adjustable. An aspherical machine is under development, based on the all mechanical spherical machine, but in which a ± 2 mm aspherecity may be imposed on the best fit sphere by moving the work spindle under numerical control.

Novel Transverse Flux Machine for Vehicle Traction Applications: Preprint

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

Wan, Z.; Ahmed, A.; Husain, I.

2015-04-02

A novel transverse flux machine topology for electric vehicle traction applications using ferrite magnets is presented in this paper. The proposed transverse flux topology utilizes novel magnet arrangements in the rotor that are similar to the Halbach array to boost flux linkage; on the stator side, cores are alternately arranged around a pair of ring windings in each phase to make use of the entire rotor flux that eliminates end windings. Analytical design considerations and finite-element methods are used for an optimized design of a scooter in-wheel motor. Simulation results from finite element analysis (FEA) show that the motor achievedmore » comparable torque density to conventional rare-earth permanent magnet (PM) machines. This machine is a viable candidate for direct-drive applications with low cost and high torque density.« less

Machine learning phases of matter

NASA Astrophysics Data System (ADS)

Carrasquilla, Juan; Melko, Roger G.

2017-02-01

Condensed-matter physics is the study of the collective behaviour of infinitely complex assemblies of electrons, nuclei, magnetic moments, atoms or qubits. This complexity is reflected in the size of the state space, which grows exponentially with the number of particles, reminiscent of the `curse of dimensionality' commonly encountered in machine learning. Despite this curse, the machine learning community has developed techniques with remarkable abilities to recognize, classify, and characterize complex sets of data. Here, we show that modern machine learning architectures, such as fully connected and convolutional neural networks, can identify phases and phase transitions in a variety of condensed-matter Hamiltonians. Readily programmable through modern software libraries, neural networks can be trained to detect multiple types of order parameter, as well as highly non-trivial states with no conventional order, directly from raw state configurations sampled with Monte Carlo.

Disc-geometry homopolar synchronous machine

NASA Astrophysics Data System (ADS)

Evans, P. D.; Eastham, J. F.

1980-09-01

Results of an experimental and theoretical investigation of a disc-geometry homopolar synchronous machine with field excitation on the primary side are presented. The unlaminated mild-steel rotor contains no windings and is brushless. The prototype machine produces approximately 7.5 kW of mechanical output at 3000 rev/min, with a product of power factor and efficiency greater than 0.7. The construction of the stator core is unusual and incorporates both laminated and unlaminated portions. The magnetic circuit is also arranged to minimize the axial force between the stator and rotor. A novel rotor design which achieves a reduced quadrature-axis reactance is shown experimentally to be superior to the conventional homopolar rotor.

Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination

NASA Technical Reports Server (NTRS)

Zenowich, Brian; Crowell, Adam; Townsend, William T.

2013-01-01

The design of machines that rely on arrays of servomotors such as robotic arms, orbital platforms, and combinations of both, imposes a heavy computational burden to coordinate their actions to perform coherent tasks. For example, the robotic equivalent of a person tracing a straight line in space requires enormously complex kinematics calculations, and complexity increases with the number of servo nodes. A new high-level architecture for coordinated servo-machine control enables a practical, distributed transputer alternative to conventional central processor electronics. The solution is inherently scalable, dramatically reduces bulkiness and number of conductor runs throughout the machine, requires only a fraction of the power, and is designed for cooling in a vacuum.

Factors Governing Surface Form Accuracy In Diamond Machined Components

NASA Astrophysics Data System (ADS)

Myler, J. K.; Page, D. A.

1988-10-01

Manufacturing methods for diamond machined optical surfaces, for application at infrared wavelengths, require that a new set of criteria must be recognised for the specification of surface form. Appropriate surface form parameters are discussed with particular reference to an XY cartesian geometry CNC machine. Methods for reducing surface form errors in diamond machining are discussed for certain areas such as tool wear, tool centring, and the fixturing of the workpiece. Examples of achievable surface form accuracy are presented. Traditionally, optical surfaces have been produced by use of random polishing techniques using polishing compounds and lapping tools. For lens manufacture, the simplest surface which could be created corresponded to a sphere. The sphere is a natural outcome of a random grinding and polishing process. The measurement of the surface form accuracy would most commonly be performed using a contact test gauge plate, polished to a sphere of known radius of curvature. QA would simply be achieved using a diffuse monochromatic source and looking for residual deviations between the polished surface and the test plate. The specifications governing the manufacture of surfaces using these techniques would call for the accuracy to which the generated surface should match the test plate as defined by a spherical deviations from the required curvature and a non spherical astigmatic error. Consequently, optical design software has tolerancing routines which specifically allow the designer to assess the influence of spherical error and astigmatic error on the optical performance. The creation of general aspheric surfaces is not so straightforward using conventional polishing techniques since the surface profile is non spherical and a good approximation to a power series. For infra red applications (X = 8-12p,m) numerically controlled single point diamond turning is an alternative manufacturing technology capable of creating aspheric profiles as well as simple spheres. It is important however to realise that a diamond turning process will possess a new set of criteria which limit the accuracy of the surface profile created corresponding to a completely new set of specifications. The most important factors are:- tool centring accuracy, surface waviness, conical form error, and other rotationally symmetric non spherical errors. The fixturing of the workpiece is very different from that of a conventional lap, since in many cases the diamond machine resembles a conventional lathe geometry where the workpiece rotates at a few thousand R.P.M. Substrates must be held rigidly for rotation at such speeds as compared with more delicate mounting methods for conventional laps. Consequently the workpiece may suffer from other forms of deformation which are non-rotationally symmetric due to mounting stresses (static deformation) and stresses induced at the speed of rotation (dynamic deformation). The magnitude of each of these contributions to overall form error will be a function of the type of machine, the material, substrate, and testing design. The following sections describe each of these effects in more detail based on experience obtained on a Pneumo Precision MSG325 XY CNC machine. Certain in-process measurement techniques have been devised to minimise and quantify each contribution.

MRR and TWR evaluation on electrical discharge machining of Ti-6Al-4V using tungsten : copper composite electrode

NASA Astrophysics Data System (ADS)

Prasanna, J.; Rajamanickam, S.; Amith Kumar, O.; Karthick Raj, G.; Sathya Narayanan, P. V. V.

2017-05-01

In this paper Ti-6Al-4V used as workpiece material and it is keenly seen in variety of field including medical, chemical, marine, automotive, aerospace, aviation, electronic industries, nuclear reactor, consumer products etc., The conventional machining of Ti-6Al-4V is very difficult due to its distinctive properties. The Electrical Discharge Machining (EDM) is right choice of machining this material. The tungsten copper composite material is employed as tool material. The gap voltage, peak current, pulse on time and duty factor is considered as the machining parameter to analyze the machining characteristics Material Removal Rate (MRR) and Tool Wear Rate (TWR). The Taguchi method is provided to work for finding the significant parameter of EDM. It is found that for MRR significant parameters rated in the following order Gap Voltage, Pulse On-Time, Peak Current and Duty Factor. On the other hand for TWR significant parameters are listed in line of Gap Voltage, Duty Factor, Peak Current and Pulse On-Time.

A micro-machined source transducer for a parametric array in air.

PubMed

Lee, Haksue; Kang, Daesil; Moon, Wonkyu

2009-04-01

Parametric array applications in air, such as highly directional parametric loudspeaker systems, usually rely on large radiators to generate the high-intensity primary beams required for nonlinear interactions. However, a conventional transducer, as a primary wave projector, requires a great deal of electrical power because its electroacoustic efficiency is very low due to the large characteristic mechanical impedance in air. The feasibility of a micro-machined ultrasonic transducer as an efficient finite-amplitude wave projector was studied. A piezoelectric micro-machined ultrasonic transducer array consisting of lead zirconate titanate uni-morph elements was designed and fabricated for this purpose. Theoretical and experimental evaluations showed that a micro-machined ultrasonic transducer array can be used as an efficient source transducer for a parametric array in air. The beam patterns and propagation curves of the difference frequency wave and the primary wave generated by the micro-machined ultrasonic transducer array were measured. Although the theoretical results were based on ideal parametric array models, the theoretical data explained the experimental results reasonably well. These experiments demonstrated the potential of micro-machined primary wave projector.

Cost saving synergistic shaft seal

NASA Technical Reports Server (NTRS)

Ludwig, L. P.; Strom, T. N.

1976-01-01

Segmented carbon rings, used to replace elastomeric seal lip, provide resistance to high temperatures generated in lubricating film. Machining and close manufacturing tolerances of conventional segmented seal are avoided by mounting segmented rings in elastomeric flex section.

Pavement edge treatment.

DOT National Transportation Integrated Search

2013-01-01

Four projects were built over two construction seasons using special devices attached to the paving machine that produces a 30 slope on the outside pavement edge instead of the near vertical drop-off common with conventional paving equipment. This ...

Rock sampling. [method for controlling particle size distribution

NASA Technical Reports Server (NTRS)

Blum, P. (Inventor)

1971-01-01

A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.

Effect of magnetic polarity on surface roughness during magnetic field assisted EDM of tool steel

NASA Astrophysics Data System (ADS)

Efendee, A. M.; Saifuldin, M.; Gebremariam, MA; Azhari, A.

2018-04-01

Electrical discharge machining (EDM) is one of the non-traditional machining techniques where the process offers wide range of parameters manipulation and machining applications. However, surface roughness, material removal rate, electrode wear and operation costs were among the topmost issue within this technique. Alteration of magnetic device around machining area offers exciting output to be investigated and the effects of magnetic polarity on EDM remain unacquainted. The aim of this research is to investigate the effect of magnetic polarity on surface roughness during magnetic field assisted electrical discharge machining (MFAEDM) on tool steel material (AISI 420 mod.) using graphite electrode. A Magnet with a force of 18 Tesla was applied to the EDM process at selected parameters. The sparks under magnetic field assisted EDM produced better surface finish than the normal conventional EDM process. At the presence of high magnetic field, the spark produced was squeezed and discharge craters generated on the machined surface was tiny and shallow. Correct magnetic polarity combination of MFAEDM process is highly useful to attain a high efficiency machining and improved quality of surface finish to meet the demand of modern industrial applications.

The machinability of cast titanium and Ti-6Al-4V.

PubMed

Ohkubo, C; Watanabe, I; Ford, J P; Nakajima, H; Hosoi, T; Okabe, T

2000-02-01

This study investigated the machinability (ease of metal removal) of commercially pure (CP) titanium and Ti-6Al-4V alloy. Both CP Ti and Ti-6Al-4V were cast into magnesia molds. Two types of specimens (with alpha-case and without alpha-case) were made for CP Ti and Ti-6Al-4V. Machinability (n = 5) was evaluated as volume loss (mm3) by cutting/grinding the 3.0 mm surface using fissure burs and silicon carbide (SiC) under two machining conditions: (1) two machining forces (100 or 300 gf) at two rotational speeds (15000 or 30000 rpm) for 1 min, and (2) constant machining force of 100 gf and rotational speed of 15000 rpm for 1, 2, 5, 10, and 30 min. As controls, conventionally cast Co-Cr and Type IV gold alloys were evaluated in the same manner as the titanium. When fissure burs were used, there was a significant difference in the machinability between CP titanium with alpha-case and without alpha-case. On the other hand, there was no appreciable difference in the amount of metal removed for each tested metal when using the SiC points.

Reversible micromachining locator

DOEpatents

Salzer, L.J.; Foreman, L.R.

1999-08-31

This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved. 7 figs.

Development of plasma chemical vaporization machining

NASA Astrophysics Data System (ADS)

Mori, Yuzo; Yamauchi, Kazuto; Yamamura, Kazuya; Sano, Yasuhisa

2000-12-01

Conventional machining processes, such as turning, grinding, or lapping are still applied for many materials including functional ones. But those processes are accompanied with the formation of a deformed layer, so that machined surfaces cannot perform their original functions. In order to avoid such points, plasma chemical vaporization machining (CVM) has been developed. Plasma CVM is a chemical machining method using neutral radicals, which are generated by the atmospheric pressure plasma. By using a rotary electrode for generation of plasma, a high density of neutral radicals was formed, and we succeeded in obtaining high removal rate of several microns to several hundred microns per minute for various functional materials such as fused silica, single crystal silicon, molybdenum, tungsten, silicon carbide, and diamond. Especially, a high removal rate equal to lapping in the mechanical machining of fused silica and silicon was realized. 1.4 nm (p-v) was obtained as a surface roughness in the case of machining a silicon wafer. The defect density of a silicon wafer surface polished by various machining method was evaluated by the surface photo voltage spectroscopy. As a result, the defect density of the surface machined by plasma CVM was under 1/100 in comparison with the surface machined by mechanical polishing and argon ion sputtering, and very low defect density which was equivalent to the chemical etched surface was realized. A numerically controlled CVM machine for x-ray mirror fabrication is detailed in the accompanying article in this issue.

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

NASA Astrophysics Data System (ADS)

Schopf, C.; Rascher, R.

2016-11-01

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

A modular and cost-effective superconducting generator design for offshore wind turbines

NASA Astrophysics Data System (ADS)

Keysan, Ozan; Mueller, Markus

2015-03-01

Superconducting generators have the potential to reduce the tower head mass for large (∼10 MW) offshore wind turbines. However, a high temperature superconductor generator should be as reliable as conventional generators for successful entry into the market. Most of the proposed designs use the superconducting synchronous generator concept, which has a higher cost than conventional generators and suffers from reliability issues. In this paper, a novel claw pole type of superconducting machine is presented. The design has a stationary superconducting field winding, which simplifies the design and increases the reliability. The machine can be operated in independent modules; thus even if one of the sections fails, the rest can operate until the next planned maintenance. Another advantage of the design is the very low superconducting wire requirement; a 10 MW, 10 rpm design is presented which uses 13 km of MgB2 wire at 30 K. The outer diameter of the machine is 6.63 m and it weighs 184 tonnes including the structural mass. The design is thought to be a good candidate for entering the renewable energy market, with its low cost and robust structure.

Plastic superconductor bearings any size-any shape: 77 K and up

NASA Technical Reports Server (NTRS)

Reick, Franklin G.

1991-01-01

'Friction free' bearings at 77 K or higher are possible using the high T(sub c) copper oxide ceramic superconductors. The conventional method for making such bearings is to use a sintered ceramic monolith. This puts great restraints on size, shape, and postforming machining. The material is hard and abrasive. It is possible to grind up ceramic superconductors and suspend the granules in a suitable matrix. Mechanical properties improve and are largely dependent on the binder. The Meissner effect is confined to individual grains containing electron vortices. Tracks, rails, levitation areas, and bearings can be made this way with conventional plastic molding and extruding machines or by painting. The parts are easily machined. The sacrifice is in bulk electrical conductivity. A percolating wick feed for LN2 is used to cool remote superconductors and large areas quite effectively. A hollow spheroid or cylinder of superconductor material is molded with the internal surfaces shielded by the Meissner effect. It can be thought of as the DC magnetic analog of the Faraday cage and the inside is the 'Meissner space'. It is selective. The AC fields are transmitted with minor attenuation. Particle size and distribution have a profound effect on final magnetic and electrical characteristics.

Combining machine learning and matching techniques to improve causal inference in program evaluation.

PubMed

Linden, Ariel; Yarnold, Paul R

2016-12-01

Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balance is assessed before estimating treatment effects. This paper introduces a novel analytic framework utilizing a machine learning algorithm called optimal discriminant analysis (ODA) for assessing covariate balance and estimating treatment effects, once the matching strategy has been implemented. This framework holds several key advantages over the conventional approach: application to any variable metric and number of groups; insensitivity to skewed data or outliers; and use of accuracy measures applicable to all prognostic analyses. Moreover, ODA accepts analytic weights, thereby extending the methodology to any study design where weights are used for covariate adjustment or more precise (differential) outcome measurement. One-to-one matching on the propensity score was used as the matching strategy. Covariate balance was assessed using standardized difference in means (conventional approach) and measures of classification accuracy (ODA). Treatment effects were estimated using ordinary least squares regression and ODA. Using empirical data, ODA produced results highly consistent with those obtained via the conventional methodology for assessing covariate balance and estimating treatment effects. When ODA is combined with matching techniques within a treatment effects framework, the results are consistent with conventional approaches. However, given that it provides additional dimensions and robustness to the analysis versus what can currently be achieved using conventional approaches, ODA offers an appealing alternative. © 2016 John Wiley & Sons, Ltd.

The Effect of Surface Irregularities on Wing Drag. I. Rivets and Spot Welds. 1; Rivets and Spot Welds

NASA Technical Reports Server (NTRS)

Hood, Manley J.

1938-01-01

Tests have been conducted in the NACA 8-foot high-speed wind tunnel to determine the effect of exposed rivet heads and spot welds on wing drag. Most of the tests were made with an airfoil of 5-foot chord. The air speed was varied from 80 to 500 miles per hour and the lift coefficient from 0 to 0.30. The increases in the drag of the 5-foot airfoil varied from 6%, due to countersunk rivets, to 27%, due to 3/32-inch brazier-head rivets, with the rivets in a representative arrangement. The drag increases caused by protruding rivet heads were roughly proportional to the height of the heads. With the front row of rivets well forward, changes in spanwise pitch had negligible effects on drag unless the pitch was more than 2.5% of the chord. Data are presented for evaluating the drag reduction attained by removing rivets from the forward part of the wing surface; for example, it is shown that over 70% of the rivet drag is caused by the rivets on the forward 30% of the airfoil in a typical case.

Machine learning classifiers for glaucoma diagnosis based on classification of retinal nerve fibre layer thickness parameters measured by Stratus OCT.

PubMed

Bizios, Dimitrios; Heijl, Anders; Hougaard, Jesper Leth; Bengtsson, Boel

2010-02-01

To compare the performance of two machine learning classifiers (MLCs), artificial neural networks (ANNs) and support vector machines (SVMs), with input based on retinal nerve fibre layer thickness (RNFLT) measurements by optical coherence tomography (OCT), on the diagnosis of glaucoma, and to assess the effects of different input parameters. We analysed Stratus OCT data from 90 healthy persons and 62 glaucoma patients. Performance of MLCs was compared using conventional OCT RNFLT parameters plus novel parameters such as minimum RNFLT values, 10th and 90th percentiles of measured RNFLT, and transformations of A-scan measurements. For each input parameter and MLC, the area under the receiver operating characteristic curve (AROC) was calculated. There were no statistically significant differences between ANNs and SVMs. The best AROCs for both ANN (0.982, 95%CI: 0.966-0.999) and SVM (0.989, 95% CI: 0.979-1.0) were based on input of transformed A-scan measurements. Our SVM trained on this input performed better than ANNs or SVMs trained on any of the single RNFLT parameters (p < or = 0.038). The performance of ANNs and SVMs trained on minimum thickness values and the 10th and 90th percentiles were at least as good as ANNs and SVMs with input based on the conventional RNFLT parameters. No differences between ANN and SVM were observed in this study. Both MLCs performed very well, with similar diagnostic performance. Input parameters have a larger impact on diagnostic performance than the type of machine classifier. Our results suggest that parameters based on transformed A-scan thickness measurements of the RNFL processed by machine classifiers can improve OCT-based glaucoma diagnosis.

Testing filamentary composites

NASA Technical Reports Server (NTRS)

Dow, N. F.; Rosen, B. W.

1970-01-01

NOL ring split-dee tensile test has the advantages that the specimen is readily fabricated by winding and the test is performed in a conventional testing machine without special fixtures. Strain gages cannot be mounted, however, and substantial bending moments are introduced.

NAVA: Tying In to the Information Machine

ERIC Educational Resources Information Center

McIntyre, Joe

1975-01-01

The article describes the types of memberships and the services (conventions, publications, and workshops) of the National Audio-Visual Association (NAVA), a dealer organization, emphasizing their availability and importance to manufacturers and users of audio-visual equipment. (MS)

DEGAS: Dynamic Exascale Global Address Space Programming Environments

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

Demmel, James

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speedmore » and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.« less

CNN based approach for activity recognition using a wrist-worn accelerometer.

PubMed

Panwar, Madhuri; Dyuthi, S Ram; Chandra Prakash, K; Biswas, Dwaipayan; Acharyya, Amit; Maharatna, Koushik; Gautam, Arvind; Naik, Ganesh R

2017-07-01

In recent years, significant advancements have taken place in human activity recognition using various machine learning approaches. However, feature engineering have dominated conventional methods involving the difficult process of optimal feature selection. This problem has been mitigated by using a novel methodology based on deep learning framework which automatically extracts the useful features and reduces the computational cost. As a proof of concept, we have attempted to design a generalized model for recognition of three fundamental movements of the human forearm performed in daily life where data is collected from four different subjects using a single wrist worn accelerometer sensor. The validation of the proposed model is done with different pre-processing and noisy data condition which is evaluated using three possible methods. The results show that our proposed methodology achieves an average recognition rate of 99.8% as opposed to conventional methods based on K-means clustering, linear discriminant analysis and support vector machine.

Halbach array DC motor/generator

DOEpatents

Merritt, B.T.; Dreifuerst, G.R.; Post, R.F.

1998-01-06

A new configuration of DC motor/generator is based on a Halbach array of permanent magnets. This motor does not use ferrous materials so that the only losses are winding losses and losses due to bearings and windage. An ``inside-out`` design is used as compared to a conventional motor/generator design. The rotating portion, i.e., the rotor, is on the outside of the machine. The stationary portion, i.e., the stator, is formed by the inside of the machine. The rotor contains an array of permanent magnets that provide a uniform field. The windings of the motor are placed in or on the stator. The stator windings are then ``switched`` or ``commutated`` to provide a DC motor/generator much the same as in a conventional DC motor. The commutation can be performed by mechanical means using brushes or by electronic means using switching circuits. The invention is useful in electric vehicles and adjustable speed DC drives. 17 figs.

Halbach array DC motor/generator

DOEpatents

Merritt, Bernard T.; Dreifuerst, Gary R.; Post, Richard F.

1998-01-01

A new configuration of DC motor/generator is based on a Halbach array of permanent magnets. This motor does not use ferrous materials so that the only losses are winding losses and losses due to bearings and windage. An "inside-out" design is used as compared to a conventional motor/generator design. The rotating portion, i.e., the rotor, is on the outside of the machine. The stationary portion, i.e., the stator, is formed by the inside of the machine. The rotor contains an array of permanent magnets that provide a uniform field. The windings of the motor are placed in or on the stator. The stator windings are then "switched" or "commutated" to provide a DC motor/generator much the same as in a conventional DC motor. The commutation can be performed by mechanical means using brushes or by electronic means using switching circuits. The invention is useful in electric vehicles and adjustable speed DC drives.

The Oregon State University wind studies. [economic feasibility of windpowered generators

NASA Technical Reports Server (NTRS)

Wilson, R. E.

1973-01-01

The economic feasibility of commercial use of wind generated power in selected areas of Oregon is assessed. A number of machines for generating power have been examined. These include the Savonius rotor, translators, conventional wind turbines, the circulation controlled rotor and the vertical axis winged turbine. Of these machines, the conventional wind turbine and the vertical axis winged turbine show the greatest promise on the basis of the power developed per unit of rotor blade area. Attention has been focused on the structural and fatigue analysis of rotors since the economics of rotary winged, wind generated power depends upon low cost, long lifetime rotors. Analysis of energy storage systems and tower design has also been undertaken. An economic means of energy storage has not been found to date. Tower design studies have produced cost estimates that are in general agreement with the cost of the updated Putnam 110-foot tower.

A Review on Parametric Analysis of Magnetic Abrasive Machining Process

NASA Astrophysics Data System (ADS)

Khattri, Krishna; Choudhary, Gulshan; Bhuyan, B. K.; Selokar, Ashish

2018-03-01

The magnetic abrasive machining (MAM) process is a highly developed unconventional machining process. It is frequently used in manufacturing industries for nanometer range surface finishing of workpiece with the help of Magnetic abrasive particles (MAPs) and magnetic force applied in the machining zone. It is precise and faster than conventional methods and able to produce defect free finished components. This paper provides a comprehensive review on the recent advancement of MAM process carried out by different researcher till date. The effect of different input parameters such as rotational speed of electromagnet, voltage, magnetic flux density, abrasive particles size and working gap on the performances of Material Removal Rate (MRR) and surface roughness (Ra) have been discussed. On the basis of review, it is observed that the rotational speed of electromagnet, voltage and mesh size of abrasive particles have significant impact on MAM process.

Comparison of peri-implant bone formation around injection-molded and machined surface zirconia implants in rabbit tibiae

PubMed Central

Kim, Hong-Kyun; Woo, Kyung mi; Shon, Won-Jun; Ahn, Jin-Soo; Cha, Seunghee; Park, Young-Seok

2017-01-01

The aim of this study was to compare osseointegration and surface characteristics of zirconia implants made by the powder injection molding (PIM) technique and made by the conventional milling procedure in rabbit tibiae. Surface characteristics of 2 types of implant were evaluated. Sixteeen rabbits received 2 types of external hex implants with similar geometry, machined zirconia implants and PIM zirconia implants, in the tibiae. Removal torque tests and histomorphometric analyses were performed. The roughness of PIM zirconia implants was higher than that of machined zirconia implants. The PIM zirconia implants exhibited significantly higher bone-implant contact and removal torque values than the machined zirconia implants (P < 0.001). The osseointegration of the PIM zirconia implant is promising, and PIM, using the roughened mold etching technique, can produce substantially rough surfaces on zirconia implants. PMID:26235717

Smart Screening System (S3) In Taconite Processing

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

Daryoush Allaei; Ryan Wartman; David Tarnowski

2006-03-01

The conventional screening machines used in processing plants have had undesirable high noise and vibration levels. They also have had unsatisfactorily low screening efficiency, high energy consumption, high maintenance cost, low productivity, and poor worker safety. These conventional vibrating machines have been used in almost every processing plant. Most of the current material separation technology uses heavy and inefficient electric motors with an unbalanced rotating mass to generate the shaking. In addition to being excessively noisy, inefficient, and high-maintenance, these vibrating machines are often the bottleneck in the entire process. Furthermore, these motors, along with the vibrating machines and supportingmore » structure, shake other machines and structures in the vicinity. The latter increases maintenance costs while reducing worker health and safety. The conventional vibrating fine screens at taconite processing plants have had the same problems as those listed above. This has resulted in lower screening efficiency, higher energy and maintenance cost, and lower productivity and workers safety concerns. The focus of this work is on the design of a high performance screening machine suitable for taconite processing plants. SmartScreens{trademark} technology uses miniaturized motors, based on smart materials, to generate the shaking. The underlying technologies are Energy Flow Control{trademark} and Vibration Control by Confinement{trademark}. These concepts are used to direct energy flow and confine energy efficiently and effectively to the screen function. The SmartScreens{trademark} technology addresses problems related to noise and vibration, screening efficiency, productivity, and maintenance cost and worker safety. Successful development of SmartScreens{trademark} technology will bring drastic changes to the screening and physical separation industry. The final designs for key components of the SmartScreens{trademark} have been developed. The key components include smart motor and associated electronics, resonators, and supporting structural elements. It is shown that the smart motors have an acceptable life and performance. Resonator (or motion amplifier) designs are selected based on the final system requirement and vibration characteristics. All the components for a fully functional prototype are fabricated. The development program is on schedule. The last semi-annual report described the completion of the design refinement phase. This phase resulted in a Smart Screen design that meets performance targets both in the dry condition and with taconite slurry flow using PZT motors. This system was successfully demonstrated for the DOE and partner companies at the Coleraine Mineral Research Laboratory in Coleraine, Minnesota. Since then, the fabrication of the dry application prototype (incorporating an electromagnetic drive mechanism and a new deblinding concept) has been completed and successfully tested at QRDC's lab.« less

Combined high vacuum/high frequency fatigue tester

NASA Technical Reports Server (NTRS)

Honeycutt, C. R.; Martin, T. F.

1971-01-01

Apparatus permits application of significantly greater number of cycles or equivalent number of cycles in shorter time than conventional fatigue test machines. Environment eliminates problems associated with high temperature oxidation and with sensitivity of refractory alloy behavior to atmospheric contamination.

Comparison the Marginal and Internal Fit of Metal Copings Cast from Wax Patterns Fabricated by CAD/CAM and Conventional Wax up Techniques.

PubMed

Vojdani, M; Torabi, K; Farjood, E; Khaledi, Aar

2013-09-01

Metal-ceramic crowns are most commonly used as the complete coverage restorations in clinical daily use. Disadvantages of conventional hand-made wax-patterns introduce some alternative ways by means of CAD/CAM technologies. This study compares the marginal and internal fit of copings cast from CAD/CAM and conventional fabricated wax-patterns. Twenty-four standardized brass dies were prepared and randomly divided into 2 groups according to the wax-patterns fabrication method (CAD/CAM technique and conventional method) (n=12). All the wax-patterns were fabricated in a standard fashion by means of contour, thickness and internal relief (M1-M12: representative of CAD/CAM group, C1-C12: representative of conventional group). CAD/CAM milling machine (Cori TEC 340i; imes-icore GmbH, Eiterfeld, Germany) was used to fabricate the CAD/CAM group wax-patterns. The copings cast from 24 wax-patterns were cemented to the corresponding dies. For all the coping-die assemblies cross-sectional technique was used to evaluate the marginal and internal fit at 15 points. The Student's t- test was used for statistical analysis (α=0.05). The overall mean (SD) for absolute marginal discrepancy (AMD) was 254.46 (25.10) um for CAD/CAM group and 88.08(10.67) um for conventional group (control). The overall mean of internal gap total (IGT) was 110.77(5.92) um for CAD/CAM group and 76.90 (10.17) um for conventional group. The Student's t-test revealed significant differences between 2 groups. Marginal and internal gaps were found to be significantly higher at all measured areas in CAD/CAM group than conventional group (p< 0.001). Within limitations of this study, conventional method of wax-pattern fabrication produced copings with significantly better marginal and internal fit than CAD/CAM (machine-milled) technique. All the factors for 2 groups were standardized except wax pattern fabrication technique, therefore, only the conventional group results in copings with clinically acceptable margins of less than 120um.

Comparison the Marginal and Internal Fit of Metal Copings Cast from Wax Patterns Fabricated by CAD/CAM and Conventional Wax up Techniques

PubMed Central

Vojdani, M; Torabi, K; Farjood, E; Khaledi, AAR

2013-01-01

Statement of Problem: Metal-ceramic crowns are most commonly used as the complete coverage restorations in clinical daily use. Disadvantages of conventional hand-made wax-patterns introduce some alternative ways by means of CAD/CAM technologies. Purpose: This study compares the marginal and internal fit of copings cast from CAD/CAM and conventional fabricated wax-patterns. Materials and Method: Twenty-four standardized brass dies were prepared and randomly divided into 2 groups according to the wax-patterns fabrication method (CAD/CAM technique and conventional method) (n=12). All the wax-patterns were fabricated in a standard fashion by means of contour, thickness and internal relief (M1-M12: representative of CAD/CAM group, C1-C12: representative of conventional group). CAD/CAM milling machine (Cori TEC 340i; imes-icore GmbH, Eiterfeld, Germany) was used to fabricate the CAD/CAM group wax-patterns. The copings cast from 24 wax-patterns were cemented to the corresponding dies. For all the coping-die assemblies cross-sectional technique was used to evaluate the marginal and internal fit at 15 points. The Student’s t- test was used for statistical analysis (α=0.05). Results: The overall mean (SD) for absolute marginal discrepancy (AMD) was 254.46 (25.10) um for CAD/CAM group and 88.08(10.67) um for conventional group (control). The overall mean of internal gap total (IGT) was 110.77(5.92) um for CAD/CAM group and 76.90 (10.17) um for conventional group. The Student’s t-test revealed significant differences between 2 groups. Marginal and internal gaps were found to be significantly higher at all measured areas in CAD/CAM group than conventional group (p< 0.001). Conclusion: Within limitations of this study, conventional method of wax-pattern fabrication produced copings with significantly better marginal and internal fit than CAD/CAM (machine-milled) technique. All the factors for 2 groups were standardized except wax pattern fabrication technique, therefore, only the conventional group results in copings with clinically acceptable margins of less than 120um. PMID:24724133

The Value of Data and Metadata Standardization for Interoperability in Giovanni Or: Why Your Product's Metadata Causes Us Headaches!

NASA Technical Reports Server (NTRS)

Smit, Christine; Hegde, Mahabaleshwara; Strub, Richard; Bryant, Keith; Li, Angela; Petrenko, Maksym

2017-01-01

Giovanni is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization.

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

Bates, Robert; McConnell, Elizabeth

Machining methods across many industries generally require multiple operations to machine and process advanced materials, features with micron precision, and complex shapes. The resulting multiple machining platforms can significantly affect manufacturing cycle time and the precision of the final parts, with a resultant increase in cost and energy consumption. Ultrafast lasers represent a transformative and disruptive technology that removes material with micron precision and in a single step manufacturing process. Such precision results from athermal ablation without modification or damage to the remaining material which is the key differentiator between ultrafast laser technologies and traditional laser technologies or mechanical processes.more » Athermal ablation without modification or damage to the material eliminates post-processing or multiple manufacturing steps. Combined with the appropriate technology to control the motion of the work piece, ultrafast lasers are excellent candidates to provide breakthrough machining capability for difficult-to-machine materials. At the project onset in early 2012, the project team recognized that substantial effort was necessary to improve the application of ultrafast laser and precise motion control technologies (for micromachining difficult-to-machine materials) to further the aggregate throughput and yield improvements over conventional machining methods. The project described in this report advanced these leading-edge technologies thru the development and verification of two platforms: a hybrid enhanced laser chassis and a multi-application testbed.« less

Exploring a potential energy surface by machine learning for characterizing atomic transport

NASA Astrophysics Data System (ADS)

Kanamori, Kenta; Toyoura, Kazuaki; Honda, Junya; Hattori, Kazuki; Seko, Atsuto; Karasuyama, Masayuki; Shitara, Kazuki; Shiga, Motoki; Kuwabara, Akihide; Takeuchi, Ichiro

2018-03-01

We propose a machine-learning method for evaluating the potential barrier governing atomic transport based on the preferential selection of dominant points for atomic transport. The proposed method generates numerous random samples of the entire potential energy surface (PES) from a probabilistic Gaussian process model of the PES, which enables defining the likelihood of the dominant points. The robustness and efficiency of the method are demonstrated on a dozen model cases for proton diffusion in oxides, in comparison with a conventional nudge elastic band method.

A Comparative Study Using Numerical Methods for Surface X Ray Doses with Conventional and Digital Radiology Equipment in Pediatric Radiology

NASA Astrophysics Data System (ADS)

Dan, Posa Ioan; Florin, Georgescu Remus; Virgil, Ciobanu; Antonescu, Elisabeta

2011-09-01

The place of the study is a pediatrics clinic which realizes a great variety of emergency, ambulatory ad hospital examinations. The radiology compartment respects work procedures and a system to ensure the quality of X ray examinations. The results show a constant for the programmator of the digital detector machine for the tension applied to the tube. For the screen-film detector machine the applied tension increases proportionally with the physical development of the child considering the trunk thickness.

Magnet reliability in the Fermilab Main Injector and implications for the ILC

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

Tartaglia, M.A.; Blowers, J.; Capista, D.

2007-08-01

The International Linear Collider reference design requires over 13000 magnets, of approximately 135 styles, which must operate with very high reliability. The Fermilab Main Injector represents a modern machine with many conventional magnet styles, each of significant quantity, that has now accumulated many hundreds of magnet-years of operation. We review here the performance of the magnets built for this machine, assess their reliability and categorize the failure modes, and discuss implications for reliability of similar magnet styles expected to be used at the ILC.

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

Geometry and surface damage in micro electrical discharge machining of micro-holes

NASA Astrophysics Data System (ADS)

Ekmekci, Bülent; Sayar, Atakan; Tecelli Öpöz, Tahsin; Erden, Abdulkadir

2009-10-01

Geometry and subsurface damage of blind micro-holes produced by micro electrical discharge machining (micro-EDM) is investigated experimentally to explore the relational dependence with respect to pulse energy. For this purpose, micro-holes are machined with various pulse energies on plastic mold steel samples using a tungsten carbide tool electrode and a hydrocarbon-based dielectric liquid. Variations in the micro-hole geometry, micro-hole depth and over-cut in micro-hole diameter are measured. Then, unconventional etching agents are applied on the cross sections to examine micro structural alterations within the substrate. It is observed that the heat-damaged segment is composed of three distinctive layers, which have relatively high thicknesses and vary noticeably with respect to the drilling depth. Crack formation is identified on some sections of the micro-holes even by utilizing low pulse energies during machining. It is concluded that the cracking mechanism is different from cracks encountered on the surfaces when machining is performed by using the conventional EDM process. Moreover, an electrically conductive bridge between work material and debris particles is possible at the end tip during machining which leads to electric discharges between the piled segments of debris particles and the tool electrode during discharging.

Automated drafting system uses computer techniques

NASA Technical Reports Server (NTRS)

Millenson, D. H.

1966-01-01

Automated drafting system produces schematic and block diagrams from the design engineers freehand sketches. This system codes conventional drafting symbols and their coordinate locations on standard size drawings for entry on tapes that are used to drive a high speed photocomposition machine.

PROGRAMED TEACHING OF CHEMISTRY.

ERIC Educational Resources Information Center

SHAPOVALENKO, S.G.

DEVELOPMENT OF NON-MACHINE PROGRAMED INSTRUCTION ACCORDING TO STATE-SPECIFIED EDUCATIONAL GOALS AND TRADITIONAL PSYCHOLOGICAL PRINCIPLES WILL ALLOW EFFICIENT, INDEPENDENT, CONTROLLED LEARNING, BUT MUST BE USED IN COMBINATION WITH CONVENTIONAL INSTRUCTION TO FORTIFY IN PUPILS THE FEELING OF COLLECTIVISM. EXPERIMENTAL WORK WITH SEVENTH GRADE SHOWS…

Fault detection in rotating machines with beamforming: Spatial visualization of diagnosis features

NASA Astrophysics Data System (ADS)

Cardenas Cabada, E.; Leclere, Q.; Antoni, J.; Hamzaoui, N.

2017-12-01

Rotating machines diagnosis is conventionally related to vibration analysis. Sensors are usually placed on the machine to gather information about its components. The recorded signals are then processed through a fault detection algorithm allowing the identification of the failing part. This paper proposes an acoustic-based diagnosis method. A microphone array is used to record the acoustic field radiated by the machine. The main advantage over vibration-based diagnosis is that the contact between the sensors and the machine is no longer required. Moreover, the application of acoustic imaging makes possible the identification of the sources of acoustic radiation on the machine surface. The display of information is then spatially continuous while the accelerometers only give it discrete. Beamforming provides the time-varying signals radiated by the machine as a function of space. Any fault detection tool can be applied to the beamforming output. Spectral kurtosis, which highlights the impulsiveness of a signal as function of frequency, is used in this study. The combination of spectral kurtosis with acoustic imaging makes possible the mapping of the impulsiveness as a function of space and frequency. The efficiency of this approach lays on the source separation in the spatial and frequency domains. These mappings make possible the localization of such impulsive sources. The faulty components of the machine have an impulsive behavior and thus will be highlighted on the mappings. The study presents experimental validations of the method on rotating machines.

wACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials

NASA Astrophysics Data System (ADS)

Gastegger, M.; Schwiedrzik, L.; Bittermann, M.; Berzsenyi, F.; Marquetand, P.

2018-06-01

We introduce weighted atom-centered symmetry functions (wACSFs) as descriptors of a chemical system's geometry for use in the prediction of chemical properties such as enthalpies or potential energies via machine learning. The wACSFs are based on conventional atom-centered symmetry functions (ACSFs) but overcome the undesirable scaling of the latter with an increasing number of different elements in a chemical system. The performance of these two descriptors is compared using them as inputs in high-dimensional neural network potentials (HDNNPs), employing the molecular structures and associated enthalpies of the 133 855 molecules containing up to five different elements reported in the QM9 database as reference data. A substantially smaller number of wACSFs than ACSFs is needed to obtain a comparable spatial resolution of the molecular structures. At the same time, this smaller set of wACSFs leads to a significantly better generalization performance in the machine learning potential than the large set of conventional ACSFs. Furthermore, we show that the intrinsic parameters of the descriptors can in principle be optimized with a genetic algorithm in a highly automated manner. For the wACSFs employed here, we find however that using a simple empirical parametrization scheme is sufficient in order to obtain HDNNPs with high accuracy.

Plastic superconductor bearings any size, any shape, 77 k and up

NASA Technical Reports Server (NTRS)

Reick, Franklin G.

1990-01-01

Friction free bearings at 77 k or higher are possible using the high T(sub c) copper oxide ceramic superconductors. The conventional method for making such bearings is to use a sintered ceramic monolith. This puts great restraints on size, shape and postforming machining. The material is hard and abrasive. It's possible to grind up ceramic superconductors and suspend the granules in a suitable matrix. Mechanical properties improve and are largely dependent on the binder. The Meissner effect is confined to individual grains containing electron vortices. Tracks, rails, levitation areas and bearings can be made this way with conventional plastic molding and extruding machines or by painting. The parts are easily machined. The sacrifice is in bulk electrical conductivity. A percolating wick feel for LN2 can be used to cool remote superconductors and large areas quite effectively. A hollow spheroid or cylinder of superconductor material can be molded with the internal surfaces shielded by the Meissner effect. It might be thought of as the dc magnetic analogue of the Faraday cage and the inside can be called the Meissner space. It's selective. The ac fields are transmitted with minor attenuation. Particle size and distribution have a profound effect on final magnetic and electrical characteristics.

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

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

Investigations of Effect of Rotary EDM Electrode on Machining Performance of Al6061 Alloy

NASA Astrophysics Data System (ADS)

Robinson Smart, D. S.; Jenish Smart, Joses; Periasamy, C.; Ratna Kumar, P. S. Samuel

2018-04-01

Electric Discharge Machining is an essential process which is being used for machining desired shape using electrical discharges which creates sparks. There will be electrodes subjected to electric voltage and which are separated by a dielectric liquid. Removing of material will be due to the continuous and rapid current discharges between two electrodes.. The spark is very carefully controlled and localized so that it only affects the surface of the material. Usually in order to prevent the defects which are arising due to the conventional machining, the Electric Discharge Machining (EDM) machining is preferred. Also intricate and complicated shapes can be machined effectively by use of Electric Discharge Machining (EDM). The EDM process usually does not affect the heat treat below the surface. This research work focus on the design and fabrication of rotary EDM tool for machining Al6061alloy and investigation of effect of rotary tool on surface finish, material removal rate and tool wear rate. Also the effect of machining parameters of EDM such as pulse on & off time, current on material Removal Rate (MRR), Surface Roughness (SR) and Electrode wear rate (EWR) have studied. Al6061 alloy can be used for marine and offshore applications by reinforcing some other elements. The investigations have revealed that MRR (material removal rate), surface roughness (Ra) have been improved with the reduction in the tool wear rate (TWR) when the tool is rotating instead of stationary. It was clear that as rotary speed of the tool is increasing the material removal rate is increasing with the reduction of surface finish and tool wear rate.

Rapid method for sampling metals for materials identification

NASA Technical Reports Server (NTRS)

Higgins, L. E.

1971-01-01

Nondamaging process similar to electrochemical machining is useful in obtaining metal samples from places inaccessible to conventional sampling methods or where methods would be hazardous or contaminating to specimens. Process applies to industries where metals or metal alloys play a vital role.

"Grinding" cavities in polyurethane foam

NASA Technical Reports Server (NTRS)

Brower, J. R.; Davey, R. E.; Dixon, W. F.; Robb, P. H.; Zebus, P. P.

1980-01-01

Grinding tool installed on conventional milling machine cuts precise cavities in foam blocks. Method is well suited for prototype or midsize production runs and can be adapted to computer control for mass production. Method saves time and materials compared to bonding or hot wire techniques.

Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.

PubMed

Rachmadi, Muhammad Febrian; Valdés-Hernández, Maria Del C; Agan, Maria Leonora Fatimah; Di Perri, Carol; Komura, Taku

2018-06-01

We propose an adaptation of a convolutional neural network (CNN) scheme proposed for segmenting brain lesions with considerable mass-effect, to segment white matter hyperintensities (WMH) characteristic of brains with none or mild vascular pathology in routine clinical brain magnetic resonance images (MRI). This is a rather difficult segmentation problem because of the small area (i.e., volume) of the WMH and their similarity to non-pathological brain tissue. We investigate the effectiveness of the 2D CNN scheme by comparing its performance against those obtained from another deep learning approach: Deep Boltzmann Machine (DBM), two conventional machine learning approaches: Support Vector Machine (SVM) and Random Forest (RF), and a public toolbox: Lesion Segmentation Tool (LST), all reported to be useful for segmenting WMH in MRI. We also introduce a way to incorporate spatial information in convolution level of CNN for WMH segmentation named global spatial information (GSI). Analysis of covariance corroborated known associations between WMH progression, as assessed by all methods evaluated, and demographic and clinical data. Deep learning algorithms outperform conventional machine learning algorithms by excluding MRI artefacts and pathologies that appear similar to WMH. Our proposed approach of incorporating GSI also successfully helped CNN to achieve better automatic WMH segmentation regardless of network's settings tested. The mean Dice Similarity Coefficient (DSC) values for LST-LGA, SVM, RF, DBM, CNN and CNN-GSI were 0.2963, 0.1194, 0.1633, 0.3264, 0.5359 and 5389 respectively. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition.

PubMed

Jauregi Unanue, Iñigo; Zare Borzeshi, Ehsan; Piccardi, Massimo

2017-12-01

Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word "embeddings". (i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets. Two deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models. We have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset. We present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary. Copyright © 2017 Elsevier Inc. All rights reserved.

The Modern Integrated Anaesthesia Workstation

PubMed Central

Patil, Vijaya P; Shetmahajan, Madhavi G; Divatia, Jigeeshu V

2013-01-01

Over the years, the conventional anaesthesia machine has evolved into an advanced carestation. The new machines use advanced electronics, software and technology to offer extensive capabilities for ventilation, monitoring, inhaled agent delivery, low-flow anaesthesia and closed-loop anaesthesia. They offer integrated monitoring and recording facilities and seamless integration with anaesthesia information systems. It is possible to deliver tidal volumes accurately and eliminate several hazards associated with the low pressure system and oxygen flush. Appropriate use can result in enhanced safety and ergonomy of anaesthetic delivery and monitoring. However, these workstations have brought in a new set of limitations and potential drawbacks. There are differences in technology and operational principles amongst the new workstations. Understand the principles of operation of these workstations and have a thorough knowledge of the operating manual of the individual machines. PMID:24249877

Robotic inspection of fiber reinforced composites using phased array UT

NASA Astrophysics Data System (ADS)

Stetson, Jeffrey T.; De Odorico, Walter

2014-02-01

Ultrasound is the current NDE method of choice to inspect large fiber reinforced airframe structures. Over the last 15 years Cartesian based scanning machines using conventional ultrasound techniques have been employed by all airframe OEMs and their top tier suppliers to perform these inspections. Technical advances in both computing power and commercially available, multi-axis robots now facilitate a new generation of scanning machines. These machines use multiple end effector tools taking full advantage of phased array ultrasound technologies yielding substantial improvements in inspection quality and productivity. This paper outlines the general architecture for these new robotic scanning systems as well as details the variety of ultrasonic techniques available for use with them including advances such as wide area phased array scanning and sound field adaptation for non-flat, non-parallel surfaces.

Prediction of 3D chip formation in the facing cutting with lathe machine using FEM

NASA Astrophysics Data System (ADS)

Prasetyo, Yudhi; Tauviqirrahman, Mohamad; Rusnaldy

2016-04-01

This paper presents the prediction of the chip formation at the machining process using a lathe machine in a more specific way focusing on facing cutting (face turning). The main purpose is to propose a new approach to predict the chip formation with the variation of the cutting directions i.e., the backward and forward direction. In addition, the interaction between stress analysis and chip formation on cutting process was also investigated. The simulations were conducted using three dimensional (3D) finite element method based on ABAQUS software with aluminum and high speed steel (HSS) as the workpiece and the tool materials, respectively. The simulation result showed that the chip resulted using a backward direction depicts a better formation than that using a conventional (forward) direction.

Electron beam machining using rotating and shaped beam power distribution

DOEpatents

Elmer, John W.; O'Brien, Dennis W.

1996-01-01

An apparatus and method for electron beam (EB) machining (drilling, cutting and welding) that uses conventional EB guns, power supplies, and welding machine technology without the need for fast bias pulsing technology. The invention involves a magnetic lensing (EB optics) system and electronic controls to: 1) concurrently bend, focus, shape, scan, and rotate the beam to protect the EB gun and to create a desired effective power-density distribution, and 2) rotate or scan this shaped beam in a controlled way. The shaped beam power-density distribution can be measured using a tomographic imaging system. For example, the EB apparatus of this invention has the ability to drill holes in metal having a diameter up to 1000 .mu.m (1 mm or larger), compared to the 250 .mu.m diameter of laser drilling.

Re-Shielding of Cobalt-60 Teletherapy Rooms for Tomotherapy and Conventional Linear Accelerators using Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Çeçen, Yiğit; Yazgan, Çağrı

2017-09-01

Purpose. Nearly all Cobalt-60 teletherapy machines were removed around the world during the last two decades. The remaining ones are being used for experimental purposes. However, the rooms of these teletherapy machines are valuable because of lack of space in radiotherapy clinics. In order to place a new technology treatment machine in one of these rooms, one should re-shield the room since it was designed only for 1.25 MeV gamma beams on average. Mostly, the vendor of the new machine constructs the new shielding of the room using their experience. However, every radiotherapy room has different surrounding work areas and it would be wise to shield the room considering these special conditions. Also, the shield design goal of the clinic may be much lower than the International Atomic Energy Agency (IAEA) or the local association accepts. The study shows re-shielding of a Cobalt-60 room, specific to the clinic, using Monte Carlo simulations. Materials & Methods: First, a 6 MV Tomotherapy machine, then a 10 MV conventional linear accelerator (LINAC) was placed inside the Cobalt-60 teletherapy room. The photon flux outside the room was simulated using Monte Carlo N-Particle (MCNP6.1) code before and after re-shielding. For the Tomotherapy simulation, flux distributions around the machine were obtained from the vendor and implemented as the source of the model. The LINAC model was more generic with the 10 MeV electron source, the tungsten target, first and secondary collimators. The aim of the model was to obtain the maximum (40x40 cm2) open field at the isocenter. Two different simulations were carried out for gantry angles 90o and 270o. The LINAC was placed in the room such that the primary walls were A' (Gantry 270o) and C' (Gantry 90o) (figure 1). The second part of the study was to model the re-shielding of the room for Tomotherapy and for the conventional LINAC, separately. The aim was to investigate the recommended shielding by the vendors. Left side of the room was adjacent to a LINAC room with 2 meters thick concrete wall (figure 1). No shielding was necessary for that wall. Behind wall A-A' there was an outdoors forbidden area; behind wall B-B' was the contouring room for the doctors; and the control room was behind wall C-C' (figure 1). After some modifications, the final shielding was designed. Results: The photon flux distributions outside the room before and after the re-shielding were compared. The re-shielding of Tomotherapy reduced the flux down to 1.89 % on average with respect to pre-shielding (table 1). For the conventional LINAC case; after re-shielding, the photon flux in the control room -which corresponds to gantry 90°- decreased down to 0.57% with respect to pre-shielding (table 2). The photon flux behind wall A' -which corresponds to gantry 270°- decreased down to 2.46%. Everybody was all safe behind wall B' even before re-shielding.

Quantification of incisal tooth wear in upper anterior teeth: conventional vs new method using toolmakers microscope and a three-dimensional measuring technique.

PubMed

Al-Omiri, Mahmoud K; Sghaireen, Mohd G; Alzarea, Bader K; Lynch, Edward

2013-12-01

This study aimed to quantify tooth wear in upper anterior teeth using a new CAD-CAM Laser scanning machine, tool maker microscope and conventional tooth wear index. Fifty participants (25 males and 25 females, mean age = 25 ± 4 years) were assessed for incisal tooth wear of upper anterior teeth using Smith and Knight clinical tooth wear index (TWI) on two occasions, the study baseline and 1 year later. Stone dies for each tooth were prepared and scanned using the CAD-CAM Laser Cercon System. Scanned images were printed and examined under a toolmaker microscope to quantify tooth wear and then the dies were directly assessed under the microscope to measure tooth wear. The Wilcoxon Signed Ranks Test was used to analyze the data. TWI scores for incisal edges were 0-3 and were similar at both occasions. Score 4 was not detected. Wear values measured by directly assessing the dies under the toolmaker microscope (range = 113 - 150 μm, mean = 130 ± 20 μm) were significantly more than those measured from Cercon Digital Machine images (range=52-80 μm, mean = 68 ± 23 μm) and both showed significant differences between the two occasions. Wear progression in upper anterior teeth was effectively detected by directly measuring the dies or the images of dies under toolmaker microscope. Measuring the dies of worn dentition directly under tool maker microscope enabled detection of wear progression more accurately than measuring die images obtained with Cercon Digital Machine. Conventional method was the least sensitive for tooth wear quantification and was unable to identify wear progression in most cases. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advent of Greige Cotton Nonwovens Made By Hydro-Entanglement Process

USDA-ARS?s Scientific Manuscript database

Using greige (scour/bleachless) cotton, a few nonwoven fabrics have been successfully produced by adopting conventional fiber opening, cleaning and (modified) carding machines followed by cross-lapping, pre/light needling, and hydro-entanglement (H-E) on modern commercial machinery and equipment. Us...

Maximum-Likelihood Estimation With a Contracting-Grid Search Algorithm

PubMed Central

Hesterman, Jacob Y.; Caucci, Luca; Kupinski, Matthew A.; Barrett, Harrison H.; Furenlid, Lars R.

2010-01-01

A fast search algorithm capable of operating in multi-dimensional spaces is introduced. As a sample application, we demonstrate its utility in the 2D and 3D maximum-likelihood position-estimation problem that arises in the processing of PMT signals to derive interaction locations in compact gamma cameras. We demonstrate that the algorithm can be parallelized in pipelines, and thereby efficiently implemented in specialized hardware, such as field-programmable gate arrays (FPGAs). A 2D implementation of the algorithm is achieved in Cell/BE processors, resulting in processing speeds above one million events per second, which is a 20× increase in speed over a conventional desktop machine. Graphics processing units (GPUs) are used for a 3D application of the algorithm, resulting in processing speeds of nearly 250,000 events per second which is a 250× increase in speed over a conventional desktop machine. These implementations indicate the viability of the algorithm for use in real-time imaging applications. PMID:20824155

[Investigation of infiltration glass of the machinable infiltrated ceramic(MIC)].

PubMed

Liao, Y; Yang, H; Xan, S; Xue, Y; Chai, F

2000-03-01

To explore the manufacture arts and determine the properties of the infiltration glass of the MIC. In order to determine the glass forming range of the MIC infiltration glass, molten glass was prepared in Al2O3 crucibles by heating the components to 1450 degrees C. Thermal analytic device was employed to study the thermal properties of the glass. Its crystal phases after micro-crystallization were analyzed with XRD. Flexural strength was measured by means of 3-point bending test. The chemical components of MIC glass were determined. Conventional fluorophlogopite glass was converted into an infiltration glass with low viscosity, good infiltration capability and low fusing temperature by introducing B2O3, La2O3 and Li2O into the glass. Fluorophlogopite crystals formed after crystallization. Conventional mica glass can be changed according to the requirements of properties. Modified mica MIC glass in this study has good infiltration ability in Al2O3 matrix while remains machinability.

Study on Damage Evaluation and Machinability of UD-CFRP for the Orthogonal Cutting Operation Using Scanning Acoustic Microscopy and the Finite Element Method.

PubMed

Wang, Dongyao; He, Xiaodong; Xu, Zhonghai; Jiao, Weicheng; Yang, Fan; Jiang, Long; Li, Linlin; Liu, Wenbo; Wang, Rongguo

2017-02-20

Owing to high specific strength and designability, unidirectional carbon fiber reinforced polymer (UD-CFRP) has been utilized in numerous fields to replace conventional metal materials. Post machining processes are always required for UD-CFRP to achieve dimensional tolerance and assembly specifications. Due to inhomogeneity and anisotropy, UD-CFRP differs greatly from metal materials in machining and failure mechanism. To improve the efficiency and avoid machining-induced damage, this paper undertook to study the correlations between cutting parameters, fiber orientation angle, cutting forces, and cutting-induced damage for UD-CFRP laminate. Scanning acoustic microscopy (SAM) was employed and one-/two-dimensional damage factors were then created to quantitatively characterize the damage of the laminate workpieces. According to the 3D Hashin's criteria a numerical model was further proposed in terms of the finite element method (FEM). A good agreement between simulation and experimental results was validated for the prediction and structural optimization of the UD-CFRP.

Hardware Acceleration of Adaptive Neural Algorithms.

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

James, Conrad D.

As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - worldmore » conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.« less

Study on Damage Evaluation and Machinability of UD-CFRP for the Orthogonal Cutting Operation Using Scanning Acoustic Microscopy and the Finite Element Method

PubMed Central

Wang, Dongyao; He, Xiaodong; Xu, Zhonghai; Jiao, Weicheng; Yang, Fan; Jiang, Long; Li, Linlin; Liu, Wenbo; Wang, Rongguo

2017-01-01

Owing to high specific strength and designability, unidirectional carbon fiber reinforced polymer (UD-CFRP) has been utilized in numerous fields to replace conventional metal materials. Post machining processes are always required for UD-CFRP to achieve dimensional tolerance and assembly specifications. Due to inhomogeneity and anisotropy, UD-CFRP differs greatly from metal materials in machining and failure mechanism. To improve the efficiency and avoid machining-induced damage, this paper undertook to study the correlations between cutting parameters, fiber orientation angle, cutting forces, and cutting-induced damage for UD-CFRP laminate. Scanning acoustic microscopy (SAM) was employed and one-/two-dimensional damage factors were then created to quantitatively characterize the damage of the laminate workpieces. According to the 3D Hashin’s criteria a numerical model was further proposed in terms of the finite element method (FEM). A good agreement between simulation and experimental results was validated for the prediction and structural optimization of the UD-CFRP. PMID:28772565

Stacked Corrugated Horn Rings

NASA Technical Reports Server (NTRS)

Sosnowski, John B.

2010-01-01

This Brief describes a method of machining and assembly when the depth of corrugations far exceeds the width and conventional machining is not practical. The horn is divided into easily machined, individual rings with shoulders to control the depth. In this specific instance, each of the corrugations is identical in profile, and only differs in diameter and outer profile. The horn is segmented into rings that are cut with an interference fit (zero clearance with all machining errors biased toward contact). The interference faces can be cut with a reverse taper to increase the holding strength of the joint. The taper is a compromise between the interference fit and the clearance of the two faces during assembly. Each internal ring is dipped in liquid nitrogen, then nested in the previous, larger ring. The ring is rotated in the nest until the temperature of the two parts equalizes and the pieces lock together. The resulting assay is stable, strong, and has an internal finish that cannot be achieved through other methods.

Using machine learning to assess covariate balance in matching studies.

PubMed

Linden, Ariel; Yarnold, Paul R

2016-12-01

In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.

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

Angers, Crystal Plume; Bottema, Ryan; Buckley, Les

Purpose: Treatment unit uptime statistics are typically used to monitor radiation equipment performance. The Ottawa Hospital Cancer Centre has introduced the use of Quality Control (QC) test success as a quality indicator for equipment performance and overall health of the equipment QC program. Methods: Implemented in 2012, QATrack+ is used to record and monitor over 1100 routine machine QC tests each month for 20 treatment and imaging units ( http://qatrackplus.com/ ). Using an SQL (structured query language) script, automated queries of the QATrack+ database are used to generate program metrics such as the number of QC tests executed and themore » percentage of tests passing, at tolerance or at action. These metrics are compared against machine uptime statistics already reported within the program. Results: Program metrics for 2015 show good correlation between pass rate of QC tests and uptime for a given machine. For the nine conventional linacs, the QC test success rate was consistently greater than 97%. The corresponding uptimes for these units are better than 98%. Machines that consistently show higher failure or tolerance rates in the QC tests have lower uptimes. This points to either poor machine performance requiring corrective action or to problems with the QC program. Conclusions: QATrack+ significantly improves the organization of QC data but can also aid in overall equipment management. Complimenting machine uptime statistics with QC test metrics provides a more complete picture of overall machine performance and can be used to identify areas of improvement in the machine service and QC programs.« less

Radiation tolerant combinational logic cell

NASA Technical Reports Server (NTRS)

Maki, Gary R. (Inventor); Whitaker, Sterling (Inventor); Gambles, Jody W. (Inventor)

2009-01-01

A system has a reduced sensitivity to Single Event Upset and/or Single Event Transient(s) compared to traditional logic devices. In a particular embodiment, the system includes an input, a logic block, a bias stage, a state machine, and an output. The logic block is coupled to the input. The logic block is for implementing a logic function, receiving a data set via the input, and generating a result f by applying the data set to the logic function. The bias stage is coupled to the logic block. The bias stage is for receiving the result from the logic block and presenting it to the state machine. The state machine is coupled to the bias stage. The state machine is for receiving, via the bias stage, the result generated by the logic block. The state machine is configured to retain a state value for the system. The state value is typically based on the result generated by the logic block. The output is coupled to the state machine. The output is for providing the value stored by the state machine. Some embodiments of the invention produce dual rail outputs Q and Q'. The logic block typically contains combinational logic and is similar, in size and transistor configuration, to a conventional CMOS combinational logic design. However, only a very small portion of the circuits of these embodiments, is sensitive to Single Event Upset and/or Single Event Transients.

Recent developments in turning hardened steels - A review

NASA Astrophysics Data System (ADS)

Sivaraman, V.; Prakash, S.

2017-05-01

Hard materials ranging from HRC 45 - 68 such as hardened AISI H13, AISI 4340, AISI 52100, D2 STL, D3 STEEL Steel etc., need super hard tool materials to machine. Turning of these hard materials is termed as hard turning. Hard turning makes possible direct machining of the hard materials and also eliminates the lubricant requirement and thus favoring dry machining. Hard turning is a finish turning process and hence conventional grinding is not required. Development of the new advanced super hard tool materials such as ceramic inserts, Cubic Boron Nitride, Polycrystalline Cubic Boron Nitride etc. enabled the turning of these materials. PVD and CVD methods of coating have made easier the production of single and multi layered coated tool inserts. Coatings of TiN, TiAlN, TiC, Al2O3, AlCrN over cemented carbide inserts has lead to the machining of difficult to machine materials. Advancement in the process of hard machining paved way for better surface finish, long tool life, reduced tool wear, cutting force and cutting temperatures. Micro and Nano coated carbide inserts, nanocomposite coated PCBN inserts, micro and nano CBN coated carbide inserts and similar developments have made machining of hardened steels much easier and economical. In this paper, broad literature review on turning of hardened steels including optimizing process parameters, cooling requirements, different tool materials etc., are done.

Research interface on a programmable ultrasound scanner.

PubMed

Shamdasani, Vijay; Bae, Unmin; Sikdar, Siddhartha; Yoo, Yang Mo; Karadayi, Kerem; Managuli, Ravi; Kim, Yongmin

2008-07-01

Commercial ultrasound machines in the past did not provide the ultrasound researchers access to raw ultrasound data. Lack of this ability has impeded evaluation and clinical testing of novel ultrasound algorithms and applications. Recently, we developed a flexible ultrasound back-end where all the processing for the conventional ultrasound modes, such as B, M, color flow and spectral Doppler, was performed in software. The back-end has been incorporated into a commercial ultrasound machine, the Hitachi HiVision 5500. The goal of this work is to develop an ultrasound research interface on the back-end for acquiring raw ultrasound data from the machine. The research interface has been designed as a software module on the ultrasound back-end. To increase the amount of raw ultrasound data that can be spooled in the limited memory available on the back-end, we have developed a method that can losslessly compress the ultrasound data in real time. The raw ultrasound data could be obtained in any conventional ultrasound mode, including duplex and triplex modes. Furthermore, use of the research interface does not decrease the frame rate or otherwise affect the clinical usability of the machine. The lossless compression of the ultrasound data in real time can increase the amount of data spooled by approximately 2.3 times, thus allowing more than 6s of raw ultrasound data to be acquired in all the modes. The interface has been used not only for early testing of new ideas with in vitro data from phantoms, but also for acquiring in vivo data for fine-tuning ultrasound applications and conducting clinical studies. We present several examples of how newer ultrasound applications, such as elastography, vibration imaging and 3D imaging, have benefited from this research interface. Since the research interface is entirely implemented in software, it can be deployed on existing HiVision 5500 ultrasound machines and may be easily upgraded in the future. The developed research interface can aid researchers in the rapid testing and clinical evaluation of new ultrasound algorithms and applications. Additionally, we believe that our approach would be applicable to designing research interfaces on other ultrasound machines.

Scale effects and a method for similarity evaluation in micro electrical discharge machining

NASA Astrophysics Data System (ADS)

Liu, Qingyu; Zhang, Qinhe; Wang, Kan; Zhu, Guang; Fu, Xiuzhuo; Zhang, Jianhua

2016-08-01

Electrical discharge machining(EDM) is a promising non-traditional micro machining technology that offers a vast array of applications in the manufacturing industry. However, scale effects occur when machining at the micro-scale, which can make it difficult to predict and optimize the machining performances of micro EDM. A new concept of "scale effects" in micro EDM is proposed, the scale effects can reveal the difference in machining performances between micro EDM and conventional macro EDM. Similarity theory is presented to evaluate the scale effects in micro EDM. Single factor experiments are conducted and the experimental results are analyzed by discussing the similarity difference and similarity precision. The results show that the output results of scale effects in micro EDM do not change linearly with discharge parameters. The values of similarity precision of machining time significantly increase when scaling-down the capacitance or open-circuit voltage. It is indicated that the lower the scale of the discharge parameter, the greater the deviation of non-geometrical similarity degree over geometrical similarity degree, which means that the micro EDM system with lower discharge energy experiences more scale effects. The largest similarity difference is 5.34 while the largest similarity precision can be as high as 114.03. It is suggested that the similarity precision is more effective in reflecting the scale effects and their fluctuation than similarity difference. Consequently, similarity theory is suitable for evaluating the scale effects in micro EDM. This proposed research offers engineering values for optimizing the machining parameters and improving the machining performances of micro EDM.

Single phase space laundry development

NASA Technical Reports Server (NTRS)

Colombo, Gerald V.; Putnam, David F.; Lunsford, Teddie D.; Streech, Neil D.; Wheeler, Richard R., Jr.; Reimers, Harold

1993-01-01

This paper describes a newly designed, 2.7 Kg (6 pound) capacity, laundry machine called the Single Phase Laundry (SPSL). The machine was designed to wash and dry crew clothing in a micro-gravity environment. A prototype unit was fabricated for NASA-JSC under a Small Business Innovated Research (SBIR) contract extending from September 1990 to January 1993. The unit employs liquid jet agitation, microwave vacuum drying, and air jet tumbling, which was perfected by KC-135 zero-g flight testing. Operation is completely automated except for loading and unloading clothes. The unit uses about 20 percent less power than a conventional household appliance.

Precision injection molding of freeform optics

NASA Astrophysics Data System (ADS)

Fang, Fengzhou; Zhang, Nan; Zhang, Xiaodong

2016-08-01

Precision injection molding is the most efficient mass production technology for manufacturing plastic optics. Applications of plastic optics in field of imaging, illumination, and concentration demonstrate a variety of complex surface forms, developing from conventional plano and spherical surfaces to aspheric and freeform surfaces. It requires high optical quality with high form accuracy and lower residual stresses, which challenges both optical tool inserts machining and precision injection molding process. The present paper reviews recent progress in mold tool machining and precision injection molding, with more emphasis on precision injection molding. The challenges and future development trend are also discussed.

Machine learning in the rational design of antimicrobial peptides.

PubMed

Rondón-Villarreal, Paola; Sierra, Daniel A; Torres, Rodrigo

2014-01-01

One of the most important public health issues is the microbial and bacterial resistance to conventional antibiotics by pathogen microorganisms. In recent years, many researches have been focused on the development of new antibiotics. Among these, antimicrobial peptides (AMPs) have raised as a promising alternative to combat antibioticresistant microorganisms. For this reason, many theoretical efforts have been done in the development of new computational tools for the rational design of both better and effective AMPs. In this review, we present an overview of the rational design of AMPs using machine learning techniques and new research fields.

Cooperative combinatorial optimization: evolutionary computation case study.

PubMed

Burgin, Mark; Eberbach, Eugene

2008-01-01

This paper presents a formalization of the notion of cooperation and competition of multiple systems that work toward a common optimization goal of the population using evolutionary computation techniques. It is proved that evolutionary algorithms are more expressive than conventional recursive algorithms, such as Turing machines. Three classes of evolutionary computations are introduced and studied: bounded finite, unbounded finite, and infinite computations. Universal evolutionary algorithms are constructed. Such properties of evolutionary algorithms as completeness, optimality, and search decidability are examined. A natural extension of evolutionary Turing machine (ETM) model is proposed to properly reflect phenomena of cooperation and competition in the whole population.

Smart Screening System (S3) In Taconite Processing

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

Daryoush Allaei; Angus Morison; David Tarnowski

2005-09-01

The conventional screening machines used in processing plants have had undesirable high noise and vibration levels. They also have had unsatisfactorily low screening efficiency, high energy consumption, high maintenance cost, low productivity, and poor worker safety. These conventional vibrating machines have been used in almost every processing plant. Most of the current material separation technology uses heavy and inefficient electric motors with an unbalanced rotating mass to generate the shaking. In addition to being excessively noisy, inefficient, and high-maintenance, these vibrating machines are often the bottleneck in the entire process. Furthermore, these motors, along with the vibrating machines and supportingmore » structure, shake other machines and structures in the vicinity. The latter increases maintenance costs while reducing worker health and safety. The conventional vibrating fine screens at taconite processing plants have had the same problems as those listed above. This has resulted in lower screening efficiency, higher energy and maintenance cost, and lower productivity and workers safety concerns. The focus of this work is on the design of a high performance screening machine suitable for taconite processing plants. SmartScreens{trademark} technology uses miniaturized motors, based on smart materials, to generate the shaking. The underlying technologies are Energy Flow Control{trademark} and Vibration Control by Confinement{trademark}. These concepts are used to direct energy flow and confine energy efficiently and effectively to the screen function. The SmartScreens{trademark} technology addresses problems related to noise and vibration, screening efficiency, productivity, and maintenance cost and worker safety. Successful development of SmartScreens{trademark} technology will bring drastic changes to the screening and physical separation industry. The final designs for key components of the SmartScreens{trademark} have been developed. The key components include smart motor and associated electronics, resonators, and supporting structural elements. It is shown that the smart motors have an acceptable life and performance. Resonator (or motion amplifier) designs are selected based on the final system requirement and vibration characteristics. All the components for a fully functional prototype are fabricated. The development program is on schedule. The last semi-annual report described the process of FE model validation and correlation with experimental data in terms of dynamic performance and predicted stresses. It also detailed efforts into making the supporting structure less important to system performance. Finally, an introduction into the dry application concept was presented. Since then, the design refinement phase was completed. This has resulted in a Smart Screen design that meets performance targets both in the dry condition and with taconite slurry flow using PZT motors. Furthermore, this system was successfully demonstrated for the DOE and partner companies at the Coleraine Mineral Research Laboratory in Coleraine, Minnesota.« less

An evaluation of retrofit engineering control interventions to reduce perchloroethylene exposures in commercial dry-cleaning shops.

PubMed

Earnest, G Scott; Ewers, Lynda M; Ruder, Avima M; Petersen, Martin R; Kovein, Ronald J

2002-02-01

Real-time monitoring was used to evaluate the ability of engineering control devices retrofitted on two existing dry-cleaning machines to reduce worker exposures to perchloroethylene. In one dry-cleaning shop, a refrigerated condenser was installed on a machine that had a water-cooled condenser to reduce the air temperature, improve vapor recovery, and lower exposures. In a second shop, a carbon adsorber was retrofitted on a machine to adsorb residual perchloroethylene not collected by the existing refrigerated condenser to improve vapor recovery and reduce exposures. Both controls were successful at reducing the perchloroethylene exposures of the dry-cleaning machine operator. Real-time monitoring was performed to evaluate how the engineering controls affected exposures during loading and unloading the dry-cleaning machine, a task generally considered to account for the highest exposures. The real-time monitoring showed that dramatic reductions occurred in exposures during loading and unloading of the dry-cleaning machine due to the engineering controls. Peak operator exposures during loading and unloading were reduced by 60 percent in the shop that had a refrigerated condenser installed on the dry-cleaning machine and 92 percent in the shop that had a carbon adsorber installed. Although loading and unloading exposures were dramatically reduced, drops in full-shift time-weighted average (TWA) exposures were less dramatic. TWA exposures to perchloroethylene, as measured by conventional air sampling, showed smaller reductions in operator exposures of 28 percent or less. Differences between exposure results from real-time and conventional air sampling very likely resulted from other uncontrolled sources of exposure, differences in shop general ventilation before and after the control was installed, relatively small sample sizes, and experimental variability inherent in field research. Although there were some difficulties and complications with installation and maintenance of the engineering controls, this study showed that retrofitting engineering controls may be a feasible option for some dry-cleaning shop owners to reduce worker exposures to perchloroethylene. By installing retrofit controls, a dry-cleaning facility can reduce exposures, in some cases dramatically, and bring operators into compliance with the Occupational Safety and Health Administration (OSHA) peak exposure limit of 300 ppm. Retrofit engineering controls are also likely to enable many dry-cleaning workers to lower their overall personal TWA exposures to perchloroethylene.

Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.

PubMed

Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G

2017-09-01

To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.

Comparison of machine learned approaches for thyroid nodule characterization from shear wave elastography images

NASA Astrophysics Data System (ADS)

Pereira, Carina; Dighe, Manjiri; Alessio, Adam M.

2018-02-01

Various Computer Aided Diagnosis (CAD) systems have been developed that characterize thyroid nodules using the features extracted from the B-mode ultrasound images and Shear Wave Elastography images (SWE). These features, however, are not perfect predictors of malignancy. In other domains, deep learning techniques such as Convolutional Neural Networks (CNNs) have outperformed conventional feature extraction based machine learning approaches. In general, fully trained CNNs require substantial volumes of data, motivating several efforts to use transfer learning with pre-trained CNNs. In this context, we sought to compare the performance of conventional feature extraction, fully trained CNNs, and transfer learning based, pre-trained CNNs for the detection of thyroid malignancy from ultrasound images. We compared these approaches applied to a data set of 964 B-mode and SWE images from 165 patients. The data were divided into 80% training/validation and 20% testing data. The highest accuracies achieved on the testing data for the conventional feature extraction, fully trained CNN, and pre-trained CNN were 0.80, 0.75, and 0.83 respectively. In this application, classification using a pre-trained network yielded the best performance, potentially due to the relatively limited sample size and sub-optimal architecture for the fully trained CNN.

Development and Demonstration of Adanced Tooling Alloys for Molds and Dies

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

Kevin M. McHugh; Enrique J. Lavernia

2006-01-01

This report summarizes research results in the project Development and Demonstration of Advanced Tooling Alloys for Molds and Dies. Molds, dies and related tooling are used to manufacture most of the plastic and metal products we use every day. Conventional fabrication of molds and dies involves a multiplicity of machining, benching and heat treatment unit operations. This approach is very expensive and time consuming. Rapid Solidifcation Process (RSP) Tooling is a spray-forming technology tailored for producing molds and dies. The appraoch combines rapid solidifcation processing and net-shape materials processing in a single step. An atomized spray of a tool-forming alloy,more » typically a tool steel, is deposited onto an easy-to-form tool pattern to replicate the pattern's shape and surface features. By so doing, the approach eliminates many machining operations in conventional mold making, significantly reducing cost, lead time and energy. Moreover, rapid solidification creates unique microstructural features by suppressing carbide precipitation and growth, and creating metastable phases. This can result in unique material properties following heat treatment. Spray-formed and aged tool steel dies have exhibited extended life compared to conventional dies in many forming operations such as forging, extrusion and die casting. RSP Tooling technolocy was commercialized with the formation of RSP Tooling, LLC in Solon, Oh.« less

Efficient forced vibration reanalysis method for rotating electric machines

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Development of system decision support tools for behavioral trends monitoring of machinery maintenance in a competitive environment

NASA Astrophysics Data System (ADS)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani

2017-06-01

The article is centred on software system development for manufacturing company that produces polyethylene bags using mostly conventional machines in a competitive world where each business enterprise desires to stand tall. This is meant to assist in gaining market shares, taking maintenance and production decisions by the dynamism and flexibilities embedded in the package as customers' demand varies under the duress of meeting the set goals. The production and machine condition monitoring software (PMCMS) is programmed in C# and designed in such a way to support hardware integration, real-time machine conditions monitoring, which is based on condition maintenance approach, maintenance decision suggestions and suitable production strategies as the demand for products keeps changing in a highly competitive environment. PMCMS works with an embedded device which feeds it with data from the various machines being monitored at the workstation, and the data are read at the base station through transmission via a wireless transceiver and stored in a database. A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

Formal hardware verification of digital circuits

NASA Technical Reports Server (NTRS)

Joyce, J.; Seger, C.-J.

1991-01-01

The use of formal methods to verify the correctness of digital circuits is less constrained by the growing complexity of digital circuits than conventional methods based on exhaustive simulation. This paper briefly outlines three main approaches to formal hardware verification: symbolic simulation, state machine analysis, and theorem-proving.

Expanding the utility of the Agricultural Research Service (ARS) process bleaching

USDA-ARS?s Scientific Manuscript database

The ARS Process for bleaching, biopolishing, and shrinkproofing wool is a novel alternative to chlorination and conventional bleaching. Consumer acceptance of domestic machine-washable, comfortable wool which can be worn next to the skin will lead to niche-market- potential and competitive, increas...

Electron beam machining using rotating and shaped beam power distribution

DOEpatents

Elmer, J.W.; O`Brien, D.W.

1996-07-09

An apparatus and method are disclosed for electron beam (EB) machining (drilling, cutting and welding) that uses conventional EB guns, power supplies, and welding machine technology without the need for fast bias pulsing technology. The invention involves a magnetic lensing (EB optics) system and electronic controls to: (1) concurrently bend, focus, shape, scan, and rotate the beam to protect the EB gun and to create a desired effective power-density distribution, and (2) rotate or scan this shaped beam in a controlled way. The shaped beam power-density distribution can be measured using a tomographic imaging system. For example, the EB apparatus of this invention has the ability to drill holes in metal having a diameter up to 1,000 {micro}m (1 mm or larger), compared to the 250 {micro}m diameter of laser drilling. 5 figs.

Adaptive Sampling using Support Vector Machines

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

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

CMLLite: a design philosophy for CML

PubMed Central

2011-01-01

CMLLite is a collection of definitions and processes which provide strong and flexible validation for a document in Chemical Markup Language (CML). It consists of an updated CML schema (schema3), conventions specifying rules in both human and machine-understandable forms and a validator available both online and offline to check conformance. This article explores the rationale behind the changes which have been made to the schema, explains how conventions interact and how they are designed, formulated, implemented and tested, and gives an overview of the validation service. PMID:21999395

Effect of shot peening on the residual stress and mechanical behaviour of low-temperature and high-temperature annealed martensitic gear steel 18CrNiMo7-6

NASA Astrophysics Data System (ADS)

Yang, R.; Zhang, X.; Mallipeddi, D.; Angelou, N.; Toftegaard, H. L.; Li, Y.; Ahlström, J.; Lorentzen, L.; Wu, G.; Huang, X.

2017-07-01

A martensitic gear steel (18CrNiMo7-6) was annealed at 180 °C for 2h and at ˜ 750 °C for 1h to design two different starting microstructures for shot peening. One maintains the original as-transformed martensite while the other contains irregular-shaped sorbite together with ferrite. These two materials were shot peened using two different peening conditions. The softer sorbite + ferrite microstructure was shot peened using 0.6 mm conditioned cut steel shots at an average speed of 25 m/s in a conventional shot peening machine, while the harder tempered martensite steel was shot peened using 1.5 mm steel shots at a speed of 50 m/s in an in-house developed shot peening machine. The shot speeds in the conventional shot peening machine were measured using an in-house lidar set-up. The microstructure of each sample was characterized by optical and scanning electron microscopy, and the mechanical properties examined by microhardness and tensile testing. The residual stresses were measured using an Xstress 3000 G2R diffractometer equipped with a Cr Kα x-ray source. The correspondence between the residual stress profile and the gradient structure produced by shot peening, and the relationship between the microstructure and strength, are analyzed and discussed.

R&D of high reliable refrigeration system for superconducting generators

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

Hosoya, T.; Shindo, S.; Yaguchi, H.

1996-12-31

Super-GM carries out R&D of 70 MW class superconducting generators (model machines), refrigeration system and superconducting wires to apply superconducting technology to electric power apparatuses. The helium refrigeration system for keeping field windings of superconducting generator (SCG) in cryogenic environment must meet the requirement of high reliability for uninterrupted long term operation of the SCG. In FY 1992, a high reliable conventional refrigeration system for the model machines was integrated by combining components such as compressor unit, higher temperature cold box and lower temperature cold box which were manufactured utilizing various fundamental technologies developed in early stage of the projectmore » since 1988. Since FY 1993, its performance tests have been carried out. It has been confirmed that its performance was fulfilled the development target of liquefaction capacity of 100 L/h and impurity removal in the helium gas to < 0.1 ppm. Furthermore, its operation method and performance were clarified to all different modes as how to control liquefaction rate and how to supply liquid helium from a dewar to the model machine. In addition, the authors have made performance tests and system performance analysis of oil free screw type and turbo type compressors which greatly improve reliability of conventional refrigeration systems. The operation performance and operational control method of the compressors has been clarified through the tests and analysis.« less

Impact of spot charge inaccuracies in IMPT treatments.

PubMed

Kraan, Aafke C; Depauw, Nicolas; Clasie, Ben; Giunta, Marina; Madden, Tom; Kooy, Hanne M

2017-08-01

Spot charge is one parameter of pencil-beam scanning dose delivery system whose accuracy is typically high but whose required value has not been investigated. In this work we quantify the dose impact of spot charge inaccuracies on the dose distribution in patients. Knowing the effect of charge errors is relevant for conventional proton machines, as well as for new generation proton machines, where ensuring accurate charge may be challenging. Through perturbation of spot charge in treatment plans for seven patients and a phantom, we evaluated the dose impact of absolute (up to 5× 10 6 protons) and relative (up to 30%) charge errors. We investigated the dependence on beam width by studying scenarios with small, medium and large beam sizes. Treatment plan statistics included the Γ passing rate, dose-volume-histograms and dose differences. The allowable absolute charge error for small spot plans was about 2× 10 6 protons. Larger limits would be allowed if larger spots were used. For relative errors, the maximum allowable error size for small, medium and large spots was about 13%, 8% and 6% for small, medium and large spots, respectively. Dose distributions turned out to be surprisingly robust against random spot charge perturbation. Our study suggests that ensuring spot charge errors as small as 1-2% as is commonly aimed at in conventional proton therapy machines, is clinically not strictly needed. © 2017 American Association of Physicists in Medicine.

Residential energy use and potential conservation through reduced laundering temperatures in the United States and Canada.

PubMed

Sabaliunas, Darius; Pittinger, Charles; Kessel, Cristy; Masscheleyn, Patrick

2006-04-01

A residential energy-use model was developed to estimate energy budgets for household laundering practices in the United States and Canada. The thermal energy for heating water and mechanical energy for agitating clothes in conventional washing machines were calculated for representative households in the United States and Canada. Comparisons in energy consumption among hot-, warm-, and cold-water wash and rinse cycles, horizontal- and vertical-axis washing machines, and gas and electric water heaters, were calculated on a per-wash-load basis. Demographic data for current laundering practices in the United States and Canada were then incorporated to estimate household and national energy consumption on an annual basis for each country. On average, the thermal energy required to heat water using either gas or electric energy constitutes 80% to 85% of the total energy consumed per wash in conventional, vertical-axis (top-loading) washing machines. The balance of energy used is mechanical energy. Consequently, the potential energy savings per load in converting from hot-and-warm- to cold-wash temperatures can be significant. Annual potential energy and cost savings and reductions in carbon dioxide emissions are also estimated for each country, assuming full conversion to cold-wash water temperatures. This study provides useful information to consumers for conserving energy in the home, as well as to, manufacturers in the design of more energy-efficient laundry formulations and appliances.

The measurement of creep in ultrahigh molecular weight polyethylene: a comparison of conventional versus highly cross-linked polyethylene.

PubMed

Estok, Daniel M; Bragdon, Charles R; Plank, Gordon R; Huang, Anna; Muratoglu, Orhun K; Harris, William H

2005-02-01

Quantification of creep of highly cross-linked polyethylene would enable separation of creep from wear when evaluating femoral head penetration into polyethylene. We compared creep magnitude of a highly cross-linked versus conventional polyethylene in the laboratory. Twelve acetabular liners of each material were tested, 6 of which had a 32-mm inner diameter (ID) and 6 had 28-mm ID. Creep was measured using coordinate measuring machines during loading at 2 Hz without motion to 4 million cycles. Penetration into 32-mm ID conventional liners reached 97 microm versus 107 microm for highly cross-linked material, not significant. Penetration into 28-mm conventional liners was 132 microm versus 155 microm for highly cross-linked material (P = .017). Ninety percent of the creep had occurred by 2.5 million cycles.

Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

NASA Astrophysics Data System (ADS)

Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

2018-03-01

Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p < 0.05) and odds ratio was 4.60 with a 95% confidence interval of [3.16, 6.70]. Study demonstrated that this new LPP-based feature regeneration approach enabled to produce an optimal feature vector and yield improved performance in assisting to predict risk of women having breast cancer detected in the next subsequent mammography screening.

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods

PubMed Central

Burlina, Philippe; Billings, Seth; Joshi, Neil

2017-01-01

Objective To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Methods Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and “engineered” features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. Results The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). Conclusions This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification. PMID:28854220

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

PubMed

Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima

2017-01-01

To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

Smart material screening machines using smart materials and controls

NASA Astrophysics Data System (ADS)

Allaei, Daryoush; Corradi, Gary; Waigand, Al

2002-07-01

The objective of this product is to address the specific need for improvements in the efficiency and effectiveness in physical separation technologies in the screening areas. Currently, the mining industry uses approximately 33 billion kW-hr per year, costing 1.65 billion dollars at 0.05 cents per kW-hr, of electrical energy for physical separations. Even though screening and size separations are not the single most energy intensive process in the mining industry, they are often the major bottleneck in the whole process. Improvements to this area offer tremendous potential in both energy savings and production improvements. Additionally, the vibrating screens used in the mining processing plants are the most costly areas from maintenance and worker health and safety point of views. The goal of this product is to reduce energy use in the screening and total processing areas. This goal is accomplished by developing an innovative screening machine based on smart materials and smart actuators, namely smart screen that uses advanced sensory system to continuously monitor the screening process and make appropriate adjustments to improve production. The theory behind the development of Smart Screen technology is based on two key technologies, namely smart actuators and smart Energy Flow ControlT (EFCT) strategies, developed initially for military applications. Smart Screen technology controls the flow of vibration energy and confines it to the screen rather than shaking much of the mass that makes up the conventional vibratory screening machine. Consequently, Smart Screens eliminates and downsizes many of the structural components associated with conventional vibratory screening machines. As a result, the surface area of the screen increases for a given envelope. This increase in usable screening surface area extends the life of the screens, reduces required maintenance by reducing the frequency of screen change-outs and improves throughput or productivity.

Paperless Braille Reading: A Preliminary Research Report.

ERIC Educational Resources Information Center

Bourgeois, M.; Ashcroft, S. C.

The study involving three blind elementary school, six blind high school, and four blind college students was designed to establish oral reading rates and oral reading error rates for Ss reading conventional braille volumes and brailled materials with the Digi-cassette, an electronic braille reading and writing machine. Data suggested several…

Development and Operation of a Database Machine for Online Access and Update of a Large Database.

ERIC Educational Resources Information Center

Rush, James E.

1980-01-01

Reviews the development of a fault tolerant database processor system which replaced OCLC's conventional file system. A general introduction to database management systems and the operating environment is followed by a description of the hardware selection, software processes, and system characteristics. (SW)

Teaching Conversations with the XDS Sigma 7. Systems Description.

ERIC Educational Resources Information Center

Bork, Alfred M.; Mosmann, Charles

Some computers permit conventional programing languages to be extended by the use of macro-instructions, a sophisticated programing tool which is especially useful in writing instructional dialogs. Macro-instructions (or "macro's") are complex commands defined in terms of the machine language or other macro-instructions. Like terms in…

Familiarity Vs Trust: A Comparative Study of Domain Scientists' Trust in Visual Analytics and Conventional Analysis Methods.

PubMed

Dasgupta, Aritra; Lee, Joon-Yong; Wilson, Ryan; Lafrance, Robert A; Cramer, Nick; Cook, Kristin; Payne, Samuel

2017-01-01

Combining interactive visualization with automated analytical methods like statistics and data mining facilitates data-driven discovery. These visual analytic methods are beginning to be instantiated within mixed-initiative systems, where humans and machines collaboratively influence evidence-gathering and decision-making. But an open research question is that, when domain experts analyze their data, can they completely trust the outputs and operations on the machine-side? Visualization potentially leads to a transparent analysis process, but do domain experts always trust what they see? To address these questions, we present results from the design and evaluation of a mixed-initiative, visual analytics system for biologists, focusing on analyzing the relationships between familiarity of an analysis medium and domain experts' trust. We propose a trust-augmented design of the visual analytics system, that explicitly takes into account domain-specific tasks, conventions, and preferences. For evaluating the system, we present the results of a controlled user study with 34 biologists where we compare the variation of the level of trust across conventional and visual analytic mediums and explore the influence of familiarity and task complexity on trust. We find that despite being unfamiliar with a visual analytic medium, scientists seem to have an average level of trust that is comparable with the same in conventional analysis medium. In fact, for complex sense-making tasks, we find that the visual analytic system is able to inspire greater trust than other mediums. We summarize the implications of our findings with directions for future research on trustworthiness of visual analytic systems.

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

PubMed

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

2012-05-01

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

MOD-2 wind turbine farm stability study

NASA Technical Reports Server (NTRS)

Hinrichsen, E. N.

1980-01-01

The dynamics of single and multiple 2.5 ME, Boeing MOD-2 wind turbine generators (WTGs) connected to utility power systems were investigated. The analysis was based on digital simulation. Both time response and frequency response methods were used. The dynamics of this type of WTG are characterized by two torsional modes, a low frequency 'shaft' mode below 1 Hz and an 'electrical' mode at 3-5 Hz. High turbine inertia and low torsional stiffness between turbine and generator are inherent features. Turbine control is based on electrical power, not turbine speed as in conventional utility turbine generators. Multi-machine dynamics differ very little from single machine dynamics.

Social and Economic Impact of Solar Electricity at Schuchuli Village

NASA Technical Reports Server (NTRS)

Bifano, W. J.; Ratajczak, A. F.; Bahr, D. M.; Garrett, B. G.

1979-01-01

Schuchuli, a small remote village on the Papago Indian Reservation in southwest Arizona, is 27 kilometers (17 miles) from the nearest available utility power. Its lack of conventional power is due to the prohibitive cost of supplying a small electrical load with a long-distance distribution line. Furthermore, alternate energy sources are expensive and place a burden on the resources of the villagers. On December 16, 1978, as part of a federally funded project, a solar cell power system was put into operation at Schuchuli. The system powers the village water pump, lighting for homes and other village buildings, family refrigerators and a communal washing machine and sewing machine.

Portable home hemodialysis for kidney failure.

PubMed

Scott, A

2007-11-01

(1) Home hemodialysis has been in limited use in Canada for some time. Newer, portable hemodialysis machines that are easier for patients to operate may encourage the uptake of this technology. (2) One portable system is already available in the US. The NxStage System One hemodialysis machine operates on standard electric current, does not require plumbing or specialized disinfection, and is small enough for patients to travel with. (3) It is not yet clear whether the use of the NxStage system improves long-term survival and quality of life. (4) Home hemodialysis is less costly than conventional in-centre programs, but it is unknown whether these savings extend to portable devices.

In-process fault detection for textile fabric production: onloom imaging

NASA Astrophysics Data System (ADS)

Neumann, Florian; Holtermann, Timm; Schneider, Dorian; Kulczycki, Ashley; Gries, Thomas; Aach, Til

2011-05-01

Constant and traceable high fabric quality is of high importance both for technical and for high-quality conventional fabrics. Usually, quality inspection is carried out by trained personal, whose detection rate and maximum period of concentration are limited. Low resolution automated fabric inspection machines using texture analysis were developed. Since 2003, systems for the in-process inspection on weaving machines ("onloom") are commercially available. With these defects can be detected, but not measured quantitative precisely. Most systems are also prone to inevitable machine vibrations. Feedback loops for fault prevention are not established. Technology has evolved since 2003: Camera and computer prices dropped, resolutions were enhanced, recording speeds increased. These are the preconditions for real-time processing of high-resolution images. So far, these new technological achievements are not used in textile fabric production. For efficient use, a measurement system must be integrated into the weaving process; new algorithms for defect detection and measurement must be developed. The goal of the joint project is the development of a modern machine vision system for nondestructive onloom fabric inspection. The system consists of a vibration-resistant machine integration, a high-resolution machine vision system, and new, reliable, and robust algorithms with quality database for defect documentation. The system is meant to detect, measure, and classify at least 80 % of economically relevant defects. Concepts for feedback loops into the weaving process will be pointed out.

Prediction of mortality after radical cystectomy for bladder cancer by machine learning techniques.

PubMed

Wang, Guanjin; Lam, Kin-Man; Deng, Zhaohong; Choi, Kup-Sze

2015-08-01

Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

Stereodivergent synthesis with a programmable molecular machine

NASA Astrophysics Data System (ADS)

Kassem, Salma; Lee, Alan T. L.; Leigh, David A.; Marcos, Vanesa; Palmer, Leoni I.; Pisano, Simone

2017-09-01

It has been convincingly argued that molecular machines that manipulate individual atoms, or highly reactive clusters of atoms, with Ångström precision are unlikely to be realized. However, biological molecular machines routinely position rather less reactive substrates in order to direct chemical reaction sequences, from sequence-specific synthesis by the ribosome to polyketide synthases, where tethered molecules are passed from active site to active site in multi-enzyme complexes. Artificial molecular machines have been developed for tasks that include sequence-specific oligomer synthesis and the switching of product chirality, a photo-responsive host molecule has been described that is able to mechanically twist a bound molecular guest, and molecular fragments have been selectively transported in either direction between sites on a molecular platform through a ratchet mechanism. Here we detail an artificial molecular machine that moves a substrate between different activating sites to achieve different product outcomes from chemical synthesis. This molecular robot can be programmed to stereoselectively produce, in a sequential one-pot operation, an excess of any one of four possible diastereoisomers from the addition of a thiol and an alkene to an α,β-unsaturated aldehyde in a tandem reaction process. The stereodivergent synthesis includes diastereoisomers that cannot be selectively synthesized through conventional iminium-enamine organocatalysis. We anticipate that future generations of programmable molecular machines may have significant roles in chemical synthesis and molecular manufacturing.

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

PubMed

Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

2018-04-30

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

A model predictive current control of flux-switching permanent magnet machines for torque ripple minimization

NASA Astrophysics Data System (ADS)

Huang, Wentao; Hua, Wei; Yu, Feng

2017-05-01

Due to high airgap flux density generated by magnets and the special double salient structure, the cogging torque of the flux-switching permanent magnet (FSPM) machine is considerable, which limits the further applications. Based on the model predictive current control (MPCC) and the compensation control theory, a compensating-current MPCC (CC-MPCC) scheme is proposed and implemented to counteract the dominated components in cogging torque of an existing three-phase 12/10 FSPM prototyped machine, and thus to alleviate the influence of the cogging torque and improve the smoothness of electromagnetic torque as well as speed, where a comprehensive cost function is designed to evaluate the switching states. The simulated results indicate that the proposed CC-MPCC scheme can suppress the torque ripple significantly and offer satisfactory dynamic performances by comparisons with the conventional MPCC strategy. Finally, experimental results validate both the theoretical and simulated predictions.

Applications of high power lasers. [using reflection holograms for machining and surface treatment

NASA Technical Reports Server (NTRS)

Angus, J. C.

1979-01-01

The use of computer generated, reflection holograms in conjunction with high power lasers for precision machining of metals and ceramics was investigated. The Reflection holograms which were developed and made to work at both optical wavelength (He-Ne, 6328 A) and infrared (CO2, 10.6) meet the primary practical requirement of ruggedness and are relatively economical and simple to fabricate. The technology is sufficiently advanced now so that reflection holography could indeed be used as a practical manufacturing device in certain applications requiring low power densities. However, the present holograms are energy inefficient and much of the laser power is lost in the zero order spot and higher diffraction orders. Improvements of laser machining over conventional methods are discussed and addition applications are listed. Possible uses in the electronics industry include drilling holes in printed circuit boards making soldered connections, and resistor trimming.

A Java-based enterprise system architecture for implementing a continuously supported and entirely Web-based exercise solution.

PubMed

Wang, Zhihui; Kiryu, Tohru

2006-04-01

Since machine-based exercise still uses local facilities, it is affected by time and place. We designed a web-based system architecture based on the Java 2 Enterprise Edition that can accomplish continuously supported machine-based exercise. In this system, exercise programs and machines are loosely coupled and dynamically integrated on the site of exercise via the Internet. We then extended the conventional health promotion model, which contains three types of players (users, exercise trainers, and manufacturers), by adding a new player: exercise program creators. Moreover, we developed a self-describing strategy to accommodate a variety of exercise programs and provide ease of use to users on the web. We illustrate our novel design with examples taken from our feasibility study on a web-based cycle ergometer exercise system. A biosignal-based workload control approach was introduced to ensure that users performed appropriate exercise alone.

Robust iterative learning contouring controller with disturbance observer for machine tool feed drives.

PubMed

Simba, Kenneth Renny; Bui, Ba Dinh; Msukwa, Mathew Renny; Uchiyama, Naoki

2018-04-01

In feed drive systems, particularly machine tools, a contour error is more significant than the individual axial tracking errors from the view point of enhancing precision in manufacturing and production systems. The contour error must be within the permissible tolerance of given products. In machining complex or sharp-corner products, large contour errors occur mainly owing to discontinuous trajectories and the existence of nonlinear uncertainties. Therefore, it is indispensable to design robust controllers that can enhance the tracking ability of feed drive systems. In this study, an iterative learning contouring controller consisting of a classical Proportional-Derivative (PD) controller and disturbance observer is proposed. The proposed controller was evaluated experimentally by using a typical sharp-corner trajectory, and its performance was compared with that of conventional controllers. The results revealed that the maximum contour error can be reduced by about 37% on average. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Laser processing of ceramics for microelectronics manufacturing

NASA Astrophysics Data System (ADS)

Sposili, Robert S.; Bovatsek, James; Patel, Rajesh

2017-03-01

Ceramic materials are used extensively in the microelectronics, semiconductor, and LED lighting industries because of their electrically insulating and thermally conductive properties, as well as for their high-temperature-service capabilities. However, their brittleness presents significant challenges for conventional machining processes. In this paper we report on a series of experiments that demonstrate and characterize the efficacy of pulsed nanosecond UV and green lasers in machining ceramics commonly used in microelectronics manufacturing, such as aluminum oxide (alumina) and aluminum nitride. With a series of laser pocket milling experiments, fundamental volume ablation rate and ablation efficiency data were generated. In addition, techniques for various industrial machining processes, such as shallow scribing and deep scribing, were developed and demonstrated. We demonstrate that lasers with higher average powers offer higher processing rates with the one exception of deep scribes in aluminum nitride, where a lower average power but higher pulse energy source outperformed a higher average power laser.

Potential application of machine learning in health outcomes research and some statistical cautions.

PubMed

Crown, William H

2015-03-01

Traditional analytic methods are often ill-suited to the evolving world of health care big data characterized by massive volume, complexity, and velocity. In particular, methods are needed that can estimate models efficiently using very large datasets containing healthcare utilization data, clinical data, data from personal devices, and many other sources. Although very large, such datasets can also be quite sparse (e.g., device data may only be available for a small subset of individuals), which creates problems for traditional regression models. Many machine learning methods address such limitations effectively but are still subject to the usual sources of bias that commonly arise in observational studies. Researchers using machine learning methods such as lasso or ridge regression should assess these models using conventional specification tests. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

NASA Astrophysics Data System (ADS)

Zhu, Kunpeng; Wong, Yoke San; Hong, Geok Soon

2009-02-01

In-process monitoring of tool conditions is important in micro-machining due to the high precision requirement and high tool wear rate. Tool condition monitoring in micro-machining poses new challenges compared to conventional machining. In this paper, a multi-category classification approach is proposed for tool flank wear state identification in micro-milling. Continuous Hidden Markov models (HMMs) are adapted for modeling of the tool wear process in micro-milling, and estimation of the tool wear state given the cutting force features. For a noise-robust approach, the HMM outputs are connected via a medium filter to minimize the tool state before entry into the next state due to high noise level. A detailed study on the selection of HMM structures for tool condition monitoring (TCM) is presented. Case studies on the tool state estimation in the micro-milling of pure copper and steel demonstrate the effectiveness and potential of these methods.

Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

NASA Astrophysics Data System (ADS)

Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

2015-10-01

In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

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

Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar

With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual modelmore » has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.« less

The influence of Span-20 surfactant and micro-/nano-Chromium (Cr) Powder Mixed Electrical Discharge Machining (PMEDM) on the surface characteristics of AISI D2 hardened steel

NASA Astrophysics Data System (ADS)

Hosni, N. A. J.; Lajis, M. A.

2018-04-01

The application of powder mixed dielectric to improve the efficiency of electrical discharge machining (EDM) has been extensively studied. Therefore, PMEDM have attracted the attention of many researchers since last few decades. Improvement in EDM process has resulted in the use of span-20 surfactant and Cr powder mixed in dielectric fluid, which results in increasing machiniability, better surface quality and faster machining time. However, the study of powder suspension size of surface charateristics in EDM field is still limited. This paper presents the improvement of micro-/nano- Cr powder size on the surface characteristics of the AISI D2 hardened steels in PMEDM. It has found that the reacst layer in PMEDM improved by as high as 41-53 % compared to conventional EDM. Also notably, the combination of added Cr powder and span-20 surfactant reduced the recast layer thickness significantly especially in nano-Cr size. This improvement was great potential adding nano-size Cr powder to dielectric for machining performance.

Investigation of tool wear and surface roughness on machining of titanium alloy with MT-CVD cutting tool

NASA Astrophysics Data System (ADS)

Maity, Kalipada; Pradhan, Swastik

2018-04-01

In this study, machining of titanium alloy (grade 5) is carried out using MT-CVD coated cutting tool. Titanium alloys possess superior strength-to-weight ratio with good corrosion resistance. Most of the industries used titanium alloy for the manufacturing of various types of lightweight components. The parts made from Ti-6Al-4V largely used in aerospace, biomedical, automotive and marine sectors. The conventional machining of this material is very difficult, due to low thermal conductivity and high chemical reactivity properties. To achieve a good surface finish with minimum tool wear of cutting tool, the machining is carried out using MT-CVD coated cutting tool. The experiment is carried out using of Taguchi L27 array layout with three cutting variables and levels. To find out the optimum parametric setting desirability function analysis (DFA) approach is used. The analysis of variance is studied to know the percentage contribution of each cutting variables. The optimum parametric setting results calculated from DFA were validated through the confirmation test.

Preventing chatter vibrations in heavy-duty turning operations in large horizontal lathes

NASA Astrophysics Data System (ADS)

Urbikain, G.; Campa, F.-J.; Zulaika, J.-J.; López de Lacalle, L.-N.; Alonso, M.-A.; Collado, V.

2015-03-01

Productivity and surface finish are typical user manufacturer requirements that are restrained by chatter vibrations sooner or later in every machining operation. Thus, manufacturers are interested in knowing, before building the machine, the dynamic behaviour of each machine structure with respect to another. Stability lobe graphs are the most reliable approach to analyse the dynamic performance. During heavy rough turning operations a model containing (a) several modes, or (b) modes with non-conventional (Cartesian) orientations is necessary. This work proposes two methods which are combined with multimode analysis to predict chatter in big horizontal lathes. First, a traditional single frequency model (SFM) is used. Secondly, the modern collocation method based on the Chebyshev polynomials (CCM) is alternatively studied. The models can be used to identify the machine design features limiting lathe productivity, as well as the threshold values for choosing good cutting parameters. The results have been compared with experimental tests in a horizontal turning centre. Besides the model and approach, this work offers real worthy values for big lathes, difficult to be got from literature.

PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

PubMed

Koul, Atesh; Becchio, Cristina; Cavallo, Andrea

2017-12-12

Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional univariate techniques, they still lack an established and accessible implementation. The aim of current work was to build an open-source R toolbox - "PredPsych" - that could make these methods readily available to all psychologists. PredPsych is a user-friendly, R toolbox based on machine-learning predictive algorithms. In this paper, we present the framework of PredPsych via the analysis of a recently published multiple-subject motion capture dataset. In addition, we discuss examples of possible research questions that can be addressed with the machine-learning algorithms implemented in PredPsych and cannot be easily addressed with univariate statistical analysis. We anticipate that PredPsych will be of use to researchers with limited programming experience not only in the field of psychology, but also in that of clinical neuroscience, enabling computational assessment of putative bio-behavioral markers for both prognosis and diagnosis.

Evaluating data distribution and drift vulnerabilities of machine learning algorithms in secure and adversarial environments

NASA Astrophysics Data System (ADS)

Nelson, Kevin; Corbin, George; Blowers, Misty

2014-05-01

Machine learning is continuing to gain popularity due to its ability to solve problems that are difficult to model using conventional computer programming logic. Much of the current and past work has focused on algorithm development, data processing, and optimization. Lately, a subset of research has emerged which explores issues related to security. This research is gaining traction as systems employing these methods are being applied to both secure and adversarial environments. One of machine learning's biggest benefits, its data-driven versus logic-driven approach, is also a weakness if the data on which the models rely are corrupted. Adversaries could maliciously influence systems which address drift and data distribution changes using re-training and online learning. Our work is focused on exploring the resilience of various machine learning algorithms to these data-driven attacks. In this paper, we present our initial findings using Monte Carlo simulations, and statistical analysis, to explore the maximal achievable shift to a classification model, as well as the required amount of control over the data.

The Value of Data and Metadata Standardization for Interoperability in Giovanni

NASA Astrophysics Data System (ADS)

Smit, C.; Hegde, M.; Strub, R. F.; Bryant, K.; Li, A.; Petrenko, M.

2017-12-01

Giovanni (https://giovanni.gsfc.nasa.gov/giovanni/) is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization. This poster gives examples of how our metadata and data standards, both external and internal, have both simplified our code base and improved our users' experiences.

Function modeling improves the efficiency of spatial modeling using big data from remote sensing

Treesearch

John Hogland; Nathaniel Anderson

2017-01-01

Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have...

Improved analyses using function datasets and statistical modeling

Treesearch

John S. Hogland; Nathaniel M. Anderson

2014-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space and have limited statistical functionality and machine learning algorithms. To address this issue, we developed a new modeling framework using C# and ArcObjects and integrated that framework...

Unconventional Wisdom about Buying Technology

ERIC Educational Resources Information Center

Sullivan, Michael F.

2004-01-01

Conventional wisdom says that people should not buy anything in education until research is seen. The following questions should be asked: (1) Does that particular technology enhance learning? (2) Does that piece of software increase test scores? and (3) Do those machines reduce absenteeism? Of course the answer is always yes. No vendor is going…

Cleaning With Supercritical CO2

NASA Technical Reports Server (NTRS)

Herzstock, James J.

1990-01-01

Supercritical carbon dioxide effective industrial cleaning agent. Replaces conventional halocarbon solvents for degreasing parts becoming coated with oil during such manufacturing procedures as forming and machining. Presents none of environmental threats and occupational hazards associated with halocarbon solvents. Spontaneously evaporates after use and leaves no waste to be disposed of. Evaporated gas readily collected and recycled.

Does the Holland Code Predict Job Satisfaction and Productivity in Clothing Factory Workers?

ERIC Educational Resources Information Center

Heesacker, Martin; And Others

1988-01-01

Administered Self-Directed Search to sewing machine operators to determine Holland code, and assessed work productivity, job satisfaction, absenteeism, and insurance claims. Most workers were of the Social code. Social subjects were the most satisfied, Conventional and Realistic subjects next, and subjects of other codes less so. Productivity of…

Short guide to SDI profiling at ORNL

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

Pomerance, H.S.

1976-06-01

ORNL has machine-searchable data bases that correspond to printed indexes and abstracts. This guide describes the peculiarities of those several data bases and the conventions of the ORNL search system so that users can write their own queries or search profiles and can interpret the part of the output that is encoded.

Shielded cables with optimal braided shields

NASA Astrophysics Data System (ADS)

Homann, E.

1991-01-01

Extensive tests were done in order to determine what factors govern the design of braids with good shielding effectiveness. The results are purely empirical and relate to the geometrical relationships between the braid parameters. The influence of various parameters on the shape of the transfer impedance versus frequency curve were investigated step by step. It was found that the optical coverage had been overestimated in the past. Good shielding effectiveness results not from high optical coverage as such, but from the proper type of coverage, which is a function of the braid angle and the element width. These dependences were measured for the ordinary range of braid angles (20 to 40 degrees). They apply to all plaiting machines and all gages of braid wire. The design rules are largely the same for bright, tinned, silver-plated and even lacquered copper wires. A new type of braid, which has marked advantages over the conventional design, was proposed. With the 'mixed-element' technique, an optimal braid design can be specified on any plaiting machine, for any possible cable diameter, and for any desired angle. This is not possible for the conventional type of braid.

Comparative investigation of smooth polycrystalline diamond films on dental burs by chemical vapor deposition

NASA Astrophysics Data System (ADS)

Sein, Htet; Ahmed, Waqar; Rego, Christopher; Jackson, Mark; Polini, Riccardo

2006-04-01

Depositions of hot filament chemical vapor-deposited diamond on cobalt-cemented tungsten carbide (WC-Co) rotary cutting dental burs are presented. Conventional dental tools made of sintered polycrystalline diamond have a number of problems associated with the heterogeneity of the crystallite, decreased cutting efficiency, and short life. A preferential (111) faceted diamond was obtained after 15 h of deposition at a growth rate of 1.1 µm/h. Diamond-coated WC-Co dental burs and conventional sintered burs are mainly used in turning, milling, and drilling operations for machining metal ceramic hard alloys such as CoCr, composite teeth, and aluminum alloy in the dental laboratory. The influence of structure, the mechanical characteristics of both diamond grains and hard alloys on the wear behavior, as well as the regimen of grinding on diamond wear are considered. Erosion wear properties are also investigated under air-sand erosion testing. After machining with excessive cutting performance, calculations can be made on flank and crater wear areas. Diamond-coated WC-Co dental burs offered significantly better erosion and wear resistance compared with uncoated WC-Co tools and sintered burs.

Study of support vector machine and serum surface-enhanced Raman spectroscopy for noninvasive esophageal cancer detection

NASA Astrophysics Data System (ADS)

Li, Shao-Xin; Zeng, Qiu-Yao; Li, Lin-Fang; Zhang, Yan-Jiao; Wan, Ming-Ming; Liu, Zhi-Ming; Xiong, Hong-Lian; Guo, Zhou-Yi; Liu, Song-Hao

2013-02-01

The ability of combining serum surface-enhanced Raman spectroscopy (SERS) with support vector machine (SVM) for improving classification esophageal cancer patients from normal volunteers is investigated. Two groups of serum SERS spectra based on silver nanoparticles (AgNPs) are obtained: one group from patients with pathologically confirmed esophageal cancer (n=30) and the other group from healthy volunteers (n=31). Principal components analysis (PCA), conventional SVM (C-SVM) and conventional SVM combination with PCA (PCA-SVM) methods are implemented to classify the same spectral dataset. Results show that a diagnostic accuracy of 77.0% is acquired for PCA technique, while diagnostic accuracies of 83.6% and 85.2% are obtained for C-SVM and PCA-SVM methods based on radial basis functions (RBF) models. The results prove that RBF SVM models are superior to PCA algorithm in classification serum SERS spectra. The study demonstrates that serum SERS in combination with SVM technique has great potential to provide an effective and accurate diagnostic schema for noninvasive detection of esophageal cancer.

Point-of-care testing in the early diagnosis of acute pesticide intoxication: The example of paraquat.

PubMed

Wei, Ting-Yen; Yen, Tzung-Hai; Cheng, Chao-Min

2018-01-01

Acute pesticide intoxication is a common method of suicide globally. This article reviews current diagnostic methods and makes suggestions for future development. In the case of paraquat intoxication, it is characterized by multi-organ failure, causing substantial mortality and morbidity. Early diagnosis may save the life of a paraquat intoxication patient. Conventional paraquat intoxication diagnostic methods, such as symptom review and urine sodium dithionite assay, are time-consuming and impractical in resource-scarce areas where most intoxication cases occur. Several experimental and clinical studies have shown the potential of portable Surface Enhanced Raman Scattering (SERS), paper-based devices, and machine learning for paraquat intoxication diagnosis. Portable SERS and new SERS substrates maintain the sensitivity of SERS while being less costly and more convenient than conventional SERS. Paper-based devices provide the advantages of price and portability. Machine learning algorithms can be implemented as a mobile phone application and facilitate diagnosis in resource-limited areas. Although these methods have not yet met all features of an ideal diagnostic method, the combination and development of these methods offer much promise.

A Constant-Force Resistive Exercise Unit

NASA Technical Reports Server (NTRS)

Colosky, Paul; Ruttley, Tara

2010-01-01

A constant-force resistive exercise unit (CFREU) has been invented for use in both normal gravitational and microgravitational environments. In comparison with a typical conventional exercise machine, this CFREU weighs less and is less bulky: Whereas weight plates and associated bulky supporting structures are used to generate resistive forces in typical conventional exercise machines, they are not used in this CFREU. Instead, resistive forces are generated in this CFREU by relatively compact, lightweight mechanisms based on constant-torque springs wound on drums. Each such mechanism is contained in a module, denoted a resistive pack, that includes a shaft for making a torque connection to a cable drum. During a stroke of resistive exercise, the cable is withdrawn from the cable drum against the torque exerted by the resistance pack. The CFREU includes a housing, within which can be mounted one or more resistive pack(s). The CFREU also includes mechanisms for engaging any combination of (1) one or more resistive pack(s) and (2) one or more spring(s) within each resistive pack to obtain a desired level of resistance.

FOCIS: A forest classification and inventory system using LANDSAT and digital terrain data

NASA Technical Reports Server (NTRS)

Strahler, A. H.; Franklin, J.; Woodcook, C. E.; Logan, T. L.

1981-01-01

Accurate, cost-effective stratification of forest vegetation and timber inventory is the primary goal of a Forest Classification and Inventory System (FOCIS). Conventional timber stratification using photointerpretation can be time-consuming, costly, and inconsistent from analyst to analyst. FOCIS was designed to overcome these problems by using machine processing techniques to extract and process tonal, textural, and terrain information from registered LANDSAT multispectral and digital terrain data. Comparison of samples from timber strata identified by conventional procedures showed that both have about the same potential to reduce the variance of timber volume estimates over simple random sampling.

An efficient parallel algorithm for the solution of a tridiagonal linear system of equations

NASA Technical Reports Server (NTRS)

Stone, H. S.

1971-01-01

Tridiagonal linear systems of equations are solved on conventional serial machines in a time proportional to N, where N is the number of equations. The conventional algorithms do not lend themselves directly to parallel computations on computers of the ILLIAC IV class, in the sense that they appear to be inherently serial. An efficient parallel algorithm is presented in which computation time grows as log sub 2 N. The algorithm is based on recursive doubling solutions of linear recurrence relations, and can be used to solve recurrence relations of all orders.

Sensors of vibration and acoustic emission for monitoring of boring with skiving cutters

NASA Astrophysics Data System (ADS)

Shamarin, N. N.; Filippov, A. V.; Podgornyh, O. A.; Filippova, E. O.

2017-01-01

Diagnosing processing system conditions is a key area in automation of modern machinery production. The article presents the results of a preliminary experimental research of the boring process using conventional and skiving cutters under the conditions of the low stiffness processing system. Acoustic emission and vibration sensors are used for cutting process diagnosis. Surface roughness after machining is determined using a laser scanning microscope. As a result, it is found that the use of skiving cutters provides greater stability of the cutting process and lower surface roughness as compared with conventional cutters.

Hacker tracking Security system for HMI

NASA Astrophysics Data System (ADS)

Chauhan, Rajeev Kumar

2011-12-01

Conventional Supervisory control and data Acquisition (SCADA) systems use PC, notebook, thin client, and PDA as a Client. Nowadays the Process Industries are following multi shift system that's why multi- client of different category have to work at a single human Machine Interface (HMI). They may hack the HMI Display and change setting of the other client. This paper introduces a Hacker tracking security (HTS) System for HMI. This is developed by using the conventional and Biometric authentication. HTS system is developed by using Numeric passwords, Smart card, biometric, blood flow and Finger temperature. This work is also able to identify the hackers.

MO-FG-CAMPUS-TeP3-04: Deliverable Robust Optimization in IMPT Using Quadratic Objective Function

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

Shan, J; Liu, W; Bues, M

Purpose: To find and evaluate the way of applying deliverable MU constraints into robust spot intensity optimization in Intensity-Modulated- Proton-Therapy (IMPT) to prevent plan quality and robustness from degrading due to machine deliverable MU-constraints. Methods: Currently, the influence of the deliverable MU-constraints is retrospectively evaluated by post-processing immediately following optimization. In this study, we propose a new method based on the quasi-Newton-like L-BFGS-B algorithm with which we turn deliverable MU-constraints on and off alternatively during optimization. Seven patients with two different machine settings (small and large spot size) were planned with both conventional and new methods. For each patient, threemore » kinds of plans were generated — conventional non-deliverable plan (plan A), conventional deliverable plan with post-processing (plan B), and new deliverable plan (plan C). We performed this study with both realistic (small) and artificial (large) deliverable MU-constraints. Results: With small minimum MU-constraints considered, new method achieved a slightly better plan quality than conventional method (D95% CTV normalized to the prescription dose: 0.994[0.992∼0.996] (Plan C) vs 0.992[0.986∼0.996] (Plan B)). With large minimum MU constraints considered, results show that the new method maintains plan quality while plan quality from the conventional method is degraded greatly (D95% CTV normalized to the prescription dose: 0.987[0.978∼0.994] (Plan C) vs 0.797[0.641∼1.000] (Plan B)). Meanwhile, plan robustness of these two method’s results is comparable. (For all 7 patients, CTV DVH band gap at D95% normalized to the prescription dose: 0.015[0.005∼0.043] (Plan C) vs 0.012[0.006∼0.038] (Plan B) with small MU-constraints and 0.019[0.009∼0.039] (Plan C) vs 0.030[0.015∼0.041] (Plan B) with large MU-constraints) Conclusion: Positive correlation has been found between plan quality degeneration and magnitude of deliverable minimal MU. Compared to conventional post-processing method, our new method of incorporating deliverable minimal MU-constraints directly into plan optimization, can produce machine-deliverable plans with better plan qualities and non-compromised plan robustness. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant and by The Kemper Marley Foundation.« less

ODISEES: A New Paradigm in Data Access

NASA Astrophysics Data System (ADS)

Huffer, E.; Little, M. M.; Kusterer, J.

2013-12-01

As part of its ongoing efforts to improve access to data, the Atmospheric Science Data Center has developed a high-precision Earth Science domain ontology (the 'ES Ontology') implemented in a graph database ('the Semantic Metadata Repository') that is used to store detailed, semantically-enhanced, parameter-level metadata for ASDC data products. The ES Ontology provides the semantic infrastructure needed to drive the ASDC's Ontology-Driven Interactive Search Environment for Earth Science ('ODISEES'), a data discovery and access tool, and will support additional data services such as analytics and visualization. The ES ontology is designed on the premise that naming conventions alone are not adequate to provide the information needed by prospective data consumers to assess the suitability of a given dataset for their research requirements; nor are current metadata conventions adequate to support seamless machine-to-machine interactions between file servers and end-user applications. Data consumers need information not only about what two data elements have in common, but also about how they are different. End-user applications need consistent, detailed metadata to support real-time data interoperability. The ES ontology is a highly precise, bottom-up, queriable model of the Earth Science domain that focuses on critical details about the measurable phenomena, instrument techniques, data processing methods, and data file structures. Earth Science parameters are described in detail in the ES Ontology and mapped to the corresponding variables that occur in ASDC datasets. Variables are in turn mapped to well-annotated representations of the datasets that they occur in, the instrument(s) used to create them, the instrument platforms, the processing methods, etc., creating a linked-data structure that allows both human and machine users to access a wealth of information critical to understanding and manipulating the data. The mappings are recorded in the Semantic Metadata Repository as RDF-triples. An off-the-shelf Ontology Development Environment and a custom Metadata Conversion Tool comprise a human-machine/machine-machine hybrid tool that partially automates the creation of metadata as RDF-triples by interfacing with existing metadata repositories and providing a user interface that solicits input from a human user, when needed. RDF-triples are pushed to the Ontology Development Environment, where a reasoning engine executes a series of inference rules whose antecedent conditions can be satisfied by the initial set of RDF-triples, thereby generating the additional detailed metadata that is missing in existing repositories. A SPARQL Endpoint, a web-based query service and a Graphical User Interface allow prospective data consumers - even those with no familiarity with NASA data products - to search the metadata repository to find and order data products that meet their exact specifications. A web-based API will provide an interface for machine-to-machine transactions.

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

Saleh, Z; Tang, X; Song, Y

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

Healthier snacks in school vending machines: a pilot project in four Ontario high schools.

PubMed

Callaghan, Christine; Mandich, Gillian; He, Meizi

2010-01-01

The Healthy Vending Machine Pilot Project (HVMPP) was a public health initiative intended to create a healthier school nutrition environment by making healthier snacks available in vending machines, while maintaining a profit margin. The HVMPP was evaluated using quantitative and qualitative measures. Vending machines were stocked with healthier choices and conventional vending products at a 50:50 ratio. The HVMPP was implemented from February to May 2007 in four Ontario secondary schools in Middlesex-London, Elgin, and Oxford counties. Product sales were tracked, and focus groups were conducted to obtain students' opinions about healthy eating and vending choices. "Healthier choice" sales ranged from 14% to 17%. In all schools, vending revenues declined from 0.7% to 66%. A majority of participants had substantial knowledge of healthy eating and were in favour of healthier choices in vending machines; however, price, value, and taste were barriers that led them to purchase these products rarely. Students preferred to have "real" healthy snacks, such as yogurt, fruit, and vegetables, available in schools. Replacing 50% of vending stock with healthier snacks resulted in a decline in vending revenues. Future health programs in schools need to provide "real" healthy snacks, such as low-fat dairy products, fruits, and vegetables.

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

PubMed

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

2011-01-01

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

Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Classification of highly unbalanced CYP450 data of drugs using cost sensitive machine learning techniques.

PubMed

Eitrich, T; Kless, A; Druska, C; Meyer, W; Grotendorst, J

2007-01-01

In this paper, we study the classifications of unbalanced data sets of drugs. As an example we chose a data set of 2D6 inhibitors of cytochrome P450. The human cytochrome P450 2D6 isoform plays a key role in the metabolism of many drugs in the preclinical drug discovery process. We have collected a data set from annotated public data and calculated physicochemical properties with chemoinformatics methods. On top of this data, we have built classifiers based on machine learning methods. Data sets with different class distributions lead to the effect that conventional machine learning methods are biased toward the larger class. To overcome this problem and to obtain sensitive but also accurate classifiers we combine machine learning and feature selection methods with techniques addressing the problem of unbalanced classification, such as oversampling and threshold moving. We have used our own implementation of a support vector machine algorithm as well as the maximum entropy method. Our feature selection is based on the unsupervised McCabe method. The classification results from our test set are compared structurally with compounds from the training set. We show that the applied algorithms enable the effective high throughput in silico classification of potential drug candidates.

A novel flux-switching permanent magnet machine with v-shaped magnets

NASA Astrophysics Data System (ADS)

Zhao, Guishu; Hua, Wei

2017-05-01

In this paper, firstly a novel 6-stator-coil/17-rotor-pole (6/17) flux-switching permanent magnet (FSPM) machine with V-shaped magnets, deduced from conventional 12/17 FSPM machines is proposed to achieve more symmetrical phase back-electromotive force (back-EMF), and smaller torque ripple by comparing with an existing 6/10 V-shaped FSPM machine. Then, to obtain larger electromagnetic torque, less torque ripple, and easier mechanical processing, two improved variants based on the original 6/17 V-shaped topology are proposed. For the first variant, the separate stator-core segments located on the stator yoke are connected into a united stator yoke, while for the second variant the stator core is a whole entity by adding magnetic bridges at the ends of permanent magnets (PMs). Consequently, the performances of the three 6/17 V-shaped FSPM machines, namely, the original one and the two variants, are conducted by finite element analysis (FEA). The results reveal that the first variant exhibits significantly larger torque and considerably improved torque per magnet volume, i.e., the magnet utilization ratio than the original one, and the second variant exhibits the smallest torque ripple, least total harmonic distribution (THD) of phase back-EMF, and easiest mechanical processing for manufacturing.

Optimization of Gas Composition Used in Plasma Chemical Vaporization Machining for Figuring of Reaction-Sintered Silicon Carbide with Low Surface Roughness.

PubMed

Sun, Rongyan; Yang, Xu; Ohkubo, Yuji; Endo, Katsuyoshi; Yamamura, Kazuya

2018-02-05

In recent years, reaction-sintered silicon carbide (RS-SiC) has been of interest in many engineering fields because of its excellent properties, such as its light weight, high rigidity, high heat conductance and low coefficient of thermal expansion. However, RS-SiC is difficult to machine owing to its high hardness and chemical inertness and because it contains multiple components. To overcome the problem of the poor machinability of RS-SiC in conventional machining, the application of atmospheric-pressure plasma chemical vaporization machining (AP-PCVM) to RS-SiC was proposed. As a highly efficient and damage-free figuring technique, AP-PCVM has been widely applied for the figuring of single-component materials, such as Si, SiC, quartz crystal wafers, and so forth. However, it has not been applied to RS-SiC since it is composed of multiple components. In this study, we investigated the AP-PCVM etching characteristics for RS-SiC by optimizing the gas composition. It was found that the different etching rates of the different components led to a large surface roughness. A smooth surface was obtained by applying the optimum gas composition, for which the etching rate of the Si component was equal to that of the SiC component.

Resolution improvement of 3D stereo-lithography through the direct laser trajectory programming: Application to microfluidic deterministic lateral displacement device.

PubMed

Juskova, Petra; Ollitrault, Alexis; Serra, Marco; Viovy, Jean-Louis; Malaquin, Laurent

2018-02-13

The vast majority of current microfluidic devices are produced using soft lithography, a technique with strong limitations regarding the fabrication of three-dimensional architectures. Additive manufacturing holds great promises to overcome these limitations, but conventional machines still lack the resolution required by most microfluidic applications. 3D printing machines based on two-photon lasers, in contrast, have the needed resolution but are too limited in speed and size of the global device. Here we demonstrate how the resolution of conventional stereolithographic machines can be improved by a direct programming of the laser path and can contribute to bridge the gap between the two above technologies, allowing the direct printing of features between 10 and 100 μm, corresponding to a large fraction of microfluidic applications. This strategy allows to achieve resolutions limited only by the physical size of the laser beam, decreasing by a factor at least 2× the size of the smallest features printable, and increasing their reproducibility by a factor 5. The approach was applied to produce an open microfluidic device with the reversible seal, integrating periodical patterns using the simple motifs, and validated by the fabrication of a deterministic lateral displacement particles sorting device. The sorting of polystyrene beads (diameter: 20 μm and 45 μm) was achieved with a specificity >95%, comparable with that achieved with arrays prepared by microlithography. Copyright © 2017 Elsevier B.V. All rights reserved.

TIMSS 2011 Student and Teacher Predictors for Mathematics Achievement Explored and Identified via Elastic Net.

PubMed

Yoo, Jin Eun

2018-01-01

A substantial body of research has been conducted on variables relating to students' mathematics achievement with TIMSS. However, most studies have employed conventional statistical methods, and have focused on selected few indicators instead of utilizing hundreds of variables TIMSS provides. This study aimed to find a prediction model for students' mathematics achievement using as many TIMSS student and teacher variables as possible. Elastic net, the selected machine learning technique in this study, takes advantage of both LASSO and ridge in terms of variable selection and multicollinearity, respectively. A logistic regression model was also employed to predict TIMSS 2011 Korean 4th graders' mathematics achievement. Ten-fold cross-validation with mean squared error was employed to determine the elastic net regularization parameter. Among 162 TIMSS variables explored, 12 student and 5 teacher variables were selected in the elastic net model, and the prediction accuracy, sensitivity, and specificity were 76.06, 70.23, and 80.34%, respectively. This study showed that the elastic net method can be successfully applied to educational large-scale data by selecting a subset of variables with reasonable prediction accuracy and finding new variables to predict students' mathematics achievement. Newly found variables via machine learning can shed light on the existing theories from a totally different perspective, which in turn propagates creation of a new theory or complement of existing ones. This study also examined the current scale development convention from a machine learning perspective.

TIMSS 2011 Student and Teacher Predictors for Mathematics Achievement Explored and Identified via Elastic Net

PubMed Central

Yoo, Jin Eun

2018-01-01

A substantial body of research has been conducted on variables relating to students' mathematics achievement with TIMSS. However, most studies have employed conventional statistical methods, and have focused on selected few indicators instead of utilizing hundreds of variables TIMSS provides. This study aimed to find a prediction model for students' mathematics achievement using as many TIMSS student and teacher variables as possible. Elastic net, the selected machine learning technique in this study, takes advantage of both LASSO and ridge in terms of variable selection and multicollinearity, respectively. A logistic regression model was also employed to predict TIMSS 2011 Korean 4th graders' mathematics achievement. Ten-fold cross-validation with mean squared error was employed to determine the elastic net regularization parameter. Among 162 TIMSS variables explored, 12 student and 5 teacher variables were selected in the elastic net model, and the prediction accuracy, sensitivity, and specificity were 76.06, 70.23, and 80.34%, respectively. This study showed that the elastic net method can be successfully applied to educational large-scale data by selecting a subset of variables with reasonable prediction accuracy and finding new variables to predict students' mathematics achievement. Newly found variables via machine learning can shed light on the existing theories from a totally different perspective, which in turn propagates creation of a new theory or complement of existing ones. This study also examined the current scale development convention from a machine learning perspective. PMID:29599736

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

PubMed

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Imbalance aware lithography hotspot detection: a deep learning approach

NASA Astrophysics Data System (ADS)

Yang, Haoyu; Luo, Luyang; Su, Jing; Lin, Chenxi; Yu, Bei

2017-03-01

With the advancement of VLSI technology nodes, light diffraction caused lithographic hotspots have become a serious problem affecting manufacture yield. Lithography hotspot detection at the post-OPC stage is imperative to check potential circuit failures when transferring designed patterns onto silicon wafers. Although conventional lithography hotspot detection methods, such as machine learning, have gained satisfactory performance, with extreme scaling of transistor feature size and more and more complicated layout patterns, conventional methodologies may suffer from performance degradation. For example, manual or ad hoc feature extraction in a machine learning framework may lose important information when predicting potential errors in ultra-large-scale integrated circuit masks. In this paper, we present a deep convolutional neural network (CNN) targeting representative feature learning in lithography hotspot detection. We carefully analyze impact and effectiveness of different CNN hyper-parameters, through which a hotspot-detection-oriented neural network model is established. Because hotspot patterns are always minorities in VLSI mask design, the training data set is highly imbalanced. In this situation, a neural network is no longer reliable, because a trained model with high classification accuracy may still suffer from high false negative results (missing hotspots), which is fatal in hotspot detection problems. To address the imbalance problem, we further apply minority upsampling and random-mirror flipping before training the network. Experimental results show that our proposed neural network model achieves highly comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

Rotor compound concept for designing an industrial HTS synchronous motor

NASA Astrophysics Data System (ADS)

Kashani, M.; Hosseina, M.; Sarrafan, K.; Darabi, A.

2013-06-01

Recently, producing power with smaller amount of losses become as a goal in our daily life. Today, large amount of energy waste in power networks all around the world. The main reason is “resistive electric equipments” of power networks. Since early 1980s, simultaneous with the development of high temperature superconductive (HTS) technology, superconductors gently attracted the mankind attentions. Using superconductive equipments instead of conventional resistive ones are result in salient electric loss reduction in power systems. Especially to reduce losses in power networks superconductive industrial rotating machines can potentially perform a significant role. In early recent century, first generation of HTS rotating machines was born. But unfortunately they have long way to penetrate the commercial markets yet. In HTS rotating machines the conventional copper made windings are replaced with the HTS superconductors. In this paper an industrial HTS synchronous motor with YBCO coated conductor field windings was designed. As a new approach, model was equipped with a compound rotor that includes both magnetic and non-magnetic materials. So, large amount of heavy iron made part was replaced by light non-magnetic material such as G-10 fiberglass. Furthermore, in this structure iron loss in rotor could be reduced to its lowest value. Also less weight and more air gap energy density were the additional advantages. Regarding zero electric loss production in field windings and less iron loss in rotor construction, this model potentially is more effective than the other iron made HTS motors.

Core Muscle Activity, Exercise Preference, and Perceived Exertion during Core Exercise with Elastic Resistance versus Machine.

PubMed

Vinstrup, Jonas; Sundstrup, Emil; Brandt, Mikkel; Jakobsen, Markus D; Calatayud, Joaquin; Andersen, Lars L

2015-01-01

Objectives. To investigate core muscle activity, exercise preferences, and perceived exertion during two selected core exercises performed with elastic resistance versus a conventional training machine. Methods. 17 untrained men aged 26-67 years participated in surface electromyography (EMG) measurements of five core muscles during torso-twists performed from left to right with elastic resistance and in the machine, respectively. The order of the exercises was randomized and each exercise consisted of 3 repetitions performed at a 10 RM load. EMG amplitude was normalized (nEMG) to maximum voluntary isometric contraction (MVC). Results. A higher right erector spinae activity in the elastic exercise compared with the machine exercise (50% [95% CI 36-64] versus 32% [95% CI 18-46] nEMG) was found. By contrast, the machine exercise, compared with the elastic exercise, showed higher left external oblique activity (77% [95% CI 64-90] versus 54% [95% CI 40-67] nEMG). For the rectus abdominis, right external oblique, and left erector spinae muscles there were no significant differences. Furthermore, 76% preferred the torso-twist with elastic resistance over the machine exercise. Perceived exertion (Borg CR10) was not significantly different between machine (5.8 [95% CI 4.88-6.72]) and elastic exercise (5.7 [95% CI 4.81-6.59]). Conclusion. Torso-twists using elastic resistance showed higher activity of the erector spinae, whereas torso-twist in the machine resulted in higher activity of the external oblique. For the remaining core muscles the two training modalities induced similar muscular activation. In spite of similar perceived exertion the majority of the participants preferred the exercise using elastic resistance.

Experimental investigation into effect of cutting parameters on surface integrity of hardened tool steel

NASA Astrophysics Data System (ADS)

Bashir, K.; Alkali, A. U.; Elmunafi, M. H. S.; Yusof, N. M.

2018-04-01

Recent trend in turning hardened materials have gained popularity because of its immense machinability benefits. However, several machining processes like thermal assisted machining and cryogenic machining have reveal superior machinability benefits over conventional dry turning of hardened materials. Various engineering materials have been studied. However, investigations on AISI O1 tool steel have not been widely reported. In this paper, surface finish and surface integrity dominant when hard turning AISI O1 tool steel is analysed. The study is focused on the performance of wiper coated ceramic tool with respect to surface roughness and surface integrity of hardened tool steel. Hard turned tool steel was machined at varying cutting speed of 100, 155 and 210 m/min and feed rate of 0.05, 0.125 and 0.20mm/rev. The depth of cut of 0.2mm was maintained constant throughout the machining trials. Machining was conducted using dry turning on 200E-axis CNC lathe. The experimental study revealed that the surface finish is relatively superior at higher cutting speed of 210m/min. The surface finish increases when cutting speed increases whereas surface finish is generally better at lower feed rate of 0.05mm/rev. The experimental study conducted have revealed that phenomena such as work piece vibration due to poor or improper mounting on the spindle also contributed to higher surface roughness value of 0.66Ra during turning at 0.2mm/rev. Traces of white layer was observed when viewed with optical microscope which shows evidence of cutting effects on the turned work material at feed rate of 0.2 rev/min

Machining of Molybdenum by EDM-EP and EDC Processes

NASA Astrophysics Data System (ADS)

Wu, K. L.; Chen, H. J.; Lee, H. M.; Lo, J. S.

2017-12-01

Molybdenum metal (Mo) can be machined with conventional tools and equipment, however, its refractory propertytends to chip when being machined. In this study, the nonconventional processes of electrical discharge machining (EDM) and electro-polishing (EP) have been conducted to investigate the machining of Mo metal and fabrication of Mo grid. Satisfactory surface quality was obtained using appropriate EDM parameters of Ip ≦ 3A and Ton < 80μs at a constant pulse interval of 100μs. The finished Mometal has accomplished by selecting appropriate EP parameters such as electrolyte flow rate of 0.42m/s under EP voltage of 50V and flush time of 20 sec to remove the recast layer and craters on the surface of Mo metal. The surface roughness of machined Mo metal can be improved from Ra of 0.93μm (Rmax = 8.51μm) to 0.23μm (Rmax = 1.48μm). Machined Mo metal surface, when used as grid component in electron gun, needs to be modified by coating materials with high work function, such as silicon carbide (SiC). The main purpose of this study is to explore the electrical discharge coating (EDC) process for coating the SiC layer on EDMed Mo metal. Experimental results proved that the appropriate parameters of Ip = 5A and Ton = 50μs at Toff = 10μs can obtain the deposit with about 60μm thickness. The major phase of deposit on machined Mo surface was SiC ceramic, while the minor phases included MoSi2 and/or SiO2 with the presence of free Si due to improper discharging parameters and the use of silicone oil as the dielectric fluid.

Machine learning molecular dynamics for the simulation of infrared spectra.

PubMed

Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

2017-10-01

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

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

PubMed

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

2017-11-01

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

Examination of redirected continuous miner scrubber discharge configurations for exhaust face ventilation systems

PubMed Central

Organiscak, J.A.; Beck, T.W.

2015-01-01

The U.S. National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) has recently studied several redirected scrubber discharge configurations in its full-scale continuous miner gallery for both dust and gas control when using an exhaust face ventilation system. Dust and gas measurements around the continuous mining machine in the laboratory showed that the conventional scrubber discharge directed outby the face with a 12.2-m (40-ft) exhaust curtain setback appeared to be one of the better configurations for controlling dust and gas. Redirecting all the air toward the face equally up both sides of the machine increased the dust and gas concentrations around the machine. When all of the air was redirected toward the face on the off-curtain side of the machine, gas accumulations tended to be reduced at the face, at the expense of increased dust levels in the return and on the curtain side of the mining machine. A 6.1-m (20-ft) exhaust curtain setback without the scrubber operating resulted in the lowest dust levels around the continuous mining machine, but this configuration resulted in some of the highest levels of dust in the return and gas on the off-curtain side of the mining face. Two field studies showed some similarities to the laboratory findings, with elevated dust levels at the rear corners of the continuous miner when all of the scrubber exhaust was redirected toward the face either up the off-tubing side or equally up both sides of the mining machine. PMID:26251566

Analysis of surface integrity in machining of AISI 304 stainless steel under various cooling and cutting conditions

NASA Astrophysics Data System (ADS)

Klocke, F.; Döbbeler, B.; Lung, S.; Seelbach, T.; Jawahir, I. S.

2018-05-01

Recent studies have shown that machining under specific cooling and cutting conditions can be used to induce a nanocrystalline surface layer in the workspiece. This layer has beneficial properties, such as improved fatigue strength, wear resistance and tribological behavior. In machining, a promising approach for achieving grain refinement in the surface layer is the application of cryogenic cooling. The aim is to use the last step of the machining operation to induce the desired surface quality to save time-consuming and expensive post machining surface treatments. The material used in this study was AISI 304 stainless steel. This austenitic steel suffers from low yield strength that limits its technological applications. In this paper, liquid nitrogen (LN2) as cryogenic coolant, as well as minimum quantity lubrication (MQL), was applied and investigated. As a reference, conventional flood cooling was examined. Besides the cooling conditions, the feed rate was varied in four steps. A large rounded cutting edge radius and finishing cutting parameters were chosen to increase the mechanical load on the machined surface. The surface integrity was evaluated at both, the microstructural and the topographical levels. After turning experiments, a detailed analysis of the microstructure was carried out including the imaging of the surface layer and hardness measurements at varying depths within the machined layer. Along with microstructural investigations, different topological aspects, e.g., the surface roughness, were analyzed. It was shown that the resulting microstructure strongly depends on the cooling condition. This study also shows that it was possible to increase the micro hardness in the top surface layer significantly.

Assessing the potential of surface-immobilized molecular logic machines for integration with solid state technology.

PubMed

Dunn, Katherine E; Trefzer, Martin A; Johnson, Steven; Tyrrell, Andy M

2016-08-01

Molecular computation with DNA has great potential for low power, highly parallel information processing in a biological or biochemical context. However, significant challenges remain for the field of DNA computation. New technology is needed to allow multiplexed label-free readout and to enable regulation of molecular state without addition of new DNA strands. These capabilities could be provided by hybrid bioelectronic systems in which biomolecular computing is integrated with conventional electronics through immobilization of DNA machines on the surface of electronic circuitry. Here we present a quantitative experimental analysis of a surface-immobilized OR gate made from DNA and driven by strand displacement. The purpose of our work is to examine the performance of a simple representative surface-immobilized DNA logic machine, to provide valuable information for future work on hybrid bioelectronic systems involving DNA devices. We used a quartz crystal microbalance to examine a DNA monolayer containing approximately 5×10(11)gatescm(-2), with an inter-gate separation of approximately 14nm, and we found that the ensemble of gates took approximately 6min to switch. The gates could be switched repeatedly, but the switching efficiency was significantly degraded on the second and subsequent cycles when the binding site for the input was near to the surface. Otherwise, the switching efficiency could be 80% or better, and the power dissipated by the ensemble of gates during switching was approximately 0.1nWcm(-2), which is orders of magnitude less than the power dissipated during switching of an equivalent array of transistors. We propose an architecture for hybrid DNA-electronic systems in which information can be stored and processed, either in series or in parallel, by a combination of molecular machines and conventional electronics. In this architecture, information can flow freely and in both directions between the solution-phase and the underlying electronics via surface-immobilized DNA machines that provide the interface between the molecular and electronic domains. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Effect of micro-scale texturing on the cutting tool performance

NASA Astrophysics Data System (ADS)

Vasumathy, D.; Meena, Anil

2018-05-01

The present study is mainly focused on the cutting performance of the micro-scale textured carbide tools while turning AISI 304 austenitic stainless steel under dry cutting environment. The texture on the rake face of the carbide tools was fabricated by laser machining. The cutting performance of the textured tools was further compared with conventional tools in terms of cutting forces, tool wear, machined surface quality and chip curl radius. SEM and EDS analyses have been also performed to better understand the tool surface characteristics. Results show that the grooves help in breaking the tool-chip contact leading to a lesser tool-chip contact area which results in reduced iron (Fe) adhesion to the tool.

General-Purpose Front End for Real-Time Data Processing

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

FRONTIER is a computer program that functions as a front end for any of a variety of other software of both the artificial intelligence (AI) and conventional data-processing types. As used here, front end signifies interface software needed for acquiring and preprocessing data and making the data available for analysis by the other software. FRONTIER is reusable in that it can be rapidly tailored to any such other software with minimum effort. Each component of FRONTIER is programmable and is executed in an embedded virtual machine. Each component can be reconfigured during execution. The virtual-machine implementation making FRONTIER independent of the type of computing hardware on which it is executed.

Approach for axisymmetrical asphere polishing with full-area tools

NASA Astrophysics Data System (ADS)

Novi, Andrea; Melozzi, Mauro

1999-09-01

Aspherics up to 500 nm diameter in optical glass or in ceramic substrates have been fabricated using area- compensated polishing tools and conventional optical shop machines. The tool forms are derived starting from the actual shape of the part under figuring. The figure error is measured using an interferometer mounted on-line with the polishing machine. Measurements are taken after each polishing step to compute the new tool form. The process speeds up the fabrication of aspheres and it improves repeatability in the manufacturing of axisymmetrical optics using moderate cost equipment's up to astronomical requirements. In the paper we present some examples of polishing results using the above mentioned approach on different aspherics for space applications.

Near-Field Terahertz Transmission Imaging at 0.210 Terahertz Using a Simple Aperture Technique

DTIC Science & Technology

2015-10-01

This report discusses a simple aperture useful for terahertz near-field imaging at .2010 terahertz ( lambda = 1.43 millimeters). The aperture requires...achieve a spatial resolution of lambda /7. The aperture can be scaled with the assistance of machinery found in conventional machine shops to achieve similar results using shorter terahertz wavelengths.

"Your Model Is Predictive-- but Is It Useful?" Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation

ERIC Educational Resources Information Center

González-Brenes, José P.; Huang, Yun

2015-01-01

Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…

On Wonderful Machines: The Transmission of Mechanical Knowledge by Jesuits

ERIC Educational Resources Information Center

Feldhay, Rivka

2006-01-01

This paper attempts to draw attention to non-conventional but popular modes of transmitting scientific knowledge in Jesuit institutions in the 17th century. The particular case study focuses on a fictive dialogue between Galileo, Mersenne and Paulus Guldin on the power needed for moving the huge globe of the earth by mechanical means. The dialogue…

CoCom and the Future of Conventional Arms Exports in the Former Communist Bloc

DTIC Science & Technology

1993-12-01

structure and background of each of these firms. The first example is the Godollo Machine Factory which was primarily involved in repair and renovation of...regularizedŚ Such an attitude is noteworthy because the potential for growth in the space industry is so great. Not only does Russia produce the " Energia

Felling small trees with a drive-to-tree feller-buncher

Treesearch

Dana Mitchell

2008-01-01

Conventional forestry equipment is often used to harvest small-diameter trees. The typical ground-based logging operation is highly mechanized, with the most common using feller-bunchers, grapple skidders, and a chipper or grinder. But these machines may not be economical when used in pre-commercial or unmerchantable thinning operations in which the number of trees to...

Summarization as the base for text assessment

NASA Astrophysics Data System (ADS)

Karanikolas, Nikitas N.

2015-02-01

We present a model that apply shallow text summarization as a cheap (in resources needed) process for Automatic (machine based) free text answer Assessment (AA). The evaluation of the proposed method induces the inference that the Conventional Assessment (CA, man made assessment of free text answers) does not have an obvious mechanical replacement. However, this is a research challenge.

Development of an Electric Motor Powered Low Cost Coconut Deshelling Machine

NASA Astrophysics Data System (ADS)

Mondal, Imdadul Hoque; Prasanna Kumar, G. V.

2016-06-01

An electric motor powered coconut deshelling machine was developed in line with the commercially available unit, but with slight modifications. The machine worked on the principle that the coconut shell can be caused to fail in shear and compressive forces. It consisted of a toothed wheel, a deshelling rod, an electric motor, and a compound chain drive. A bevelled 16 teeth sprocket with 18 mm pitch was used as the toothed wheel. Mild steel round bar of 18 mm diameter was used as the deshelling rod. The sharp edge tip of the deshelling rod was inserted below the shell to apply shear force on the shell, and the fruit was tilted toward the rotary toothed wheel to apply the compressive force on the shell. The speed of rotation of the toothed wheel was set at 34 ± 2 rpm. The output capacity of the machine was found to be 24 coconuts/h with 95 % of the total time effectively used for deshelling. The labour requirement was found to be 43 man-h/1000 nuts. About 13 % of the kernels got scraped and about 7 % got sliced during the operation. The developed coconut deshelling machine was recommended for the minimum annual use of 200 h or deshelling of 4700 coconuts per year. The cost of operation for 200 h of annual use was found to be about ` 47/h. The developed machine was found to be simple, easy to operate, energy efficient, safe and reduce drudgery involved in deshelling by conventional methods.

Application of high-performance computing to numerical simulation of human movement

NASA Technical Reports Server (NTRS)

Anderson, F. C.; Ziegler, J. M.; Pandy, M. G.; Whalen, R. T.

1995-01-01

We have examined the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimization problems for human movement. Specifically, we compared the computational expense of determining the optimal controls for the single support phase of gait using a conventional serial machine (SGI Iris 4D25), a MIMD parallel machine (Intel iPSC/860), and a parallel-vector-processing machine (Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for gait could take up to 3 months of CPU time on the Iris. Both the Cray and the Intel are able to reduce this time to practical levels. The optimal solution for gait can be found with about 77 hours of CPU on the Cray and with about 88 hours of CPU on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are better suited to different portions of the computational algorithm used. The Intel was best suited to computing the derivatives of the performance criterion and the constraints whereas the Cray was best suited to parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.

PubMed

Churpek, Matthew M; Yuen, Trevor C; Winslow, Christopher; Meltzer, David O; Kattan, Michael W; Edelson, Dana P

2016-02-01

Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter database. Observational cohort study. Five hospitals, from November 2008 until January 2013. Hospitalized ward patients None Demographic variables, laboratory values, and vital signs were utilized in a discrete-time survival analysis framework to predict the combined outcome of cardiac arrest, intensive care unit transfer, or death. Two logistic regression models (one using linear predictor terms and a second utilizing restricted cubic splines) were compared to several different machine learning methods. The models were derived in the first 60% of the data by date and then validated in the next 40%. For model derivation, each event time window was matched to a non-event window. All models were compared to each other and to the Modified Early Warning score, a commonly cited early warning score, using the area under the receiver operating characteristic curve (AUC). A total of 269,999 patients were admitted, and 424 cardiac arrests, 13,188 intensive care unit transfers, and 2,840 deaths occurred in the study. In the validation dataset, the random forest model was the most accurate model (AUC, 0.80 [95% CI, 0.80-0.80]). The logistic regression model with spline predictors was more accurate than the model utilizing linear predictors (AUC, 0.77 vs 0.74; p < 0.01), and all models were more accurate than the MEWS (AUC, 0.70 [95% CI, 0.70-0.70]). In this multicenter study, we found that several machine learning methods more accurately predicted clinical deterioration than logistic regression. Use of detection algorithms derived from these techniques may result in improved identification of critically ill patients on the wards.

Living systematic reviews: 2. Combining human and machine effort.

PubMed

Thomas, James; Noel-Storr, Anna; Marshall, Iain; Wallace, Byron; McDonald, Steven; Mavergames, Chris; Glasziou, Paul; Shemilt, Ian; Synnot, Anneliese; Turner, Tari; Elliott, Julian

2017-11-01

New approaches to evidence synthesis, which use human effort and machine automation in mutually reinforcing ways, can enhance the feasibility and sustainability of living systematic reviews. Human effort is a scarce and valuable resource, required when automation is impossible or undesirable, and includes contributions from online communities ("crowds") as well as more conventional contributions from review authors and information specialists. Automation can assist with some systematic review tasks, including searching, eligibility assessment, identification and retrieval of full-text reports, extraction of data, and risk of bias assessment. Workflows can be developed in which human effort and machine automation can each enable the other to operate in more effective and efficient ways, offering substantial enhancement to the productivity of systematic reviews. This paper describes and discusses the potential-and limitations-of new ways of undertaking specific tasks in living systematic reviews, identifying areas where these human/machine "technologies" are already in use, and where further research and development is needed. While the context is living systematic reviews, many of these enabling technologies apply equally to standard approaches to systematic reviewing. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Exploiting the Dynamics of Soft Materials for Machine Learning

PubMed Central

Hauser, Helmut; Li, Tao; Pfeifer, Rolf

2018-01-01

Abstract Soft materials are increasingly utilized for various purposes in many engineering applications. These materials have been shown to perform a number of functions that were previously difficult to implement using rigid materials. Here, we argue that the diverse dynamics generated by actuating soft materials can be effectively used for machine learning purposes. This is demonstrated using a soft silicone arm through a technique of multiplexing, which enables the rich transient dynamics of the soft materials to be fully exploited as a computational resource. The computational performance of the soft silicone arm is examined through two standard benchmark tasks. Results show that the soft arm compares well to or even outperforms conventional machine learning techniques under multiple conditions. We then demonstrate that this system can be used for the sensory time series prediction problem for the soft arm itself, which suggests its immediate applicability to a real-world machine learning problem. Our approach, on the one hand, represents a radical departure from traditional computational methods, whereas on the other hand, it fits nicely into a more general perspective of computation by way of exploiting the properties of physical materials in the real world. PMID:29708857

Exploiting the Dynamics of Soft Materials for Machine Learning.

PubMed

Nakajima, Kohei; Hauser, Helmut; Li, Tao; Pfeifer, Rolf

2018-06-01

Soft materials are increasingly utilized for various purposes in many engineering applications. These materials have been shown to perform a number of functions that were previously difficult to implement using rigid materials. Here, we argue that the diverse dynamics generated by actuating soft materials can be effectively used for machine learning purposes. This is demonstrated using a soft silicone arm through a technique of multiplexing, which enables the rich transient dynamics of the soft materials to be fully exploited as a computational resource. The computational performance of the soft silicone arm is examined through two standard benchmark tasks. Results show that the soft arm compares well to or even outperforms conventional machine learning techniques under multiple conditions. We then demonstrate that this system can be used for the sensory time series prediction problem for the soft arm itself, which suggests its immediate applicability to a real-world machine learning problem. Our approach, on the one hand, represents a radical departure from traditional computational methods, whereas on the other hand, it fits nicely into a more general perspective of computation by way of exploiting the properties of physical materials in the real world.

Effects of cutting parameters and machining environments on surface roughness in hard turning using design of experiment

NASA Astrophysics Data System (ADS)

Mia, Mozammel; Bashir, Mahmood Al; Dhar, Nikhil Ranjan

2016-07-01

Hard turning is gradually replacing the time consuming conventional turning process, which is typically followed by grinding, by producing surface quality compatible to grinding. The hard turned surface roughness depends on the cutting parameters, machining environments and tool insert configurations. In this article the variation of the surface roughness of the produced surfaces with the changes in tool insert configuration, use of coolant and different cutting parameters (cutting speed, feed rate) has been investigated. This investigation was performed in machining AISI 1060 steel, hardened to 56 HRC by heat treatment, using coated carbide inserts under two different machining environments. The depth of cut, fluid pressure and material hardness were kept constant. The Design of Experiment (DOE) was performed to determine the number and combination sets of different cutting parameters. A full factorial analysis has been performed to examine the effect of main factors as well as interaction effect of factors on surface roughness. A statistical analysis of variance (ANOVA) was employed to determine the combined effect of cutting parameters, environment and tool configuration. The result of this analysis reveals that environment has the most significant impact on surface roughness followed by feed rate and tool configuration respectively.

Big Data and Machine Learning in Plastic Surgery: A New Frontier in Surgical Innovation.

PubMed

Kanevsky, Jonathan; Corban, Jason; Gaster, Richard; Kanevsky, Ari; Lin, Samuel; Gilardino, Mirko

2016-05-01

Medical decision-making is increasingly based on quantifiable data. From the moment patients come into contact with the health care system, their entire medical history is recorded electronically. Whether a patient is in the operating room or on the hospital ward, technological advancement has facilitated the expedient and reliable measurement of clinically relevant health metrics, all in an effort to guide care and ensure the best possible clinical outcomes. However, as the volume and complexity of biomedical data grow, it becomes challenging to effectively process "big data" using conventional techniques. Physicians and scientists must be prepared to look beyond classic methods of data processing to extract clinically relevant information. The purpose of this article is to introduce the modern plastic surgeon to machine learning and computational interpretation of large data sets. What is machine learning? Machine learning, a subfield of artificial intelligence, can address clinically relevant problems in several domains of plastic surgery, including burn surgery; microsurgery; and craniofacial, peripheral nerve, and aesthetic surgery. This article provides a brief introduction to current research and suggests future projects that will allow plastic surgeons to explore this new frontier of surgical science.

LED light design method for high contrast and uniform illumination imaging in machine vision.

PubMed

Wu, Xiaojun; Gao, Guangming

2018-03-01

In machine vision, illumination is very critical to determine the complexity of the inspection algorithms. Proper lights can obtain clear and sharp images with the highest contrast and low noise between the interested object and the background, which is conducive to the target being located, measured, or inspected. Contrary to the empirically based trial-and-error convention to select the off-the-shelf LED light in machine vision, an optimization algorithm for LED light design is proposed in this paper. It is composed of the contrast optimization modeling and the uniform illumination technology for non-normal incidence (UINI). The contrast optimization model is built based on the surface reflection characteristics, e.g., the roughness, the reflective index, and light direction, etc., to maximize the contrast between the features of interest and the background. The UINI can keep the uniformity of the optimized lighting by the contrast optimization model. The simulation and experimental results demonstrate that the optimization algorithm is effective and suitable to produce images with the highest contrast and uniformity, which is very inspirational to the design of LED illumination systems in machine vision.

Improved Correction of Atmospheric Pressure Data Obtained by Smartphones through Machine Learning

PubMed Central

Kim, Yong-Hyuk; Ha, Ji-Hun; Kim, Na-Young; Im, Hyo-Hyuc; Sim, Sangjin; Choi, Reno K. Y.

2016-01-01

A correction method using machine learning aims to improve the conventional linear regression (LR) based method for correction of atmospheric pressure data obtained by smartphones. The method proposed in this study conducts clustering and regression analysis with time domain classification. Data obtained in Gyeonggi-do, one of the most populous provinces in South Korea surrounding Seoul with the size of 10,000 km2, from July 2014 through December 2014, using smartphones were classified with respect to time of day (daytime or nighttime) as well as day of the week (weekday or weekend) and the user's mobility, prior to the expectation-maximization (EM) clustering. Subsequently, the results were analyzed for comparison by applying machine learning methods such as multilayer perceptron (MLP) and support vector regression (SVR). The results showed a mean absolute error (MAE) 26% lower on average when regression analysis was performed through EM clustering compared to that obtained without EM clustering. For machine learning methods, the MAE for SVR was around 31% lower for LR and about 19% lower for MLP. It is concluded that pressure data from smartphones are as good as the ones from national automatic weather station (AWS) network. PMID:27524999

High productivity mould robotic milling in Al-5083

NASA Astrophysics Data System (ADS)

Urresti, Iker; Arrazola, Pedro Jose; Ørskov, Klaus Bonde; Pelegay, Jose Angel

2018-05-01

Industrial serial robots were usually limited to welding, handling or spray painting operations until very recent years. However, some industries have already realized about their important capabilities in terms of flexibility, working space, adaptability and cost. Hence, currently they are seriously being considered to carry out certain metal machining tasks. Therefore, robot based machining is presented as a cost-saving and flexible manufacturing alternative compared to conventional CNC machines especially for roughing or even pre-roughing of large parts. Nevertheless, there are still some drawbacks usually referred as low rigidity, accuracy and repeatability. Thus, the process productivity is usually sacrificed getting low Material Removal Rates (MRR), and consequently not being competitive. Nevertheless, in this paper different techniques to obtain increased productivity are presented, though an appropriate selection of cutting strategies and parameters that are essential for it. During this research some rough milling tests in Al-5083 are presented where High Feed Milling (HFM) is implemented as productive cutting strategy and the experimental modal analysis named Tap-testing is used for the suitable choice of cutting conditions. Competitive productivity rates are experienced while process stability is checked through the cutting forces measurements in order to prove the effectiveness of the experimental modal analysis for robotic machining.

Energy-Efficient Neuromorphic Classifiers.

PubMed

Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

2016-10-01

Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, thereby obfuscating a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technology developed by IBM can be leveraged to realize neuromorphic circuits that operate as classifiers of complex real-world stimuli. Specifically, we provide a set of general prescriptions to enable the practical implementation of neural architectures that compete with state-of-the-art classifiers. We also show that the energy consumption of these architectures, realized on the IBM chip, is typically two or more orders of magnitude lower than that of conventional digital machines implementing classifiers with comparable performance. Moreover, the spike-based dynamics display a trade-off between integration time and accuracy, which naturally translates into algorithms that can be flexibly deployed for either fast and approximate classifications, or more accurate classifications at the mere expense of longer running times and higher energy costs. This work finally proves that the neuromorphic approach can be efficiently used in real-world applications and has significant advantages over conventional digital devices when energy consumption is considered.

Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles

NASA Astrophysics Data System (ADS)

Hannel, Mark D.; Abdulali, Aidan; O'Brien, Michael; Grier, David G.

2018-06-01

Holograms of colloidal particles can be analyzed with the Lorenz-Mie theory of light scattering to measure individual particles' three-dimensional positions with nanometer precision while simultaneously estimating their sizes and refractive indexes. Extracting this wealth of information begins by detecting and localizing features of interest within individual holograms. Conventionally approached with heuristic algorithms, this image analysis problem can be solved faster and more generally with machine-learning techniques. We demonstrate that two popular machine-learning algorithms, cascade classifiers and deep convolutional neural networks (CNN), can solve the feature-localization problem orders of magnitude faster than current state-of-the-art techniques. Our CNN implementation localizes holographic features precisely enough to bootstrap more detailed analyses based on the Lorenz-Mie theory of light scattering. The wavelet-based Haar cascade proves to be less precise, but is so computationally efficient that it creates new opportunities for applications that emphasize speed and low cost. We demonstrate its use as a real-time targeting system for holographic optical trapping.

Development of a lemon cutting machine.

PubMed

Hrishikesh Tavanandi, A; Deepak, S; Venkateshmurthy, K; Raghavarao, K S M S

2014-12-01

Cutting of lemon and other similar fruits is conventionally done manually by sharp knife, which is labor intensive and often un-hygienic. In the present work, a device has been designed and developed for cutting of lemon hygienically into four pieces of similar shape based on stationery cutters and rotating centralizing/locating slit plate concept. Machine has a unique knife assembly consisting of two bird wing shaped knives, joined by welding perpendicularly to a vertical knife, so that the lemon can be cut into four pieces in a single sweep. Six numbers of rotating centralizing/locating slit plates are welded on to the side plates and the plates carry a groove on its inner face, to enable the wing shaped knife to complete the horizontal cut. The rotating slit plates, having centralizing angle of 90°, are rotated by an electric geared motor. The prototype machine has capacity of over 5,000 lemons/h with a power consumption of 0.11 kW.

Soft, Conformal Bioelectronics for a Wireless Human-Wheelchair Interface

PubMed Central

Mishra, Saswat; Norton, James J. S.; Lee, Yongkuk; Lee, Dong Sup; Agee, Nicolas; Chen, Yanfei; Chun, Youngjae; Yeo, Woon-Hong

2017-01-01

There are more than 3 million people in the world whose mobility relies on wheelchairs. Recent advancement on engineering technology enables more intuitive, easy-to-use rehabilitation systems. A human-machine interface that uses non-invasive, electrophysiological signals can allow a systematic interaction between human and devices; for example, eye movement-based wheelchair control. However, the existing machine-interface platforms are obtrusive, uncomfortable, and often cause skin irritations as they require a metal electrode affixed to the skin with a gel and acrylic pad. Here, we introduce a bioelectronic system that makes dry, conformal contact to the skin. The mechanically comfortable sensor records high-fidelity electrooculograms, comparable to the conventional gel electrode. Quantitative signal analysis and infrared thermographs show the advantages of the soft biosensor for an ergonomic human-machine interface. A classification algorithm with an optimized set of features shows the accuracy of 94% with five eye movements. A Bluetooth-enabled system incorporating the soft bioelectronics demonstrates a precise, hands-free control of a robotic wheelchair via electrooculograms. PMID:28152485

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

NASA Astrophysics Data System (ADS)

Wang, R.; Demerdash, N. A.

1992-06-01

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

3D-Printed Detector Band for Magnetic Off-Plane Flux Measurements in Laminated Machine Cores

PubMed Central

Pfützner, Helmut; Palkovits, Martin; Windischhofer, Andreas; Giefing, Markus

2017-01-01

Laminated soft magnetic cores of transformers, rotating machines etc. may exhibit complex 3D flux distributions with pronounced normal fluxes (off-plane fluxes), perpendicular to the plane of magnetization. As recent research activities have shown, detections of off-plane fluxes tend to be essential for the optimization of core performances aiming at a reduction of core losses and of audible noise. Conventional sensors for off-plane flux measurements tend to be either of high thickness, influencing the measured fluxes significantly, or require laborious preparations. In the current work, thin novel detector bands for effective and simple off-plane flux detections in laminated machine cores were manufactured. They are printed in an automatic way by an in-house developed 3D/2D assembler. The latter enables a unique combination of conductive and non-conductive materials. The detector bands were effectively tested in the interior of a two-package, three-phase model transformer core. They proved to be mechanically resilient, even for strong clamping of the core. PMID:29257063

3D-Printed Detector Band for Magnetic Off-Plane Flux Measurements in Laminated Machine Cores.

PubMed

Shilyashki, Georgi; Pfützner, Helmut; Palkovits, Martin; Windischhofer, Andreas; Giefing, Markus

2017-12-19

Laminated soft magnetic cores of transformers, rotating machines etc. may exhibit complex 3D flux distributions with pronounced normal fluxes (off-plane fluxes), perpendicular to the plane of magnetization. As recent research activities have shown, detections of off-plane fluxes tend to be essential for the optimization of core performances aiming at a reduction of core losses and of audible noise. Conventional sensors for off-plane flux measurements tend to be either of high thickness, influencing the measured fluxes significantly, or require laborious preparations. In the current work, thin novel detector bands for effective and simple off-plane flux detections in laminated machine cores were manufactured. They are printed in an automatic way by an in-house developed 3D/2D assembler. The latter enables a unique combination of conductive and non-conductive materials. The detector bands were effectively tested in the interior of a two-package, three-phase model transformer core. They proved to be mechanically resilient, even for strong clamping of the core.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1992-01-01

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

Machine Vision Applied to Navigation of Confined Spaces

NASA Technical Reports Server (NTRS)

Briscoe, Jeri M.; Broderick, David J.; Howard, Ricky; Corder, Eric L.

2004-01-01

The reliability of space related assets has been emphasized after the second loss of a Space Shuttle. The intricate nature of the hardware being inspected often requires a complete disassembly to perform a thorough inspection which can be difficult as well as costly. Furthermore, it is imperative that the hardware under inspection not be altered in any other manner than that which is intended. In these cases the use of machine vision can allow for inspection with greater frequency using less intrusive methods. Such systems can provide feedback to guide, not only manually controlled instrumentation, but autonomous robotic platforms as well. This paper serves to detail a method using machine vision to provide such sensing capabilities in a compact package. A single camera is used in conjunction with a projected reference grid to ascertain precise distance measurements. The design of the sensor focuses on the use of conventional components in an unconventional manner with the goal of providing a solution for systems that do not require or cannot accommodate more complex vision systems.

Generation of gear tooth surfaces by application of CNC machines

NASA Technical Reports Server (NTRS)

Litvin, F. L.; Chen, N. X.

1994-01-01

This study will demonstrate the importance of application of computer numerically controlled (CNC) machines in generation of gear tooth surfaces with new topology. This topology decreases gear vibration and will extend the gear capacity and service life. A preliminary investigation by a tooth contact analysis (TCA) program has shown that gear tooth surfaces in line contact (for instance, involute helical gears with parallel axes, worm gear drives with cylindrical worms, etc.) are very sensitive to angular errors of misalignment that cause edge contact and an unfavorable shape of transmission errors and vibration. The new topology of gear tooth surfaces is based on the localization of bearing contact, and the synthesis of a predesigned parabolic function of transmission errors that is able to absorb a piecewise linear function of transmission errors caused by gear misalignment. The report will describe the following topics: description of kinematics of CNC machines with six degrees of freedom that can be applied for generation of gear tooth surfaces with new topology. A new method for grinding of gear tooth surfaces by a cone surface or surface of revolution based on application of CNC machines is described. This method provides an optimal approximation of the ground surface to the given one. This method is especially beneficial when undeveloped ruled surfaces are to be ground. Execution of motions of the CNC machine is also described. The solution to this problem can be applied as well for the transfer of machine tool settings from a conventional generator to the CNC machine. The developed theory required the derivation of a modified equation of meshing based on application of the concept of space curves, space curves represented on surfaces, geodesic curvature, surface torsion, etc. Condensed information on these topics of differential geometry is provided as well.

Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.

PubMed

Ranjith, G; Parvathy, R; Vikas, V; Chandrasekharan, Kesavadas; Nair, Suresh

2015-04-01

With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine learning, a branch of artificial intelligence, is increasingly being used in medical image analysis applications such as image segmentation, registration and computer-aided diagnosis and detection. Histopathological analysis is currently the gold standard for classification of brain tumors. The use of machine learning algorithms along with extraction of relevant features from magnetic resonance imaging (MRI) holds promise of replacing conventional invasive methods of tumor classification. The aim of the study is to classify gliomas into benign and malignant types using MRI data. Retrospective data from 28 patients who were diagnosed with glioma were used for the analysis. WHO Grade II (low-grade astrocytoma) was classified as benign while Grade III (anaplastic astrocytoma) and Grade IV (glioblastoma multiforme) were classified as malignant. Features were extracted from MR spectroscopy. The classification was done using four machine learning algorithms: multilayer perceptrons, support vector machine, random forest and locally weighted learning. Three of the four machine learning algorithms gave an area under ROC curve in excess of 0.80. Random forest gave the best performance in terms of AUC (0.911) while sensitivity was best for locally weighted learning (86.1%). The performance of different machine learning algorithms in the classification of gliomas is promising. An even better performance may be expected by integrating features extracted from other MR sequences. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Transferability of glass lens molding

NASA Astrophysics Data System (ADS)

Katsuki, Masahide

2006-02-01

Sphere lenses have been used for long time. But it is well known that sphere lenses theoretically have spherical aberration, coma and so on. And, aspheric lenses attract attention recently. Plastic lenses are molded easily with injection machines, and are relatively low cost. They are suitable for mass production. On the other hand, glass lenses have several excellent features such as high refractive index, heat resistance and so on. Many aspheric glass lenses came to be used for the latest digital camera and mobile phone camera module. It is very difficult to produce aspheric glass lenses by conventional process of curve generating and polishing. For the solution of this problem, Glass Molding Machine was developed and is spreading through the market. High precision mold is necessary to mold glass lenses with Glass Molding Machine. The mold core is ground or turned by high precision NC aspheric generator. To obtain higher transferability of the mold core, the function of the molding machine and the conditions of molding are very important. But because of high molding temperature, there are factors of thermal expansion and contraction of the mold and glass material. And it is hard to avoid the factors. In this session, I introduce following items. [1] Technology of glass molding and the machine is introduced. [2] The transferability of glass molding is analyzed with some data of glass lenses molded. [3] Compensation of molding shape error is discussed with examples.

Machine learning derived risk prediction of anorexia nervosa.

PubMed

Guo, Yiran; Wei, Zhi; Keating, Brendan J; Hakonarson, Hakon

2016-01-20

Anorexia nervosa (AN) is a complex psychiatric disease with a moderate to strong genetic contribution. In addition to conventional genome wide association (GWA) studies, researchers have been using machine learning methods in conjunction with genomic data to predict risk of diseases in which genetics play an important role. In this study, we collected whole genome genotyping data on 3940 AN cases and 9266 controls from the Genetic Consortium for Anorexia Nervosa (GCAN), the Wellcome Trust Case Control Consortium 3 (WTCCC3), Price Foundation Collaborative Group and the Children's Hospital of Philadelphia (CHOP), and applied machine learning methods for predicting AN disease risk. The prediction performance is measured by area under the receiver operating characteristic curve (AUC), indicating how well the model distinguishes cases from unaffected control subjects. Logistic regression model with the lasso penalty technique generated an AUC of 0.693, while Support Vector Machines and Gradient Boosted Trees reached AUC's of 0.691 and 0.623, respectively. Using different sample sizes, our results suggest that larger datasets are required to optimize the machine learning models and achieve higher AUC values. To our knowledge, this is the first attempt to assess AN risk based on genome wide genotype level data. Future integration of genomic, environmental and family-based information is likely to improve the AN risk evaluation process, eventually benefitting AN patients and families in the clinical setting.

New laser machining processes for shape memory alloys

NASA Astrophysics Data System (ADS)

Haferkamp, Heinz; Paschko, Stefan; Goede, Martin

2001-04-01

Due to special material properties, shape memory alloys (SMA) are finding increasing attention in micro system technology. However, only a few processes are available for the machining of miniaturized SMA-components. In this connection, laser material processing offers completely new possibilities. This paper describes the actual status of two projects that are being carried out to qualify new methods to machine SMA components by means of laser radiation. Within one project, the laser material ablation process of miniaturized SMA- components using ultra-short laser pulses (pulse duration: approx. 200 fs) in comparison to conventional laser material ablation is being investigated. Especially for SMA micro- sensors and actuators, it is important to minimize the heat affected zone (HAZ) to maintain the special mechanical properties. Light-microscopic investigations of the grain texture of SMA devices processed with ultra-short laser pulses show that the HAZ can be neglected. Presently, the main goal of the project is to qualify this new processing technique for the micro-structuring of complex SMA micro devices with high precision. Within a second project, investigations are being carried out to realize the induction of the two-way memory effect (TWME) into SMA components using laser radiation. By precisely heating SMA components with laser radiation, local tensions remain near the component surface. In connection with the shape memory effect, these tensions can be used to make the components execute complicated movements. Compared to conventional training methods to induce the TWME, this procedure is faster and easier. Furthermore, higher numbers of thermal cycling are expected because of the low dislocation density in the main part of the component.

Imbalance aware lithography hotspot detection: a deep learning approach

NASA Astrophysics Data System (ADS)

Yang, Haoyu; Luo, Luyang; Su, Jing; Lin, Chenxi; Yu, Bei

2017-07-01

With the advancement of very large scale integrated circuits (VLSI) technology nodes, lithographic hotspots become a serious problem that affects manufacture yield. Lithography hotspot detection at the post-OPC stage is imperative to check potential circuit failures when transferring designed patterns onto silicon wafers. Although conventional lithography hotspot detection methods, such as machine learning, have gained satisfactory performance, with the extreme scaling of transistor feature size and layout patterns growing in complexity, conventional methodologies may suffer from performance degradation. For example, manual or ad hoc feature extraction in a machine learning framework may lose important information when predicting potential errors in ultra-large-scale integrated circuit masks. We present a deep convolutional neural network (CNN) that targets representative feature learning in lithography hotspot detection. We carefully analyze the impact and effectiveness of different CNN hyperparameters, through which a hotspot-detection-oriented neural network model is established. Because hotspot patterns are always in the minority in VLSI mask design, the training dataset is highly imbalanced. In this situation, a neural network is no longer reliable, because a trained model with high classification accuracy may still suffer from a high number of false negative results (missing hotspots), which is fatal in hotspot detection problems. To address the imbalance problem, we further apply hotspot upsampling and random-mirror flipping before training the network. Experimental results show that our proposed neural network model achieves comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

Composite Ceramic Superconducting Wires for Electric Motor Applications

DTIC Science & Technology

1988-12-30

current a-yi t6-ransition. - Emerson Motor Division has begun work on DC heteropolar and homopolar motor designs. The mechanical stresses on conventional...Emerson Motor Division has begun work on DC heteropolar motor designs and, through Professor Novotny at U. Wisconsin, DC homopolar machines. The...123 3.2 Literature Research .............................. .. 124 3 3.3 Application Study .............................. .. 124 3.3.1 Homopolar Motor

Economics of Coharvesting Smallwood by Chainsaw and Skidder for Crop Tree Management in Missouri

Treesearch

Peter Becker; E.M.(Ted) Bilek; Terry Cunningham; Michael Bill; Marty Calvert; Jason Jensen; Michael Norris; Terry Thompson

2011-01-01

Forest improvement harvests using individual-tree and group selection were conducted in four oak or oak-hickory stands in the Missouri Ozarks with conventional equipment (chainsaw and skidder). Volumes (and revenues) for different timber classes (sawlogs and smallwood from topwood and small trees) and hours of machine use were recorded to calculate production rates....

A Simple Deep Learning Method for Neuronal Spike Sorting

NASA Astrophysics Data System (ADS)

Yang, Kai; Wu, Haifeng; Zeng, Yu

2017-10-01

Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

Fully-Enclosed Ceramic Micro-burners Using Fugitive Phase and Powder-based Processing

NASA Astrophysics Data System (ADS)

Do, Truong; Shin, Changseop; Kwon, Patrick; Yeom, Junghoon

2016-08-01

Ceramic-based microchemical systems (μCSs) are more suitable for operation under harsh environments such as high temperature and corrosive reactants compared to the more conventional μCS materials such as silicon and polymers. With the recent renewed interests in chemical manufacturing and process intensification, simple, inexpensive, and reliable ceramic manufacturing technologies are needed. The main objective of this paper is to introduce a new powder-based fabrication framework, which is a one-pot, cost-effective, and versatile process for ceramic μCS components. The proposed approach employs the compaction of metal-oxide sub-micron powders with a graphite fugitive phase that is burned out to create internal cavities and microchannels before full sintering. Pure alumina powder has been used without any binder phase, enabling more precise dimensional control and less structure shrinkage upon sintering. The key process steps such as powder compaction, graphite burnout during partial sintering, machining in a conventional machine tool, and final densification have been studied to characterize the process. This near-full density ceramic structure with the combustion chamber and various internal channels was fabricated to be used as a micro-burner for gas sensing applications.

An efficient ensemble learning method for gene microarray classification.

PubMed

Osareh, Alireza; Shadgar, Bita

2013-01-01

The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

Fully-Enclosed Ceramic Micro-burners Using Fugitive Phase and Powder-based Processing

PubMed Central

Do, Truong; Shin, Changseop; Kwon, Patrick; Yeom, Junghoon

2016-01-01

Ceramic-based microchemical systems (μCSs) are more suitable for operation under harsh environments such as high temperature and corrosive reactants compared to the more conventional μCS materials such as silicon and polymers. With the recent renewed interests in chemical manufacturing and process intensification, simple, inexpensive, and reliable ceramic manufacturing technologies are needed. The main objective of this paper is to introduce a new powder-based fabrication framework, which is a one-pot, cost-effective, and versatile process for ceramic μCS components. The proposed approach employs the compaction of metal-oxide sub-micron powders with a graphite fugitive phase that is burned out to create internal cavities and microchannels before full sintering. Pure alumina powder has been used without any binder phase, enabling more precise dimensional control and less structure shrinkage upon sintering. The key process steps such as powder compaction, graphite burnout during partial sintering, machining in a conventional machine tool, and final densification have been studied to characterize the process. This near-full density ceramic structure with the combustion chamber and various internal channels was fabricated to be used as a micro-burner for gas sensing applications. PMID:27546059

Influence of Feedstock Materials and Spray Parameters on Thermal Conductivity of Wire-Arc-Sprayed Coatings

NASA Astrophysics Data System (ADS)

Yao, H. H.; Zhou, Z.; Wang, G. H.; He, D. Y.; Bobzin, K.; Zhao, L.; Öte, M.; Königstein, T.

2017-03-01

To manufacture a protective coating with high thermal conductivity on drying cylinders in paper production machines, a FeCrB-cored wire was developed, and the spraying parameters for wire-arc spraying were optimized in this study. The conventional engineering materials FeCrAl and FeCrMo coatings were produced as the reference coatings under the same experimental condition. It has been shown that the oxide content in coating influences the thermal conductivity of coating significantly. The FeCrB coating exhibits a relative higher thermal conductivity due to the lower oxide content in comparison with conventional FeCrAl and FeCrMo coatings. Moreover, the oxidation of in-flight particles can be reduced by decreasing the standoff distance contributing to the increase in the thermal conductivity of coating. Total energy consumption of a papermaking machine can be significantly reduced if the coatings applied to dryer section exhibit high thermal conductivity. Therefore, the FeCrB coating developed in this study is a highly promising coating system for drying cylinders regarding the improved thermal conductivity and low operation costs in paper production industry.

Robust recognition of degraded machine-printed characters using complementary similarity measure and error-correction learning

NASA Astrophysics Data System (ADS)

Hagita, Norihiro; Sawaki, Minako

1995-03-01

Most conventional methods in character recognition extract geometrical features such as stroke direction, connectivity of strokes, etc., and compare them with reference patterns in a stored dictionary. Unfortunately, geometrical features are easily degraded by blurs, stains and the graphical background designs used in Japanese newspaper headlines. This noise must be removed before recognition commences, but no preprocessing method is completely accurate. This paper proposes a method for recognizing degraded characters and characters printed on graphical background designs. This method is based on the binary image feature method and uses binary images as features. A new similarity measure, called the complementary similarity measure, is used as a discriminant function. It compares the similarity and dissimilarity of binary patterns with reference dictionary patterns. Experiments are conducted using the standard character database ETL-2 which consists of machine-printed Kanji, Hiragana, Katakana, alphanumeric, an special characters. The results show that this method is much more robust against noise than the conventional geometrical feature method. It also achieves high recognition rates of over 92% for characters with textured foregrounds, over 98% for characters with textured backgrounds, over 98% for outline fonts, and over 99% for reverse contrast characters.

Food powders flowability characterization: theory, methods, and applications.

PubMed

Juliano, Pablo; Barbosa-Cánovas, Gustavo V

2010-01-01

Characterization of food powders flowability is required for predicting powder flow from hoppers in small-scale systems such as vending machines or at the industrial scale from storage silos or bins dispensing into powder mixing systems or packaging machines. This review covers conventional and new methods used to measure flowability in food powders. The method developed by Jenike (1964) for determining hopper outlet diameter and hopper angle has become a standard for the design of bins and is regarded as a standard method to characterize flowability. Moreover, there are a number of shear cells that can be used to determine failure properties defined by Jenike's theory. Other classic methods (compression, angle of repose) and nonconventional methods (Hall flowmeter, Johanson Indicizer, Hosokawa powder tester, tensile strength tester, powder rheometer), used mainly for the characterization of food powder cohesiveness, are described. The effect of some factors preventing flow, such as water content, temperature, time consolidation, particle composition and size distribution, is summarized for the characterization of specific food powders with conventional and other methods. Whereas time-consuming standard methods established for hopper design provide flow properties, there is yet little comparative evidence demonstrating that other rapid methods may provide similar flow prediction.

A discrete wavelet based feature extraction and hybrid classification technique for microarray data analysis.

PubMed

Bennet, Jaison; Ganaprakasam, Chilambuchelvan Arul; Arputharaj, Kannan

2014-01-01

Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

Spectral and spatial characterisation of laser-driven positron beams

DOE PAGES

Sarri, G.; Warwick, J.; Schumaker, W.; ...

2016-10-18

The generation of high-quality relativistic positron beams is a central area of research in experimental physics, due to their potential relevance in a wide range of scientific and engineering areas, ranging from fundamental science to practical applications. There is now growing interest in developing hybrid machines that will combine plasma-based acceleration techniques with more conventional radio-frequency accelerators, in order to minimise the size and cost of these machines. Here we report on recent experiments on laser-driven generation of high-quality positron beams using a relatively low energy and potentially table-top laser system. Lastly, the results obtained indicate that current technology allowsmore » to create, in a compact setup, positron beams suitable for injection in radio-frequency accelerators.« less

Harnessing Disordered-Ensemble Quantum Dynamics for Machine Learning

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Nakajima, Kohei

2017-08-01

The quantum computer has an amazing potential of fast information processing. However, the realization of a digital quantum computer is still a challenging problem requiring highly accurate controls and key application strategies. Here we propose a platform, quantum reservoir computing, to solve these issues successfully by exploiting the natural quantum dynamics of ensemble systems, which are ubiquitous in laboratories nowadays, for machine learning. This framework enables ensemble quantum systems to universally emulate nonlinear dynamical systems including classical chaos. A number of numerical experiments show that quantum systems consisting of 5-7 qubits possess computational capabilities comparable to conventional recurrent neural networks of 100-500 nodes. This discovery opens up a paradigm for information processing with artificial intelligence powered by quantum physics.

Molecules in the Spotlight

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

Cryan, James

2010-01-26

SLAC has just unveiled the world's first X-ray laser, the LCLS. This machine produces pulses of X-rays that are ten billion times brighter than those from conventional sources. One of the goals of this machine is to make movies of chemical reactions, including reactions necessary for life and reactions that might power new energy technologies. This public lecture will show the first results from the LCLS. As a first target, we have chosen nitrogen gas, the main component of the air we breathe. Using the unprecedented power of the LCLS X-rays as a blasting torch, we have created new formsmore » of this molecule and with unique electronic arrangements. Please share with us the first insights from this new technology.« less

Architecture and data processing alternatives for Tse computer. Volume 1: Tse logic design concepts and the development of image processing machine architectures

NASA Technical Reports Server (NTRS)

Rickard, D. A.; Bodenheimer, R. E.

1976-01-01

Digital computer components which perform two dimensional array logic operations (Tse logic) on binary data arrays are described. The properties of Golay transforms which make them useful in image processing are reviewed, and several architectures for Golay transform processors are presented with emphasis on the skeletonizing algorithm. Conventional logic control units developed for the Golay transform processors are described. One is a unique microprogrammable control unit that uses a microprocessor to control the Tse computer. The remaining control units are based on programmable logic arrays. Performance criteria are established and utilized to compare the various Golay transform machines developed. A critique of Tse logic is presented, and recommendations for additional research are included.

From quantum heat engines to laser cooling: Floquet theory beyond the Born–Markov approximation

NASA Astrophysics Data System (ADS)

Restrepo, Sebastian; Cerrillo, Javier; Strasberg, Philipp; Schaller, Gernot

2018-05-01

We combine the formalisms of Floquet theory and full counting statistics with a Markovian embedding strategy to access the dynamics and thermodynamics of a periodically driven thermal machine beyond the conventional Born–Markov approximation. The working medium is a two-level system and we drive the tunneling as well as the coupling to one bath with the same period. We identify four different operating regimes of our machine which include a heat engine and a refrigerator. As the coupling strength with one bath is increased, the refrigerator regime disappears, the heat engine regime narrows and their efficiency and coefficient of performance decrease. Furthermore, our model can reproduce the setup of laser cooling of trapped ions in a specific parameter limit.

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

NASA Astrophysics Data System (ADS)

Wielandts, Marc; Wielandts, Remi

2015-10-01

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

Precision diamond grinding of ceramics and glass

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

Smith, S.; Paul, H.; Scattergood, R.O.

A new research initiative will be undertaken to investigate the effect of machine parameters and material properties on precision diamond grinding of ceramics and glass. The critical grinding depth to initiate the plastic flow-to-brittle fracture regime will be directly measured using plunge-grind tests. This information will be correlated with machine parameters such as wheel bonding and diamond grain size. Multiaxis grinding tests will then be made to provide data more closely coupled with production technology. One important aspect of the material property studies involves measuring fracture toughness at the very short crack sizes commensurate with grinding damage. Short crack toughnessmore » value`s can be much less than the long-crack toughness values measured in conventional fracture tests.« less

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

NASA Technical Reports Server (NTRS)

Prater, T.; Tilson, W.; Jones, Z.

2015-01-01

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Ultrafine-grained commercially pure titanium and microstructure response to hydroxyapatite coating methods

NASA Astrophysics Data System (ADS)

Calvert, Kayla L.

Commercially pure titanium (cp-Ti) is an ideal biomaterial as it does not evoke an inflammatory foreign body response in the body. However, the low strength of cp-Ti prevents the use in most orthopaedic load bearing applications. Therefore, many metal orthopaedic implants are commonly made of higher strength metal alloys that are less biocompatible. Nanostructured materials exhibit superior mechanical properties compared to their conventional grain sized counterparts. Severe plastic deformation (SPD) of metals has been shown to produce nanostructured materials. SPD by machining is a single-step deformation route that refines the grain microstructure, to develop an ultrafine grained (UFG) microstructure. UFG cp-Ti strips were developed with induced shear strains of up to 4.0 using a machining-based process. Both Vickers microhardness evaluation and microstructural analysis were used to characterize the as-received (annealed) and machined states. For induced shear strains between 1.9 and 4.0 in grade 2 cp-Ti the hardness was increased from 188 +/- 7 kg/mm2 in the as-received state to between 244 +/- 6 and 264 +/- 12 kg/mm 2 in the as-machined state, corresponding to an increase in hardness between 31 and 41%. The microstructural analysis revealed a grain size reduction from 34 +/- 11 mum in the as-received state to ˜ 100 nm for machined grade 2-Ti. A complete annealing study suggested that recovery/recrystallization occurs between 300 and 400°C, with a significant hardness drop between 400 and 600°C, while grain growth is continuous, starting at the lowest annealing temperature of 300°C. Hydroxyapatite (HA) is commonly applied to orthopaedic devices to promote bone growth. Machined Ti strips were coated with HA using conventional plasma spray as well as two alternative low-temperature application routes (sol-gel with calcination and anodization with hydrothermal treatment) to evaluate the thermal influence on the UFG-Ti substrate. Plasma spray produced a thick (20 to 70 mum) HA crystalline coating, sol-gel followed by calcination did not produce crystalline HA, while anodization with the proper hydrothermal treatment yielded a homogenous crystalline HA coating 5 to 15 mum thick based on the anodization condition. Mechanical and microstructural evaluation of the UFG-Ti substrates revealed that both the plasma spray and anodization followed by hydrothermal treatment (220 -- 225°C) did not affect the substrate grain size or hardness, while the thermal processing and calcination treatment at 313 -- 446°C for the sol-gel method caused recovery and grain growth, as well as a significant decrease in the hardness of the Ti-substrates.

Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

PubMed

Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

2018-01-05

Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value <0.05) that cannot be discovered by other machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

AN EXPERIMENTAL COMPARISON OF A CONVENTIONAL TV LESSON WITH A PROGRAMMED TV LESSON REQUIRING ACTIVE STUDENT RESPONSE. STUDIES IN TELEVISED INSTRUCTION, REPORT 2.

ERIC Educational Resources Information Center

GROPPER, GEORGE L.; LUMSDAINE, ARTHUR A.

A SERIES OF EXPERIMENTS WAS CONDUCTED TO TEST THE EFFECTIVENESS OF TELEVISED INSTRUCTION. THIS REPORT, THE SECOND IN A SERIES, EXAMINED THE EFFECTIVENESS OF ACTIVE STUDENT RESPONSE ON LEARNING DURING TELEVISED LESSON. PRINCIPLES OF PROGRAMING DERIVED FROM TEACHING-MACHINE RESEARCH AND APPLIED IN THIS STUDY INCLUDED (1) THE REDUCTION OF LESSON…

Caged Birds and Cloning Machines: How Student Imagery "Speaks" to Us about Cultures of Schooling and Student Participation

ERIC Educational Resources Information Center

Leitch, Ruth; Mitchell, Stephanie

2007-01-01

With the advent of the United Nations Convention on the Rights of the Child (CRC), there is an increasing requirement that schools ensure children and young people's views are voiced, listened to and taken seriously on matters of significance. Encouraging these shifts by law is one thing; changing the culture in schools is another. For a…

Diagnostic Assessment of Troubleshooting Skill in an Intelligent Tutoring System

DTIC Science & Technology

1994-03-01

the information that can be provided from studying gauges and indicators and conventional test equipment procedures. Experts are particularly adept at...uses the results of the strategy and action evaluator to update the student profile, represented as a network, using the ERGO ( Noetic Systems, 1993...1990). Individualized tutoring using an intelligent fuzzy temporal relational database. International Tournal of Man-Machine Studies . & 409-429. 𔄁. 34

Human-centered automation and AI - Ideas, insights, and issues from the Intelligent Cockpit Aids research effort

NASA Technical Reports Server (NTRS)

Abbott, Kathy H.; Schutte, Paul C.

1989-01-01

A development status evaluation is presented for the NASA-Langley Intelligent Cockpit Aids research program, which encompasses AI, human/machine interfaces, and conventional automation. Attention is being given to decision-aiding concepts for human-centered automation, with emphasis on inflight subsystem fault management, inflight mission replanning, and communications management. The cockpit envisioned is for advanced commercial transport aircraft.

Teaching Algebra to Ninth and Tenth Grade Pupils with the Use of Programmed Materials and Teaching Machines.

ERIC Educational Resources Information Center

Raymond, Roger A.

In the second year of a study to compare and evaluate programed and conventional instruction in algebra for the ninth and tenth grades, comparisons of the control and experimental groups in each grade were again based on scores from the Lankton First-Year Algebra Test and the California Study Methods Survey (CSMS). Although there was a…

Verification of Entrance Dose Measurements with Thermoluminescent Dosimeters in Conventional Radiotherapy Procedures Delivered with Co-60 Teletherapy Machine.

PubMed

Evwierhurhoma, O B; Ibitoye, Z A; Ojieh, C A; Duncan, Jtk

2015-01-01

The use of in vivo dosimetry with thermolumiscent dosimeters (TLDs) as a veritable means of quality control in conventional radiotherapy procedures was determined in this work. The objective of this study was to determine the role of in vivo dosimetry with thermoluminescent dosimeters (TLDs) as part of quality control and audit in conventional radiotherapy procedures delivered with Co-60 teletherapy machine. Fifty-seven patients with cancers of the breast, pelvis, head and neck were admitted for this study. TLD system at the Radiation Monitoring and Protection Centre, Lagos State University, Ojo, Lagos-Nigeria was used for the in vivo entrance dose readings. All patients were treated with Co-60 (T780c) teletherapy machine at 80 cm source to surface distance located at Eko Hospitals, Lagos. Two TLDs were placed on the patient surface within 1 cm from the center of the field of treatment. Build-up material made of paraffin wax with a density of 0.939 g/cm(3) and a thickness 0.5 cm was placed on top of the TLDs. A RADOS RE 200 TLD reader was used to read out the TLDs over 12 s and at a temperature of 300°C. The results showed that there was no significant difference between the expected dose and measured dose of breast (P = 0.11), H and N (P = 0.52), and pelvis (P = 0.31) patients. Furthermore, percentage difference between expected dose and measured dose of the three treatment sites were not significantly different (P = 0.11). More so, 88.9% (16/18) treated breast, 91.3% (21/23) pelvis, and 86.7% (13/15) H and N patients had percentage deviation difference less than 5%. In general, 89.3% (50/56) patients admitted for this study had their percentage deviation difference below 5% recommended standard limit. The values obtained establish that there are no major differences from similar studies reported in literature. This study was also part of quality control and audit of the radiotherapy procedures in the center as expected by national and international regulatory bodies.

Applications for Gradient Metal Alloys Fabricated Using Additive Manufacturing

NASA Technical Reports Server (NTRS)

Hofmann, Douglas C.; Borgonia, John Paul C.; Dillon, Robert P.; Suh, Eric J.; Mulder, jerry L.; Gardner, Paul B.

2013-01-01

Recently, additive manufacturing (AM) techniques have been developed that may shift the paradigm of traditional metal production by allowing complex net-shaped hardware to be built up layer-by-layer, rather than being machined from a billet. The AM process is ubiquitous with polymers due to their low melting temperatures, fast curing, and controllable viscosity, and 3D printers are widely available as commercial or consumer products. 3D printing with metals is inherently more complicated than with polymers due to their higher melting temperatures and reactivity with air, particularly when heated or molten. The process generally requires a high-power laser or other focused heat source, like an electron beam, for precise melting and deposition. Several promising metal AM techniques have been developed, including laser deposition (also called laser engineered net shaping or LENS® and laser deposition technology (LDT)), direct metal laser sintering (DMLS), and electron beam free-form (EBF). These machines typically use powders or wire feedstock that are melted and deposited using a laser or electron beam. Complex net-shape parts have been widely demonstrated using these (and other) AM techniques and the process appears to be a promising alternative to machining in some cases. Rather than simply competing with traditional machining for cost and time savings, the true advantage of AM involves the fabrication of hardware that cannot be produced using other techniques. This could include parts with "blind" features (like foams or trusses), parts that are difficult to machine conventionally, or parts made from materials that do not exist in bulk forms. In this work, the inventors identify that several AM techniques can be used to develop metal parts that change composition from one location in the part to another, allowing for complete control over the mechanical or physical properties. This changes the paradigm for conventional metal fabrication, which relies on an assortment of "post-processing" methods to locally alter properties (such as coating, heat treating, work hardening, shot peening, etching, anodizing, among others). Building the final part in an additive process allows for the development of an entirely new class of metals, so-called "functionally graded metals" or "gradient alloys." By carefully blending feedstock materials with different properties in an AM process, hardware can be developed with properties that cannot be obtained using other techniques but with the added benefit of the net-shaped fabrication that AM allows.

Emulating short-term synaptic dynamics with memristive devices

NASA Astrophysics Data System (ADS)

Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

2016-01-01

Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

Nanosecond multi-pulse laser milling for certain area removal of metal coating on plastics surface

NASA Astrophysics Data System (ADS)

Zhao, Kai; Jia, Zhenyuan; Ma, Jianwei; Liu, Wei; Wang, Ling

2014-12-01

Metal coating with functional pattern on engineering plastics surface plays an important role in industry applications; it can be obtained by adding or removing certain area of metal coating on engineering plastics surface. However, the manufacturing requirements are improved continuously and the plastic substrate presents three-dimensional (3D) structure-many of these parts cannot be fabricated by conventional processing methods, and a new manufacturing method is urgently needed. As the laser-processing technology has many advantages like high machining accuracy and constraints free substrate structure, the machining of the parts is studied through removing certain area of metal coating based on the nanosecond multi-pulse laser milling. To improve the edge quality of the functional pattern, generation mechanism and corresponding avoidance strategy of the processing defects are studied. Additionally, a prediction model for the laser ablation depth is proposed, which can effectively avoid the existence of residual metal coating and reduces the damage of substrate. With the optimal machining parameters, an equiangular spiral pattern on copper-clad polyimide (CCPI) is machined based on the laser milling at last. The experimental results indicate that the edge of the pattern is smooth and consistent, the substrate is flat and without damage. The achievements in this study could be applied in industrial production.

MapReduce SVM Game

DOE PAGES

Vineyard, Craig M.; Verzi, Stephen J.; James, Conrad D.; ...

2015-08-10

Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently andmore » recom- bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.« less

High Performance Distributed Computing in a Supercomputer Environment: Computational Services and Applications Issues

NASA Technical Reports Server (NTRS)

Kramer, Williams T. C.; Simon, Horst D.

1994-01-01

This tutorial proposes to be a practical guide for the uninitiated to the main topics and themes of high-performance computing (HPC), with particular emphasis to distributed computing. The intent is first to provide some guidance and directions in the rapidly increasing field of scientific computing using both massively parallel and traditional supercomputers. Because of their considerable potential computational power, loosely or tightly coupled clusters of workstations are increasingly considered as a third alternative to both the more conventional supercomputers based on a small number of powerful vector processors, as well as high massively parallel processors. Even though many research issues concerning the effective use of workstation clusters and their integration into a large scale production facility are still unresolved, such clusters are already used for production computing. In this tutorial we will utilize the unique experience made at the NAS facility at NASA Ames Research Center. Over the last five years at NAS massively parallel supercomputers such as the Connection Machines CM-2 and CM-5 from Thinking Machines Corporation and the iPSC/860 (Touchstone Gamma Machine) and Paragon Machines from Intel were used in a production supercomputer center alongside with traditional vector supercomputers such as the Cray Y-MP and C90.

MapReduce SVM Game

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

Vineyard, Craig M.; Verzi, Stephen J.; James, Conrad D.

Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently andmore » recom- bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.« less

New tool holder design for cryogenic machining of Ti6Al4V

NASA Astrophysics Data System (ADS)

Bellin, Marco; Sartori, Stefano; Ghiotti, Andrea; Bruschi, Stefania

2017-10-01

The renewed demand of increasing the machinability of the Ti6Al4V titanium alloy to produce biomedical and aerospace parts working at high temperature has recently led to the application of low-temperature coolants instead of conventional cutting fluids to increase both the tool life and the machined surface integrity. In particular, the liquid nitrogen directed to the tool rake face has shown a great capability of reducing the temperature at the chip-tool interface, as well as the chemical interaction between the tool coating and the titanium to be machined, therefore limiting the tool crater wear, and improving, at the same time, the chip breakability. Furthermore, the nitrogen is a safe, non-harmful, non-corrosive, odorless, recyclable, non-polluting and abundant gas, characteristics that further qualify it as an environmental friendly coolant to be applied to machining processes. However, the behavior of the system composed by the tool and the tool holder, exposed to the cryogenics temperatures may represent a critical issue in order to obtain components within the required geometrical tolerances. On this basis, the paper aims at presenting the design of an innovative tool holder installed on a CNC lathe, which includes the cryogenic coolant provision system, and which is able to hinder the part possible distortions due to the liquid nitrogen adduction by stabilizing its dimensions through the use of heating cartridges and appropriate sensors to monitor the temperature evolution of the tool holder.

Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest.

PubMed

Blasco, José; Munera, Sandra; Aleixos, Nuria; Cubero, Sergio; Molto, Enrique

Individual items of any agricultural commodity are different from each other in terms of colour, shape or size. Furthermore, as they are living thing, they change their quality attributes over time, thereby making the development of accurate automatic inspection machines a challenging task. Machine vision-based systems and new optical technologies make it feasible to create non-destructive control and monitoring tools for quality assessment to ensure adequate accomplishment of food standards. Such systems are much faster than any manual non-destructive examination of fruit and vegetable quality, thus allowing the whole production to be inspected with objective and repeatable criteria. Moreover, current technology makes it possible to inspect the fruit in spectral ranges beyond the sensibility of the human eye, for instance in the ultraviolet and near-infrared regions. Machine vision-based applications require the use of multiple technologies and knowledge, ranging from those related to image acquisition (illumination, cameras, etc.) to the development of algorithms for spectral image analysis. Machine vision-based systems for inspecting fruit and vegetables are targeted towards different purposes, from in-line sorting into commercial categories to the detection of contaminants or the distribution of specific chemical compounds on the product's surface. This chapter summarises the current state of the art in these techniques, starting with systems based on colour images for the inspection of conventional colour, shape or external defects and then goes on to consider recent developments in spectral image analysis for internal quality assessment or contaminant detection.

Design comparison of single phase outer and inner-rotor hybrid excitation flux switching motor for hybrid electric vehicles

NASA Astrophysics Data System (ADS)

Mazlan, Mohamed Mubin Aizat; Sulaiman, Erwan; Husin, Zhafir Aizat; Othman, Syed Muhammad Naufal Syed; Khan, Faisal

2015-05-01

In hybrid excitation machines (HEMs), there are two main flux sources which are permanent magnet (PM) and field excitation coil (FEC). These HEMs have better features when compared with the interior permanent magnet synchronous machines (IPMSM) used in conventional hybrid electric vehicles (HEVs). Since all flux sources including PM, FEC and armature coils are located on the stator core, the rotor becomes a single piece structure similar with switch reluctance machine (SRM). The combined flux generated by PM and FEC established more excitation fluxes that are required to produce much higher torque of the motor. In addition, variable DC FEC can control the flux capabilities of the motor, thus the machine can be applied for high-speed motor drive system. In this paper, the comparisons of single-phase 8S-4P outer and inner rotor hybrid excitation flux switching machine (HEFSM) are presented. Initially, design procedures of the HEFSM including parts drawing, materials and conditions setting, and properties setting are explained. Flux comparisons analysis is performed to investigate the flux capabilities at various current densities. Then the flux linkages of PM with DC FEC of various DC FEC current densities are examined. Finally torque performances are analyzed at various armature and FEC current densities for both designs. As a result, the outer-rotor HEFSM has higher flux linkage of PM with DC FEC and higher average torque of approximately 10% when compared with inner-rotor HEFSM.

Effects of a cementing technique in addition to luting agent on the uniaxial retention force of a single-tooth implant-supported restoration: an in vitro study.

PubMed

Santosa, Robert E; Martin, William; Morton, Dean

2010-01-01

Excess residual cement around the implant margin has been shown to be detrimental to the peri-implant tissue. This in vitro study examines the retentive strengths of two different cementing techniques and two different luting agents on a machined titanium abutment and solid screw implants. The amount of reduction of excess cement weight between the two cementation techniques was assessed. Forty gold castings were fabricated for 4.1 mm in diameter and 10 mm in length solid-screw dental implants paired with 5.5-mm machined titanium abutments. Twenty implants received a provisional cement, and 20 implants received a definitive cement. Each group was further divided into two groups. In the control group, cement was applied and the castings seated over the implant-abutment assembly. The excess cement was then removed. In the study group, a "practice abutment" was used to express excess cement prior to cementation. The weight of the implant-casting assembly was measured and the residual weight of cement was calculated. The samples were then stored for 24 hours at 100% humidity prior to tensile strength testing. Statistical analysis revealed significant differences in tensile strength across the groups. Further Tukey tests showed no significant difference in tensile strength between the practice abutment technique and the conventional technique for both definitive and provisional cements. There was a significant reduction in residual cement weight, irrespective of the type of cement, when the practice abutment was used prior to cementation. Cementation of implant restorations on a machined abutment using the practice abutment technique and definitive cement may provide similar uniaxial retention force and significantly reduced residual cement weight compared to the conventional technique of cement removal.

Performance analysis of cutting graphite-epoxy composite using a 90,000psi abrasive waterjet

NASA Astrophysics Data System (ADS)

Choppali, Aiswarya

Graphite-epoxy composites are being widely used in many aerospace and structural applications because of their properties: which include lighter weight, higher strength to weight ratio and a greater flexibility in design. However, the inherent anisotropy of these composites makes it difficult to machine them using conventional methods. To overcome the major issues that develop with conventional machining such as fiber pull out, delamination, heat generation and high tooling costs, an effort is herein made to study abrasive waterjet machining of composites. An abrasive waterjet is used to cut 1" thick graphite epoxy composites based on baseline data obtained from the cutting of ¼" thick material. The objective of this project is to study the surface roughness of the cut surface with a focus on demonstrating the benefits of using higher pressures for cutting composites. The effects of major cutting parameters: jet pressure, traverse speed, abrasive feed rate and cutting head size are studied at different levels. Statistical analysis of the experimental data provides an understanding of the effect of the process parameters on surface roughness. Additionally, the effect of these parameters on the taper angle of the cut is studied. The data is analyzed to obtain a set of process parameters that optimize the cutting of 1" thick graphite-epoxy composite. The statistical analysis is used to validate the experimental data. Costs involved in the cutting process are investigated in term of abrasive consumed to better understand and illustrate the practical benefits of using higher pressures. It is demonstrated that, as pressure increased, ultra-high pressure waterjets produced a better surface quality at a faster traverse rate with lower costs.

Rapid fabrication of microfluidic chips based on the simplest LED lithography

NASA Astrophysics Data System (ADS)

Li, Yue; Wu, Ping; Luo, Zhaofeng; Ren, Yuxuan; Liao, Meixiang; Feng, Lili; Li, Yuting; He, Liqun

2015-05-01

Microfluidic chips are generally fabricated by a soft lithography method employing commercial lithography equipment. These heavy machines require a critical room environment and high lamp power, and the cost remains too high for most normal laboratories. Here we present a novel microfluidics fabrication method utilizing a portable ultraviolet (UV) LED as an alternative UV source for photolithography. With this approach, we can repeat several common microchannels as do these conventional commercial exposure machines, and both the verticality of the channel sidewall and lithography resolution are proved to be acceptable. Further microfluidics applications such as mixing, blood typing and microdroplet generation are implemented to validate the practicability of the chips. This simple but innovative method decreases the cost and requirement of chip fabrication dramatically and may be more popular with ordinary laboratories.

Research on mechanical and sensoric set-up for high strain rate testing of high performance fibers

NASA Astrophysics Data System (ADS)

Unger, R.; Schegner, P.; Nocke, A.; Cherif, C.

2017-10-01

Within this research project, the tensile behavior of high performance fibers, such as carbon fibers, is investigated under high velocity loads. This contribution (paper) focuses on the clamp set-up of two testing machines. Based on a kinematic model, weight optimized clamps are designed and evaluated. By analyzing the complex dynamic behavior of conventional high velocity testing machines, it has been shown that the impact typically exhibits an elastic characteristic. This leads to barely predictable breaking speeds and will not work at higher speeds when acceleration force exceeds material specifications. Therefore, a plastic impact behavior has to be achieved, even at lower testing speeds. This type of impact behavior at lower speeds can be realized by means of some minor test set-up adaptions.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT.

PubMed

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-12-09

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT

PubMed Central

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-01-01

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object. PMID:29232850

Design and fabrication of novel anode flow-field for commercial size solid oxide fuel cells

NASA Astrophysics Data System (ADS)

Canavar, Murat; Timurkutluk, Bora

2017-04-01

In this study, nickel based woven meshes are tested as not only anode current collecting meshes but also anode flow fields instead of the conventional gas channels fabricated by machining. For this purpose, short stacks with different anode flow fields are designed and built by using different number of meshes with various wire diameters and widths of opening. A short stack with classical machined flow channels is also constructed. Performance and impedance measurements of the short stacks with commercial size cells of 81 cm2 active area are performed and compared. The results reveal that it is possible to create solid oxide fuel cell anode flow fields with woven meshes and obtain acceptable power with a proper selection of the mesh number, type and orientation.

Rotating electrical machines: Poynting flow

NASA Astrophysics Data System (ADS)

Donaghy-Spargo, C.

2017-09-01

This paper presents a complementary approach to the traditional Lorentz and Faraday approaches that are typically adopted in the classroom when teaching the fundamentals of electrical machines—motors and generators. The approach adopted is based upon the Poynting vector, which illustrates the ‘flow’ of electromagnetic energy. It is shown through simple vector analysis that the energy-flux density flow approach can provide insight into the operation of electrical machines and it is also shown that the results are in agreement with conventional Maxwell stress-based theory. The advantage of this approach is its complementary completion of the physical picture regarding the electromechanical energy conversion process—it is also a means of maintaining student interest in this subject and as an unconventional application of the Poynting vector during normal study of electromagnetism.

Machine Learning for Slow but Steady Interplanetary Construction

NASA Technical Reports Server (NTRS)

Agogino, Adrian

2017-01-01

For prolonged manned missions to destinations such as the moon and Mars, there is a need for significant infrastructure construction ahead of time, such as habitats and landing pads. Unfortunately we have little experience in remote construction and using conventional methods is likely to be expensive, cumbersome and unreliable. Fortunately these challenges may be overcome by taking advantage of the long lead time for such missions and using teams of small and slow construction robots. We propose using teams of simple autonomous robots for this purpose that would perform continuous construction over a period of many years or even decades. While individual robot reliability will be low over such long time frames, system reliability will be maintained by using machine learning over simulations to achieve coordination and reconfigurations in the event of lost robots.

A modified artificial immune system based pattern recognition approach -- an application to clinic diagnostics

PubMed Central

Zhao, Weixiang; Davis, Cristina E.

2011-01-01

Objective This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis. Methods and materials Conventionally, the AIS approach is often coupled with the k nearest neighbor (k-NN) algorithm to form a classification method called AIS-kNN. In this paper we discuss the basic principle and possible problems of this conventional approach, and propose a new approach where AIS is integrated with the radial basis function – partial least square regression (AIS-RBFPLS). Additionally, both the two AIS-based approaches are compared with two classical and powerful machine learning methods, back-propagation neural network (BPNN) and orthogonal radial basis function network (Ortho-RBF network). Results The diagnosis results show that: (1) both the AIS-kNN and the AIS-RBFPLS proved to be a good machine leaning method for clinical diagnosis, but the proposed AIS-RBFPLS generated an even lower misclassification ratio, especially in the cases where the conventional AIS-kNN approach generated poor classification results because of possible improper AIS parameters. For example, based upon the AIS memory cells of “replacement threshold = 0.3”, the average misclassification ratios of two approaches for study 1 are 3.36% (AIS-RBFPLS) and 9.07% (AIS-kNN), and the misclassification ratios for study 2 are 19.18% (AIS-RBFPLS) and 28.36% (AIS-kNN); (2) the proposed AIS-RBFPLS presented its robustness in terms of the AIS-created memory cells, showing a smaller standard deviation of the results from the multiple trials than AIS-kNN. For example, using the result from the first set of AIS memory cells as an example, the standard deviations of the misclassification ratios for study 1 are 0.45% (AIS-RBFPLS) and 8.71% (AIS-kNN) and those for study 2 are 0.49% (AIS-RBFPLS) and 6.61% (AIS-kNN); and (3) the proposed AIS-RBFPLS classification approaches also yielded better diagnosis results than two classical neural network approaches of BPNN and Ortho-RBF network. Conclusion In summary, this paper proposed a new machine learning method for complex systems by integrating the AIS system with RBFPLS. This new method demonstrates its satisfactory effect on classification accuracy for clinical diagnosis, and also indicates its wide potential applications to other diagnosis and detection problems. PMID:21515033

Modeling of Principal Flank Wear: An Empirical Approach Combining the Effect of Tool, Environment and Workpiece Hardness

NASA Astrophysics Data System (ADS)

Mia, Mozammel; Al Bashir, Mahmood; Dhar, Nikhil Ranjan

2016-10-01

Hard turning is increasingly employed in machining, lately, to replace time-consuming conventional turning followed by grinding process. An excessive amount of tool wear in hard turning is one of the main hurdles to be overcome. Many researchers have developed tool wear model, but most of them developed it for a particular work-tool-environment combination. No aggregate model is developed that can be used to predict the amount of principal flank wear for specific machining time. An empirical model of principal flank wear (VB) has been developed for the different hardness of workpiece (HRC40, HRC48 and HRC56) while turning by coated carbide insert with different configurations (SNMM and SNMG) under both dry and high pressure coolant conditions. Unlike other developed model, this model includes the use of dummy variables along with the base empirical equation to entail the effect of any changes in the input conditions on the response. The base empirical equation for principal flank wear is formulated adopting the Exponential Associate Function using the experimental results. The coefficient of dummy variable reflects the shifting of the response from one set of machining condition to another set of machining condition which is determined by simple linear regression. The independent cutting parameters (speed, rate, depth of cut) are kept constant while formulating and analyzing this model. The developed model is validated with different sets of machining responses in turning hardened medium carbon steel by coated carbide inserts. For any particular set, the model can be used to predict the amount of principal flank wear for specific machining time. Since the predicted results exhibit good resemblance with experimental data and the average percentage error is <10 %, this model can be used to predict the principal flank wear for stated conditions.

Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes.

PubMed

Wang, Yuanjia; Chen, Tianle; Zeng, Donglin

2016-01-01

Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse probability weighting or rank-based regression, which may be inefficient. In this paper, we develop a new support vector hazards machine (SVHM) approach to predict censored outcomes. Our method is based on predicting the counting process associated with the time-to-event outcomes among subjects at risk via a series of support vector machines. Introducing counting processes to represent time-to-event data leads to a connection between support vector machines in supervised learning and hazards regression in standard survival analysis. To account for different at risk populations at observed event times, a time-varying offset is used in estimating risk scores. The resulting optimization is a convex quadratic programming problem that can easily incorporate non-linearity using kernel trick. We demonstrate an interesting link from the profiled empirical risk function of SVHM to the Cox partial likelihood. We then formally show that SVHM is optimal in discriminating covariate-specific hazard function from population average hazard function, and establish the consistency and learning rate of the predicted risk using the estimated risk scores. Simulation studies show improved prediction accuracy of the event times using SVHM compared to existing machine learning methods and standard conventional approaches. Finally, we analyze two real world biomedical study data where we use clinical markers and neuroimaging biomarkers to predict age-at-onset of a disease, and demonstrate superiority of SVHM in distinguishing high risk versus low risk subjects.

Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.

PubMed

Kim, Jongin; Lee, Boreom

2018-05-07

Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which is likely to be very useful for diagnosis of AD and MCI. Therefore, it is possible to develop a more effective and accurate AD/MCI automatic diagnosis method by integrating complementary information of different modalities. In this paper, we propose multi-modal sparse hierarchical extreme leaning machine (MSH-ELM). We used volume and mean intensity extracted from 93 regions of interest (ROIs) as features of MRI and FDG-PET, respectively, and used p-tau, t-tau, and Aβ42 as CSF features. In detail, high-level representation was individually extracted from each of MRI, FDG-PET, and CSF using a stacked sparse extreme learning machine auto-encoder (sELM-AE). Then, another stacked sELM-AE was devised to acquire a joint hierarchical feature representation by fusing the high-level representations obtained from each modality. Finally, we classified joint hierarchical feature representation using a kernel-based extreme learning machine (KELM). The results of MSH-ELM were compared with those of conventional ELM, single kernel support vector machine (SK-SVM), multiple kernel support vector machine (MK-SVM) and stacked auto-encoder (SAE). Performance was evaluated through 10-fold cross-validation. In the classification of AD vs. HC and MCI vs. HC problem, the proposed MSH-ELM method showed mean balanced accuracies of 96.10% and 86.46%, respectively, which is much better than those of competing methods. In summary, the proposed algorithm exhibits consistently better performance than SK-SVM, ELM, MK-SVM and SAE in the two binary classification problems (AD vs. HC and MCI vs. HC). © 2018 Wiley Periodicals, Inc.

Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

PubMed

Feng, Zhichao; Rong, Pengfei; Cao, Peng; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei

2018-04-01

To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • Although conventional CT is useful for diagnosis of SRMs, it has limitations. • Machine-learning based CT texture analysis facilitate differentiation of small AMLwvf from RCC. • The highest accuracy of SVM-RFE+SMOTE classifier reached 93.9 %. • Texture analysis combined with machine-learning methods might spare unnecessary surgery for AMLwvf.

Study on effect of tool electrodes on surface finish during electrical discharge machining of Nitinol

NASA Astrophysics Data System (ADS)

Sahu, Anshuman Kumar; Chatterjee, Suman; Nayak, Praveen Kumar; Sankar Mahapatra, Siba

2018-03-01

Electrical discharge machining (EDM) is a non-traditional machining process which is widely used in machining of difficult-to-machine materials. EDM process can produce complex and intrinsic shaped component made of difficult-to-machine materials, largely applied in aerospace, biomedical, die and mold making industries. To meet the required applications, the EDMed components need to possess high accuracy and excellent surface finish. In this work, EDM process is performed using Nitinol as work piece material and AlSiMg prepared by selective laser sintering (SLS) as tool electrode along with conventional copper and graphite electrodes. The SLS is a rapid prototyping (RP) method to produce complex metallic parts by additive manufacturing (AM) process. Experiments have been carried out varying different process parameters like open circuit voltage (V), discharge current (Ip), duty cycle (τ), pulse-on-time (Ton) and tool material. The surface roughness parameter like average roughness (Ra), maximum height of the profile (Rt) and average height of the profile (Rz) are measured using surface roughness measuring instrument (Talysurf). To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L27 orthogonal array has been chosen. The surface properties of the EDM specimen are optimized by desirability function approach and the best parametric setting is reported for the EDM process. Type of tool happens to be the most significant parameter followed by interaction of tool type and duty cycle, duty cycle, discharge current and voltage. Better surface finish of EDMed specimen can be obtained with low value of voltage (V), discharge current (Ip), duty cycle (τ) and pulse on time (Ton) along with the use of AlSiMg RP electrode.

Influence of different luting protocols on shear bond strength of computer aided design/computer aided manufacturing resin nanoceramic material to dentin

PubMed Central

Poggio, Claudio; Pigozzo, Marco; Ceci, Matteo; Scribante, Andrea; Beltrami, Riccardo; Chiesa, Marco

2016-01-01

Background: The purpose of this study was to evaluate the influence of three different luting protocols on shear bond strength of computer aided design/computer aided manufacturing (CAD/CAM) resin nanoceramic (RNC) material to dentin. Materials and Methods: In this in vitro study, 30 disks were milled from RNC blocks (Lava Ultimate/3M ESPE) with CAD/CAM technology. The disks were subsequently cemented to the exposed dentin of 30 recently extracted bovine permanent mandibular incisors. The specimens were randomly assigned into 3 groups of 10 teeth each. In Group 1, disks were cemented using a total-etch protocol (Scotchbond™ Universal Etchant phosphoric acid + Scotchbond Universal Adhesive + RelyX™ Ultimate conventional resin cement); in Group 2, disks were cemented using a self-etch protocol (Scotchbond Universal Adhesive + RelyX™ Ultimate conventional resin cement); in Group 3, disks were cemented using a self-adhesive protocol (RelyX™ Unicem 2 Automix self-adhesive resin cement). All cemented specimens were placed in a universal testing machine (Instron Universal Testing Machine 3343) and submitted to a shear bond strength test to check the strength of adhesion between the two substrates, dentin, and RNC disks. Specimens were stressed at a crosshead speed of 1 mm/min. Data were analyzed with analysis of variance and post-hoc Tukey's test at a level of significance of 0.05. Results: Post-hoc Tukey testing showed that the highest shear strength values (P < 0.001) were reported in Group 2. The lowest data (P < 0.001) were recorded in Group 3. Conclusion: Within the limitations of this in vitro study, conventional resin cements (coupled with etch and rinse or self-etch adhesives) showed better shear strength values compared to self-adhesive resin cements. Furthermore, conventional resin cements used together with a self-etch adhesive reported the highest values of adhesion. PMID:27076822

Miniature Scroll Pumps Fabricated by LIGA

NASA Technical Reports Server (NTRS)

Wiberg, Dean; Shcheglov, Kirill; White, Victor; Bae, Sam

2009-01-01

Miniature scroll pumps have been proposed as roughing pumps (low - vacuum pumps) for miniature scientific instruments (e.g., portable mass spectrometers and gas analyzers) that depend on vacuum. The larger scroll pumps used as roughing pumps in some older vacuum systems are fabricated by conventional machining. Typically, such an older scroll pump includes (1) an electric motor with an eccentric shaft to generate orbital motion of a scroll and (2) conventional bearings to restrict the orbital motion to a circle. The proposed miniature scroll pumps would differ from the prior, larger ones in both design and fabrication. A miniature scroll pump would include two scrolls: one mounted on a stationary baseplate and one on a flexure stage (see figure). An electromagnetic actuator in the form of two pairs of voice coils in a push-pull configuration would make the flexure stage move in the desired circular orbit. The capacitance between the scrolls would be monitored to provide position (gap) feedback to a control system that would adjust the drive signals applied to the voice coils to maintain the circular orbit as needed for precise sealing of the scrolls. To minimize power consumption and maximize precision of control, the flexure stage would be driven at the frequency of its mechanical resonance. The miniaturization of these pumps would entail both operational and manufacturing tolerances of <1 m. Such tight tolerances cannot be achieved easily by conventional machining of high-aspect-ratio structures like those of scroll-pump components. In addition, the vibrations of conventional motors and ball bearings exceed these tight tolerances by an order of magnitude. Therefore, the proposed pumps would be fabricated by the microfabrication method known by the German acronym LIGA ( lithographie, galvanoformung, abformung, which means lithography, electroforming, molding) because LIGA has been shown to be capable of providing the required tolerances at large aspect ratios.

Influence of different luting protocols on shear bond strength of computer aided design/computer aided manufacturing resin nanoceramic material to dentin.

PubMed

Poggio, Claudio; Pigozzo, Marco; Ceci, Matteo; Scribante, Andrea; Beltrami, Riccardo; Chiesa, Marco

2016-01-01

The purpose of this study was to evaluate the influence of three different luting protocols on shear bond strength of computer aided design/computer aided manufacturing (CAD/CAM) resin nanoceramic (RNC) material to dentin. In this in vitro study, 30 disks were milled from RNC blocks (Lava Ultimate/3M ESPE) with CAD/CAM technology. The disks were subsequently cemented to the exposed dentin of 30 recently extracted bovine permanent mandibular incisors. The specimens were randomly assigned into 3 groups of 10 teeth each. In Group 1, disks were cemented using a total-etch protocol (Scotchbond™ Universal Etchant phosphoric acid + Scotchbond Universal Adhesive + RelyX™ Ultimate conventional resin cement); in Group 2, disks were cemented using a self-etch protocol (Scotchbond Universal Adhesive + RelyX™ Ultimate conventional resin cement); in Group 3, disks were cemented using a self-adhesive protocol (RelyX™ Unicem 2 Automix self-adhesive resin cement). All cemented specimens were placed in a universal testing machine (Instron Universal Testing Machine 3343) and submitted to a shear bond strength test to check the strength of adhesion between the two substrates, dentin, and RNC disks. Specimens were stressed at a crosshead speed of 1 mm/min. Data were analyzed with analysis of variance and post-hoc Tukey's test at a level of significance of 0.05. Post-hoc Tukey testing showed that the highest shear strength values (P < 0.001) were reported in Group 2. The lowest data (P < 0.001) were recorded in Group 3. Within the limitations of this in vitro study, conventional resin cements (coupled with etch and rinse or self-etch adhesives) showed better shear strength values compared to self-adhesive resin cements. Furthermore, conventional resin cements used together with a self-etch adhesive reported the highest values of adhesion.

Bidirectional extreme learning machine for regression problem and its learning effectiveness.

PubMed

Yang, Yimin; Wang, Yaonan; Yuan, Xiaofang

2012-09-01

It is clear that the learning effectiveness and learning speed of neural networks are in general far slower than required, which has been a major bottleneck for many applications. Recently, a simple and efficient learning method, referred to as extreme learning machine (ELM), was proposed by Huang , which has shown that, compared to some conventional methods, the training time of neural networks can be reduced by a thousand times. However, one of the open problems in ELM research is whether the number of hidden nodes can be further reduced without affecting learning effectiveness. This brief proposes a new learning algorithm, called bidirectional extreme learning machine (B-ELM), in which some hidden nodes are not randomly selected. In theory, this algorithm tends to reduce network output error to 0 at an extremely early learning stage. Furthermore, we find a relationship between the network output error and the network output weights in the proposed B-ELM. Simulation results demonstrate that the proposed method can be tens to hundreds of times faster than other incremental ELM algorithms.

Modeling and Designing of A Nonlineartemperature-Humidity Controller Using Inmushroom-Drying Machine

NASA Astrophysics Data System (ADS)

Wu, Xiuhua; Luo, Haiyan; Shi, Minhui

Drying-process of many kinds of farm produce in a close room, such as mushroom-drying machine, is generally a complicated nonlinear and timedelay cause, in which the temperature and the humidity are the main controlled elements. The accurate controlling of the temperature and humidity is always an interesting problem. It's difficult and very important to make a more accurate mathematical model about the varying of the two. A math model was put forward after considering many aspects and analyzing the actual working circumstance in this paper. Form the model it can be seen that the changes of temperature and humidity in drying machine are not simple linear but an affine nonlinear process. Controlling the process exactly is the key that influences the quality of the dried mushroom. In this paper, the differential geometry theories and methods are used to analyze and solve the model of these smallenvironment elements. And at last a kind of nonlinear controller which satisfied the optimal quadratic performance index is designed. It can be proved more feasible and practical than the conventional controlling.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

A magnetic damper for first mode vibration reduction in multimass flexible rotors

NASA Technical Reports Server (NTRS)

Kasarda, M. E. F.; Allaire, P. E.; Humphris, R. R.; Barrett, L. E.

1989-01-01

Many rotating machines such as compressors, turbines and pumps have long thin shafts with resulting vibration problems, and would benefit from additional damping near the center of the shaft. Magnetic dampers have the potential to be employed in these machines because they can operate in the working fluid environment unlike conventional bearings. An experimental test rig is described which was set up with a long thin shaft and several masses to represent a flexible shaft machine. An active magnetic damper was placed in three locations: near the midspan, near one end disk, and close to the bearing. With typical control parameter settings, the midspan location reduced the first mode vibration 82 percent, the disk location reduced it 75 percent and the bearing location attained a 74 percent reduction. Magnetic damper stiffness and damping values used to obtain these reductions were only a few percent of the bearing stiffness and damping values. A theoretical model of both the rotor and the damper was developed and compared to the measured results. The agreement was good.

Development of Keropok Keping Drying Machine for Small & Medium Enterprises (SMEs)

NASA Astrophysics Data System (ADS)

Mohamaddan, S.; Mohd Mohtar, A. M. A. A.; Junaidi, N.; Mohtadzar, N. A. A.; Mohamad Suffian, M. S. Z.

2016-02-01

Keropok is a traditional cracker product in Southeast Asia. Keropok is made from fish, squid or shrimp mixed with starch or sago flour and eggs. In Malaysia, keropok industry is widely operated at the coastal areas where the fish/seafood supply can be easily accessed. Keropok need to be dried before the packaging process. At the moment, conventional method was used where the keropok is arranged under the sunlight on a board called pemidai. The method is considered less hygienic since it exposed to the dirt and dust and less practical especially during the raining season. This research is focusing on a new automation technique to solve the problems. Rotary drum with internal holder was developed as the drying machine. Keropok keping (types of keropok) was selected to be experimented using the machine with three different rotating speeds. Preliminary experiment result shows that the broken rate of the keropok keping was around 27% of the total weight. The development of new automation system is hoped to improve the small medium enterprises (SMEs) in Malaysia.

The wear properties of CFR-PEEK-OPTIMA articulating against ceramic assessed on a multidirectional pin-on-plate machine.

PubMed

Scholes, S C; Unsworth, A

2007-04-01

In an attempt to prolong the lives of rubbing implantable devices, several 'new' materials have been examined to determine their suitability as joint couplings. Tests were performed on a multidirectional pin-on-plate machine to determine the wear of both pitch and PAN (polyacrylonitrile)-based carbon fibre reinforced-polyetheretherketone (CFR-PEEK-OPTIMA) pins articulating against both BioLox Delta and BioLox Forte plates (ceramic materials). Both reciprocation and rotational motion were applied to the samples. The tests were conducted using 24.5 per cent bovine serum as the lubricant (protein concentration 15 g/l). Although all four material combinations gave similar low wear with no statistically significant difference (p > 0.25), the lowest average total wear of these pin-on-plate tests was provided by CFR-PEEK-OPTIMA pitch pins versus BioLox Forte plates. This was much lower than the wear produced by conventional joint materials (metal-on-polyethylene) and metal-on-metal combinations when tested on the pin-on-plate machine. This therefore indicates optimism that these PEEK-OPTIMA-based material combinations may perform well in joint applications.

Performance characteristics and typical industrial applications of Selfshield® electron accelerators (< 300 kV)

NASA Astrophysics Data System (ADS)

Aaronson, Judith N.; Nablo, Sam V.

1985-05-01

Selfshielded electron accelerators have been successfully used in industry for more than ten years. One of the important advantages of these machines is their compactness for easy adaptation to conventional coating and product finishing machinery. It is equally important that these machines qualify for use under "unrestricted" conditions as specified by OSHA. The shielding and product handling configurations which make this unrestricted designation possible for operating voltages under 300 kV are discussed. Thin film dosimetry techniques used for the determination of the machine performance parameters are discussed along with the rotary scanner techniques employed for the dose rate studies which are important in the application of these processors. Paper and wood coatings, which are important industrial applications involving electron initiated polymerization, are reviewed. The sterilization and disinfestation applications are also discussed. The increasing concern of these industries for the more efficient use of energy and for compliance with more stringent pollution regulations, coupled with the novel processes this energy source makes possible, assure a bright future for this developing technology.

Accelerating Industrial Adoption of Metal Additive Manufacturing Technology

NASA Astrophysics Data System (ADS)

Vartanian, Kenneth; McDonald, Tom

2016-03-01

While metal additive manufacturing (AM) technology has clear benefits, there are still factors preventing its adoption by industry. These factors include the high cost of metal AM systems, the difficulty for machinists to learn and operate metal AM machines, the long approval process for part qualification/certification, and the need for better process controls; however, the high AM system cost is the main barrier deterring adoption. In this paper, we will discuss an America Makes-funded program to reduce AM system cost by combining metal AM technology with conventional computerized numerical controlled (CNC) machine tools. Information will be provided on how an Optomec-led team retrofitted a legacy CNC vertical mill with laser engineered net shaping (LENS®—LENS is a registered trademark of Sandia National Labs) AM technology, dramatically lowering deployment cost. The upgraded system, dubbed LENS Hybrid Vertical Mill, enables metal additive and subtractive operations to be performed on the same machine tool and even on the same part. Information on the LENS Hybrid system architecture, learnings from initial system deployment and continuing development work will also be provided to help guide further development activities within the materials community.

Economic use of CBN grinding tools in the production of jet turbine components

NASA Astrophysics Data System (ADS)

Geisler, R.; Hallen, D.

The use of cubical boron nitride (CBN) grinding wheels in the production of jet turbine components of superalloys such as Inconel 100, Nimonic 90 or Rene 120 with the aid of an example of guide vane machining for low pressure turbines is described. Cost savings achieved by the use of CBN wheels as compared with conventional grinding wheels and spark erosion are presented in tabular form.

Laser circular cutting of Kevlar sheets: Analysis of thermal stress filed and assessment of cutting geometry

NASA Astrophysics Data System (ADS)

Yilbas, B. S.; Akhtar, S. S.; Karatas, C.

2017-11-01

A Kevlar laminate has negative thermal expansion coefficient, which makes it difficult to machine at room temperaures using the conventional cutting tools. Contararily, laser machining of a Kevlar laminate provides advantages over the conventional methods because of the non-mechanical contact between the cutting tool and the workpiece. In the present study, laser circular cutting of Kevlar laminate is considered. The experiment is carried out to examine and evaluate the cutting sections. Temperature and stress fields formed in the cutting section are simulated in line with the experimental study. The influence of hole diameters on temperature and stress fields are investigated incorporating two different hole diameters. It is found that the Kevlar laminate cutting section is free from large size asperities such as large scale sideways burnings and attachemnt of charred residues. The maximum temperature along the cutting circumference remains higher for the large diameter hole than that of the small diameter hole. Temperature decay is sharp around the cutting section in the region where the cutting terminates. This, in turn, results in high temperature gradients and the thermal strain in the cutting region. von Mises stress remains high in the region where temperature gradients are high. von Mises stress follows similar to the trend of temperature decay around the cutting edges.

High power density superconducting rotating machines—development status and technology roadmap

NASA Astrophysics Data System (ADS)

Haran, Kiruba S.; Kalsi, Swarn; Arndt, Tabea; Karmaker, Haran; Badcock, Rod; Buckley, Bob; Haugan, Timothy; Izumi, Mitsuru; Loder, David; Bray, James W.; Masson, Philippe; Stautner, Ernst Wolfgang

2017-12-01

Superconducting technology applications in electric machines have long been pursued due to their significant advantages of higher efficiency and power density over conventional technology. However, in spite of many successful technology demonstrations, commercial adoption has been slow, presumably because the threshold for value versus cost and technology risk has not yet been crossed. One likely path for disruptive superconducting technology in commercial products could be in applications where its advantages become key enablers for systems which are not practical with conventional technology. To help systems engineers assess the viability of such future solutions, we present a technology roadmap for superconducting machines. The timeline considered was ten years to attain a Technology Readiness Level of 6+, with systems demonstrated in a relevant environment. Future projections, by definition, are based on the judgment of specialists, and can be subjective. Attempts have been made to obtain input from a broad set of organizations for an inclusive opinion. This document was generated through a series of teleconferences and in-person meetings, including meetings at the 2015 IEEE PES General meeting in Denver, CO, the 2015 ECCE in Montreal, Canada, and a final workshop in April 2016 at the University of Illinois, Urbana-Champaign that brought together a broad group of technical experts spanning the industry, government and academia.

Effect of incorporation of zinc oxide nanoparticles on mechanical properties of conventional glass ionomer cements.

PubMed

Panahandeh, Narges; Torabzadeh, Hassan; Aghaee, Mohammadamin; Hasani, Elham; Safa, Saeed

2018-01-01

The aim of this study is to investigate the physical properties of conventional and resin-modified glass ionomer cements (GICs) compared to GICs supplemented with zinc oxide (ZnO) nanofiller particles at 5% (w/w). In this in vitro study, ZnO nanoparticles of different morphologies (nanospherical, nanorod, and nanoflower) were incorporated to glass ionomer powder. The samples were subjected to the flexural strength ( n = 20) and surface hardness test ( n = 12) using a universal testing machine and a Vickers hardness machine, respectively. Surface analysis and crystal structure of samples were performed with scanning electron microscope and X-radiation diffraction, respectively. The data were analyzed using one-way ANOVA, Shapiro-Wilk, and Tukey's tests ( P < 0.05). Flexural strength of glass ionomer containing nanoparticles was not significantly different from the control group ( P > 0.05). The surface hardness of the glass ionomer containing nanospherical or nanoflower ZnO was significantly lower than the control group ( P < 0.05). However, the surface hardness of glass ionomer containing nanorod ZnO was not significantly different from the control group ( P = 0.868). Incorporation of nanospherical and nanoflower ZnO to glass ionomer decreased their surface hardness, without any changes on their flexural strength. Incorporation of nanorod ZnO particles caused no effect on the mechanical properties.

Tensile Properties and Microstructure of Inconel 718 Fabricated with Electron Beam Freeform Fabrication (EBF(sup 3))

NASA Technical Reports Server (NTRS)

Bird, R. Keith; Hibberd, Joshua

2009-01-01

Electron beam freeform fabrication (EBF3) direct metal deposition processing was used to fabricate two Inconel 718 single-bead-width wall builds and one multiple-bead-width block build. Specimens were machined to evaluate microstructure and room temperature tensile properties. The tensile strength and yield strength of the as-deposited material from the wall and block builds were greater than those for conventional Inconel 718 castings but were less than those for conventional cold-rolled sheet. Ductility levels for the EBF3 material were similar to those for conventionally-processed sheet and castings. An unexpected result was that the modulus of the EBF3-deposited Inconel 718 was significantly lower than that of the conventional material. This low modulus may be associated with a preferred crystallographic orientation resultant from the deposition and rapid solidification process. A heat treatment with a high solution treatment temperature resulted in a recrystallized microstructure and an increased modulus. However, the modulus was not increased to the level that is expected for Inconel 718.

Power-Factor and Torque Calculation under Consideration of Cross Saturation of the Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

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

Lee, Seong T; Burress, Timothy A; Tolbert, Leon M

2009-01-01

This paper introduces a new method for calculating the power factor and output torque by considering the cross saturation between direct-axis (d-axis) and quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux atmore » high speed, which was developed for the traction motor of a hybrid electric vehicle. The conventional two-axis IPMSM model was modified to include the cross-saturation effect by adding the cross-coupled inductance terms Ldq and Lqd. By the advantage of the excited structure of the experimental IPMSM, the analyzing works were performed under two conditions, the highest and lowest excited conditions. Therefore, it is possible to investigate the cross-saturation effect when a machine has higher magnetic flux from its rotor. The following is a summary of conclusions that may be drawn from this work: (1) Considering cross saturation of an IPMSM offers more accurate expected values of motor parameters in output torque calculation, especially when negative d-axis current is high; (2) A less saturated synchronous machine could be more affected by the cross-coupled saturation effect; (3) Both cross-coupled inductances, L{sub qd} and L{sub dq}, are mainly governed by d-axis current rather than q-axis current; (4) The modified torque equation, can be used for the dynamic model of an IPMSM for developing a better control model or control strategy; and (5) It is possible that the brushless field excitation structure has a common magnetic flux path on both d- and q-axis, and as a result, the reluctance torque of the machine could be reduced.« less

Coniferous forest classification and inventory using Landsat and digital terrain data

NASA Technical Reports Server (NTRS)

Franklin, J.; Logan, T. L.; Woodcock, C. E.; Strahler, A. H.

1986-01-01

Machine-processing techniques were used in a Forest Classification and Inventory System (FOCIS) procedure to extract and process tonal, textural, and terrain information from registered Landsat multispectral and digital terrain data. Using FOCIS as a basis for stratified sampling, the softwood timber volumes of the Klamath National Forest and Eldorado National Forest were estimated within standard errors of 4.8 and 4.0 percent, respectively. The accuracy of these large-area inventories is comparable to the accuracy yielded by use of conventional timber inventory methods, but, because of automation, the FOCIS inventories are more rapid (9-12 months compared to 2-3 years for conventional manual photointerpretation, map compilation and drafting, field sampling, and data processing) and are less costly.

A review of X-ray explosives detection techniques for checked baggage.

PubMed

Wells, K; Bradley, D A

2012-08-01

In recent times, the security focus for civil aviation has shifted from hijacking in the 1980s, towards deliberate sabotage. X-ray imaging provides a major tool in checked baggage inspection, with various sensitive techniques being brought to bear in determining the form, and density of items within luggage as well as other material dependent parameters. This review first examines the various challenges to X-ray technology in securing a safe system of passenger transportation. An overview is then presented of the various conventional and less conventional approaches that are available to the airline industry, leading to developments in state-of-the-art imaging technology supported by enhanced machine and observer-based decision making principles. Copyright © 2012 Elsevier Ltd. All rights reserved.

High-capacity high-speed recording

NASA Astrophysics Data System (ADS)

Jamberdino, A. A.

1981-06-01

Continuing advances in wideband communications and information handling are leading to extremely large volume digital data systems for which conventional data storage techniques are becoming inadequate. The paper presents an assessment of alternative recording technologies for the extremely wideband, high capacity storage and retrieval systems currently under development. Attention is given to longitudinal and rotary head high density magnetic recording, laser holography in human readable/machine readable devices and a wideband recorder, digital optical disks, and spot recording in microfiche formats. The electro-optical technologies considered are noted to be capable of providing data bandwidths up to 1000 megabits/sec and total data storage capacities in the 10 to the 11th to 10 to the 12th bit range, an order of magnitude improvement over conventional technologies.

Nano Mechanical Machining Using AFM Probe

NASA Astrophysics Data System (ADS)

Mostofa, Md. Golam

Complex miniaturized components with high form accuracy will play key roles in the future development of many products, as they provide portability, disposability, lower material consumption in production, low power consumption during operation, lower sample requirements for testing, and higher heat transfer due to their very high surface-to-volume ratio. Given the high market demand for such micro and nano featured components, different manufacturing methods have been developed for their fabrication. Some of the common technologies in micro/nano fabrication are photolithography, electron beam lithography, X-ray lithography and other semiconductor processing techniques. Although these methods are capable of fabricating micro/nano structures with a resolution of less than a few nanometers, some of the shortcomings associated with these methods, such as high production costs for customized products, limited material choices, necessitate the development of other fabricating techniques. Micro/nano mechanical machining, such an atomic force microscope (AFM) probe based nano fabrication, has, therefore, been used to overcome some the major restrictions of the traditional processes. This technique removes material from the workpiece by engaging micro/nano size cutting tool (i.e. AFM probe) and is applicable on a wider range of materials compared to the photolithographic process. In spite of the unique benefits of nano mechanical machining, there are also some challenges with this technique, since the scale is reduced, such as size effects, burr formations, chip adhesions, fragility of tools and tool wear. Moreover, AFM based machining does not have any rotational movement, which makes fabrication of 3D features more difficult. Thus, vibration-assisted machining is introduced into AFM probe based nano mechanical machining to overcome the limitations associated with the conventional AFM probe based scratching method. Vibration-assisted machining reduced the cutting forces and burr formations through intermittent cutting. Combining the AFM probe based machining with vibration-assisted machining enhanced nano mechanical machining processes by improving the accuracy, productivity and surface finishes. In this study, several scratching tests are performed with a single crystal diamond AFM probe to investigate the cutting characteristics and model the ploughing cutting forces. Calibration of the probe for lateral force measurements, which is essential, is also extended through the force balance method. Furthermore, vibration-assisted machining system is developed and applied to fabricate different materials to overcome some of the limitations of the AFM probe based single point nano mechanical machining. The novelty of this study includes the application of vibration-assisted AFM probe based nano scale machining to fabricate micro/nano scale features, calibration of an AFM by considering different factors, and the investigation of the nano scale material removal process from a different perspective.

Comparison of portable and conventional ultrasound imaging in spinal curvature measurement

NASA Astrophysics Data System (ADS)

Yan, Christina; Tabanfar, Reza; Kempston, Michael; Borschneck, Daniel; Ungi, Tamas; Fichtinger, Gabor

2016-03-01

PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks, but bones have reduced visibility in ultrasound imaging and high quality ultrasound machines are often expensive and not portable. In this work, we investigate the image quality and measurement accuracy of a low cost and portable ultrasound machine in comparison to a standard ultrasound machine in scoliosis monitoring. METHODS: Two different kinds of ultrasound machines were tested on three human subjects, using the same position tracker and software. Spinal curves were measured in the same reference coordinate system using both ultrasound machines. Lines were defined by connecting two symmetric landmarks identified on the left and right transverse process of the same vertebrae, and spinal curvature was defined as the transverse process angle between two such lines, projected on the coronal plane. RESULTS: Three healthy volunteers were scanned by both ultrasound configurations. Three experienced observers localized transverse processes as skeletal landmarks and obtained transverse process angles in images obtained from both ultrasounds. The mean difference per transverse process angle measured was 3.00 +/-2.1°. 94% of transverse processes visualized in the Sonix Touch were also visible in the Telemed. Inter-observer error in the Telemed was 4.5° and 4.3° in the Sonix Touch. CONCLUSION: Price, convenience and accessibility suggest the Telemed to be a viable alternative in scoliosis monitoring, however further improvements in measurement protocol and image noise reduction must be completed before implementing the Telemed in the clinical setting.

Novel model of stator design to reduce the mass of superconducting generators

NASA Astrophysics Data System (ADS)

Kails, Kevin; Li, Quan; Mueller, Markus

2018-05-01

High temperature superconductors (HTS), with much higher current density than conventional copper wires, make it feasible to develop very powerful and compact power generators. Thus, they are considered as one promising solution for large (10 + MW) direct-drive offshore wind turbines due to their low tower head mass. However, most HTS generator designs are based on a radial topology, which requires an excessive amount of HTS material and suffers from cooling and reliability issues. Axial flux machines on the other hand offer higher torque/volume ratios than the radial machines, which makes them an attractive option where space and transportation becomes an issue. However, their disadvantage is heavy structural mass. In this paper a novel stator design is introduced for HTS axial flux machines which enables a reduction in their structural mass. The stator is for the first time designed with a 45° angle that deviates the air gap closing forces into the vertical direction reducing the axial forces. The reduced axial forces improve the structural stability and consequently simplify their structural design. The novel methodology was then validated through an existing design of the HTS axial flux machine achieving a ∼10% mass reduction from 126 tonnes down to 115 tonnes. In addition, the air gap flux density increases due to the new claw pole shapes improving its power density from 53.19 to 61.90 W kg‑1. It is expected that the HTS axial flux machines designed with the new methodology offer a competitive advantage over other proposed superconducting generator designs in terms of cost, reliability and power density.

Representing high-dimensional data to intelligent prostheses and other wearable assistive robots: A first comparison of tile coding and selective Kanerva coding.

PubMed

Travnik, Jaden B; Pilarski, Patrick M

2017-07-01

Prosthetic devices have advanced in their capabilities and in the number and type of sensors included in their design. As the space of sensorimotor data available to a conventional or machine learning prosthetic control system increases in dimensionality and complexity, it becomes increasingly important that this data be represented in a useful and computationally efficient way. Well structured sensory data allows prosthetic control systems to make informed, appropriate control decisions. In this study, we explore the impact that increased sensorimotor information has on current machine learning prosthetic control approaches. Specifically, we examine the effect that high-dimensional sensory data has on the computation time and prediction performance of a true-online temporal-difference learning prediction method as embedded within a resource-limited upper-limb prosthesis control system. We present results comparing tile coding, the dominant linear representation for real-time prosthetic machine learning, with a newly proposed modification to Kanerva coding that we call selective Kanerva coding. In addition to showing promising results for selective Kanerva coding, our results confirm potential limitations to tile coding as the number of sensory input dimensions increases. To our knowledge, this study is the first to explicitly examine representations for realtime machine learning prosthetic devices in general terms. This work therefore provides an important step towards forming an efficient prosthesis-eye view of the world, wherein prompt and accurate representations of high-dimensional data may be provided to machine learning control systems within artificial limbs and other assistive rehabilitation technologies.

The NASA Lewis large wind turbine program

NASA Technical Reports Server (NTRS)

Thomas, R. L.; Baldwin, D. H.

1981-01-01

The program is directed toward development of the technology for safe, reliable, environmentally acceptable large wind turbines that have the potential to generate a significant amount of electricity at costs competitive with conventional electric generation systems. In addition, these large wind turbines must be fully compatible with electric utility operations and interface requirements. Advances are made by gaining a better understanding of the system design drivers, improvements in the analytical design tools, verification of design methods with operating field data, and the incorporation of new technology and innovative designs. An overview of the program activities is presented and includes results from the first and second generation field machines (Mod-OA, -1, and -2), the design phase of the third generation wind turbine (Mod-5) and the advanced technology projects. Also included is the status of the Department of Interior WTS-4 machine.

Quantum optimization for training support vector machines.

PubMed

Anguita, Davide; Ridella, Sandro; Rivieccio, Fabio; Zunino, Rodolfo

2003-01-01

Refined concepts, such as Rademacher estimates of model complexity and nonlinear criteria for weighting empirical classification errors, represent recent and promising approaches to characterize the generalization ability of Support Vector Machines (SVMs). The advantages of those techniques lie in both improving the SVM representation ability and yielding tighter generalization bounds. On the other hand, they often make Quadratic-Programming algorithms no longer applicable, and SVM training cannot benefit from efficient, specialized optimization techniques. The paper considers the application of Quantum Computing to solve the problem of effective SVM training, especially in the case of digital implementations. The presented research compares the behavioral aspects of conventional and enhanced SVMs; experiments in both a synthetic and real-world problems support the theoretical analysis. At the same time, the related differences between Quadratic-Programming and Quantum-based optimization techniques are considered.

Experiments on a non-smoothly-forced oscillator

NASA Astrophysics Data System (ADS)

Virgin, Lawrence N.; George, Christopher; Kini, Ashwath

2015-12-01

This paper describes some typical behavior encountered in the response of a harmonically-excited mechanical system in which a severe nonlinearity occurs due to an impact. Although such systems have received considerable recent attention (most of it from a theoretical viewpoint), the system scrutinized in this paper also involves a discrete input of energy at the impact condition. That is, it is kicked when contact is made. One of the motivations for this work is related to a classic pinball machine in which a ball striking a bumper experiences a sudden impulse, introducing additional unpredictability to the motion of the ball. A one-dimensional analog of a pinball machine was the subject of a detailed mathematical study in Pring and Budd (2011), and the current paper details behavior obtained from a mechanical experiment and describes dynamics not observed in a conventional (passive) impact oscillator.

Directly spheroidizing during hot deformation in GCr15 steels

NASA Astrophysics Data System (ADS)

Zhu, Guo-hui; Zheng, Gang

2008-03-01

The spheroidizing heat treatment is normally required prior to the cold forming in GCr15 steel in order to improve its machinability. In the conventional spheroidizing process, very long annealing time, generally more than 10 h, is needed to assure proper spheroidizing. It results in low productivity, high cost, and especially high energy consumption. Therefore, the possibility of directly spheroidizing during hot deformation in GCr15 steel is preliminarily explored. The effect of hot deformation parameters on the final microstructure and hardness is investigated systematically in order to develop a directly spheroidizing technology. Experimental results illustrate that low deformation temperature and slow cooling rate is the favorite in directly softening and/or spheroidizing during hot deformation, which allows the properties of asrolled GCr15 to be applicable for post-machining without requirement of prior annealing.

A novel cause of rebreathing carbon dioxide related to removed CLIC-seal on the Dräger Apollo© anesthesia machine.

PubMed

Niknam, B; Bebic, Z; Roseman, A

2018-05-26

We present a case report involving two sequential, surgically uneventful, laparoscopic cholecystectomies using the same anesthesia machine (Drager Apollo©) for which the level of inspired carbon dioxide was noted to be elevated following various diagnostic interventions including replacing the sodalime, increasing fresh gas flows, and a full inspection of equipment for malfunction. Eventually it was discovered that a rubber ring seal connecting the Dragersorb CLIC system© to the sodalime canister was inadvertently removed during the initial canister exchange resulting in an apparent bypassing of the absorbent and thus an inability of the exhaled gas to contact the sodalime. To our knowledge this is the first such description of this potential cause of elevated inspired carbon dioxide and should warrant consideration when other conventional interventions have failed.

Optimization and Simulation of Plastic Injection Process using Genetic Algorithm and Moldflow

NASA Astrophysics Data System (ADS)

Martowibowo, Sigit Yoewono; Kaswadi, Agung

2017-03-01

The use of plastic-based products is continuously increasing. The increasing demands for thinner products, lower production costs, yet higher product quality has triggered an increase in the number of research projects on plastic molding processes. An important branch of such research is focused on mold cooling system. Conventional cooling systems are most widely used because they are easy to make by using conventional machining processes. However, the non-uniform cooling processes are considered as one of their weaknesses. Apart from the conventional systems, there are also conformal cooling systems that are designed for faster and more uniform plastic mold cooling. In this study, the conformal cooling system is applied for the production of bowl-shaped product made of PP AZ564. Optimization is conducted to initiate machine setup parameters, namely, the melting temperature, injection pressure, holding pressure and holding time. The genetic algorithm method and Moldflow were used to optimize the injection process parameters at a minimum cycle time. It is found that, an optimum injection molding processes could be obtained by setting the parameters to the following values: T M = 180 °C; P inj = 20 MPa; P hold = 16 MPa and t hold = 8 s, with a cycle time of 14.11 s. Experiments using the conformal cooling system yielded an average cycle time of 14.19 s. The studied conformal cooling system yielded a volumetric shrinkage of 5.61% and the wall shear stress was found at 0.17 MPa. The difference between the cycle time obtained through simulations and experiments using the conformal cooling system was insignificant (below 1%). Thus, combining process parameters optimization and simulations by using genetic algorithm method with Moldflow can be considered as valid.

Comparing the performance-enhancing effects of squats on a vibration platform with conventional squats in recreationally resistance-trained men.

PubMed

Rønnestad, Bent R

2004-11-01

The purpose of this investigation was to compare the performance-enhancing effects of squats on a vibration platform with conventional squats in recreationally resistance-trained men. The subjects were 14 recreationally resistance-trained men (age, 21-40 years) and the intervention period consisted of 5 weeks. After the initial testing, subjects were randomly assigned to either the "squat whole body vibration" (SWBV) group (n = 7), which performed squats on a vibration platform on a Smith Machine, or the "squat"(S) group (n = 7), which performed conventional squats with no vibrations on a Smith Machine. Testing was performed at the beginning and the end of the study and consisted of 1 repetition maximum (1RM) in squat and maximum jump height in countermovement jump (CMJ). A modified daily undulating periodization program was used during the intervention period in both groups. Both groups trained at the same percentage of 1RM in squats (6-10RM). After the intervention, CMJ performance increased significantly only in the SWBV (p < 0.01), but there was no significant difference between groups in relative jump height increase (p = 0.088). Both groups showed significant increases in 1RM performance in squats (p < 0.01). Although there was a trend toward a greater relative strength increase in the SWBV group, it did not reach a significant level. In conclusion, the preliminary results of this study point toward a tendency of superiority of squats performed on a vibration platform compared with squats without vibrations regarding maximal strength and explosive power as long as the external load is similar in recreationally resistance-trained men.

Extended glaze firing on ceramics for hard machining: Crack healing, residual stresses, optical and microstructural aspects.

PubMed

Aurélio, Iana L; Dorneles, Lucio S; May, Liliana G

2017-02-01

To evaluate the effect of extended and conventional (manufacturer-recommended) glaze firings on crack healing, residual stresses, optical characteristics and crystalline structure of four ceramics for hard machining. Rectangular specimens were obtained by sectioning densely sintered feldspathic (FEL), leucite- (LEU), lithium disilicate- (DIS), and zirconia-reinforced lithium silicate-based (ZLS) prefabricated ceramic blocks and divided into groups according to the applied glaze firing (n=5): conventional glaze/manufacturer-recommended (G), extended glaze (EG) and control/no heat treatment (C). Defects generated by indentation were analyzed by scanning electron microscopy before and after firing (n=1) to evaluate crack healing. Residual stresses were determined by the indentation technique. Color differences (ΔE) after firing were measured by CIEDE2000 formula, and translucency variations were quantified by contrast ratio. Stability of crystalline microstructure was analyzed by X-ray diffraction. Regardless of the material, EG had greater ability than G to heal defects, and produced compressive residual stresses, while G generated tensile stresses. Color differences produced by EG were: imperceptible for FEL and LEU ceramics; perceptible, but still clinically acceptable for DIS; clinically unacceptable for ZLS. G produced no perceptible color change. The DIS and ZLS ceramics became ≈1% more opaque after G, ≈4% and ≈15%, respectively, after EG. The crystalline phase of all the ceramics remained stable after G and EG. Extended glaze firing could be an alternative to finish feldspathic, leucite-, and lithium disilicate-based ceramic restorations, since it provides greater crack healing than the conventional glaze firing. It develops tolerable residual stresses, and produces clinically acceptable color alterations, without altering the microstructure of these materials. Copyright © 2016 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Accuracy of Small Base Metal Dental Castings,

DTIC Science & Technology

1980-07-10

onre r puf~ eece an dif bydo:k itse Base metal al oy, c s ii.ing c ucyicatin nesmncatn ecnqe an.DISRBTOTTMN in( sten te hiquestatetrdISoc20itifrntrmRpr...34alternatives" to conventional dental golds. Determination and evaluation of composition , structure, physical and chemical properties, biologic features...maxillary right first molar was made from an industrial grade silicone . Then the tooth was machined to receive a full crown cast restoration. The tapered

Lathe Attachment Finishes Inner Surface of Tubes

NASA Technical Reports Server (NTRS)

Lancki, A. J.

1982-01-01

Extremely smooth finishes are machined on inside surfaces of tubes by new attachment for a lathe. The relatively inexpensive accessory, called a "microhone," holds a honing stone against workpiece by rigid tangs instead of springs as in conventional honing tools. Inner rod permits adjustment of microhoning stone, while outer tube supports assembly. Outer tube is held between split blocks on lathe toolpost. Microhoning can be done with either microhone or workpiece moving and other member stationary.

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

Göring, Gerald; Dietrich, Philipp-Immanuel; Blaicher, Matthias

3D direct laser writing based on two-photon polymerization is considered as a tool to fabricate tailored probes for atomic force microscopy. Tips with radii of 25 nm and arbitrary shape are attached to conventionally shaped micro-machined cantilevers. Long-term scanning measurements reveal low wear rates and demonstrate the reliability of such tips. Furthermore, we show that the resonance spectrum of the probe can be tuned for multi-frequency applications by adding rebar structures to the cantilever.

Method for machining holes in composite materials

NASA Technical Reports Server (NTRS)

Daniels, Julia G. (Inventor); Ledbetter, Frank E., III (Inventor); Clemons, Johnny M. (Inventor); Penn, Benjamin G. (Inventor); White, William T. (Inventor)

1987-01-01

A method for boring well defined holes in a composite material such as graphite/epoxy is discussed. A slurry of silicon carbide powder and water is projected onto a work area of the composite material in which a hole is to be bored with a conventional drill bit. The silicon carbide powder and water slurry allow the drill bit, while experiencing only normal wear, to bore smooth, cylindrical holes in the composite material.

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

Not Available

This paper is actually a composite of two papers dealing with automation and computerized control of underground mining equipment. The paper primarily discusses drills, haulage equipment, and tunneling machines. It compares performance and cost benefits of conventional equipment to the new automated methods. The company involved are iron ore mining companies in Scandinavia. The papers also discusses the different equipment using air power, water power, hydraulic power, and computer power. The different drill rigs are compared for performance and cost.

Serving Real-Time Point Observation Data in netCDF using Climate and Forecasting Discrete Sampling Geometry Conventions

NASA Astrophysics Data System (ADS)

Ward-Garrison, C.; May, R.; Davis, E.; Arms, S. C.

2016-12-01

NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The Climate and Forecasting (CF) metadata conventions for netCDF foster the ability to work with netCDF files in general and useful ways. These conventions include metadata attributes for physical units, standard names, and spatial coordinate systems. While these conventions have been successful in easing the use of working with netCDF-formatted output from climate and forecast models, their use for point-based observation data has been less so. Unidata has prototyped using the discrete sampling geometry (DSG) CF conventions to serve, using the THREDDS Data Server, the real-time point observation data flowing across the Internet Data Distribution (IDD). These data originate in text format reports for individual stations (e.g. METAR surface data or TEMP upper air data) and are converted and stored in netCDF files in real-time. This work discusses the experiences and challenges of using the current CF DSG conventions for storing such real-time data. We also test how parts of netCDF's extended data model can address these challenges, in order to inform decisions for a future version of CF (CF 2.0) that would take advantage of features of the netCDF enhanced data model.

Machine learning-based in-line holographic sensing of unstained malaria-infected red blood cells.

PubMed

Go, Taesik; Kim, Jun H; Byeon, Hyeokjun; Lee, Sang J

2018-04-19

Accurate and immediate diagnosis of malaria is important for medication of the infectious disease. Conventional methods for diagnosing malaria are time consuming and rely on the skill of experts. Therefore, an automatic and simple diagnostic modality is essential for healthcare in developing countries that lack the expertise of trained microscopists. In the present study, a new automatic sensing method using digital in-line holographic microscopy (DIHM) combined with machine learning algorithms was proposed to sensitively detect unstained malaria-infected red blood cells (iRBCs). To identify the RBC characteristics, 13 descriptors were extracted from segmented holograms of individual RBCs. Among the 13 descriptors, 10 features were highly statistically different between healthy RBCs (hRBCs) and iRBCs. Six machine learning algorithms were applied to effectively combine the dominant features and to greatly improve the diagnostic capacity of the present method. Among the classification models trained by the 6 tested algorithms, the model trained by the support vector machine (SVM) showed the best accuracy in separating hRBCs and iRBCs for training (n = 280, 96.78%) and testing sets (n = 120, 97.50%). This DIHM-based artificial intelligence methodology is simple and does not require blood staining. Thus, it will be beneficial and valuable in the diagnosis of malaria. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and Evaluation of a Wide-Bed Former for Vegetable Cultivation in Controlled Tractor Traffic

NASA Astrophysics Data System (ADS)

Dixit, Anoop; Khurana, Rohinish; Verma, Aseem; Singh, Arshdeep; Manes, G. S.

2018-05-01

India is the second largest producer of vegetables in the world. For vegetable cultivation, a good seed bed preparation is an important task which involves 6-10 different operations. To tackle the issue of multiple operations, a prototype of tractor operated wide bed former was developed and evaluated. The machine comprises of a rotary tiller and a bed forming setup. It forms bed of 1000 mm top width which is suitable as per the track width of an average sized tractor in India. The height of the beds formed is 130 mm whereas the top and bottom width of channel formed on both sides of the bed is 330 and 40 mm respectively at soil moisture content of 12.5-16% (db). The forward speed of 2.75 km/h was observed to be suitable for proper bed formation. The average fuel consumption of the machine was 5.9 l/h. The average bulk density of soil before and after the bed formation was 1.46 and 1.63 g/cc respectively. Field capacity of the machine was found to be 0.31 ha/h. The machine resulted in 93.8% labour saving and 80.4% saving in cost of bed preparation as compared to conventional farmer practice. Overall performance of wide-bed former was found to be satisfactory.

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

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

Hu, Wenjian; Singh, Rajiv R. P.; Scalettar, Richard T.

Here, we apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models - the square and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-one Ising (BSI) model, and the 2D XY model, and examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow exploration of different phases and symmetry-breaking, but can distinguish phase transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which ismore » particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the 'charge' correlations (vorticity) in the BSI model (XY model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the 'antoencoder method', and demonstrate that it too can be trained to capture phase transitions and critical points.« less

Development of large, horizontal-axis wind turbines

NASA Technical Reports Server (NTRS)

Baldwin, D. H.; Kennard, J.

1985-01-01

A program to develop large, horizontal-axis wind turbines is discussed. The program is directed toward developing the technology for safe, reliable, environmentally acceptable large wind turbines that can generate a significant amount of electricity at costs competitive with those of conventional electricity-generating systems. In addition, these large wind turbines must be fully compatible with electric utility operations and interface requirements. Several ongoing projects in large-wind-turbine development are directed toward meeting the technology requirements for utility applications. The machines based on first-generation technology (Mod-OA and Mod-1) successfully completed their planned periods of experimental operation in June, 1982. The second-generation machines (Mod-2) are in operation at selected utility sites. A third-generation machine (Mod-5) is under contract. Erection and initial operation of the Mod-5 in Hawaii should take place in 1986. Each successive generation of technology increased reliability and energy capture while reducing the cost of electricity. These advances are being made by gaining a better understanding of the system-design drivers, improving the analytical design tools, verifying design methods with operating field data, and incorporating new technology and innovative designs. Information is given on the results from the first- and second-generation machines (Mod-OA, - 1, and -2), the status of the Department of Interior, and the status of the third-generation wind turbine (Mod-5).

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

DOE PAGES

Hu, Wenjian; Singh, Rajiv R. P.; Scalettar, Richard T.

2017-06-19

Here, we apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models - the square and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-one Ising (BSI) model, and the 2D XY model, and examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow exploration of different phases and symmetry-breaking, but can distinguish phase transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which ismore » particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the 'charge' correlations (vorticity) in the BSI model (XY model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the 'antoencoder method', and demonstrate that it too can be trained to capture phase transitions and critical points.« less

Study of PVD AlCrN Coating for Reducing Carbide Cutting Tool Deterioration in the Machining of Titanium Alloys.

PubMed

Cadena, Natalia L; Cue-Sampedro, Rodrigo; Siller, Héctor R; Arizmendi-Morquecho, Ana M; Rivera-Solorio, Carlos I; Di-Nardo, Santiago

2013-05-24

The manufacture of medical and aerospace components made of titanium alloys and other difficult-to-cut materials requires the parallel development of high performance cutting tools coated with materials capable of enhanced tribological and resistance properties. In this matter, a thin nanocomposite film made out of AlCrN (aluminum-chromium-nitride) was studied in this research, showing experimental work in the deposition process and its characterization. A heat-treated monolayer coating, competitive with other coatings in the machining of titanium alloys, was analyzed. Different analysis and characterizations were performed on the manufactured coating by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDXS), and X-ray diffraction (XRD). Furthermore, the mechanical behavior of the coating was evaluated through hardness test and tribology with pin-on-disk to quantify friction coefficient and wear rate. Finally, machinability tests using coated tungsten carbide cutting tools were executed in order to determine its performance through wear resistance, which is a key issue of cutting tools in high-end cutting at elevated temperatures. It was demonstrated that the specimen (with lower friction coefficient than previous research) is more efficient in machinability tests in Ti6Al4V alloys. Furthermore, the heat-treated monolayer coating presented better performance in comparison with a conventional monolayer of AlCrN coating.

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

NASA Astrophysics Data System (ADS)

Hu, Wenjian; Singh, Rajiv R. P.; Scalettar, Richard T.

2017-06-01

We apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models—the square- and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-1 Ising (BSI) model, and the two-dimensional X Y model—and we examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow the exploration of different phases and symmetry-breaking, but they can distinguish phase-transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which is particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the "charge" correlations (vorticity) in the BSI model (X Y model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the "autoencoder method," and we demonstrate that it too can be trained to capture phase transitions and critical points.

Study of PVD AlCrN Coating for Reducing Carbide Cutting Tool Deterioration in the Machining of Titanium Alloys

PubMed Central

Cadena, Natalia L.; Cue-Sampedro, Rodrigo; Siller, Héctor R.; Arizmendi-Morquecho, Ana M.; Rivera-Solorio, Carlos I.; Di-Nardo, Santiago

2013-01-01

The manufacture of medical and aerospace components made of titanium alloys and other difficult-to-cut materials requires the parallel development of high performance cutting tools coated with materials capable of enhanced tribological and resistance properties. In this matter, a thin nanocomposite film made out of AlCrN (aluminum–chromium–nitride) was studied in this research, showing experimental work in the deposition process and its characterization. A heat-treated monolayer coating, competitive with other coatings in the machining of titanium alloys, was analyzed. Different analysis and characterizations were performed on the manufactured coating by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDXS), and X-ray diffraction (XRD). Furthermore, the mechanical behavior of the coating was evaluated through hardness test and tribology with pin-on-disk to quantify friction coefficient and wear rate. Finally, machinability tests using coated tungsten carbide cutting tools were executed in order to determine its performance through wear resistance, which is a key issue of cutting tools in high-end cutting at elevated temperatures. It was demonstrated that the specimen (with lower friction coefficient than previous research) is more efficient in machinability tests in Ti6Al4V alloys. Furthermore, the heat-treated monolayer coating presented better performance in comparison with a conventional monolayer of AlCrN coating. PMID:28809266

Bellco Formula Domus Home Care System.

PubMed

Trewin, Elizabeth

2004-01-01

There are certain characteristics in a dialysis machine that would be desirable for use in home and limited care environments. These features relate to safety, ease of use, consideration of physical space, and reliability. The Bellco Formula Domus Home Care System was designed to meet all these requirements. Bellco's philosophy of patient treatment centers on global biocompatibility. This is evident in the design of the Formula Domus Home Care System. It has the smallest hydraulic fluid pathway of any dialysis machine on the market. Formula is capable of preparing ultrapure dialysate. The ultrafiltration measurement mechanism, the patented Coriolis flow meter, measures the mass of the dialysate, not the volume. For this reason it is the only dialysis machine that detects actual backfiltration, not just the theoretical possibility of it based on transmembrane pressure. The Coriolis flow meter also ensures that dialysate flow is a true single pass. The operator interface is a single window operating control. It is possible to select up to 14 different languages. There is an online help key to assist patients with troubleshooting. Programmable start-up and shutdown times save time for the patient. Formula is the only dialysis machine to offer a backup battery feature. Formula is capable of communicating with any software available. The focus on global biocompatibility ensures the best quality dialysis treatments for a population of patients who will likely remain on dialysis for a longer period of time than conventional dialysis patients.

Modern laser technologies used for cutting textile materials

NASA Astrophysics Data System (ADS)

Isarie, Claudiu; Dragan, Anca; Isarie, Laura; Nastase, Dan

2006-02-01

With modern laser technologies we can cut multiple layers at once, yielding high production levels and short setup times between cutting runs. One example could be the operation of cutting the material named Nylon 66, used to manufacture automobile airbags. With laser, up to seven layers of Nylon 66 can be cut in one pass, that means high production rates on a single machine. Airbags must be precisely crafted piece of critical safety equipment that is built to very high levels of precision in a mass production environment. Of course, synthetic material, used for airbags, can be cut also by a conventional fixed blade system, but for a high production rates and a long term low-maintenance, laser cutting is most suitable. Most systems, are equipped with two material handling systems, which can cut on one half of he table while the finished product is being removed from the other half and the new stock material laid out. The laser system is reliable and adaptable to any flatbed-cutting task. Computer controlled industrial cutting and plotting machines are the latest offerings from a well established and experienced industrial engineering company that is dedicated to reduce cutting costs and boosting productivity in today's competitive industrial machine tool market. In this way, just one machine can carry out a multitude of production tasks. Authors have studied the cutting parameters for different textile materials, to reach the maximum output of the process.

Evaluation of the force generated by gradual deflection of orthodontic wires in conventional metallic, esthetic, and self-ligating brackets.

PubMed

Francisconi, Manoela Fávaro; Janson, Guilherme; Henriques, José Fernando Castanha; Freitas, Karina Maria Salvatore de

2016-01-01

The purpose of this study was to evaluate the deflection forces of Nitinol orthodontic wires placed in different types of brackets: metallic, reinforced polycarbonate with metallic slots, sapphire, passive and active self-ligating, by assessing strength values variation according to gradual increase in wire diameter and deflection and comparing different combinations in the different deflections. Specimens were set in a clinical simulation model and evaluated in a Universal Testing Machine (INSTRON 3342), using the ISO 15841 protocol. Data were subjected to One-way ANOVA, followed by Tukey tests (p<0.05). Self-ligating brackets presented the most similar behavior to each other. For conventional brackets there was no consistent behavior for any of the deflections studied. Self-ligating brackets presented the most consistent and predictable results while conventional brackets, as esthetic brackets, showed very different patterns of forces. Self-ligating brackets showed higher strength in all deflections when compared with the others, in 0.020-inch wires.

Dynamic remedial action scheme using online transient stability analysis

NASA Astrophysics Data System (ADS)

Shrestha, Arun

Economic pressure and environmental factors have forced the modern power systems to operate closer to their stability limits. However, maintaining transient stability is a fundamental requirement for the operation of interconnected power systems. In North America, power systems are planned and operated to withstand the loss of any single or multiple elements without violating North American Electric Reliability Corporation (NERC) system performance criteria. For a contingency resulting in the loss of multiple elements (Category C), emergency transient stability controls may be necessary to stabilize the power system. Emergency control is designed to sense abnormal conditions and subsequently take pre-determined remedial actions to prevent instability. Commonly known as either Remedial Action Schemes (RAS) or as Special/System Protection Schemes (SPS), these emergency control approaches have been extensively adopted by utilities. RAS are designed to address specific problems, e.g. to increase power transfer, to provide reactive support, to address generator instability, to limit thermal overloads, etc. Possible remedial actions include generator tripping, load shedding, capacitor and reactor switching, static VAR control, etc. Among various RAS types, generation shedding is the most effective and widely used emergency control means for maintaining system stability. In this dissertation, an optimal power flow (OPF)-based generation-shedding RAS is proposed. This scheme uses online transient stability calculation and generator cost function to determine appropriate remedial actions. For transient stability calculation, SIngle Machine Equivalent (SIME) technique is used, which reduces the multimachine power system model to a One-Machine Infinite Bus (OMIB) equivalent and identifies critical machines. Unlike conventional RAS, which are designed using offline simulations, online stability calculations make the proposed RAS dynamic and adapting to any power system configuration and operating state. The generation-shedding cost is calculated using pre-RAS and post-RAS OPF costs. The criteria for selecting generators to trip is based on the minimum cost rather than minimum amount of generation to shed. For an unstable Category C contingency, the RAS control action that results in stable system with minimum generation shedding cost is selected among possible candidate solutions. The RAS control actions update whenever there is a change in operating condition, system configuration, or cost functions. The effectiveness of the proposed technique is demonstrated by simulations on the IEEE 9-bus system, the IEEE 39-bus system, and IEEE 145-bus system. This dissertation also proposes an improved, yet relatively simple, technique for solving Transient Stability-Constrained Optimal Power Flow (TSC-OPF) problem. Using the SIME method, the sets of dynamic and transient stability constraints are reduced to a single stability constraint, decreasing the overall size of the optimization problem. The transient stability constraint is formulated using the critical machines' power at the initial time step, rather than using the machine rotor angles. This avoids the addition of machine steady state stator algebraic equations in the conventional OPF algorithm. A systematic approach to reach an optimal solution is developed by exploring the quasi-linear behavior of critical machine power and stability margin. The proposed method shifts critical machines active power based on generator costs using an OPF algorithm. Moreover, the transient stability limit is based on stability margin, and not on a heuristically set limit on OMIB rotor angle. As a result, the proposed TSC-OPF solution is more economical and transparent. The proposed technique enables the use of fast and robust commercial OPF tool and time-domain simulation software for solving large scale TSC-OPF problem, which makes the proposed method also suitable for real-time application.

The ultrasonic machining of silicon carbide / alumina composites

NASA Astrophysics Data System (ADS)

Nicholson, Garth Martyn John

Silicon carbide fibre reinforced alumina is a ceramic composite which was developed in conjunction with the Rolls-Royce Aerospace Group. The material is intended for use in the latest generation of jet engines, specifically for high temperature applications such as flame holders, combustor barrel segments and turbine blade tip seals. The material in question has properties which have been engineered by optimizing fibre volume fractions, weaves and fibre interface materials to meet the following main requirements : high thermal resistance, high thermal shock resistance and low density.Components intended for manufacture using this material will use the "direct metal oxidation" (DIMOX) method. This process involves manufacturing a near net shape component from the woven fibre matting, and infiltrating the matting with the alumina matrix material. Some of the components outlined require high tolerance features to be included in their design. The combustor barrel segments for example require slots to be formed within them for sealing purposes, the dimensions of these features preclude their formation using DIMOX, and therefore require a secondary process to be performed. Conventional machining techniques such as drilling, turning and milling cannot be used because of the brittle nature of the material. Electrodischarge machining (E.D.M.) cannot be used since the material is an insulator. Electrochemical machining (E.C.M.) cannot be used since the material is chemically inert. One machining method which could be used is ultrasonic machining (U.S.M.).The research programme investigated the feasibility of using ultrasonic machining as a manufacturing method for this new fibre reinforced composite. Two variations of ultrasonic machining were used : ultrasonic drilling and ultrasonic milling. Factors such as dimensional accuracy, surface roughness and delamination effects were examined. Previously performed ultrasonic machining experimental programmes were reviewed, as well as process models which have been developed. The process models were found to contain empirical constants which usually require specific material data for their calculation.Since a limited amount of the composite was available, and ultrasonic machining has many process variables, a Taguchi factorial experiment was conducted in order to ascertain the most relevant factors in machining. A full factorial experiment was then performed using the relevant factors. Techniques used in the research included both optical and scanning electron microscopy, surface roughness analysis, x-ray analysis and finite element stress analysis. A full set of machining data was obtained including relationships between the factors examined and both material removal rates, and surface roughness values. An attempt was made to explain these findings by examining established brittle fracture mechanisms. These established mechanisms did not seem to apply entirely to this material, an alternative method of material removal is therefore proposed. It is hoped that the data obtained from this research programme may contribute to the development of a more realistic mathematical model.

Some Alignment Considerations for the Next Linear Collider

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

Ruland, R

Next Linear Collider type accelerators require a new level of alignment quality. The relative alignment of these machines is to be maintained in an error envelope dimensioned in micrometers and for certain parts in nanometers. In the nanometer domain our terra firma cannot be considered monolithic but compares closer to jelly. Since conventional optical alignment methods cannot deal with the dynamics and cannot approach the level of accuracy, special alignment and monitoring techniques must be pursued.

Diamond fly cutting of aluminum thermal infrared flat mirrors for the OSIRIS-REx Thermal Emission Spectrometer (OTES) instrument

NASA Astrophysics Data System (ADS)

Groppi, Christopher E.; Underhill, Matthew; Farkas, Zoltan; Pelham, Daniel

2016-07-01

We present the fabrication and measurement of monolithic aluminum flat mirrors designed to operate in the thermal infrared for the OSIRIS-Rex Thermal Emission Spectrometer (OTES) space instrument. The mirrors were cut using a conventional fly cutter with a large radius diamond cutting tool on a high precision Kern Evo 3-axis CNC milling machine. The mirrors were measured to have less than 150 angstroms RMS surface error.

Landmark navigation and autonomous landing approach with obstacle detection for aircraft

NASA Astrophysics Data System (ADS)

Fuerst, Simon; Werner, Stefan; Dickmanns, Dirk; Dickmanns, Ernst D.

1997-06-01

A machine perception system for aircraft and helicopters using multiple sensor data for state estimation is presented. By combining conventional aircraft sensor like gyros, accelerometers, artificial horizon, aerodynamic measuring devices and GPS with vision data taken by conventional CCD-cameras mounted on a pan and tilt platform, the position of the craft can be determined as well as the relative position to runways and natural landmarks. The vision data of natural landmarks are used to improve position estimates during autonomous missions. A built-in landmark management module decides which landmark should be focused on by the vision system, depending on the distance to the landmark and the aspect conditions. More complex landmarks like runways are modeled with different levels of detail that are activated dependent on range. A supervisor process compares vision data and GPS data to detect mistracking of the vision system e.g. due to poor visibility and tries to reinitialize the vision system or to set focus on another landmark available. During landing approach obstacles like trucks and airplanes can be detected on the runway. The system has been tested in real-time within a hardware-in-the-loop simulation. Simulated aircraft measurements corrupted by noise and other characteristic sensor errors have been fed into the machine perception system; the image processing module for relative state estimation was driven by computer generated imagery. Results from real-time simulation runs are given.

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

A novel automated device for rapid nucleic acid extraction utilizing a zigzag motion of magnetic silica beads.

PubMed

Yamaguchi, Akemi; Matsuda, Kazuyuki; Uehara, Masayuki; Honda, Takayuki; Saito, Yasunori

2016-02-04

We report a novel automated device for nucleic acid extraction, which consists of a mechanical control system and a disposable cassette. The cassette is composed of a bottle, a capillary tube, and a chamber. After sample injection in the bottle, the sample is lysed, and nucleic acids are adsorbed on the surface of magnetic silica beads. These magnetic beads are transported and are vibrated through the washing reagents in the capillary tube under the control of the mechanical control system, and thus, the nucleic acid is purified without centrifugation. The purified nucleic acid is automatically extracted in 3 min for the polymerase chain reaction (PCR). The nucleic acid extraction is dependent on the transport speed and the vibration frequency of the magnetic beads, and optimizing these two parameters provided better PCR efficiency than the conventional manual procedure. There was no difference between the detection limits of our novel device and that of the conventional manual procedure. We have already developed the droplet-PCR machine, which can amplify and detect specific nucleic acids rapidly and automatically. Connecting the droplet-PCR machine to our novel automated extraction device enables PCR analysis within 15 min, and this system can be made available as a point-of-care testing in clinics as well as general hospitals. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison study on disturbance estimation techniques in precise slow motion control

NASA Astrophysics Data System (ADS)

Fan, S.; Nagamune, R.; Altintas, Y.; Fan, D.; Zhang, Z.

2010-08-01

Precise low speed motion control is important for the industrial applications of both micro-milling machine tool feed drives and electro-optical tracking servo systems. It calls for precise position and instantaneous velocity measurement and disturbance, which involves direct drive motor force ripple, guide way friction and cutting force etc., estimation. This paper presents a comparison study on dynamic response and noise rejection performance of three existing disturbance estimation techniques, including the time-delayed estimators, the state augmented Kalman Filters and the conventional disturbance observers. The design technique essentials of these three disturbance estimators are introduced. For designing time-delayed estimators, it is proposed to substitute Kalman Filter for Luenberger state observer to improve noise suppression performance. The results show that the noise rejection performances of the state augmented Kalman Filters and the time-delayed estimators are much better than the conventional disturbance observers. These two estimators can give not only the estimation of the disturbance but also the low noise level estimations of position and instantaneous velocity. The bandwidth of the state augmented Kalman Filters is wider than the time-delayed estimators. In addition, the state augmented Kalman Filters can give unbiased estimations of the slow varying disturbance and the instantaneous velocity, while the time-delayed estimators can not. The simulation and experiment conducted on X axis of a 2.5-axis prototype micro milling machine are provided.

Crack identification for rigid pavements using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bahaddin Ersoz, Ahmet; Pekcan, Onur; Teke, Turker

2017-09-01

Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation of existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based pavement monitoring systems have been in-use in assessing the remaining life of in-service pavements. Although such systems produce accurate results, their use can be expensive and data processing can be time consuming, which make them infeasible considering the demand for quick pavement evaluation. To overcome such problems, Unmanned Aerial Vehicles (UAVs) can be used as an alternative as they are relatively cheaper and easier-to-use. In this study, we propose a UAV based pavement crack identification system for monitoring rigid pavements’ existing conditions. The system consists of recently introduced image processing algorithms used together with conventional machine learning techniques, both of which are used to perform detection of cracks on rigid pavements’ surface and their classification. Through image processing, the distinct features of labelled crack bodies are first obtained from the UAV based images and then used for training of a Support Vector Machine (SVM) model. The performance of the developed SVM model was assessed with a field study performed along a rigid pavement exposed to low traffic and serious temperature changes. Available cracks were classified using the UAV based system and obtained results indicate it ensures a good alternative solution for pavement monitoring applications.

Tool for Two Types of Friction Stir Welding

NASA Technical Reports Server (NTRS)

Carter, Robert

2006-01-01

A tool that would be useable in both conventional and self-reacting friction stir welding (FSW) has been proposed. The tool would embody both a prior tooling concept for self-reacting FSW and an auto-adjustable pin-tool (APT) capability developed previously as an augmentation for conventional FSW. Some definitions of terms are prerequisite to a meaningful description of the proposed tool. In conventional FSW, depicted in Figure 1, one uses a tool that includes (1) a rotating shoulder on top (or front) of the workpiece and (2) a rotating pin that protrudes from the shoulder into the depth of the workpiece. The main axial force exerted by the tool on the workpiece is reacted through a ridged backing anvil under (behind) the workpiece. When conventional FSW is augmented with an APT capability, the depth of penetration of the pin into the workpiece is varied in real time by a position- or force-control system that extends or retracts the pin as needed to obtain the desired effect. In self-reacting (also known as self-reacted) friction stir welding (SR-FSW), there are two rotating shoulders: one on top (or front) and one on the bottom (or back) of the workpiece. In this case, a threaded shaft protrudes from the tip of the pin to beyond the back surface of the workpiece. The back shoulder is held axially in place against tension by a nut on the threaded shaft. The main axial force exerted on the workpiece by the tool and front shoulder is reacted through the back shoulder and the threaded shaft, back into the FSW machine head, so that a backing anvil is no longer needed. A key transmits torque between the bottom shoulder and the threaded shaft, so that the bottom shoulder rotates with the shaft. A tool for SRFSW embodying this concept was reported in "Mechanism for Self-Reacted Friction Stir Welding" (MFS-31914), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 53. In its outward appearance, the proposed tool (see Figure 2) would fit the above description of an SR-FSW tool. In this case, the FSW machine would have an APT capability and the pin would be modified to accept a bottom shoulder. The APT capability could be used to vary the distance between the front and back shoulders in real time to accommodate process and workpiece-thickness variations. The tool could readily be converted to a conventional FSW tool, with or without APT capability, by simply replacing the modified pin with a conventional FSW pin.

An investigation of the effects of measurement noise in the use of instantaneous angular speed for machine diagnosis

NASA Astrophysics Data System (ADS)

Gu, Fengshou; Yesilyurt, Isa; Li, Yuhua; Harris, Georgina; Ball, Andrew

2006-08-01

In order to discriminate small changes for early fault diagnosis of rotating machines, condition monitoring demands that the measurement of instantaneous angular speed (IAS) of the machines be as accurate as possible. This paper develops the theoretical basis and practical implementation of IAS data acquisition and IAS estimation when noise influence is included. IAS data is modelled as a frequency modulated signal of which the signal-to-noise ratio can be improved by using a high-resolution encoder. From this signal model and analysis, optimal configurations for IAS data collection are addressed for high accuracy IAS measurement. Simultaneously, a method based on analytic signal concept and fast Fourier transform is also developed for efficient and accurate estimation of IAS. Finally, a fault diagnosis is carried out on an electric induction motor driving system using IAS measurement. The diagnosis results show that using a high-resolution encoder and a long data stream can achieve noise reduction by more than 10 dB in the frequency range of interest, validating the model and algorithm developed. Moreover, the results demonstrate that IAS measurement outperforms conventional vibration in diagnosis of incipient faults of motor rotor bar defects and shaft misalignment.

A GPS based fawn saving system using relative distance and angle determination

NASA Astrophysics Data System (ADS)

Ascher, A.; Eberhardt, M.; Lehner, M.; Biebl, E.

2016-09-01

Active UHF RFID systems are often used for identifying, tracking and locating objects. In the present publication a GPS- based localization system for saving fawns during pasture mowing was introduced and tested. Fawns were first found by a UAV before mowing began. They were then tagged with small active RFID transponders, and an appropriate reader was installed on a mowing machine. Conventional direction-of-arrival approaches require a large antenna array with multiple elements and a corresponding coherent receiver, which introduces a large degree of complexity on the reader-side. Instead, our transponders were equipped with a small GPS module, allowing a transponder to determine its own position on request from the reader. A UHF link was used to transmit the location to a machine- mounted reader, where a second GPS receiver was installed. Using information from this second position and a machine- mounted magnetometer for determining the relative north direction of a vehicle, relative distance, and angle between GPS receivers can be calculated. The accuracy and reliability of this novel method were tested under realistic operating conditions, considering critical factors such as the height of grass, the lying position of a fawn, humidity and geographical area.

Gas Wave Bearings: A Stable Alternative to Journal Bearings for High-Speed Oil-Free Machines

NASA Technical Reports Server (NTRS)

Dimofte, Florin

2005-01-01

To run both smoothly and efficiently, high-speed machines need stable, low-friction bearings to support their rotors. In addition, an oil-free bearing system is a common requirement in today's designs. Therefore, self-acting gas film bearings are becoming the bearing of choice in high-performance rotating machinery, including that used in the machine tool industry. Although plain journal bearings carry more load and have superior lift and land characteristics, they suffer from instability problems. Since 1992, a new type of fluid film bearing, the wave bearing, has been under development at the NASA Lewis Research Center in Cleveland, Ohio, by Dr. Florin Dimofte, a Senior Research Associate of the University of Toledo. One unique characteristic of the waved journal bearing that gives it improved capabilities over conventional journal bearings is the low-amplitude waves of its inner diameter surface. The radial clearance is on the order of one thousandth of the shaft radius, and the wave amplitude is nominally up to one-half the clearance. This bearing concept offers a load capacity which is very close to that of a plain journal bearing, but it runs more stably at nominal speeds.

Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.

Breast cancer risk assessment and diagnosis model using fuzzy support vector machine based expert system

NASA Astrophysics Data System (ADS)

Dheeba, J.; Jaya, T.; Singh, N. Albert

2017-09-01

Classification of cancerous masses is a challenging task in many computerised detection systems. Cancerous masses are difficult to detect because these masses are obscured and subtle in mammograms. This paper investigates an intelligent classifier - fuzzy support vector machine (FSVM) applied to classify the tissues containing masses on mammograms for breast cancer diagnosis. The algorithm utilises texture features extracted using Laws texture energy measures and a FSVM to classify the suspicious masses. The new FSVM treats every feature as both normal and abnormal samples, but with different membership. By this way, the new FSVM have more generalisation ability to classify the masses in mammograms. The classifier analysed 219 clinical mammograms collected from breast cancer screening laboratory. The tests made on the real clinical mammograms shows that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and Laws texture features, the area under the Receiver operating characteristic curve reached .95, which corresponds to a sensitivity of 93.27% with a specificity of 87.17%. The results suggest that detecting masses using FSVM contribute to computer-aided detection of breast cancer and as a decision support system for radiologists.

Geologic Carbon Sequestration Leakage Detection: A Physics-Guided Machine Learning Approach

NASA Astrophysics Data System (ADS)

Lin, Y.; Harp, D. R.; Chen, B.; Pawar, R.

2017-12-01

One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the large subsurface uncertainty and complex governing physics. Traditional leakage detection and monitoring techniques rely on geophysical observations including pressure. However, the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation, therefore yielding in-accurate estimates of leakage rates and locations. In this work, we develop a novel machine-learning technique based on support vector regression to effectively and efficiently predict the leakage locations and leakage rates based on limited number of pressure observations. Compared to the conventional data-driven approaches, which can be usually seem as a "black box" procedure, we develop a physics-guided machine learning method to incorporate the governing physics into the learning procedure. To validate the performance of our proposed leakage detection method, we employ our method to both 2D and 3D synthetic subsurface models. Our novel CO2 leakage detection method has shown high detection accuracy in the example problems.

Lightweight MgB2 superconducting 10 MW wind generator

NASA Astrophysics Data System (ADS)

Marino, I.; Pujana, A.; Sarmiento, G.; Sanz, S.; Merino, J. M.; Tropeano, M.; Sun, J.; Canosa, T.

2016-02-01

The offshore wind market demands a higher power rate and more reliable turbines in order to optimize capital and operational costs. The state-of-the-art shows that both geared and direct-drive conventional generators are difficult to scale up to 10 MW and beyond due to their huge size and weight. Superconducting direct-drive wind generators are considered a promising solution to achieve lighter weight machines. This work presents an innovative 10 MW 8.1 rpm direct-drive partial superconducting generator using MgB2 wire for the field coils. It has a warm iron rotor configuration with the superconducting coils working at 20 K while the rotor core and the armature are at ambient temperature. A cooling system based on cryocoolers installed in the rotor extracts the heat from the superconducting coils by conduction. The generator's main parameters are compared against a permanent magnet reference machine, showing a significant weight and size reduction. The 10 MW superconducting generator concept will be experimentally validated with a small-scale magnetic machine, which has innovative components such as superconducting coils, modular cryostats and cooling systems, and will have similar size and characteristics as the 10 MW generator.

Structural Mechanics and Dynamics Branch

NASA Technical Reports Server (NTRS)

Stefko, George

2003-01-01

The 2002 annual report of the Structural Mechanics and Dynamics Branch reflects the majority of the work performed by the branch staff during the 2002 calendar year. Its purpose is to give a brief review of the branch s technical accomplishments. The Structural Mechanics and Dynamics Branch develops innovative computational tools, benchmark experimental data, and solutions to long-term barrier problems in the areas of propulsion aeroelasticity, active and passive damping, engine vibration control, rotor dynamics, magnetic suspension, structural mechanics, probabilistics, smart structures, engine system dynamics, and engine containment. Furthermore, the branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more electric" aircraft. An ultra-high-power-density machine that can generate projected power densities of 50 hp/lb or more, in comparison to conventional electric machines, which generate usually 0.2 hp/lb, is under development for application to electric drives for propulsive fans or propellers. In the future, propulsion and power systems will need to be lighter, to operate at higher temperatures, and to be more reliable in order to achieve higher performance and economic viability. The Structural Mechanics and Dynamics Branch is working to achieve these complex, challenging goals.

Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches

PubMed Central

Memarian, Negar; Torre, Jared B.; Haltom, Kate E.; Stanton, Annette L.

2017-01-01

Abstract Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. PMID:28992270

Preparation of Mo-Re-C samples containing Mo7Re13C with the β-Mn-type structure by solid state reaction of planetary-ball-milled powder mixtures of Mo, Re and C, and their crystal structures and superconductivity

NASA Astrophysics Data System (ADS)

Oh-ishi, Katsuyoshi; Nagumo, Kenta; Tateishi, Kazuya; Takafumi, Ohnishi; Yoshikane, Kenta; Sugiyama, Machiko; Oka, Kengo; Kobayashi, Ryota

2017-01-01

Mo-Re-C compounds containing Mo7Re13C with the β-Mn structure were synthesized with high-melting-temperature metals Mo, Re, and C powders using a conventional solid state method with a planetary ball milling machine instead of the arc melting method. Use of the ball milling machine was necessary to obtain Mo7Re13C with the β-Mn structure using the solid state method. Almost single-phase Mo7Re13C with a trace of impurity were obtained using the synthesis method. By XRF and lattice parameter measurements on the samples, Fe element existed in the compound synthesized using the planetary ball milling machine with a pot and balls made of steel, though Fe element was not detected in the compound synthesized using a pot and balls made of tungsten carbide. The former compound containg the Fe atom did not show superconductivity but the latter compound without the Fe atom showed superconductivity at 6.1 K.

A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method.

PubMed

Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin

2016-03-04

Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications.