Monitored Retrievable Storage/Multi-Purpose Canister analysis: Simulation and economics of automation

International Nuclear Information System (INIS)

Bennett, P.C.; Stringer, J.B.

1994-01-01

Robotic automation is examined as a possible alternative to manual spent nuclear fuel, transport cask and Multi-Purpose canister (MPC) handling at a Monitored Retrievable Storage (MRS) facility. Automation of key operational aspects for the MRS/MPC system are analyzed to determine equipment requirements, through-put times and equipment costs is described. The economic and radiation dose impacts resulting from this automation are compared to manual handling methods

A comparison of rule-based and machine learning approaches for classifying patient portal messages.

Science.gov (United States)

Cronin, Robert M; Fabbri, Daniel; Denny, Joshua C; Rosenbloom, S Trent; Jackson, Gretchen Purcell

2017-09-01

Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows. Manual management of portal messages is costly and time consuming. Automated classification of portal messages could potentially expedite message triage and delivery of care. We developed automated patient portal message classifiers with rule-based and machine learning techniques using bag of words and natural language processing (NLP) approaches. To evaluate classifier performance, we used a gold standard of 3253 portal messages manually categorized using a taxonomy of communication types (i.e., main categories of informational, medical, logistical, social, and other communications, and subcategories including prescriptions, appointments, problems, tests, follow-up, contact information, and acknowledgement). We evaluated our classifiers' accuracies in identifying individual communication types within portal messages with area under the receiver-operator curve (AUC). Portal messages often contain more than one type of communication. To predict all communication types within single messages, we used the Jaccard Index. We extracted the variables of importance for the random forest classifiers. The best performing approaches to classification for the major communication types were: logistic regression for medical communications (AUC: 0.899); basic (rule-based) for informational communications (AUC: 0.842); and random forests for social communications and logistical communications (AUCs: 0.875 and 0.925, respectively). The best performing classification approach of classifiers for individual communication subtypes was random forests for Logistical-Contact Information (AUC: 0.963). The Jaccard Indices by approach were: basic classifier, Jaccard Index: 0.674; Naïve Bayes, Jaccard Index: 0.799; random forests, Jaccard Index: 0.859; and logistic regression, Jaccard

FACSIM/MRS-1: Cask receiving and consolidation model documentation and user's guide

International Nuclear Information System (INIS)

Lotz, T.L.; Shay, M.R.

1987-06-01

The Pacific Northwest Laboratory (PNL) has developed a stochastic computer model, FACSIM/MRS, to assist in assessing the operational performance of the Monitored Retrievable Storage (MRS) waste-handling facility. This report provides the documentation and user's guide for the component FACSIM/MRS-1, which is also referred to as the front-end model. The FACSIM/MRS-1 model simulates the MRS cask-receiving and spent-fuel consolidation activities. The results of the assessment of the operational performance of these activities are contained in a second report, FACSIM/MRS-1: Cask Receiving and Consolidation Performance Assessment (Lotz and Shay 1987). The model of MRS canister storage and shipping operations is presented in FACSIM/MRS-2: Storage and Shipping Model Documentation and User's Guide (Huber et al. 1987). The FACSIM/MRS model uses the commercially available FORTRAN-based SIMAN (SIMulation ANalysis language) simulation package (Pegden 1982). SIMAN provides a set of FORTRAN-coded commands, called block operations, which are used to build detailed models of continuous or discrete events that make up the operations of any process, such as the operation of an MRS facility. The FACSIM models were designed to run on either an IBM-PC or a VAX minicomputer. The FACSIM/MRS-1 model is flexible enough to collect statistics concerning almost any aspect of the cask receiving and consolidation operations of an MRS facility. The MRS model presently collects statistics on 51 quantities of interest during the simulation. SIMAN reports the statistics with two forms of output: a SIMAN simulation summary and an optional set of SIMAN output files containing data for use by more detailed post processors and report generators

Incorporating public outreach in the MRS Design

International Nuclear Information System (INIS)

Richardson, J.; Charles, C.

1993-01-01

As the design of the proposed DOE-OCRWM MRS facility progresses, facility layouts that allow for frequent and unhindered viewing of the MRS processes by the public should be developed. By allowing the public to observe operations, the DOE believes that trust and confidence in the program will greatly improve. A program should be developed to educate the public so that they can see for themselves that the MRS facility does not pose an undue risk to public health and that the DOE is open, honest, and can be trusted. At the same time, a positive safety message will be implicitly conveyed, which should engender more positive public feelings about nuclear energy. Visitory access to the MRS Facility should not be limited to a Visitors Center, but rather should be expanded to allow the general public a chance to view the actual processes, such as the cask handling and spent fuel transfers that go on within the facility. This paper will describe the desirable features of any approach to give unlimited public access to the MRS facility and operations and thereby enhance public understanding and acceptance

Development of an automated asbestos counting software based on fluorescence microscopy.

Science.gov (United States)

Alexandrov, Maxym; Ichida, Etsuko; Nishimura, Tomoki; Aoki, Kousuke; Ishida, Takenori; Hirota, Ryuichi; Ikeda, Takeshi; Kawasaki, Tetsuo; Kuroda, Akio

2015-01-01

An emerging alternative to the commonly used analytical methods for asbestos analysis is fluorescence microscopy (FM), which relies on highly specific asbestos-binding probes to distinguish asbestos from interfering non-asbestos fibers. However, all types of microscopic asbestos analysis require laborious examination of large number of fields of view and are prone to subjective errors and large variability between asbestos counts by different analysts and laboratories. A possible solution to these problems is automated counting of asbestos fibers by image analysis software, which would lower the cost and increase the reliability of asbestos testing. This study seeks to develop a fiber recognition and counting software for FM-based asbestos analysis. We discuss the main features of the developed software and the results of its testing. Software testing showed good correlation between automated and manual counts for the samples with medium and high fiber concentrations. At low fiber concentrations, the automated counts were less accurate, leading us to implement correction mode for automated counts. While the full automation of asbestos analysis would require further improvements in accuracy of fiber identification, the developed software could already assist professional asbestos analysts and record detailed fiber dimensions for the use in epidemiological research.

Mescalero Apache Tribe Monitored Retrievable Storage (MRS)

Energy Technology Data Exchange (ETDEWEB)

Peso, F.

1992-03-13

The Nuclear Waste Policy Act of 1982, as amended, authorizes the siting, construction and operation of a Monitored Retrievable Storage (MRS) facility. The MRS is intended to be used for the temporary storage of spent nuclear fuel from the nation's nuclear power plants beginning as early as 1998. Pursuant to the Nuclear Waste Policy Act, the Office of the Nuclear Waste Negotiator was created. On October 7, 1991, the Nuclear Waste Negotiator invited the governors of states and the Presidents of Indian tribes to apply for government grants in order to conduct a study to assess under what conditions, if any, they might consider hosting an MRS facility. Pursuant to this invitation, on October 11, 1991 the Mescalero Apache Indian Tribe of Mescalero, NM applied for a grant to conduct a phased, preliminary study of the safety, technical, political, environmental, social and economic feasibility of hosting an MRS. The preliminary study included: (1) An investigative education process to facilitate the Tribe's comprehensive understanding of the safety, environmental, technical, social, political, and economic aspects of hosting an MRS, and; (2) The development of an extensive program that is enabling the Tribe, in collaboration with the Negotiator, to reach an informed and carefully researched decision regarding the conditions, (if any), under which further pursuit of the MRS would be considered. The Phase 1 grant application enabled the Tribe to begin the initial activities necessary to determine whether further consideration is warranted for hosting the MRS facility. The Tribe intends to pursue continued study of the MRS in order to meet the following objectives: (1) Continuing the education process towards a comprehensive understanding of the safety, environmental, technical, social and economic aspects of the MRS; (2) Conducting an effective public participation and information program; (3) Participating in MRS meetings.

Mescalero Apache Tribe Monitored Retrievable Storage (MRS)

International Nuclear Information System (INIS)

Peso, F.

1992-01-01

The Nuclear Waste Policy Act of 1982, as amended, authorizes the siting, construction and operation of a Monitored Retrievable Storage (MRS) facility. The MRS is intended to be used for the temporary storage of spent nuclear fuel from the nation's nuclear power plants beginning as early as 1998. Pursuant to the Nuclear Waste Policy Act, the Office of the Nuclear Waste Negotiator was created. On October 7, 1991, the Nuclear Waste Negotiator invited the governors of states and the Presidents of Indian tribes to apply for government grants in order to conduct a study to assess under what conditions, if any, they might consider hosting an MRS facility. Pursuant to this invitation, on October 11, 1991 the Mescalero Apache Indian Tribe of Mescalero, NM applied for a grant to conduct a phased, preliminary study of the safety, technical, political, environmental, social and economic feasibility of hosting an MRS. The preliminary study included: (1) An investigative education process to facilitate the Tribe's comprehensive understanding of the safety, environmental, technical, social, political, and economic aspects of hosting an MRS, and; (2) The development of an extensive program that is enabling the Tribe, in collaboration with the Negotiator, to reach an informed and carefully researched decision regarding the conditions, (if any), under which further pursuit of the MRS would be considered. The Phase 1 grant application enabled the Tribe to begin the initial activities necessary to determine whether further consideration is warranted for hosting the MRS facility. The Tribe intends to pursue continued study of the MRS in order to meet the following objectives: (1) Continuing the education process towards a comprehensive understanding of the safety, environmental, technical, social and economic aspects of the MRS; (2) Conducting an effective public participation and information program; (3) Participating in MRS meetings

Automation in Warehouse Development

CERN Document Server

Verriet, Jacques

2012-01-01

The warehouses of the future will come in a variety of forms, but with a few common ingredients. Firstly, human operational handling of items in warehouses is increasingly being replaced by automated item handling. Extended warehouse automation counteracts the scarcity of human operators and supports the quality of picking processes. Secondly, the development of models to simulate and analyse warehouse designs and their components facilitates the challenging task of developing warehouses that take into account each customer’s individual requirements and logistic processes. Automation in Warehouse Development addresses both types of automation from the innovative perspective of applied science. In particular, it describes the outcomes of the Falcon project, a joint endeavour by a consortium of industrial and academic partners. The results include a model-based approach to automate warehouse control design, analysis models for warehouse design, concepts for robotic item handling and computer vision, and auton...

A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification

Science.gov (United States)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.

MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.

Classification of Automated Search Traffic

Science.gov (United States)

Buehrer, Greg; Stokes, Jack W.; Chellapilla, Kumar; Platt, John C.

As web search providers seek to improve both relevance and response times, they are challenged by the ever-increasing tax of automated search query traffic. Third party systems interact with search engines for a variety of reasons, such as monitoring a web site’s rank, augmenting online games, or possibly to maliciously alter click-through rates. In this paper, we investigate automated traffic (sometimes referred to as bot traffic) in the query stream of a large search engine provider. We define automated traffic as any search query not generated by a human in real time. We first provide examples of different categories of query logs generated by automated means. We then develop many different features that distinguish between queries generated by people searching for information, and those generated by automated processes. We categorize these features into two classes, either an interpretation of the physical model of human interactions, or as behavioral patterns of automated interactions. Using the these detection features, we next classify the query stream using multiple binary classifiers. In addition, a multiclass classifier is then developed to identify subclasses of both normal and automated traffic. An active learning algorithm is used to suggest which user sessions to label to improve the accuracy of the multiclass classifier, while also seeking to discover new classes of automated traffic. Performance analysis are then provided. Finally, the multiclass classifier is used to predict the subclass distribution for the search query stream.

Integral Monitored Retrievable Storage (MRS) Facility conceptual design report

International Nuclear Information System (INIS)

1985-09-01

This document, Volume 5 Book 1, contains cost estimate summaries for a monitored retrievable storage (MRS) facility. The cost estimate is based on the engineering performed during the conceptual design phase of the MRS Facility project

Report of the Task Force on the MRS/repository interface

International Nuclear Information System (INIS)

1986-02-01

In April 1985, the DOE established an MRS/repository interface task force to analyze the cost and schedule impacts of implementing an integrated waste-management system on the repository and the MRS facility. The intended end products of the study were preliminary conceptual designs of repository and MRS facilities, cost and schedule estimates, and other analyses that would advance the definition of the role and function of the MRS facility, support the preparation of the MRS proposal to Congress, and serve as a source of baseline data for further studies of the integrated waste-management system. From the general overall objectives, specific equations were developed to guide the task-force effort, e.g., What would the surface facilities at the repository look like and cost with an MRS facility in the system. In order to address these questions, five scenarios were defined and analyzed. (A number of other scenarios and associated issues were also explored to a lesser extent.) These five scenarios are as follows. Scenario 1: reference case (no MRS facility). Scenario 2: MRS facility with overpacking of both spent fuel and defense high-level waste. Scenario 3: MRS facility with overpacking of spent fuel only (defense-waste overpacking at the repository). Scenario 4: MRS facility with all overpacking at the repository. Scenario 5: MRS facility with all overpacking at the repository and western fuel shipped directly to the repository. It is apparent that, with such a limited set of scenarios, determination of the optimum system was not an objective of this study. Furthermore, time constraints limited the level of detail to which facility designs could be developed; this level can best be characterized as ''preconceptual.'' These limitations are, however, compatible with the intent of the study, which was to make general comparisons between the several systems on an internally consistent basis

Automated time activity classification based on global positioning system (GPS) tracking data.

Science.gov (United States)

Wu, Jun; Jiang, Chengsheng; Houston, Douglas; Baker, Dean; Delfino, Ralph

2011-11-14

Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust

Lean automation development : applying lean principles to the automation development process

OpenAIRE

Granlund, Anna; Wiktorsson, Magnus; Grahn, Sten; Friedler, Niklas

2014-01-01

By a broad empirical study it is indicated that automation development show potential of improvement. In the paper, 13 lean product development principles are contrasted to the automation development process and it is suggested why and how these principles can facilitate, support and improve the automation development process. The paper summarises a description of what characterises a lean automation development process and what consequences it entails. Main differences compared to current pr...

The DOE position on the MRS [monitored retrievable storage] facility

International Nuclear Information System (INIS)

1989-06-01

The DOE supports the development of an MRS facility as an integral part of the waste-management system because an MRS facility would allow the DOE to better meet its strategic objectives of timely disposal, timely and adequate waste acceptance, schedule confidence, and system flexibility. This facility would receive, store, and stage shipments of intact spent fuel to the repository and could be later expanded to perform additional functions that may be determined to be beneficial or required as the system design matures. Recognizing the difficulty of DOE-directed siting through national or regional screening, the DOE prefers an MRS facility that is sited through the efforts of the Nuclear Waste Negotiator, especially if the siting negotiations lead to linkages that allow the advantages of an MRS facility to be more fully realized. Even if such revised linkages are not achieved, however, the DOE supports the development of the MRS facility. 23 refs

Identified problems in fabricating Mobile Radioscopy System (MRS)

International Nuclear Information System (INIS)

Arshad Yassin; Khairul Anuar Mohd Salleh; Ab Razak Hamzah; Khari Che Ros; Hasni Hashim

2009-01-01

This paper describes problems found and solving method in our effort to fabricate the first up to standard mobile radioscopy system (MRS). The MRS is expected to solve problems faced by small and medium local industries to have their own digital industrial radiography system (DIR) i.e. expensive cost, lack of experience in handling radiation electronic detector, etc. Most of the problems occurred give the challenge to obtain the best radiographic image quality in terms of quantitative evaluation. With the upcoming developments, the MRS is expected to acceptable to be us in oil and gas industry and power generation plant. (Author)

Integral Monitored Retrievable Storage (MRS) Facility conceptual design report

International Nuclear Information System (INIS)

1985-09-01

The Basis for Design established the functional requirements and design criteria for an Integral Monitored Retrievable Storage (MRS) facility. The MRS Facility design, described in this report, is based on those requirements and includes all infrastructure, facilities, and equipment required to routinely receive, unload, prepare for storage, and store spent fuel (SF), high-level waste (HLW), and transuranic waste (TRU), and to decontaminate and return shipping casks received by both rail and truck. The facility is complete with all supporting facilities to make the MRS Facility a self-sufficient installation

Alternate technologies for MRS design

International Nuclear Information System (INIS)

Smith, R.I.; Triplett, M.B.; Ashton, W.B.; Kelly, W.S.

1984-01-01

This paper describes the process conducted by the Pacific Northwest Laboratory (PNL) to evaluate candidate MRS concepts and to recommend the two most preferred concepts. The eight concepts studied are: metal cask (stationary and transportable); concrete cask (silo); concrete cask-in-trench; field drywell; tunnel drywell; open cycle vault; closed cycle vault; and tunnel rack vault. To achieve a more equitable comparison of the concepts, conceptual design analyses were performed for the candidate concepts using a common set of specified design requirements selected with consideration of the MRS mission. Using this normalized conceptual design information, the MRS concepts were evaluated and compared on the basis of their relative performance on seven criteria: flexibility, concept maturity, cost, environmental impacts, safety and licensing, socioeconomic impacts, and siting requirements. These seven criteria were judged to form a reasonable and complete basis for the evaluation of MRS concepts' ability to satisfy the MRS mission requirements. 5 references, 8 figures, 1 table

Quality of life and hormone use: new validation results of MRS scale

Directory of Open Access Journals (Sweden)

Heinemann Lothar AJ

2006-05-01

Full Text Available Abstract Background The Menopause Rating Scale is a health-related Quality of Life scale developed in the early 1990s and step-by-step validated since then. Recently the MRS scale was validated as outcomes measure for hormone therapy. The suspicion however was expressed that the data were too optimistic due to methodological problems of the study. A new study became available to check how founded this suspicion was. Method An open post-marketing study of 3282 women with pre- and post- treatment data of the self-administered version of the MRS scale was analyzed to evaluate the capacity of the scale to detect hormone treatment related effects with the MRS scale. The main results were then compared with the old study where the interview-based version of the MRS scale was used. Results The hormone-therapy related improvement of complaints relative to the baseline score was about or less than 30% in total or domain scores, whereas it exceeded 30% improvement in the old study. Similarly, the relative improvement after therapy, stratified by the degree of severity at baseline, was lower in the new than in the old study, but had the same slope. Although we cannot exclude different treatment effects with the study method used, this supports our hypothesis that the individual MRS interviews performed by the physician biased the results towards over-estimation of the treatment effects. This hypothesis is underlined by the degree of concordance of physician's assessment and patient's perception of treatment success (MRS results: Sensitivity (correct prediction of the positive assessment by the treating physician of the MRS and specificity (correct prediction of a negative assessment by the physician were lower than the results obtained with the interview-based MRS scale in the previous publication. Conclusion The study confirmed evidence for the capacity of the MRS scale to measure treatment effects on quality of life across the full range of severity of

Naive Bayes classifiers for verbal autopsies: comparison to physician-based classification for 21,000 child and adult deaths.

Science.gov (United States)

Miasnikof, Pierre; Giannakeas, Vasily; Gomes, Mireille; Aleksandrowicz, Lukasz; Shestopaloff, Alexander Y; Alam, Dewan; Tollman, Stephen; Samarikhalaj, Akram; Jha, Prabhat

2015-11-25

Verbal autopsies (VA) are increasingly used in low- and middle-income countries where most causes of death (COD) occur at home without medical attention, and home deaths differ substantially from hospital deaths. Hence, there is no plausible "standard" against which VAs for home deaths may be validated. Previous studies have shown contradictory performance of automated methods compared to physician-based classification of CODs. We sought to compare the performance of the classic naive Bayes classifier (NBC) versus existing automated classifiers, using physician-based classification as the reference. We compared the performance of NBC, an open-source Tariff Method (OTM), and InterVA-4 on three datasets covering about 21,000 child and adult deaths: the ongoing Million Death Study in India, and health and demographic surveillance sites in Agincourt, South Africa and Matlab, Bangladesh. We applied several training and testing splits of the data to quantify the sensitivity and specificity compared to physician coding for individual CODs and to test the cause-specific mortality fractions at the population level. The NBC achieved comparable sensitivity (median 0.51, range 0.48-0.58) to OTM (median 0.50, range 0.41-0.51), with InterVA-4 having lower sensitivity (median 0.43, range 0.36-0.47) in all three datasets, across all CODs. Consistency of CODs was comparable for NBC and InterVA-4 but lower for OTM. NBC and OTM achieved better performance when using a local rather than a non-local training dataset. At the population level, NBC scored the highest cause-specific mortality fraction accuracy across the datasets (median 0.88, range 0.87-0.93), followed by InterVA-4 (median 0.66, range 0.62-0.73) and OTM (median 0.57, range 0.42-0.58). NBC outperforms current similar COD classifiers at the population level. Nevertheless, no current automated classifier adequately replicates physician classification for individual CODs. There is a need for further research on automated

Spent-fuel storage - MRS and/or on-site?

International Nuclear Information System (INIS)

Fuierer, A.A.

1991-01-01

The US government through the Office of Civilian Radioactive Waste Management (OCRWM) is seeking by the use of an authorized negotiator a site for a monitored retrievable storage (MRS) facility. Based on a public information document provided by the office of the negotiator, the MRS will be an integral part of the federal system for safe and permanent disposal of the nation's high-level radioactive wastes. It is planned that the MRS will accept and store spent fuel above ground until a repository opens and spent fuel that has been stored is shipped from the MRS to the repository. Additional spent fuel stored at reactor sites will be shipped to the MRS, which will be used as a staging area to assemble dedicated trains for shipment to the repository. The intent of the MRS is to reduce utilities' needs to expand on-site storage of spent fuel. A utility viewpoint may emphasize an alternate set of priorities. The waste management system must be considered as an overall system involving both the utility and DOE that begins with the first discharge of spent nuclear fuel from a commercial reactor and ends with high-level waste in a final repository. Many studies have been made on individual components of a waste system. This study, with the benefit of past hands-on experience as a guide, looks at costs and reliability for a total system concept with particular emphasis on the interface between the utility and Department of Energy

Automated data acquisition technology development:Automated modeling and control development

Science.gov (United States)

Romine, Peter L.

1995-01-01

This report documents the completion of, and improvements made to, the software developed for automated data acquisition and automated modeling and control development on the Texas Micro rackmounted PC's. This research was initiated because a need was identified by the Metal Processing Branch of NASA Marshall Space Flight Center for a mobile data acquisition and data analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC based system was chosen. The Welding Measurement System (WMS), is a dedicated instrument strickly for use of data acquisition and data analysis. In addition to the data acquisition functions described in this thesis, WMS also supports many functions associated with process control. The hardware and software requirements for an automated acquisition system for welding process parameters, welding equipment checkout, and welding process modeling were determined in 1992. From these recommendations, NASA purchased the necessary hardware and software. The new welding acquisition system is designed to collect welding parameter data and perform analysis to determine the voltage versus current arc-length relationship for VPPA welding. Once the results of this analysis are obtained, they can then be used to develop a RAIL function to control welding startup and shutdown without torch crashing.

Context based mixture model for cell phase identification in automated fluorescence microscopy

Directory of Open Access Journals (Sweden)

Zhou Xiaobo

2007-01-01

Full Text Available Abstract Background Automated identification of cell cycle phases of individual live cells in a large population captured via automated fluorescence microscopy technique is important for cancer drug discovery and cell cycle studies. Time-lapse fluorescence microscopy images provide an important method to study the cell cycle process under different conditions of perturbation. Existing methods are limited in dealing with such time-lapse data sets while manual analysis is not feasible. This paper presents statistical data analysis and statistical pattern recognition to perform this task. Results The data is generated from Hela H2B GFP cells imaged during a 2-day period with images acquired 15 minutes apart using an automated time-lapse fluorescence microscopy. The patterns are described with four kinds of features, including twelve general features, Haralick texture features, Zernike moment features, and wavelet features. To generate a new set of features with more discriminate power, the commonly used feature reduction techniques are used, which include Principle Component Analysis (PCA, Linear Discriminant Analysis (LDA, Maximum Margin Criterion (MMC, Stepwise Discriminate Analysis based Feature Selection (SDAFS, and Genetic Algorithm based Feature Selection (GAFS. Then, we propose a Context Based Mixture Model (CBMM for dealing with the time-series cell sequence information and compare it to other traditional classifiers: Support Vector Machine (SVM, Neural Network (NN, and K-Nearest Neighbor (KNN. Being a standard practice in machine learning, we systematically compare the performance of a number of common feature reduction techniques and classifiers to select an optimal combination of a feature reduction technique and a classifier. A cellular database containing 100 manually labelled subsequence is built for evaluating the performance of the classifiers. The generalization error is estimated using the cross validation technique. The

Proton MRS in neurological disorders

Energy Technology Data Exchange (ETDEWEB)

Bonavita, S.; Di Salle, F.; Tedeschi, G

1999-05-01

Proton magnetic resonance spectroscopy ({sup 1}H MRS) permits the acquisition of the signal arising from several brain metabolites. At long echo-time (TE) {sup 1}H MRS can detect N-acetyl-aspartate containing compounds, choline containing compounds, creatine+phosphocreatine and lactate. At short TE, lipids, tryglicerides, alanine, glutamate, glutamine, GABA, scyllo-inositol, glucose, myo-inositol, carnosine and histydine are visible. {sup 1}H MRS can be performed with single-voxel, multivoxel, single slice and multislice techniques. With single voxel {sup 1}H MRS it is possible to measure metabolites relaxation time, which allows the measurement of metabolite concentrations. This technique can be useful in the study of focal lesions in the central nervous system (CNS) such as epilepsy (pre-surgical identification of epileptic focus), brain tumors (evaluation of recurrence and radiation necrosis), stroke, multiple sclerosis, etc. Single slice and multislice {sup 1}H MRS imaging ({sup 1}H MRSI) can be performed only at long TE and permits the mapping of the brain metabolites distribution which makes them particularly useful in studying diffuse diseases and heterogeneous lesions of the CNS. {sup 1}H MRS can also be useful in the evaluation of 'ischemic penumbra' of stroke; developmental (myelin and neuronal dysgenesis); head trauma (evaluation of cerebral damage not visible with MRI); degenerative disorders (identification of microscopic pathology not visible with MRI); and metabolic diseases (metabolic disturbances with specific metabolic patterns)

Mrs. Squandertime

Science.gov (United States)

Anstey, Josephine; Pape, Dave

2013-03-01

In this paper we discuss Mrs. Squandertime, a real-time, persistent simulation of a virtual character, her living room, and the view from her window, designed to be a wall-size, projected art installation. Through her large picture window, the eponymous Mrs. Squandertime watches the sea: boats, clouds, gulls, the tide going in and out, people on the sea wall. The hundreds of images that compose the view are drawn from historical printed sources. The program that assembles and animates these images is driven by weather, time, and tide data constantly updated from a real physical location. The character herself is rendered photographically in a series of slowly dissolving stills which correspond to the character's current behavior.

Automated lung nodule classification following automated nodule detection on CT: A serial approach

International Nuclear Information System (INIS)

Armato, Samuel G. III; Altman, Michael B.; Wilkie, Joel; Sone, Shusuke; Li, Feng; Doi, Kunio; Roy, Arunabha S.

2003-01-01

We have evaluated the performance of an automated classifier applied to the task of differentiating malignant and benign lung nodules in low-dose helical computed tomography (CT) scans acquired as part of a lung cancer screening program. The nodules classified in this manner were initially identified by our automated lung nodule detection method, so that the output of automated lung nodule detection was used as input to automated lung nodule classification. This study begins to narrow the distinction between the 'detection task' and the 'classification task'. Automated lung nodule detection is based on two- and three-dimensional analyses of the CT image data. Gray-level-thresholding techniques are used to identify initial lung nodule candidates, for which morphological and gray-level features are computed. A rule-based approach is applied to reduce the number of nodule candidates that correspond to non-nodules, and the features of remaining candidates are merged through linear discriminant analysis to obtain final detection results. Automated lung nodule classification merges the features of the lung nodule candidates identified by the detection algorithm that correspond to actual nodules through another linear discriminant classifier to distinguish between malignant and benign nodules. The automated classification method was applied to the computerized detection results obtained from a database of 393 low-dose thoracic CT scans containing 470 confirmed lung nodules (69 malignant and 401 benign nodules). Receiver operating characteristic (ROC) analysis was used to evaluate the ability of the classifier to differentiate between nodule candidates that correspond to malignant nodules and nodule candidates that correspond to benign lesions. The area under the ROC curve for this classification task attained a value of 0.79 during a leave-one-out evaluation

Criticality safety considerations. Integral Monitored Retrievable Storage (MRS) Facility

International Nuclear Information System (INIS)

1986-09-01

This report summarizes the criticality analysis performed to address criticality safety concerns and to support facility design during the conceptual design phase of the Monitored Retrievable Storage (MRS) Facility. The report addresses the criticality safety concerns, the design features of the facility relative to criticality, and the results of the analysis of both normal operating and hypothetical off-normal conditions. Key references are provided (Appendix C) if additional information is desired by the reader. The MRS Facility design was developed and the related analysis was performed in accordance with the MRS Facility Functional Design Criteria and the Basis for Design. The detailed description and calculations are documented in the Integral MRS Facility Conceptual Design Report. In addition to the summary portion of this report, explanatary notes for various terms, calculation methodology, and design parameters are presented in Appendix A. Appendix B provides a brief glossary of technical terms

FACSIM/MRS [Monitored Retrievable Storage]-2: Storage and shipping model documentation and user's guide

International Nuclear Information System (INIS)

Huber, H.D.; Chockie, A.D.; Hostick, C.J.; Otis, P.T.; Sovers, R.A.

1987-06-01

The Pacific Northwest Laboratory (PNL) has developed a stochastic computer model, FACSIM/MRS, to assist in assessing the operational performance of the Monitored Retrievable Storage (MRS) waste-handling facility. This report provides the documentation and user's guide for FACSIM/MRS-2, which is also referred to as the back-end model. The FACSIM/MRS-2 model simulates the MRS storage and shipping operations, which include handling canistered spent fuel and secondary waste in the shielded canyon cells, in onsite yard storage, and in repository shipping cask loading areas

Home made FPGA based instrumentation development for linac automation at IUAC

International Nuclear Information System (INIS)

Antony, J.; Mathuria, D.S.; Sacharias, J.

2011-01-01

In order to make the Inter-University Accelerator Centre (IUAC) linac operation with less human intervention and with minimum effort, different mechanisms of automation are being thought of and are being implemented. Among the various projects in the automation, the first one is the development of a 16-channel digital linearizer unit for RF power read-backs and control. In another development, 8 channel programmable pulse generators (PPG) were designed, developed and used at the time of RF pulse conditioning of the SC resonators. As a third project of linac automation, a computer controlled drive probe controller was developed to control the movement of 8 drive couplers of the resonator along with position sensor read back mechanisms. (author)

MRS systems study, Task F: Transportation impacts of a monitored retrievable storage facility

Energy Technology Data Exchange (ETDEWEB)

Brentlinger, L.A.; Gupta, S.; Plummer, A.M.; Smith, L.A.; Tzemos, S.

1989-05-01

The passage of the Nuclear Waste Policy Amendments Act of 1987 (NWPAA) modified the basis from which the Office of Civilian Radioactive Waste Management (OCRWM) had derived and developed the configuration of major elements of the waste system (repository, monitored retrievable storage, and transportation). While the key aspects of the Nuclear Waste Policy Act of 1982 remain unaltered, NWPAA provisions focusing site characterization solely at Yucca Mountain, authorizing a monitored retrievable storage (MRS) facility with specific linkages to the repository, and establishing an MRS Review Commission make it prudent for OCRWM to update its analysis of the role of the MRS in the overall waste system configuration. This report documents the differences in transportation costs and radiological dose under alternative scenarios pertaining to a nuclear waste management system with and without an MRS, to include the effect of various MRS packaging functions and locations. The analysis is limited to the impacts of activities related directly to the hauling of high-level radioactive waste (HLW), including the capital purchase and maintenance costs of the transportation cask system. Loading and unloading impacts are not included in this study because they are treated as facility costs in the other task reports. Transportation costs are based on shipments of 63,000 metric tons of uranium (MTU) of spent nuclear fuel and 7,000 MTU equivalent of HLW. 10 refs., 41 tabs.

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha

2013-11-25

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Mobile App to Streamline the Development of Wearable Sensor-Based Exercise Biofeedback Systems: System Development and Evaluation.

Science.gov (United States)

O'Reilly, Martin; Duffin, Joe; Ward, Tomas; Caulfield, Brian

2017-08-21

Biofeedback systems that use inertial measurement units (IMUs) have been shown recently to have the ability to objectively assess exercise technique. However, there are a number of challenges in developing such systems; vast amounts of IMU exercise datasets must be collected and manually labeled for each exercise variation, and naturally occurring technique deviations may not be well detected. One method of combatting these issues is through the development of personalized exercise technique classifiers. We aimed to create a tablet app for physiotherapists and personal trainers that would automate the development of personalized multiple and single IMU-based exercise biofeedback systems for their clients. We also sought to complete a preliminary investigation of the accuracy of such individualized systems in a real-world evaluation. A tablet app was developed that automates the key steps in exercise technique classifier creation through synchronizing video and IMU data collection, automatic signal processing, data segmentation, data labeling of segmented videos by an exercise professional, automatic feature computation, and classifier creation. Using a personalized single IMU-based classification system, 15 volunteers (12 males, 3 females, age: 23.8 [standard deviation, SD 1.8] years, height: 1.79 [SD 0.07] m, body mass: 78.4 [SD 9.6] kg) then completed 4 lower limb compound exercises. The real-world accuracy of the systems was evaluated. The tablet app successfully automated the process of creating individualized exercise biofeedback systems. The personalized systems achieved 89.50% (1074/1200) accuracy, with 90.00% (540/600) sensitivity and 89.00% (534/600) specificity for assessing aberrant and acceptable technique with a single IMU positioned on the left thigh. A tablet app was developed that automates the process required to create a personalized exercise technique classification system. This tool can be applied to any cyclical, repetitive exercise. The

Advanced processing and simulation of MRS data using the FID appliance (FID-A)-An open source, MATLAB-based toolkit.

Science.gov (United States)

Simpson, Robin; Devenyi, Gabriel A; Jezzard, Peter; Hennessy, T Jay; Near, Jamie

2017-01-01

To introduce a new toolkit for simulation and processing of magnetic resonance spectroscopy (MRS) data, and to demonstrate some of its novel features. The FID appliance (FID-A) is an open-source, MATLAB-based software toolkit for simulation and processing of MRS data. The software is designed specifically for processing data with multiple dimensions (eg, multiple radiofrequency channels, averages, spectral editing dimensions). It is equipped with functions for importing data in the formats of most major MRI vendors (eg, Siemens, Philips, GE, Agilent) and for exporting data into the formats of several common processing software packages (eg, LCModel, jMRUI, Tarquin). This paper introduces the FID-A software toolkit and uses examples to demonstrate its novel features, namely 1) the use of a spectral registration algorithm to carry out useful processing routines automatically, 2) automatic detection and removal of motion-corrupted scans, and 3) the ability to perform several major aspects of the MRS computational workflow from a single piece of software. This latter feature is illustrated through both high-level processing of in vivo GABA-edited MEGA-PRESS MRS data, as well as detailed quantum mechanical simulations to generate an accurate LCModel basis set for analysis of the same data. All of the described processing steps resulted in a marked improvement in spectral quality compared with unprocessed data. Fitting of MEGA-PRESS data using a customized basis set resulted in improved fitting accuracy compared with a generic MEGA-PRESS basis set. The FID-A software toolkit enables high-level processing of MRS data and accurate simulation of in vivo MRS experiments. Magn Reson Med 77:23-33, 2017. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Visit of Mrs Gisela Kopper

CERN Multimedia

Jimenez, Jose Miguel

2014-01-01

Mrs Gisela Kopper Minister of Science, Technology and Telecommunications, Republic of Costa Rica; Mrs Roxana Tinoco, Minister Counsellor, Permanent Mission of Costa Rica to the United Nations; Mr Mario Vega, Minister Counsellor, Permanent Mission of Costa Rica to the United Nations; Dr Jose Miguel Jimenez, Technology Department Head; Prof. Emmanuel Tsesmelis, Deputy Head of International Relations

Automated Resource Classifier for agglomerative functional ...

Indian Academy of Sciences (India)

2007-06-16

Jun 16, 2007 ... Automated resource; functional classification; integrative biology ... which is an open source software meeting the user requirements of flexibility. ... entries into any of the 7 basic non-overlapping functional classes: Cell wall, ...

Support vector machine as a binary classifier for automated object detection in remotely sensed data

International Nuclear Information System (INIS)

Wardaya, P D

2014-01-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result

Support vector machine as a binary classifier for automated object detection in remotely sensed data

Science.gov (United States)

Wardaya, P. D.

2014-02-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result.

Knowledge-based requirements analysis for automating software development

Science.gov (United States)

Markosian, Lawrence Z.

1988-01-01

We present a new software development paradigm that automates the derivation of implementations from requirements. In this paradigm, informally-stated requirements are expressed in a domain-specific requirements specification language. This language is machine-understable and requirements expressed in it are captured in a knowledge base. Once the requirements are captured, more detailed specifications and eventually implementations are derived by the system using transformational synthesis. A key characteristic of the process is that the required human intervention is in the form of providing problem- and domain-specific engineering knowledge, not in writing detailed implementations. We describe a prototype system that applies the paradigm in the realm of communication engineering: the prototype automatically generates implementations of buffers following analysis of the requirements on each buffer.

Mescalero Apache Tribe Monitored Retrievable Storage (MRS). Phase 1 feasibility study report

Energy Technology Data Exchange (ETDEWEB)

Peso, F.

1992-03-13

The Nuclear Waste Policy Act of 1982, as amended, authorizes the siting, construction and operation of a Monitored Retrievable Storage (MRS) facility. The MRS is intended to be used for the temporary storage of spent nuclear fuel from the nation`s nuclear power plants beginning as early as 1998. Pursuant to the Nuclear Waste Policy Act, the Office of the Nuclear Waste Negotiator was created. On October 7, 1991, the Nuclear Waste Negotiator invited the governors of states and the Presidents of Indian tribes to apply for government grants in order to conduct a study to assess under what conditions, if any, they might consider hosting an MRS facility. Pursuant to this invitation, on October 11, 1991 the Mescalero Apache Indian Tribe of Mescalero, NM applied for a grant to conduct a phased, preliminary study of the safety, technical, political, environmental, social and economic feasibility of hosting an MRS. The preliminary study included: (1) An investigative education process to facilitate the Tribe`s comprehensive understanding of the safety, environmental, technical, social, political, and economic aspects of hosting an MRS, and; (2) The development of an extensive program that is enabling the Tribe, in collaboration with the Negotiator, to reach an informed and carefully researched decision regarding the conditions, (if any), under which further pursuit of the MRS would be considered. The Phase 1 grant application enabled the Tribe to begin the initial activities necessary to determine whether further consideration is warranted for hosting the MRS facility. The Tribe intends to pursue continued study of the MRS in order to meet the following objectives: (1) Continuing the education process towards a comprehensive understanding of the safety, environmental, technical, social and economic aspects of the MRS; (2) Conducting an effective public participation and information program; (3) Participating in MRS meetings.

Monitoring of aquifer pump tests with Magnetic Resonance Sounding (MRS): a synthetic case study

DEFF Research Database (Denmark)

Herckenrath, Daan; Auken, E.; Bauer-Gottwein, Peter

2011-01-01

Magnetic Resonance Sounding (MRS) can provide valuable data to constrain and calibrate groundwater flow and transport models. With this non-invasive geophysical technique, measurements of water content and hydraulic conductivity can be obtained. We developed a hydrogeophyiscal forward method, which...... calculates the MRS-signal generated by an aquifer pump test. A synthetic MRS-dataset was subsequently used to determine the hydrogeological parameters in an inverse parameter estimation approach. This was done for a virtual pump test with a partially and a fully penetrating well. With the MRS data we were...

Generating prior probabilities for classifiers of brain tumours using belief networks

Directory of Open Access Journals (Sweden)

Arvanitis Theodoros N

2007-09-01

Full Text Available Abstract Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET, germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.

Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals

Directory of Open Access Journals (Sweden)

Jianfeng Hu

2017-08-01

fatigue through the classification of EEG signals.Conclusion: By using combination of FE features and AdaBoost classifier to detect EEG-based driver fatigue, this paper ensured confidence in exploring the inherent physiological mechanisms and wearable application.

Cooking up an open source EMR for developing countries: OpenMRS - a recipe for successful collaboration.

Science.gov (United States)

Mamlin, Burke W; Biondich, Paul G; Wolfe, Ben A; Fraser, Hamish; Jazayeri, Darius; Allen, Christian; Miranda, Justin; Tierney, William M

2006-01-01

Millions of people are continue to die each year from HIV/AIDS. The majority of infected persons (>95%) live in the developing world. A worthy response to this pandemic will require coordinated, scalable, and flexible information systems. We describe the OpenMRS system, an open source, collaborative effort that can serve as a foundation for EMR development in developing countries. We report our progress to date, lessons learned, and future directions.

MRS [monitored retrievable storage] Systems Study Task 1 report: Waste management system reliability analysis

International Nuclear Information System (INIS)

Clark, L.L.; Myers, R.S.

1989-04-01

This is one of nine studies undertaken by contractors to the US Department of Energy (DOE), Office of Civilian Radioactive Waste Management (OCRWM), to provide a technical basis for re-evaluating the role of a monitored retrievable storage (MRS) facility. The study evaluates the relative reliabilities of systems with and without an MRS facility using current facility design bases. The principal finding of this report is that the MRS system has several operational advantages that enhance system reliability. These are: (1) the MRS system is likely to encounter fewer technical issues, (2) the MRS would assure adequate system surface storage capacity to accommodate repository construction and startup delays of up to five years or longer if the Nuclear Waste Policy Amendments Act (NWPAA) were amended, (3) the system with an MRS has two federal acceptance facilities with parallel transportation routing and surface storage capacity, and (4) the MRS system would allow continued waste acceptance for up to a year after a major disruption of emplacement operations at the repository

FACSIM/MRS (Monitored Retrievable Storage)-2: Storage and shipping model documentation and user's guide

Energy Technology Data Exchange (ETDEWEB)

Huber, H.D.; Chockie, A.D.; Hostick, C.J.; Otis, P.T.; Sovers, R.A.

1987-06-01

The Pacific Northwest Laboratory (PNL) has developed a stochastic computer model, FACSIM/MRS, to assist in assessing the operational performance of the Monitored Retrievable Storage (MRS) waste-handling facility. This report provides the documentation and user's guide for FACSIM/MRS-2, which is also referred to as the back-end model. The FACSIM/MRS-2 model simulates the MRS storage and shipping operations, which include handling canistered spent fuel and secondary waste in the shielded canyon cells, in onsite yard storage, and in repository shipping cask loading areas.

Semantics-based Automated Web Testing

Directory of Open Access Journals (Sweden)

Hai-Feng Guo

2015-08-01

Full Text Available We present TAO, a software testing tool performing automated test and oracle generation based on a semantic approach. TAO entangles grammar-based test generation with automated semantics evaluation using a denotational semantics framework. We show how TAO can be incorporated with the Selenium automation tool for automated web testing, and how TAO can be further extended to support automated delta debugging, where a failing web test script can be systematically reduced based on grammar-directed strategies. A real-life parking website is adopted throughout the paper to demonstrate the effectivity of our semantics-based web testing approach.

Detection of inflammatory bowel disease by proton magnetic resonance spectroscopy (1H MRS using an animal model

Directory of Open Access Journals (Sweden)

Dolenko Brion

2007-11-01

Full Text Available Abstract Background The aim of this study was to analyze the potential of proton magnetic resonance spectroscopy (1H MRS in diagnosing early inflammatory bowel disease (IBD. Methods Thirty male Sprague Dawley rats were fed 2% carrageenan in their diet for either 1 or 2 weeks. 1H MRS was performed ex-vivo on colonic mucosal samples (n = 123 and the spectra were analyzed by a multivariate method of analysis. The results of the multivariate analysis were correlated with histological analysis performed using H & E stain for the presence of inflammation in the samples from each group. Results Multivariate analysis classified the samples in their respective groups with an accuracy of 82%. Our region selection algorithm identified four regions in the spectra as being discriminatory. The metabolites assigned to these regions include creatine, phosphatidylcholine, the -CH2HC= group in fatty acyl chain, and the glycerol backbone of lipids. The differences in concentration of these metabolites in each group offer insight into the biochemical changes occurring during IBD and confer diagnostic potential to 1H MRS as a tool to study colonic inflammation in conjunction with biopsy. Conclusion 1H MRS is a sensitive tool to detect early colonic inflammation in an animal model of IBD.

MRS algorithm: a new method for searching myocardial region in SPECT myocardial perfusion images.

Science.gov (United States)

He, Yuan-Lie; Tian, Lian-Fang; Chen, Ping; Li, Bin; Mao, Zhong-Yuan

2005-10-01

First, the necessity of automatically segmenting myocardium from myocardial SPECT image is discussed in Section 1. To eliminate the influence of the background, the optimal threshold segmentation method modified for the MRS algorithm is explained in Section 2. Then, the image erosion structure is applied to identify the myocardium region and the liver region. The contour tracing method is introduced to extract the myocardial contour. To locate the centriod of the myocardium, the myocardial centriod searching method is developed. The protocol of the MRS algorithm is summarized in Section 6. The performance of the MRS algorithm is investigated and the conclusion is drawn in Section 7. Finally, the importance of the MRS algorithm and the improvement of the MRS algorithm are discussed.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

Science.gov (United States)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

A SOA-Based Embedded Systems Development Environment for Industrial Automation

Directory of Open Access Journals (Sweden)

G. Doukas

2007-10-01

Full Text Available Currently available toolsets for the development of embedded systems adopt traditional architectural styles and do not cover the whole requirements of the development process, with extensibility being the major drawback. In this paper, a service-oriented architectural framework that exploits semantic web is defined. Features required in the development process are defined as web services and published into the public domain, so as to be used on demand by developers to construct their projects' specific integrated development environments (IDEs. The infrastructure required to build a web service-based IDE is presented. Specific web services are defined and the way these services affect the development process is discussed. Special focus is given on the device model and the means that such a modelling can significantly improve the development process. A prototype implementation demonstrates the applicability and usefulness of the proposed demand-led development process in the industrial automation domain.

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

Science.gov (United States)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Novel insights in agent-based complex automated negotiation

CERN Document Server

Lopez-Carmona, Miguel; Ito, Takayuki; Zhang, Minjie; Bai, Quan; Fujita, Katsuhide

2014-01-01

This book focuses on all aspects of complex automated negotiations, which are studied in the field of autonomous agents and multi-agent systems. This book consists of two parts. I: Agent-Based Complex Automated Negotiations, and II: Automated Negotiation Agents Competition. The chapters in Part I are extended versions of papers presented at the 2012 international workshop on Agent-Based Complex Automated Negotiation (ACAN), after peer reviews by three Program Committee members. Part II examines in detail ANAC 2012 (The Third Automated Negotiating Agents Competition), in which automated agents that have different negotiation strategies and are implemented by different developers are automatically negotiated in the several negotiation domains. ANAC is an international competition in which automated negotiation strategies, submitted by a number of universities and research institutes across the world, are evaluated in tournament style. The purpose of the competition is to steer the research in the area of bilate...

Development of Articulated Competency-Based Curriculum in Automated Systems/Robotics Technology. Final Report.

Science.gov (United States)

Luzerne County Community Coll., Nanticoke, PA.

The project described in this report was conducted at the Community College of Luzerne County (Pennsylvania) to develop, in conjunction with area vocational-technical schools, the second year of a competency-based curriculum in automated systems/robotics technology. During the project, a task force of teachers from the area schools and the college…

MRS [monitored retrievable storage] to transportation system interfaces

International Nuclear Information System (INIS)

Row, T.H.; Croff, A.G.

1987-01-01

In March 1987, the US Department of Energy presented to Congress the proposal to construct and operate a facility for the monitored retrievable storage (MRS) of spent fuel at a site on the Clinch River in the Roane County portions of Oak Ridge. In discussing the MRS to Transportation System Interfaces, the authors provide a blending of the technical and institutional issues, for they do not believe the solutions to success of this enterprise lie wholly in one area. The authors cover: early chronology of the MRS; comparison of total-system life cycle cost estimates of the authorized system and improved-performance system (i.e., the system that includes a facility for MRS); transportation costs resulting from shipping, security and cask; assumptions for dedicated rail transport from MRS to repository; and significant results from the Total System Life Cycle Cost (TSLCC) analysis of the improved performance system. (AT)

A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER

Directory of Open Access Journals (Sweden)

A. Hadavand

2015-12-01

Full Text Available In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS, a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

A SOA-Based Embedded Systems Development Environment for Industrial Automation

Directory of Open Access Journals (Sweden)

Thramboulidis KC

2008-01-01

Full Text Available Abstract Currently available toolsets for the development of embedded systems adopt traditional architectural styles and do not cover the whole requirements of the development process, with extensibility being the major drawback. In this paper, a service-oriented architectural framework that exploits semantic web is defined. Features required in the development process are defined as web services and published into the public domain, so as to be used on demand by developers to construct their projects' specific integrated development environments (IDEs. The infrastructure required to build a web service-based IDE is presented. Specific web services are defined and the way these services affect the development process is discussed. Special focus is given on the device model and the means that such a modelling can significantly improve the development process. A prototype implementation demonstrates the applicability and usefulness of the proposed demand-led development process in the industrial automation domain.

Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers

Directory of Open Access Journals (Sweden)

Dawei Li

2017-01-01

Full Text Available This study develops a tree augmented naive Bayesian (TAN classifier based incident detection algorithm. Compared with the Bayesian networks based detection algorithms developed in the previous studies, this algorithm has less dependency on experts’ knowledge. The structure of TAN classifier for incident detection is learned from data. The discretization of continuous attributes is processed using an entropy-based method automatically. A simulation dataset on the section of the Ayer Rajah Expressway (AYE in Singapore is used to demonstrate the development of proposed algorithm, including wavelet denoising, normalization, entropy-based discretization, and structure learning. The performance of TAN based algorithm is evaluated compared with the previous developed Bayesian network (BN based and multilayer feed forward (MLF neural networks based algorithms with the same AYE data. The experiment results show that the TAN based algorithms perform better than the BN classifiers and have a similar performance to the MLF based algorithm. However, TAN based algorithm would have wider vista of applications because the theory of TAN classifiers is much less complicated than MLF. It should be found from the experiment that the TAN classifier based algorithm has a significant superiority over the speed of model training and calibration compared with MLF.

MRS on Indian lands? Congress shuffles feet

International Nuclear Information System (INIS)

Hudson, M.

1995-01-01

This article discusses the political, social, and economic aspects of siting the Monitored Retrieval Storage (MRS) facility. The first focus is on siting in American Indian lands, specifically in Mescalero, New Mexico, followed by a more general discussion of the problems surrounding MRS siting

Silicon avalanche photodiodes on the base of metal-resistor-semiconductor (MRS) structures

CERN Document Server

Saveliev, V

2000-01-01

The development of a high quantum efficiency, fast photodetector, with internal gain amplification for the wavelength range 450-600 nm is one of the critical issues for experimental physics - registration of low-intensity light photons flux. The new structure of Silicon Avalanche Detectors with high internal amplification (10 sup 5 -10 sup 6) has been designed, manufactured and tested for registration of visible light photons and charge particles. The main features of Metal-Resistor-Semiconductor (MRS) structures are the high charge multiplication in nonuniform electric field near the 'needle' pn-junction and negative feedback for stabilization of avalanche process due to resistive layer.

Development of a web-based CANDU core management procedures automation system

International Nuclear Information System (INIS)

Lee, S.; Park, D.; Yeom, C.; Suh, H.

2007-01-01

Introduce CANDU core management procedures automation system (COMPAS) - A web-based application which semi-automates several CANDU core management tasks. It provides various functionalities including selection and evaluation of refueling channel, detector calibration, coolant flow estimation and thermal power calculation through automated interfacing with analysis codes (RFSP, NUCIRC, etc.) and plant data. It also utilizes brand new .NET computing technology such as ASP.NET, smart client, web services and so on. Since almost all functions are abstracted from the previous experiences of the current working members of the Wolsong Nuclear Power Plant (NPP), it will lead to an efficient and safe operation of CANDU plants. (author)

Development of a web-based CANDU core management procedures automation system

Energy Technology Data Exchange (ETDEWEB)

Lee, S.; Park, D.; Yeom, C. [Inst. for Advanced Engineering (IAE), Yongin (Korea, Republic of); Suh, H. [Korea Hydro and Nuclear Power (KHNP), Wolsong (Korea, Republic of)

2007-07-01

Introduce CANDU core management procedures automation system (COMPAS) - A web-based application which semi-automates several CANDU core management tasks. It provides various functionalities including selection and evaluation of refueling channel, detector calibration, coolant flow estimation and thermal power calculation through automated interfacing with analysis codes (RFSP, NUCIRC, etc.) and plant data. It also utilizes brand new .NET computing technology such as ASP.NET, smart client, web services and so on. Since almost all functions are abstracted from the previous experiences of the current working members of the Wolsong Nuclear Power Plant (NPP), it will lead to an efficient and safe operation of CANDU plants. (author)

Proton MRS imaging in pediatric brain tumors

Energy Technology Data Exchange (ETDEWEB)

Zarifi, Maria [Aghia Sophia Children' s Hospital, Department of Radiology, Athens (Greece); Tzika, A.A. [Harvard Medical School, Department of Surgery, Massachusetts General Hospital, Boston, MA (United States); Shriners Burn Hospital, Boston, MA (United States)

2016-06-15

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors. (orig.)

Knowledge-based automated radiopharmaceutical manufacturing for Positron Emission Tomography

International Nuclear Information System (INIS)

Alexoff, D.L.

1991-01-01

This article describes the application of basic knowledge engineering principles to the design of automated synthesis equipment for radiopharmaceuticals used in Positron Emission Tomography (PET). Before discussing knowledge programming, an overview of the development of automated radiopharmaceutical synthesis systems for PET will be presented. Since knowledge systems will rely on information obtained from machine transducers, a discussion of the uses of sensory feedback in today's automated systems follows. Next, the operation of these automated systems is contrasted to radiotracer production carried out by chemists, and the rationale for and basic concepts of knowledge-based programming are explained. Finally, a prototype knowledge-based system supporting automated radiopharmaceutical manufacturing of 18FDG at Brookhaven National Laboratory (BNL) is described using 1stClass, a commercially available PC-based expert system shell

Data Stream Classification Based on the Gamma Classifier

Directory of Open Access Journals (Sweden)

Abril Valeria Uriarte-Arcia

2015-01-01

Full Text Available The ever increasing data generation confronts us with the problem of handling online massive amounts of information. One of the biggest challenges is how to extract valuable information from these massive continuous data streams during single scanning. In a data stream context, data arrive continuously at high speed; therefore the algorithms developed to address this context must be efficient regarding memory and time management and capable of detecting changes over time in the underlying distribution that generated the data. This work describes a novel method for the task of pattern classification over a continuous data stream based on an associative model. The proposed method is based on the Gamma classifier, which is inspired by the Alpha-Beta associative memories, which are both supervised pattern recognition models. The proposed method is capable of handling the space and time constrain inherent to data stream scenarios. The Data Streaming Gamma classifier (DS-Gamma classifier implements a sliding window approach to provide concept drift detection and a forgetting mechanism. In order to test the classifier, several experiments were performed using different data stream scenarios with real and synthetic data streams. The experimental results show that the method exhibits competitive performance when compared to other state-of-the-art algorithms.

Operational Based Vision Assessment Automated Vision Test Collection User Guide

Science.gov (United States)

2017-05-15

AFRL-SA-WP-SR-2017-0012 Operational Based Vision Assessment Automated Vision Test Collection User Guide Elizabeth Shoda, Alex...June 2015 – May 2017 4. TITLE AND SUBTITLE Operational Based Vision Assessment Automated Vision Test Collection User Guide 5a. CONTRACT NUMBER... automated vision tests , or AVT. Development of the AVT was required to support threshold-level vision testing capability needed to investigate the

Integral Monitored Retrievable Storage (MRS) Facility conceptual design report

International Nuclear Information System (INIS)

1985-09-01

In April 1985, the Department of Energy (DOE) selected the Clinch River site as its preferred site for the construction and operation of the monitored retrievable storage (MRS) facility (USDOE, 1985). In support of the DOE MRS conceptual design activity, available data describing the site have been gathered and analyzed. A composite geotechnical description of the Clinch River site has been developed and is presented herein. This report presents Clinch River site description data in the following sections: general site description, surface hydrologic characteristics, groundwater characteristics, geologic characteristics, vibratory ground motion, surface faulting, stability of subsurface materials, slope stability, and references. 48 refs., 35 figs., 6 tabs

Rethinking the MRS

International Nuclear Information System (INIS)

Colglazier, E.W.

1989-01-01

In this paper various options for utilizing monitored retrievable storage of civilian spent fuel have been compared using the criteria of maximizing the likelihood of implementing successfully a comprehensive U.S. nuclear waste management system (taking into account scientific and institutional uncertainties) and minimizing the costs, risks, and other impacts. The option that appears to be most robust for dealing with the key uncertainties has two components: an integrated management system that maximizes dry-storage at reactors using dual purpose casks and shipment via dedicated trains and a more experimental approach to the development of the repository at Yucca Mountain and authorization of an unconstrained MRS facility on the Nevada Test Site

1H-MRS is useful to reinforce the suspicion of primary central nervous system lymphoma prior to surgery

International Nuclear Information System (INIS)

Mora, Paloma; Majos, Carles; Aguilera, Carles; Castaner, Sara; Sanchez, Juan J.; Gabarros, Andreu; Muntane, Amadeo; Arus, Carles

2014-01-01

To assess whether 1 H-MRS may be useful to reinforce the radiological suspicion of PCNSL. In this retrospective study, we included 546 patients with untreated brain tumours in which single-voxel spectroscopy at TE 30 ms and 136 ms had been performed. The patients were split into two subgroups: ''training set'' and ''test set.'' Differences between PCNSL and five other types of intracranial tumours were assessed in the test set of patients using the Mann-Whitney U nonparametric test and cut-off values for pair-wise comparisons defined by constructing receiver operating characteristic curves. These thresholds were used to construct classifiers for binary comparison between PCNSL and non-PCNSL. The performance of the obtained classifiers was assessed in the independent test set of patients. Significant differences were found between PCNSL and the other groups evaluated. All bilateral comparisons performed in the test set obtained accuracy values above 70 % (71-89 %). Lipids were found to be useful to discriminate between PCNSL and glioblastoma/metastasis at short TE. Myo-inositol resonance was found to be very consistent for discriminating between PCNSL and astrocytomas at short TE. 1 H-MRS is useful to reinforce diagnostic suspicion of PCNSL on MRI. (orig.)

ApoE4 effects on automated diagnostic classifiers for mild cognitive impairment and Alzheimer's disease

Directory of Open Access Journals (Sweden)

Liana G. Apostolova

2014-01-01

Full Text Available Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD. No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC, mild cognitive impairment (MCI and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aβ, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates

Automation-assisted cervical cancer screening in manual liquid-based cytology with hematoxylin and eosin staining.

Science.gov (United States)

Zhang, Ling; Kong, Hui; Ting Chin, Chien; Liu, Shaoxiong; Fan, Xinmin; Wang, Tianfu; Chen, Siping

2014-03-01

Current automation-assisted technologies for screening cervical cancer mainly rely on automated liquid-based cytology slides with proprietary stain. This is not a cost-efficient approach to be utilized in developing countries. In this article, we propose the first automation-assisted system to screen cervical cancer in manual liquid-based cytology (MLBC) slides with hematoxylin and eosin (H&E) stain, which is inexpensive and more applicable in developing countries. This system consists of three main modules: image acquisition, cell segmentation, and cell classification. First, an autofocusing scheme is proposed to find the global maximum of the focus curve by iteratively comparing image qualities of specific locations. On the autofocused images, the multiway graph cut (GC) is performed globally on the a* channel enhanced image to obtain cytoplasm segmentation. The nuclei, especially abnormal nuclei, are robustly segmented by using GC adaptively and locally. Two concave-based approaches are integrated to split the touching nuclei. To classify the segmented cells, features are selected and preprocessed to improve the sensitivity, and contextual and cytoplasm information are introduced to improve the specificity. Experiments on 26 consecutive image stacks demonstrated that the dynamic autofocusing accuracy was 2.06 μm. On 21 cervical cell images with nonideal imaging condition and pathology, our segmentation method achieved a 93% accuracy for cytoplasm, and a 87.3% F-measure for nuclei, both outperformed state of the art works in terms of accuracy. Additional clinical trials showed that both the sensitivity (88.1%) and the specificity (100%) of our system are satisfyingly high. These results proved the feasibility of automation-assisted cervical cancer screening in MLBC slides with H&E stain, which is highly desirable in community health centers and small hospitals. © 2013 International Society for Advancement of Cytometry.

Lineshape estimation for magnetic resonance spectroscopy (MRS) signals: self-deconvolution revisited

International Nuclear Information System (INIS)

Sima, D M; Garcia, M I Osorio; Poullet, J; Van Huffel, S; Suvichakorn, A; Antoine, J-P; Van Ormondt, D

2009-01-01

Magnetic resonance spectroscopy (MRS) is an effective diagnostic technique for monitoring biochemical changes in an organism. The lineshape of MRS signals can deviate from the theoretical Lorentzian lineshape due to inhomogeneities of the magnetic field applied to patients and to tissue heterogeneity. We call this deviation a distortion and study the self-deconvolution method for automatic estimation of the unknown lineshape distortion. The method is embedded within a time-domain metabolite quantitation algorithm for short-echo-time MRS signals. Monte Carlo simulations are used to analyze whether estimation of the unknown lineshape can improve the overall quantitation result. We use a signal with eight metabolic components inspired by typical MRS signals from healthy human brain and allocate special attention to the step of denoising and spike removal in the self-deconvolution technique. To this end, we compare several modeling techniques, based on complex damped exponentials, splines and wavelets. Our results show that self-deconvolution performs well, provided that some unavoidable hyper-parameters of the denoising methods are well chosen. Comparison of the first and last iterations shows an improvement when considering iterations instead of a single step of self-deconvolution

Operator-based metric for nuclear operations automation assessment

Energy Technology Data Exchange (ETDEWEB)

Zacharias, G.L.; Miao, A.X.; Kalkan, A. [Charles River Analytics Inc., Cambridge, MA (United States)] [and others

1995-04-01

Continuing advances in real-time computational capabilities will support enhanced levels of smart automation and AI-based decision-aiding systems in the nuclear power plant (NPP) control room of the future. To support development of these aids, we describe in this paper a research tool, and more specifically, a quantitative metric, to assess the impact of proposed automation/aiding concepts in a manner that can account for a number of interlinked factors in the control room environment. In particular, we describe a cognitive operator/plant model that serves as a framework for integrating the operator`s information-processing capabilities with his procedural knowledge, to provide insight as to how situations are assessed by the operator, decisions made, procedures executed, and communications conducted. Our focus is on the situation assessment (SA) behavior of the operator, the development of a quantitative metric reflecting overall operator awareness, and the use of this metric in evaluating automation/aiding options. We describe the results of a model-based simulation of a selected emergency scenario, and metric-based evaluation of a range of contemplated NPP control room automation/aiding options. The results demonstrate the feasibility of model-based analysis of contemplated control room enhancements, and highlight the need for empirical validation.

Reinforcement Learning Based Artificial Immune Classifier

Directory of Open Access Journals (Sweden)

Mehmet Karakose

2013-01-01

Full Text Available One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.

In vivo MRS metabolite quantification using genetic optimization

Science.gov (United States)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; van Ormondt, D.; Graveron-Demilly, D.

2011-11-01

The in vivo quantification of metabolites' concentrations, revealed in magnetic resonance spectroscopy (MRS) spectra, constitutes the main subject under investigation in this work. Significant contributions based on artificial intelligence tools, such as neural networks (NNs), with good results have been presented lately but have shown several drawbacks, regarding their quantification accuracy under difficult conditions. A general framework that encounters the quantification procedure as an optimization problem, which is solved using a genetic algorithm (GA), is proposed in this paper. Two different lineshape models are examined, while two GA configurations are applied on artificial data. Moreover, the introduced quantification technique deals with metabolite peaks' overlapping, a considerably difficult situation occurring under real conditions. Appropriate experiments have proved the efficiency of the introduced methodology, in artificial MRS data, by establishing it as a generic metabolite quantification procedure.

In vivo MRS metabolite quantification using genetic optimization

International Nuclear Information System (INIS)

Papakostas, G A; Mertzios, B G; Karras, D A; Van Ormondt, D; Graveron-Demilly, D

2011-01-01

The in vivo quantification of metabolites' concentrations, revealed in magnetic resonance spectroscopy (MRS) spectra, constitutes the main subject under investigation in this work. Significant contributions based on artificial intelligence tools, such as neural networks (NNs), with good results have been presented lately but have shown several drawbacks, regarding their quantification accuracy under difficult conditions. A general framework that encounters the quantification procedure as an optimization problem, which is solved using a genetic algorithm (GA), is proposed in this paper. Two different lineshape models are examined, while two GA configurations are applied on artificial data. Moreover, the introduced quantification technique deals with metabolite peaks' overlapping, a considerably difficult situation occurring under real conditions. Appropriate experiments have proved the efficiency of the introduced methodology, in artificial MRS data, by establishing it as a generic metabolite quantification procedure

Long-term operation of a multi-channel cosmic muon system based on scintillation counters with MRS APD light readout

CERN Document Server

Akindinov, A.; Grigoriev, E.; Grishuk, Yu.; Kuleshov, S.; Mal'kevich, D.; Martemiyanov, A.; Nedosekin, A.; Ryabinin, M.; Voloshin, K.

2009-01-01

A Cosmic Ray Test Facility (CRTF) is the first large-scale implementation of a scintillation triggering system based on a new scintillation technique known as START. In START, the scintillation light is collected and transported by WLS optical fibers, while light detection is performed by pairs of avalanche photodiodes with the Metal-Resistor-Semiconductor structure operated in the Geiger mode (MRS APD). START delivers 100% efficiency of cosmic muon detection, while its intrinsic noise level is less than 10^{-2} Hz. CRTF, consisting of 160 START channels, has been continuously operated by the ALICE TOF collaboration for more than 25 000 hours, and has demonstrated a high level of stability. Fewer than 10% of MRS APDs had to be replaced during this period.

Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

Directory of Open Access Journals (Sweden)

Bogdan Gliwa

2011-01-01

Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

Automated audiometry using apple iOS-based application technology.

Science.gov (United States)

Foulad, Allen; Bui, Peggy; Djalilian, Hamid

2013-11-01

The aim of this study is to determine the feasibility of an Apple iOS-based automated hearing testing application and to compare its accuracy with conventional audiometry. Prospective diagnostic study. Setting Academic medical center. An iOS-based software application was developed to perform automated pure-tone hearing testing on the iPhone, iPod touch, and iPad. To assess for device variations and compatibility, preliminary work was performed to compare the standardized sound output (dB) of various Apple device and headset combinations. Forty-two subjects underwent automated iOS-based hearing testing in a sound booth, automated iOS-based hearing testing in a quiet room, and conventional manual audiometry. The maximum difference in sound intensity between various Apple device and headset combinations was 4 dB. On average, 96% (95% confidence interval [CI], 91%-100%) of the threshold values obtained using the automated test in a sound booth were within 10 dB of the corresponding threshold values obtained using conventional audiometry. When the automated test was performed in a quiet room, 94% (95% CI, 87%-100%) of the threshold values were within 10 dB of the threshold values obtained using conventional audiometry. Under standardized testing conditions, 90% of the subjects preferred iOS-based audiometry as opposed to conventional audiometry. Apple iOS-based devices provide a platform for automated air conduction audiometry without requiring extra equipment and yield hearing test results that approach those of conventional audiometry.

Development and Evaluation of an Automated, Home-Based, Electronic Questionnaire for Detecting COPD Exacerbations

Directory of Open Access Journals (Sweden)

Francisco de B. Velazquez-Peña

2015-01-01

Full Text Available Collaboration between patients and their medical and technical experts enabled the development of an automated questionnaire for the early detection of COPD exacerbations (AQCE. The questionnaire consisted of fourteen questions and was implemented on a computer system for use by patients at home in an un-supervised environment. Psychometric evaluation was conducted after a 6-month field trial. Fifty-two patients were involved in the development of the questionnaire. Reproducibility was studied using 19 patients (ICC = 0.94. Sixteen out of the 19 subjects started the 6 month-field trial with the computer application. Cronbach’s alpha of 0.81 was achieved. In the concurrent validity analysis, a correlation of 0.80 (p = 0.002 with the CCQ was reported. The results suggest that AQCE is a valid and reliable questionnaire, showing that an automated home-based electronic questionnaire may enable early detection of exacerbations of COPD.

Interfacing the existing cask fleet with the MRS

International Nuclear Information System (INIS)

Doman, J.W.; Hahn, R.E.

1992-01-01

This paper reports that the Department of Energy (DOE) is considering the possibility of using the existing fleet of casks to achieve spent fuel receipt at the Monitored Retrievable Storage (MRS) facility. The existing cask fleet includes the NLI-1/2, the NAC-LWT, the TN-8 (and TN-8L), the TN-9, and the IF-300 casks. Other casks may be available, but their status is not certain. Use of the existing cask fleet at the MRS places additional design requirements on the system, and specifically affects the cask-to-MRS interface. The decision to use the existing cask fleet also places additional demands on training needs and operator certification, and the configuration management system. Some existing cask designs may not be able to mate with a bottom opening hot cell MRS. Use of the existing cask fleet also greatly increases the number of shipments that must be received, to the point that a facility larger than originally envisioned may be required

A systems biology-based classifier for hepatocellular carcinoma diagnosis.

Directory of Open Access Journals (Sweden)

Yanqiong Zhang

Full Text Available AIM: The diagnosis of hepatocellular carcinoma (HCC in the early stage is crucial to the application of curative treatments which are the only hope for increasing the life expectancy of patients. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with HCC progression. However, those marker sets shared few genes in common and were poorly validated using independent data. Therefore, we developed a systems biology based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC diagnosis. METHODS AND RESULTS: In the Oncomine platform, genes differentially expressed in HCC tissues relative to their corresponding normal tissues were filtered by a corrected Q value cut-off and Concept filters. The identified genes that are common to different microarray datasets were chosen as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, an HCC diagnostic classifier was constructed by Partial Least Squares modeling based on the microarray gene expression data of the hub genes. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.88∼92.71% and area under ROC curve (approximating 1.0, and that the network topological features integrated into this classifier contribute greatly to improving the predictive performance. Furthermore, it has been demonstrated that this modeling strategy is not only applicable to HCC, but also to other cancers. CONCLUSION: Our analysis suggests that the systems biology-based classifier that combines the differential gene expression and topological features of human protein interaction network may enhance the diagnostic performance of HCC classifier.

Confirmation of MRS/MPC transfer facility sizing using simulation modeling

International Nuclear Information System (INIS)

Houston, E.S.; Hadley, J.D.

1994-01-01

The Nuclear Waste Policy Act (NWPA) of 1982, as amended, requires the Department of Energy to begin receiving spent nuclear fuel (SNF) from utilities in January 1998. A repository will not be completed in time for the scheduled receipt of SNF. A Monitored Retrievable Storage (MRS) Facility is therefore a feasible solution to bridge the gap between the 1998 date for fuel acceptance and the startup of the repository. SNF will be stored temporarily at the MRS and later retrieved from storage and shipped to the repository. To simplify fuel handling and to standardize components, the multi-purpose canister (MPC) concept was investigated. The MPC would be a sealed, metallic canister containing multiple SNF assemblies in a dry inert environment. MPCs would be placed into different overpacks for transportation, storage, and disposal at the repository. The MRS transfer facility MPC and SNF throughput requirements, assumptions, and operating concepts were used to initially determine the size of the facility and the major equipment contained within the facility. This initial estimate was based on simplified calculation techniques. The adequacy of the design configurations were then confirmed using SLAM simulation modeling software. Modeling incorporates uncertainties in task durations, the effects of equipment reliability, availability of personnel and equipment, and system breakdowns. This paper describes how the model was developed and how it is used to verify the transfer facility size. It also illustrates how problems with the facility design, operational concepts, and staffing are identified with the results of the model

PREFACE: E-MRS 2012 Spring Meeting, Symposium M: More than Moore: Novel materials approaches for functionalized Silicon based Microelectronics

Science.gov (United States)

Wenger, Christian; Fompeyrine, Jean; Vallée, Christophe; Locquet, Jean-Pierre

2012-12-01

More than Moore explores a new area of Silicon based microelectronics, which reaches beyond the boundaries of conventional semiconductor applications. Creating new functionality to semiconductor circuits, More than Moore focuses on motivating new technological possibilities. In the past decades, the main stream of microelectronics progresses was mainly powered by Moore's law, with two focused development arenas, namely, IC miniaturization down to nano scale, and SoC based system integration. While the microelectronics community continues to invent new solutions around the world to keep Moore's law alive, there is increasing momentum for the development of 'More than Moore' technologies which are based on silicon technologies but do not simply scale with Moore's law. Typical examples are RF, Power/HV, Passives, Sensor/Actuator/MEMS or Bio-chips. The More than Moore strategy is driven by the increasing social needs for high level heterogeneous system integration including non-digital functions, the necessity to speed up innovative product creation and to broaden the product portfolio of wafer fabs, and the limiting cost and time factors of advanced SoC development. It is believed that More than Moore will add value to society on top of and beyond advanced CMOS with fast increasing marketing potentials. Important key challenges for the realization of the 'More than Moore' strategy are: perspective materials for future THz devices materials systems for embedded sensors and actuators perspective materials for epitaxial approaches material systems for embedded innovative memory technologies development of new materials with customized characteristics The Hot topics covered by the symposium M (More than Moore: Novel materials approaches for functionalized Silicon based Microelectronics) at E-MRS 2012 Spring Meeting, 14-18 May 2012 have been: development of functional ceramics thin films New dielectric materials for advanced microelectronics bio- and CMOS compatible

Evaluation of storage/transportation options to support criteria development for the Phase I MRS

International Nuclear Information System (INIS)

Sorenson, K.B.; Brown, N.N.; Bennett, P.C.; Lake, W.

1991-01-01

The DOE's Office of Civilian Waste Management (OCRWM) plans to develop an interim storage facility to enable acceptance of spent fuel in 1998. It is estimated that this interim storage facility would be needed for about two years. A Monitored Retrievable Storage (MRS) facility is anticipated in 2000 and a repository in 2010. Acceptance and transport of spent fuel by DOE/OCRWM in 1998 will require an operating transportation system. Because this interim storage facility is not yet defined, development of an optimally compatible transportation system is not a certainty. In order to assure a transport capability for 1998 acceptance of spent fuel, it was decided that the OCRWM transportation program had to identify likely options for an interim storage facility, including identification of the components needed for compatibility between likely interim storage facility options and transportation. Primary attention was given to existing hardware, although conceptual designs were also considered. A systems-based probabilistic decision model was suggested by Sandia National Labs. and accepted by DOE/OCRWM's transportation program. Performance of the evaluation task involved several elements of the transportation program. This paper describes the decision model developed to accomplish this task, along with some of the results and conclusions

Scintillation counter with MRS APD light readout

International Nuclear Information System (INIS)

Akindinov, A.; Bondarenko, G.; Golovin, V.; Grigoriev, E.; Grishuk, Yu.; Mal'kevich, D.; Martemiyanov, A.; Ryabinin, M.; Smirnitskiy, A.; Voloshin, K.

2005-01-01

START, a high-efficiency and low-noise scintillation detector for ionizing particles, was developed for the purpose of creating a high-granular system for triggering cosmic muons. Scintillation light in START is detected by MRS APDs (Avalanche Photo-Diodes with Metal-Resistance-Semiconductor Structure), operated in the Geiger mode, which have 1mm 2 sensitive areas. START is assembled from a 15x15x1cm 3 scintillating plastic plate, two MRS APDs and two pieces of wavelength-shifting optical fiber stacked in circular coils inside the plastic. The front-end electronic card is mounted directly on the detector. Tests with START have confirmed its operational consistency, over 99% efficiency of MIP registration and good homogeneity. START demonstrates a low intrinsic noise of about 10 -2 Hz. If these detectors are to be mass-produced, the cost of a mosaic array of STARTs is estimated at a moderate level of 2-3kUSD/m 2

MRS Action Plan Task B report: Analyses of alternative designs and operating approaches for a Monitored Retrievable Storage Facility

International Nuclear Information System (INIS)

Woods, W.D.; Jowdy, A.K.; Keehn, C.H.; Gale, R.M.; Smith, R.I.

1988-12-01

The Nuclear Waste Policy Amendments Act (NWPAA) instituted a number of changes in the DOE commercial nuclear waste management system. After passage of the Act, the DOE initiated a number of systems studies to reevaluate the role of Monitored Retrievable Storage (MRS) within the federal waste management system. This report summarizes the results of a study to determine the schedules and costs of developing those MRS facilities needed under a number of scenarios, with differing functions allocated to the MRS and/or different spent fuel acceptance schedules. Nine cases were defined for the system study, seven of which included an MRS Facility. The study cases or scenarios evaluated varied relative to the specific functions to be performed at the MRS. The scenarios ranged in magnitude from storage and shipment of bare, intact spent fuel to consolidating the spent fuel into repository emplacement containers prior to storage and shipment. Each scenario required specific modifications to be made to the design developed for the MRS proposal to Congress (the Conceptual Design Report). 41 figs., 326 tabs

NASA space station automation: AI-based technology review

Science.gov (United States)

Firschein, O.; Georgeff, M. P.; Park, W.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

1985-01-01

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures.

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

International Nuclear Information System (INIS)

Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

2007-01-01

Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development

Studies on hippocampal sclerosis by 1H MRS and MRI

International Nuclear Information System (INIS)

Qi Jing; Du Xiangke; Luan Guoming; Wang Dehang

2000-01-01

Objective: To determine the relative utility of 1 H MRS and MRI for pre-surgical diagnosis of hippocampal sclerosis by the study on metabolic abnormalities and anatomical alterations in the brain of patients with temporal lobe epilepsy (TLE). Methods: 1 H MRS and MRI were performed on 8 patients with pathologically confirmed hippocampal sclerosis and 8 healthy volunteers on 2.0 T 1 H MRS/MRI system. The values of NAA, Cr and Cho were calculated by integration of their peaks and the ratios of NAA/Cr, NAA/(Cr + Cho), and Cho/Cr were measured. The volumes of both hippocampal formations in every case were observed and the differences of hippocampal formation (DHF) were analyzed. Results: The ratios of NAA/Cr, NAA/(Cr + Cho), and Cho/Cr in ipsilateral side were 0.55, 1.77 and 1.38, and in control subjects were 0.77, 1.38 and 1.06 separately. The ratios of NAA/Cr and NAA/(Cr + Cho) were decreased on ipsilateral side (t = 2.15, 4.83 separately, P 1 H MRS and MRI, seven of eight cases could be lateralized. Conclusion: 1 H MRS is sensitive to the diagnosis of neuron abnormality and coincident well with the pathological results 1 H MRS and MRI correctly lateralize most patients with hippocampal sclerosis and complement each other in final lateralization. The combination of 1 H MRS and MRI can provide useful information for pre-surgical diagnosis of hippocampal sclerosis

Vision-based obstacle recognition system for automated lawn mower robot development

Science.gov (United States)

Mohd Zin, Zalhan; Ibrahim, Ratnawati

2011-06-01

Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

Automated Clinical Assessment from Smart home-based Behavior Data

Science.gov (United States)

Dawadi, Prafulla Nath; Cook, Diane Joyce; Schmitter-Edgecombe, Maureen

2016-01-01

Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behaviour in the home and predicting standard clinical assessment scores of the residents. To accomplish this goal, we propose a Clinical Assessment using Activity Behavior (CAAB) approach to model a smart home resident’s daily behavior and predict the corresponding standard clinical assessment scores. CAAB uses statistical features that describe characteristics of a resident’s daily activity performance to train machine learning algorithms that predict the clinical assessment scores. We evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years using prediction and classification-based experiments. In the prediction-based experiments, we obtain a statistically significant correlation (r = 0.72) between CAAB-predicted and clinician-provided cognitive assessment scores and a statistically significant correlation (r = 0.45) between CAAB-predicted and clinician-provided mobility scores. Similarly, for the classification-based experiments, we find CAAB has a classification accuracy of 72% while classifying cognitive assessment scores and 76% while classifying mobility scores. These prediction and classification results suggest that it is feasible to predict standard clinical scores using smart home sensor data and learning-based data analysis. PMID:26292348

A sensor-based automation system for handling nuclear materials

International Nuclear Information System (INIS)

Drotning, W.; Kimberly, H.; Wapman, W.; Darras, D.

1997-01-01

An automated system is being developed for handling large payloads of radioactive nuclear materials in an analytical laboratory. The automation system performs unpacking and repacking of payloads from shipping and storage containers, and delivery of the payloads to the stations in the laboratory. The system uses machine vision and force/torque sensing to provide sensor-based control of the automation system in order to enhance system safety, flexibility, and robustness, and achieve easy remote operation. The automation system also controls the operation of the laboratory measurement systems and the coordination of them with the robotic system. Particular attention has been given to system design features and analytical methods that provide an enhanced level of operational safety. Independent mechanical gripper interlock and tool release mechanisms were designed to prevent payload mishandling. An extensive Failure Modes and Effects Analysis of the automation system was developed as a safety design analysis tool

Monitored retrievable storage (MRS) facility and salt repository integration: Engineering study report

International Nuclear Information System (INIS)

1987-07-01

This MRS Facility and Salt Repository Integration Study evaluates the impacts of an integrated MRS/Salt Repository Waste Management System on the Salt Repository Surface facilities' design, operations, cost, and schedule. Eight separate cases were studied ranging from a two phase repository design with no MRS facility to a design in which the repository only received package waste from the MRS facility for emplacement. The addition of the MRS facility to the Waste Management System significantly reduced the capital cost of the salt repository. All but one of the cases studied were capable of meeting the waste acceptance data. The reduction in the size and complexity of the Salt Repository waste handling building with the integration of the MRS facility reduces the design and operating staff requirements. 7 refs., 35 figs., 43 tabs

On an efficient modification of singular value decomposition using independent component analysis for improved MRS denoising and quantification

International Nuclear Information System (INIS)

Stamatopoulos, V G; Karras, D A; Mertzios, B G

2009-01-01

An efficient modification of singular value decomposition (SVD) is proposed in this paper aiming at denoising and more importantly at quantifying more accurately the statistically independent spectra of metabolite sources in magnetic resonance spectroscopy (MRS). Although SVD is known in MRS applications and several efficient algorithms exist for estimating SVD summation terms in which the raw MRS data are analyzed, however, it would be more beneficial for such an analysis if techniques with the ability to estimate statistically independent spectra could be employed. SVD is known to separate signal and noise subspaces but it assumes orthogonal properties for the components comprising signal subspace, which is not always the case, and might impose heavy constraints for the MRS case. A much more relaxing constraint would be to assume statistically independent components. Therefore, a modification of the main methodology incorporating techniques for calculating the assumed statistically independent spectra is proposed by applying SVD on the MRS spectrogram through application of the short time Fourier transform (STFT). This approach is based on combining SVD on STFT spectrogram followed by an iterative application of independent component analysis (ICA). Moreover, it is shown that the proposed methodology combined with a regression analysis would lead to improved quantification of the MRS signals. An experimental study based on synthetic MRS signals has been conducted to evaluate the herein proposed methodologies. The results obtained have been discussed and it is shown to be quite promising

How large a training set is needed to develop a classifier for microarray data?

Science.gov (United States)

Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

2008-01-01

A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

A semi-automated method for bone age assessment using cervical vertebral maturation.

Science.gov (United States)

Baptista, Roberto S; Quaglio, Camila L; Mourad, Laila M E H; Hummel, Anderson D; Caetano, Cesar Augusto C; Ortolani, Cristina Lúcia F; Pisa, Ivan T

2012-07-01

To propose a semi-automated method for pattern classification to predict individuals' stage of growth based on morphologic characteristics that are described in the modified cervical vertebral maturation (CVM) method of Baccetti et al. A total of 188 lateral cephalograms were collected, digitized, evaluated manually, and grouped into cervical stages by two expert examiners. Landmarks were located on each image and measured. Three pattern classifiers based on the Naïve Bayes algorithm were built and assessed using a software program. The classifier with the greatest accuracy according to the weighted kappa test was considered best. The classifier showed a weighted kappa coefficient of 0.861 ± 0.020. If an adjacent estimated pre-stage or poststage value was taken to be acceptable, the classifier would show a weighted kappa coefficient of 0.992 ± 0.019. Results from this study show that the proposed semi-automated pattern classification method can help orthodontists identify the stage of CVM. However, additional studies are needed before this semi-automated classification method for CVM assessment can be implemented in clinical practice.

Development and validation of an automated, microscopy-based method for enumeration of groups of intestinal bacteria

NARCIS (Netherlands)

Jansen, GJ; Wildeboer-Veloo, ACM; Tonk, RHJ; Franks, AH; Welling, G

An automated microscopy-based method using fluorescently labelled 16S rRNA-targeted oligonucleotide probes directed against the predominant groups of intestinal bacteria was developed and validated. The method makes use of the Leica 600HR. image analysis system, a Kodak MegaPlus camera model 1.4 and

Model-based automated testing of critical PLC programs.

CERN Document Server

Fernández Adiego, B; Tournier, J-C; González Suárez, V M; Bliudze, S

2014-01-01

Testing of critical PLC (Programmable Logic Controller) programs remains a challenging task for control system engineers as it can rarely be automated. This paper proposes a model based approach which uses the BIP (Behavior, Interactions and Priorities) framework to perform automated testing of PLC programs developed with the UNICOS (UNified Industrial COntrol System) framework. This paper defines the translation procedure and rules from UNICOS to BIP which can be fully automated in order to hide the complexity of the underlying model from the control engineers. The approach is illustrated and validated through the study of a water treatment process.

Monitoring of aquifer pump tests with Magnetic Resonance Sounding (MRS)

DEFF Research Database (Denmark)

Herckenrath, Daan; Auken, Esben; Bauer-Gottwein, Peter

2009-01-01

Magnetic Resonance Sounding (MRS) can provide valuable data to constrain and calibrate groundwater flow and transport models. With this non-invasive geophysical technique, field measurements of water content and hydraulic conductivities can be obtained. We developed a hydrogeophyiscal forward...

Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm

Directory of Open Access Journals (Sweden)

Ricardo Andres Pizarro

2016-12-01

Full Text Available High-resolution three-dimensional magnetic resonance imaging (3D-MRI is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM algorithm in the quality assessment of structural brain images, using global and region of interest (ROI automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

Science.gov (United States)

Pizarro, Ricardo A; Cheng, Xi; Barnett, Alan; Lemaitre, Herve; Verchinski, Beth A; Goldman, Aaron L; Xiao, Ena; Luo, Qian; Berman, Karen F; Callicott, Joseph H; Weinberger, Daniel R; Mattay, Venkata S

2016-01-01

High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

Quantum ensembles of quantum classifiers.

Science.gov (United States)

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

{sup 1}H-MRS is useful to reinforce the suspicion of primary central nervous system lymphoma prior to surgery

Energy Technology Data Exchange (ETDEWEB)

Mora, Paloma [Hospital Universitari de Bellvitge, Department of Radiology, L' Hospitalet de Llobregat (Spain); Majos, Carles; Aguilera, Carles [Hospital Universitari de Bellvitge, Department of Radiology, Institut de Diagnostic per la Imatge (IDI), Centre Bellvitge, L' Hospitalet de Llobregat (Spain); Centro de Investigacion en Red en Bioingenieria, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Valles (Spain); Castaner, Sara; Sanchez, Juan J. [Hospital Universitari de Bellvitge, Department of Radiology, Institut de Diagnostic per la Imatge (IDI), Centre Bellvitge, L' Hospitalet de Llobregat (Spain); Gabarros, Andreu [Hospital Universitari de Bellvitge, Department of Neurosurgery, L' Hospitalet de Llobregat (Spain); Muntane, Amadeo [Hospital Universitari de Bellvitge, Department of Radiology, L' Hospitalet de Llobregat (Spain); Arus, Carles [Centro de Investigacion en Red en Bioingenieria, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Valles (Spain); Universitat Autonoma de Barcelona, Department de Bioquimica i Biologia Molecular, Unitat de Bioquimica de Biociencies, Cerdanyola del Valles (Spain); Universitat Autonoma de Barcelona, Institut de Biotecnologia i de Biomedicina, Cerdanyola del Valles (Spain)

2014-11-15

To assess whether {sup 1}H-MRS may be useful to reinforce the radiological suspicion of PCNSL. In this retrospective study, we included 546 patients with untreated brain tumours in which single-voxel spectroscopy at TE 30 ms and 136 ms had been performed. The patients were split into two subgroups: ''training set'' and ''test set.'' Differences between PCNSL and five other types of intracranial tumours were assessed in the test set of patients using the Mann-Whitney U nonparametric test and cut-off values for pair-wise comparisons defined by constructing receiver operating characteristic curves. These thresholds were used to construct classifiers for binary comparison between PCNSL and non-PCNSL. The performance of the obtained classifiers was assessed in the independent test set of patients. Significant differences were found between PCNSL and the other groups evaluated. All bilateral comparisons performed in the test set obtained accuracy values above 70 % (71-89 %). Lipids were found to be useful to discriminate between PCNSL and glioblastoma/metastasis at short TE. Myo-inositol resonance was found to be very consistent for discriminating between PCNSL and astrocytomas at short TE. {sup 1}H-MRS is useful to reinforce diagnostic suspicion of PCNSL on MRI. (orig.)

Case base classification on digital mammograms: improving the performance of case base classifier

Science.gov (United States)

Raman, Valliappan; Then, H. H.; Sumari, Putra; Venkatesa Mohan, N.

2011-10-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. The aim of the research presented here is in twofold. First stage of research involves machine learning techniques, which segments and extracts features from the mass of digital mammograms. Second level is on problem solving approach which includes classification of mass by performance based case base classifier. In this paper we build a case-based Classifier in order to diagnose mammographic images. We explain different methods and behaviors that have been added to the classifier to improve the performance of the classifier. Currently the initial Performance base Classifier with Bagging is proposed in the paper and it's been implemented and it shows an improvement in specificity and sensitivity.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

Directory of Open Access Journals (Sweden)

Fabrício R. Silva

2013-06-01

Full Text Available PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs for glaucoma diagnosis using Spectral Domain OCT (SD-OCT and standard automated perimetry (SAP. METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP and retinal nerve fiber layer (RNFL imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California. Receiver operating characteristic (ROC curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG, Naive-Bayes (NB, Multilayer Perceptron (MLP, Radial Basis Function (RBF, Random Forest (RAN, Ensemble Selection (ENS, Classification Tree (CTREE, Ada Boost M1(ADA,Support Vector Machine Linear (SVML and Support Vector Machine Gaussian (SVMG. Areas under the receiver operating characteristic curves (aROC obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE to 0.946 (RAN.The best OCT+SAP aROC obtained with RAN (0.946 was significantly larger the best single OCT parameter (p<0.05, but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19. CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Use of annotated outlines to prepare guidance for license applications for the MRS and MGDS

International Nuclear Information System (INIS)

Roberts, J.; Griffin, W.R.

1992-01-01

This paper reports that the Office of Civilian Radioactive Waste Management (OCRWM) has embarked on an aggressive program to develop guidance for preparation of the License Applications for the Mined Geological Disposal System (MGDS) and Monitored Retrievable Storage (MRS). The endeavor is a team effort that will utilize personnel and funding from the Office of Systems and Compliance at DOE Headquarters, the MRS Project (i.e., DOE Office of Storage and Transportation) and the Yucca Mountain Project (i.e., DOE Office of Geologic Disposal). The endeavor was initiated in the Spring of 1991. It will continue via an iterative process until License Applications are completed for the MRS and MGDS projects

Fusion of classifiers for REIS-based detection of suspicious breast lesions

Science.gov (United States)

Lederman, Dror; Wang, Xingwei; Zheng, Bin; Sumkin, Jules H.; Tublin, Mitchell; Gur, David

2011-03-01

After developing a multi-probe resonance-frequency electrical impedance spectroscopy (REIS) system aimed at detecting women with breast abnormalities that may indicate a developing breast cancer, we have been conducting a prospective clinical study to explore the feasibility of applying this REIS system to classify younger women (breast cancer. The system comprises one central probe placed in contact with the nipple, and six additional probes uniformly distributed along an outside circle to be placed in contact with six points on the outer breast skin surface. In this preliminary study, we selected an initial set of 174 examinations on participants that have completed REIS examinations and have clinical status verification. Among these, 66 examinations were recommended for biopsy due to findings of a highly suspicious breast lesion ("positives"), and 108 were determined as negative during imaging based procedures ("negatives"). A set of REIS-based features, extracted using a mirror-matched approach, was computed and fed into five machine learning classifiers. A genetic algorithm was used to select an optimal subset of features for each of the five classifiers. Three fusion rules, namely sum rule, weighted sum rule and weighted median rule, were used to combine the results of the classifiers. Performance evaluation was performed using a leave-one-case-out cross-validation method. The results indicated that REIS may provide a new technology to identify younger women with higher than average risk of having or developing breast cancer. Furthermore, it was shown that fusion rule, such as a weighted median fusion rule and a weighted sum fusion rule may improve performance as compared with the highest performing single classifier.

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

Science.gov (United States)

Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

2018-01-01

A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

An automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images

International Nuclear Information System (INIS)

Park, Seong Hoon; Seo, Joon Beom; Kim, Nam Kug; Lee, Young Kyung; Kim, Song Soo; Chae, Eun Jin; Lee, June Goo

2007-01-01

To develop an automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images, and to evaluate the accuracy and usefulness of the system. For textural analysis, histogram features, gradient features, run length encoding, and a co-occurrence matrix were employed. A Bayesian classifier was used for automated classification. The images (image number n = 256) were selected from the HRCT images obtained from 17 healthy subjects (n = 67), 26 patients with bronchiolitis obliterans (n = 70), 28 patients with mild centrilobular emphysema (n = 65), and 21 patients with panlobular emphysema or severe centrilobular emphysema (n = 63). An five-fold cross-validation method was used to assess the performance of the system. Class-specific sensitivities were analyzed and the overall accuracy of the system was assessed with kappa statistics. The sensitivity of the system for each class was as follows: normal lung 84.9%, bronchiolitis obliterans 83.8%, mild centrilobular emphysema 77.0%, and panlobular emphysema or severe centrilobular emphysema 95.8%. The overall performance for differentiating each disease and the normal lung was satisfactory with a kappa value of 0.779. An automated classification system for the differentiation between obstructive lung diseases based on the textural analysis of HRCT images was developed. The proposed system discriminates well between the various obstructive lung diseases and the normal lung

Siting of an MRS facility: identification of a geographic region that reduces transportation requirements

International Nuclear Information System (INIS)

Holter, G.M.; Braitman, J.L.

1985-04-01

The study reported here was undertaken as part of the site screening and evaluation activities for the Monitored Retrievable Storage (MRS) Program of the Office of Civilian Radioactive Waste Management (OCRWM), Department of Energy (DOE). Its primary purpose was to determine: the location and shape of a preferred geographic region within which locating an MRS facility would minimize total shipment miles for spent fuel transported through the MRS facility to a repository, and the sensitivity of the location and shape of this region and the reduction in total shipment miles to possible variations in waste management system logistics. As a result of this analysis, a geographic region has been identified which is preferred for siting an MRS facility. This region will be referred to as the preferred region in this study. Siting an MRS facility in the preferred region will limit total shipment miles (i.e., the total miles traveled for all shipments of spent fuel) to and from the MRS facility to within 20% of the lowest achievable. The region is preferred for a mixed truck/rail system of transport from reactors to the MRS facility. It is assumed that rail will be used to ship spent fuel from the MRS facility to a geologic repository for disposal. Siting an MRS facility in the preferred region will reduce total shipment miles for all currently considered system logistics options which include an MRS facility in the system. These options include: any first repository location, the possible range of spent fuel consolidation at the MRS, use of multi-cask or single-cask train shipments, use of current or future spent fuel transport casks, servicing only the first or both the first and second repositories, and shipment of fuel from western reactors either through the MRS facility or to a western facility (a second, smaller MRS facility or the first repository)

CT, MRI and MRS of Epstein-Barr virus infection: case report

Energy Technology Data Exchange (ETDEWEB)

Cecil, K.M.; Jones, B.V.; Hedlund, G.L. [Dept. of Radiology, Children' s Hospital Medical Center, Cincinnati, OH (United States); Williams, S. [Dept. of Neurology, Children' s Hospital Medical Center, Cincinnati, OH (United States)

2000-08-01

We report MRI and proton MR spectroscopy (MRS) findings in a 12-month-old girl with Epstein-Barr virus encephalitis. CT and MRI showed focal lesions in the basal ganglia. MRS of the lesions showed decreased N-acetyl aspartate and elevation of some amino acids, indicating an infectious rather than ischemic etiology. This case illustrates the use of MRS to narrow differential diagnosis. (orig.)

CT, MRI and MRS of Epstein-Barr virus infection: case report

International Nuclear Information System (INIS)

Cecil, K.M.; Jones, B.V.; Hedlund, G.L.; Williams, S.

2000-01-01

We report MRI and proton MR spectroscopy (MRS) findings in a 12-month-old girl with Epstein-Barr virus encephalitis. CT and MRI showed focal lesions in the basal ganglia. MRS of the lesions showed decreased N-acetyl aspartate and elevation of some amino acids, indicating an infectious rather than ischemic etiology. This case illustrates the use of MRS to narrow differential diagnosis. (orig.)

(1) H-MRS processing parameters affect metabolite quantification

DEFF Research Database (Denmark)

Bhogal, Alex A; Schür, Remmelt R; Houtepen, Lotte C

2017-01-01

investigated the influence of model parameters and spectral quantification software on fitted metabolite concentration values. Sixty spectra in 30 individuals (repeated measures) were acquired using a 7-T MRI scanner. Data were processed by four independent research groups with the freedom to choose their own...... + NAAG/Cr + PCr and Glu/Cr + PCr, respectively. Metabolite quantification using identical (1) H-MRS data was influenced by processing parameters, basis sets and software choice. Locally preferred processing choices affected metabolite quantification, even when using identical software. Our results......Proton magnetic resonance spectroscopy ((1) H-MRS) can be used to quantify in vivo metabolite levels, such as lactate, γ-aminobutyric acid (GABA) and glutamate (Glu). However, there are considerable analysis choices which can alter the accuracy or precision of (1) H-MRS metabolite quantification...

AUTOMATION OF INNOVATIVE DEVELOPMENT MANAGEMENT OF THE RUSSIAN ARCTIC ZONE

Directory of Open Access Journals (Sweden)

O. Klementeva

2015-01-01

Full Text Available In the industrially developed countries about 80–95% of the GDP increase is provided by new knowledge represented by new technologies and machinery. This transition to the new innovative development became possible with the creation of new technological patterns for organization of R&D, industrial and innovative activities. Despite of the fact that the structures of national and regional innovative systems of diff erent countries have much in common which concerns the components, the functional classifi cation and the interaction procedures, the question of theoretical structural description of the regional innovative system seems to be of importance. The object of research is the interaction between the entities of the Russian Arctic innovative system from the viewpoint of the complex information inputs. The subject of research is the model-algorithmic support of the automated system providing for innovative activities within the Russian Arctic zone.The article is aimed to work out the theoretical and practical methods for automation of the regional innovative system management with application of modern information technologies. In order to achieve the specifi ed goal, the following tasks are solved in the article: determining of the modern methods and approaches of organization and management of the information flows within the contemporary business communities; the analysis and structural description of the regional innovative system; working out of the concept for the complex automated information system supporting the innovative activity. The research methods. For solving of the stated tasks some methods and approaches for creating of the social networks, methods of organization of the information fl ows based on the Web 2.0 technology and some expert methods of innovation were used. Finally, the following results were obtained: the structural description of the regional innovative system has been worked out. The main

A High-Resolution Tile-Based Approach for Classifying Biological Regions in Whole-Slide Histopathological Images.

Science.gov (United States)

Hoffman, R A; Kothari, S; Phan, J H; Wang, M D

Computational analysis of histopathological whole slide images (WSIs) has emerged as a potential means for improving cancer diagnosis and prognosis. However, an open issue relating to the automated processing of WSIs is the identification of biological regions such as tumor, stroma, and necrotic tissue on the slide. We develop a method for classifying WSI portions (512x512-pixel tiles) into biological regions by (1) extracting a set of 461 image features from each WSI tile, (2) optimizing tile-level prediction models using nested cross-validation on a small (600 tile) manually annotated tile-level training set, and (3) validating the models against a much larger (1.7x10 6 tile) data set for which ground truth was available on the whole-slide level. We calculated the predicted prevalence of each tissue region and compared this prevalence to the ground truth prevalence for each image in an independent validation set. Results show significant correlation between the predicted (using automated system) and reported biological region prevalences with p < 0.001 for eight of nine cases considered.

AUTOMATION DESIGN FOR MONORAIL - BASED SYSTEM PROCESSES

Directory of Open Access Journals (Sweden)

Bunda BESA

2016-12-01

Full Text Available Currently, conventional methods of decline development put enormous cost pressure on the profitability of mining operations. This is the case with narrow vein ore bodies where current methods and mine design of decline development may be too expensive to support economic extraction of the ore. According to studies, the time it takes to drill, clean and blast an end in conventional decline development can be up to 224 minutes. This is because once an end is blasted, cleaning should first be completed before drilling can commence, resulting in low advance rates per shift. Improvements in advance rates during decline development can be achieved by application of the Electric Monorail Transport System (EMTS based drilling system. The system consists of the drilling and loading components that use monorail technology to drill and clean the face during decline development. The two systems work simultaneously at the face in such a way that as the top part of the face is being drilled the pneumatic loading system cleans the face. However, to improve the efficiency of the two systems, critical processes performed by the two systems during mining operations must be automated. Automation increases safety and productivity, reduces operator fatigue and also reduces the labour costs of the system. The aim of this paper is, therefore, to describe automation designs of the two processes performed by the monorail drilling and loading systems during operations. During automation design, critical processes performed by the two systems and control requirements necessary to allow the two systems execute such processes automatically have also been identified.

Design and Development of a Robot-Based Automation System for Cryogenic Crystal Sample Mounting at the Advanced Photon Source

International Nuclear Information System (INIS)

Shu, D.; Preissner, C.; Nocher, D.; Han, Y.; Barraza, J.; Lee, P.; Lee, W.-K.; Cai, Z.; Ginell, S.; Alkire, R.; Lazarski, K.; Schuessler, R.; Joachimiak, A.

2004-01-01

X-ray crystallography is the primary method to determine the 3D structures of complex macromolecules at high resolution. In the years to come, the Advanced Photon Source (APS) and similar 3rd-generation synchrotron sources elsewhere will become the most powerful tools for studying atomic structures of biological molecules. One of the major bottlenecks in the x-ray data collection process is the constant need to change and realign the crystal sample. This is a very time- and manpower-consuming task. An automated sample mounting system will help to solve this bottleneck problem. We have developed a novel robot-based automation system for cryogenic crystal sample mounting at the APS. Design of the robot-based automation system, as well as its on-line test results at the Argonne Structural Biology Center (SBC) 19-BM experimental station, are presented in this paper

An ensemble of dissimilarity based classifiers for Mackerel gender determination

Science.gov (United States)

Blanco, A.; Rodriguez, R.; Martinez-Maranon, I.

2014-03-01

Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity.

An ensemble of dissimilarity based classifiers for Mackerel gender determination

International Nuclear Information System (INIS)

Blanco, A; Rodriguez, R; Martinez-Maranon, I

2014-01-01

Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity

Classifying magnetic resonance image modalities with convolutional neural networks

Science.gov (United States)

Remedios, Samuel; Pham, Dzung L.; Butman, John A.; Roy, Snehashis

2018-02-01

Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Many MR brain image processing techniques, such as tissue segmentation, require multiple MR contrasts as inputs, and each contrast is treated differently. Thus it is advantageous to automate the identification of image contrasts for various purposes, such as facilitating image processing pipelines, and managing and maintaining large databases via content-based image retrieval (CBIR). Most automated CBIR techniques focus on a two-step process: extracting features from data and classifying the image based on these features. We present a novel 3D deep convolutional neural network (CNN)- based method for MR image contrast classification. The proposed CNN automatically identifies the MR contrast of an input brain image volume. Specifically, we explored three classification problems: (1) identify T1-weighted (T1-w), T2-weighted (T2-w), and fluid-attenuated inversion recovery (FLAIR) contrasts, (2) identify pre vs postcontrast T1, (3) identify pre vs post-contrast FLAIR. A total of 3418 image volumes acquired from multiple sites and multiple scanners were used. To evaluate each task, the proposed model was trained on 2137 images and tested on the remaining 1281 images. Results showed that image volumes were correctly classified with 97.57% accuracy.

Integral Monitored Retrievable Storage (MRS) Facility conceptual design report

International Nuclear Information System (INIS)

1985-09-01

This report presents a summary design description of the Conceptual Design for an Integral Monitored Retrievable Storage (MRS) Facility, as prepared by The Ralph M. Parsons Company under an A-E services contract with the Richland Operations Office of the Department of Energy. More detailed design requirements and design data are set forth in the Basis for Design and Design Report, bound under separate cover and available for reference by those desiring such information. The design data provided in this Design Report Executive Summary, the Basis for Design, and the Design Report include contributions by the Waste Technology Services Division of Westinghouse Electric Corporation (WEC), which was responsible for the development of the waste receiving, packaging, and storage systems, and Golder Associates Incorporated (GAI), which supported the design development with program studies. The MRS Facility design requirements, which formed the basis for the design effort, were prepared by Pacific Northwest Laboratory for the US Department of Energy, Richland Operations Office, in the form of a Functional Design Criteria (FDC) document, Rev. 4, August 1985. 9 figs., 6 tabs

WEB-BASED ADAPTIVE TESTING SYSTEM (WATS FOR CLASSIFYING STUDENTS ACADEMIC ABILITY

Directory of Open Access Journals (Sweden)

Jaemu LEE,

2012-08-01

Full Text Available Computer Adaptive Testing (CAT has been highlighted as a promising assessment method to fulfill two testing purposes: estimating student academic ability and classifying student academic level. In this paper, we introduced the Web-based Adaptive Testing System (WATS developed to support a cost effective assessment for classifying students’ ability into different academic levels. Instead of using a traditional paper and pencil test, the WATS is expected to serve as an alternate method to promptly diagnosis and identify underachieving students through Web-based testing. The WATS can also help provide students with appropriate learning contents and necessary academic support in time. In this paper, theoretical background and structure of WATS, item construction process based upon item response theory, and user interfaces of WATS were discussed.

Automated Classification of Consumer Health Information Needs in Patient Portal Messages.

Science.gov (United States)

Cronin, Robert M; Fabbri, Daniel; Denny, Joshua C; Jackson, Gretchen Purcell

2015-01-01

Patients have diverse health information needs, and secure messaging through patient portals is an emerging means by which such needs are expressed and met. As patient portal adoption increases, growing volumes of secure messages may burden healthcare providers. Automated classification could expedite portal message triage and answering. We created four automated classifiers based on word content and natural language processing techniques to identify health information needs in 1000 patient-generated portal messages. Logistic regression and random forest classifiers detected single information needs well, with area under the curves of 0.804-0.914. A logistic regression classifier accurately found the set of needs within a message, with a Jaccard index of 0.859 (95% Confidence Interval: (0.847, 0.871)). Automated classification of consumer health information needs expressed in patient portal messages is feasible and may allow direct linking to relevant resources or creation of institutional resources for commonly expressed needs.

Monte Carlo Modeling for in vivo MRS : Generating and quantifying simulations via the Windows, Linux and Android platform

NARCIS (Netherlands)

De Beer, R.; Van Ormondt, D.

2014-01-01

Work in context of European Union TRANSACT project. We have developed a Java/JNI/C/Fortran based software application, called MonteCarlo, with which the users can carry out Monte Carlo studies in the field of \\emph{in vivo} MRS. The application is supposed to be used as a tool for supporting the

Developing and Integrating Advanced Movement Features Improves Automated Classification of Ciliate Species.

Science.gov (United States)

Soleymani, Ali; Pennekamp, Frank; Petchey, Owen L; Weibel, Robert

2015-01-01

Recent advances in tracking technologies such as GPS or video tracking systems describe the movement paths of individuals in unprecedented details and are increasingly used in different fields, including ecology. However, extracting information from raw movement data requires advanced analysis techniques, for instance to infer behaviors expressed during a certain period of the recorded trajectory, or gender or species identity in case data is obtained from remote tracking. In this paper, we address how different movement features affect the ability to automatically classify the species identity, using a dataset of unicellular microbes (i.e., ciliates). Previously, morphological attributes and simple movement metrics, such as speed, were used for classifying ciliate species. Here, we demonstrate that adding advanced movement features, in particular such based on discrete wavelet transform, to morphological features can improve classification. These results may have practical applications in automated monitoring of waste water facilities as well as environmental monitoring of aquatic systems.

RISK MANAGEMENT AUTOMATION OF SOFTWARE PROJECTS BASED ОN FUZZY INFERENCE

Directory of Open Access Journals (Sweden)

T. M. Zubkova

2015-09-01

Full Text Available Application suitability for one of the intelligent methods for risk management of software projects has been shown based on the review of existing algorithms for fuzzy inference in the field of applied problems. Information sources in the management of software projects are analyzed; major and minor risks are highlighted. The most critical parameters have been singled out giving the possibility to estimate the occurrence of an adverse situations (project duration, the frequency of customer’s requirements changing, work deadlines, experience of developers’ participation in such projects and others.. The method of qualitative fuzzy description based on fuzzy logic has been developed for analysis of these parameters. Evaluation of possible situations and knowledge base formation rely on a survey of experts. The main limitations of existing automated systems have been identified in relation to their applicability to risk management in the software design. Theoretical research set the stage for software system that makes it possible to automate the risk management process for software projects. The developed software system automates the process of fuzzy inference in the following stages: rule base formation of the fuzzy inference systems, fuzzification of input variables, aggregation of sub-conditions, activation and accumulation of conclusions for fuzzy production rules, variables defuzzification. The result of risk management automation process in the software design is their quantitative and qualitative assessment and expert advice for their minimization. Practical significance of the work lies in the fact that implementation of the developed automated system gives the possibility for performance improvement of software projects.

USB port compatible virtual instrument based automation for x-ray diffractometer setup

International Nuclear Information System (INIS)

Jayapandian, J.; Sheela, O.K.; Mallika, R.; Thiruarul, A.; Purniah, B.

2004-01-01

Windows based virtual instrument (VI) programs in graphic language simplify the design automation in R and D laboratories. With minimal hardware and maximum support of software, the automation becomes easier and user friendly. A novel design approach for the automation of SIEMENS make x-ray diffractometer setup is described in this paper. The automation is achieved with an indigenously developed virtual instrument program in labVIEW ver.6.0 and with a simple hardware design using 89C2051 micro-controller compatible with PC's USB port for the total automation of the experiment. (author)

mrsFAST-Ultra: a compact, SNP-aware mapper for high performance sequencing applications.

Science.gov (United States)

Hach, Faraz; Sarrafi, Iman; Hormozdiari, Farhad; Alkan, Can; Eichler, Evan E; Sahinalp, S Cenk

2014-07-01

High throughput sequencing (HTS) platforms generate unprecedented amounts of data that introduce challenges for processing and downstream analysis. While tools that report the 'best' mapping location of each read provide a fast way to process HTS data, they are not suitable for many types of downstream analysis such as structural variation detection, where it is important to report multiple mapping loci for each read. For this purpose we introduce mrsFAST-Ultra, a fast, cache oblivious, SNP-aware aligner that can handle the multi-mapping of HTS reads very efficiently. mrsFAST-Ultra improves mrsFAST, our first cache oblivious read aligner capable of handling multi-mapping reads, through new and compact index structures that reduce not only the overall memory usage but also the number of CPU operations per alignment. In fact the size of the index generated by mrsFAST-Ultra is 10 times smaller than that of mrsFAST. As importantly, mrsFAST-Ultra introduces new features such as being able to (i) obtain the best mapping loci for each read, and (ii) return all reads that have at most n mapping loci (within an error threshold), together with these loci, for any user specified n. Furthermore, mrsFAST-Ultra is SNP-aware, i.e. it can map reads to reference genome while discounting the mismatches that occur at common SNP locations provided by db-SNP; this significantly increases the number of reads that can be mapped to the reference genome. Notice that all of the above features are implemented within the index structure and are not simple post-processing steps and thus are performed highly efficiently. Finally, mrsFAST-Ultra utilizes multiple available cores and processors and can be tuned for various memory settings. Our results show that mrsFAST-Ultra is roughly five times faster than its predecessor mrsFAST. In comparison to newly enhanced popular tools such as Bowtie2, it is more sensitive (it can report 10 times or more mappings per read) and much faster (six times or

Vibration-based Energy Harvesting Systems Characterization Using Automated Electronic Equipment

Directory of Open Access Journals (Sweden)

Ioannis KOSMADAKIS

2015-04-01

Full Text Available A measurement bench has been developed to fully automate the procedure for the characterization of a vibration-based energy scavenging system. The measurement system is capable of monitoring all important characteristics of a vibration harvesting system (input and output voltage, current, and other parameters, frequency and acceleration values, etc.. It is composed of a PC, typical digital measuring instruments (oscilloscope, waveform generator, etc., certain sensors and actuators, along with a microcontroller based automation module. The automation of the procedure and the manipulation of the acquired data are performed by LabVIEW software. Typical measurements of a system consisting of a vibrating source, a vibration transducer and an active rectifier are presented.

Correction of oral contrast artifacts in CT-based attenuation correction of PET images using an automated segmentation algorithm

International Nuclear Information System (INIS)

Ahmadian, Alireza; Ay, Mohammad R.; Sarkar, Saeed; Bidgoli, Javad H.; Zaidi, Habib

2008-01-01

Oral contrast is usually administered in most X-ray computed tomography (CT) examinations of the abdomen and the pelvis as it allows more accurate identification of the bowel and facilitates the interpretation of abdominal and pelvic CT studies. However, the misclassification of contrast medium with high-density bone in CT-based attenuation correction (CTAC) is known to generate artifacts in the attenuation map (μmap), thus resulting in overcorrection for attenuation of positron emission tomography (PET) images. In this study, we developed an automated algorithm for segmentation and classification of regions containing oral contrast medium to correct for artifacts in CT-attenuation-corrected PET images using the segmented contrast correction (SCC) algorithm. The proposed algorithm consists of two steps: first, high CT number object segmentation using combined region- and boundary-based segmentation and second, object classification to bone and contrast agent using a knowledge-based nonlinear fuzzy classifier. Thereafter, the CT numbers of pixels belonging to the region classified as contrast medium are substituted with their equivalent effective bone CT numbers using the SCC algorithm. The generated CT images are then down-sampled followed by Gaussian smoothing to match the resolution of PET images. A piecewise calibration curve was then used to convert CT pixel values to linear attenuation coefficients at 511 keV. The visual assessment of segmented regions performed by an experienced radiologist confirmed the accuracy of the segmentation and classification algorithms for delineation of contrast-enhanced regions in clinical CT images. The quantitative analysis of generated μmaps of 21 clinical CT colonoscopy datasets showed an overestimation ranging between 24.4% and 37.3% in the 3D-classified regions depending on their volume and the concentration of contrast medium. Two PET/CT studies known to be problematic demonstrated the applicability of the technique in

Massively Multi-core Acceleration of a Document-Similarity Classifier to Detect Web Attacks

Energy Technology Data Exchange (ETDEWEB)

Ulmer, C; Gokhale, M; Top, P; Gallagher, B; Eliassi-Rad, T

2010-01-14

This paper describes our approach to adapting a text document similarity classifier based on the Term Frequency Inverse Document Frequency (TFIDF) metric to two massively multi-core hardware platforms. The TFIDF classifier is used to detect web attacks in HTTP data. In our parallel hardware approaches, we design streaming, real time classifiers by simplifying the sequential algorithm and manipulating the classifier's model to allow decision information to be represented compactly. Parallel implementations on the Tilera 64-core System on Chip and the Xilinx Virtex 5-LX FPGA are presented. For the Tilera, we employ a reduced state machine to recognize dictionary terms without requiring explicit tokenization, and achieve throughput of 37MB/s at slightly reduced accuracy. For the FPGA, we have developed a set of software tools to help automate the process of converting training data to synthesizable hardware and to provide a means of trading off between accuracy and resource utilization. The Xilinx Virtex 5-LX implementation requires 0.2% of the memory used by the original algorithm. At 166MB/s (80X the software) the hardware implementation is able to achieve Gigabit network throughput at the same accuracy as the original algorithm.

Automated Classification of Consumer Health Information Needs in Patient Portal Messages

Science.gov (United States)

Cronin, Robert M.; Fabbri, Daniel; Denny, Joshua C.; Jackson, Gretchen Purcell

2015-01-01

Patients have diverse health information needs, and secure messaging through patient portals is an emerging means by which such needs are expressed and met. As patient portal adoption increases, growing volumes of secure messages may burden healthcare providers. Automated classification could expedite portal message triage and answering. We created four automated classifiers based on word content and natural language processing techniques to identify health information needs in 1000 patient-generated portal messages. Logistic regression and random forest classifiers detected single information needs well, with area under the curves of 0.804–0.914. A logistic regression classifier accurately found the set of needs within a message, with a Jaccard index of 0.859 (95% Confidence Interval: (0.847, 0.871)). Automated classification of consumer health information needs expressed in patient portal messages is feasible and may allow direct linking to relevant resources or creation of institutional resources for commonly expressed needs. PMID:26958285

A unified classifier for robust face recognition based on combining multiple subspace algorithms

Science.gov (United States)

Ijaz Bajwa, Usama; Ahmad Taj, Imtiaz; Waqas Anwar, Muhammad

2012-10-01

Face recognition being the fastest growing biometric technology has expanded manifold in the last few years. Various new algorithms and commercial systems have been proposed and developed. However, none of the proposed or developed algorithm is a complete solution because it may work very well on one set of images with say illumination changes but may not work properly on another set of image variations like expression variations. This study is motivated by the fact that any single classifier cannot claim to show generally better performance against all facial image variations. To overcome this shortcoming and achieve generality, combining several classifiers using various strategies has been studied extensively also incorporating the question of suitability of any classifier for this task. The study is based on the outcome of a comprehensive comparative analysis conducted on a combination of six subspace extraction algorithms and four distance metrics on three facial databases. The analysis leads to the selection of the most suitable classifiers which performs better on one task or the other. These classifiers are then combined together onto an ensemble classifier by two different strategies of weighted sum and re-ranking. The results of the ensemble classifier show that these strategies can be effectively used to construct a single classifier that can successfully handle varying facial image conditions of illumination, aging and facial expressions.

Fuzzy prototype classifier based on items and its application in recommender system

Directory of Open Access Journals (Sweden)

Mei Cai

2017-01-01

Full Text Available Currently, recommender systems (RS are incorporating implicit information from social circle of the Internet. The implicit social information in human mind is not easy to reflect in appropriate decision making techniques. This paper consists of 2 contributions. First, we develop an item-based prototype classifier (IPC in which a prototype represents a social circlers preferences as a pattern classification technique. We assume the social circle which distinguishes with others by the items their members like. The prototype structure of the classifier is defined by two2-dimensional matrices. We use information gain and OWA aggregator to construct a feature space. The item-based classifier assigns a new item to some prototypes with different prototypicalities. We reform a typical data setmIris data set in UCI Machine Learning Repository to verify our fuzzy prototype classifier. The second proposition of this paper is to give the application of IPC in recommender system to solve new item cold-start problems. We modify the dataset of MovieLens to perform experimental demonstrations of the proposed ideas.

Development of a Web-based CANDU Core Management Procedure Automation System

International Nuclear Information System (INIS)

Lee, Sanghoon; Kim, Eunggon; Park, Daeyou; Yeom, Choongsub; Suh, Hyungbum; Kim, Sungmin

2006-01-01

CANDU reactor core needs efficient core management to increase safety, stability, high performance as well as to decrease operational cost. The most characteristic feature of CANDU is so called 'on-power refueling' i.e., there is no shutdown during refueling in opposition to that of PWR. Although this on-power refueling increases the efficiency of the plant, it requires heavy operational task and difficulties in real time operation such as regulating power distribution, burnup distribution, LZC statistics, the position of control devices and so on. To enhance the CANDU core management, there are several approaches to help operator and reduce difficulties, one of them is the COMOS (CANDU Core On-line Monitoring System). It has developed as an online core surveillance system based on the standard incre instrumentation and the numerical analysis codes such as RFSP (Reactor Fueling Simulation Program). As the procedure is getting more complex and the number of programs is increased, it is required that integrated and cooperative system. So, KHNP and IAE have been developing a new web-based system which can support effective and accurate reactor operational environment called COMPAS that means CANDU cOre Management Procedure Automation System. To ensure development of successful system, several steps of identifying requirements have been performed and Software Requirement Specification (SRS) document was developed. In this paper we emphasis on the how to keep consistency between the requirements and system products by applying requirement traceability methodology

Automation for a base station stability testing

OpenAIRE

Punnek, Elvis

2016-01-01

This Batchelor’s thesis was commissioned by Oy LM Ericsson Ab Oulu. The aim of it was to help to investigate and create a test automation solution for the stability testing of the LTE base station. The main objective was to create a test automation for a predefined test set. This test automation solution had to be created for specific environments and equipment. This work included creating the automation for the test cases and putting them to daily test automation jobs. The key factor...

MRI and MRS and outcome in infants with hypoxic ischaemic cerebral injury

International Nuclear Information System (INIS)

Saddick, D.; Charlton, M.; Carse, E.; Barfield, C.; Coleman, L.; Goergen, S.

2002-01-01

Full text: To audit clinical outcome at 18 to 30 months in infants with hypoxic ischaemic encephalopathy (HIE) and who had MRI and proton MR spectroscopy (MRS) in infancy. 7 infants diagnosed with HIE at birth were examined prior to day 10 of life (mean = 4.5 days) with cranial MRI and MRS. MRS consisted of a single voxel placed over the basal ganglia and a STEAM (TE = 20ms) or PRESS (TE = 270ms) technique. A TE = 135 was used if a lactate doublet was identified at 1.3ppm. T1, T2, PD, FLAIR and diffusion weighted (DW) MR images were scored independently by two radiologists blinded to outcome. Metabolite peak areas were calculated for lactate, NAA, and creatine and a qualitative assessment of glutamine/ glutamate elevation was made. Of the 7 children, one died on day 6 and the others were invited to participate in neurodevelopmental assessment between 18 and 30 months of age. The MDI and PDI of the Bayley scales of infant development were used to assess intellectual and fine and gross motor development respectively and 3 children have attended the clinic thus far. A neurologist performed a standard neurological examination and graded the result on a six-point scale. The two children who had a very poor outcome on the MDI, PDI and/or neurological assessment and the infant died all had Lac: NAA greater than 1.0 or NAA: Cr less than 0.7 and extensive white matter injury. One child had normal MRS and MRI but has not yet presented for assessment at 18 months. The DW images were abnormal in only one child. The findings of marked lactate elevation and extensive white matter injury correlated with poor prognosis in our small group of patients. Diffusion weighted images were frequently normal. Copyright (2002) Blackwell Science Pty Ltd

Development of an Automated Security Risk Assessment Methodology Tool for Critical Infrastructures.

Energy Technology Data Exchange (ETDEWEB)

Jaeger, Calvin Dell; Roehrig, Nathaniel S.; Torres, Teresa M.

2008-12-01

This document presents the security automated Risk Assessment Methodology (RAM) prototype tool developed by Sandia National Laboratories (SNL). This work leverages SNL's capabilities and skills in security risk analysis and the development of vulnerability assessment/risk assessment methodologies to develop an automated prototype security RAM tool for critical infrastructures (RAM-CITM). The prototype automated RAM tool provides a user-friendly, systematic, and comprehensive risk-based tool to assist CI sector and security professionals in assessing and managing security risk from malevolent threats. The current tool is structured on the basic RAM framework developed by SNL. It is envisioned that this prototype tool will be adapted to meet the requirements of different CI sectors and thereby provide additional capabilities.

Automated quality control in a file-based broadcasting workflow

Science.gov (United States)

Zhang, Lina

2014-04-01

Benefit from the development of information and internet technologies, television broadcasting is transforming from inefficient tape-based production and distribution to integrated file-based workflows. However, no matter how many changes have took place, successful broadcasting still depends on the ability to deliver a consistent high quality signal to the audiences. After the transition from tape to file, traditional methods of manual quality control (QC) become inadequate, subjective, and inefficient. Based on China Central Television's full file-based workflow in the new site, this paper introduces an automated quality control test system for accurate detection of hidden troubles in media contents. It discusses the system framework and workflow control when the automated QC is added. It puts forward a QC criterion and brings forth a QC software followed this criterion. It also does some experiments on QC speed by adopting parallel processing and distributed computing. The performance of the test system shows that the adoption of automated QC can make the production effective and efficient, and help the station to achieve a competitive advantage in the media market.

Radiation dose-dependent change in brain 1H-MRS

International Nuclear Information System (INIS)

Matsushima, Shigeru; Muroka, Mamoru; Uchiyama, Yukio; Morita, Kozo; Nomoto, Yoshihito; Kinosada, Yasutomi.

1994-01-01

We have investigated the usefulness of 1 H-magnetic resonance spectroscopy ( 1 H-MRS) for the assessment of acute radiation damage of the human brain. Nineteen patients were treated with the whole brain irradiation. Biochemical changes in white matter were measured by in vivo 1 H-MRS. The measurement was performed 1 or 2 times in each case at radiation doses ranging from 0 to 44.4 Gy with conventional fractionation (2 Gy per fraction, once a day) or accelerated hyperfractionation (1.5 Gy per fraction, twice a day). For the measurement of 1 H-MRS, 1.5T whole body MR system was used and stimulated echo acquisition mode (STEAM) with chemical shift selective (CHESS) pulse was applied. Volume of the interest (VOI) was 2.5 x 2.5 x 2.5 cm 3 , and the repetition time and echo time were 2000 ms and 272 ms, respectively. The acute radiation damage of the brain was evaluated by the change of peak area ratio (PAR) of choline, creatine and N-acetylaspartate (NAA). 1 H-MR spectra obtained before irradiation were different from those observed during irradiation. There were statistically significant (p 1 H-MRS can be useful for assessment of acute radiation damage. (author)

Comparison of 1H-MRS-detected metabolic characteristics in single metastatic brain tumors of different origin

International Nuclear Information System (INIS)

Chernov, M.F.; Ono, Yuko; Kubo, Osami; Hori, Tomokatsu

2006-01-01

Various types of intracranial metastases exhibit different growth patterns, which can be reflected in their metabolic characteristics and investigated noninvasively by proton magnetic resonance spectroscopy ( 1 H-MRS). The objective of the present study was comparison of the 1 H-MRS-detected metabolic parameters in brain metastases of different origin. Twenty-five patients (15 men and 10 women; mean age, 62.0 years) with single, previously nontreated metastatic brain tumors were investigated by long-echo single-voxel volume-selected 1 H-MRS. The primary cancer was located in the lungs (10 cases), colon and rectum (8 cases), breast (3 cases), kidney (2 cases), prostate (1 case), and cardiac muscle (1 case). Comparison of clinical and radiological variables, including type of tumor contrast enhancement and extension of peritumoral edema, did not disclose statistically significant differences in metastatic brain tumors of different origin. At the same time, comparison of 1 H-MRS-detected metabolic characteristics revealed that metastases of colorectal carcinoma have greater content of mobile lipids (Lip) compared to other neoplasms. In conclusion, high Lip content in the viable brain metastases of colorectal carcinoma can be used as an additional diagnostic clue for noninvasive identification of these tumors and should be taken into consideration in cases of 1 H-MRS-based differentiation of their recurrence and radiation-induced necrosis after radiosurgical or radiotherapeutic treatment. (author)

Development of Nuclear Power Plant Safety Evaluation Method for the Automation Algorithm Application

Energy Technology Data Exchange (ETDEWEB)

Kim, Seung Geun; Seong, Poong Hyun [KAIST, Daejeon (Korea, Republic of)

2016-10-15

It is commonly believed that replacing human operators to the automated system would guarantee greater efficiency, lower workloads, and fewer human error. Conventional machine learning techniques are considered as not capable to handle complex situations in NPP. Due to these kinds of issues, automation is not actively adopted although human error probability drastically increases during abnormal situations in NPP due to overload of information, high workload, and short time available for diagnosis. Recently, new machine learning techniques, which are known as ‘deep learning’ techniques have been actively applied to many fields, and the deep learning technique-based artificial intelligences (AIs) are showing better performance than conventional AIs. In 2015, deep Q-network (DQN) which is one of the deep learning techniques was developed and applied to train AI that automatically plays various Atari 2800 games, and this AI surpassed the human-level playing in many kind of games. Also in 2016, ‘Alpha-Go’, which was developed by ‘Google Deepmind’ based on deep learning technique to play the game of Go (i.e. Baduk), was defeated Se-dol Lee who is the World Go champion with score of 4:1. By the effort for reducing human error in NPPs, the ultimate goal of this study is the development of automation algorithm which can cover various situations in NPPs. As the first part, quantitative and real-time NPP safety evaluation method is being developed in order to provide the training criteria for automation algorithm. For that, EWS concept of medical field was adopted, and the applicability is investigated in this paper. Practically, the application of full automation (i.e. fully replaces human operators) may requires much more time for the validation and investigation of side-effects after the development of automation algorithm, and so the adoption in the form of full automation will take long time.

Development of Nuclear Power Plant Safety Evaluation Method for the Automation Algorithm Application

International Nuclear Information System (INIS)

Kim, Seung Geun; Seong, Poong Hyun

2016-01-01

It is commonly believed that replacing human operators to the automated system would guarantee greater efficiency, lower workloads, and fewer human error. Conventional machine learning techniques are considered as not capable to handle complex situations in NPP. Due to these kinds of issues, automation is not actively adopted although human error probability drastically increases during abnormal situations in NPP due to overload of information, high workload, and short time available for diagnosis. Recently, new machine learning techniques, which are known as ‘deep learning’ techniques have been actively applied to many fields, and the deep learning technique-based artificial intelligences (AIs) are showing better performance than conventional AIs. In 2015, deep Q-network (DQN) which is one of the deep learning techniques was developed and applied to train AI that automatically plays various Atari 2800 games, and this AI surpassed the human-level playing in many kind of games. Also in 2016, ‘Alpha-Go’, which was developed by ‘Google Deepmind’ based on deep learning technique to play the game of Go (i.e. Baduk), was defeated Se-dol Lee who is the World Go champion with score of 4:1. By the effort for reducing human error in NPPs, the ultimate goal of this study is the development of automation algorithm which can cover various situations in NPPs. As the first part, quantitative and real-time NPP safety evaluation method is being developed in order to provide the training criteria for automation algorithm. For that, EWS concept of medical field was adopted, and the applicability is investigated in this paper. Practically, the application of full automation (i.e. fully replaces human operators) may requires much more time for the validation and investigation of side-effects after the development of automation algorithm, and so the adoption in the form of full automation will take long time

Mutations in the Arabidopsis AtMRS2-11/AtMGT10/VAR5 Gene Cause Leaf Reticulation

Directory of Open Access Journals (Sweden)

Shuang Liang

2017-11-01

Full Text Available In higher plants, the development of functional chloroplasts is essential for photosynthesis and many other physiological processes. With a long-term goal of elucidating the genetic regulation of chloroplast development, we identified two allelic leaf variegation mutants, variegated5-1 (var5-1 and var5-2. Both mutants showed a distinct leaf reticulation phenotype of yellow paraveinal regions and green interveinal regions, and the leaf reticulation phenotype correlated with photosynthetic defects. Through the identification of mutation sites in the two mutant alleles and the molecular complementation, we confirmed that VAR5 encodes a CorA family of Mg2+ transporters also known as AtMRS2-11/AtMGT10. Using protoplast transient expression and biochemical fractionation assays, we demonstrated that AtMRS2-11/AtMGT10/VAR5 likely localizes to the chloroplast envelope. Moreover, we established that AtMRS2-11/AtMGT10/VAR5 forms large molecular weight complexes in the chloroplast and the sizes of these complexes clearly exceed those of their bacterial counterparts, suggesting the compositions of CorA Mg2+ transporter complex is different between the chloroplast and bacteria. Our findings indicate that AtMRS2-11/AtMGT10/VAR5 plays an important role in the tissue specific regulation of chloroplast development.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

Directory of Open Access Journals (Sweden)

Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Economic analysis of including an MRS facility in the waste management system

International Nuclear Information System (INIS)

Williams, J.W.; Conner, C.; Leiter, A.J.; Ching, E.

1992-01-01

The MRS System Study Summary Report (System Study) in June 1989 concluded that an MRS facility would provide early spent fuel acceptance as well as flexibility for the waste management system. However, these advantages would be offset by an increase in the total system cost (i.e., total cost to the ratepayer) ranging from $1.3 billion to about $2.8 billion depending on the configuration of the waste management system. This paper discusses this new investigation which will show that, in addition to the advantages of an MRS facility described above, a basic (i.e., store-only) MRS facility may result in a cost savings to the total system, primarily due to the inclusion in the analysis of additional at-reactor operating costs for maintaining shutdown reactor sites

High-field proton MRS of human brain

Energy Technology Data Exchange (ETDEWEB)

Di Costanzo, Alfonso E-mail: alfonso.dicostanzo@unina2.it; Trojsi, F.; Tosetti, M.; Giannatempo, G.M.; Nemore, F.; Piccirillo, M.; Bonavita, S.; Tedeschi, G.; Scarabino, T

2003-11-01

Proton magnetic resonance spectroscopy ({sup 1}H-MRS) of the brain reveals specific biochemical information about cerebral metabolites, which may support clinical diagnoses and enhance the understanding of neurological disorders. The advantages of performing {sup 1}H-MRS at higher field strengths include better signal to noise ratio (SNR) and increased spectral, spatial and temporal resolution, allowing the acquisition of high quality, easily quantifiable spectra in acceptable imaging times. In addition to improved measurement precision of N-acetylaspartate, choline, creatine and myo-inositol, high-field systems allow the high-resolution measurement of other metabolites, such as glutamate, glutamine, {gamma}-aminobutyric acid, scyllo-inositol, aspartate, taurine, N-acetylaspartylglutamate, glucose and branched amino acids, thus extending the range of metabolic information. However, these advantages may be hampered by intrinsic field-dependent technical difficulties, such as decreased T2 signal, chemical shift dispersion errors, J-modulation anomalies, increased magnetic susceptibility, eddy current artifacts, limitations in the design of homogeneous and sensitive radiofrequency (RF) coils, magnetic field instability and safety issues. Several studies demonstrated that these limitations could be overcome, suggesting that the appropriate optimization of high-field {sup 1}H-MRS would expand the application in the fields of clinical research and diagnostic routine.

Diagnostic value of MRS-quantified brain tissue lactate level in identifying children with mitochondrial disorders

International Nuclear Information System (INIS)

Lunsing, Roelineke J.; Strating, Kim; Koning, Tom J. de; Sijens, Paul E.

2017-01-01

Magnetic resonance spectroscopy (MRS) of children with or without neurometabolic disease is used for the first time for quantitative assessment of brain tissue lactate signals, to elaborate on previous suggestions of MRS-detected lactate as a marker of mitochondrial disease. Multivoxel MRS of a transverse plane of brain tissue cranial to the ventricles was performed in 88 children suspected of having neurometabolic disease, divided into 'definite' (n = 17, ≥1 major criteria), 'probable' (n = 10, ≥2 minor criteria), 'possible' (n = 17, 1 minor criterion) and 'unlikely' mitochondrial disease (n = 44, none of the criteria). Lactate levels, expressed in standardized arbitrary units or relative to creatine, were derived from summed signals from all voxels. Ten 'unlikely' children with a normal neurological exam served as the MRS reference subgroup. For 61 of 88 children, CSF lactate values were obtained. MRS lactate level (>12 arbitrary units) and the lactate-to-creatine ratio (L/Cr >0.22) differed significantly between the definite and the unlikely group (p = 0.015 and p = 0.001, respectively). MRS L/Cr also differentiated between the probable and the MRS reference subgroup (p = 0.03). No significant group differences were found for CSF lactate. MRS-quantified brain tissue lactate levels can serve as diagnostic marker for identifying mitochondrial disease in children. (orig.)

Evaluation of storage/transportation options to support criteria development for the Phase I MRS [Monitored Retrievable Storage

International Nuclear Information System (INIS)

Sorenson, K.B.; Brown, N.N.; Bennett, P.C.; Lake, W.

1991-01-01

The Department of Energy's (DOE) Office of Civilian Waste Management (OCRWM) plans to develop an interim storage facility to enable acceptance of spent fuel in 1998. It is estimated that this interim storage facility would be needed for about two years. A Monitored Retrievable Storage (MRS) facility is anticipated in 2000 and a repository in 2010. Acceptance and transport of spent fuel by DOE/OCRWM in 1998 will require an operating transportation system. Because this interim storage facility is not yet defined, development of an optimally compatible transportation system is not a certainty. In order to assure a transport capability for 1998 acceptance of spent fuel, it was decided that the OCRWM transportation program had to identify likely options for an interim storage facility, including identification of the components needed for compatibility between likely interim storage facility options and transportation. Primary attention was given to existing hardware, although conceptual designs were also considered. A systems-based probabilistic decision model was suggested by Sandia National Laboratories and accepted by DOE/OCRWM's transportation program. Performance of the evaluation task involved several elements of the transportation program. This paper describes the decision model developed to accomplish this task, along with some of the results and conclusions. 1 ref., 4 figs

Metabolic changes assessed by MRS accurately reflect brain function during drug-induced epilepsy in mice in contrast to fMRI-based hemodynamic readouts.

Science.gov (United States)

Seuwen, Aline; Schroeter, Aileen; Grandjean, Joanes; Rudin, Markus

2015-10-15

Functional proton magnetic resonance spectroscopy (1H-MRS) enables the non-invasive assessment of neural activity by measuring signals arising from endogenous metabolites in a time resolved manner. Proof-of-principle of this approach has been demonstrated in humans and rats; yet functional 1H-MRS has not been applied in mice so far, although it would be of considerable interest given the many genetically engineered models of neurological disorders established in this species only. Mouse 1H-MRS is challenging as the high demands on spatial resolution typically result in long data acquisition times not commensurable with functional studies. Here, we propose an approach based on spectroscopic imaging in combination with the acquisition of the free induction decay to maximize signal intensity. Highly resolved metabolite maps have been recorded from mouse brain with 12 min temporal resolution. This enabled monitoring of metabolic changes following the administration of bicuculline, a GABA-A receptor antagonist. Changes in levels of metabolites involved in energy metabolism (lactate and phosphocreatine) and neurotransmitters (glutamate) were investigated in a region-dependent manner and shown to scale with the bicuculline dose. GABAergic inhibition induced spectral changes characteristic for increased neurotransmitter turnover and oxidative stress. In contrast to metabolic readouts, BOLD and CBV fMRI responses did not scale with the bicuculline dose indicative of the failure of neurovascular coupling. Nevertheless fMRI measurements supported the notion of increased oxidative stress revealed by functional MRS. Hence, the combined analysis of metabolic and hemodynamic changes in response to stimulation provides complementary insight into processes associated with neural activity. Copyright © 2015 Elsevier Inc. All rights reserved.

Monitored Retrievable Storage (MRS) Facility and its impact on spent fuel transportation

International Nuclear Information System (INIS)

Joy, D.S.; Jolley, R.L.

1986-01-01

The Department of Energy has identified nine potential sites for a repository to permanently dispose of radioactive wastes. DOE has released several sets of maps and tables identifying expected transportation routes between nuclear reactors and repository sites. More recently, the DOE has announced three potential Monitored Retrievable Storage Facility (MRS) sites in the state of Tennessee. Obviously, if a large portion of the spent fuel is routed to Tennessee for consolidation and repackaging, there will be significant changes in the estimated routes. For typical scenarios, the number of shipments in the vicinity of the repository will be reduced. For example, with direct reactor to repository shipments, 995 highway and 262 rail shipments are expected to arrive at the repository annually. With a MRS these numbers are reduced to 201 and 30, respectively. The remaining consolidated fuel would be transported from the MRS in 22 dedicated trains (each train transporting five casks). Conversely, the MRS would result in an increase in the number of spent fuel shipments traveling through the eastern part of Tennessee. However, the operation of a MRS would significantly reduce the number of shipments through the central and western parts of the state

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

Directory of Open Access Journals (Sweden)

A.V. Faria

2011-02-01

Full Text Available High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

Automated image based prominent nucleoli detection.

Science.gov (United States)

Yap, Choon K; Kalaw, Emarene M; Singh, Malay; Chong, Kian T; Giron, Danilo M; Huang, Chao-Hui; Cheng, Li; Law, Yan N; Lee, Hwee Kuan

2015-01-01

Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

Automated image based prominent nucleoli detection

Directory of Open Access Journals (Sweden)

Choon K Yap

2015-01-01

Full Text Available Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

Automation-aided Task Loads Index based on the Automation Rate Reflecting the Effects on Human Operators in NPPs

International Nuclear Information System (INIS)

Lee, Seungmin; Seong, Poonghyun; Kim, Jonghyun

2013-01-01

Many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs) was suggested. These suggested measures express how much automation support human operators but it cannot express the change of human operators' workload, whether the human operators' workload is increased or decreased. Before considering automation rates, whether the adopted automation is good or bad might be estimated in advance. In this study, to estimate the appropriateness of automation according to the change of the human operators' task loads, automation-aided task loads index is suggested based on the concept of the suggested automation rate. To insure plant safety and efficiency on behalf of human operators, various automation systems have been installed in NPPs, and many works which were previously conducted by human operators can now be supported by computer-based operator aids. According to the characteristics of the automation types, the estimation method of the system automation and the cognitive automation rate were suggested. The proposed estimation method concentrates on the effects of introducing automation, so it directly express how much the automated system support human operators. Based on the suggested automation rates, the way to estimate how much the automated system can affect the human operators' cognitive task load is suggested in this study. When there is no automation, the calculated index is 1, and it means there is no change of human operators' task load

Classifying sows' activity types from acceleration patterns

DEFF Research Database (Denmark)

Cornou, Cecile; Lundbye-Christensen, Søren

2008-01-01

An automated method of classifying sow activity using acceleration measurements would allow the individual sow's behavior to be monitored throughout the reproductive cycle; applications for detecting behaviors characteristic of estrus and farrowing or to monitor illness and welfare can be foreseen....... This article suggests a method of classifying five types of activity exhibited by group-housed sows. The method involves the measurement of acceleration in three dimensions. The five activities are: feeding, walking, rooting, lying laterally and lying sternally. Four time series of acceleration (the three...

Automated classification of self-grooming in mice using open-source software.

Science.gov (United States)

van den Boom, Bastijn J G; Pavlidi, Pavlina; Wolf, Casper J H; Mooij, Adriana H; Willuhn, Ingo

2017-09-01

Manual analysis of behavior is labor intensive and subject to inter-rater variability. Although considerable progress in automation of analysis has been made, complex behavior such as grooming still lacks satisfactory automated quantification. We trained a freely available, automated classifier, Janelia Automatic Animal Behavior Annotator (JAABA), to quantify self-grooming duration and number of bouts based on video recordings of SAPAP3 knockout mice (a mouse line that self-grooms excessively) and wild-type animals. We compared the JAABA classifier with human expert observers to test its ability to measure self-grooming in three scenarios: mice in an open field, mice on an elevated plus-maze, and tethered mice in an open field. In each scenario, the classifier identified both grooming and non-grooming with great accuracy and correlated highly with results obtained by human observers. Consistently, the JAABA classifier confirmed previous reports of excessive grooming in SAPAP3 knockout mice. Thus far, manual analysis was regarded as the only valid quantification method for self-grooming. We demonstrate that the JAABA classifier is a valid and reliable scoring tool, more cost-efficient than manual scoring, easy to use, requires minimal effort, provides high throughput, and prevents inter-rater variability. We introduce the JAABA classifier as an efficient analysis tool for the assessment of rodent self-grooming with expert quality. In our "how-to" instructions, we provide all information necessary to implement behavioral classification with JAABA. Copyright © 2017 Elsevier B.V. All rights reserved.

A bench-top hyperspectral imaging system to classify beef from Nellore cattle based on tenderness

Science.gov (United States)

Nubiato, Keni Eduardo Zanoni; Mazon, Madeline Rezende; Antonelo, Daniel Silva; Calkins, Chris R.; Naganathan, Govindarajan Konda; Subbiah, Jeyamkondan; da Luz e Silva, Saulo

2018-03-01

The aim of this study was to evaluate the accuracy of classification of Nellore beef aged for 0, 7, 14, or 21 days and classification based on tenderness and aging period using a bench-top hyperspectral imaging system. A hyperspectral imaging system (λ = 928-2524 nm) was used to collect hyperspectral images of the Longissimus thoracis et lumborum (aging n = 376 and tenderness n = 345) of Nellore cattle. The image processing steps included selection of region of interest, extraction of spectra, and indentification and evalution of selected wavelengths for classification. Six linear discriminant models were developed to classify samples based on tenderness and aging period. The model using the first derivative of partial absorbance spectra (give wavelength range spectra) was able to classify steaks based on the tenderness with an overall accuracy of 89.8%. The model using the first derivative of full absorbance spectra was able to classify steaks based on aging period with an overall accuracy of 84.8%. The results demonstrate that the HIS may be a viable technology for classifying beef based on tenderness and aging period.

Diagnostic value of MRS-quantified brain tissue lactate level in identifying children with mitochondrial disorders

Energy Technology Data Exchange (ETDEWEB)

Lunsing, Roelineke J.; Strating, Kim [University Medical Centre Groningen, University of Groningen, Department of Child Neurology, Groningen (Netherlands); Koning, Tom J. de [University Medical Centre Groningen, University of Groningen, Department of Pediatric Metabolic Diseases, Groningen (Netherlands); Sijens, Paul E. [University Medical Centre Groningen, University of Groningen, Department of Radiology, Groningen (Netherlands)

2017-03-15

Magnetic resonance spectroscopy (MRS) of children with or without neurometabolic disease is used for the first time for quantitative assessment of brain tissue lactate signals, to elaborate on previous suggestions of MRS-detected lactate as a marker of mitochondrial disease. Multivoxel MRS of a transverse plane of brain tissue cranial to the ventricles was performed in 88 children suspected of having neurometabolic disease, divided into 'definite' (n = 17, ≥1 major criteria), 'probable' (n = 10, ≥2 minor criteria), 'possible' (n = 17, 1 minor criterion) and 'unlikely' mitochondrial disease (n = 44, none of the criteria). Lactate levels, expressed in standardized arbitrary units or relative to creatine, were derived from summed signals from all voxels. Ten 'unlikely' children with a normal neurological exam served as the MRS reference subgroup. For 61 of 88 children, CSF lactate values were obtained. MRS lactate level (>12 arbitrary units) and the lactate-to-creatine ratio (L/Cr >0.22) differed significantly between the definite and the unlikely group (p = 0.015 and p = 0.001, respectively). MRS L/Cr also differentiated between the probable and the MRS reference subgroup (p = 0.03). No significant group differences were found for CSF lactate. MRS-quantified brain tissue lactate levels can serve as diagnostic marker for identifying mitochondrial disease in children. (orig.)

A model based message passing approach for flexible and scalable home automation controllers

Energy Technology Data Exchange (ETDEWEB)

Bienhaus, D. [INNIAS GmbH und Co. KG, Frankenberg (Germany); David, K.; Klein, N.; Kroll, D. [ComTec Kassel Univ., SE Kassel Univ. (Germany); Heerdegen, F.; Jubeh, R.; Zuendorf, A. [Kassel Univ. (Germany). FG Software Engineering; Hofmann, J. [BSC Computer GmbH, Allendorf (Germany)

2012-07-01

There is a large variety of home automation systems that are largely proprietary systems from different vendors. In addition, the configuration and administration of home automation systems is frequently a very complex task especially, if more complex functionality shall be achieved. Therefore, an open model for home automation was developed that is especially designed for easy integration of various home automation systems. This solution also provides a simple modeling approach that is inspired by typical home automation components like switches, timers, etc. In addition, a model based technology to achieve rich functionality and usability was implemented. (orig.)

Designing of smart home automation system based on Raspberry Pi

Science.gov (United States)

Saini, Ravi Prakash; Singh, Bhanu Pratap; Sharma, Mahesh Kumar; Wattanawisuth, Nattapol; Leeprechanon, Nopbhorn

2016-03-01

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning "on" and "off" of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

Automated Diagnosis of Otitis Media: Vocabulary and Grammar

Science.gov (United States)

Kuruvilla, Anupama; Hoberman, Alejandro; Kovačević, Jelena

2013-01-01

We propose a novel automated algorithm for classifying diagnostic categories of otitis media: acute otitis media, otitis media with effusion, and no effusion. Acute otitis media represents a bacterial superinfection of the middle ear fluid, while otitis media with effusion represents a sterile effusion that tends to subside spontaneously. Diagnosing children with acute otitis media is difficult, often leading to overprescription of antibiotics as they are beneficial only for children with acute otitis media. This underscores the need for an accurate and automated diagnostic algorithm. To that end, we design a feature set understood by both otoscopists and engineers based on the actual visual cues used by otoscopists; we term this the otitis media vocabulary. We also design a process to combine the vocabulary terms based on the decision process used by otoscopists; we term this the otitis media grammar. The algorithm achieves 89.9% classification accuracy, outperforming both clinicians who did not receive special training and state-of-the-art classifiers. PMID:23997759

An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by Combining Landsat, MODIS, and Secondary Data

OpenAIRE

Thenkabail, Prasad S.; Wu, Zhuoting

2012-01-01

The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated vs. rainfed) over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan u...

Noninvasive brain metabolism measurement using carbon-13 magnetic resonance spectroscopy ({sup 13}C-MRS); Tanso 13 jiki kyomei spectroscopy ({sup 13}C-MRS) ni yoru mushinshuteki notaisha keisoku

Energy Technology Data Exchange (ETDEWEB)

Okamoto, K.; Tsukada, Y. [Toshiba Corp., Tokyo (Japan)

1998-10-10

Carbon-13 magnetic resonance spectroscopy ({sup 13}C-MRS) and research and development efforts for brain metabolism measurement are described. Brain metabolism is a process characterized in that it not only extracts energy by disintegrating grape sugar that is the practically sole source of energy into H2O, CO2, etc., but also vigorously synthesizes amino acids that perform important functions in neural transmission, such as glutamic acid, glutamine, and {gamma}-amino acid. MRS is a technique that utilizes the magnetic resonance, which is generated when an atomic nucleus with a spin is placed in a magnetic field, for the isolation and identification of chemicals in a living body through examining the delicate difference in the magnetic resonance frequencies of the nuclei under observation. Since the signals from {sup 13}C are low in intensity as compared with those from other nuclides, a method was contrived around 1980, which observes {sup 1}H combined with {sup 13}C in grape sugar and amino acids, named the HSQC (heteronuclear single quantum coherence) method. The author et al., combining gradient magnetic pulses with HSQC, actually measure Homo sapiens brain metabolism using {sup 13}C-MRS, and now believe that the technology will be put to practical application. 7 refs., 10 figs., 1 tab.

Spectral data de-noising using semi-classical signal analysis: application to localized MRS

KAUST Repository

Laleg-Kirati, Taous-Meriem

2016-09-05

In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrodinger operator. In this manner, the MRS spectral peaks represented as a sum of these \\'shaped like\\' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

Spectral data de-noising using semi-classical signal analysis: application to localized MRS

KAUST Repository

Laleg-Kirati, Taous-Meriem; Zhang, Jiayu; Achten, Eric; Serrai, Hacene

2016-01-01

In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrodinger operator. In this manner, the MRS spectral peaks represented as a sum of these 'shaped like' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

Virk: An Active Learning-based System for Bootstrapping Knowledge Base Development in the Neurosciences

Directory of Open Access Journals (Sweden)

Kyle H. Ambert

2013-12-01

Full Text Available The frequency and volume of newly-published scientific literature is quickly making manual maintenance of publicly-available databases of primary data unrealistic and costly. Although machine learning can be useful for developing automated approaches to identifying scientific publications containing relevant information for a database, developing such tools necessitates manually annotating an unrealistic number of documents. One approach to this problem, active learning, builds classification models by iteratively identifying documents that provide the most information to a classifier. Although this approach has been shown to be effective for related problems, in the context of scientific databases curation, it falls short. We present Virk, an active learning system that, while being trained, simultaneously learns a classification model and identifies documents having information of interest for a knowledge base. Our approach uses a support vector machine classifier with input features derived from neuroscience-related publications from the primary literature. Using our approach, we were able to increase the size of the Neuron Registry, a knowledge base of neuron-related information, by a factor of 90%, a knowledge base of neuron-related information, in 3 months. Using standard biocuration methods, it would have taken between 1-2 years to make the same number of contributions to the Neuron Registry. Here, we describe the system pipeline in detail, and evaluate its performance against other approaches to sampling in active learning.

Automation-aided Task Loads Index based on the Automation Rate Reflecting the Effects on Human Operators in NPPs

Energy Technology Data Exchange (ETDEWEB)

Lee, Seungmin; Seong, Poonghyun [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Kim, Jonghyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2013-05-15

Many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs) was suggested. These suggested measures express how much automation support human operators but it cannot express the change of human operators' workload, whether the human operators' workload is increased or decreased. Before considering automation rates, whether the adopted automation is good or bad might be estimated in advance. In this study, to estimate the appropriateness of automation according to the change of the human operators' task loads, automation-aided task loads index is suggested based on the concept of the suggested automation rate. To insure plant safety and efficiency on behalf of human operators, various automation systems have been installed in NPPs, and many works which were previously conducted by human operators can now be supported by computer-based operator aids. According to the characteristics of the automation types, the estimation method of the system automation and the cognitive automation rate were suggested. The proposed estimation method concentrates on the effects of introducing automation, so it directly express how much the automated system support human operators. Based on the suggested automation rates, the way to estimate how much the automated system can affect the human operators' cognitive task load is suggested in this study. When there is no automation, the calculated index is 1, and it means there is no change of human operators' task load.

Development of an Automated Technique for Failure Modes and Effect Analysis

DEFF Research Database (Denmark)

Blanke, M.; Borch, Ole; Allasia, G.

1999-01-01

Advances in automation have provided integration of monitoring and control functions to enhance the operator's overview and ability to take remedy actions when faults occur. Automation in plant supervision is technically possible with integrated automation systems as platforms, but new design...... methods are needed to cope efficiently with the complexity and to ensure that the functionality of a supervisor is correct and consistent. In particular these methods are expected to significantly improve fault tolerance of the designed systems. The purpose of this work is to develop a software module...... implementing an automated technique for Failure Modes and Effects Analysis (FMEA). This technique is based on the matrix formulation of FMEA for the investigation of failure propagation through a system. As main result, this technique will provide the design engineer with decision tables for fault handling...

Development of an automated technique for failure modes and effect analysis

DEFF Research Database (Denmark)

Blanke, Mogens; Borch, Ole; Bagnoli, F.

1999-01-01

Advances in automation have provided integration of monitoring and control functions to enhance the operator's overview and ability to take remedy actions when faults occur. Automation in plant supervision is technically possible with integrated automation systems as platforms, but new design...... methods are needed to cope efficiently with the complexity and to ensure that the functionality of a supervisor is correct and consistent. In particular these methods are expected to significantly improve fault tolerance of the designed systems. The purpose of this work is to develop a software module...... implementing an automated technique for Failure Modes and Effects Analysis (FMEA). This technique is based on the matrix formulation of FMEA for the investigation of failure propagation through a system. As main result, this technique will provide the design engineer with decision tables for fault handling...

Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA).

Science.gov (United States)

Salimi, Nima; Loh, Kar Hoe; Kaur Dhillon, Sarinder; Chong, Ving Ching

2016-01-01

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

Development of automated blender and dispensing system

International Nuclear Information System (INIS)

Kulkarni, Anupama; Aherwal, P.; Patil, C.B.

2014-01-01

This paper describes automated blender and dispensing system designed and developed in Nuclear Recycle Board for its reprocessing plant. Obtaining sinterable grade oxide powder from the product solution received in the heavy metal product line involves skilled manpower and time consuming, laborious manual operations. Entire treatment is carried out in a train of closed containments called as glove boxes. In view of this Automated blender and dispensing system has been developed to reduce tedious manual operations. System consists of PLC based control system to drive motorised charging mechanism, a conical ribbon blender which homogenises the product and load cell triggered, indexing dispensing mechanism. Schematic design of the system has been done in-house, while fabrication was outsourced. System has been built, tested and installed at component test facility (CTF) at Tarapur. Actual blending tests were carried out by using dummy material like calcium carbonate and barium carbonate powder, with different sets of parameter. Blended product was chemically analysed for its homogeneity. System has now been put to trial runs by operating staff. This development has circumvented tedious operations of Scooping and increased the throughput. This paper describes challenges in undertaking this developmental work. (author)

Automated Bug Assignment: Ensemble-based Machine Learning in Large Scale Industrial Contexts

OpenAIRE

Jonsson, Leif; Borg, Markus; Broman, David; Sandahl, Kristian; Eldh, Sigrid; Runeson, Per

2016-01-01

Bug report assignment is an important part of software maintenance. In particular, incorrect assignments of bug reports to development teams can be very expensive in large software development projects. Several studies propose automating bug assignment techniques using machine learning in open source software contexts, but no study exists for large-scale proprietary projects in industry. The goal of this study is to evaluate automated bug assignment techniques that are based on machine learni...

A comprehensive review of the 1H-MRS metabolite spectrum in autism spectrum disorder.

Directory of Open Access Journals (Sweden)

Talitha eFord

2016-03-01

Full Text Available Neuroimaging studies of neuropsychiatric behaviour biomarkers across spectrum disorders are typically based on diagnosis, thus failing to account for the heterogeneity of multi-dimensional spectrum disorders such as autism (ASD. Control group trait phenotypes are also seldom reported. Proton magnetic resonance spectroscopy (1H-MRS measures the abundance of neurochemicals such as neurotransmitters and metabolites and hence can probe disorder phenotypes at clinical and sub-clinical levels. This detailed review summarises and critiques the current 1H-MRS research in ASD. The literature reports reduced N-acetylaspartate (NAA, glutamate and glutamine (Glx, gamma-aminobutyric acid (GABA, creatine and choline, and increased glutamate for children with ASD. Adult studies are few and results are inconclusive. Overall, the literature has several limitations arising from differences in 1H-MRS methodology and sample demographics. We argue that more consistent methods and greater emphasis on phenotype studies will advance understanding of underlying cortical metabolite disturbance in ASD, and the detection, diagnosis and treatment of ASD and other multi-dimensional psychiatric disorders.

Launch Control System Software Development System Automation Testing

Science.gov (United States)

Hwang, Andrew

2017-01-01

The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administration's (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This system requires high quality testing that will measure and test the capabilities of the system. For the past two years, the Exploration and Operations Division at Kennedy Space Center (KSC) has assigned a group including interns and full-time engineers to develop automated tests to save the project time and money. The team worked on automating the testing process for the SCCS GUI that would use streamed simulated data from the testing servers to produce data, plots, statuses, etc. to the GUI. The software used to develop automated tests included an automated testing framework and an automation library. The automated testing framework has a tabular-style syntax, which means the functionality of a line of code must have the appropriate number of tabs for the line to function as intended. The header section contains either paths to custom resources or the names of libraries being used. The automation library contains functionality to automate anything that appears on a desired screen with the use of image recognition software to detect and control GUI components. The data section contains any data values strictly created for the current testing file. The body section holds the tests that are being run. The function section can include any number of functions that may be used by the current testing file or any other file that resources it. The resources and body section are required for all test files; the data and function sections can be left empty if the data values and functions being used are from a resourced library or another file. To help equip the automation team with better tools, the Project Lead of the Automated Testing Team, Jason Kapusta, assigned the task to install and train an optical character recognition (OCR

Web-based automation of green building rating index and life cycle cost analysis

Science.gov (United States)

Shahzaib Khan, Jam; Zakaria, Rozana; Aminuddin, Eeydzah; IzieAdiana Abidin, Nur; Sahamir, Shaza Rina; Ahmad, Rosli; Nafis Abas, Darul

2018-04-01

Sudden decline in financial markets and economic meltdown has slow down adaptation and lowered interest of investors towards green certified buildings due to their higher initial costs. Similarly, it is essential to fetch investor’s attention towards more development of green buildings through automated tools for the construction projects. Though, historical dearth is found on the automation of green building rating tools that brings up an essential gap to develop an automated analog computerized programming tool. This paper present a proposed research aim to develop an integrated web-based automated analog computerized programming that applies green building rating assessment tool, green technology and life cycle cost analysis. It also emphasizes to identify variables of MyCrest and LCC to be integrated and developed in a framework then transformed into automated analog computerized programming. A mix methodology of qualitative and quantitative survey and its development portray the planned to carry MyCrest-LCC integration to an automated level. In this study, the preliminary literature review enriches better understanding of Green Building Rating Tools (GBRT) integration to LCC. The outcome of this research is a pave way for future researchers to integrate other efficient tool and parameters that contributes towards green buildings and future agendas.

Agent-Oriented Embedded Control System Design and Development of a Vision-Based Automated Guided Vehicle

Directory of Open Access Journals (Sweden)

Wu Xing

2012-07-01

Full Text Available This paper presents a control system design and development approach for a vision-based automated guided vehicle (AGV based on the multi-agent system (MAS methodology and embedded system resources. A three-phase agent-oriented design methodology Prometheus is used to analyse system functions, construct operation scenarios, define agent types and design the MAS coordination mechanism. The control system is then developed in an embedded implementation containing a digital signal processor (DSP and an advanced RISC machine (ARM by using the multitasking processing capacity of multiple microprocessors and system services of a real-time operating system (RTOS. As a paradigm, an onboard embedded controller is designed and developed for the AGV with a camera detecting guiding landmarks, and the entire procedure has a high efficiency and a clear hierarchy. A vision guidance experiment for our AGV is carried out in a space-limited laboratory environment to verify the perception capacity and the onboard intelligence of the agent-oriented embedded control system.

Automated road network extraction from high spatial resolution multi-spectral imagery

Science.gov (United States)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

Ensemble of classifiers based network intrusion detection system performance bound

CSIR Research Space (South Africa)

Mkuzangwe, Nenekazi NP

2017-11-01

Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

Development of Hardware and Software for Automated Ultrasonic Testing

International Nuclear Information System (INIS)

Choi, Sung Nam; Lee, Hee Jong; Yang, Seung Ok

2012-01-01

Nondestructive testing (NDT) for the construction and operating of NPPs plays an important role in confirming the integrity of the NPPs. Especially, Automated ultrasonic testing (AUT) is one of the primary nondestructive examination methods for in-service inspection of the welding parts in major components in NPPs. AUT is a reliable nondestructive testing because the data of AUT are saved and reviewed with other examiners. Korea Hydro and Nuclear Power-Central Research Institute (KHNP-CRI) has developed an automated ultrasonic testing (AUT) system based on a high speed pulser-receiver. In combination with the designed software and hardware architecture, this new system permits user configurations for a wide range of user-specific applications through fully automated inspections using compact portable systems with up to eight channels. This paper gives an overview of hardware (H/W) and software (S/W) for the AUT system to inspect welds in NPPs

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy.

Directory of Open Access Journals (Sweden)

Lina Zhang

Full Text Available Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information, PSSM (Position Specific Scoring Matrix, RSA (Relative Solvent Accessibility, and CTD (Composition, Transition, Distribution. The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest, SMO (Sequential Minimal Optimization, NNA (Nearest Neighbor Algorithm, and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew's Correlation Coefficient of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

MRS transfer facility feasibility study

International Nuclear Information System (INIS)

Jowdy, A.K.; Smith, R.I.

1990-12-01

Under contract to the US Department of Energy, Parsons was requested to evaluate the feasibility of building a simple hot cell (waste handling) transfer facility at the Monitored Retrievable Storage (MRS) site to facilitate acceptance of spent fuel into the Federal Waste Management System starting in early 1998. The Transfer Facility was intended to provide a receiving and transfer to storage capability at a relatively low throughput rate (approximately 500 MTU/yr) and to provide the recovery capability needed on the site in the event of a transport or storage cask seal failure during a period of about two years while the larger Spent Fuel Handling Building (SFHB) was being completed. Although the original study basis postulated an incremental addition to the larger, previously considered MRS configurations, study results show that the Transfer Facility may be capable of receiving and storing spent fuel at annual rates of 3000 MTU/yr or more, making a larger fuel handling structure unnecessary. In addition, the study analyses showed that the Transfer Facility could be constructed and put into service in 15--17 months and would cost less than the previous configurations. 2 figs., 2 tabs

Working Memory Modulates Glutamate Levels in the Dorsolateral Prefrontal Cortex during 1H fMRS

Directory of Open Access Journals (Sweden)

Eric A. Woodcock

2018-03-01

Full Text Available Glutamate is involved in excitatory neurotransmission and metabolic processes related to brain function. Previous studies using proton functional magnetic resonance spectroscopy (1H fMRS have demonstrated elevated cortical glutamate levels by 2–4% during visual and motor stimulation, relative to periods of no stimulation. Here, we extended this approach to working memory cognitive task performance, which has been consistently associated with dorsolateral prefrontal cortex (dlPFC activation. Sixteen healthy adult volunteers completed a continuous visual fixation “rest” task followed by a letter 2-back working memory task during 1H fMRS acquisition of the left dlPFC, which encompassed Brodmann areas 45 and 46 over a 4.5-cm3 volume. Using a 100% automated fitting procedure integrated with LCModel, raw spectra were eddy current-, phase-, and shift-corrected prior to quantification resulting in a 32s temporal resolution or 8 averages per spectra. Task compliance was high (95 ± 11% correct and the mean Cramer-Rao Lower Bound of glutamate was 6.9 ± 0.9%. Relative to continuous passive visual fixation, left dlPFC glutamate levels were significantly higher by 2.7% (0.32 mmol/kg wet weight during letter 2-back performance. Elevated dlPFC glutamate levels reflect increased metabolic activity and excitatory neurotransmission driven by working memory-related cognitive demands. These results provide the first in vivo demonstration of elevated dlPFC glutamate levels during working memory.

Utilización del medio Mrs-s en el aislamiento de bacterias lácticas mesofilas en leche de cabra Utilización del medio Mrs-s en el aislamiento de bacterias lacticas mesofilas en leche de cabra

Directory of Open Access Journals (Sweden)

Fortes F. Celia L. de Luces

1990-12-01

Full Text Available Con el fin de evaluar el MRS-S (Sorbato al 0.10% en el aislamiento de bacterias lácticas se cultivaron muestras de leche de cabra cruda en MRS-S y PCA en profundidad y se incubaron en aerobiósis a 320C durante 48 horas. Los cocos gram positivos, catalasa negativos que crecieron en MRS-S se aislaron y sometieron a caracterización preliminar a través del crecimiento en agar MRS-S, MRS-T (tetraciclina 0.20 µg/ml, N-L (bacterias aromáticas, reducción de la leche tornasolada a 40 y 21oC y crecimiento a 45 y 10oC.Las cepas seleccionadas se sometieron a caracterización fisiológica y Bioquímica. El medio MRS-S mostró ser efectivo con un porcentaje de inhibición de la flora indeseable del 86.56%, y adecuado por el aislamiento de Lactococcus. De acuerdo con los perfiles taxonómicos se consiguió aislar de un total de 156 colonias dos Lactococcus lactis subsp. lactis y un Lactococcus lactis biovar diacetilactis.With the objective of evaluating the MRS-S (0.10% of sorbate in the isolation of lactic bacteria samples of raw goat milk were cultivated in MRS-S and PCA in deep and incubated in aerobic conditions for 48 hours al 32oC. Gram positive coccus, negative catalase which grew in MRS-S were isolated and preliminarly characterized through the growing process in agar MRS-S, MRS-T (O.20ltg/ml tetracycline, N-L (aromatic bacteria, litmus milk reduction at 40 and 210C and growing at 45 and 10oC. Selected strains were subject to the physiological and biochemical characterization. MRS-S media showed to be effective with an 86.56% of inhibition for indesirable bacteria and adequated for Lactococcus isolation. Related to taxonomic profiles from 156 colonies were isolated two lactococcus lactis subsp. lactis and one Lactococcus luctis biovar diacetilactis.

“The Naming of Cats”: Automated Genre Classification

Directory of Open Access Journals (Sweden)

Yunhyong Kim

2007-07-01

Full Text Available This paper builds on the work presented at the ECDL 2006 in automated genre classification as a step toward automating metadata extraction from digital documents for ingest into digital repositories such as those run by archives, libraries and eprint services (Kim & Ross, 2006b. We have previously proposed dividing features of a document into five types (features for visual layout, language model features, stylometric features, features for semantic structure, and contextual features as an object linked to previously classified objects and other external sources and have examined visual and language model features. The current paper compares results from testing classifiers based on image and stylometric features in a binary classification to show that certain genres have strong image features which enable effective separation of documents belonging to the genre from a large pool of other documents.

A rule-based smart automated fertilization and irrigation systems

Science.gov (United States)

Yousif, Musab El-Rashid; Ghafar, Khairuddin; Zahari, Rahimi; Lim, Tiong Hoo

2018-04-01

Smart automation in industries has become very important as it can improve the reliability and efficiency of the systems. The use of smart technologies in agriculture have increased over the year to ensure and control the production of crop and address food security. However, it is important to use proper irrigation systems avoid water wastage and overfeeding of the plant. In this paper, a Smart Rule-based Automated Fertilization and Irrigation System is proposed and evaluated. We propose a rule based decision making algorithm to monitor and control the food supply to the plant and the soil quality. A build-in alert system is also used to update the farmer using a text message. The system is developed and evaluated using a real hardware.

Application of NUHOMS to an integrated MRS/transportation system

International Nuclear Information System (INIS)

Rosa, J.M.; Lehnert, R.A.; Quinn, R.D.

1992-01-01

This paper reports that storage of spent fuel a reactor sites in weld sealed canisters has been increasing steadily since 1989, with three utilities now having ISFSIs which employ the NUHOMS technology. Expansion of existing Independent Spent Fuel Storage Installations (ISFSIs) and implementation of new ones will result in a substantial fraction of the at-reactor spent fuel inventory in dry storage canisters by 1998 and beyond. Since the same technology is readily applicable to the MRS, it is advantageous to transfer canisters directly from the ISFSI to the MRS for storage thee without the need to reopen the canisters or rehandle the fuel. A store-only MRS offers the possibility of a simple, economical facility which can more easily be demonstrated to be temporary and environmentally benign. Transportation of an intact canister is feasible in a shipping cask of conventional design that is compatible with existing railcars and railroad interchange rules. The use of canisterized fuel also has advantages for eventual shipment and disposal at the federal repository

Integral Monitored Retrievable Storage (MRS) Facility conceptual basis for design

International Nuclear Information System (INIS)

1985-10-01

The purpose of the Conceptual Basis for Design is to provide a control document that establishes the basis for executing the conceptual design of the Integral Monitored Retrievable Storage (MRS) Facility. This conceptual design shall provide the basis for preparation of a proposal to Congress by the Department of Energy (DOE) for construction of one or more MRS Facilities for storage of spent nuclear fuel, high-level radioactive waste, and transuranic (TRU) waste. 4 figs., 25 tabs

Network-based automation for SMEs

DEFF Research Database (Denmark)

Parizi, Mohammad Shahabeddini; Radziwon, Agnieszka

2017-01-01

The implementation of appropriate automation concepts which increase productivity in Small and Medium Sized Enterprises (SMEs) requires a lot of effort, due to their limited resources. Therefore, it is strongly recommended for small firms to open up for the external sources of knowledge, which...... could be obtained through network interaction. Based on two extreme cases of SMEs representing low-tech industry and an in-depth analysis of their manufacturing facilities this paper presents how collaboration between firms embedded in a regional ecosystem could result in implementation of new...... with other members of the same regional ecosystem. The findings highlight two main automation related areas where manufacturing SMEs could leverage on external sources on knowledge – these are assistance in defining automation problem as well as appropriate solution and provider selection. Consequently...

J-difference-edited MRS measures of γ-aminobutyric acid before and after acute caffeine administration.

Science.gov (United States)

Oeltzschner, Georg; Zöllner, Helge J; Jonuscheit, Marc; Lanzman, Rotem S; Schnitzler, Alfons; Wittsack, Hans-Jörg

2018-05-12

The aim of this study was to investigate potential effects of acute caffeine intake on J-difference-edited MRS measures of the primary inhibitory neurotransmitter γ-aminobutyric acid (GABA). J-difference-edited Mescher-Garwood PRESS (MEGA-PRESS) and conventional PRESS data were acquired at 3T from voxels in the anterior cingulate and occipital area of the brain in 15 healthy subjects, before and after oral intake of a 200-mg caffeine dose. MEGA-PRESS data were analyzed with the MATLAB-based Gannet tool to estimate GABA+ macromolecule (GABA+) levels, while PRESS data were analyzed with LCModel to estimate levels of glutamate, glutamate+glutamine, N-acetylaspartate, and myo-inositol. All metabolites were quantified with respect to the internal reference compounds creatine and tissue water, and compared between the pre- and post-caffeine intake condition. For both MRS voxels, mean GABA+ estimates did not differ before and after caffeine intake. Slightly lower estimates of myo-inositol were observed after caffeine intake in both voxels. N-acetylaspartate, glutamate, and glutamate+glutamine did not show significant differences between conditions. Mean GABA+ estimates from J-difference-edited MRS in two different brain regions are not altered by acute oral administration of caffeine. These findings may increase subject recruitment efficiency for MRS studies. © 2018 International Society for Magnetic Resonance in Medicine.

Diversity requirements for safety critical software-based automation systems

International Nuclear Information System (INIS)

Korhonen, J.; Pulkkinen, U.; Haapanen, P.

1998-03-01

System vendors nowadays propose software-based systems even for the most critical safety functions in nuclear power plants. Due to the nature and mechanisms of influence of software faults new methods are needed for the safety and reliability evaluation of these systems. In the research project 'Programmable automation systems in nuclear power plants (OHA)' various safety assessment methods and tools for software based systems are developed and evaluated. This report first discusses the (common cause) failure mechanisms in software-based systems, then defines fault-tolerant system architectures to avoid common cause failures, then studies the various alternatives to apply diversity and their influence on system reliability. Finally, a method for the assessment of diversity is described. Other recently published reports in OHA-report series handles the statistical reliability assessment of software based (STUK-YTO-TR 119), usage models in reliability assessment of software-based systems (STUK-YTO-TR 128) and handling of programmable automation in plant PSA-studies (STUK-YTO-TR 129)

Automated Non-Destructive Testing Array Evaluation System

Energy Technology Data Exchange (ETDEWEB)

Wei, T.; Zavaljevski, N.; Bakhtiari, S.; Miron, A.; Jupperman, D.

2004-12-31

Utilities perform eddy current tests on nuclear power plant steam generator (SG) tubes to detect degradation. This report summarizes the status of ongoing research to develop signal processing algorithms that automate analysis of eddy current test data. The research focuses on analyzing array probe data for detecting, classifying, and characterizing degradation in SG tubes.

Automated Non-Destructive Testing Array Evaluation System

International Nuclear Information System (INIS)

Wei, T.; Zavaljevski, N.; Bakhtiari, S.; Miron, A.; Kupperman, D.

2004-01-01

Utilities perform eddy current tests on nuclear power plant steam generator (SG) tubes to detect degradation. This report summarizes the status of ongoing research to develop signal processing algorithms that automate analysis of eddy current test data. The research focuses on analyzing array probe data for detecting, classifying, and characterizing degradation in SG tubes

Developments towards a fully automated AMS system

International Nuclear Information System (INIS)

Steier, P.; Puchegger, S.; Golser, R.; Kutschera, W.; Priller, A.; Rom, W.; Wallner, A.; Wild, E.

2000-01-01

The possibilities of computer-assisted and automated accelerator mass spectrometry (AMS) measurements were explored. The goal of these efforts is to develop fully automated procedures for 'routine' measurements at the Vienna Environmental Research Accelerator (VERA), a dedicated 3-MV Pelletron tandem AMS facility. As a new tool for automatic tuning of the ion optics we developed a multi-dimensional optimization algorithm robust to noise, which was applied for 14 C and 10 Be. The actual isotope ratio measurements are performed in a fully automated fashion and do not require the presence of an operator. Incoming data are evaluated online and the results can be accessed via Internet. The system was used for 14 C, 10 Be, 26 Al and 129 I measurements

PREFACE: Brazil MRS Meeting 2014

Science.gov (United States)

2015-11-01

The annual meetings, organized by the Brazilian materials research society - B-MRS, are amongst the most import discussion forums in the area of materials science and engineering in Brazil, with a growing interest from the national and international scientific society. In the last 4 years, more than 1,500 participants have attended the B-MRS meetings, promoting an auspicious environment for presentation and discussion of scientific and technological works in the materials science area. The XIII Brazilian Materials Research Society Meeting was held from 28 September to 02 October, 2014, in João Pessoa, PB, Brazil. The Meeting congregated more than 1650 participants from the whole of Brazil and from 28 other countries. More than 2100 abstracts were accepted for presentation, distributed along 19 Symposia following the format used in traditional meetings of Materials Research Societies. These involved topics such as: synthesis of new materials, computer simulations, optical, magnetic and electronic properties, traditional materials as clays and cements, advanced metals, carbon and graphene nanostructures, nanomaterials for nanostructures, energy storage systems, composites, surface engineering and others. A novelty was a symposium dedicated to innovation and technology transfer in materials research. The program also included 7 Plenary Lectures presented by internationally renowned researchers: Alberto Salleo from Stanford University, United States of America; Roberto Dovesi from Universita' degli Studi di Torino, Italy; Luís Antonio F. M. Dias Carlos from Universidade de Aveiro, Portugal; Jean Marie Dubois from Institut Jean-Lamour, France; Sir Colin Humphreys from University of Cambridge, England; Karl Leo from Technische Universität Dresden, Germany; Robert Chang from Northwestern University, Evanston, United States of America. The numbers of participants in the B-MRS meetings have been growing continuously, and in this meeting we had almost 2200 presentations

Simulation of the MRS receiving and handling facility

International Nuclear Information System (INIS)

Triplett, M.B.; Imhoff, C.H.; Hostick, C.J.

1984-02-01

Monitored retrievable storage (MRS) will be required to handle a large volume of spent fuel or high-level waste (HLW) in case of delays in repository deployment. The quantities of materials to be received and repackaged for storage far exceed the requirements of existing waste mangement facilities. A computer simulation model of the MRS receiving and handling (R and H) fcility has been constructed and used to evaluate design alternatives. Studies have identified processes or activities which may constrain throughput performance. In addition, the model has helped to assess design tradeoffs such as those to be made among improved process times, redundant service lines, and improved component availability. 1 reference, 5 figures

Evaluation of acute radiation damage of the human brain by 1H-MRS

International Nuclear Information System (INIS)

Matsushima, Shigeru; Kinosada, Yasutomi.

1993-01-01

Fourteen patients (17 cases) were treated with the whole brain irradiation. Physiological changes in white matter were measured by in vivo 1 H magnetic resonance spectroscopy ( 1 H-MRS). Phantom examination proved the accuracy of our 1 H-MRS method to be valid. The measurement was performed 2 or 3 times in each case at the radiation doses ranging from 0 to 40 Gy with 2 Gy daily fractionation. For the measurement of 1 H-MRS, 1.5 T whole body MR system was used and stimulated echo acquisition mode (STEAM) with chemical shift selective (CHESS) pulse was applied. Volume of the interest (VOI) was 2.5x2.5x2.5 cm 3 , and the repetition time and echo time were 2000 ms and 272 ms, respectively. Acute radiation damage of the brain was evaluated by the change of peak area ratio (PAR) of choline, creatine and N-acetyl aspartate (NAA). 1 H-MRS spectra before irradiation were different from those observed during irradiation. There were statistically significant (p 1 H-MRS is a powerful modality, detecting the subtle physiological change which is difficult to evaluate with conventional images. (author)

Models and automation technologies for the curriculum development

Directory of Open Access Journals (Sweden)

V. N. Volkova

2016-01-01

Full Text Available The aim of the research was to determine the sequence of the curriculum development stages on the basis of the system analysis, as well as to create models and information technologies for the implementation of thesestages.The methods and the models of the systems’ theory and the system analysis, including methods and automated procedures for structuring organizational aims, models and automated procedures for organizing complex expertise.On the basis of the analysis of existing studies in the field of curriculum modeling, using formal mathematical language, including optimization models, that help to make distribution of disciplines by years and semesters in accordance with the relevant restrictions, it is shown, that the complexity and dimension of these tasks require the development of special software; the problem of defining the input data and restrictions requires a large time investment, that seems to be difficult to provide in real conditions of plans’ developing, thus it is almost impossible to verify the objectivity of the input data and the restrictions in such models. For a complete analysis of the process of curriculum development it is proposed to use the system definition, based on the system-targeted approach. On the basis of this definition the reasonable sequence of the integrated stages for the development of the curriculum was justified: 1 definition (specification of the requirements for the educational content; 2 determining the number of subjects, included in the curriculum; 3 definition of the sequence of the subjects; 4 distribution of subjects by semesters. The models and technologies for the implementation of these stages of curriculum development were given in the article: 1 models, based on the information approach of A.Denisov and the modified degree of compliance with objectives based on Denisov’s evaluation index (in the article the idea of evaluating the degree of the impact of disciplines for realization

WIRELESS HOME AUTOMATION SYSTEM BASED ON MICROCONTROLLER

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MUNA H. SALEH

2017-11-01

Full Text Available This paper presents the development of Global System Mobile (GSM-based control home air-conditioner for home automation system. The main aim of the prototype development is to reduce electricity wastage. GSM module was used for receiving Short Message Service (SMS from the user’s mobile phone that automatically enable the controller to take any further action such as to switch ON and OFF the home air-conditioner. The system controls the air-conditioner based on the temperature reading through the sensor. Every period temperature sensor sends the degree to Micro Controller Unit (MCU through ZigBee. Based on temperature degree MCU send ON or OFF signal to switch. Additionally, system allows user to operate or shut down the airconditioner remotely through SMS.

Brain metabolic impairment of OSAS: evidence from MRS

International Nuclear Information System (INIS)

Shen Jie; Long Miaomiao; Shen Wen; Qi Ji

2011-01-01

Objective: To evaluate the impact of obstructive sleep apnea syndrome (OSAS) on human cerebral metabolism by using magnetic resonance spectroscopy (MRS). Materials and methods: Twenty-one severe OSAS patients, 14 mild-moderate OSAS patients, and 15 healthy control subjects were included. All subjects underwent MRS using the point-resolved echo spin spectroscopy (PRESS). Proton volumes of interest were placed in the bilateral frontal lobes and left temporal -parietal-occipital cortex, and left hippocampus. Results: 1. Compared to the controls, the NAA/Cr ratio was significantly decreased in the left frontal lobe in the severe OSAS group (P=0.004), and in the right frontal lobe in the severe (P=0.002) and mild-moderate (P=0.007) OSAS patients. The NAA/Cr ratio trended to be decreased in the left hippocampus in the OSAS patients compared to controls. 2. A significant increase in the ml/Cr ratio was detected in the right frontal regions in the severe (P=0.008) and mild-moderate (P<0.001) OSAS groups. 3. Clx/Cr ratio values were significantly smaller than controls in the left (P=0.006) and right (P=0.027) frontal regions. Conclusion: Bilateral frontal lobes are the vulnerable location in patients with OSAS. MRS can be used to screen the brain metabolic impairment. (authors)

An Ethical Interpretation of Virginia Woolf's Mrs.Dalloway%An Ethical Interpretation of Virginia Woolf's Mrs. Dalloway

Institute of Scientific and Technical Information of China (English)

朱蕾

2011-01-01

As a stream-of-consciousness novelist,Woolf is usually seen as being far away from social and political reality.This thesis attempts to apply Ethical Literary Criticism to analyze by rereading the text in detail in order to explore the ethical thinking embodied in Woolfs Mrs.Dalloway,exploring those ethical connotations usually ignored by former critics and scholars.

nRC: non-coding RNA Classifier based on structural features.

Science.gov (United States)

Fiannaca, Antonino; La Rosa, Massimo; La Paglia, Laura; Rizzo, Riccardo; Urso, Alfonso

2017-01-01

Non-coding RNA (ncRNA) are small non-coding sequences involved in gene expression regulation of many biological processes and diseases. The recent discovery of a large set of different ncRNAs with biologically relevant roles has opened the way to develop methods able to discriminate between the different ncRNA classes. Moreover, the lack of knowledge about the complete mechanisms in regulative processes, together with the development of high-throughput technologies, has required the help of bioinformatics tools in addressing biologists and clinicians with a deeper comprehension of the functional roles of ncRNAs. In this work, we introduce a new ncRNA classification tool, nRC (non-coding RNA Classifier). Our approach is based on features extraction from the ncRNA secondary structure together with a supervised classification algorithm implementing a deep learning architecture based on convolutional neural networks. We tested our approach for the classification of 13 different ncRNA classes. We obtained classification scores, using the most common statistical measures. In particular, we reach an accuracy and sensitivity score of about 74%. The proposed method outperforms other similar classification methods based on secondary structure features and machine learning algorithms, including the RNAcon tool that, to date, is the reference classifier. nRC tool is freely available as a docker image at https://hub.docker.com/r/tblab/nrc/. The source code of nRC tool is also available at https://github.com/IcarPA-TBlab/nrc.

Development and Evaluation of a Measure of Library Automation.

Science.gov (United States)

Pungitore, Verna L.

1986-01-01

Construct validity and reliability estimates indicate that study designed to measure utilization of automation in public and academic libraries was successful in tentatively identifying and measuring three subdimensions of level of automation: quality of hardware, method of software development, and number of automation specialists. Questionnaire…

Designing of smart home automation system based on Raspberry Pi

International Nuclear Information System (INIS)

Saini, Ravi Prakash; Singh, Bhanu Pratap; Sharma, Mahesh Kumar; Wattanawisuth, Nattapol; Leeprechanon, Nopbhorn

2016-01-01

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning “on” and “off” of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

Designing of smart home automation system based on Raspberry Pi

Energy Technology Data Exchange (ETDEWEB)

Saini, Ravi Prakash; Singh, Bhanu Pratap [B K Birla Institute of Engineering & Technology, Pilani, Rajasthan (India); Sharma, Mahesh Kumar; Wattanawisuth, Nattapol; Leeprechanon, Nopbhorn, E-mail: Dr.N.L@ieee.org [Thammasat University, Rangsit Campus, Pathum Thani (Thailand)

2016-03-09

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning “on” and “off” of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

MRS role in reducing technical uncertainties in geological disposal

International Nuclear Information System (INIS)

Ramspott, L.D.

1990-06-01

A high-level nuclear waste repository has inherent technical uncertainty due to its first-of-a-kind nature and the unprecedented time over which it must function. Three possible technical modifications to the currently planned US high-level nuclear waste system are reviewed in this paper. These modifications would be facilitated by inclusion of a monitored retrievable storage (MRS) in the system. The modifications are (1) an underground MRS at Yucca Mountain, (2) a phased repository, and (3) a ''cold'' repository. These modifications are intended to enhance scientific confidence that a repository system would function satisfactorily despite technical uncertainty. 12 refs

The assessment of fetus in distress using MRI and 1H MRS - based on performed observation

International Nuclear Information System (INIS)

Borowska-Matwiejczuk, K.; Tarasow, E.; Walecki, J.; Lemancewicz, A.; Kubas, B.; Urban, R.

2003-01-01

Hypoxia is one of the basic factor that cause lesions and intrauterine fetus' death. This is why the recognition of early changes before the appearance of irreversible damages should be the main aim of the assessment and monitoring of a fetus. Apart from the methods of the assessment of a fetus' state that have been applied so far, a new non-invasive imaging technique in obstetrics as MR has appeared. This method makes it possible to assess morphologic structures of a brain, and metabolic processes with use of magnetic resonance spectroscopy (MRS). The study was carried out in 20 pregnant women with pregnancy-induced hypertension (11 cases), chronic hypertension (2 cases), gestational diabetes (6 cases) and IUGR (6 cases). The cardiotocography color Doppler flow assessment of umbilical artery and medial cerebral artery were performed. In cases of abnormal cardiotocography, and Doppler examinations suggested ischemic lesions 5 cases of focal ischemic areas in MR and 6 abnormal MRS spectra were demonstrated. (author)

Automation and robotics considerations for a lunar base

Science.gov (United States)

Sliwa, Nancy E.; Harrison, F. Wallace, Jr.; Soloway, Donald I.; Mckinney, William S., Jr.; Cornils, Karin; Doggett, William R.; Cooper, Eric G.; Alberts, Thomas E.

1992-01-01

An envisioned lunar outpost shares with other NASA missions many of the same criteria that have prompted the development of intelligent automation techniques with NASA. Because of increased radiation hazards, crew surface activities will probably be even more restricted than current extravehicular activity in low Earth orbit. Crew availability for routine and repetitive tasks will be at least as limited as that envisioned for the space station, particularly in the early phases of lunar development. Certain tasks are better suited to the untiring watchfulness of computers, such as the monitoring and diagnosis of multiple complex systems, and the perception and analysis of slowly developing faults in such systems. In addition, mounting costs and constrained budgets require that human resource requirements for ground control be minimized. This paper provides a glimpse of certain lunar base tasks as seen through the lens of automation and robotic (A&R) considerations. This can allow a more efficient focusing of research and development not only in A&R, but also in those technologies that will depend on A&R in the lunar environment.

EVALUATING A COMPUTER BASED SKILLS ACQUISITION TRAINER TO CLASSIFY BADMINTON PLAYERS

Directory of Open Access Journals (Sweden)

Minh Vu Huynh

2011-09-01

Full Text Available The aim of the present study was to compare the statistical ability of both neural networks and discriminant function analysis on the newly developed SATB program. Using these statistical tools, we identified the accuracy of the SATB in classifying badminton players into different skill level groups. Forty-one participants, classified as advanced, intermediate, or beginner skilled level, participated in this study. Results indicated neural networks are more effective in predicting group membership, and displayed higher predictive validity when compared to discriminant analysis. Using these outcomes, in conjunction with the physiological and biomechanical variables of the participants, we assessed the authenticity and accuracy of the SATB and commented on the overall effectiveness of the visual based training approach to training badminton athletes

A high resolution chromosome image processor for study purposes, NIRS-1000:CHROMO STUDY, and algorithm developing to classify radiation induced aberrations.

Science.gov (United States)

Yamamoto, M; Hayata, I; Furuta, S

1992-03-01

Since 1989 we have promoted a project to develop an automated scoring system of radiation induced chromosome aberrations. As a first step, a high resolution image processing system for study purposes, NIRS-1000:CHROMO STUDY, has been developed. It is composed of: (1) CHROMO MARKER whose main purpose is to mark on images to make image data base, (2) CHROMO ALGO whose purpose is algorithm development, and (3) METAPHASE RANKER whose purposes are metaphase finding and ranking with a high power objective lens. However, METAPHASE RANKER is presently under development. The system utilizes a high definition video system so as to realize the best spatial resolution that is achievable with an optical microscope using an objective lens (x 100, numerical aperture 1.4). The video camera has 1024 effective scan lines to realize 0.1 microns sampling on a specimen. The system resolution achieved on the hard copy is less than 0.3 microns on a specimen. A preliminary algorithm has been developed to classify the aberrations on the system using projection information of gray level. The preliminary test results on excellent 10 metaphases show that the correct classification ratio is 92.7%, that the detection rate of the aberrations is 83.3% and that the false positive rate is 6.1%.

Literary aesthetics: beauty, the brain, and Mrs. Dalloway.

Science.gov (United States)

Hogan, Patrick Colm

2013-01-01

Empirical research indicates that beauty is in part a matter of prototype approximation. Some research suggests that unanticipated pattern recognition is important as well. This essay begins by briefly outlining an account of beauty based on these factors. It goes on to consider complications. Minor complications include the partial incompatibility of these accounts and the importance of differentiating judgments of beauty from aesthetic response. More serious issues include the relative neglect of literature in neurologically-based discussions of beauty, which tend to focus on music or visual art. There is also a relative neglect of emotion, beyond the reward system. Finally, there is the almost complete absence of the sublime. After considering these problems broadly, the essay turns to Virginia Woolf's Mrs. Dalloway, examining its treatment of beauty and sublimity. The aim of this section is not merely to illuminate Woolf's novel by reference to neuroscientific research. It is equally, perhaps more fully, to expand our neuroscientifically grounded account of aesthetic response by drawing on Woolf's novel. In Mrs. Dalloway, there are gestures toward prototypes and patterns in beauty. But the key features are clearly emotional. Specifically, the emotions at issue in feelings of beauty and sublimity appear to be primarily attachment, on the one hand, and a profound sense of isolation, on the other. Woolf's novel also points us toward other features of aesthetic experience, crucially including the emotion-sharing that is a key function of the production and circulation of art. © 2013 Elsevier B.V. All rights reserved.

Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

Science.gov (United States)

Gutta, Sandeep; Cheng, Qi

2016-03-01

Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

(1)H MRS assessment of hepatic steatosis in overweight children and adolescents

DEFF Research Database (Denmark)

Chabanova, Elizaveta; Bille, Dorthe S; Thisted, Ebbe

2012-01-01

magnetic resonance systems due to limited space. The purpose of this study was to examine the ability of open 1T system to monitor liver fat with proton MRS and to compare hepatic fat fractions (HFFs) obtained using an open 1T system with assessment with 3T proton MRS. METHODS: The study included 23...

Development and verification testing of automation and robotics for assembly of space structures

Science.gov (United States)

Rhodes, Marvin D.; Will, Ralph W.; Quach, Cuong C.

1993-01-01

A program was initiated within the past several years to develop operational procedures for automated assembly of truss structures suitable for large-aperture antennas. The assembly operations require the use of a robotic manipulator and are based on the principle of supervised autonomy to minimize crew resources. A hardware testbed was established to support development and evaluation testing. A brute-force automation approach was used to develop the baseline assembly hardware and software techniques. As the system matured and an operation was proven, upgrades were incorprated and assessed against the baseline test results. This paper summarizes the developmental phases of the program, the results of several assembly tests, the current status, and a series of proposed developments for additional hardware and software control capability. No problems that would preclude automated in-space assembly of truss structures have been encountered. The current system was developed at a breadboard level and continued development at an enhanced level is warranted.

Objective automated quantification of fluorescence signal in histological sections of rat lens.

Science.gov (United States)

Talebizadeh, Nooshin; Hagström, Nanna Zhou; Yu, Zhaohua; Kronschläger, Martin; Söderberg, Per; Wählby, Carolina

2017-08-01

Visual quantification and classification of fluorescent signals is the gold standard in microscopy. The purpose of this study was to develop an automated method to delineate cells and to quantify expression of fluorescent signal of biomarkers in each nucleus and cytoplasm of lens epithelial cells in a histological section. A region of interest representing the lens epithelium was manually demarcated in each input image. Thereafter, individual cell nuclei within the region of interest were automatically delineated based on watershed segmentation and thresholding with an algorithm developed in Matlab™. Fluorescence signal was quantified within nuclei, cytoplasms and juxtaposed backgrounds. The classification of cells as labelled or not labelled was based on comparison of the fluorescence signal within cells with local background. The classification rule was thereafter optimized as compared with visual classification of a limited dataset. The performance of the automated classification was evaluated by asking 11 independent blinded observers to classify all cells (n = 395) in one lens image. Time consumed by the automatic algorithm and visual classification of cells was recorded. On an average, 77% of the cells were correctly classified as compared with the majority vote of the visual observers. The average agreement among visual observers was 83%. However, variation among visual observers was high, and agreement between two visual observers was as low as 71% in the worst case. Automated classification was on average 10 times faster than visual scoring. The presented method enables objective and fast detection of lens epithelial cells and quantification of expression of fluorescent signal with an accuracy comparable with the variability among visual observers. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Identifying and Classifying Mobile Business Models Based on Meta-Synthesis Approach

Directory of Open Access Journals (Sweden)

Porrandokht Niroomand

2012-03-01

Full Text Available The appearance of mobile has provided unique opportunities and fields through the development and creation of businesses and has been able to create the new job opportunities. The current research tries to familiarize entrepreneures who are running the businesses especially in the area of mobile services with business models. These business models can familiarize them for implementing the new ideas and designs since they can enter to business market. Searching in many papers shows that there are no propitiated papers and researches that can identify, categorize and analyze the mobile business models. Consequently, this paper involves innovation. The first part of this paper presents the review about the concepts and theories about the different mobile generations, the mobile commerce and business models. Afterwards, 92 models are compared, interpreted, translated and combined using 33 papers, books based on two different criteria that are expert criterion and kind of product criterion. In the classification of models according to models that are presented by experts, the models are classified based on criteria such as business fields, business partners, the rate of dynamism, the kind of activity, the focus areas, the mobile generations, transparency, the type of operator activities, marketing and advertisements. The models that are classified based on the kind of product have been analyzed and classified at four different areas of mobile commerce including the content production, technology (software and hardware, network and synthetic.

Co-creative design developments for accessibility and home automation

OpenAIRE

Taib, SM; De Coster, R; Sabri Tekantape, E

2017-01-01

The term “Home Automation” can be referred to a networked home, which provides electronically controlled security and convenience for its users. Home automation is also defined as the integration of home-based technology and services for a better quality of living (Quynh, et al., 2012). The main purpose of home automation technologies is to enhance home comfort for everyone through the automation of higher security, domestic tasks and easy communication. Home automation should be able to enha...

Automated detection of heuristics and biases among pathologists in a computer-based system.

Science.gov (United States)

Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

2013-08-01

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.

Optimization-based Method for Automated Road Network Extraction

International Nuclear Information System (INIS)

Xiong, D

2001-01-01

Automated road information extraction has significant applicability in transportation. It provides a means for creating, maintaining, and updating transportation network databases that are needed for purposes ranging from traffic management to automated vehicle navigation and guidance. This paper is to review literature on the subject of road extraction and to describe a study of an optimization-based method for automated road network extraction

A LabVIEW based template for user created experiment automation.

Science.gov (United States)

Kim, D J; Fisk, Z

2012-12-01

We have developed an expandable software template to automate user created experiments. The LabVIEW based template is easily modifiable to add together user created measurements, controls, and data logging with virtually any type of laboratory equipment. We use reentrant sequential selection to implement sequence script making it possible to wrap a long series of the user created experiments and execute them in sequence. Details of software structure and application examples for scanning probe microscope and automated transport experiments using custom built laboratory electronics and a cryostat are described.

A Decision Support Framework for Automated Screening of Diabetic Retinopathy

Directory of Open Access Journals (Sweden)

2006-01-01

Full Text Available The early signs of diabetic retinopathy (DR are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.

Recent advances in agent-based complex automated negotiation

CERN Document Server

Ito, Takayuki; Zhang, Minjie; Fujita, Katsuhide; Robu, Valentin

2016-01-01

This book covers recent advances in Complex Automated Negotiations as a widely studied emerging area in the field of Autonomous Agents and Multi-Agent Systems. The book includes selected revised and extended papers from the 7th International Workshop on Agent-Based Complex Automated Negotiation (ACAN2014), which was held in Paris, France, in May 2014. The book also includes brief introductions about Agent-based Complex Automated Negotiation which are based on tutorials provided in the workshop, and brief summaries and descriptions about the ANAC'14 (Automated Negotiating Agents Competition) competition, where authors of selected finalist agents explain the strategies and the ideas used by them. The book is targeted to academic and industrial researchers in various communities of autonomous agents and multi-agent systems, such as agreement technology, mechanism design, electronic commerce, related areas, as well as graduate, undergraduate, and PhD students working in those areas or having interest in them.

Discrimination of Breast Tumors in Ultrasonic Images by Classifier Ensemble Trained with AdaBoost

Science.gov (United States)

Takemura, Atsushi; Shimizu, Akinobu; Hamamoto, Kazuhiko

In this paper, we propose a novel method for acurate automated discrimination of breast tumors (carcinoma, fibroadenoma, and cyst). We defined 199 features related to diagnositic observations noticed when a doctor judges breast tumors, such as internal echo, shape, and boundary echo. These features included novel features based on a parameter of log-compressed K distribution, which reflect physical characteristics of ultrasonic B-mode imaging. Furthermore, we propose a discrimination method of breast tumors by using an ensemble classifier based on the multi-class AdaBoost algorithm with effective features selection. Verification by analyzing 200 carcinomas, 30 fibroadenomas and 30 cycts showed the usefulness of the newly defined features and the effectiveness of the discrimination by using an ensemble classifier trained by AdaBoost.

Dynamic nuclear polarization and optimal control spatial-selective 13C MRI and MRS

DEFF Research Database (Denmark)

Vinding, Mads Sloth; Laustsen, Christoffer; Maximov, Ivan I.

2013-01-01

. This is achieved through the development of spatial-selective single-shot spiral-readout MRI and MRS experiments combined with dynamic nuclear polarization hyperpolarized [1-13C]pyruvate on a 4.7T pre-clinical MR scanner. The method stands out from related techniques by facilitating anatomic shaped region...

Automated Essay Grading using Machine Learning Algorithm

Science.gov (United States)

Ramalingam, V. V.; Pandian, A.; Chetry, Prateek; Nigam, Himanshu

2018-04-01

Essays are paramount for of assessing the academic excellence along with linking the different ideas with the ability to recall but are notably time consuming when they are assessed manually. Manual grading takes significant amount of evaluator’s time and hence it is an expensive process. Automated grading if proven effective will not only reduce the time for assessment but comparing it with human scores will also make the score realistic. The project aims to develop an automated essay assessment system by use of machine learning techniques by classifying a corpus of textual entities into small number of discrete categories, corresponding to possible grades. Linear regression technique will be utilized for training the model along with making the use of various other classifications and clustering techniques. We intend to train classifiers on the training set, make it go through the downloaded dataset, and then measure performance our dataset by comparing the obtained values with the dataset values. We have implemented our model using java.

Toward automated assessment of health Web page quality using the DISCERN instrument.

Science.gov (United States)

Allam, Ahmed; Schulz, Peter J; Krauthammer, Michael

2017-05-01

As the Internet becomes the number one destination for obtaining health-related information, there is an increasing need to identify health Web pages that convey an accurate and current view of medical knowledge. In response, the research community has created multicriteria instruments for reliably assessing online medical information quality. One such instrument is DISCERN, which measures health Web page quality by assessing an array of features. In order to scale up use of the instrument, there is interest in automating the quality evaluation process by building machine learning (ML)-based DISCERN Web page classifiers. The paper addresses 2 key issues that are essential before constructing automated DISCERN classifiers: (1) generation of a robust DISCERN training corpus useful for training classification algorithms, and (2) assessment of the usefulness of the current DISCERN scoring schema as a metric for evaluating the performance of these algorithms. Using DISCERN, 272 Web pages discussing treatment options in breast cancer, arthritis, and depression were evaluated and rated by trained coders. First, different consensus models were compared to obtain a robust aggregated rating among the coders, suitable for a DISCERN ML training corpus. Second, a new DISCERN scoring criterion was proposed (features-based score) as an ML performance metric that is more reflective of the score distribution across different DISCERN quality criteria. First, we found that a probabilistic consensus model applied to the DISCERN instrument was robust against noise (random ratings) and superior to other approaches for building a training corpus. Second, we found that the established DISCERN scoring schema (overall score) is ill-suited to measure ML performance for automated classifiers. Use of a probabilistic consensus model is advantageous for building a training corpus for the DISCERN instrument, and use of a features-based score is an appropriate ML metric for automated DISCERN

Automated in vivo identification of fungal infection on human scalp using optical coherence tomography and machine learning

Science.gov (United States)

Dubey, Kavita; Srivastava, Vishal; Singh Mehta, Dalip

2018-04-01

Early identification of fungal infection on the human scalp is crucial for avoiding hair loss. The diagnosis of fungal infection on the human scalp is based on a visual assessment by trained experts or doctors. Optical coherence tomography (OCT) has the ability to capture fungal infection information from the human scalp with a high resolution. In this study, we present a fully automated, non-contact, non-invasive optical method for rapid detection of fungal infections based on the extracted features from A-line and B-scan images of OCT. A multilevel ensemble machine model is designed to perform automated classification, which shows the superiority of our classifier to the best classifier based on the features extracted from OCT images. In this study, 60 samples (30 fungal, 30 normal) were imaged by OCT and eight features were extracted. The classification algorithm had an average sensitivity, specificity and accuracy of 92.30, 90.90 and 91.66%, respectively, for identifying fungal and normal human scalps. This remarkable classifying ability makes the proposed model readily applicable to classifying the human scalp.

Automation of program model developing for complex structure control objects

International Nuclear Information System (INIS)

Ivanov, A.P.; Sizova, T.B.; Mikhejkina, N.D.; Sankovskij, G.A.; Tyufyagin, A.N.

1991-01-01

A brief description of software for automated developing the models of integrating modular programming system, program module generator and program module library providing thermal-hydraulic calcualtion of process dynamics in power unit equipment components and on-line control system operation simulation is given. Technical recommendations for model development are based on experience in creation of concrete models of NPP power units. 8 refs., 1 tab., 4 figs

The use of short-echo-time 1H MRS for childhood cerebellar tumours prior to histopathological diagnosis

International Nuclear Information System (INIS)

Harris, Lisa M.; Peet, Andrew C.; Davies, Nigel; Natarajan, Kal; MacPherson, Lesley; Foster, Katharine; Lateef, Shaheen; Sgouros, Spyridon; Brundler, Marie-Anne; Arvanitis, Theodoros N.; Grundy, Richard G.

2007-01-01

Proton magnetic resonance spectroscopy (MRS) measures concentrations of metabolites in vivo and provides a powerful method for identifying tumours. MRS has not entered routine clinical use partly due to the difficulty of analysing the spectra. To create a straightforward method for interpreting short-echo-time MRS of childhood cerebellar tumours. Single-voxel MRS (1.5-T Siemens Symphony NUM4, TR/TE 1,500/30 ms) was performed at presentation in 30 children with cerebellar tumours. The MRS results were analysed for comparison with histological diagnosis. Peak heights for N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mIns) were determined and receiver operator characteristic curves used to select ratios that best discriminated between the tumour types. The method was implemented by a group of clinicians and scientists, blinded to the results. A total of 27 MRS studies met the quality control criteria. NAA/Cr >4.0 distinguished all but one of the astrocytomas from the other tumours. A combination of Cr/Cho <0.75 and mIns/NAA <2.1 separated all the medulloblastomas from the ependymomas. Peak height ratios from short-echo-time MRS can accurately predict the histopathology of childhood cerebellar tumours. (orig.)

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

Science.gov (United States)

Piccinini, Filippo; Balassa, Tamas; Szkalisity, Abel; Molnar, Csaba; Paavolainen, Lassi; Kujala, Kaisa; Buzas, Krisztina; Sarazova, Marie; Pietiainen, Vilja; Kutay, Ulrike; Smith, Kevin; Horvath, Peter

2017-06-28

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org. Copyright © 2017 Elsevier Inc. All rights reserved.

AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

International Nuclear Information System (INIS)

Tsai, Yingssu; McPhillips, Scott E.; González, Ana; McPhillips, Timothy M.; Zinn, Daniel; Cohen, Aina E.; Feese, Michael D.; Bushnell, David; Tiefenbrunn, Theresa; Stout, C. David; Ludaescher, Bertram; Hedman, Britt; Hodgson, Keith O.; Soltis, S. Michael

2013-01-01

New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully

Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.

Science.gov (United States)

Pires, Ramon; Carvalho, Tiago; Spurling, Geoffrey; Goldenstein, Siome; Wainer, Jacques; Luckie, Alan; Jelinek, Herbert F; Rocha, Anderson

2015-01-01

Diabetic Retinopathy (DR) is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.

Combined MRI and MRS improves pre-therapeutic diagnoses of pediatric brain tumors over MRI alone

Energy Technology Data Exchange (ETDEWEB)

Shiroishi, Mark S.; Nelson, Marvin D. [Children' s Hospital Los Angeles/Keck School of Medicine of USC, Department of Radiology, Los Angeles, CA (United States); Panigrahy, Ashok [Children' s Hospital Los Angeles/Keck School of Medicine of USC, Department of Radiology, Los Angeles, CA (United States); Children' s Hospital of Pittsburgh of University of Pittsburgh Medical Center, Department of Pediatric Radiology, Pittsburgh, PA (United States); Moore, Kevin R. [Primary Children' s Medical Center, Department of Radiology, Salt Lake City, UT (United States); Gilles, Floyd H. [Children' s Hospital Los Angeles/Keck School of Medicine of USC, Department of Pathology, Los Angeles, CA (United States); Gonzalez-Gomez, Ignacio [All Children' s Hospital, Department of Pathology, St. Petersburg, FL (United States); Blueml, Stefan [Children' s Hospital Los Angeles/Keck School of Medicine of USC, Department of Radiology, Los Angeles, CA (United States); Rudi Schulte Research Institute, Santa Barbara, CA (United States)

2015-09-15

The specific goal of this study was to determine whether the inclusion of MRS had a measureable and positive impact on the accuracy of pre-surgical MR examinations of untreated pediatric brain tumors over that of MRI alone in clinical practice. Final imaging reports of 120 pediatric patients with newly detected brain tumors who underwent combined MRI/MRS examinations were retrospectively reviewed. Final pathology was available in all cases. Group A comprised 60 subjects studied between June 2001 and January 2005, when MRS was considered exploratory and radiologists utilized only conventional MRI to arrive at a diagnosis. For group B, comprising 60 subjects studied between January 2005 and March 2008, the radiologists utilized information from both MRI and MRS. Furthermore, radiologists revisited group A (blind review, time lapse >4 years) to determine whether the additional information from MRS would have altered their interpretation. Sixty-three percent of patients in group A were diagnosed correctly, whereas in 10 % the report was partially correct with the final tumor type mentioned (but not mentioned as most likely tumor), while in 27 % of cases the reports were wrong. For group B, the diagnoses were correct in 87 %, partially correct in 5 %, and incorrect in 8 % of the cases, which is a significant improvement (p < 0.005). Re-review of combined MRI and MRS of group A resulted 87 % correct, 7 % partially correct, and 7 % incorrect diagnoses, which is a significant improvement over the original diagnoses (p < 0.05). Adding MRS to conventional MRI significantly improved diagnostic accuracy in preoperative pediatric patients with untreated brain tumors. (orig.)

Combined MRI and MRS improves pre-therapeutic diagnoses of pediatric brain tumors over MRI alone

International Nuclear Information System (INIS)

Shiroishi, Mark S.; Nelson, Marvin D.; Panigrahy, Ashok; Moore, Kevin R.; Gilles, Floyd H.; Gonzalez-Gomez, Ignacio; Blueml, Stefan

2015-01-01

The specific goal of this study was to determine whether the inclusion of MRS had a measureable and positive impact on the accuracy of pre-surgical MR examinations of untreated pediatric brain tumors over that of MRI alone in clinical practice. Final imaging reports of 120 pediatric patients with newly detected brain tumors who underwent combined MRI/MRS examinations were retrospectively reviewed. Final pathology was available in all cases. Group A comprised 60 subjects studied between June 2001 and January 2005, when MRS was considered exploratory and radiologists utilized only conventional MRI to arrive at a diagnosis. For group B, comprising 60 subjects studied between January 2005 and March 2008, the radiologists utilized information from both MRI and MRS. Furthermore, radiologists revisited group A (blind review, time lapse >4 years) to determine whether the additional information from MRS would have altered their interpretation. Sixty-three percent of patients in group A were diagnosed correctly, whereas in 10 % the report was partially correct with the final tumor type mentioned (but not mentioned as most likely tumor), while in 27 % of cases the reports were wrong. For group B, the diagnoses were correct in 87 %, partially correct in 5 %, and incorrect in 8 % of the cases, which is a significant improvement (p < 0.005). Re-review of combined MRI and MRS of group A resulted 87 % correct, 7 % partially correct, and 7 % incorrect diagnoses, which is a significant improvement over the original diagnoses (p < 0.05). Adding MRS to conventional MRI significantly improved diagnostic accuracy in preoperative pediatric patients with untreated brain tumors. (orig.)

Methods of physical experiment and installation automation on the base of computers

International Nuclear Information System (INIS)

Stupin, Yu.V.

1983-01-01

Peculiarities of using computers for physical experiment and installation automation are considered. Systems for data acquisition and processing on the base of microprocessors, micro- and mini-computers, CAMAC equipment and real time operational systems as well as systems intended for automation of physical experiments on accelerators and installations of laser thermonuclear fusion and installations for plasma investigation are dpscribed. The problems of multimachine complex and multi-user system, arrangement, development of automated systems for collective use, arrangement of intermachine data exchange and control of experimental data base are discussed. Data on software systems used for complex experimental data processing are presented. It is concluded that application of new computers in combination with new possibilities provided for users by universal operational systems essentially exceeds efficiency of a scientist work

Interface Prostheses With Classifier-Feedback-Based User Training.

Science.gov (United States)

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well

MRS/IS facility co-located with a repository: preconceptual design and life-cycle cost estimates

International Nuclear Information System (INIS)

Smith, R.I.; Nesbitt, J.F.

1982-11-01

A program is described to examine the various alternatives for monitored retrievable storage (MRS) and interim storage (IS) of spent nuclear fuel, solidified high-level waste (HLW), and transuranic (TRU) waste until appropriate geologic repository/repositories are available. The objectives of this study are: (1) to develop a preconceptual design for an MRS/IS facility that would become the principal surface facility for a deep geologic repository when the repository is opened, (2) to examine various issues such as transportation of wastes, licensing of the facility, and environmental concerns associated with operation of such a facility, and (3) to estimate the life cycle costs of the facility when operated in response to a set of scenarios which define the quantities and types of waste requiring storage in specific time periods, which generally span the years from 1990 until 2016. The life cycle costs estimated in this study include: the capital expenditures for structures, casks and/or drywells, storage areas and pads, and transfer equipment; the cost of staff labor, supplies, and services; and the incremental cost of transporting the waste materials from the site of origin to the MRS/IS facility. Three scenarios are examined to develop estimates of life cycle costs of the MRS/IS facility. In the first scenario, HLW canisters are stored, starting in 1990, until the co-located repository is opened in the year 1998. Additional reprocessing plants and repositories are placed in service at various intervals. In the second scenario, spent fuel is stored, starting in 1990, because the reprocessing plants are delayed in starting operations by 10 years, but no HLW is stored because the repositories open on schedule. In the third scenario, HLW is stored, starting in 1990, because the repositories are delayed 10 years, but the reprocessing plants open on schedule

Robotics and Automation Education: Developing the Versatile, Practical Lab.

Science.gov (United States)

Stenerson, Jon

1986-01-01

Elements of the development of a robotics and automation laboratory are discussed. These include the benefits of upgrading current staff, ways to achieve this staff development, formation of a robotics factory automation committee, topics to be taught with a robot, elements of a laboratory, laboratory funding, and design safety. (CT)

Evaluation of the need, feasibility, and siting of the MRS in Tennessee

Energy Technology Data Exchange (ETDEWEB)

Colglazier, E.W. Jr. (Tennessee Univ., Knoxville, TN (United States))

1985-12-16

This summary report outlines the results of an independent assessment of the need, feasibility, and siting of the proposed Monitored Retrievable Storage (MRS) facility. The detailed reports of this assessment are included as appendices to the summary report. The Department of Energy (DOE) has concluded that the MRS is not absolutely necessary, but preferred, in order to manage and move spent fuel from reactors to a repository. The team has attemped to assess need'' by comparing to advantages and disadvantages of various systems, with and without the MRS. Feasibility has been assessed by comparing the technical and economic advantages and disadvantages. The team was not asked to recommend a preferred system. That choice will depend on the importance that are used to compare alternatives. The five key criteria selected by the team for comparing alternate systems were: economic cost, radiological risk, non-radiological transportation impacts, the likelihood of successful implementation and operation of the system, and the likelihood of meeting the schedule in the Nuclear Waste Policy Act. The team compared twelve different systems and modeled the transportation impacts and risks with three repository sites and two MRS sites.

A novel tool for automated evaluation of radiographic weld images

International Nuclear Information System (INIS)

Rajagopalan, C.; Venkatraman, B.; Jayakumar, T.; Kalyanasundaram, P.; Raj, B.

2004-01-01

Radiography is one of the oldest and the most widely used NDT method for the detection of volumetric defects in welds and castings. Once a radiograph of a weld or a casting or an assembly is taken, the radiographer examines the same. The task of the radiographer consists of identifying the defects and quantitatively evaluating the same based on codes and specifications. Radiographic interpretation primarily depends on the expertise of the individual radiographer. To overcome the subjectivity involved in human interpretation, it is thus desirable to develop a computer based automated system to aid in the interpretation of radiographs. Towards this goal, the authors have developed a flowchart chalking out the various stages involved. Typical weld images of tube to tubesheet weld joints were digitised using high resolution digitiser. The images were segmented and 52 invariant moments were computed to be used as features. The results of these are presented in this paper. Once the features (invariant moments) are extracted and ranked, a neural network classifier based on error back-propagation has to classify the (top ranking) features and evaluate the image for acceptance or rejection. (author)

Optimization of automation: III. Development of optimization method for determining automation rate in nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Min; Kim, Jong Hyun; Kim, Man Cheol; Seong, Poong Hyun

2016-01-01

Highlights: • We propose an appropriate automation rate that enables the best human performance. • We analyze the shortest working time considering Situation Awareness Recovery (SAR). • The optimized automation rate is estimated by integrating the automation and ostracism rate estimation methods. • The process to derive the optimized automation rate is demonstrated through case studies. - Abstract: Automation has been introduced in various industries, including the nuclear field, because it is commonly believed that automation promises greater efficiency, lower workloads, and fewer operator errors through reducing operator errors and enhancing operator and system performance. However, the excessive introduction of automation has deteriorated operator performance due to the side effects of automation, which are referred to as Out-of-the-Loop (OOTL), and this is critical issue that must be resolved. Thus, in order to determine the optimal level of automation introduction that assures the best human operator performance, a quantitative method of optimizing the automation is proposed in this paper. In order to propose the optimization method for determining appropriate automation levels that enable the best human performance, the automation rate and ostracism rate, which are estimation methods that quantitatively analyze the positive and negative effects of automation, respectively, are integrated. The integration was conducted in order to derive the shortest working time through considering the concept of situation awareness recovery (SAR), which states that the automation rate with the shortest working time assures the best human performance. The process to derive the optimized automation rate is demonstrated through an emergency operation scenario-based case study. In this case study, four types of procedures are assumed through redesigning the original emergency operating procedure according to the introduced automation and ostracism levels. Using the

Preconceptual design for a Monitored Retrievable Storage (MRS) transfer facility

International Nuclear Information System (INIS)

Woods, W.D.; Jowdy, A.K.; Smith, R.I.

1990-09-01

The contract between the DOE and the utilities specifies that the DOE will receive spent fuel from the nuclear utilities in 1998. This study investigates the feasibility of employing a simple Transfer Facility which can be constructed quickly, and operate while the full-scale MRS facilities are being constructed. The Transfer Facility is a hot cell designed only for the purpose of transferring spent fuel assemblies from the Office of Civilian Radioactive Waste Management (OCRWM) transport casks (shipped from the utility sites) into onsite concrete storage casks. No operational functions other than spent fuel assembly transfers and the associated cask handling, opening, and closing would be performed in this facility. Radioactive waste collected in the Transfer Facility during operations would be stored until the treatment facilities in the full-scale MRS facility became operational, approximately 2 years after the Transfer Facility started operation. An alternate wherein the Transfer Facility was the only waste handling building on the MRS site was also examined and evaluated. 6 figs., 26 tabs

Personal computer based home automation system

OpenAIRE

Hellmuth, George F.

1993-01-01

The systems engineering process is applied in the development of the preliminary design of a home automation communication protocol. The objective of the communication protocol is to provide a means for a personal computer to communicate with adapted appliances in the home. A needs analysis is used to ascertain that a need exist for a home automation system. Numerous design alternatives are suggested and evaluated to determine the best possible protocol design. Coaxial cable...

Retrospective on lessons from 1985 Tennessee MRS attempted siting: The local view

International Nuclear Information System (INIS)

Peelle, E.

1991-01-01

Six years have elapsed since the unsuccessful US Department of Energy (DOE) effort to site a monitored retrievable storage (MRS) facility in Tennessee. The local MRS task force (TF) effort in 1985 has been described extensively in prior publications. These articles described the successful interactions between DOE and the local TF in the context of extensive state and regional opposition. The MRS TF found that while the proposed facility could be safe, many conditions were needed to ensure its long-term safety and to change the net benefit balance from negative to positive. The DOE and the TF reached agreement on many of the TF conditions but were still far apart on others when negotiations ended in 1985. The local governments that had created the TF unanimously accepted its conclusion. The governor of Tennessee eventually vetoed the siting process, and the state sued in 1985 to stop the DOE from continuing its efforts. When Tennessee's legal block was removed in 1987, DOE presented its MRS recommendations to Congress. Two brief periods of activity among the TF and local political leaders included testimony in 1987 before two Congressional committees and before the MRS Study Commission in 1989. This testimony sought those additional conditions for siting the DOE had not given in its negotiations with the TF. The purpose of this paper is to evaluate key points and lessons learned from this path-breaking effort by a local unpaid TF of citizens and elected officials through its entire life until disbanding in 1989

Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

Science.gov (United States)

Raposo, Letícia M; Nobre, Flavio F

2017-08-30

Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

Feature and score fusion based multiple classifier selection for iris recognition.

Science.gov (United States)

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

Directory of Open Access Journals (Sweden)

Md. Rabiul Islam

2014-01-01

Full Text Available The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Automated dating of the world’s language families based on lexical similarity

OpenAIRE

Holman, E.; Brown, C.; Wichmann, S.; Müller, A.; Velupillai, V.; Hammarström, H.; Sauppe, S.; Jung, H.; Bakker, D.; Brown, P.; Belyaev, O.; Urban, M.; Mailhammer, R.; List, J.; Egorov, D.

2011-01-01

This paper describes a computerized alternative to glottochronology for estimating elapsed time since parent languages diverged into daughter languages. The method, developed by the Automated Similarity Judgment Program (ASJP) consortium, is different from glottochronology in four major respects: (1) it is automated and thus is more objective, (2) it applies a uniform analytical approach to a single database of worldwide languages, (3) it is based on lexical similarity as determined from Leve...

Development of design principles for automated systems in transport control.

Science.gov (United States)

Balfe, Nora; Wilson, John R; Sharples, Sarah; Clarke, Theresa

2012-01-01

This article reports the results of a qualitative study investigating attitudes towards and opinions of an advanced automation system currently used in UK rail signalling. In-depth interviews were held with 10 users, key issues associated with automation were identified and the automation's impact on the signalling task investigated. The interview data highlighted the importance of the signallers' understanding of the automation and their (in)ability to predict its outputs. The interviews also covered the methods used by signallers to interact with and control the automation, and the perceived effects on their workload. The results indicate that despite a generally low level of understanding and ability to predict the actions of the automation system, signallers have developed largely successful coping mechanisms that enable them to use the technology effectively. These findings, along with parallel work identifying desirable attributes of automation from the literature in the area, were used to develop 12 principles of automation which can be used to help design new systems which better facilitate cooperative working. The work reported in this article was completed with the active involvement of operational rail staff who regularly use automated systems in rail signalling. The outcomes are currently being used to inform decisions on the extent and type of automation and user interfaces in future generations of rail control systems.

Studying neonatal bilirubin encephalopathy with conventional MRI, MRS, and DWI

International Nuclear Information System (INIS)

Wang, Xiaoyi; Wu, Wulin; Chineah, Ashley; Liu, Fan; Liao, Weihua; Hou, Bob L.; Zhang, Ping

2008-01-01

The purpose of this study was to evaluate the diagnostic value of conventional magnetic resonance imaging (MRI), proton magnetic resonance spectroscopy ( 1 H-MRS), and diffusion-weighted imaging (DWI) for neonatal bilirubin encephalopathy. We collected conventional MRI in 24 neonates with neonatal bilirubin encephalopathy. We performed 1 H-MRS and DWI sequences to nine of the 24 patients and seven age-matched healthy control subjects. Multiple-voxel 1 H-MRS data were acquired using PRESS pulse sequence with TE=135 ms and TR=1500 ms. The spectroscopic regions of interest were the bilateral basal ganglia and thalamus with a 1.0 mL spatial resolution. The data from DWI were collected by using a single shot-spin echo-echo planar imaging sequence with TR/TE: 2900/98, and imaging regions were also focused on the bilateral basal ganglia and thalamus. Nineteen of the 24 patients had abnormal T 1 -weighted image hyperintensity in the globus pallidus, but these lesions appeared as normal T 2 -weighted image intensity in the same region. Ten of the 24 patients had T 1 -weighted image high signal intensity in the subthalamic nucleus and appeared as normal intensity in the region for the T 2 -weighted images. The peak area ratios of NAA/Cho and NAA/Cr were significantly decreased (t-test, P 1 H-MRS are important complementary tools in the diagnosis of neonatal bilirubin encephalopathy. The study provides important information for applying these MR modalities to evaluate neonates with bilirubin encephalopathy. (orig.)

Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier.

Science.gov (United States)

Li, Qiang; Gu, Yu; Jia, Jing

2017-01-30

Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS) and support vector machine (SVM) algorithms in a quartz crystal microbalance (QCM)-based electronic nose (e-nose) we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3%) showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN) classifier (93.3%) and moving average-linear discriminant analysis (MA-LDA) classifier (87.6%). The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization) performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors.

Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier

Directory of Open Access Journals (Sweden)

Qiang Li

2017-01-01

Full Text Available Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS and support vector machine (SVM algorithms in a quartz crystal microbalance (QCM-based electronic nose (e-nose we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3% showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN classifier (93.3% and moving average-linear discriminant analysis (MA-LDA classifier (87.6%. The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors.

Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis

Directory of Open Access Journals (Sweden)

Qu Lijia

2009-03-01

Full Text Available Abstract Background Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public. Results In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion, data reduction (PCA, LDA, ULDA, unsupervised clustering (K-Mean and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM. Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile. Conclusion Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases

Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis.

Science.gov (United States)

Wang, Tao; Shao, Kang; Chu, Qinying; Ren, Yanfei; Mu, Yiming; Qu, Lijia; He, Jie; Jin, Changwen; Xia, Bin

2009-03-16

Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public. In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion), data reduction (PCA, LDA, ULDA), unsupervised clustering (K-Mean) and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM). Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile. Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases. Moreover, with its open source architecture, interested

PHOTOGRAMMETRY-BASED AUTOMATED MEASUREMENTS FOR TOOTH SHAPE AND OCCLUSION ANALYSIS

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V. A. Knyaz

2016-06-01

Full Text Available Tooth measurements (odontometry are performed for various scientific and practical applications, including dentistry. Present-day techniques are being increasingly based on 3D model use that provides wider prospects in comparison to measurements on real objects: teeth or their plaster copies. The main advantages emerge through application of new measurement methods which provide the needed degree of non-invasiveness, precision, convenience and details. Tooth measurements have been always regarded as a time-consuming research, even more so with use of new methods due to their wider opportunities. This is where automation becomes essential for further development and implication of measurement techniques. In our research automation in obtaining 3D models and automation of measurements provided essential data that was analysed to suggest recommendations for tooth preparation – one of the most responsible clinical procedures in prosthetic dentistry – within a comparatively short period of time. The original photogrammetric 3D reconstruction system allows to generate 3D models of dental arches, reproduce their closure, or occlusion, and to perform a set of standard measurement in automated mode.

Photogrammetry-Based Automated Measurements for Tooth Shape and Occlusion Analysis

Science.gov (United States)

Knyaz, V. A.; Gaboutchian, A. V.

2016-06-01

Tooth measurements (odontometry) are performed for various scientific and practical applications, including dentistry. Present-day techniques are being increasingly based on 3D model use that provides wider prospects in comparison to measurements on real objects: teeth or their plaster copies. The main advantages emerge through application of new measurement methods which provide the needed degree of non-invasiveness, precision, convenience and details. Tooth measurements have been always regarded as a time-consuming research, even more so with use of new methods due to their wider opportunities. This is where automation becomes essential for further development and implication of measurement techniques. In our research automation in obtaining 3D models and automation of measurements provided essential data that was analysed to suggest recommendations for tooth preparation - one of the most responsible clinical procedures in prosthetic dentistry - within a comparatively short period of time. The original photogrammetric 3D reconstruction system allows to generate 3D models of dental arches, reproduce their closure, or occlusion, and to perform a set of standard measurement in automated mode.

Application of NUHOMS reg-sign to an integrated MRS/transportation system

International Nuclear Information System (INIS)

Rosa, J.M.; Lehnert, R.A.; Quinn, R.D.

1992-01-01

Storage of spent fuel at reactor sites in weld sealed canisters has been increasing steadily since 1989, with three facilities now having ISFSIs which employ the NUHOMS reg-sign technology. Expansion of existing Independent Spent Fuel Storage Installations (ISFSIs) and implementation of new ones will result in a substantial fraction of the at-reactor spent fuel inventory in dry storage canisters by 1998 and beyond. Since this same technology is readily applicable to the MRS, it is advantageous to transfer canisters directly from the ISFSI to the MRS for storage there without the need to reopen the canisters or rehandle the fuel. A store-only MRS offers the possibility of a simple, economical facility which can more easily be demonstrated to be temporary and environmentally benign. Transportation of an intact canister is feasible in a shipping cask of conventional design that is compatible with existing railcars and railroad interchange rules. The use of canisterized fuel also has advantages for eventual shipment and disposal at the federal repository

Automated classification of eligibility criteria in clinical trials to facilitate patient-trial matching for specific patient populations.

Science.gov (United States)

Zhang, Kevin; Demner-Fushman, Dina

2017-07-01

To develop automated classification methods for eligibility criteria in ClinicalTrials.gov to facilitate patient-trial matching for specific populations such as persons living with HIV or pregnant women. We annotated 891 interventional cancer trials from ClinicalTrials.gov based on their eligibility for human immunodeficiency virus (HIV)-positive patients using their eligibility criteria. These annotations were used to develop classifiers based on regular expressions and machine learning (ML). After evaluating classification of cancer trials for eligibility of HIV-positive patients, we sought to evaluate the generalizability of our approach to more general diseases and conditions. We annotated the eligibility criteria for 1570 of the most recent interventional trials from ClinicalTrials.gov for HIV-positive and pregnancy eligibility, and the classifiers were retrained and reevaluated using these data. On the cancer-HIV dataset, the baseline regex model, the bag-of-words ML classifier, and the ML classifier with named entity recognition (NER) achieved macro-averaged F2 scores of 0.77, 0.87, and 0.87, respectively; the addition of NER did not result in a significant performance improvement. On the general dataset, ML + NER achieved macro-averaged F2 scores of 0.91 and 0.85 for HIV and pregnancy, respectively. The eligibility status of specific patient populations, such as persons living with HIV and pregnant women, for clinical trials is of interest to both patients and clinicians. We show that it is feasible to develop a high-performing, automated trial classification system for eligibility status that can be integrated into consumer-facing search engines as well as patient-trial matching systems. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.

Automated Operations Development for Advanced Exploration Systems

Science.gov (United States)

Haddock, Angie T.; Stetson, Howard

2012-01-01

Automated space operations command and control software development and its implementation must be an integral part of the vehicle design effort. The software design must encompass autonomous fault detection, isolation, recovery capabilities and also provide "single button" intelligent functions for the crew. Development, operations and safety approval experience with the Timeliner system onboard the International Space Station (ISS), which provided autonomous monitoring with response and single command functionality of payload systems, can be built upon for future automated operations as the ISS Payload effort was the first and only autonomous command and control system to be in continuous execution (6 years), 24 hours a day, 7 days a week within a crewed spacecraft environment. Utilizing proven capabilities from the ISS Higher Active Logic (HAL) System, along with the execution component design from within the HAL 9000 Space Operating System, this design paper will detail the initial HAL System software architecture and interfaces as applied to NASA's Habitat Demonstration Unit (HDU) in support of the Advanced Exploration Systems, Autonomous Mission Operations project. The development and implementation of integrated simulators within this development effort will also be detailed and is the first step in verifying the HAL 9000 Integrated Test-Bed Component [2] designs effectiveness. This design paper will conclude with a summary of the current development status and future development goals as it pertains to automated command and control for the HDU.

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

Science.gov (United States)

Broderick, Ron

1997-01-01

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

Comparisons of 13NH3, 18FDG PET and MRS in the presurgical evaluation of intractable epilepsy

International Nuclear Information System (INIS)

Cai Li; Gao Shuo; Li Dacheng; Li Zugui

2004-01-01

Purpose: Surgery offers a high chance of seizure-free outcome in patients with intractable epilepsy. Other than EEG, several functional and morphologic imaging Methods are used to define the spatial seizure origin. Blood flow perfusion and metabolic abnormalities in those patients are well described respectively. Proton MR spectroscopy (MRS) is still in the early stages in the evaluation of epilepsy. Comparisons with 13NH3 perfusion, 18FDG metabolic PET imaging and MRS in the same patients have rarely been documented. The present study was undertaken to compare the merits of 13NH3 PET, 18FDG PET, magnetic resonance imaging (MRI) and MRS for the lateralization of seizure foci. Methods: Preoperative long-term-EEG, Video-EEG, 13NH3 perfusion PET, 18FDG metabolic PET, MRI, MRS and neuropsychological assessment were performed in 15 patients with intractable epilepsy within 2 weeks(mean age=24.8 years, range 4 to 44 years; mean epilepsy duration=11 years, range 2 to 36 years), who received electrocorticography (ECoG). Antiepileptic drug (AED) was stopped taking at least 2 days before PET scanning. 13NH3 and FDG PET was performed in one day and analyzed with a region of interest template. An absolute asymmetry index, |AI|, greater than 0.15 was considered abnormal. 13 subjects were underwent MRS obtained from the hippocampus bilaterally, who had a presumptive temporal seizure focus based on seizure semiology, video-EEG and MRI. Metabolite ratio of NAA/Cho+Cr was calculated from the relative peak height measurements. An NAA/Cho+Cr ratio of 0.72 or less was regarded as abnormal. All the examination Results were compared with EcoG to evaluate their values of seizure foci lateraliaztion. Results: 1. The results were divided into ictal (n=4) and interictal (n= 11) groups. In the ictal group, the sensitivity of 13NH3 PET and 18FDG PET were both 100%(4/4), and 13NH3 PET showed bilateral hippocampus hyperfusion foci in one case. In the interictal group, 13NH3 PET correctly

SVM Classifiers: The Objects Identification on the Base of Their Hyperspectral Features

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Demidova Liliya

2017-01-01

Full Text Available The problem of the objects identification on the base of their hyperspectral features has been considered. It is offered to use the SVM classifiers on the base of the modified PSO algorithm, adapted to specifics of the problem of the objects identification on the base of their hyperspectral features. The results of the objects identification on the base of their hyperspectral features with using of the SVM classifiers have been presented.

A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments

Science.gov (United States)

Jeffrey S. Evans; Andrew T. Hudak

2007-01-01

One prerequisite to the use of light detection and ranging (LiDAR) across disciplines is differentiating ground from nonground returns. The objective was to automatically and objectively classify points within unclassified LiDAR point clouds, with few model parameters and minimal postprocessing. Presented is an automated method for classifying LiDAR returns as ground...

Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences.

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Ali, Safdar; Majid, Abdul

2015-04-01

The diagnostic of human breast cancer is an intricate process and specific indicators may produce negative results. In order to avoid misleading results, accurate and reliable diagnostic system for breast cancer is indispensable. Recently, several interesting machine-learning (ML) approaches are proposed for prediction of breast cancer. To this end, we developed a novel classifier stacking based evolutionary ensemble system "Can-Evo-Ens" for predicting amino acid sequences associated with breast cancer. In this paper, first, we selected four diverse-type of ML algorithms of Naïve Bayes, K-Nearest Neighbor, Support Vector Machines, and Random Forest as base-level classifiers. These classifiers are trained individually in different feature spaces using physicochemical properties of amino acids. In order to exploit the decision spaces, the preliminary predictions of base-level classifiers are stacked. Genetic programming (GP) is then employed to develop a meta-classifier that optimal combine the predictions of the base classifiers. The most suitable threshold value of the best-evolved predictor is computed using Particle Swarm Optimization technique. Our experiments have demonstrated the robustness of Can-Evo-Ens system for independent validation dataset. The proposed system has achieved the highest value of Area Under Curve (AUC) of ROC Curve of 99.95% for cancer prediction. The comparative results revealed that proposed approach is better than individual ML approaches and conventional ensemble approaches of AdaBoostM1, Bagging, GentleBoost, and Random Subspace. It is expected that the proposed novel system would have a major impact on the fields of Biomedical, Genomics, Proteomics, Bioinformatics, and Drug Development. Copyright © 2015 Elsevier Inc. All rights reserved.

Experience in the development of an automated data retrieval system in radiology

International Nuclear Information System (INIS)

Zhakov, I.G.; Kratenok, V.E.; Gorel'ko, K.P.; Leoshkevich, N.V.

1988-01-01

The first version of an automated data retrival system in radiology, radiobiology and oncology has been developed in the Research Institute of Oncology and medical Radiology of the Ministry of Health, Byelorussian Soviet Socialist Republic. The system is realized on the basis of a packet of applied programs of an automated document processing system, computerized data-bases of the All-Union Scienctific and Technical Information Institute and the ES-1022 computer. the system functions in the following modes: 1 - selective propagation of information on 194 fixed requests of users; 2 - personal search in the dialogue mode; 3 - updating of data files. The use of the automated system made it possible to enhance the effectiveness and quality of document search as compared to conventinal forms of operation

MRI and MRS on preserved samples as a tool in fish ecology.

Science.gov (United States)

Bock, Christian; Wermter, Felizitas C; Mintenbeck, Katja

2017-05-01

Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) gain increasing attention and importance as a tool in marine ecology. So far, studies were largely limited to morphological studies, e.g. for the creation of digital libraries. Here, the utility of MRI and MRS for ecologists is tested and exemplified using formalin preserved samples of the Antarctic silverfish, Pleuragramma antarctica. As this species lacks a swim bladder, buoyancy is attained by the deposition of large amounts of lipids that are mainly stored in subcutaneous and intermuscular lipid sacs. In this study MRI and MRS are not only used to study internal morphology, but additionally to investigate functional morphology and to measure parameters of high ecological interest. The data are compared with literature data obtained by means of traditional ecological methods. The results from this study show that MR scans are not only an alternative to histological sections (as shown before), but even allow the visualization of particular features in delicate soft tissues, such as Pleuragramma's lipid sacs. 3D rendering techniques proved to be a useful tool to study organ volumes and lipid content, which usually requires laborious chemical lipid extraction and analysis. Moreover, the application of MRS even allows for an analysis of lipids and fatty acids within lipid sacs, which wouldn't be possible using destructive methods. MRI and MRS, in particular when used in combination, have the capacity to provide useful data on parameters of high ecological relevance and thus have proven to be a highly valuable addition, if not alternative, to the classical methods. Copyright © 2016 Elsevier Inc. All rights reserved.

Patients in assisted automated peritoneal dialysis develop strategies for selfcare

DEFF Research Database (Denmark)

Holch, Kirsten

  Patients in Assisted Automated Peritoneal Dialysis develop strategies for self-care Background: Since 2000 a model for Assisted Automated Peritoneal Dialysis (AAPD) in the patients own home has been developed at Aarhus University Hospital, Skejby. The patient group consists of physically...

Tolerance to missing data using a likelihood ratio based classifier for computer-aided classification of breast cancer

International Nuclear Information System (INIS)

Bilska-Wolak, Anna O; Floyd, Carey E Jr

2004-01-01

While mammography is a highly sensitive method for detecting breast tumours, its ability to differentiate between malignant and benign lesions is low, which may result in as many as 70% of unnecessary biopsies. The purpose of this study was to develop a highly specific computer-aided diagnosis algorithm to improve classification of mammographic masses. A classifier based on the likelihood ratio was developed to accommodate cases with missing data. Data for development included 671 biopsy cases (245 malignant), with biopsy-proved outcome. Sixteen features based on the BI-RADS TM lexicon and patient history had been recorded for the cases, with 1.3 ± 1.1 missing feature values per case. Classifier evaluation methods included receiver operating characteristic and leave-one-out bootstrap sampling. The classifier achieved 32% specificity at 100% sensitivity on the 671 cases with 16 features that had missing values. Utilizing just the seven features present for all cases resulted in decreased performance at 100% sensitivity with average 19% specificity. No cases and no feature data were omitted during classifier development, showing that it is more beneficial to utilize cases with missing values than to discard incomplete cases that cannot be handled by many algorithms. Classification of mammographic masses was commendable at high sensitivity levels, indicating that benign cases could be potentially spared from biopsy

Class-specific Error Bounds for Ensemble Classifiers

Energy Technology Data Exchange (ETDEWEB)

Prenger, R; Lemmond, T; Varshney, K; Chen, B; Hanley, W

2009-10-06

The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missed detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.

Comparative analysis of instance selection algorithms for instance-based classifiers in the context of medical decision support

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Tourassi, Georgia D; Malof, Jordan M

2011-01-01

When constructing a pattern classifier, it is important to make best use of the instances (a.k.a. cases, examples, patterns or prototypes) available for its development. In this paper we present an extensive comparative analysis of algorithms that, given a pool of previously acquired instances, attempt to select those that will be the most effective to construct an instance-based classifier in terms of classification performance, time efficiency and storage requirements. We evaluate seven previously proposed instance selection algorithms and compare their performance to simple random selection of instances. We perform the evaluation using k-nearest neighbor classifier and three classification problems: one with simulated Gaussian data and two based on clinical databases for breast cancer detection and diagnosis, respectively. Finally, we evaluate the impact of the number of instances available for selection on the performance of the selection algorithms and conduct initial analysis of the selected instances. The experiments show that for all investigated classification problems, it was possible to reduce the size of the original development dataset to less than 3% of its initial size while maintaining or improving the classification performance. Random mutation hill climbing emerges as the superior selection algorithm. Furthermore, we show that some previously proposed algorithms perform worse than random selection. Regarding the impact of the number of instances available for the classifier development on the performance of the selection algorithms, we confirm that the selection algorithms are generally more effective as the pool of available instances increases. In conclusion, instance selection is generally beneficial for instance-based classifiers as it can improve their performance, reduce their storage requirements and improve their response time. However, choosing the right selection algorithm is crucial.

Developing an Automated Machine Learning Marine Oil Spill Detection System with Synthetic Aperture Radar

Science.gov (United States)

Pinales, J. C.; Graber, H. C.; Hargrove, J. T.; Caruso, M. J.

2016-02-01

Previous studies have demonstrated the ability to detect and classify marine hydrocarbon films with spaceborne synthetic aperture radar (SAR) imagery. The dampening effects of hydrocarbon discharges on small surface capillary-gravity waves renders the ocean surface "radar dark" compared with the standard wind-borne ocean surfaces. Given the scope and impact of events like the Deepwater Horizon oil spill, the need for improved, automated and expedient monitoring of hydrocarbon-related marine anomalies has become a pressing and complex issue for governments and the extraction industry. The research presented here describes the development, training, and utilization of an algorithm that detects marine oil spills in an automated, semi-supervised manner, utilizing X-, C-, or L-band SAR data as the primary input. Ancillary datasets include related radar-borne variables (incidence angle, etc.), environmental data (wind speed, etc.) and textural descriptors. Shapefiles produced by an experienced human-analyst served as targets (validation) during the training portion of the investigation. Training and testing datasets were chosen for development and assessment of algorithm effectiveness as well as optimal conditions for oil detection in SAR data. The algorithm detects oil spills by following a 3-step methodology: object detection, feature extraction, and classification. Previous oil spill detection and classification methodologies such as machine learning algorithms, artificial neural networks (ANN), and multivariate classification methods like partial least squares-discriminant analysis (PLS-DA) are evaluated and compared. Statistical, transform, and model-based image texture techniques, commonly used for object mapping directly or as inputs for more complex methodologies, are explored to determine optimal textures for an oil spill detection system. The influence of the ancillary variables is explored, with a particular focus on the role of strong vs. weak wind forcing.

Lung Nodule Detection in CT Images using Neuro Fuzzy Classifier

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M. Usman Akram

2013-07-01

Full Text Available Automated lung cancer detection using computer aided diagnosis (CAD is an important area in clinical applications. As the manual nodule detection is very time consuming and costly so computerized systems can be helpful for this purpose. In this paper, we propose a computerized system for lung nodule detection in CT scan images. The automated system consists of two stages i.e. lung segmentation and enhancement, feature extraction and classification. The segmentation process will result in separating lung tissue from rest of the image, and only the lung tissues under examination are considered as candidate regions for detecting malignant nodules in lung portion. A feature vector for possible abnormal regions is calculated and regions are classified using neuro fuzzy classifier. It is a fully automatic system that does not require any manual intervention and experimental results show the validity of our system.

Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.

Directory of Open Access Journals (Sweden)

Ramon Pires

Full Text Available Diabetic Retinopathy (DR is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.

Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement

Directory of Open Access Journals (Sweden)

Hakan Kartal

2018-06-01

Full Text Available Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

Next frontier in agent-based complex automated negotiation

CERN Document Server

Ito, Takayuki; Zhang, Minjie; Robu, Valentin

2015-01-01

This book focuses on automated negotiations based on multi-agent systems. It is intended for researchers and students in various fields involving autonomous agents and multi-agent systems, such as e-commerce tools, decision-making and negotiation support systems, and collaboration tools. The contents will help them to understand the concept of automated negotiations, negotiation protocols, negotiating agents’ strategies, and the applications of those strategies. In this book, some negotiation protocols focusing on the multiple interdependent issues in negotiations are presented, making it possible to find high-quality solutions for the complex agents’ utility functions. This book is a compilation of the extended versions of the very best papers selected from the many that were presented at the International Workshop on Agent-Based Complex Automated Negotiations.

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

Science.gov (United States)

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Automated Systems for Road Safety control in a Developing World ...

African Journals Online (AJOL)

An Automated system was finally designed and developed for road safety control. This Automated system is believed to have the capacity to minimize or eliminate the problems identified in this study on traffic control in a developing world. Key words: drivers, traffic situation information, accident causation, FRSC ...

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

Science.gov (United States)

Hong, Weizhe; Kennedy, Ann; Burgos-Artizzu, Xavier P; Zelikowsky, Moriel; Navonne, Santiago G; Perona, Pietro; Anderson, David J

2015-09-22

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body "pose" of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.

Magnetic resonance spectroscopy (MRS) of vertebral column – an additional tool for evaluation of aggressiveness of vertebral haemangioma like lesion

International Nuclear Information System (INIS)

Jeromel, Miran; Podobnik, Janez

2014-01-01

Most vertebral haemangioma are asymptomatic and discovered incidentally. Sometimes the symptomatic lesions present with radiological signs of aggressiveness and their appearance resemble other aggressive lesions (e.g. solitary plasmacytoma). We present a patient with large symptomatic aggressive haemangioma like lesion in 12 th thoracic vertebra in which a magnetic resonance spectroscopy (MRS) was used to analyse fat content within the lesion. The lesion in affected vertebrae showed low fat content with 33% of fat fraction (%FF). The fat content in non-affected (1 st lumbar) vertebra was as expected for patient’s age (68%). Based on MRS data, the lesion was characterized as an aggressive haemangioma. The diagnosis was confirmed with biopsy, performed during the treatment – percutaneous vertebroplasty. The presented case shows that MRS can be used as an additional tool for evaluation of aggressiveness of vertebral haemangioma like lesions

Development of the automated bunker door by using a microcontroller-system

Science.gov (United States)

Ahmad, M. A.; Leo, K. W.; Mohamad, G. H. P.; Ahmad, A.; Hashim, S. A.; Chulan, R. M.; Baijan, A. H.

2018-01-01

The new low energy electron beam accelerator bunker was designed and built locally to allocate a 500 keV electron beam accelerator at Block 43T in Malaysian Nuclear Agency. This bunker is equipped with a locally made radiation shielding door of 10 tons. Originally, this door is moving manually by a wheel and fitted with a gear system. However, it is still heavy and need longer time to operate it manually. To overcome those issues, a new automated control system has been designed and developed. In this paper, the complete steps and design of automated control system based on the microcontroller (PIC16F84A) is described.

Classifying a Person's Degree of Accessibility From Natural Body Language During Social Human-Robot Interactions.

Science.gov (United States)

McColl, Derek; Jiang, Chuan; Nejat, Goldie

2017-02-01

For social robots to be successfully integrated and accepted within society, they need to be able to interpret human social cues that are displayed through natural modes of communication. In particular, a key challenge in the design of social robots is developing the robot's ability to recognize a person's affective states (emotions, moods, and attitudes) in order to respond appropriately during social human-robot interactions (HRIs). In this paper, we present and discuss social HRI experiments we have conducted to investigate the development of an accessibility-aware social robot able to autonomously determine a person's degree of accessibility (rapport, openness) toward the robot based on the person's natural static body language. In particular, we present two one-on-one HRI experiments to: 1) determine the performance of our automated system in being able to recognize and classify a person's accessibility levels and 2) investigate how people interact with an accessibility-aware robot which determines its own behaviors based on a person's speech and accessibility levels.

Integral Monitored Retrievable Storage (MRS) Facility conceptual design report

International Nuclear Information System (INIS)

1985-09-01

This document, Volume 5 Book 7, contains cost estimate information for a monitored retrievable storage (MRS) facility. Cost estimates are for onsite improvements, waste storage, and offsite improvements for the Clinch River Site

Correlation between MRS and serum PSA in the diagnosis of local recurrence after radical prostatectomy

Directory of Open Access Journals (Sweden)

Ghafuri M

2012-08-01

Full Text Available Background: Multifocality, multicentricity and extension beyond the prostate capsule are all characteristics of prostatic adenocarcinoma that may escape diagnosis by conventional CT scanning or MRI. This study was designed to assess the diagnostic value of magnetic resonance spectroscopy (MRS in prostatic carcinoma and its compatibility with prostatic specific antigen (PSA as the conventional method.Methods: In this cross-sectional study, we recruited 139 patients with previous radical prostatectomy referring to Radiology department of Hazrate-e-Rasul Hospital during the first half of 2011 for the evaluation of local recurrence. Traditionally, local recurrence is defined as serum PSA concentration >0.2 ng/dl. We used 1.5-tesla Siemens Avanto MRI unit with endorectal coil and measured creatine, choline and citrate levels before calculating choline-creatine/citrate ratio. Correlation between MRS findings with PSA concentration was evaluated in regards to the multiple levels of the previously mentioned ratio.Results: Local recurrence was found in 107 (77% patients based on PSA levels. The mean values for serum PSA levels and creatine-choline/citrate ratio were significantly different in patients with and without local recurrence. Creatine-choline/citrate ratios greater than 50, 100 and 150 (as different cut-off points of recurrence were respectively seen in 104, 102 and 97 patients and agreement ratio between MRS and PSA in these levels were 94.1%, 94.4% and 85.1%, respectively. Correlation coefficient between these two methods was 0.481.Conclusion: MRS is a valuable tool for evaluating recurrence inpatients with prostate cancer treated by radical prostatectomy and it is in good agreement with serum PSA levels.

An automated methodology development. [software design for combat simulation

Science.gov (United States)

Hawley, L. R.

1985-01-01

The design methodology employed in testing the applicability of Ada in large-scale combat simulations is described. Ada was considered as a substitute for FORTRAN to lower life cycle costs and ease the program development efforts. An object-oriented approach was taken, which featured definitions of military targets, the capability of manipulating their condition in real-time, and one-to-one correlation between the object states and real world states. The simulation design process was automated by the problem statement language (PSL)/problem statement analyzer (PSA). The PSL/PSA system accessed the problem data base directly to enhance the code efficiency by, e.g., eliminating non-used subroutines, and provided for automated report generation, besides allowing for functional and interface descriptions. The ways in which the methodology satisfied the responsiveness, reliability, transportability, modifiability, timeliness and efficiency goals are discussed.

Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification

Directory of Open Access Journals (Sweden)

Stefan Dech

2012-09-01

Full Text Available We present a novel and innovative automated processing environment for the derivation of land cover (LC and land use (LU information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS, as introduced by the Open Geospatial Consortium (OGC, are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective.

NASA space station automation: AI-based technology review. Executive summary

Science.gov (United States)

Firschein, O.; Georgeff, M. P.; Park, W.; Cheeseman, P. C.; Goldberg, J.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

1985-01-01

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics.

System description of the Basic MRS System for the FY 1990 Systems Integration Program studies

International Nuclear Information System (INIS)

McKee, R.W.; Young, J.R.; Konzek, G.J.

1991-07-01

This document provides both functional and physical descriptions of a conceptual high-level waste management system defined as a Basic MRS System. Its purpose is to provide a basis for required system computer modeling and system studies initiated in FY 1990 under the Systems Integration Program of the Office of Civilian Radioactive Waste Management Office (OCRWM). Two specific systems studies initiated in FY 1990, the Reference System Performance Evaluation and the Aggregate Receipt Rate Study, utilize the information in this document. The Basic MRS System is the current OCRWM reference high-level radioactive wastes repository system concept. It is designed to accept 3000 MTU per year of spent fuel and 400 equivalent MTU per year of high-level wastes. The Basic MRS System includes a storage-only MRS that provides for a limited amount of commercial spent fuel storage capacity prior to acceptance by the geologic repository for disposal. This document contains both functional descriptions of the processes in the waste management system and physical descriptions of the equipment and facilities necessary for performance of those processes. The basic MRS system contains all system components, from the waste storage facilities of the waste generators to the underground facilities for final disposal of the wastes. The major facilities in the system are the waste generator waste storage facilities, an MRS facility that provides interim storage wastes accepted from the waste generators, a repository facility that packages the wastes and then emplaces them in the geologic repository, and the transportation equipment and facilities for transporting the waste between these major facilities

Automation in Warehouse Development

NARCIS (Netherlands)

Hamberg, R.; Verriet, J.

2012-01-01

The warehouses of the future will come in a variety of forms, but with a few common ingredients. Firstly, human operational handling of items in warehouses is increasingly being replaced by automated item handling. Extended warehouse automation counteracts the scarcity of human operators and

LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

OpenAIRE

M. Favorskaya; A. Nosov; A. Popov

2015-01-01

Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin dete...

Detection of microaneurysms in retinal images using an ensemble classifier

Directory of Open Access Journals (Sweden)

M.M. Habib

2017-01-01

Full Text Available This paper introduces, and reports on the performance of, a novel combination of algorithms for automated microaneurysm (MA detection in retinal images. The presence of MAs in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR which is one of the leading causes of blindness amongst the working age population. An extensive survey of the literature is presented and current techniques in the field are summarised. The proposed technique first detects an initial set of candidates using a Gaussian Matched Filter and then classifies this set to reduce the number of false positives. A Tree Ensemble classifier is used with a set of 70 features (the most commons features in the literature. A new set of 32 MA groundtruth images (with a total of 256 labelled MAs based on images from the MESSIDOR dataset is introduced as a public dataset for benchmarking MA detection algorithms. We evaluate our algorithm on this dataset as well as another public dataset (DIARETDB1 v2.1 and compare it against the best available alternative. Results show that the proposed classifier is superior in terms of eliminating false positive MA detection from the initial set of candidates. The proposed method achieves an ROC score of 0.415 compared to 0.2636 achieved by the best available technique. Furthermore, results show that the classifier model maintains consistent performance across datasets, illustrating the generalisability of the classifier and that overfitting does not occur.

DEVELOPMENT OF AUTOMATED SYSTEM OF CLIMATE CONDITIONS MANAGEMENT

Directory of Open Access Journals (Sweden)

Novikova L.V.

2017-12-01

Full Text Available The scientific work is devoted to the analysis and development of the automated control system of the climatic conditions of the minites. The analysis of existing automated control systems is carried out, in particular attention is paid to the systems of climate control of greenhouses. The technical means of the control system are determined. As a platform, Arduino®Uno is selected.

A support vector machine (SVM) based voltage stability classifier

Energy Technology Data Exchange (ETDEWEB)

Dosano, R.D.; Song, H. [Kunsan National Univ., Kunsan, Jeonbuk (Korea, Republic of); Lee, B. [Korea Univ., Seoul (Korea, Republic of)

2007-07-01

Power system stability has become even more complex and critical with the advent of deregulated energy markets and the growing desire to completely employ existing transmission and infrastructure. The economic pressure on electricity markets forces the operation of power systems and components to their limit of capacity and performance. System conditions can be more exposed to instability due to greater uncertainty in day to day system operations and increase in the number of potential components for system disturbances potentially resulting in voltage stability. This paper proposed a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. It described the procedure for fast classification of long-term voltage stability using the SVM algorithm. The application of the SVM based voltage stability classifier was presented with reference to the choice of input parameters; input data preconditioning; moving window for feature vector; determination of learning samples; and other considerations in SVM applications. The paper presented a case study with numerical examples of an 11-bus test system. The test results for the feasibility study demonstrated that the classifier could offer an excellent performance in classification with time-series measurements in terms of long-term voltage stability. 9 refs., 14 figs.

Quality management in in vivo proton MRS.

Science.gov (United States)

Pedrosa de Barros, Nuno; Slotboom, Johannes

2017-07-15

The quality of MR-Spectroscopy data can easily be affected in in vivo applications. Several factors may produce signal artefacts, and often these are not easily detected, not even by experienced spectroscopists. Reliable and reproducible in vivo MRS-data requires the definition of quality requirements and goals, implementation of measures to guarantee quality standards, regular control of data quality, and a continuous search for quality improvement. The first part of this review includes a general introduction to different aspects of quality management in MRS. It is followed by the description of a series of tests and phantoms that can be used to assure the quality of the MR system. In the third part, several methods and strategies used for quality control of the spectroscopy data are presented. This review concludes with a reference to a few interesting techniques and aspects that may help to further improve the quality of in vivo MR-spectra. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated mapping of soybean and corn using phenology

Science.gov (United States)

Zhong, Liheng; Hu, Lina; Yu, Le; Gong, Peng; Biging, Gregory S.

2016-09-01

For the two of the most important agricultural commodities, soybean and corn, remote sensing plays a substantial role in delivering timely information on the crop area for economic, environmental and policy studies. Traditional long-term mapping of soybean and corn is challenging as a result of the high cost of repeated training data collection, the inconsistency in image process and interpretation, and the difficulty of handling the inter-annual variability of weather and crop progress. In this study, we developed an automated approach to map soybean and corn in the state of Paraná, Brazil for crop years 2010-2015. The core of the approach is a decision tree classifier with rules manually built based on expert interaction for repeated use. The automated approach is advantageous for its capacity of multi-year mapping without the need to re-train or re-calibrate the classifier. Time series MODerate-resolution Imaging Spectroradiometer (MODIS) reflectance product (MCD43A4) were employed to derive vegetation phenology to identify soybean and corn based on crop calendar. To deal with the phenological similarity between soybean and corn, the surface reflectance of the shortwave infrared band scaled to a phenological stage was used to fully separate the two crops. Results suggested that the mapped areas of soybean and corn agreed with official statistics at the municipal level. The resultant map in the crop year 2012 was evaluated using an independent reference data set, and the overall accuracy and Kappa coefficient were 87.2% and 0.804 respectively. As a result of mixed pixel effect at the 500 m resolution, classification results were biased depending on topography. In the flat, broad and highly-cropped areas, uncultivated lands were likely to be identified as soybean or corn, causing over-estimation of cropland area. By contrast, scattered crop fields in mountainous regions with dense natural vegetation tend to be overlooked. For future mapping efforts, it has great

MRS2016: Rigid Moon Rotation Series in the Relativistic Approximation

Science.gov (United States)

Pashkevich, V. V.

2017-03-01

The rigid Moon rotation problem is studied for the relativistic (kinematical) case, in which the geodetic perturbations in the Moon rotation are taken into account. As the result of this research the high-precision Moon Rotation Series MRS2016 in the relativistic approximation was constructed for the first time and the discrepancies between the high-precision numerical and the semi-analytical solutions of the rigid Moon rotation were investigated with respect to the fixed ecliptic of epoch J2000, by the numerical and analytical methods. The residuals between the numerical solution and MRS2016 in the perturbing terms of the physical librations do not exceed 80 mas and 10 arc seconds over 2000 and 6000 years, respectively.

Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing

Science.gov (United States)

Ballangan, Cherry; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Feng, Dagan

2010-03-01

We propose an automated lung tumor segmentation method for whole body PET images based on a novel downhill region growing (DRG) technique, which regards homogeneous tumor hotspots as 3D monotonically decreasing functions. The method has three major steps: thoracic slice extraction with K-means clustering of the slice features; hotspot segmentation with DRG; and decision tree analysis based hotspot classification. To overcome the common problem of leakage into adjacent hotspots in automated lung tumor segmentation, DRG employs the tumors' SUV monotonicity features. DRG also uses gradient magnitude of tumors' SUV to improve tumor boundary definition. We used 14 PET volumes from patients with primary NSCLC for validation. The thoracic region extraction step achieved good and consistent results for all patients despite marked differences in size and shape of the lungs and the presence of large tumors. The DRG technique was able to avoid the problem of leakage into adjacent hotspots and produced a volumetric overlap fraction of 0.61 +/- 0.13 which outperformed four other methods where the overlap fraction varied from 0.40 +/- 0.24 to 0.59 +/- 0.14. Of the 18 tumors in 14 NSCLC studies, 15 lesions were classified correctly, 2 were false negative and 15 were false positive.

Automation synthesis modules review

International Nuclear Information System (INIS)

Boschi, S.; Lodi, F.; Malizia, C.; Cicoria, G.; Marengo, M.

2013-01-01

The introduction of 68 Ga labelled tracers has changed the diagnostic approach to neuroendocrine tumours and the availability of a reliable, long-lived 68 Ge/ 68 Ga generator has been at the bases of the development of 68 Ga radiopharmacy. The huge increase in clinical demand, the impact of regulatory issues and a careful radioprotection of the operators have boosted for extensive automation of the production process. The development of automated systems for 68 Ga radiochemistry, different engineering and software strategies and post-processing of the eluate were discussed along with impact of automation with regulations. - Highlights: ► Generators availability and robust chemistry boosted for the huge diffusion of 68Ga radiopharmaceuticals. ► Different technological approaches for 68Ga radiopharmaceuticals will be discussed. ► Generator eluate post processing and evolution to cassette based systems were the major issues in automation. ► Impact of regulations on the technological development will be also considered

Automated assessment of cognitive health using smart home technologies.

Science.gov (United States)

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2013-01-01

The goal of this work is to develop intelligent systems to monitor the wellbeing of individuals in their home environments. This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve=0.80, g-mean=0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained.

Exploratory analysis of methods for automated classification of laboratory test orders into syndromic groups in veterinary medicine.

Directory of Open Access Journals (Sweden)

Fernanda C Dórea

Full Text Available BACKGROUND: Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes--syndromic surveillance--using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users. METHODS: This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory. RESULTS: High performance (F1-macro = 0.9995 was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F(1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F(1-macro, due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F(1-micro score of 0.923 (falling to 0.311 when classes are given equal weight. A Naïve Bayes classifier learned all classes and achieved high performance (F(1-micro= 0.994 and F(1-macro = .955, however the classification process is not transparent to the domain experts. CONCLUSION: The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish

An automation of physics research on base of open standards

International Nuclear Information System (INIS)

Smirnov, V.A.

1997-01-01

A wide range of problems is considered concerning an automation of Laboratory of High Energies, JINR set-ups oriented to carry out the experimental researches in high energy and relativistic nuclear physics. Electronics of discussed automation systems is performed in open standards. Main peculiarities in the creation process of automation tools for experimental set-ups, stands and accelerators are shown. Some possibilities to build some accelerator control subsystems on base of industrial automation methods and techniques are discussed

Magnetic Resonance Imaging (MRI and Spectroscopy (MRS in Breast Cancer

Directory of Open Access Journals (Sweden)

Uma Sharma

2008-01-01

Full Text Available Breast cancer is a major health problem in women and early detection is of prime importance. Breast magnetic resonance imaging (MRI provides both physical and physiologic tissue features that are useful in discriminating malignant from benign lesions. Contrast enhanced MRI is valuable for diagnosis of small tumors in dense breast and the structural and kinetic parameters improved the specificity of diagnosing benign from malignant lesions. It is a complimentary modality for preoperative staging, to follow response to therapy, to detect recurrences and for screening high risk women. Diffusion, perfusion and MR elastography have been applied to breast lesion characterization and show promise.In-vivo MR spectroscopy (MRS is a valuable method to obtain the biochemical status of normal and diseased tissues. Malignant tissues contain high concentration of choline containing compounds that can be used as a biochemical marker. MRS helps to increase the specificity of MRI in lesions larger than 1cm and to monitor the tumor response. Various MR techniques show promise primarily as adjunct to the existing standard detection techniques, and its acceptability as a screening method will increase if specificity can be improved. This review presents the progress made in different MRI and MRS techniques in breast cancer management.

Magnetic Resonance Imaging (MRI and Spectroscopy (MRS in Breast Cancer

Directory of Open Access Journals (Sweden)

Uma Sharma

2008-01-01

Full Text Available Breast cancer is a major health problem in women and early detection is of prime importance. Breast magnetic resonance imaging (MRI provides both physical and physiologic tissue features that are useful in discriminating malignant from benign lesions. Contrast enhanced MRI is valuable for diagnosis of small tumors in dense breast and the structural and kinetic parameters improved the specificity of diagnosing benign from malignant lesions. It is a complimentary modality for preoperative staging, to follow response to therapy, to detect recurrences and for screening high risk women. Diffusion, perfusion and MR elastography have been applied to breast lesion characterization and show promise. In-vivo MR spectroscopy (MRS is a valuable method to obtain the biochemical status of normal and diseased tissues. Malignant tissues contain high concentration of choline containing compounds that can be used as a biochemical marker. MRS helps to increase the specificity of MRI in lesions larger than 1cm and to monitor the tumor response. Various MR techniques show promise primarily as adjunct to the existing standard detection techniques, and its acceptability as a screening method will increase if specificity can be improved. This review presents the progress made in different MRI and MRS techniques in beast cancer management.

In vivo hepatic lipid quantification using MRS at 7 Tesla in a mouse model of glycogen storage disease type 1a.

Science.gov (United States)

Ramamonjisoa, Nirilanto; Ratiney, Helene; Mutel, Elodie; Guillou, Herve; Mithieux, Gilles; Pilleul, Frank; Rajas, Fabienne; Beuf, Olivier; Cavassila, Sophie

2013-07-01

The assessment of liver lipid content and composition is needed in preclinical research to investigate steatosis and steatosis-related disorders. The purpose of this study was to quantify in vivo hepatic fatty acid content and composition using a method based on short echo time proton magnetic resonance spectroscopy (MRS) at 7 Tesla. A mouse model of glycogen storage disease type 1a with inducible liver-specific deletion of the glucose-6-phosphatase gene (L-G6pc(-/-)) mice and control mice were fed a standard diet or a high-fat/high-sucrose (HF/HS) diet for 9 months. In control mice, hepatic lipid content was found significantly higher with the HF/HS diet than with the standard diet. As expected, hepatic lipid content was already elevated in L-G6pc(-/-) mice fed a standard diet compared with control mice. L-G6pc(-/-) mice rapidly developed steatosis which was not modified by the HF/HS diet. On the standard diet, estimated amplitudes from olefinic protons were found significantly higher in L-G6pc(-/-) mice compared with that in control mice. L-G6pc(-/-) mice showed no noticeable polyunsaturation from diallylic protons. Total unsaturated fatty acid indexes measured by gas chromatography were in agreement with MRS measurements. These results showed the great potential of high magnetic field MRS to follow the diet impact and lipid alterations in mouse liver.

Correlation Dimension-Based Classifier

Czech Academy of Sciences Publication Activity Database

Jiřina, Marcel; Jiřina jr., M.

2014-01-01

Roč. 44, č. 12 (2014), s. 2253-2263 ISSN 2168-2267 R&D Projects: GA MŠk(CZ) LG12020 Institutional support: RVO:67985807 Keywords : classifier * multidimensional data * correlation dimension * scaling exponent * polynomial expansion Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.469, year: 2014

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers

Directory of Open Access Journals (Sweden)

Ting Shu

2017-01-01

Full Text Available At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Automated subsystems control development. [for life support systems of space station

Science.gov (United States)

Block, R. F.; Heppner, D. B.; Samonski, F. H., Jr.; Lance, N., Jr.

1985-01-01

NASA has the objective to launch a Space Station in the 1990s. It has been found that the success of the Space Station engineering development, the achievement of initial operational capability (IOC), and the operation of a productive Space Station will depend heavily on the implementation of an effective automation and control approach. For the development of technology needed to implement the required automation and control function, a contract entitled 'Automated Subsystems Control for Life Support Systems' (ASCLSS) was awarded to two American companies. The present paper provides a description of the ASCLSS program. Attention is given to an automation and control architecture study, a generic automation and control approach for hardware demonstration, a standard software approach, application of Air Revitalization Group (ARG) process simulators, and a generic man-machine interface.

Demonstration of automated robotic workcell for hazardous waste characterization

International Nuclear Information System (INIS)

Holliday, M.; Dougan, A.; Gavel, D.; Gustaveson, D.; Johnson, R.; Kettering, B.; Wilhelmsen, K.

1993-02-01

An automated robotic workcell to classify hazardous waste stream items with previously unknown characteristics has been designed, tested and demonstrated The object attributes being quantified are radiation signature, metal content, and object orientation and volume. The multi sensor information is used to make segregation decisions plus do automatic grasping of objects. The work-cell control program uses an off-line programming system by Cimetrix Inc. as a server to do both simulation control as well as actual hardware control of the workcell. This paper will discuss the overall workcell layout, sensor specifications, workcell supervisory control, 2D vision based automated grasp planning and object classification algorithms

Safeguards and security design guidelines for conceptual monitored retrievable storage (MRS) facilities

International Nuclear Information System (INIS)

Byers, K.R.; Clark, R.G.; Harms, N.L.; Roberts, F.P.

1984-07-01

Existing safeguards/security regulations and licensing requirements that may be applicable to an MRS facility are not currently well-defined. Protection requirements consistent with the NRC-graded safeguards approach are identified, as a baseline safeguards system with a comparison of the impacts on safeguards and security of salient features of the different storage concepts. In addition, MRS facility design features and operational considerations are proposed that would enhance facility protection and provide additional assurance that protection systems and procedures would be effectively implemented. 3 figures

The Truth and Reconciliation Commission and gender: The Testimony of Mrs Konile revisited

Directory of Open Access Journals (Sweden)

Sandiswa L. Kobe

2017-12-01

Full Text Available This article draws on a well-known narration of the Gugulethu Seven incident from the Truth and Reconciliation Commission (TRC proceedings with specific reference to testimonies of the mothers of the Gugulethu Seven. The article focuses on Mrs Konile’s testimony as a case study: Testimony of a black woman whose son was murdered by the apartheid government’s security forces. During the TRC hearings, Mrs Konile ‘failed’ to effectively narrate her story, which resulted in her testimony being dismissed as being incoherent. This article examines the underlying attributes of Mrs Konile’s testimony and revisits why she was considered ‘incapable’ of articulating her experience in a convincing manner. The analysis aims to acknowledge, identify and give insights about this woman’s testimony from an African women theologian viewpoint (specifically with references to the Isixhosa religious cultural background.

Policy challenges of increasing automation in driving

Directory of Open Access Journals (Sweden)

Ata M. Khan

2012-03-01

Full Text Available The convergence of information and communication technologies (ICT with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010, future developments in the medium term (level II 2010–2025 are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025+ scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.

Phosphorus MRS study in bone and soft-tissue tumors

International Nuclear Information System (INIS)

Du Xiangke; Jiang Baoguo

2000-01-01

Objective: To study the metabolite changes in bone and soft-tissue tumors using phosphorus MRS for better understanding of the phospholipid metabolite and energy metabolite of tumors, which will provide more information for clinical diagnosis and therapy. Methods: Phosphorus MRS and MRI were performed in 14 bone and soft-tissue tumor patients (benign 6, malignant 8) and 19 healthy volunteers at 2.0 T. The areas under the peak of various metabolite in spectra were measured. The ratios of the other metabolite related to β-ATP, ATP, and Pcr were calculated. Intracellular pH was calculated according to the chemical shift change of Pi relative to Pcr. Results: The ratio of PME/β-ATP, PME/ATP, Pcr/PME in both benign and malignant group, intracellular pH in malignant group and LEP/Pcr in benign group were higher than that of the normal group significantly (P < 0.01). the ratios of Pi/Pcr in benign and malignant group, PDE/ATP, PDE/β-ATP, LET/Pcr, Pi/β-ATP in malignant group and LET/β-ATP in benign group were significantly different from that of the normal group (P < 0.05). Between benign and malignant tumors group, the ratios of Pcr/PME and Intracellular pH were different significantly (P < 0.05). Conclusion: The in vivo phosphorus MRS can non-invasively find abnormal phospholipid metabolite, energy metabolite and pH changes in bone and soft tissue tumors

Efficient full decay inversion of MRS data with a stretched-exponential approximation of the ? distribution

Science.gov (United States)

Behroozmand, Ahmad A.; Auken, Esben; Fiandaca, Gianluca; Christiansen, Anders Vest; Christensen, Niels B.

2012-08-01

We present a new, efficient and accurate forward modelling and inversion scheme for magnetic resonance sounding (MRS) data. MRS, also called surface-nuclear magnetic resonance (surface-NMR), is the only non-invasive geophysical technique that directly detects free water in the subsurface. Based on the physical principle of NMR, protons of the water molecules in the subsurface are excited at a specific frequency, and the superposition of signals from all protons within the excited earth volume is measured to estimate the subsurface water content and other hydrological parameters. In this paper, a new inversion scheme is presented in which the entire data set is used, and multi-exponential behaviour of the NMR signal is approximated by the simple stretched-exponential approach. Compared to the mono-exponential interpretation of the decaying NMR signal, we introduce a single extra parameter, the stretching exponent, which helps describe the porosity in terms of a single relaxation time parameter, and helps to determine correct initial amplitude and relaxation time of the signal. Moreover, compared to a multi-exponential interpretation of the MRS data, the decay behaviour is approximated with considerably fewer parameters. The forward response is calculated in an efficient numerical manner in terms of magnetic field calculation, discretization and integration schemes, which allows fast computation while maintaining accuracy. A piecewise linear transmitter loop is considered for electromagnetic modelling of conductivities in the layered half-space providing electromagnetic modelling of arbitrary loop shapes. The decaying signal is integrated over time windows, called gates, which increases the signal-to-noise ratio, particularly at late times, and the data vector is described with a minimum number of samples, that is, gates. The accuracy of the forward response is investigated by comparing a MRS forward response with responses from three other approaches outlining

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel based ‘mouse pup syllable classification calculator’

Directory of Open Access Journals (Sweden)

Jasmine eGrimsley

2013-01-01

Full Text Available Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified ten syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

Resting functional imaging tools (MRS, SPECT, PET and PCT)

NARCIS (Netherlands)

van der Naalt, Joukje; Grafman, Jordan; Salazar, Andres M

2015-01-01

Functional imaging includes imaging techniques that provide information about the metabolic and hemodynamic status of the brain. Most commonly applied functional imaging techniques in patients with traumatic brain injury (TBI) include magnetic resonance spectroscopy (MRS), single photon emission

Automated Scoring of L2 Spoken English with Random Forests

Science.gov (United States)

Kobayashi, Yuichiro; Abe, Mariko

2016-01-01

The purpose of the present study is to assess second language (L2) spoken English using automated scoring techniques. Automated scoring aims to classify a large set of learners' oral performance data into a small number of discrete oral proficiency levels. In automated scoring, objectively measurable features such as the frequencies of lexical and…

Finger vein identification using fuzzy-based k-nearest centroid neighbor classifier

Science.gov (United States)

Rosdi, Bakhtiar Affendi; Jaafar, Haryati; Ramli, Dzati Athiar

2015-02-01

In this paper, a new approach for personal identification using finger vein image is presented. Finger vein is an emerging type of biometrics that attracts attention of researchers in biometrics area. As compared to other biometric traits such as face, fingerprint and iris, finger vein is more secured and hard to counterfeit since the features are inside the human body. So far, most of the researchers focus on how to extract robust features from the captured vein images. Not much research was conducted on the classification of the extracted features. In this paper, a new classifier called fuzzy-based k-nearest centroid neighbor (FkNCN) is applied to classify the finger vein image. The proposed FkNCN employs a surrounding rule to obtain the k-nearest centroid neighbors based on the spatial distributions of the training images and their distance to the test image. Then, the fuzzy membership function is utilized to assign the test image to the class which is frequently represented by the k-nearest centroid neighbors. Experimental evaluation using our own database which was collected from 492 fingers shows that the proposed FkNCN has better performance than the k-nearest neighbor, k-nearest-centroid neighbor and fuzzy-based-k-nearest neighbor classifiers. This shows that the proposed classifier is able to identify the finger vein image effectively.

An ontology for automated scenario-based training

NARCIS (Netherlands)

Peeters, M.M.M.; Bosch, K. van den; Neerincx, M.A.; Meyer, J.J.Ch.

2014-01-01

An intelligent system for automated scenario-based training (SBT) needs knowledge about the training domain, events taking place in the simulated environment, the behaviour of the participating characters, and teaching strategies for effective learning. This knowledge base should be theoretically

Automated detection of fundus photographic red lesions in diabetic retinopathy.

Science.gov (United States)

Larsen, Michael; Godt, Jannik; Larsen, Nicolai; Lund-Andersen, Henrik; Sjølie, Anne Katrin; Agardh, Elisabet; Kalm, Helle; Grunkin, Michael; Owens, David R

2003-02-01

To compare a fundus image-analysis algorithm for automated detection of hemorrhages and microaneurysms with visual detection of retinopathy in patients with diabetes. Four hundred fundus photographs (35-mm color transparencies) were obtained in 200 eyes of 100 patients with diabetes who were randomly selected from the Welsh Community Diabetic Retinopathy Study. A gold standard reference was defined by classifying each patient as having or not having diabetic retinopathy based on overall visual grading of the digitized transparencies. A single-lesion visual grading was made independently, comprising meticulous outlining of all single lesions in all photographs and used to develop the automated red lesion detection system. A comparison of visual and automated single-lesion detection in replicating the overall visual grading was then performed. Automated red lesion detection demonstrated a specificity of 71.4% and a resulting sensitivity of 96.7% in detecting diabetic retinopathy when applied at a tentative threshold setting for use in diabetic retinopathy screening. The accuracy of 79% could be raised to 85% by adjustment of a single user-supplied parameter determining the balance between the screening priorities, for which a considerable range of options was demonstrated by the receiver-operating characteristic (area under the curve 90.3%). The agreement of automated lesion detection with overall visual grading (0.659) was comparable to the mean agreement of six ophthalmologists (0.648). Detection of diabetic retinopathy by automated detection of single fundus lesions can be achieved with a performance comparable to that of experienced ophthalmologists. The results warrant further investigation of automated fundus image analysis as a tool for diabetic retinopathy screening.

MR spectroscopy (MRS) and magnetisation transfer imaging (MTI), lesion load and clinical scores in early relapsing remitting multiple sclerosis: a combined cross-sectional and longitudinal study

International Nuclear Information System (INIS)

Bellmann-Strobl, J.; Paul, F.; Aktas, O.; Zipp, F.; Stiepani, H.; Bohner, G.; Klingebiel, R.; Wuerfel, J.; Warmuth, C.; Wandinger, K.P.

2009-01-01

The purpose of this study was to correlate magnetic resonance imaging (MRI)-based lesion load assessment with clinical disability in early relapsing remitting multiple sclerosis (RRMS). Seventeen untreated patients (ten women, seven men; mean age 33.0±7.9 years) with the initial diagnosis of RRMS were included for cross-sectional as well as longitudinal (24 months) clinical and MRI-based assessment in comparison with age-matched healthy controls. Conventional MR sequences, MR spectroscopy (MRS) and magnetisation transfer imaging (MTI) were performed at 1.5 T. Lesion number and volume, MRS and MTI measurements for lesions and normal appearing white matter (NAWM) were correlated to clinical scores [Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC)] for monitoring disease course after treatment initiation (interferon β-1a). MTI and MRS detected changes [magnetisation transfer ratio (MTR), N-acetylaspartate (NAA)/creatine ratio] in NAWM over time. EDSS and lesional MTR increases correlated throughout the disease course. Average MTR of NAWM raised during the study (p<0.05) and correlated to the MSFC score (r=0.476, p<0.001). At study termination, NAA/creatine ratio of NAWM correlated to the MSFC score (p<0.05). MTI and MRS were useful for initial disease assessment in NAWM. MTI and MRS correlated with clinical scores, indicating potential for monitoring the disease course and gaining new insights into treatment-related effects. (orig.)

MR spectroscopy (MRS) and magnetisation transfer imaging (MTI), lesion load and clinical scores in early relapsing remitting multiple sclerosis: a combined cross-sectional and longitudinal study

Energy Technology Data Exchange (ETDEWEB)

Bellmann-Strobl, J.; Paul, F.; Aktas, O.; Zipp, F. [Charite - University Medicine Berlin and Max Delbrueck Center for Molecular Medicine, Cecilie Vogt Clinic for Neurology, Berlin (Germany); Stiepani, H.; Bohner, G.; Klingebiel, R. [Charite - University Medicine Berlin, Department of Neuroradiology, Berlin (Germany); Wuerfel, J. [Charite - University Medicine Berlin and Max Delbrueck Center for Molecular Medicine, Cecilie Vogt Clinic for Neurology, Berlin (Germany); University Schleswig-Holstein, Institute of Neuroradiology, Campus Luebeck, Kiel (Germany); Warmuth, C. [Charite - University Medicine Berlin, Department of Radiology, Berlin (Germany); Wandinger, K.P. [Charite - University Medicine Berlin, Department of Neurology, Berlin (Germany)

2009-08-15

The purpose of this study was to correlate magnetic resonance imaging (MRI)-based lesion load assessment with clinical disability in early relapsing remitting multiple sclerosis (RRMS). Seventeen untreated patients (ten women, seven men; mean age 33.0{+-}7.9 years) with the initial diagnosis of RRMS were included for cross-sectional as well as longitudinal (24 months) clinical and MRI-based assessment in comparison with age-matched healthy controls. Conventional MR sequences, MR spectroscopy (MRS) and magnetisation transfer imaging (MTI) were performed at 1.5 T. Lesion number and volume, MRS and MTI measurements for lesions and normal appearing white matter (NAWM) were correlated to clinical scores [Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC)] for monitoring disease course after treatment initiation (interferon {beta}-1a). MTI and MRS detected changes [magnetisation transfer ratio (MTR), N-acetylaspartate (NAA)/creatine ratio] in NAWM over time. EDSS and lesional MTR increases correlated throughout the disease course. Average MTR of NAWM raised during the study (p<0.05) and correlated to the MSFC score (r=0.476, p<0.001). At study termination, NAA/creatine ratio of NAWM correlated to the MSFC score (p<0.05). MTI and MRS were useful for initial disease assessment in NAWM. MTI and MRS correlated with clinical scores, indicating potential for monitoring the disease course and gaining new insights into treatment-related effects. (orig.)

An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study.

Science.gov (United States)

De Tobel, J; Radesh, P; Vandermeulen, D; Thevissen, P W

2017-12-01

Automated methods to evaluate growth of hand and wrist bones on radiographs and magnetic resonance imaging have been developed. They can be applied to estimate age in children and subadults. Automated methods require the software to (1) recognise the region of interest in the image(s), (2) evaluate the degree of development and (3) correlate this to the age of the subject based on a reference population. For age estimation based on third molars an automated method for step (1) has been presented for 3D magnetic resonance imaging and is currently being optimised (Unterpirker et al. 2015). To develop an automated method for step (2) based on lower third molars on panoramic radiographs. A modified Demirjian staging technique including ten developmental stages was developed. Twenty panoramic radiographs per stage per gender were retrospectively selected for FDI element 38. Two observers decided in consensus about the stages. When necessary, a third observer acted as a referee to establish the reference stage for the considered third molar. This set of radiographs was used as training data for machine learning algorithms for automated staging. First, image contrast settings were optimised to evaluate the third molar of interest and a rectangular bounding box was placed around it in a standardised way using Adobe Photoshop CC 2017 software. This bounding box indicated the region of interest for the next step. Second, several machine learning algorithms available in MATLAB R2017a software were applied for automated stage recognition. Third, the classification performance was evaluated in a 5-fold cross-validation scenario, using different validation metrics (accuracy, Rank-N recognition rate, mean absolute difference, linear kappa coefficient). Transfer Learning as a type of Deep Learning Convolutional Neural Network approach outperformed all other tested approaches. Mean accuracy equalled 0.51, mean absolute difference was 0.6 stages and mean linearly weighted kappa was

Design and development of a PC based data acquisition system for automating thermal impact reporting

International Nuclear Information System (INIS)

Garman, B.K.; Carter, P.B.; Davis, J.A.

1992-01-01

The objective of this paper is to describe the design and development of an automated personal computer (PC) based data acquisition system for reporting the thermal impact of a fossil fueled power plant on its circulating water source. The system's prime functions are to collect and archive data and perform thermal hydraulic calculations necessary for reporting the plant's thermal impact on Waters of the United States to the Illinois Environmental Protection Agency (IEPA). The main objectives of the monitoring project were to reduce the labor required in the reporting process and to improve the accuracy in determining the circulating water flow rates through each of the station's three generating units. Additional efforts concentrated on enhancing condenser and circulating water pump performance information and providing an interface with the existing plant performance monitoring system

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.

Science.gov (United States)

Mao, Keming; Deng, Zhuofu

2016-01-01

This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

Directory of Open Access Journals (Sweden)

Keming Mao

2016-01-01

Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

A multicenter reproducibility study of single-voxel 1H-MRS of the medial temporal lobe

International Nuclear Information System (INIS)

Traeber, Frank; Block, Wolfgang; Guer, Okan; Schild, Hans H.; Freymann, Nikolaus; Heun, Reinhard; Jessen, Frank; Kucinski, Thomas; Hammen, Thilo; Ende, Gabriele; Pilatus, Ulrich; Hampel, Harald

2006-01-01

Proton magnetic resonance spectroscopy ( 1 H-MRS) has provided evidence for a reduction of N-acetyl-aspartate (NAA) in the medial temporal lobe (MTL) in cerebral disorders such as Alzheimer's Disease. Within the 1 H-MRS study of the German Research Network on Dementia, we determined the multicenter reproducibility of single-voxel 1 H-MRS of the MTL. At five sites with 1.5T MR systems, single-voxel 1 H spectra from the MTL of an identical healthy subject were measured. The same subject was also examined at one of the sites five times to assess intracenter stability. The protocol included water-suppressed spectra with TE 272 ms and TE 30 ms and unsuppressed spectra for absolute quantification of metabolite concentrations. The intracenter reproducibility of absolute NAA concentration, expressed as coefficient of variation (CV), was 1.8%. CV for the concentrations of creatine (Cr), choline (Cho), and myoinositol (MI) and for the ratios NAA/Cr, NAA/Cho, and MI/NAA varied by 11-16%. Intercenter CV was 3.9% for NAA and were below 10% for all other metabolites and metabolic ratios. Our study demonstrates that quantitative assessment of NAA with single-voxel MRS can be performed with high intercenter reproducibility. This is the basis for applying 1 H-MRS in large-scale early recognition and treatment studies in MTL affecting disorders. (orig.)

Brain white matter 1 H MRS in Leber optic neuropathy mutation carriers

DEFF Research Database (Denmark)

Ostojic, Jelena; Jancic, Jasna; Kozic, Dusko

2009-01-01

OBJECTIVE: This study was conducted in order to test the hypothesis that proton MR spectroscopic (1H MRS) profile of Leber's hereditary optic neuropathy (LHON) mutation carriers group (including both symptomatic and asymptomatic) differs from group of healthy individuals and to determine metabolite...... or ratio that contributes most to differentiation. PATIENTS AND METHODS: We performed single voxel 1H MRS in normal appearing white matter of eighteen LHON mtDNA mutation carriers bearing one of three LHON mtDNA point mutations and in fifty control subjects. RESULTS: ANOVA showed significant difference...

The PDD-MRS : An instrument for identification of autism spectrum disorders in persons with mental retardation

NARCIS (Netherlands)

Kraijer, D; de Bildt, A

The Scale of Pervasive Developmental Disorder in Mentally Retarded Persons (PDD-MRS) is described. The PDD-MRS is a simple classification and screening instrument devised for identification of autistic disorders (of the entire spectrum) in persons with mental retardation from mild to profound

Development and evaluation of an automated system for testing current meters

Directory of Open Access Journals (Sweden)

Ezequiel Saretta

2016-02-01

Full Text Available ABSTRACT Current meters are equipment widely used for estimating flow velocity in rivers and streams. Periodic calibrations of current meters are important to ensure the quality of measurements, but the required testing facilities are complex and only available in a few institutions. However, advances in electronics and automation may contribute to developing simple and reliable calibration systems. Thus, this study aimed to develop an automated system for testing current meters, which consisted of a trapezoidal channel, a step motor, a tow car and a management system, composed of a supervisory application and microprocessed modules to control the motor and the data acquisition. Evaluations of the displacement velocity showed that it matched the reference value up to 1.85 m s-1 for a vertical-axis current meter and 2.3 m s-1 for a horizontal-axis one. The developed system showed reliability during tests, for both current meter movement and data acquisition. The management of the system based on the developed modules and the supervisory application improved its user interface, turning all the procedure into a simple task.

Automatic discrimination between safe and unsafe swallowing using a reputation-based classifier

Directory of Open Access Journals (Sweden)

Nikjoo Mohammad S

2011-11-01

Full Text Available Abstract Background Swallowing accelerometry has been suggested as a potential non-invasive tool for bedside dysphagia screening. Various vibratory signal features and complementary measurement modalities have been put forth in the literature for the potential discrimination between safe and unsafe swallowing. To date, automatic classification of swallowing accelerometry has exclusively involved a single-axis of vibration although a second axis is known to contain additional information about the nature of the swallow. Furthermore, the only published attempt at automatic classification in adult patients has been based on a small sample of swallowing vibrations. Methods In this paper, a large corpus of dual-axis accelerometric signals were collected from 30 older adults (aged 65.47 ± 13.4 years, 15 male referred to videofluoroscopic examination on the suspicion of dysphagia. We invoked a reputation-based classifier combination to automatically categorize the dual-axis accelerometric signals into safe and unsafe swallows, as labeled via videofluoroscopic review. From these participants, a total of 224 swallowing samples were obtained, 164 of which were labeled as unsafe swallows (swallows where the bolus entered the airway and 60 as safe swallows. Three separate support vector machine (SVM classifiers and eight different features were selected for classification. Results With selected time, frequency and information theoretic features, the reputation-based algorithm distinguished between safe and unsafe swallowing with promising accuracy (80.48 ± 5.0%, high sensitivity (97.1 ± 2% and modest specificity (64 ± 8.8%. Interpretation of the most discriminatory features revealed that in general, unsafe swallows had lower mean vibration amplitude and faster autocorrelation decay, suggestive of decreased hyoid excursion and compromised coordination, respectively. Further, owing to its performance-based weighting of component classifiers, the static

Process automation

International Nuclear Information System (INIS)

Moser, D.R.

1986-01-01

Process automation technology has been pursued in the chemical processing industries and to a very limited extent in nuclear fuel reprocessing. Its effective use has been restricted in the past by the lack of diverse and reliable process instrumentation and the unavailability of sophisticated software designed for process control. The Integrated Equipment Test (IET) facility was developed by the Consolidated Fuel Reprocessing Program (CFRP) in part to demonstrate new concepts for control of advanced nuclear fuel reprocessing plants. A demonstration of fuel reprocessing equipment automation using advanced instrumentation and a modern, microprocessor-based control system is nearing completion in the facility. This facility provides for the synergistic testing of all chemical process features of a prototypical fuel reprocessing plant that can be attained with unirradiated uranium-bearing feed materials. The unique equipment and mission of the IET facility make it an ideal test bed for automation studies. This effort will provide for the demonstration of the plant automation concept and for the development of techniques for similar applications in a full-scale plant. A set of preliminary recommendations for implementing process automation has been compiled. Some of these concepts are not generally recognized or accepted. The automation work now under way in the IET facility should be useful to others in helping avoid costly mistakes because of the underutilization or misapplication of process automation. 6 figs

[Automated analyzer of enzyme immunoassay].

Science.gov (United States)

Osawa, S

1995-09-01

Automated analyzers for enzyme immunoassay can be classified by several points of view: the kind of labeled antibodies or enzymes, detection methods, the number of tests per unit time, analytical time and speed per run. In practice, it is important for us consider the several points such as detection limits, the number of tests per unit time, analytical range, and precision. Most of the automated analyzers on the market can randomly access and measure samples. I will describe the recent advance of automated analyzers reviewing their labeling antibodies and enzymes, the detection methods, the number of test per unit time and analytical time and speed per test.

Design of a high-sensitivity classifier based on a genetic algorithm: application to computer-aided diagnosis

International Nuclear Information System (INIS)

Sahiner, Berkman; Chan, Heang-Ping; Petrick, Nicholas; Helvie, Mark A.; Goodsitt, Mitchell M.

1998-01-01

A genetic algorithm (GA) based feature selection method was developed for the design of high-sensitivity classifiers, which were tailored to yield high sensitivity with high specificity. The fitness function of the GA was based on the receiver operating characteristic (ROC) partial area index, which is defined as the average specificity above a given sensitivity threshold. The designed GA evolved towards the selection of feature combinations which yielded high specificity in the high-sensitivity region of the ROC curve, regardless of the performance at low sensitivity. This is a desirable quality of a classifier used for breast lesion characterization, since the focus in breast lesion characterization is to diagnose correctly as many benign lesions as possible without missing malignancies. The high-sensitivity classifier, formulated as the Fisher's linear discriminant using GA-selected feature variables, was employed to classify 255 biopsy-proven mammographic masses as malignant or benign. The mammograms were digitized at a pixel size of 0.1mmx0.1mm, and regions of interest (ROIs) containing the biopsied masses were extracted by an experienced radiologist. A recently developed image transformation technique, referred to as the rubber-band straightening transform, was applied to the ROIs. Texture features extracted from the spatial grey-level dependence and run-length statistics matrices of the transformed ROIs were used to distinguish malignant and benign masses. The classification accuracy of the high-sensitivity classifier was compared with that of linear discriminant analysis with stepwise feature selection (LDA sfs ). With proper GA training, the ROC partial area of the high-sensitivity classifier above a true-positive fraction of 0.95 was significantly larger than that of LDA sfs , although the latter provided a higher total area (A z ) under the ROC curve. By setting an appropriate decision threshold, the high-sensitivity classifier and LDA sfs correctly

(1) H-MRS processing parameters affect metabolite quantification: The urgent need for uniform and transparent standardization

NARCIS (Netherlands)

Bhogal, A.A.; Schur, R.R.; Houtepen, L.C.; Bank, B.L. van de; Boer, V.O.; Marsman, A.; Barker, P.B.; Scheenen, T.W.J.; Wijnen, J.P.; Vinkers, C.H.; Klomp, D.W.J.

2017-01-01

Proton magnetic resonance spectroscopy ((1) H-MRS) can be used to quantify in vivo metabolite levels, such as lactate, gamma-aminobutyric acid (GABA) and glutamate (Glu). However, there are considerable analysis choices which can alter the accuracy or precision of (1) H-MRS metabolite

The Menopause Rating Scale (MRS scale: A methodological review

Directory of Open Access Journals (Sweden)

Strelow Frank

2004-09-01

Full Text Available Abstract Background This paper compiles data from different sources to get a first comprehensive picture of psychometric and other methodological characteristics of the Menopause Rating Scale (MRS scale. The scale was designed and standardized as a self-administered scale to (a to assess symptoms/complaints of aging women under different conditions, (b to evaluate the severity of symptoms over time, and (c to measure changes pre- and postmenopause replacement therapy. The scale became widespread used (available in 10 languages. Method A large multinational survey (9 countries in 4 continents from 2001/ 2002 is the basis for in depth analyses on reliability and validity of the MRS. Additional small convenience samples were used to get first impressions about test-retest reliability. The data were centrally analyzed. Data from a postmarketing HRT study were used to estimate discriminative validity. Results Reliability measures (consistency and test-retest stability were found to be good across countries, although the sample size for test-retest reliability was small. Validity: The internal structure of the MRS across countries was astonishingly similar to conclude that the scale really measures the same phenomenon in symptomatic women. The sub-scores and total score correlations were high (0.7–0.9 but lower among the sub-scales (0.5–0.7. This however suggests that the subscales are not fully independent. Norm values from different populations were presented showing that a direct comparison between Europe and North America is possible, but caution recommended with comparisons of data from Latin America and Indonesia. But this will not affect intra-individual comparisons within clinical trials. The comparison with the Kupperman Index showed sufficiently good correlations, illustrating an adept criterion-oriented validity. The same is true for the comparison with the generic quality-of-life scale SF-36 where also a sufficiently close association

Automated real-time software development

Science.gov (United States)

Jones, Denise R.; Walker, Carrie K.; Turkovich, John J.

1993-01-01

A Computer-Aided Software Engineering (CASE) system has been developed at the Charles Stark Draper Laboratory (CSDL) under the direction of the NASA Langley Research Center. The CSDL CASE tool provides an automated method of generating source code and hard copy documentation from functional application engineering specifications. The goal is to significantly reduce the cost of developing and maintaining real-time scientific and engineering software while increasing system reliability. This paper describes CSDL CASE and discusses demonstrations that used the tool to automatically generate real-time application code.

Integral Monitored Retrievable Storage (MRS) Facility conceptual design report

International Nuclear Information System (INIS)

1985-09-01

This document, Volume 6 Book 1, contains information on design studies of a Monitored Retrievable Storage (MRS) facility. Topics include materials handling; processing; support systems; support utilities; spent fuel; high-level waste and alpha-bearing waste storage facilities; and field drywell storage

Development and validation of satellite-based estimates of surface visibility

Science.gov (United States)

Brunner, J.; Pierce, R. B.; Lenzen, A.

2016-02-01

A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

Development and validation of satellite based estimates of surface visibility

Science.gov (United States)

Brunner, J.; Pierce, R. B.; Lenzen, A.

2015-10-01

A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

Clever Toolbox - the Art of Automated Genre Classification

DEFF Research Database (Denmark)

2005-01-01

Automatic musical genre classification can be defined as the science of finding computer algorithms that a digitized sound clip as input and yield a musical genre as output. The goal of automated genre classification is, of course, that the musical genre should agree with the human classificasion....... This demo illustrates an approach to the problem that first extract frequency-based sound features followed by a "linear regression" classifier. The basic features are the so-called mel-frequency cepstral coefficients (MFCCs), which are extracted on a time-scale of 30 msec. From these MFCC features, auto......) is subsequently used for classification. This classifier is rather simple; current research investigates more advanced methods of classification....

Double Ramp Loss Based Reject Option Classifier

Science.gov (United States)

2015-05-22

of convex (DC) functions. To minimize it, we use DC programming approach [1]. The proposed method has following advantages: (1) the proposed loss LDR ...space constraints. We see that LDR does not put any restriction on ρ for it to be an upper bound of L0−d−1. 2.2 Risk Formulation Using LDR Let S = {(xn...classifier learnt using LDR based approach (C = 100, μ = 1, d = .2). Filled circles and triangles represent the support vectors. 4 Experimental Results We show

Visual Servoing-Based Nanorobotic System for Automated Electrical Characterization of Nanotubes inside SEM.

Science.gov (United States)

Ding, Huiyang; Shi, Chaoyang; Ma, Li; Yang, Zhan; Wang, Mingyu; Wang, Yaqiong; Chen, Tao; Sun, Lining; Toshio, Fukuda

2018-04-08

The maneuvering and electrical characterization of nanotubes inside a scanning electron microscope (SEM) has historically been time-consuming and laborious for operators. Before the development of automated nanomanipulation-enabled techniques for the performance of pick-and-place and characterization of nanoobjects, these functions were still incomplete and largely operated manually. In this paper, a dual-probe nanomanipulation system vision-based feedback was demonstrated to automatically perform 3D nanomanipulation tasks, to investigate the electrical characterization of nanotubes. The XY-position of Atomic Force Microscope (AFM) cantilevers and individual carbon nanotubes (CNTs) were precisely recognized via a series of image processing operations. A coarse-to-fine positioning strategy in the Z-direction was applied through the combination of the sharpness-based depth estimation method and the contact-detection method. The use of nanorobotic magnification-regulated speed aided in improving working efficiency and reliability. Additionally, we proposed automated alignment of manipulator axes by visual tracking the movement trajectory of the end effector. The experimental results indicate the system's capability for automated measurement electrical characterization of CNTs. Furthermore, the automated nanomanipulation system has the potential to be extended to other nanomanipulation tasks.

Stress fracture development classified by bone scintigraphy

International Nuclear Information System (INIS)

Zwas, S.T.; Elkanovich, R.; Frank, G.; Aharonson, Z.

1985-01-01

There is no consensus on classifying stress fractures (SF) appearing on bone scans. The authors present a system of classification based on grading the severity and development of bone lesions by visual inspection, according to three main scintigraphic criteria: focality and size, intensity of uptake compare to adjacent bone, and local medular extension. Four grades of development (I-IV) were ranked, ranging from ill defined slightly increased cortical uptake to well defined regions with markedly increased uptake extending transversely bicortically. 310 male subjects aged 19-2, suffering several weeks from leg pains occurring during intensive physical training underwent bone scans of the pelvis and lower extremities using Tc-99-m-MDP. 76% of the scans were positive with 354 lesions, of which 88% were in th4e mild (I-II) grades and 12% in the moderate (III) and severe (IV) grades. Post-treatment scans were obtained in 65 cases having 78 lesions during 1- to 6-month intervals. Complete resolution was found after 1-2 months in 36% of the mild lesions but in only 12% of the moderate and severe ones, and after 3-6 months in 55% of the mild lesions and 15% of the severe ones. 75% of the moderate and severe lesions showed residual uptake in various stages throughout the follow-up period. Early recognition and treatment of mild SF lesions in this study prevented protracted disability and progression of the lesions and facilitated complete healing

Development of automated analytical systems for large throughput

International Nuclear Information System (INIS)

Ernst, P.C.; Hoffman, E.L.

1982-01-01

The need to be able to handle a large throughput of samples for neutron activation analysis has led to the development of automated counting and sample handling systems. These are coupled with available computer-assisted INAA techniques to perform a wide range of analytical services on a commercial basis. A fully automated delayed neutron counting system and a computer controlled pneumatic transfer for INAA use are described, as is a multi-detector gamma-spectroscopy system. (author)

1H-MRS processing parameters affect metabolite quantification : The urgent need for uniform and transparent standardization

NARCIS (Netherlands)

Bhogal, Alex A.; Schür, Remmelt; Houtepen, Lotte C.; van de Bank, B.L.; Boer, Vincent O.; Marsman, Anouk; Barker, Peter B.; Scheenen, Tom W. J.; Wijnen, Jannie P.; Vinkers, Christiaan H.; Klomp, Dennis W.J.

2017-01-01

Proton magnetic resonance spectroscopy (1H-MRS) can be used to quantify in vivo metabolite levels, such as lactate, γ-aminobutyric acid (GABA) and glutamate (Glu). However, there are considerable analysis choices which can alter the accuracy or precision of 1H-MRS metabolite quantification. It is

A Generic Deep-Learning-Based Approach for Automated Surface Inspection.

Science.gov (United States)

Ren, Ruoxu; Hung, Terence; Tan, Kay Chen

2018-03-01

Automated surface inspection (ASI) is a challenging task in industry, as collecting training dataset is usually costly and related methods are highly dataset-dependent. In this paper, a generic approach that requires small training data for ASI is proposed. First, this approach builds classifier on the features of image patches, where the features are transferred from a pretrained deep learning network. Next, pixel-wise prediction is obtained by convolving the trained classifier over input image. An experiment on three public and one industrial data set is carried out. The experiment involves two tasks: 1) image classification and 2) defect segmentation. The results of proposed algorithm are compared against several best benchmarks in literature. In the classification tasks, the proposed method improves accuracy by 0.66%-25.50%. In the segmentation tasks, the proposed method reduces error escape rates by 6.00%-19.00% in three defect types and improves accuracies by 2.29%-9.86% in all seven defect types. In addition, the proposed method achieves 0.0% error escape rate in the segmentation task of industrial data.

Hyperspectral image classifier based on beach spectral feature

International Nuclear Information System (INIS)

Liang, Zhang; Lianru, Gao; Bing, Zhang

2014-01-01

The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

Towards an Automated Requirements-driven Development of Smart Cyber-Physical Systems

Directory of Open Access Journals (Sweden)

Jiri Vinarek

2016-03-01

Full Text Available The Invariant Refinement Method for Self Adaptation (IRM-SA is a design method targeting development of smart Cyber-Physical Systems (sCPS. It allows for a systematic translation of the system requirements into the system architecture expressed as an ensemble-based component system (EBCS. However, since the requirements are captured using natural language, there exists the danger of their misinterpretation due to natural language requirements' ambiguity, which could eventually lead to design errors. Thus, automation and validation of the design process is desirable. In this paper, we (i analyze the translation process of natural language requirements into the IRM-SA model, (ii identify individual steps that can be automated and/or validated using natural language processing techniques, and (iii propose suitable methods.

Design and development on automated control system of coated fuel particle fabrication process

International Nuclear Information System (INIS)

Liu Malin; Shao Youlin; Liu Bing

2013-01-01

With the development trend of the large-scale production of the HTR coated fuel particles, the original manual control system can not meet the requirement and the automation control system of coated fuel particle fabrication in modern industrial grade is needed to develop. The comprehensive analysis aiming at successive 4-layer coating process of TRISO type coated fuel particles was carried out. It was found that the coating process could be divided into five subsystems and nine operating states. The establishment of DCS-type (distributed control system) of automation control system was proposed. According to the rigorous requirements of preparation process for coated particles, the design considerations of DCS were proposed, including the principle of coordinated control, safety and reliability, integration specification, practical and easy to use, and open and easy to update. A complete set of automation control system for coated fuel particle preparation process was manufactured based on fulfilling the requirements of these principles in manufacture practice. The automated control system was put into operation in the production of irradiated samples for HTRPM demonstration project. The experimental results prove that the system can achieve better control of coated fuel particle preparation process and meet the requirements of factory-scale production. (authors)

"First generation" automated DNA sequencing technology.

Science.gov (United States)

Slatko, Barton E; Kieleczawa, Jan; Ju, Jingyue; Gardner, Andrew F; Hendrickson, Cynthia L; Ausubel, Frederick M

2011-10-01

Beginning in the 1980s, automation of DNA sequencing has greatly increased throughput, reduced costs, and enabled large projects to be completed more easily. The development of automation technology paralleled the development of other aspects of DNA sequencing: better enzymes and chemistry, separation and imaging technology, sequencing protocols, robotics, and computational advancements (including base-calling algorithms with quality scores, database developments, and sequence analysis programs). Despite the emergence of high-throughput sequencing platforms, automated Sanger sequencing technology remains useful for many applications. This unit provides background and a description of the "First-Generation" automated DNA sequencing technology. It also includes protocols for using the current Applied Biosystems (ABI) automated DNA sequencing machines. © 2011 by John Wiley & Sons, Inc.

Reviewing Automated Sensor-Based Visitor Tracking Studies

DEFF Research Database (Denmark)

Mygind, Lærke; Bentsen, Peter

2017-01-01

The method of timing and tracking has a long history within visitor studies and exhibition evaluation. With an increase in indoor tracking research, sensor-based positioning tool usage in museums has grown, as have expectations regarding the efficacy of technological sensing systems. This literat......The method of timing and tracking has a long history within visitor studies and exhibition evaluation. With an increase in indoor tracking research, sensor-based positioning tool usage in museums has grown, as have expectations regarding the efficacy of technological sensing systems...... methods in terms of obtained level of detail, accuracy, level of obtrusiveness, automation of data entry, ability to time concurrent behaviors, and amount of observer training needed. Although individual sensor-based and traditional, observational methods had both strengths and weaknesses, all sensor......-based timing and tracking methods provided automated data entry and the opportunity to track a number of visitors simultaneously regardless of the available personnel....

Experience based ageing analysis of NPP protection automation in Finland

International Nuclear Information System (INIS)

Simola, K.

2000-01-01

This paper describes three successive studies on ageing of protection automation of nuclear power plants. These studies were aimed at developing a methodology for an experience based ageing analysis, and applying it to identify the most critical components from ageing and safety points of view. The analyses resulted also to suggestions for improvement of data collection systems for the purpose of further ageing analyses. (author)

Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

Science.gov (United States)

Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

2018-05-01

Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

How the signal‐to‐noise ratio influences hyperpolarized 13C dynamic MRS data fitting and parameter estimation

DEFF Research Database (Denmark)

Santarelli, Maria Filomena; Positano, Vincenzo; Giovannetti, Giulio

2012-01-01

signals with low signal‐to‐noise ratio (SNR). The relationship between SNR and the precision of quantitative analysis for the evaluation of the in vivo kinetic behavior of metabolites is unknown. In this article, this topic is addressed by Monte Carlo simulations, covering the problem of MRS signal model......MRS of hyperpolarized 13C‐labeled compounds represents a promising technique for in vivo metabolic studies. However, robust quantification and metabolic modeling are still important areas of investigation. In particular, time and spatial resolution constraints may lead to the analysis of MRS...

Temporal subtraction in chest radiography: Automated assessment of registration accuracy

International Nuclear Information System (INIS)

Armato, Samuel G. III; Doshi, Devang J.; Engelmann, Roger; Croteau, Charles L.; MacMahon, Heber

2006-01-01

Radiologists routinely compare multiple chest radiographs acquired from the same patient over time to more completely understand changes in anatomy and pathology. While such comparisons are achieved conventionally through a side-by-side display of images, image registration techniques have been developed to combine information from two separate radiographic images through construction of a 'temporal subtraction image'. Although temporal subtraction images provide a powerful mechanism for the enhanced visualization of subtle change, errors in the clinical evaluation of these images may arise from misregistration artifacts that can mimic or obscure pathologic change. We have developed a computerized method for the automated assessment of registration accuracy as demonstrated in temporal subtraction images created from radiographic chest image pairs. The registration accuracy of 150 temporal subtraction images constructed from the computed radiography images of 72 patients was rated manually using a five-point scale ranging from '5-excellent' to '1-poor'; ratings of 3, 4, or 5 reflected clinically acceptable subtraction images, and ratings of 1 or 2 reflected clinically unacceptable images. Gray-level histogram-based features and texture measures are computed at multiple spatial scales within a 'lung mask' region that encompasses both lungs in the temporal subtraction images. A subset of these features is merged through a linear discriminant classifier. With a leave-one-out-by-patient training/testing paradigm, the automated method attained an A z value of 0.92 in distinguishing between temporal subtraction images that demonstrated clinically acceptable and clinically unacceptable registration accuracy. A second linear discriminant classifier yielded an A z value of 0.82 based on a feature subset selected from an independent database of digitized film images. These methods are expected to advance the clinical utility of temporal subtraction images for chest

In-Vivo Detection and Tracking of T Cells in Various Organs in a Melanoma Tumor Model by 19F-Fluorine MRS/MRI.

Directory of Open Access Journals (Sweden)

Christine Gonzales

Full Text Available 19F-MRI and 19F-MRS can identify specific cell types after in-vitro or in-vivo 19F-labeling. Knowledge on the potential to track in-vitro 19F-labeled immune cells in tumor models by 19F-MRI/MRS is scarce.To study 19F-based MR techniques for in-vivo tracking of adoptively transferred immune cells after in-vitro 19F-labeling, i.e. to detect and monitor their migration non-invasively in melanoma-bearing mice.Splenocytes (SP were labeled in-vitro with a perfluorocarbon (PFC and IV-injected into non-tumor bearing mice. In-vitro PFC-labeled ovalbumin (OVA-specific T cells from the T cell receptor-transgenic line OT-1, activated with anti-CD3 and anti-CD28 antibodies (Tact or OVA-peptide pulsed antigen presenting cells (TOVA-act, were injected into B16 OVA melanoma-bearing mice. The distribution of the 19F-labelled donor cells was determined in-vivo by 19F-MRI/MRS. In-vivo 19F-MRI/MRS results were confirmed by ex-vivo 19F-NMR and flow cytometry.SP, Tact, and TOVA-act were successfully PFC-labeled in-vitro yielding 3x1011-1.4x1012 19F-atoms/cell in the 3 groups. Adoptively transferred 19F-labeled SP, TOVA-act, and Tact were detected by coil-localized 19F-MRS in the chest, abdomen, and left flank in most animals (corresponding to lungs, livers, and spleens, respectively, with highest signal-to-noise for SP vs TOVA-act and Tact, p<0.009 for both. SP and Tact were successfully imaged by 19F-MRI (n = 3; liver. These in-vivo data were confirmed by ex-vivo high-resolution 19F-NMR-spectroscopy. By flow cytometric analysis, however, TOVA-act tended to be more abundant versus SP and Tact (liver: p = 0.1313; lungs: p = 0.1073; spleen: p = 0.109. Unlike 19F-MRI/MRS, flow cytometry also identified transferred immune cells (SP, Tact, and TOVA-act in the tumors.SP, Tact, and TOVA-act were successfully PFC-labeled in-vitro and detected in-vivo by non-invasive 19F-MRS/MRI in liver, lung, and spleen. The portion of 19F-labeled T cells in the adoptively transferred cell

Development of an Automated Decision-Making Tool for Supervisory Control System

Energy Technology Data Exchange (ETDEWEB)

Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Muhlheim, Michael David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Flanagan, George F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kisner, Roger A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-09-01

This technical report was generated as a product of the Supervisory Control for Multi-Modular Small Modular Reactor (SMR) Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (AdvSMR) Research and Development Program of the US Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular AdvSMR plants. This research activity advances the state of the art by incorporating real-time, probabilistic-based decision-making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides background information on the state of the art of automated decision-making, including the description of existing methodologies. It then presents a description of a generalized decision-making framework, upon which the supervisory control decision-making algorithm is based. The probabilistic portion of automated decision-making is demonstrated through a simple hydraulic loop example.

Mrs Hitler and her doctor.

Science.gov (United States)

Macleod, Sandy

2005-12-01

The doctor who attended the mother of Adolf Hitler in her terminal illness has been blamed as a cause of the Holocaust. The medical details recorded of this professional relationship are presented and discussed. Dr Bloch's medical care of Mrs Hitler was consistent with the prevailing medical practice of the management of fungating breast carcinoma. Indeed, the general practitioner's care and attention of the family appear to have been astute and supportive. There is nothing to suggest that Dr Bloch's medical care was other than competent. Doctors who have the (mis)fortune to professionally attend major figures of history may be unfairly viewed, despite their appropriate and adequate care.

AUTOMATING THE DATA SECURITY PROCESS

Directory of Open Access Journals (Sweden)

Florin Ogigau-Neamtiu

2017-11-01

Full Text Available Contemporary organizations face big data security challenges in the cyber environment due to modern threats and actual business working model which relies heavily on collaboration, data sharing, tool integration, increased mobility, etc. The nowadays data classification and data obfuscation selection processes (encryption, masking or tokenization suffer because of the human implication in the process. Organizations need to shirk data security domain by classifying information based on its importance, conduct risk assessment plans and use the most cost effective data obfuscation technique. The paper proposes a new model for data protection by using automated machine decision making procedures to classify data and to select the appropriate data obfuscation technique. The proposed system uses natural language processing capabilities to analyze input data and to select the best course of action. The system has capabilities to learn from previous experiences thus improving itself and reducing the risk of wrong data classification.

A multicenter reproducibility study of single-voxel {sup 1}H-MRS of the medial temporal lobe

Energy Technology Data Exchange (ETDEWEB)

Traeber, Frank; Block, Wolfgang; Guer, Okan; Schild, Hans H. [University of Bonn, Department of Radiology, Bonn (Germany); Freymann, Nikolaus; Heun, Reinhard; Jessen, Frank [University of Bonn, Department of Psychiatry, Bonn (Germany); Kucinski, Thomas [University of Hamburg, Department of Neuroradiology, Hamburg (Germany); Hammen, Thilo [University of Erlangen, Department of Psychiatry, Erlangen (Germany); Ende, Gabriele [Central Institute of Mental Health, NMR Research in Psychiatry, Mannheim (Germany); Pilatus, Ulrich [University of Frankfurt, Department of Neuroradiology, Frankfurt (Germany); Hampel, Harald [University of Munich, Department of Psychiatry, Munich (Germany)

2006-05-15

Proton magnetic resonance spectroscopy ({sup 1}H-MRS) has provided evidence for a reduction of N-acetyl-aspartate (NAA) in the medial temporal lobe (MTL) in cerebral disorders such as Alzheimer's Disease. Within the {sup 1}H-MRS study of the German Research Network on Dementia, we determined the multicenter reproducibility of single-voxel {sup 1}H-MRS of the MTL. At five sites with 1.5T MR systems, single-voxel {sup 1}H spectra from the MTL of an identical healthy subject were measured. The same subject was also examined at one of the sites five times to assess intracenter stability. The protocol included water-suppressed spectra with TE 272 ms and TE 30 ms and unsuppressed spectra for absolute quantification of metabolite concentrations. The intracenter reproducibility of absolute NAA concentration, expressed as coefficient of variation (CV), was 1.8%. CV for the concentrations of creatine (Cr), choline (Cho), and myoinositol (MI) and for the ratios NAA/Cr, NAA/Cho, and MI/NAA varied by 11-16%. Intercenter CV was 3.9% for NAA and were below 10% for all other metabolites and metabolic ratios. Our study demonstrates that quantitative assessment of NAA with single-voxel MRS can be performed with high intercenter reproducibility. This is the basis for applying {sup 1}H-MRS in large-scale early recognition and treatment studies in MTL affecting disorders. (orig.)

FERAL : Network-based classifier with application to breast cancer outcome prediction

NARCIS (Netherlands)

Allahyar, A.; De Ridder, J.

2015-01-01

Motivation: Breast cancer outcome prediction based on gene expression profiles is an important strategy for personalize patient care. To improve performance and consistency of discovered markers of the initial molecular classifiers, network-based outcome prediction methods (NOPs) have been proposed.

Automated model building

CERN Document Server

Caferra, Ricardo; Peltier, Nicholas

2004-01-01

This is the first book on automated model building, a discipline of automated deduction that is of growing importance Although models and their construction are important per se, automated model building has appeared as a natural enrichment of automated deduction, especially in the attempt to capture the human way of reasoning The book provides an historical overview of the field of automated deduction, and presents the foundations of different existing approaches to model construction, in particular those developed by the authors Finite and infinite model building techniques are presented The main emphasis is on calculi-based methods, and relevant practical results are provided The book is of interest to researchers and graduate students in computer science, computational logic and artificial intelligence It can also be used as a textbook in advanced undergraduate courses

Effective Sequential Classifier Training for SVM-Based Multitemporal Remote Sensing Image Classification

Science.gov (United States)

Guo, Yiqing; Jia, Xiuping; Paull, David

2018-06-01

The explosive availability of remote sensing images has challenged supervised classification algorithms such as Support Vector Machines (SVM), as training samples tend to be highly limited due to the expensive and laborious task of ground truthing. The temporal correlation and spectral similarity between multitemporal images have opened up an opportunity to alleviate this problem. In this study, a SVM-based Sequential Classifier Training (SCT-SVM) approach is proposed for multitemporal remote sensing image classification. The approach leverages the classifiers of previous images to reduce the required number of training samples for the classifier training of an incoming image. For each incoming image, a rough classifier is firstly predicted based on the temporal trend of a set of previous classifiers. The predicted classifier is then fine-tuned into a more accurate position with current training samples. This approach can be applied progressively to sequential image data, with only a small number of training samples being required from each image. Experiments were conducted with Sentinel-2A multitemporal data over an agricultural area in Australia. Results showed that the proposed SCT-SVM achieved better classification accuracies compared with two state-of-the-art model transfer algorithms. When training data are insufficient, the overall classification accuracy of the incoming image was improved from 76.18% to 94.02% with the proposed SCT-SVM, compared with those obtained without the assistance from previous images. These results demonstrate that the leverage of a priori information from previous images can provide advantageous assistance for later images in multitemporal image classification.

Qualification of academic facilities for small-scale automated manufacture of autologous cell-based products.

Science.gov (United States)

Hourd, Paul; Chandra, Amit; Alvey, David; Ginty, Patrick; McCall, Mark; Ratcliffe, Elizabeth; Rayment, Erin; Williams, David J

2014-01-01

Academic centers, hospitals and small companies, as typical development settings for UK regenerative medicine assets, are significant contributors to the development of autologous cell-based therapies. Often lacking the appropriate funding, quality assurance heritage or specialist regulatory expertise, qualifying aseptic cell processing facilities for GMP compliance is a significant challenge. The qualification of a new Cell Therapy Manufacturing Facility with automated processing capability, the first of its kind in a UK academic setting, provides a unique demonstrator for the qualification of small-scale, automated facilities for GMP-compliant manufacture of autologous cell-based products in these settings. This paper shares our experiences in qualifying the Cell Therapy Manufacturing Facility, focusing on our approach to streamlining the qualification effort, the challenges, project delays and inefficiencies we encountered, and the subsequent lessons learned.

The Automated Threaded Fastening Based on On-line Identification

Directory of Open Access Journals (Sweden)

Nicolas Ivan Giannoccaro

2008-11-01

Full Text Available The principle of the thread fastenings have been known and used for decades with the purpose of joining one component to another. Threaded fastenings are popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually. It is a difficult problem to automat. As a result there is very little published research on automating threaded fastenings, and most research on automated assembly focus on the peg-in-hole assembly problem. This paper investigates the problem of automated monitoring of the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw insertions. However, the model requires parameters on the screw dimensions and plate material properties are difficult to measure. This paper presents a study on on-line identification during screw fastenings. An identification methodology for two unknown parameter estimation during a self-tapping screw insertion process is presented. It is shown that friction and screw properties required by the model can be reliably estimated on-line. Experimental results are presented to validate the identification procedure.

Evaluation of the need, feasibility, and siting of the MRS in Tennessee. Draft final report

Energy Technology Data Exchange (ETDEWEB)

Colglazier, E.W. Jr. [Tennessee Univ., Knoxville, TN (United States)

1985-12-16

This summary report outlines the results of an independent assessment of the need, feasibility, and siting of the proposed Monitored Retrievable Storage (MRS) facility. The detailed reports of this assessment are included as appendices to the summary report. The Department of Energy (DOE) has concluded that the MRS is not absolutely necessary, but preferred, in order to manage and move spent fuel from reactors to a repository. The team has attemped to assess ``need`` by comparing to advantages and disadvantages of various systems, with and without the MRS. ``Feasibility has been assessed by comparing the technical and economic advantages and disadvantages. The team was not asked to recommend a preferred system. That choice will depend on the importance that are used to compare alternatives. The five key criteria selected by the team for comparing alternate systems were: economic cost, radiological risk, non-radiological transportation impacts, the likelihood of successful implementation and operation of the system, and the likelihood of meeting the schedule in the Nuclear Waste Policy Act. The team compared twelve different systems and modeled the transportation impacts and risks with three repository sites and two MRS sites.

31P-MRS study for the assessment of tumor response after radiotherapy and/or hyperthermia

International Nuclear Information System (INIS)

Kimura, Hirohiko; Itho, Satoshi; Nakatsugawa, Sigekazu; Maeda, Masayuki; Iwasaki, Toshiko; Yamamoto, Kazutaka; Ishii, Yasushi

1992-01-01

The metabolic changes of human lung cancer implanted in nude mice were studied by the use of in vivo 31 P nuclear magnetic resonance spectroscopy ( 31 P-MRS) after radiotherapy, hyperthermia or the combined therapy of radiation and hyperthermia. 31 P-MRS of the tumors showed increased Pi/β-NTP ratio and acidic pH value on 1 day after hyperthermia, that indicated metabolic decline caused by hyperthermia. On the other hand, lower Pi/β-NTP ratios during 3 to 10 days after irradiation suggested metabolic activation of the tumors. In the tumors treated with the combined therapy, 31 P-MRS revealed increase of Pi/β-NTP ratio within 1 day and its decrease subsequent 6 to 10 days after treatment, that indicated additive bi-phasic changes induced by radiation and hyperthermia, respectively. Since Pi/β-NTP ratio had significant correlation to the tumor blood perfusion measured by hydrogen gas clearance studies, these bi-phasic changes were considered to correspond to two different physiological states, namely, ischemic and reperfused states. 31 P-MRS obtained from tumors could be useful to asses the physiological consequence following radiation, hyperthermia or the combined therapy. (author)

Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis.

Science.gov (United States)

Kammen, Alexandra; Law, Meng; Tjan, Bosco S; Toga, Arthur W; Shi, Yonggang

2016-01-15

Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic

How automated image analysis techniques help scientists in species identification and classification?

Science.gov (United States)

Yousef Kalafi, Elham; Town, Christopher; Kaur Dhillon, Sarinder

2017-09-04

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification increased over the last two decades. Automation of data classification is primarily focussed on images, incorporating and analysing image data has recently become easier due to developments in computational technology. Research efforts in identification of species include specimens' image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, categorizing and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies.

Automation of Aditya vacuum control system based on CODAC Core System

Energy Technology Data Exchange (ETDEWEB)

Raulji, Vismaysinh D., E-mail: vismay@ipr.res.in; Pujara, Harshad; Arambhadiya, Bharat; Jadeja, Kumarpalsinh; Bhatt, Shailesh; Rajpal, Rachana

2016-11-15

Highlights: • Monitor and control of vacuum control system based on CODAC Core System. • Communication between SIEMENS PLC and open source software EPICS. • With CODAC Core easy to configure and programming of slow controller. - Abstract: The main objective of vacuum control system is to provide ultrahigh vacuum for Aditya Tokamak operations. Aditya Vacuum vessel is having four vacuum pumping lines. To demonstrate implementation of automation; a study case is under taken by automating single Pumping Line of the Aditya vacuum system using CODAC Core System (CCS). Currently, vacuum system is operated manually. The CCS based control system allows remote control, monitoring, alarm handling of vacuum parameters. The CODAC Core System is the Linux based software package that is distributed by ITER Organization for the development of Plant System I&C software. CODAC Core System includes EPICS, CSS (Control System Studio) etc. CSS is used for HMI (Human Machine Interface), alarms and archives. SDD (Self Description Data) tool is used to configure plant system I&C. SDD Editor is an Eclipse based application to define the plant system, interface, I&C component, interfaced signals, configure variable. SCADA (Supervisory Control and Data Acquisition) system is developed in CSS. Data is transferred between PLC and CSS through EPICS. The complete system is tested with Aditya Vacuum Control System with process interlocks. Operator interface is also developed using Lab VIEW as a choice of the user. This paper will describe the salient features of the developed control system in detail.

Observation and control of hepatic specimens with MRI and MRS

International Nuclear Information System (INIS)

Ludescher, B.; Wietek, B.; Machann, J.; Graf, H.; Schick, F.; Subke, J.; Claussen, C.D.

2004-01-01

Purpose: The purpose of this study was to observe the process of fixation in liver specimens non-invasively by means of magnetic resonance. The fixation process of several formaldehyde-containing solutions was monitored with MRI and MRS at two different temperatures. Materials and Methods: Liver specimens were conserved in aqueous fixative solutions containing formaldehyde concentrations of 0.7, 1.8, 4 and 7.2% and at different temperatures of 5 C and 20 C. MRI was performed with T1-, T2- and PD-weighted TSE sequences, a 2D FLASH-sequence with and without magnetization transfer, and a FISP 3D-sequence on a clinical 1.5 Tesla MR whole-body unit, and MRS with 1 H-spectroscopic methods (STEAM-sequence) on a 3 Tesla MR whole-body unit. Results: The diffusion of formaldehyde into the tissue was best identified on PD- and T1-weighted images as a band under the liver surface with increasing thickness, penetrating especially fast during the first three days. Spectroscopic measurements revealed the rising formaldehyde concentration in the inner part of the organs. Temperature had no significant influence on the velocity of immersing, but cooling conditions produced less gas-filled caverns due to reduced undesired decomposition processes. Conclusion: The spatial and temporal process of ongoing fixation in the liver can be monitored by MRI. MRS confirms a rising concentration of formaldehyde during ongoing fixation. (orig.) [de

Development of multicriteria models to classify energy efficiency alternatives

International Nuclear Information System (INIS)

Neves, Luis Pires; Antunes, Carlos Henggeler; Dias, Luis Candido; Martins, Antonio Gomes

2005-01-01

This paper aims at describing a novel constructive approach to develop decision support models to classify energy efficiency initiatives, including traditional Demand-Side Management and Market Transformation initiatives, overcoming the limitations and drawbacks of Cost-Benefit Analysis. A multicriteria approach based on the ELECTRE-TRI method is used, focusing on four perspectives: - an independent Agency with the aim of promoting energy efficiency; - Distribution-only utilities under a regulated framework; - the Regulator; - Supply companies in a competitive liberalized market. These perspectives were chosen after a system analysis of the decision situation regarding the implementation of energy efficiency initiatives, looking for the main roles and power relations, with the purpose of structuring the decision problem by identifying the actors, the decision makers, the decision paradigm, and the relevant criteria. The multicriteria models developed allow considering different kinds of impacts, but avoiding difficult measurements and unit conversions due to the nature of the multicriteria method chosen. The decision is then based on all the significant effects of the initiative, both positive and negative ones, including ancillary effects often forgotten in cost-benefit analysis. The ELECTRE-TRI, as most multicriteria methods, provides to the Decision Maker the ability of controlling the relevance each impact can have on the final decision. The decision support process encompasses a robustness analysis, which, together with a good documentation of the parameters supplied into the model, should support sound decisions. The models were tested with a set of real-world initiatives and compared with possible decisions based on Cost-Benefit analysis

Recognition of pornographic web pages by classifying texts and images.

Science.gov (United States)

Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

2007-06-01

With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

Harvest: an open platform for developing web-based biomedical data discovery and reporting applications.

Science.gov (United States)

Pennington, Jeffrey W; Ruth, Byron; Italia, Michael J; Miller, Jeffrey; Wrazien, Stacey; Loutrel, Jennifer G; Crenshaw, E Bryan; White, Peter S

2014-01-01

Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at http://harvest.research.chop.edu.

Discovering mammography-based machine learning classifiers for breast cancer diagnosis.

Science.gov (United States)

Ramos-Pollán, Raúl; Guevara-López, Miguel Angel; Suárez-Ortega, Cesar; Díaz-Herrero, Guillermo; Franco-Valiente, Jose Miguel; Rubio-Del-Solar, Manuel; González-de-Posada, Naimy; Vaz, Mario Augusto Pires; Loureiro, Joana; Ramos, Isabel

2012-08-01

This work explores the design of mammography-based machine learning classifiers (MLC) and proposes a new method to build MLC for breast cancer diagnosis. We massively evaluated MLC configurations to classify features vectors extracted from segmented regions (pathological lesion or normal tissue) on craniocaudal (CC) and/or mediolateral oblique (MLO) mammography image views, providing BI-RADS diagnosis. Previously, appropriate combinations of image processing and normalization techniques were applied to reduce image artifacts and increase mammograms details. The method can be used under different data acquisition circumstances and exploits computer clusters to select well performing MLC configurations. We evaluated 286 cases extracted from the repository owned by HSJ-FMUP, where specialized radiologists segmented regions on CC and/or MLO images (biopsies provided the golden standard). Around 20,000 MLC configurations were evaluated, obtaining classifiers achieving an area under the ROC curve of 0.996 when combining features vectors extracted from CC and MLO views of the same case.

Ontology-Based Device Descriptions and Device Repository for Building Automation Devices

Directory of Open Access Journals (Sweden)

Dibowski Henrik

2011-01-01

Full Text Available Device descriptions play an important role in the design and commissioning of modern building automation systems and help reducing the design time and costs. However, all established device descriptions are specialized for certain purposes and suffer from several weaknesses. This hinders a further design automation, which is strongly needed for the more and more complex building automation systems. To overcome these problems, this paper presents novel Ontology-based Device Descriptions (ODDs along with a layered ontology architecture, a specific ontology view approach with virtual properties, a generic access interface, a triple store-based database backend, and a generic search mask GUI with underlying query generation algorithm. It enables a formal, unified, and extensible specification of building automation devices, ensures their comparability, and facilitates a computer-enabled retrieval, selection, and interoperability evaluation, which is essential for an automated design. The scalability of the approach to several ten thousand devices is demonstrated.

Hippocampal volume MRI and 1H-MRS study in chronic alcohol dependent patients

International Nuclear Information System (INIS)

Miao Huanmin; Chen Jun; Zha Yunfei; Zhang Yu; Liu Changsheng; Pan Ewu

2010-01-01

Objective: To observe the changes of the bilateral hippocampal volume (BHV) and 1 H- MRS appearance of chronic alcohol dependent (CAD) patients and to provide quantitative information for the clinical diagnosis of CAD. Methods: The conventional MR imaging including three-dimensional fast spoiled gradient recalled echo (3D-FSPGR) and 1 H-MRS were performed on 16 patients with CAD (CAD group) and 18 cases of volunteer (control group). The BHV were measured in both groups and the standardized BHV in CAD group and control group were compared. 1 H-MRS metabolites including N-acetylaspartate (NAA), Choline compounds (Cho), Creatine (Cr), and myoinositol (mI) of the bilateral cephalic hippocampus were acquired. The ratios of Cho/Ci, Cho/NAA, NAA/Cr and mI/Ci within the bilateral cephalic hippocampus of the two groups were compared. The t test was used to compare the BHV and the ratios of 1 H-MRS in the bilateral cephalic hippocampus between the two groups. Results: In CAD group, the left and the right hippocampal volume were 1.881±0.292, 2.139±0.328 respectively while they were 2.106±0.245 and 2.267±0.271 respectively in the control group. The BHV had no significant difference between the left and the right in either the CAD group or the control group (t=0.232, 0.147 respectively, P>0.05). The BHV had no significant difference between the CAD group and control group (t=0.424, 0.131 respectively, P>0.05). The Cho/Cr and NAA/Cr in the right cephalic hippocampus of the CAD group were 1.225±0.210 and 1.145±0.034 respectively, while they were 1.429±0.286, 1.612±0.444 respectively in the control group (t=0.321, 0.408, P 1 H-MRS could potentially provide early diagnostic evidence for CAD patients before the onset of cerebral morphological changes. (authors)

A Novel Approach for Multi Class Fault Diagnosis in Induction Machine Based on Statistical Time Features and Random Forest Classifier

Science.gov (United States)

Sonje, M. Deepak; Kundu, P.; Chowdhury, A.

2017-08-01

Fault diagnosis and detection is the important area in health monitoring of electrical machines. This paper proposes the recently developed machine learning classifier for multi class fault diagnosis in induction machine. The classification is based on random forest (RF) algorithm. Initially, stator currents are acquired from the induction machine under various conditions. After preprocessing the currents, fourteen statistical time features are estimated for each phase of the current. These parameters are considered as inputs to the classifier. The main scope of the paper is to evaluate effectiveness of RF classifier for individual and mixed fault diagnosis in induction machine. The stator, rotor and mixed faults (stator and rotor faults) are classified using the proposed classifier. The obtained performance measures are compared with the multilayer perceptron neural network (MLPNN) classifier. The results show the much better performance measures and more accurate than MLPNN classifier. For demonstration of planned fault diagnosis algorithm, experimentally obtained results are considered to build the classifier more practical.

Quantitative analysis of benign prostate hyperplasia with MRS in Chinese adult

International Nuclear Information System (INIS)

Li Feiyu; Wang Xiaoying; Huang Rong; Jiang Xuexiang; Ding Jianping; Zhou Liangping

2005-01-01

Objective: To evaluate the metabolic level of different types of benign prostate hyperplasia (BPH) with MRS in Chinese adult. Methods: Ten BPH patients verified by biopsy were divided into two types: glandular BPH and stromal BPH. 3DMRS were performed on the central zone to measure the ratio of (Cho + Cre) /Cit. Results: The mean ratio of (Cho + Cre)/Cit in central zone of glandular BPH was 0.55 ± 0.32, whereas that of stromal BPH was 0.87 ± 0.34. Statistically significant difference was detected between the two types of BPH (t=8.18, P<0.05). Conclusion: The metabolic levels of prostate with BPH could be measured with MRS quantitatively, and metabolic difference could be detected between glandular BPH and stromal BPH. (authors)

Helping a community control its future: Potential negotiating packages and benefits for an MRS host

International Nuclear Information System (INIS)

Helvey, E.; Kane, D.; Trebules, V.

1993-01-01

The voluntary sitting process for the Monitored Retrievable Storage (MRS) facility set forth in the Nuclear Waste Policy Amendments Act (NWPAA) of 1987 provides a potential host community a unique opportunity to improve its present situation and to gain greater control over its future. To take full advantage of that opportunity throughout the life of the facility, an interested host must bring two things to the negotiating table: (1) a clear understanding of the special benefits, concerns and impacts associated with siting a controversial facility along with a detailed plan for addressing the requirements and impacts of such a facility; and (2) a vision of what the community wants to be in the future and list of specific measures it might achieve through negotiations that would help it realize that future. This paper investigates potential negotiating options a host might develop that, while addressing the impacts arena, also set forth terms by which the host can use the MRS to gain greater control over its unique set of resources and needs. The first section of this paper highlights the major concerns that a community might raise when debating whether to host an MRS and lists generic mitigation techniques that address those concerns. The second section pulls those mitigation techniques together into negotiating packages to show how the same concerns can be addressed differently depending on the strengths, weaknesses, and priorities of two different hypothetical host communities

A mutation in the gene encoding mitochondrial Mg²+ channel MRS2 results in demyelination in the rat.

Directory of Open Access Journals (Sweden)

Takashi Kuramoto

2011-01-01

Full Text Available The rat demyelination (dmy mutation serves as a unique model system to investigate the maintenance of myelin, because it provokes severe myelin breakdown in the central nervous system (CNS after normal postnatal completion of myelination. Here, we report the molecular characterization of this mutation and discuss the possible pathomechanisms underlying demyelination. By positional cloning, we found that a G-to-A transition, 177 bp downstream of exon 3 of the Mrs2 (MRS2 magnesium homeostasis factor (Saccharomyces cerevisiae gene, generated a novel splice acceptor site which resulted in functional inactivation of the mutant allele. Transgenic rescue with wild-type Mrs2-cDNA validated our findings. Mrs2 encodes an essential component of the major Mg²+ influx system in mitochondria of yeast as well as human cells. We showed that the dmy/dmy rats have major mitochondrial deficits with a markedly elevated lactic acid concentration in the cerebrospinal fluid, a 60% reduction in ATP, and increased numbers of mitochondria in the swollen cytoplasm of oligodendrocytes. MRS2-GFP recombinant BAC transgenic rats showed that MRS2 was dominantly expressed in neurons rather than oligodendrocytes and was ultrastructurally observed in the inner membrane of mitochondria. Our observations led to the conclusion that dmy/dmy rats suffer from a mitochondrial disease and that the maintenance of myelin has a different mechanism from its initial production. They also established that Mg²+ homeostasis in CNS mitochondria is essential for the maintenance of myelin.

Automation of column-based radiochemical separations. A comparison of fluidic, robotic, and hybrid architectures

Energy Technology Data Exchange (ETDEWEB)

Grate, J.W.; O' Hara, M.J.; Farawila, A.F.; Ozanich, R.M.; Owsley, S.L. [Pacific Northwest National Laboratory, Richland, WA (United States)

2011-07-01

Two automated systems have been developed to perform column-based radiochemical separation procedures. These new systems are compared with past fluidic column separation architectures, with emphasis on using disposable components so that no sample contacts any surface that any other sample has contacted, and setting up samples and columns in parallel for subsequent automated processing. In the first new approach, a general purpose liquid handling robot has been modified and programmed to perform anion exchange separations using 2 mL bed columns in 6 mL plastic disposable column bodies. In the second new approach, a fluidic system has been developed to deliver clean reagents through disposable manual valves to six disposable columns, with a mechanized fraction collector that positions one of four rows of six vials below the columns. The samples are delivered to each column via a manual 3-port disposable valve from disposable syringes. This second approach, a hybrid of fluidic and mechanized components, is a simpler more efficient approach for performing anion exchange procedures for the recovery and purification of plutonium from samples. The automation architectures described can also be adapted to column-based extraction chromatography separations. (orig.)

Home Automation System Based on Intelligent Transducer Enablers

Science.gov (United States)

Suárez-Albela, Manuel; Fraga-Lamas, Paula; Fernández-Caramés, Tiago M.; Dapena, Adriana; González-López, Miguel

2016-01-01

This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet. PMID:27690031

Home Automation System Based on Intelligent Transducer Enablers.

Science.gov (United States)

Suárez-Albela, Manuel; Fraga-Lamas, Paula; Fernández-Caramés, Tiago M; Dapena, Adriana; González-López, Miguel

2016-09-28

This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.

Home Automation System Based on Intelligent Transducer Enablers

Directory of Open Access Journals (Sweden)

Manuel Suárez-Albela

2016-09-01

Full Text Available This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers, which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.

Automated Functional Testing based on the Navigation of Web Applications

Directory of Open Access Journals (Sweden)

Boni García

2011-08-01

Full Text Available Web applications are becoming more and more complex. Testing such applications is an intricate hard and time-consuming activity. Therefore, testing is often poorly performed or skipped by practitioners. Test automation can help to avoid this situation. Hence, this paper presents a novel approach to perform automated software testing for web applications based on its navigation. On the one hand, web navigation is the process of traversing a web application using a browser. On the other hand, functional requirements are actions that an application must do. Therefore, the evaluation of the correct navigation of web applications results in the assessment of the specified functional requirements. The proposed method to perform the automation is done in four levels: test case generation, test data derivation, test case execution, and test case reporting. This method is driven by three kinds of inputs: i UML models; ii Selenium scripts; iii XML files. We have implemented our approach in an open-source testing framework named Automatic Testing Platform. The validation of this work has been carried out by means of a case study, in which the target is a real invoice management system developed using a model-driven approach.

A scaling transformation for classifier output based on likelihood ratio: Applications to a CAD workstation for diagnosis of breast cancer

International Nuclear Information System (INIS)

Horsch, Karla; Pesce, Lorenzo L.; Giger, Maryellen L.; Metz, Charles E.; Jiang Yulei

2012-01-01

Purpose: The authors developed scaling methods that monotonically transform the output of one classifier to the ''scale'' of another. Such transformations affect the distribution of classifier output while leaving the ROC curve unchanged. In particular, they investigated transformations between radiologists and computer classifiers, with the goal of addressing the problem of comparing and interpreting case-specific values of output from two classifiers. Methods: Using both simulated and radiologists' rating data of breast imaging cases, the authors investigated a likelihood-ratio-scaling transformation, based on ''matching'' classifier likelihood ratios. For comparison, three other scaling transformations were investigated that were based on matching classifier true positive fraction, false positive fraction, or cumulative distribution function, respectively. The authors explored modifying the computer output to reflect the scale of the radiologist, as well as modifying the radiologist's ratings to reflect the scale of the computer. They also evaluated how dataset size affects the transformations. Results: When ROC curves of two classifiers differed substantially, the four transformations were found to be quite different. The likelihood-ratio scaling transformation was found to vary widely from radiologist to radiologist. Similar results were found for the other transformations. Our simulations explored the effect of database sizes on the accuracy of the estimation of our scaling transformations. Conclusions: The likelihood-ratio-scaling transformation that the authors have developed and evaluated was shown to be capable of transforming computer and radiologist outputs to a common scale reliably, thereby allowing the comparison of the computer and radiologist outputs on the basis of a clinically relevant statistic.

Illuminance-based slat angle selection model for automated control of split blinds

Energy Technology Data Exchange (ETDEWEB)

Hu, Jia; Olbina, Svetlana [Rinker School of Building Construction, University of Florida, Gainesville, FL 32611-5703 (United States)

2011-03-15

Venetian blinds play an important role in controlling daylight in buildings. Automated blinds overcome some limitations of manual blinds; however, the existing automated systems mainly control the direct solar radiation and glare and cannot be used for controlling innovative blind systems such as split blinds. This research developed an Illuminance-based Slat Angle Selection (ISAS) model that predicts the optimum slat angles of split blinds to achieve the designed indoor illuminance. The model was constructed based on a series of multi-layer feed-forward artificial neural networks (ANNs). The illuminance values at the sensor points used to develop the ANNs were obtained by the software EnergyPlus trademark. The weather determinants (such as horizontal illuminance and sun angles) were used as the input variables for the ANNs. The illuminance level at a sensor point was the output variable for the ANNs. The ISAS model was validated by evaluating the errors in the calculation of the: 1) illuminance and 2) optimum slat angles. The validation results showed that the power of the ISAS model to predict illuminance was 94.7% while its power to calculate the optimum slat angles was 98.5%. For about 90% of time in the year, the illuminance percentage errors were less than 10%, and the percentage errors in calculating the optimum slat angles were less than 5%. This research offers a new approach for the automated control of split blinds and a guide for future research to utilize the adaptive nature of ANNs to develop a more practical and applicable blind control system. (author)

Automated migration analysis based on cell texture: method & reliability

Directory of Open Access Journals (Sweden)

Chittenden Thomas W

2005-03-01

Full Text Available Abstract Background In this paper, we present and validate a way to measure automatically the extent of cell migration based on automated examination of a series of digital photographs. It was designed specifically to identify the impact of Second Hand Smoke (SHS on endothelial cell migration but has broader applications. The analysis has two stages: (1 preprocessing of image texture, and (2 migration analysis. Results The output is a graphic overlay that indicates the front lines of cell migration superimposed on each original image, with automated reporting of the distance traversed vs. time. Expert preference compares to manual placement of leading edge shows complete equivalence of automated vs. manual leading edge definition for cell migration measurement. Conclusion Our method is indistinguishable from careful manual determinations of cell front lines, with the advantages of full automation, objectivity, and speed.

Automated segmentation of dental CBCT image with prior-guided sequential random forests

Energy Technology Data Exchange (ETDEWEB)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7513 (United States); Chen, Ken-Chung; Tang, Zhen [Surgical Planning Laboratory, Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, Texas 77030 (United States); Xia, James J., E-mail: dgshen@med.unc.edu, E-mail: JXia@HoustonMethodist.org [Surgical Planning Laboratory, Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, Texas 77030 (United States); Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, New York 10065 (United States); Department of Oral and Craniomaxillofacial Surgery, Shanghai Jiao Tong University School of Medicine, Shanghai Ninth People’s Hospital, Shanghai 200011 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu, E-mail: JXia@HoustonMethodist.org [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7513 and Department of Brain and Cognitive Engineering, Korea University, Seoul 02841 (Korea, Republic of)

2016-01-15

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimate the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method

Automated segmentation of dental CBCT image with prior-guided sequential random forests

International Nuclear Information System (INIS)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Chen, Ken-Chung; Tang, Zhen; Xia, James J.; Shen, Dinggang

2016-01-01

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimate the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method

Sensor-based automated docking of large waste canisters

International Nuclear Information System (INIS)

Drotning, W.D.

1990-01-01

Sensor-based programmable robots have the potential to speed up remote manipulation operations while protecting operators from exposure to radiation. Conventional master/slave manipulators have proven to be very slow in performing precision remote operations. In addition, inadvertent collisions of remotely manipulated objects with their environment increase the hazards associated with remote handling. This paper describes the development of a robotic system for the sensor-based automated remote manipulation and precision docking of large payloads. Computer vision and proximity sensing are used to control the precision docking of a large object with a passive target cavity. Specifically, a container of nuclear spent fuel on a transport vehicle is mated with an emplacement door on a vertical storage borehole at a waste repository

Automation for mineral resource development

Energy Technology Data Exchange (ETDEWEB)

Norrie, A.W.; Turner, D.R. (eds.)

1986-01-01

A total of 55 papers were presented at the symposium under the following headings: automation and the future of mining; modelling and control of mining processes; transportation for mining; automation and the future of metallurgical processes; modelling and control of metallurgical processes; and general aspects. Fifteen papers have been abstracted separately.

Development of a framework of human-centered automation for the nuclear industry

International Nuclear Information System (INIS)

Nelson, W.R.; Haney, L.N.

1993-01-01

Introduction of automated systems into control rooms for advanced reactor designs is often justified on the basis of increased efficiency and reliability, without a detailed assessment of how the new technologies will influence the role of the operator. Such a ''technology-centered'' approach carries with it the risk that entirely new mechanisms for human error will be introduced, resulting in some unpleasant surprises when the plant goes into operation. The aviation industry has experienced some of these surprises since the introduction of automated systems into the cockpits of advanced technology aircraft. Pilot errors have actually been induced by automated systems, especially when the pilot doesn't fully understand what the automated systems are doing during all modes of operation. In order to structure the research program for investigating these problems, the National Aeronautics and Space Administration (NASA) has developed a framework for human-centered automation. This framework is described in the NASA document Human-Centered Aircraft Automation Philosophy by Charles Billings. It is the thesis of this paper that a corresponding framework of human-centered automation should be developed for the nuclear industry. Such a framework would serve to guide the design and regulation of automated systems for advanced reactor designs, and would help prevent some of the problems that have arisen in other applications that have followed a ''technology-centered'' approach

Composite Wavelet Filters for Enhanced Automated Target Recognition

Science.gov (United States)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Capacity Building in Open Medical Record System (OpenMRS) in ...

International Development Research Centre (IDRC) Digital Library (Canada)

Capacity Building in Open Medical Record System (OpenMRS) in Rwanda ... Partners in Health (PIH), an international nongovernmental organization, has demonstrated the usefulness of ... Journal articles ... will fund social science, population and public health, and health systems research relevant to the emerging crisis.

An open framework for automated chemical hazard assessment based on GreenScreen for Safer Chemicals: A proof of concept.

Science.gov (United States)

Wehage, Kristopher; Chenhansa, Panan; Schoenung, Julie M

2017-01-01

GreenScreen® for Safer Chemicals is a framework for comparative chemical hazard assessment. It is the first transparent, open and publicly accessible framework of its kind, allowing manufacturers and governmental agencies to make informed decisions about the chemicals and substances used in consumer products and buildings. In the GreenScreen® benchmarking process, chemical hazards are assessed and classified based on 18 hazard endpoints from up to 30 different sources. The result is a simple numerical benchmark score and accompanying assessment report that allows users to flag chemicals of concern and identify safer alternatives. Although the screening process is straightforward, aggregating and sorting hazard data is tedious, time-consuming, and prone to human error. In light of these challenges, the present work demonstrates the usage of automation to cull chemical hazard data from publicly available internet resources, assign metadata, and perform a GreenScreen® hazard assessment using the GreenScreen® "List Translator." The automated technique, written as a module in the Python programming language, generates GreenScreen® List Translation data for over 3000 chemicals in approximately 30 s. Discussion of the potential benefits and limitations of automated techniques is provided. By embedding the library into a web-based graphical user interface, the extensibility of the library is demonstrated. The accompanying source code is made available to the hazard assessment community. Integr Environ Assess Manag 2017;13:167-176. © 2016 SETAC. © 2016 SETAC.

DEVELOPMENT OF AN AUTOMATED BATCH-PROCESS SOLAR ...

African Journals Online (AJOL)

One of the shortcomings of solar disinfection of water (SODIS) is the absence of a feedback mechanism indicating treatment completion. This work presents the development of an automated batch-process water disinfection system aimed at solving this challenge. Locally sourced materials in addition to an Arduinomicro ...

What's New in the Library Automation Arena?

Science.gov (United States)

Breeding, Marshall

1998-01-01

Reviews trends in library automation based on vendors at the 1998 American Library Association Annual Conference. Discusses the major industry trend, a move from host-based computer systems to the new generation of client/server, object-oriented, open systems-based automation. Includes a summary of developments for 26 vendors. (LRW)

Just-in-time adaptive classifiers-part II: designing the classifier.

Science.gov (United States)

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.