Diagram, a Learning Environment for Initiation to Object-Oriented Modeling with UML Class Diagrams
Py, Dominique; Auxepaules, Ludovic; Alonso, Mathilde
2013-01-01
This paper presents Diagram, a learning environment for object-oriented modelling (OOM) with UML class diagrams. Diagram an open environment, in which the teacher can add new exercises without constraints on the vocabulary or the size of the diagram. The interface includes methodological help, encourages self-correcting and self-monitoring, and…
Students’ learning activities while studying biological process diagrams
Kragten, M.; Admiraal, W.; Rijlaarsdam, G.
2015-01-01
Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students’ learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each
How design guides learning from matrix diagrams
van der Meij, Jan; Amelsvoort, Marije; Anjewierden, Anjo
2017-01-01
Compared to text, diagrams are superior in their ability to structure and summarize information and to show relations between concepts and ideas. Perceptual cues, like arrows, are expected to improve the retention of diagrams by guiding the learner towards important elements or showing a preferred
How Design Guides Learning from Matrix Diagrams
van der Meij, Jan; van Amelsvoort, Marije; Anjewierden, Anjo
2017-01-01
Compared to text, diagrams are superior in their ability to structure and summarize information and to show relations between concepts and ideas. Perceptual cues, like arrows, are expected to improve the retention of diagrams by guiding the learner towards important elements or showing a preferred reading sequence. In our experiment, we analyzed…
A Study on an Accident Diagnosis Methodology Using Influence Diagrams
International Nuclear Information System (INIS)
Kang, Kyungmin; Jae, Moosung
2006-01-01
For nuclear power plants, EOPs help operators to diagnose, control and mitigate accidents. However, it is very difficult that operators follow appropriate EOPs for accidents with similar symptoms in a given short period of time. Also EOPs are very complicated to follow and have many procedures to do. Therefore, if operators cannot diagnose correctly, the accident would become severe. Correct diagnostic action depends on the decision making ability of operators. Therefore, the methodology that can diagnose accidents quickly and help operators follow appropriate procedures should be developed. Due to the complexity of the tasks, it is very important to reduce human errors during diagnostic actions. In this study, to minimize human errors an accident diagnosis model has been constructed based on EOPs, accident symptoms and component reliabilities. For construction of model, Influence Diagrams have been applied. This decision-making tool consists of nodes and arcs. It is applicable to complicated situations, such as those required for developing strategies for managing severe accidents in nuclear power plants. And quantification of model has performed with total probability and Bayesian theorem. Through this quantification, the results should help operators diagnose complex situations
Learning about Posterior Probability: Do Diagrams and Elaborative Interrogation Help?
Clinton, Virginia; Alibali, Martha W.; Nathan, Mitchell J.
2016-01-01
To learn from a text, students must make meaningful connections among related ideas in that text. This study examined the effectiveness of two methods of improving connections--elaborative interrogation and diagrams--in written lessons about posterior probability. Undergraduate students (N = 198) read a lesson in one of three questioning…
De Leng, Bas; Gijlers, Hannie
2015-05-01
To examine how collaborative diagramming affects discussion and knowledge construction when learning complex basic science topics in medical education, including its effectiveness in the reformulation phase of problem-based learning. Opinions and perceptions of students (n = 70) and tutors (n = 4) who used collaborative diagramming in tutorial groups were collected with a questionnaire and focus group discussions. A framework derived from the analysis of discourse in computer-supported collaborative leaning was used to construct the questionnaire. Video observations were used during the focus group discussions. Both students and tutors felt that collaborative diagramming positively affected discussion and knowledge construction. Students particularly appreciated that diagrams helped them to structure knowledge, to develop an overview of topics, and stimulated them to find relationships between topics. Tutors emphasized that diagramming increased interaction and enhanced the focus and detail of the discussion. Favourable conditions were the following: working with a shared whiteboard, using a diagram format that facilitated distribution, and applying half filled-in diagrams for non-content expert tutors and\\or for heterogeneous groups with low achieving students. The empirical findings in this study support the findings of earlier more descriptive studies that diagramming in a collaborative setting is valuable for learning complex knowledge in medicine.
de Leng, Bas; Gijlers, Aaltje H.
2015-01-01
Aim: To examine how collaborative diagramming affects discussion and knowledge construction when learning complex basic science topics in medical education, including its effectiveness in the reformulation phase of problem-based learning. Methods: Opinions and perceptions of students (n = 70) and
Learning Disability: Experience of Diagnosis
Kenyon, Elinor; Beail, Nigel; Jackson, Tom
2014-01-01
Studies have focused on the experience of diagnosis from the perspectives of parents of children with learning disabilities, but there has been limited methodologically rigorous investigation into the experience for the person themselves. Eight participants were recruited from a range of different backgrounds. Interviews were analysed using…
Ward, Robin E.; Wandersee, James
2000-01-01
Students must understand key concepts through reasoning, searching out related concepts, and making connections within multiple systems to learn science. The Roundhouse diagram was developed to be a concise, holistic, graphic representation of a science topic, process, or activity. Includes sample Roundhouse diagrams, a diagram checklist, and…
Automated discovery and construction of surface phase diagrams using machine learning
International Nuclear Information System (INIS)
Ulissi, Zachary W.; Singh, Aayush R.; Tsai, Charlie
2016-01-01
Surface phase diagrams are necessary for understanding surface chemistry in electrochemical catalysis, where a range of adsorbates and coverages exist at varying applied potentials. These diagrams are typically constructed using intuition, which risks missing complex coverages and configurations at potentials of interest. More accurate cluster expansion methods are often difficult to implement quickly for new surfaces. We adopt a machine learning approach to rectify both issues. Using a Gaussian process regression model, the free energy of all possible adsorbate coverages for surfaces is predicted for a finite number of adsorption sites. Our result demonstrates a rational, simple, and systematic approach for generating accurate free-energy diagrams with reduced computational resources. Finally, the Pourbaix diagram for the IrO_2(110) surface (with nine coverages from fully hydrogenated to fully oxygenated surfaces) is reconstructed using just 20 electronic structure relaxations, compared to approximately 90 using typical search methods. Similar efficiency is demonstrated for the MoS_2 surface.
Ozogul, G.; Johnson, A. M.; Moreno, R.; Reisslein, M.
2012-01-01
Technological literacy education involves the teaching of basic engineering principles and problem solving, including elementary electrical circuit analysis, to non-engineering students. Learning materials on circuit analysis typically rely on equations and schematic diagrams, which are often unfamiliar to non-engineering students. The goal of…
Hung, Y.-C.
2012-01-01
This paper investigates the impact of combining self explaining (SE) with computer architecture diagrams to help novice students learn assembly language programming. Pre- and post-test scores for the experimental and control groups were compared and subjected to covariance (ANCOVA) statistical analysis. Results indicate that the SE-plus-diagram…
A diagram retrieval method with multi-label learning
Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi
2015-01-01
In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.
Cromley, Jennifer G.; Bergey, Bradley W.; Fitzhugh, Shannon; Newcombe, Nora; Wills, Theodore W.; Shipley, Thomas F.; Tanaka, Jacqueline C.
2013-01-01
Can students be taught to better comprehend the diagrams in their textbooks? Can such teaching transfer to uninstructed diagrams in the same domain or even in a new domain? What methods work best for these goals? Building on previous research showing positive results compared to control groups in both laboratory studies and short-term…
Learning-based diagnosis and repair
Roos, Nico
2017-01-01
This paper proposes a new form of diagnosis and repair based on reinforcement learning. Self-interested agents learn locally which agents may provide a low quality of service for a task. The correctness of learned assessments of other agents is proved under conditions on exploration versus
Colwell, Morris A
1976-01-01
Electronic Diagrams is a ready reference and general guide to systems and circuit planning and in the preparation of diagrams for both newcomers and the more experienced. This book presents guidelines and logical procedures that the reader can follow and then be equipped to tackle large complex diagrams by recognition of characteristic 'building blocks' or 'black boxes'. The goal is to break down many of the barriers that often seem to deter students and laymen in learning the art of electronics, especially when they take up electronics as a spare time occupation. This text is comprised of nin
Organizational Diagnosis: Its Role in Organizational Learning.
Beer, Michael; Spector, Bert
1993-01-01
Sees diagnosis as process that helps organizations enhance their capacity to assess and change dysfunctional aspects of culture and patterns of behavior as basis for developing greater effectiveness and ensuring continuous improvement. Presents framework for understanding "learning diagnosis" in which diagnostic process is part of large-scale…
Metacomprehension judgements reflect the belief that diagrams improve learning from text.
Serra, Michael J; Dunlosky, John
2010-10-01
In two experiments we systematically explored whether people consider the format of text materials when judging their text learning, and whether doing so might inappropriately bias their judgements. Participants studied either text with diagrams (multimedia) or text alone and made both per-paragraph judgements and global judgements of their text learning. In Experiment 1 they judged their learning to be better for text with diagrams than for text alone. In that study, however, test performance was greater for multimedia, so the judgements may reflect either a belief in the power of multimedia or on-line processing. Experiment 2 replicated this finding and also included a third group that read texts with pictures that did not improve text performance. Judgements made by this group were just as high as those made by participants who received the effective multimedia format. These results confirm the hypothesis that people's metacomprehension judgements can be influenced by their beliefs about text format. Over-reliance on this multimedia heuristic, however, might reduce judgement accuracy in situations where it is invalid.
Diagnosis diagrams for passing signals on an automatic block signaling railway section
Spunei, E.; Piroi, I.; Chioncel, C. P.; Piroi, F.
2018-01-01
This work presents a diagnosis method for railway traffic security installations. More specifically, the authors present a series of diagnosis charts for passing signals on a railway block equipped with an automatic block signaling installation. These charts are based on the exploitation electric schemes, and are subsequently used to develop a diagnosis software package. The thus developed software package contributes substantially to a reduction of failure detection and remedy for these types of installation faults. The use of the software package eliminates making wrong decisions in the fault detection process, decisions that may result in longer remedy times and, sometimes, to railway traffic events.
Tippett, Christine D.
2016-03-01
The move from learning science from representations to learning science with representations has many potential and undocumented complexities. This thematic analysis partially explores the trends of representational uses in science instruction, examining 80 research studies on diagram use in science. These studies, published during 2000-2014, were located through searches of journal databases and books. Open coding of the studies identified 13 themes, 6 of which were identified in at least 10% of the studies: eliciting mental models, classroom-based research, multimedia principles, teaching and learning strategies, representational competence, and student agency. A shift in emphasis on learning with rather than learning from representations was evident across the three 5-year intervals considered, mirroring a pedagogical shift from science instruction as transmission of information to constructivist approaches in which learners actively negotiate understanding and construct knowledge. The themes and topics in recent research highlight areas of active interest and reveal gaps that may prove fruitful for further research, including classroom-based studies, the role of prior knowledge, and the use of eye-tracking. The results of the research included in this thematic review of the 2000-2014 literature suggest that both interpreting and constructing representations can lead to better understanding of science concepts.
Exploring the pros and cons of mechanistic case diagrams for problem-based learning
Directory of Open Access Journals (Sweden)
Minjeong Kim
2017-09-01
Full Text Available Purpose Mechanistic case diagram (MCD was recommended for increasing the depth of understanding of disease, but with few articles on its specific methods. We address the experience of making MCD in the fullest depth to identify the pros and cons of using MCDs in such ways. Methods During problem-based learning, we gave guidelines of MCD for its mechanistic exploration from subcellular processes to clinical features, being laid out in as much detail as possible. To understand the students’ attitudes and depth of study using MCDs, we analyzed the results of a questionnaire in an open format about experiencing MCDs and examined the resulting products. Results Through the responses to questionnaire, we found several favorable outcomes, major of which was deeper insight and comprehensive understanding of disease facilitated by the process of making well-organized diagram. The main disadvantages of these guidelines were the feeling of too much workload and difficulty of finding mechanisms. Students gave suggestions to overcome these problems: cautious reading of comprehensive texts, additional guidance from staff about depth and focus of mechanisms, and cooperative group work. From the analysis of maps, we recognized there should be allowance of diversities in the appearance of maps and many hypothetical connections, which could be related to an insufficient understanding of mechanisms in nature. Conclusion The more detailed an MCD task is, the better students can become acquainted with deep knowledges. However, this advantage should be balanced by the results that there are many ensuing difficulties for the work and deliberate help plans should be prepared.
Cheng, Peter C.-H.; Shipstone, David M.
2003-02-01
A new approach to the teaching of electricity is described that uses box and AVOW diagrams, novel representations of the properties of the electric circuit which portray current, voltage, resistance and power. The diagrams have been developed as aids to learning, understanding and problem solving. They also have the potential to promote conceptual change by challenging a number of commonly held misconceptions. The diagrams have been incorporated into A-level teaching materials on d.c. circuit theory and the rationale for this approach is contrasted with a number of strategies that have previously been reported. Part 2 of this paper (Cheng and Shipstone, International Journal of Science Education, in press) will present the results of preliminary school-based trials.
The importance of design in learning from node-link diagrams
Amelsvoort, Marije; van der Meij, Jan; Anjewierden, Anjo Allert; van der Meij, Hans
2013-01-01
Diagrams organize by location. They give spatial cues for finding and recognizing information and for making inferences. In education, diagrams are often used to help students understand and recall information. This study assessed the influence of perceptual cues on reading behavior and subsequent
Directory of Open Access Journals (Sweden)
Witkowski Kazimierz
2017-01-01
Full Text Available The paper analyzes the possibility to use the electronic type indicators in the diagnosis of marine engines. It has been shown that in-depth analysis of indicator diagrams would be useful – calculation of heat release characteristics. To make this possible, measuring indicated systems should meet a number of important requirements in or-der to ensure that they can be used for the diagnostic purposes. These includes: high precision sensors for the measurement of cylinder pressure, high speed and accuracy of measuring and recording of measured values. These also includes reliable determination of the top dead center piston (TDC. In order to demonstrate the impact of positional error TDC, simulation study was conducted in which indicated diagrams were used, obtained on a medium-speed four-stroke marine diesel engine type A25/30 and the low-speed two-stroke marine diesel engine type RTA76, Sulzer company.
Learning Diagnostic Diagrams in Transport-Based Data-Collection Systems
DEFF Research Database (Denmark)
Tran, Vu The; Eklund, Peter; Cook, Chris
2014-01-01
Insights about service improvement in a transit network can be gained by studying transit service reliability. In this paper, a general procedure for constructing a transit service reliability diagnostic (Tsrd) diagram based on a Bayesian network is proposed to automatically build a behavioural...
Rosengrant, David
2011-01-01
Multiple representations are a valuable tool to help students learn and understand physics concepts. Furthermore, representations help students learn how to think and act like real scientists. These representations include: pictures, free-body diagrams, energy bar charts, electrical circuits, and, more recently, computer simulations and…
Failure diagnosis using deep belief learning based health state classification
International Nuclear Information System (INIS)
Tamilselvan, Prasanna; Wang, Pingfeng
2013-01-01
Effective health diagnosis provides multifarious benefits such as improved safety, improved reliability and reduced costs for operation and maintenance of complex engineered systems. This paper presents a novel multi-sensor health diagnosis method using deep belief network (DBN). DBN has recently become a popular approach in machine learning for its promised advantages such as fast inference and the ability to encode richer and higher order network structures. The DBN employs a hierarchical structure with multiple stacked restricted Boltzmann machines and works through a layer by layer successive learning process. The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset. Health diagnosis using DBN based health state classification technique is compared with four existing diagnosis techniques. Benchmark classification problems and two engineering health diagnosis applications: aircraft engine health diagnosis and electric power transformer health diagnosis are employed to demonstrate the efficacy of the proposed approach
Learning disabilities: definitions, epidemiology, diagnosis, and intervention strategies.
Lagae, Lieven
2008-12-01
Learning problems occur in about 5% of school-aged children. Learning disabilities are specific and life-long but present with different school problems at different ages, depending on such factors as age, medical history, family history, and intelligence quotient. Proper individualized diagnosis and treatment plans are necessary to remediate these problems and to offer adequate coping strategies. Many children who have learning problems can be classified into one of two major categories: the dyslexia group or the nonverbal learning disability group. The role of the medical professional is important to guide parents in the diagnostic and therapeutic process.
Cerebral palsy: experiences of mothers after learning their child's diagnosis.
Huang, Yu-Ping; Kellett, Ursula M; St John, Winsome
2010-06-01
This study is a report of a study describing mothers' experience of learning that their child has been diagnosed with cerebral palsy. Learning a child's diagnosis of disability is a crisis for parents. Their reactions include shock, refusal to accept the diagnosis, anger, fear, and uncertainty about the extent of disability and associated impairment. Knowledge about parental reactions is based on studies conducted in western countries, many of which do not apply to Taiwan where Confucianism strongly influences cultural perspectives of family and disability. In this phenomenological study, data were collected in 2005-2006 using in-depth interviews and journaling with 15 Taiwanese mothers of children diagnosed with cerebral palsy. Hermeneutic analysis was undertaken of interview transcripts and journal notes. Four shared meanings associated with learning of their child's diagnosis were revealed: feeling out of control and powerless, mistrusting healthcare professionals, release and confirmation, and feeling blamed for not following traditional practices. Mothers experienced a loss of their 'ideal' child when their child was diagnosed with cerebral palsy. Expectations of 'normal' motherhood and fulfilling societal anticipation of giving birth to a healthy child were lost. Maintaining their husband's family honour and prosperity, as well as saving face in their community were threatened. Mixed feelings of disbelief, rejection, self-blame and sadness were compounded by uncertainty about their child's future. To promote better understanding of the child's condition, emotional support and information should be provided to the mother and family, both when informing them of the diagnosis and in the period after diagnosis.
Unsupervised process monitoring and fault diagnosis with machine learning methods
Aldrich, Chris
2013-01-01
This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data
Machine Learning Based Diagnosis of Lithium Batteries
Ibe-Ekeocha, Chinemerem Christopher
The depletion of the world's current petroleum reserve, coupled with the negative effects of carbon monoxide and other harmful petrochemical by-products on the environment, is the driving force behind the movement towards renewable and sustainable energy sources. Furthermore, the growing transportation sector consumes a significant portion of the total energy used in the United States. A complete electrification of this sector would require a significant development in electric vehicles (EVs) and hybrid electric vehicles (HEVs), thus translating to a reduction in the carbon footprint. As the market for EVs and HEVs grows, their battery management systems (BMS) need to be improved accordingly. The BMS is not only responsible for optimally charging and discharging the battery, but also monitoring battery's state of charge (SOC) and state of health (SOH). SOC, similar to an energy gauge, is a representation of a battery's remaining charge level as a percentage of its total possible charge at full capacity. Similarly, SOH is a measure of deterioration of a battery; thus it is a representation of the battery's age. Both SOC and SOH are not measurable, so it is important that these quantities are estimated accurately. An inaccurate estimation could not only be inconvenient for EV consumers, but also potentially detrimental to battery's performance and life. Such estimations could be implemented either online, while battery is in use, or offline when battery is at rest. This thesis presents intelligent online SOC and SOH estimation methods using machine learning tools such as artificial neural network (ANN). ANNs are a powerful generalization tool if programmed and trained effectively. Unlike other estimation strategies, the techniques used require no battery modeling or knowledge of battery internal parameters but rather uses battery's voltage, charge/discharge current, and ambient temperature measurements to accurately estimate battery's SOC and SOH. The developed
Oostrom, V. van
2004-01-01
We introduce the unifying notion of delimiting diagram. Hitherto unrelated results such as: Minimality of the internal needed strategy for orthogonal first-order term rewriting systems, maximality of the limit strategy for orthogonal higher-order pattern rewrite systems (with maximality of the
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...
Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming
Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta
2008-01-01
Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…
The Relationship of Learning and Performance Diagnosis at Different System Levels.
Lubega, Khalid
2003-01-01
Examines learning and performance diagnosis, separately and in relation to each other, as they function in organization systems; explains the relationship between learning and performance diagnosis at the individual, process, and organizational levels using a three-level performance model; and discusses types of learning, including nonlearning,…
Enhanced Data Representation by Kernel Metric Learning for Dementia Diagnosis
Directory of Open Access Journals (Sweden)
David Cárdenas-Peña
2017-07-01
Full Text Available Alzheimer's disease (AD is the kind of dementia that affects the most people around the world. Therefore, an early identification supporting effective treatments is required to increase the life quality of a wide number of patients. Recently, computer-aided diagnosis tools for dementia using Magnetic Resonance Imaging scans have been successfully proposed to discriminate between patients with AD, mild cognitive impairment, and healthy controls. Most of the attention has been given to the clinical data, provided by initiatives as the ADNI, supporting reliable researches on intervention, prevention, and treatments of AD. Therefore, there is a need for improving the performance of classification machines. In this paper, we propose a kernel framework for learning metrics that enhances conventional machines and supports the diagnosis of dementia. Our framework aims at building discriminative spaces through the maximization of center kernel alignment function, aiming at improving the discrimination of the three considered neurological classes. The proposed metric learning performance is evaluated on the widely-known ADNI database using three supervised classification machines (k-nn, SVM and NNs for multi-class and bi-class scenarios from structural MRIs. Specifically, from ADNI collection 286 AD patients, 379 MCI patients and 231 healthy controls are used for development and validation of our proposed metric learning framework. For the experimental validation, we split the data into two subsets: 30% of subjects used like a blindfolded assessment and 70% employed for parameter tuning. Then, in the preprocessing stage, each structural MRI scan a total of 310 morphological measurements are automatically extracted from by FreeSurfer software package and concatenated to build an input feature matrix. Obtained test performance results, show that including a supervised metric learning improves the compared baseline classifiers in both scenarios. In the multi
From State Diagram to Class Diagram
DEFF Research Database (Denmark)
Borch, Ole; Madsen, Per Printz
2009-01-01
UML class diagram and Java source code are interrelated and Java code is a kind of interchange format. Working with UML state diagram in CASE tools, a corresponding xml file is maintained. Designing state diagrams is mostly performed manually using design patterns and coding templates - a time...... consuming process. This article demonstrates how to compile such a diagram into Java code and later, by reverse engineering, produce a class diagram. The process from state diagram via intermediate SAX parsed xml file to Apache Velocity generated Java code is described. The result is a fast reproducible...
Machine learning, medical diagnosis, and biomedical engineering research - commentary.
Foster, Kenneth R; Koprowski, Robert; Skufca, Joseph D
2014-07-05
A large number of papers are appearing in the biomedical engineering literature that describe the use of machine learning techniques to develop classifiers for detection or diagnosis of disease. However, the usefulness of this approach in developing clinically validated diagnostic techniques so far has been limited and the methods are prone to overfitting and other problems which may not be immediately apparent to the investigators. This commentary is intended to help sensitize investigators as well as readers and reviewers of papers to some potential pitfalls in the development of classifiers, and suggests steps that researchers can take to help avoid these problems. Building classifiers should be viewed not simply as an add-on statistical analysis, but as part and parcel of the experimental process. Validation of classifiers for diagnostic applications should be considered as part of a much larger process of establishing the clinical validity of the diagnostic technique.
Deep Learning and Insomnia: Assisting Clinicians With Their Diagnosis.
Shahin, Mostafa; Ahmed, Beena; Hamida, Sana Tmar-Ben; Mulaffer, Fathima Lamana; Glos, Martin; Penzel, Thomas
2017-11-01
Effective sleep analysis is hampered by the lack of automated tools catering to disordered sleep patterns and cumbersome monitoring hardware. In this paper, we apply deep learning on a set of 57 EEG features extracted from a maximum of two EEG channels to accurately differentiate between patients with insomnia or controls with no sleep complaints. We investigated two different approaches to achieve this. The first approach used EEG data from the whole sleep recording irrespective of the sleep stage (stage-independent classification), while the second used only EEG data from insomnia-impacted specific sleep stages (stage-dependent classification). We trained and tested our system using both healthy and disordered sleep collected from 41 controls and 42 primary insomnia patients. When compared with manual assessments, an NREM + REM based classifier had an overall discrimination accuracy of 92% and 86% between two groups using both two and one EEG channels, respectively. These results demonstrate that deep learning can be used to assist in the diagnosis of sleep disorders such as insomnia.
Viral pathogenesis in diagrams
National Research Council Canada - National Science Library
Tremblay, Michel; Berthiaume, Laurent; Ackermann, Hans-Wolfgang
2001-01-01
.... The 268 diagrams in Viral Pathogenesis in Diagrams were selected from over 800 diagrams of English and French virological literature, including one derived from a famous drawing by Leonardo da Vinci...
Artrith, Nongnuch; Urban, Alexander; Ceder, Gerbrand
2018-06-01
The atomistic modeling of amorphous materials requires structure sizes and sampling statistics that are challenging to achieve with first-principles methods. Here, we propose a methodology to speed up the sampling of amorphous and disordered materials using a combination of a genetic algorithm and a specialized machine-learning potential based on artificial neural networks (ANNs). We show for the example of the amorphous LiSi alloy that around 1000 first-principles calculations are sufficient for the ANN-potential assisted sampling of low-energy atomic configurations in the entire amorphous LixSi phase space. The obtained phase diagram is validated by comparison with the results from an extensive sampling of LixSi configurations using molecular dynamics simulations and a general ANN potential trained to ˜45 000 first-principles calculations. This demonstrates the utility of the approach for the first-principles modeling of amorphous materials.
DEFF Research Database (Denmark)
Duijm, Nijs Jan
2008-01-01
Safety-barrier diagrams and the related so-called 'bow-tie' diagrams have become popular methods in risk analysis. This paper describes the syntax and principles for constructing consistent and valid safety-barrier diagrams. The relation of safety-barrier diagrams to other methods such as fault...... trees and Bayesian networks is discussed. A simple method for quantification of safety-barrier diagrams is proposed. It is concluded that safety-barrier diagrams provide a useful framework for an electronic data structure that integrates information from risk analysis with operational safety management....
Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun
2017-11-01
The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.
Carifio, James; Perla, Rocco J.
2009-01-01
This article presents a critical review and analysis of key studies that have been done in science education and other areas on the effects and effectiveness of using diagrams, graphs, photographs, illustrations, and concept maps as "adjunct visual aids" in the learning of scientific-technical content. It also summarizes and reviews those studies…
A Review of Current Machine Learning Techniques Used in Manufacturing Diagnosis
Ademujimi , Toyosi ,; Brundage , Michael ,; Prabhu , Vittaldas ,
2017-01-01
Part 6: Intelligent Diagnostics and Maintenance Solutions; International audience; Artificial intelligence applications are increasing due to advances in data collection systems, algorithms, and affordability of computing power. Within the manufacturing industry, machine learning algorithms are often used for improving manufacturing system fault diagnosis. This study focuses on a review of recent fault diagnosis applications in manufacturing that are based on several prominent machine learnin...
Introduction to Feynman diagrams
Bilenky, Samoil Mikhelevich
1974-01-01
Introduction to Feynman Diagrams provides Feynman diagram techniques and methods for calculating quantities measured experimentally. The book discusses topics Feynman diagrams intended for experimental physicists. Topics presented include methods for calculating the matrix elements (by perturbation theory) and the basic rules for constructing Feynman diagrams; techniques for calculating cross sections and polarizations; processes in which both leptons and hadrons take part; and the electromagnetic and weak form factors of nucleons. Experimental physicists and graduate students of physics will
Suarta, I Made; Suwintana, I Ketut
2015-01-01
In this paper, the Technology Acceptance Model (TAM) is extent with two external stimulus namely e-learning characteristics and basic ICT (Information and Communication Technology) competencies. The purpose of this study are (1) finding relationship between e-learning characteristics and lecturers' basic ICT competencies with the perceived ease of use and perceived usefulness of e-learning; and (2) determining the effect of e-learning characteristics and lecturer basic ICT competencies to the...
DEFF Research Database (Denmark)
Duijm, Nijs Jan
2007-01-01
Safety-barrier diagrams and the related so-called "bow-tie" diagrams have become popular methods in risk analysis. This paper describes the syntax and principles for constructing consistent and valid safety-barrier diagrams. The relation with other methods such as fault trees and Bayesian networks...... are discussed. A simple method for quantification of safety-barrier diagrams is proposed, including situations where safety barriers depend on shared common elements. It is concluded that safety-barrier diagrams provide a useful framework for an electronic data structure that integrates information from risk...... analysis with operational safety management....
A Learning Health Care System Using Computer-Aided Diagnosis.
Cahan, Amos; Cimino, James J
2017-03-08
Physicians intuitively apply pattern recognition when evaluating a patient. Rational diagnosis making requires that clinical patterns be put in the context of disease prior probability, yet physicians often exhibit flawed probabilistic reasoning. Difficulties in making a diagnosis are reflected in the high rates of deadly and costly diagnostic errors. Introduced 6 decades ago, computerized diagnosis support systems are still not widely used by internists. These systems cannot efficiently recognize patterns and are unable to consider the base rate of potential diagnoses. We review the limitations of current computer-aided diagnosis support systems. We then portray future diagnosis support systems and provide a conceptual framework for their development. We argue for capturing physician knowledge using a novel knowledge representation model of the clinical picture. This model (based on structured patient presentation patterns) holds not only symptoms and signs but also their temporal and semantic interrelations. We call for the collection of crowdsourced, automatically deidentified, structured patient patterns as means to support distributed knowledge accumulation and maintenance. In this approach, each structured patient pattern adds to a self-growing and -maintaining knowledge base, sharing the experience of physicians worldwide. Besides supporting diagnosis by relating the symptoms and signs with the final diagnosis recorded, the collective pattern map can also provide disease base-rate estimates and real-time surveillance for early detection of outbreaks. We explain how health care in resource-limited settings can benefit from using this approach and how it can be applied to provide feedback-rich medical education for both students and practitioners. ©Amos Cahan, James J Cimino. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.03.2017.
Busanello, F H; da Silveira, P F; Liedke, G S; Arús, N A; Vizzotto, M B; Silveira, H E D; Silveira, H L D
2015-11-01
Studies have shown that inappropriate therapeutic strategies may be adopted if crown and root changes are misdiagnosed, potentially leading to undesirable consequences. Therefore, the aim of this study was to evaluate a digital learning object, developed to improve skills in diagnosing radiographic dental changes. The object was developed using the Visual Basic Application (VBA) software and evaluated by 62 undergraduate students (male: 24 and female: 38) taking an imaging diagnosis course. Participants were divided in two groups: test group, which used the object and control group, which attended conventional classes. After 3 weeks, students answered a 10-question test and took a practice test to diagnose 20 changes in periapical radiographs. The results show that test group performed better that control group in both tests, with statistically significant difference (P = 0.004 and 0.003, respectively). In overall, female students were better than male students. Specific aspects of object usability were assessed using a structured questionnaire based on the System Usability Scale (SUS), with a score of 90.5 and 81.6 by male and female students, respectively. The results obtained in this study suggest that students who used the DLO performed better than those who used conventional methods. This suggests that the DLO may be a useful teaching tool for dentistry undergraduates, on distance learning courses and as a complementary tool in face-to-face teaching. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Using Supervised Learning Techniques for Diagnosis of Dynamic Systems
2002-05-04
diagnosis task is to determine the system elements that could cause decision trees [14], where classification is the result of a series of the erroneous...Rodriguez, Carlos J. Alonso y Q. Isaac Moro. Clasificaci6n de patrones temporales en sistemas dinimicos mediante Boosting y Alineamiento dinamico
A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing
Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.
2017-11-01
Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.
Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques
Chandra Prasetyo Utomo; Aan Kardiana; Rika Yuliwulandari
2014-01-01
Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks...
Fault Diagnosis for Engine Based on Single-Stage Extreme Learning Machine
Directory of Open Access Journals (Sweden)
Fei Gao
2016-01-01
Full Text Available Single-Stage Extreme Learning Machine (SS-ELM is presented to dispose of the mechanical fault diagnosis in this paper. Based on it, the traditional mapping type of extreme learning machine (ELM has been changed and the eigenvectors extracted from signal processing methods are directly regarded as outputs of the network’s hidden layer. Then the uncertainty that training data transformed from the input space to the ELM feature space with the ELM mapping and problem of the selection of the hidden nodes are avoided effectively. The experiment results of diesel engine fault diagnosis show good performance of the SS-ELM algorithm.
Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.
Parsa, Maryam; Panda, Priyadarshini; Sen, Shreyas; Roy, Kaushik
2017-07-01
Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for analysis of the large pool of data generated by the wearable devices. Deep learning is among the promising methods for analyzing such data for healthcare applications and disease diagnosis. However, the conventional deep neural networks are computationally intensive and it is impractical to use them in real-time diagnosis with low-powered on-body devices. We propose Staged Inference using Conditional Deep Learning (SICDL), as an energy efficient approach for creating healthcare monitoring systems. For smart diagnostics, we observe that all diagnoses are not equally challenging. The proposed approach thus decomposes the diagnoses into preliminary analysis (such as healthy vs unhealthy) and detailed analysis (such as identifying the specific type of cardio disease). The preliminary diagnosis is conducted real-time with a low complexity neural network realized on the resource-constrained on-body device. The detailed diagnosis requires a larger network that is implemented remotely in cloud and is conditionally activated only for detailed diagnosis (unhealthy individuals). We evaluated the proposed approach using available physiological sensor data from Physionet databases, and achieved 38% energy reduction in comparison to the conventional deep learning approach.
Aided diagnosis methods of breast cancer based on machine learning
Zhao, Yue; Wang, Nian; Cui, Xiaoyu
2017-08-01
In the field of medicine, quickly and accurately determining whether the patient is malignant or benign is the key to treatment. In this paper, K-Nearest Neighbor, Linear Discriminant Analysis, Logistic Regression were applied to predict the classification of thyroid,Her-2,PR,ER,Ki67,metastasis and lymph nodes in breast cancer, in order to recognize the benign and malignant breast tumors and achieve the purpose of aided diagnosis of breast cancer. The results showed that the highest classification accuracy of LDA was 88.56%, while the classification effect of KNN and Logistic Regression were better than that of LDA, the best accuracy reached 96.30%.
Fault Diagnosis of Batch Reactor Using Machine Learning Methods
Directory of Open Access Journals (Sweden)
Sujatha Subramanian
2014-01-01
Full Text Available Fault diagnosis of a batch reactor gives the early detection of fault and minimizes the risk of thermal runaway. It provides superior performance and helps to improve safety and consistency. It has become more vital in this technical era. In this paper, support vector machine (SVM is used to estimate the heat release (Qr of the batch reactor both normal and faulty conditions. The signature of the residual, which is obtained from the difference between nominal and estimated faulty Qr values, characterizes the different natures of faults occurring in the batch reactor. Appropriate statistical and geometric features are extracted from the residual signature and the total numbers of features are reduced using SVM attribute selection filter and principle component analysis (PCA techniques. artificial neural network (ANN classifiers like multilayer perceptron (MLP, radial basis function (RBF, and Bayes net are used to classify the different types of faults from the reduced features. It is observed from the result of the comparative study that the proposed method for fault diagnosis with limited number of features extracted from only one estimated parameter (Qr shows that it is more efficient and fast for diagnosing the typical faults.
Directory of Open Access Journals (Sweden)
Sergievskiy Maxim
2018-01-01
Full Text Available Most of object-oriented development technologies rely on the use of the universal modeling language UML; class diagrams play a very important role in the design process play, used to build a software system model. Modern CASE tools, which are the basic tools for object-oriented development, can’t be used to optimize UML diagrams. In this manuscript we will explain how, based on the use of design patterns and anti-patterns, class diagrams could be verified and optimized. Certain transformations can be carried out automatically; in other cases, potential inefficiencies will be indicated and recommendations given. This study also discusses additional CASE tools for validating and optimizing of UML class diagrams. For this purpose, a plugin has been developed that analyzes an XMI file containing a description of class diagrams.
Hockney, Roger
1987-01-01
Algorithmic phase diagrams are a neat and compact representation of the results of comparing the execution time of several algorithms for the solution of the same problem. As an example, the recent results are shown of Gannon and Van Rosendale on the solution of multiple tridiagonal systems of equations in the form of such diagrams. The act of preparing these diagrams has revealed an unexpectedly complex relationship between the best algorithm and the number and size of the tridiagonal systems, which was not evident from the algebraic formulae in the original paper. Even so, for a particular computer, one diagram suffices to predict the best algorithm for all problems that are likely to be encountered the prediction being read directly from the diagram without complex calculation.
Design ensemble machine learning model for breast cancer diagnosis.
Hsieh, Sheau-Ling; Hsieh, Sung-Huai; Cheng, Po-Hsun; Chen, Chi-Huang; Hsu, Kai-Ping; Lee, I-Shun; Wang, Zhenyu; Lai, Feipei
2012-10-01
In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.
[Identification of meridian-acupoint diagrams and meridian diagrams].
Shen, Wei-hong
2008-08-01
In acu-moxibustion literature, there are two kinds of diagrams, meridian-acupoint diagrams and meridian diagrams. Because they are very similar in outline, and people now have seldom seen the typical ancient meridian diagrams, meridian-acupoint diagrams have been being incorrectly considered to be the meridian diagrams for a long time. It results in confusion in acu-moxibustion academia. The present paper stresses its importance in academic research and introduces some methods for identifying them correctly. The key points for identification of meridian-acupoint diagrams and meridian diagrams are: the legend of diagrams and the drawing style of the ancient charts. In addition, the author makes a detailed explanation about some acu-moxibustion charts which are easily confused. In order to distinguish meridian-acupoint diagrams and meridian diagrams correctly, he or she shoulnd understand the diagrams' intrinsic information as much as possible and make a comprehensive analysis about them.
The CAREL Center for Education Diagnosis and Learning: A Self-Correcting Innovative Model.
Jenny, Albert
1968-01-01
The Central Atlantic Regional Educational Laboratory (CAREL) Center for Educational Diagnosis and Learning is a model based on a cybernetic approach for the development of educational programs designed to personalize the student's instructional experiences and humanize his daily living. The CAREL Project has set three major objectives and 12…
Differential Diagnosis of Dementia in the Field of Learning Disabilities: A Case Study
Bell, Dorothy M.; Turnbull, Allyson; Kidd, W. Bruce
2009-01-01
Assessment for a diagnosis of dementia is hard enough under the best possible conditions. There are possible alternative or concomitant diagnoses, such as depression, to consider. However, when the possible dementia concerns a gentleman with severe learning disabilities and with a severe communication disorder then this assessment becomes even…
Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit
2010-01-01
Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2010). Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the
Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit
2010-01-01
Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2010, August). Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases. Poster presented at the 32nd Annual Conference of the Cognitive Science
Chang, Yu-Ling; Bondi, Mark W.; Fennema-Notestine, Christine; McEvoy, Linda K.; Hagler, Donald J., Jr.; Jacobson, Mark W.; Dale, Anders M.
2010-01-01
Understanding the underlying qualitative features of memory deficits in mild cognitive impairment (MCI) can provide critical information for early detection of Alzheimer's disease (AD). This study sought to investigate the utility of both learning and retention measures in (a) the diagnosis of MCI, (b) predicting progression to AD, and (c)…
Learning and case-based reasoning for faults diagnosis-aiding in nuclear power plants
International Nuclear Information System (INIS)
Nicolini, C.
1998-01-01
The aim of this thesis is the design of a faults diagnosis-aiding system in a nuclear facility of the Cea. Actually the existing system allows the optimization of the production processes in regular operating conditions. Meanwhile during accidental events, the alarms, managed by threshold, are bringing no relevant information. To increase the reliability and the safety, the human operator needs a faults diagnosis-aiding system. The developed system, SECAPI, combines problem solving techniques and automatic learning techniques, that allow the diagnosis and the the simulation of various faults happening on nuclear facilities. Its reasoning principle uses case-based and rules-based techniques. SECAPI owns a learning module which reads out knowledge connected with faults. It can then simulate various faults, using the inductive logical computing. SECAPI has been applied on a radioactive tritium treatment operating channel, at the Cea with good results. (A.L.B.)
Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions.
Loh, Brian C S; Then, Patrick H H
2017-01-01
Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.
Yu, Jianbo
2016-11-01
The vibration signals of faulty machine are generally non-stationary and nonlinear under those complicated working conditions. Thus, it is a big challenge to extract and select the effective features from vibration signals for machinery fault diagnosis. This paper proposes a new manifold learning algorithm, joint global and local/nonlocal discriminant analysis (GLNDA), which aims to extract effective intrinsic geometrical information from the given vibration data. Comparisons with other regular methods, principal component analysis (PCA), local preserving projection (LPP), linear discriminant analysis (LDA) and local LDA (LLDA), illustrate the superiority of GLNDA in machinery fault diagnosis. Based on the extracted information by GLNDA, a GLNDA-based Fisher discriminant rule (FDR) is put forward and applied to machinery fault diagnosis without additional recognizer construction procedure. By importing Bagging into GLNDA score-based feature selection and FDR, a novel manifold ensemble method (selective GLNDA ensemble, SE-GLNDA) is investigated for machinery fault diagnosis. The motivation for developing ensemble of manifold learning components is that it can achieve higher accuracy and applicability than single component in machinery fault diagnosis. The effectiveness of the SE-GLNDA-based fault diagnosis method has been verified by experimental results from bearing full life testers.
Directory of Open Access Journals (Sweden)
Jose M. Bernal-de-Lázaro
2016-05-01
Full Text Available This article summarizes the main contributions of the PhD thesis titled: "Application of learning techniques based on kernel methods for the fault diagnosis in Industrial processes". This thesis focuses on the analysis and design of fault diagnosis systems (DDF based on historical data. Specifically this thesis provides: (1 new criteria for adjustment of the kernel methods used to select features with a high discriminative capacity for the fault diagnosis tasks, (2 a proposed approach process monitoring using statistical techniques multivariate that incorporates a reinforced information concerning to the dynamics of the Hotelling's T2 and SPE statistics, whose combination with kernel methods improves the detection of small-magnitude faults; (3 an robustness index to compare the diagnosis classifiers performance taking into account their insensitivity to possible noise and disturbance on historical data.
Landmark-based deep multi-instance learning for brain disease diagnosis.
Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang
2018-01-01
In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.
Organizational diagnosis of computer and information learning needs: the process and product.
Nelson, R; Anton, B
1997-01-01
Organizational diagnosis views the organization as a single entity with problems and challenges that are unique to the organization as a whole. This paper describes the process of establishing organizational diagnoses related to computer and information learning needs within a clinical or academic health care institution. The assessment of a college within a state-owned university in the U.S.A. is used to demonstrate the process of organizational diagnosis. The diagnoses identified include the need to improve information seeking skills and the information presentation skills of faculty.
Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei
2017-09-01
Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.
Sanjuan-Jimenez, Rocio; Colmenero, Juan D; Morata, Pilar
2017-06-01
Brucellosis remains an emerging and re-emerging zoonosis worldwide causing high human morbidity. It usually affects persons who are permanently exposed to fastidious microorganisms of the Brucella genus and has a nonspecific clinical picture. Thus, diagnosis of brucellosis can sometimes be difficult. Molecular techniques have recently been found very useful in the diagnosis of brucellosis together with its common and very diverse focal complications. We herein review all the lessons learned by our group concerning the molecular diagnosis of human brucellosis over the last twenty years. The results, initially using one-step conventional PCR, later PCR-ELISA and more recently real-time PCR, using both fluorescent intercalating reagents (SYBR-Green I) and specific probes (Taqman), have shown that these techniques are all much more sensitive than bacteriological methods and more specific than the usual serological techniques for the diagnosis of primary infection, the post-treatment control of the disease, early detection of relapse and the diagnosis of focal complications. Optimization of the technique and improvements introduced over the years show that molecular methods, currently accessible for most clinical laboratories, enable easy rapid diagnosis of brucellosis at the same time as they avoid any risk to laboratory personnel while handling live Brucella spp. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Magda Solange Vanzo Pestun
Full Text Available Nonverbal learning disabilities (NVLD, a clinical condition still little reported in Brazil, are characterized by damages in the visual spatial domains, visual motor integration, fine motor skills, math skills and social and emotional difficulties. Developmental Dyscalculia (DD is a neurodevelopmental disorder that affects basic arithmetic skills acquisition, including storage and recovery of arithmetic facts, calculation fluency and precision and number sense domain. Although both are persistent Math learning disorder/disability, they cause different damages. The objective of this case report is to describe, compare and analyze the neuropsychological profile of two Brazilian children with similar complaints but distinct diagnosis.
Directory of Open Access Journals (Sweden)
Zhi-Xin Yang
2016-05-01
Full Text Available Reliable and quick response fault diagnosis is crucial for the wind turbine generator system (WTGS to avoid unplanned interruption and to reduce the maintenance cost. However, the conditional data generated from WTGS operating in a tough environment is always dynamical and high-dimensional. To address these challenges, we propose a new fault diagnosis scheme which is composed of multiple extreme learning machines (ELM in a hierarchical structure, where a forwarding list of ELM layers is concatenated and each of them is processed independently for its corresponding role. The framework enables both representational feature learning and fault classification. The multi-layered ELM based representational learning covers functions including data preprocessing, feature extraction and dimension reduction. An ELM based autoencoder is trained to generate a hidden layer output weight matrix, which is then used to transform the input dataset into a new feature representation. Compared with the traditional feature extraction methods which may empirically wipe off some “insignificant’ feature information that in fact conveys certain undiscovered important knowledge, the introduced representational learning method could overcome the loss of information content. The computed output weight matrix projects the high dimensional input vector into a compressed and orthogonally weighted distribution. The last single layer of ELM is applied for fault classification. Unlike the greedy layer wise learning method adopted in back propagation based deep learning (DL, the proposed framework does not need iterative fine-tuning of parameters. To evaluate its experimental performance, comparison tests are carried out on a wind turbine generator simulator. The results show that the proposed diagnostic framework achieves the best performance among the compared approaches in terms of accuracy and efficiency in multiple faults detection of wind turbines.
Minimization of annotation work: diagnosis of mammographic masses via active learning
Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu
2018-06-01
The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the
Diagrams of natural deductions
Energy Technology Data Exchange (ETDEWEB)
Popov, S V
1982-01-01
The concept of natural deductions was investigated by the author in his analysis of the complexity of deductions in propositional computations (1975). Here some natural deduction systems are considered, and an analytical procedure proposed which results in a deduction diagram for each system. Each diagram takes the form of an orientated, charge graph, features of which can be used to establish the equivalence of classes of deductions. For each of the natural deduction systems considered, a system of equivalent transformation schemes is derived, which is complete with respect to the given definition of equivalence. 2 references.
Comprehending 3D Diagrams: Sketching to Support Spatial Reasoning.
Gagnier, Kristin M; Atit, Kinnari; Ormand, Carol J; Shipley, Thomas F
2017-10-01
Science, technology, engineering, and mathematics (STEM) disciplines commonly illustrate 3D relationships in diagrams, yet these are often challenging for students. Failing to understand diagrams can hinder success in STEM because scientific practice requires understanding and creating diagrammatic representations. We explore a new approach to improving student understanding of diagrams that convey 3D relations that is based on students generating their own predictive diagrams. Participants' comprehension of 3D spatial diagrams was measured in a pre- and post-design where students selected the correct 2D slice through 3D geologic block diagrams. Generating sketches that predicated the internal structure of a model led to greater improvement in diagram understanding than visualizing the interior of the model without sketching, or sketching the model without attempting to predict unseen spatial relations. In addition, we found a positive correlation between sketched diagram accuracy and improvement on the diagram comprehension measure. Results suggest that generating a predictive diagram facilitates students' abilities to make inferences about spatial relationships in diagrams. Implications for use of sketching in supporting STEM learning are discussed. Copyright © 2016 Cognitive Science Society, Inc.
Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning
Directory of Open Access Journals (Sweden)
Chuan Li
2016-06-01
Full Text Available Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. Vibration sensor signals collected from rotating mechanical systems are represented in the time, frequency, and time-frequency domains, each of which is then used to produce a statistical feature set. For learning statistical features, real-value Gaussian-Bernoulli restricted Boltzmann machines (GRBMs are stacked to develop a Gaussian-Bernoulli deep Boltzmann machine (GDBM. The suggested approach is applied as a deep statistical feature learning tool for both gearbox and bearing systems. The fault classification performances in experiments using this approach are 95.17% for the gearbox, and 91.75% for the bearing system. The proposed approach is compared to such standard methods as a support vector machine, GRBM and a combination model. In experiments, the best fault classification rate was detected using the proposed model. The results show that deep learning with statistical feature extraction has an essential improvement potential for diagnosing rotating machinery faults.
Li, Chuan; Sánchez, René-Vinicio; Zurita, Grover; Cerrada, Mariela; Cabrera, Diego
2016-06-17
Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. Vibration sensor signals collected from rotating mechanical systems are represented in the time, frequency, and time-frequency domains, each of which is then used to produce a statistical feature set. For learning statistical features, real-value Gaussian-Bernoulli restricted Boltzmann machines (GRBMs) are stacked to develop a Gaussian-Bernoulli deep Boltzmann machine (GDBM). The suggested approach is applied as a deep statistical feature learning tool for both gearbox and bearing systems. The fault classification performances in experiments using this approach are 95.17% for the gearbox, and 91.75% for the bearing system. The proposed approach is compared to such standard methods as a support vector machine, GRBM and a combination model. In experiments, the best fault classification rate was detected using the proposed model. The results show that deep learning with statistical feature extraction has an essential improvement potential for diagnosing rotating machinery faults.
Missed opportunities for diagnosis: lessons learned from diagnostic errors in primary care.
Goyder, Clare R; Jones, Caroline H D; Heneghan, Carl J; Thompson, Matthew J
2015-12-01
Because of the difficulties inherent in diagnosis in primary care, it is inevitable that diagnostic errors will occur. However, despite the important consequences associated with diagnostic errors and their estimated high prevalence, teaching and research on diagnostic error is a neglected area. To ascertain the key learning points from GPs' experiences of diagnostic errors and approaches to clinical decision making associated with these. Secondary analysis of 36 qualitative interviews with GPs in Oxfordshire, UK. Two datasets of semi-structured interviews were combined. Questions focused on GPs' experiences of diagnosis and diagnostic errors (or near misses) in routine primary care and out of hours. Interviews were audiorecorded, transcribed verbatim, and analysed thematically. Learning points include GPs' reliance on 'pattern recognition' and the failure of this strategy to identify atypical presentations; the importance of considering all potentially serious conditions using a 'restricted rule out' approach; and identifying and acting on a sense of unease. Strategies to help manage uncertainty in primary care were also discussed. Learning from previous examples of diagnostic errors is essential if these events are to be reduced in the future and this should be incorporated into GP training. At a practice level, learning points from experiences of diagnostic errors should be discussed more frequently; and more should be done to integrate these lessons nationally to understand and characterise diagnostic errors. © British Journal of General Practice 2015.
Czech Academy of Sciences Publication Activity Database
Markl, Martin
2002-01-01
Roč. 69, - (2002), s. 161-180 ISSN 0009-725X. [Winter School "Geometry and Physics" /21./. Srní, 13.01.2001-20.01.2001] R&D Projects: GA ČR GA201/99/0675 Keywords : colored operad%cofibrant model%homotopy diagram Subject RIV: BA - General Mathematics
Equational binary decision diagrams
J.F. Groote (Jan Friso); J.C. van de Pol (Jaco)
2000-01-01
textabstractWe incorporate equations in binary decision diagrams (BDD). The resulting objects are called EQ-BDDs. A straightforward notion of ordered EQ-BDDs (EQ-OBDD) is defined, and it is proved that each EQ-BDD is logically equivalent to an EQ-OBDD. Moreover, on EQ-OBDDs satisfiability and
Lindenbergh, R.C.
2002-01-01
The classic Voronoi diagram of a configuration of distinct points in the plane associates to each point that part of the plane that is closer to the point than to any other point in the configuration. In this thesis we no longer require all points to be distinct. After the introduction in
A Critical Appraisal of the "Day" Diagram
Roberts, Andrew P.; Tauxe, Lisa; Heslop, David; Zhao, Xiang; Jiang, Zhaoxia
2018-04-01
The "Day" diagram (Day et al., 1977, https://doi.org/10.1016/0031-9201(77)90108-X) is used widely to make inferences about the domain state of magnetic mineral assemblages. Based on theoretical and empirical arguments, the Day diagram is demarcated into stable "single domain" (SD), "pseudo single domain" ("PSD"), and "multidomain" (MD) zones. It is straightforward to make the necessary measurements for a sample and to plot results within the "domain state" framework based on the boundaries defined by Day et al. (1977, https://doi.org/10.1016/0031-9201(77)90108-X). We discuss 10 issues that limit Day diagram interpretation, including (1) magnetic mineralogy, (2) the associated magnetocrystalline anisotropy type, (3) mineral stoichiometry, (4) stress state, (5) surface oxidation, (6) magnetostatic interactions, (7) particle shape, (8) thermal relaxation, (9) magnetic particle mixtures, and (10) definitional/measurement issues. In most studies, these variables are unknowns and cannot be controlled for, so that hysteresis parameters for single bulk samples are nonunique and any data point in a Day diagram could result from infinite combinations of relevant variables. From this critical appraisal, we argue that the Day diagram is fundamentally ambiguous for domain state diagnosis. Widespread use of the Day diagram has also contributed significantly to prevalent but questionable views, including underrecognition of the importance of stable SD particles in the geological record and reinforcement of the unhelpful PSD concept and of its geological importance. Adoption of approaches that enable correct domain state diagnosis should be an urgent priority for component-specific understanding of magnetic mineral assemblages and for quantitative rock magnetic interpretation.
Vilímová, Zuzana
2015-01-01
TITLE: Perception and coping with the specific learning disabilities impacts on everyday life of children with this diagnosis. ABSTRACT This text is focused on recognition of impacts of the specific learning disabilities on everyday life as the children with this diagnosis themselves see it and the strategies used by these children in order to cope with these disabilities. The theoretical part summarizes the necessary knowledge of the early school age developmental stage, the interaction of a...
Yu-Chi Lin; Tung-Kuang Wu; Shian-Chang Huang; Ying-Ru Meng; Wen-Yau Liang
2011-01-01
Due to the implicit characteristics of learning disabilities (LDs), the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN) and support vector machine (SVM) have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST)...
Directory of Open Access Journals (Sweden)
Luís Costa
2016-01-01
Full Text Available The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer’s disease (AD. In this paper, we investigate if machine-learning classifiers offer the discriminative power for the diagnosis of AD based on postural control kinematics. We compared Support Vector Machines (SVMs, Multiple Layer Perceptrons (MLPs, Radial Basis Function Neural Networks (RBNs, and Deep Belief Networks (DBNs on 72 participants (36 AD patients and 36 healthy subjects exposed to seven increasingly difficult postural tasks. The decisional space was composed of 18 kinematic variables (adjusted for age, education, height, and weight, with or without neuropsychological evaluation (Montreal cognitive assessment (MoCA score, top ranked in an error incremental analysis. Classification results were based on threefold cross validation of 50 independent and randomized runs sets: training (50%, test (40%, and validation (10%. Having a decisional space relying solely on postural kinematics, accuracy of AD diagnosis ranged from 71.7 to 86.1%. Adding the MoCA variable, the accuracy ranged between 91 and 96.6%. MLP classifier achieved top performance in both decisional spaces. Having comprehended the interdynamic interaction between postural stability and cognitive performance, our results endorse machine-learning models as a useful tool for computer-aided diagnosis of AD based on postural control kinematics.
Repair of Partly Misspecified Causal Diagrams.
Oates, Chris J; Kasza, Jessica; Simpson, Julie A; Forbes, Andrew B
2017-07-01
Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is presented that repairs a misspecified causal diagram through the addition of edges. These edges are determined using a data-driven approach designed to provide improved statistical efficiency relative to de novo structure learning methods. Our main assumption is that the expert is "directionally informed," meaning that "false" edges provided by the expert would not create cycles if added to the "true" causal diagram. The overall procedure is cast as a preprocessing technique that is agnostic to subsequent causal inferences. Results based on simulated data and data derived from an observational cohort illustrate the potential for data-assisted elicitation in epidemiologic applications. See video abstract at, http://links.lww.com/EDE/B208.
Dong, Ruimin; Yang, Xiaoyan; Xing, Bangrong; Zou, Zihao; Zheng, Zhenda; Xie, Xujing; Zhu, Jieming; Chen, Lin; Zhou, Hanjian
2015-01-01
Concept mapping is an effective method in teaching and learning, however this strategy has not been evaluated among electrocardiogram (ECG) diagnosis learning. This study explored the use of concept maps to assist ECG study, and sought to analyze whether this method could improve undergraduate students’ ECG interpretation skills. There were 126 undergraduate medical students who were randomly selected and assigned to two groups, group A (n = 63) and group B (n = 63). Group A was taught to use concept maps to learn ECG diagnosis, while group B was taught by traditional methods. After the course, all of the students were assessed by having an ECG diagnostic test. Quantitative data which comprised test score and ECG features completion index was compared by using the unpaired Student’s t-test between the two groups. Further, a feedback questionnaire on concept maps used was also completed by group A, comments were evaluated by a five-point Likert scale. The test scores of ECGs interpretation was 7.36 ± 1.23 in Group A and 6.12 ± 1.39 in Group B. A significant advantage (P = 0.018) of concept maps was observed in ECG interpretation accuracy. No difference in the average ECG features completion index was observed between Group A (66.75 ± 15.35%) and Group B (62.93 ± 13.17%). According qualitative analysis, majority of students accepted concept maps as a helpful tool. Difficult to learn at the beginning and time consuming are the two problems in using this method, nevertheless most of the students indicated to continue using it. Concept maps could be a useful pedagogical tool in enhancing undergraduate medical students’ ECG interpretation skills. Furthermore, students indicated a positive attitude to it, and perceived it as a resource for learning. PMID:26221331
A novel local learning based approach with application to breast cancer diagnosis
Xu, Songhua; Tourassi, Georgia
2012-03-01
In this paper, we introduce a new local learning based approach and apply it for the well-studied problem of breast cancer diagnosis using BIRADS-based mammographic features. To learn from our clinical dataset the latent relationship between these features and the breast biopsy result, our method first dynamically partitions the whole sample population into multiple sub-population groups through stochastically searching the sample population clustering space. Each encountered clustering scheme in our online searching process is then used to create a certain sample population partition plan. For every resultant sub-population group identified according to a partition plan, our method then trains a dedicated local learner to capture the underlying data relationship. In our study, we adopt the linear logistic regression model as our local learning method's base learner. Such a choice is made both due to the well-understood linear nature of the problem, which is compellingly revealed by a rich body of prior studies, and the computational efficiency of linear logistic regression--the latter feature allows our local learning method to more effectively perform its search in the sample population clustering space. Using a database of 850 biopsy-proven cases, we compared the performance of our method with a large collection of publicly available state-of-the-art machine learning methods and successfully demonstrated its performance advantage with statistical significance.
Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer
Vandenberghe, Michel E.; Scott, Marietta L. J.; Scorer, Paul W.; Söderberg, Magnus; Balcerzak, Denis; Barker, Craig
2017-04-01
Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a computational approach based on deep learning that automatically scores HER2, a biomarker that defines patient eligibility for anti-HER2 targeted therapies in breast cancer. In a cohort of 71 breast tumour resection samples, automated scoring showed a concordance of 83% with a pathologist. The twelve discordant cases were then independently reviewed, leading to a modification of diagnosis from initial pathologist assessment for eight cases. Diagnostic discordance was found to be largely caused by perceptual differences in assessing HER2 expression due to high HER2 staining heterogeneity. This study provides evidence that deep learning aided diagnosis can facilitate clinical decision making in breast cancer by identifying cases at high risk of misdiagnosis.
Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu
2018-05-01
The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.
DEFF Research Database (Denmark)
Øhrstrøm, Peter
2011-01-01
Some very good arguments can be given in favor of the Augustinean wisdom, according to which it is impossible to provide a satisfactory definition of the concept of time. However, even in the absence of a proper definition, it is possible to deal with conceptual problems regarding time. It can...... be done in terms of analogies and metaphors. In particular, it is attractive to make use of Peirce's diagrams by means of which various kinds of conceptual experimentation can be carried out. This paper investigates how Peircean diagrams can be used within the study of time. In particular, we discuss 1......) the topological properties of time, 2) the implicative structure in tense logic, 3) the notions of open future and branching time models, and finally 4) tenselogical alternatives to branching time models....
International Nuclear Information System (INIS)
McCauley, T.M.; Eskinazi, M.; Henson, L.L.
1989-01-01
This paper discusses the changes in electrical document requirements that occur when construction is complete and a generating station starts commercial operation. The needs of operations and maintenance (O and M) personnel are analyzed and contrasted with those of construction to illustrate areas in which the construction documents (drawings, diagrams, and databases) are difficult to use for work at an operating station. The paper discusses the O and M electrical documents that the Arizona Nuclear Power Project (ANPP) believes are most beneficial for the three operating units at Palo Verde; these are control wiring diagrams and an associated document cross-reference list. The benefits offered by these new, station O and M-oriented documents are weighted against the cost of their creation and their impact on drawing maintenance
Energy Technology Data Exchange (ETDEWEB)
Wilms, R Scott [Los Alamos National Laboratory; Carlson, Bryan [Los Alamos National Laboratory; Coons, James [Los Alamos National Laboratory; Kubic, William [Los Alamos National Laboratory
2008-01-01
This presentation describes the development of the proposed Process Flow Diagram (PFD) for the Tokamak Exhaust Processing System (TEP) of ITER. A brief review of design efforts leading up to the PFD is followed by a description of the hydrogen-like, air-like, and waterlike processes. Two new design values are described; the mostcommon and most-demanding design values. The proposed PFD is shown to meet specifications under the most-common and mostdemanding design values.
Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis.
Radhakrishnan, Adityanarayanan; Damodaran, Karthik; Soylemezoglu, Ali C; Uhler, Caroline; Shivashankar, G V
2017-12-20
Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical properties of single cells and their nuclei as critical drivers for the onset of cancer. We here present a method to detect subtle changes in nuclear morphometrics at single-cell resolution by combining fluorescence imaging and deep learning. This assay includes a convolutional neural net pipeline and allows us to discriminate between normal and human breast cancer cell lines (fibrocystic and metastatic states) as well as normal and cancer cells in tissue slices with high accuracy. Further, we establish the sensitivity of our pipeline by detecting subtle alterations in normal cells when subjected to small mechano-chemical perturbations that mimic tumor microenvironments. In addition, our assay provides interpretable features that could aid pathological inspections. This pipeline opens new avenues for early disease diagnostics and drug discovery.
Feynman diagram drawing made easy
International Nuclear Information System (INIS)
Baillargeon, M.
1997-01-01
We present a drawing package optimised for Feynman diagrams. These can be constructed interactively with a mouse-driven graphical interface or from a script file, more suitable to work with a diagram generator. It provides most features encountered in Feynman diagrams and allows to modify every part of a diagram after its creation. Special attention has been paid to obtain a high quality printout as easily as possible. This package is written in Tcl/Tk and in C. (orig.)
Ring diagrams and phase transitions
International Nuclear Information System (INIS)
Takahashi, K.
1986-01-01
Ring diagrams at finite temperatures carry most infrared-singular parts among Feynman diagrams. Their effect to effective potentials are in general so significant that one must incorporate them as well as 1-loop diagrams. The author expresses these circumstances in some examples of supercooled phase transitions
Automation of Feynman diagram evaluations
International Nuclear Information System (INIS)
Tentyukov, M.N.
1998-01-01
A C-program DIANA (DIagram ANAlyser) for the automation of Feynman diagram evaluations is presented. It consists of two parts: the analyzer of diagrams and the interpreter of a special text manipulating language. This language can be used to create a source code for analytical or numerical evaluations and to keep the control of the process in general
Deep ensemble learning of sparse regression models for brain disease diagnosis.
Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang
2017-04-01
Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.
Brandhuber, Andreas; Travaglini, Gabriele
2006-01-01
Over the past two years, the use of on-shell techniques has deepened our understanding of the S-matrix of gauge theories and led to the calculation of many new scattering amplitudes. In these notes we review a particular on-shell method developed recently, the quantum MHV diagrams, and discuss applications to one-loop amplitudes. Furthermore, we briefly discuss the application of D-dimensional generalised unitarity to the calculation of scattering amplitudes in non-supersymmetric Yang-Mills.
Directory of Open Access Journals (Sweden)
R. Jegadeeshwaran
2015-03-01
Full Text Available In automobile, brake system is an essential part responsible for control of the vehicle. Any failure in the brake system impacts the vehicle's motion. It will generate frequent catastrophic effects on the vehicle cum passenger's safety. Thus the brake system plays a vital role in an automobile and hence condition monitoring of the brake system is essential. Vibration based condition monitoring using machine learning techniques are gaining momentum. This study is one such attempt to perform the condition monitoring of a hydraulic brake system through vibration analysis. In this research, the performance of a Clonal Selection Classification Algorithm (CSCA for brake fault diagnosis has been reported. A hydraulic brake system test rig was fabricated. Under good and faulty conditions of a brake system, the vibration signals were acquired using a piezoelectric transducer. The statistical parameters were extracted from the vibration signal. The best feature set was identified for classification using attribute evaluator. The selected features were then classified using CSCA. The classification accuracy of such artificial intelligence technique has been compared with other machine learning approaches and discussed. The Clonal Selection Classification Algorithm performs better and gives the maximum classification accuracy (96% for the fault diagnosis of a hydraulic brake system.
Directory of Open Access Journals (Sweden)
Shan Pang
2016-01-01
Full Text Available A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. Results show that, with optimized network structure, OM-ELM obtains better test accuracy in both applications and is more robust to sensor noise. Meanwhile it controls the model complexity and needs far less hidden nodes than multi-hidden-layer ELM, thus saving computer memory and making it more efficient to implement. All these advantages make our method an effective and reliable tool for engine component fault diagnosis tool.
Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima
2017-01-01
To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.
Directory of Open Access Journals (Sweden)
Philippe Burlina
Full Text Available To evaluate the use of ultrasound coupled with machine learning (ML and deep learning (DL techniques for automated or semi-automated classification of myositis.Eighty subjects comprised of 19 with inclusion body myositis (IBM, 14 with polymyositis (PM, 14 with dermatomyositis (DM, and 33 normal (N subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally were acquired. We considered three problems of classification including (A normal vs. affected (DM, PM, IBM; (B normal vs. IBM patients; and (C IBM vs. other types of myositis (DM or PM. We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification.The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A, 86.6% ± 2.4% for (B and 74.8% ± 3.9% for (C, while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A, 84.3% ± 2.3% for (B and 68.9% ± 2.5% for (C.This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.
Sun, Wenqing; Zheng, Bin; Qian, Wei
2017-10-01
This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images. Three multichannel ROI based deep structured algorithms were designed and implemented in this study: convolutional neural network (CNN), deep belief network (DBN), and stacked denoising autoencoder (SDAE). For the comparison purpose, we also implemented a CADx system using hand-crafted features including density features, texture features and morphological features. The performance of every scheme was evaluated by using a 10-fold cross-validation method and an assessment index of the area under the receiver operating characteristic curve (AUC). The observed highest area under the curve (AUC) was 0.899±0.018 achieved by CNN, which was significantly higher than traditional CADx with the AUC=0.848±0.026. The results from DBN was also slightly higher than CADx, while SDAE was slightly lower. By visualizing the automatic generated features, we found some meaningful detectors like curvy stroke detectors from deep structured schemes. The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis. With well-tuned parameters and large enough dataset, the deep learning algorithms can have better performance than current popular CADx. We believe the deep learning algorithms with similar data preprocessing procedure can be used in other medical image analysis areas as well. Copyright © 2017. Published by Elsevier Ltd.
International Nuclear Information System (INIS)
Csaki, Csaba; Grossman, Yuval; Tanedo, Philip; Tsai, Yuhsin
2011-01-01
We present an analysis of the loop-induced magnetic dipole operator in the Randall-Sundrum model of a warped extra dimension with anarchic bulk fermions and an IR brane-localized Higgs. These operators are finite at one-loop order and we explicitly calculate the branching ratio for μ→eγ using the mixed position/momentum space formalism. The particular bound on the anarchic Yukawa and Kaluza-Klein (KK) scales can depend on the flavor structure of the anarchic matrices. It is possible for a generic model to either be ruled out or unaffected by these bounds without any fine-tuning. We quantify how these models realize this surprising behavior. We also review tree-level lepton flavor bounds in these models and show that these are on the verge of tension with the μ→eγ bounds from typical models with a 3 TeV Kaluza-Klein scale. Further, we illuminate the nature of the one-loop finiteness of these diagrams and show how to accurately determine the degree of divergence of a five-dimensional loop diagram using both the five-dimensional and KK formalism. This power counting can be obfuscated in the four-dimensional Kaluza-Klein formalism and we explicitly point out subtleties that ensure that the two formalisms agree. Finally, we remark on the existence of a perturbative regime in which these one-loop results give the dominant contribution.
Deep learning and three-compartment breast imaging in breast cancer diagnosis
Drukker, Karen; Huynh, Benjamin Q.; Giger, Maryellen L.; Malkov, Serghei; Avila, Jesus I.; Fan, Bo; Joe, Bonnie; Kerlikowske, Karla; Drukteinis, Jennifer S.; Kazemi, Leila; Pereira, Malesa M.; Shepherd, John
2017-03-01
We investigated whether deep learning has potential to aid in the diagnosis of breast cancer when applied to mammograms and biologic tissue composition images derived from three-compartment (3CB) imaging. The dataset contained diagnostic mammograms and 3CB images (water, lipid, and protein content) of biopsy-sampled BIRADS 4 and 5 lesions in 195 patients. In 58 patients, the lesion manifested as a mass (13 malignant vs. 45 benign), in 87 as microcalcifications (19 vs. 68), and in 56 as (focal) asymmetry or architectural distortion (11 vs. 45). Six patients had both a mass and calcifications. For each mammogram and corresponding 3CB images, a 128x128 region of interest containing the lesion was selected by an expert radiologist and used directly as input to a deep learning method pretrained on a very large independent set of non-medical images. We used a nested leave-one-out-by-case (patient) model selection and classification protocol. The area under the ROC curve (AUC) for the task of distinguishing between benign and malignant lesions was used as performance metric. For the cases with mammographic masses, the AUC increased from 0.83 (mammograms alone) to 0.89 (mammograms+3CB, p=.162). For the microcalcification and asymmetry/architectural distortion cases the AUC increased from 0.84 to 0.91 (p=.116) and from 0.61 to 0.87 (p=.006), respectively. Our results indicate great potential for the application of deep learning methods in the diagnosis of breast cancer and additional knowledge of the biologic tissue composition appeared to improve performance, especially for lesions mammographically manifesting as asymmetries or architectural distortions.
Directory of Open Access Journals (Sweden)
Andrias Meisyal Yuwantoko
2017-03-01
Full Text Available Sebuah diagram urutan dibuat berdasarkan alur yang ada pada deskripsi kasus penggunaan. Alur tersebut dire- presentasikan dalam bentuk interaksi antara aktor dan sistem. Pemeriksaan rancangan diagram urutan perlu dilakukan untuk mengetahui ketidaksesuaian urutan alur kasus penggunaan dengan urutan pesan yang dikirimkan oleh objek-objek pada diagram urutan. Rancangan diagram yang sesuai merupakan kunci ketepatan (correctness implementasi perangkat lunak. Namun, pemeriksaan ketidaksesuaian masih dilakukan secara manual. Hal ini menjadi masalah apabila sebuah proyek perangkat lunak memiliki banyak rancangan diagram dan sumber daya manusia tidak mencukupi. Pemeriksaan membutuhkan waktu yang lama dan memiliki dampak pada waktu pengembangan perangkat lunak. Penelitian ini mengusulkan pembuatan kakas bantu untuk mendeteksi ketidaksesuaian diagram urutan dengan diagram kasus penggunaan. Ketidaksesuaian dilihat dari kemiripan semantik kalimat antara alur pada deskripsi kasus penggunaan dan triplet. Dari hasil pembuatan kakas bantu, kakas bantu yang dibuat dapat mendeteksi ketidaksesuaian diagram urutan dengan diagram kasus penggunaan. Kakas bantu ini diharapkan tidak hanya membantu pemeriksaan rancangan diagram akan tetapi mempercepat waktu pengembangan perangkat lunak.
KAYA, Yılmaz
2014-01-01
Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin B...
International Nuclear Information System (INIS)
Mohan, A.; Soni, N.C.; Moorthy, V.K.
1979-01-01
Ashby's method (see Acta Met., vol. 22, p. 275, 1974) of constructing sintering diagrams has been modified to obtain contribution diagrams directly from the computer. The interplay of sintering variables and mechanisms are studied and the factors that affect the participation of mechanisms in UO 2 are determined. By studying the physical properties, it emerges that the order of inaccuracies is small in most cases and do not affect the diagrams. On the other hand, even a 10% error in activation energies, which is quite plausible, would make a significant difference to the diagram. The main criticism of Ashby's approach is that the numerous properties and equations used, communicate their inaccuracies to the diagrams and make them unreliable. The present study has considerably reduced the number of factors that need to be refined to make the sintering diagrams more meaningful. (Auth.)
Drawing Euler Diagrams with Circles
Stapleton, Gem; Zhang, Leishi; Howse, John; Rodgers, Peter
2010-01-01
Euler diagrams are a popular and intuitive visualization tool which are used in a wide variety of application areas, including biological and medical data analysis. As with other data visualization methods, such as graphs, bar charts, or pie charts, the automated generation of an Euler diagram from a suitable data set would be advantageous, removing the burden of manual data analysis and the subsequent task of drawing an appropriate diagram. Various methods have emerged that automatically dra...
Development of a Deep Learning Algorithm for Automatic Diagnosis of Diabetic Retinopathy.
Raju, Manoj; Pagidimarri, Venkatesh; Barreto, Ryan; Kadam, Amrit; Kasivajjala, Vamsichandra; Aswath, Arun
2017-01-01
This paper mainly focuses on the deep learning application in classifying the stage of diabetic retinopathy and detecting the laterality of the eye using funduscopic images. Diabetic retinopathy is a chronic, progressive, sight-threatening disease of the retinal blood vessels. Ophthalmologists diagnose diabetic retinopathy through early funduscopic screening. Normally, there is a time delay in reporting and intervention, apart from the financial cost and risk of blindness associated with it. Using a convolutional neural network based approach for automatic diagnosis of diabetic retinopathy, we trained the prediction network on the publicly available Kaggle dataset. Approximately 35,000 images were used to train the network, which observed a sensitivity of 80.28% and a specificity of 92.29% on the validation dataset of ~53,000 images. Using 8,810 images, the network was trained for detecting the laterality of the eye and observed an accuracy of 93.28% on the validation set of 8,816 images.
Adaptive neural network/expert system that learns fault diagnosis for different structures
Simon, Solomon H.
1992-08-01
Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.
Discovering mammography-based machine learning classifiers for breast cancer diagnosis.
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.
Lin, Chin; Hsu, Chia-Jung; Lou, Yu-Sheng; Yeh, Shih-Jen; Lee, Chia-Cheng; Su, Sui-Lung; Chen, Hsiang-Cheng
2017-11-06
Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). Our objective was to compare the performance of traditional pipelines (NLP plus supervised machine learning models) with that of word embedding combined with a CNN in conducting a classification task identifying International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes in discharge notes. We used 2 classification methods: (1) extracting from discharge notes some features (terms, n-gram phrases, and SNOMED CT categories) that we used to train a set of supervised machine learning models (support vector machine, random forests, and gradient boosting machine), and (2) building a feature matrix, by a pretrained word embedding model, that we used to train a CNN. We used these methods to identify the chapter-level ICD-10-CM diagnosis codes in a set of discharge notes. We conducted the evaluation using 103,390 discharge notes covering patients hospitalized from June 1, 2015 to January 31, 2017 in the Tri-Service General Hospital in Taipei, Taiwan. We used the receiver operating characteristic curve as an evaluation measure, and calculated the area under the curve (AUC) and F-measure as the global measure of effectiveness. In 5-fold cross-validation tests, our method had a higher testing accuracy (mean AUC 0.9696; mean F-measure 0.9086) than traditional NLP-based approaches (mean AUC range 0.8183-0.9571; mean F-measure range 0.5050-0.8739). A real-world simulation that split the training sample and the testing sample by date verified this result (mean AUC 0.9645; mean F-measure 0.9003 using the proposed method). Further analysis showed that the convolutional layers of the CNN effectively identified a large number of keywords and automatically
Liu, Guo-Ping; Yan, Jian-Jun; Wang, Yi-Qin; Fu, Jing-Jing; Xu, Zhao-Xia; Guo, Rui; Qian, Peng
2012-01-01
Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs). Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:22719781
Directory of Open Access Journals (Sweden)
Guo-Ping Liu
2012-01-01
Full Text Available Background. In Traditional Chinese Medicine (TCM, most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs. Methods. We employed a multilabel learning using the relevant feature for each label (REAL algorithm to construct a syndrome diagnostic model for chronic gastritis (CG in TCM. REAL combines feature selection methods to select the significant symptoms (signs of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL, whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.
Guo, Yang; Lin, Wenfang; Yu, Shuyang; Ji, Yang
2018-01-01
Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs) and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM). However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D) to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods. PMID:29621131
Directory of Open Access Journals (Sweden)
Evanthia E. Tripoliti
Full Text Available Heart failure is a serious condition with high prevalence (about 2% in the adult population in developed countries, and more than 8% in patients older than 75 years. About 3–5% of hospital admissions are linked with heart failure incidents. Heart failure is the first cause of admission by healthcare professionals in their clinical practice. The costs are very high, reaching up to 2% of the total health costs in the developed countries. Building an effective disease management strategy requires analysis of large amount of data, early detection of the disease, assessment of the severity and early prediction of adverse events. This will inhibit the progression of the disease, will improve the quality of life of the patients and will reduce the associated medical costs. Toward this direction machine learning techniques have been employed. The aim of this paper is to present the state-of-the-art of the machine learning methodologies applied for the assessment of heart failure. More specifically, models predicting the presence, estimating the subtype, assessing the severity of heart failure and predicting the presence of adverse events, such as destabilizations, re-hospitalizations, and mortality are presented. According to the authors' knowledge, it is the first time that such a comprehensive review, focusing on all aspects of the management of heart failure, is presented. Keywords: Heart failure, Diagnosis, Prediction, Severity estimation, Classification, Data mining
Directory of Open Access Journals (Sweden)
Zhenyu Wu
2018-04-01
Full Text Available Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM. However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods.
Bhagyashree, Sheshadri Iyengar Raghavan; Nagaraj, Kiran; Prince, Martin; Fall, Caroline H D; Krishna, Murali
2018-01-01
There are limited data on the use of artificial intelligence methods for the diagnosis of dementia in epidemiological studies in low- and middle-income country (LMIC) settings. A culture and education fair battery of cognitive tests was developed and validated for population based studies in low- and middle-income countries including India by the 10/66 Dementia Research Group. We explored the machine learning methods based on the 10/66 battery of cognitive tests for the diagnosis of dementia based in a birth cohort study in South India. The data sets for 466 men and women for this study were obtained from the on-going Mysore Studies of Natal effect of Health and Ageing (MYNAH), in south India. The data sets included: demographics, performance on the 10/66 cognitive function tests, the 10/66 diagnosis of mental disorders and population based normative data for the 10/66 battery of cognitive function tests. Diagnosis of dementia from the rule based approach was compared against the 10/66 diagnosis of dementia. We have applied machine learning techniques to identify minimal number of the 10/66 cognitive function tests required for diagnosing dementia and derived an algorithm to improve the accuracy of dementia diagnosis. Of 466 subjects, 27 had 10/66 diagnosis of dementia, 19 of whom were correctly identified as having dementia by Jrip classification with 100% accuracy. This pilot exploratory study indicates that machine learning methods can help identify community dwelling older adults with 10/66 criterion diagnosis of dementia with good accuracy in a LMIC setting such as India. This should reduce the duration of the diagnostic assessment and make the process easier and quicker for clinicians, patients and will be useful for 'case' ascertainment in population based epidemiological studies.
Feynman diagrams without Feynman parameters
International Nuclear Information System (INIS)
Mendels, E.
1978-01-01
Dimensionally regularized Feynman diagrams are represented by means of products of k-functions. The infinite part of these diagrams is found very easily, also if they are overlapping, and the separation of the several kinds of divergences comes out quite naturally. Ward identities are proven in a transparent way. Series expansions in terms of the external momenta and their inner products are possible
Diagram Techniques in Group Theory
Stedman, Geoffrey E.
2009-09-01
Preface; 1. Elementary examples; 2. Angular momentum coupling diagram techniques; 3. Extension to compact simple phase groups; 4. Symmetric and unitary groups; 5. Lie groups and Lie algebras; 6. Polarisation dependence of multiphoton processes; 7. Quantum field theoretic diagram techniques for atomic systems; 8. Applications; Appendix; References; Indexes.
Contingency diagrams as teaching tools
Mattaini, Mark A.
1995-01-01
Contingency diagrams are particularly effective teaching tools, because they provide a means for students to view the complexities of contingency networks present in natural and laboratory settings while displaying the elementary processes that constitute those networks. This paper sketches recent developments in this visualization technology and illustrates approaches for using contingency diagrams in teaching.
Impact decision support diagrams
Boslough, Mark
2014-10-01
One way to frame the job of planetary defense is to “find the optimal approach for finding the optimal approach” to NEO mitigation. This requires a framework for defining in advance what should be done under various circumstances. The two-dimensional action matrix from the recent NRC report “Defending Planet Earth” can be generalized to a notional “Impact Decision Support Diagram” by extending it into a third dimension. The NRC action matrix incorporated two important axes: size and time-to-impact, but probability of impact is also critical (it is part of the definitions of both the Torino and Palermo scales). Uncertainty has been neglected, but is also crucial. It can be incorporated by subsuming it into the NEO size axis by redefining size to be three standard deviations greater than the best estimate, thereby providing a built-in conservative margin. The independent variable is time-to-impact, which is known with high precision. The other two axes are both quantitative assessments of uncertainty and are both time dependent. Thus, the diagram is entirely an expression of uncertainty. The true impact probability is either one or zero, and the true size does not change. The domain contains information about the current uncertainty, which changes with time (as opposed to reality, which does not change).
Genus Ranges of Chord Diagrams.
Burns, Jonathan; Jonoska, Nataša; Saito, Masahico
2015-04-01
A chord diagram consists of a circle, called the backbone, with line segments, called chords, whose endpoints are attached to distinct points on the circle. The genus of a chord diagram is the genus of the orientable surface obtained by thickening the backbone to an annulus and attaching bands to the inner boundary circle at the ends of each chord. Variations of this construction are considered here, where bands are possibly attached to the outer boundary circle of the annulus. The genus range of a chord diagram is the genus values over all such variations of surfaces thus obtained from a given chord diagram. Genus ranges of chord diagrams for a fixed number of chords are studied. Integer intervals that can be, and those that cannot be, realized as genus ranges are investigated. Computer calculations are presented, and play a key role in discovering and proving the properties of genus ranges.
Tay, Su Lynn; Yeo, Jennifer
2018-01-01
Great teaching is characterised by the specific actions a teacher takes in the classroom to bring about learning. In the context of model-based teaching (MBT), teachers' difficulty in working with students' models that are not scientifically consistent is troubling. To address this problem, the aim of this study is to identify the pedagogical micro-actions to support the development of scientific models and modelling skills during the evaluation and modification stages of MBT. Taking the perspective of pedagogical content knowing (PCKg), it identifies these micro-actions as an in-situ, dynamic transformation of knowledges of content, pedagogy, student and environment context. Through a case study approach, a lesson conducted by an experienced high-school physics teacher was examined. Audio and video recordings of the lesson contributed to the data sources. Taking a grounded approach in the analysis, eight pedagogical micro-actions enacted by the teacher were identified, namely 'clarification', 'evaluation', 'explanation', 'modification', 'exploration', 'referencing conventions', 'focusing' and 'meta-representing'. These micro-actions support students' learning related to the conceptual, cognitive, discursive and epistemological aspects of modelling. From the micro-actions, we identify the aspects of knowledges of PCKg that teachers need in order to competently select and enact these micro-actions. The in-situ and dynamic transformation of these knowledges implies that professional development should also be situated in the context in which these micro-actions are meaningful.
International Nuclear Information System (INIS)
Chen, Zhicong; Wu, Lijun; Cheng, Shuying; Lin, Peijie; Wu, Yue; Lin, Wencheng
2017-01-01
Highlights: •An improved Simulink based modeling method is proposed for PV modules and arrays. •Key points of I-V curves and PV model parameters are used as the feature variables. •Kernel extreme learning machine (KELM) is explored for PV arrays fault diagnosis. •The parameters of KELM algorithm are optimized by the Nelder-Mead simplex method. •The optimized KELM fault diagnosis model achieves high accuracy and reliability. -- Abstract: Fault diagnosis of photovoltaic (PV) arrays is important for improving the reliability, efficiency and safety of PV power stations, because the PV arrays usually operate in harsh outdoor environment and tend to suffer various faults. Due to the nonlinear output characteristics and varying operating environment of PV arrays, many machine learning based fault diagnosis methods have been proposed. However, there still exist some issues: fault diagnosis performance is still limited due to insufficient monitored information; fault diagnosis models are not efficient to be trained and updated; labeled fault data samples are hard to obtain by field experiments. To address these issues, this paper makes contribution in the following three aspects: (1) based on the key points and model parameters extracted from monitored I-V characteristic curves and environment condition, an effective and efficient feature vector of seven dimensions is proposed as the input of the fault diagnosis model; (2) the emerging kernel based extreme learning machine (KELM), which features extremely fast learning speed and good generalization performance, is utilized to automatically establish the fault diagnosis model. Moreover, the Nelder-Mead Simplex (NMS) optimization method is employed to optimize the KELM parameters which affect the classification performance; (3) an improved accurate Simulink based PV modeling approach is proposed for a laboratory PV array to facilitate the fault simulation and data sample acquisition. Intensive fault experiments are
Adaptive Diagrams: Handing Control over to the Learner to Manage Split-Attention Online
Agostinho, Shirley; Tindall-Ford, Sharon; Roodenrys, Kylie
2013-01-01
Based on cognitive load theory, it is well known that when studying a diagram that includes explanatory text, optimal learning occurs when the text is physically positioned close to the diagram as it eliminates the need for learners to split their attention between the two sources of information. What is not known is the effect on learning when…
Scherr, Rachel E.; Harrer, Benedikt W.; Close, Hunter G.; Daane, Abigail R.; DeWater, Lezlie S.; Robertson, Amy D.; Seeley, Lane; Vokos, Stamatis
2016-01-01
Energy is a crosscutting concept in science and features prominently in national science education documents. In the "Next Generation Science Standards," the primary conceptual learning goal is for learners to conserve energy as they "track" the transfers and transformations of energy within, into, or out of the system of…
Vidotti, Vanessa G; Costa, Vital P; Silva, Fabrício R; Resende, Graziela M; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S
2012-06-15
Purpose. To investigate the sensitivity and specificity of machine learning classifiers (MLC) and spectral domain optical coherence tomography (SD-OCT) for the diagnosis of glaucoma. Methods. Sixty-two patients with early to moderate glaucomatous visual field damage and 48 healthy individuals were included. All subjects underwent a complete ophthalmologic examination, achromatic standard automated perimetry, and RNFL imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, California, USA). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters. Subsequently, the following MLCs were tested: Classification Tree (CTREE), Random Forest (RAN), Bagging (BAG), AdaBoost M1 (ADA), Ensemble Selection (ENS), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Naive-Bayes (NB), and Support Vector Machine (SVM). Areas under the ROC curves (aROCs) obtained for each parameter and each MLC were compared. Results. The mean age was 57.0±9.2 years for healthy individuals and 59.9±9.0 years for glaucoma patients (p=0.103). Mean deviation values were -4.1±2.4 dB for glaucoma patients and -1.5±1.6 dB for healthy individuals (pposition (0.765), and 6 o'clock position (0.754). The aROCs from classifiers varied from 0.785 (ADA) to 0.818 (BAG). The aROC obtained with BAG was not significantly different from the aROC obtained with the best single SD-OCT parameter (p=0.93). Conclusions. The SD-OCT showed good diagnostic accuracy in a group of patients with early glaucoma. In this series, MLCs did not improve the sensitivity and specificity of SD-OCT for the diagnosis of glaucoma.
Para-equilibrium phase diagrams
International Nuclear Information System (INIS)
Pelton, Arthur D.; Koukkari, Pertti; Pajarre, Risto; Eriksson, Gunnar
2014-01-01
Highlights: • A rapidly cooled system may attain a state of para-equilibrium. • In this state rapidly diffusing elements reach equilibrium but others are immobile. • Application of the Phase Rule to para-equilibrium phase diagrams is discussed. • A general algorithm to calculate para-equilibrium phase diagrams is described. - Abstract: If an initially homogeneous system at high temperature is rapidly cooled, a temporary para-equilibrium state may result in which rapidly diffusing elements have reached equilibrium but more slowly diffusing elements have remained essentially immobile. The best known example occurs when homogeneous austenite is quenched. A para-equilibrium phase assemblage may be calculated thermodynamically by Gibbs free energy minimization under the constraint that the ratios of the slowly diffusing elements are the same in all phases. Several examples of calculated para-equilibrium phase diagram sections are presented and the application of the Phase Rule is discussed. Although the rules governing the geometry of these diagrams may appear at first to be somewhat different from those for full equilibrium phase diagrams, it is shown that in fact they obey exactly the same rules with the following provision. Since the molar ratios of non-diffusing elements are the same in all phases at para-equilibrium, these ratios act, as far as the geometry of the diagram is concerned, like “potential” variables (such as T, pressure or chemical potentials) rather than like “normal” composition variables which need not be the same in all phases. A general algorithm to calculate para-equilibrium phase diagrams is presented. In the limit, if a para-equilibrium calculation is performed under the constraint that no elements diffuse, then the resultant phase diagram shows the single phase with the minimum Gibbs free energy at any point on the diagram; such calculations are of interest in physical vapor deposition when deposition is so rapid that phase
Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning.
Khajehnejad, Moein; Saatlou, Forough Habibollahi; Mohammadzade, Hoda
2017-08-20
Alzheimer's disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer's disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests; therefore, an efficient approach for accurate prediction of the condition of the brain through the classification of magnetic resonance imaging (MRI) images is greatly beneficial and yet very challenging. In this paper, a novel approach is proposed for the diagnosis of very early stages of AD through an efficient classification of brain MRI images, which uses label propagation in a manifold-based semi-supervised learning framework. We first apply voxel morphometry analysis to extract some of the most critical AD-related features of brain images from the original MRI volumes and also gray matter (GM) segmentation volumes. The features must capture the most discriminative properties that vary between a healthy and Alzheimer-affected brain. Next, we perform a principal component analysis (PCA)-based dimension reduction on the extracted features for faster yet sufficiently accurate analysis. To make the best use of the captured features, we present a hybrid manifold learning framework which embeds the feature vectors in a subspace. Next, using a small set of labeled training data, we apply a label propagation method in the created manifold space to predict the labels of the remaining images and classify them in the two groups of mild Alzheimer's and normal condition (MCI/NC). The accuracy of the classification using the proposed method is 93
Directory of Open Access Journals (Sweden)
Yu-Chi Lin
2011-02-01
Full Text Available Due to the implicit characteristics of learning disabilities (LDs, the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN and support vector machine (SVM have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST, which can not only perform as a classifier, but may also produce meaningful explanations or rules, to the LD diagnosis application. Our experiments indicate that the RST approach is competitive as a tool for feature selection, and it performs better in term of prediction accuracy than other rulebased algorithms such as decision tree and ripper algorithms. We also propose to mix samples collected from sources with different LD diagnosis procedure and criteria. By pre-processing these mixed samples with simple and readily available clustering algorithms, we are able to improve the quality and support of rules generated by the RST. Overall, our study shows that the rough set approach, as a classification and knowledge discovery tool, may have great potential in playing an essential role in LD diagnosis.
Yassin, Nisreen I R; Omran, Shaimaa; El Houby, Enas M F; Allam, Hemat
2018-03-01
The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer. The SR was conducted using a comprehensive selection of scientific databases as reference sources, allowing access to diverse publications in the field. The scientific databases used are Springer Link (SL), Science Direct (SD), IEEE Xplore Digital Library, and PubMed. Inclusion and exclusion criteria were defined and applied to each retrieved work to select those of interest. From 320 studies retrieved, 154 studies were included. However, the scope of this research is limited to scientific and academic works and excludes commercial interests. This survey provides a general analysis of the current status of CAD systems according to the used image modalities and the machine learning based classifiers. Potential research studies have been discussed to create a more objective and efficient CAD systems. Copyright © 2017 Elsevier B.V. All rights reserved.
Heuristic Diagrams as a Tool to Teach History of Science
Chamizo, José A.
2012-05-01
The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The left side originally related in Gowin's Vee with philosophies, theories, models, laws or regularities now agrees with Toulmin's concepts (language, models as representation techniques and application procedures). Mexican science teachers without experience in science education research used the heuristic diagram to learn about the history of chemistry considering also in the left side two different historical times: past and present. Through a semantic differential scale teachers' attitude to the heuristic diagram was evaluated and its usefulness was demonstrated.
Causal Diagrams for Empirical Research
Pearl, Judea
1994-01-01
The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are sufficient for identifiying causal effects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal effects in ter...
Wind Diagrams in Medieval Iceland
DEFF Research Database (Denmark)
Kedwards, Dale
2014-01-01
This article presents a study of the sole wind diagram that survives from medieval Iceland, preserved in the encyclopaedic miscellany in Copenhagen's Arnamagnæan Institute with the shelf mark AM 732b 4to (c. 1300-25). It examines the wind diagram and its accompanying text, an excerpt on the winds...... from Isidore of Seville's Etymologies. It also examines the perimeter of winds on two medieval Icelandic world maps, and the visual traditions from which they draw....
Phase diagrams of the elements
International Nuclear Information System (INIS)
Young, D.A.
1975-01-01
A summary of the pressure-temperature phase diagrams of the elements is presented, with graphs of the experimentally determined solid-solid phase boundaries and melting curves. Comments, including theoretical discussion, are provided for each diagram. The crystal structure of each solid phase is identified and discussed. This work is aimed at encouraging further experimental and theoretical research on phase transitions in the elements
Use of machine learning to shorten observation-based screening and diagnosis of autism.
Wall, D P; Kosmicki, J; Deluca, T F; Harstad, E; Fusaro, V A
2012-04-10
The Autism Diagnostic Observation Schedule-Generic (ADOS) is one of the most widely used instruments for behavioral evaluation of autism spectrum disorders. It is composed of four modules, each tailored for a specific group of individuals based on their language and developmental level. On average, a module takes between 30 and 60 min to deliver. We used a series of machine-learning algorithms to study the complete set of scores from Module 1 of the ADOS available at the Autism Genetic Resource Exchange (AGRE) for 612 individuals with a classification of autism and 15 non-spectrum individuals from both AGRE and the Boston Autism Consortium (AC). Our analysis indicated that 8 of the 29 items contained in Module 1 of the ADOS were sufficient to classify autism with 100% accuracy. We further validated the accuracy of this eight-item classifier against complete sets of scores from two independent sources, a collection of 110 individuals with autism from AC and a collection of 336 individuals with autism from the Simons Foundation. In both cases, our classifier performed with nearly 100% sensitivity, correctly classifying all but two of the individuals from these two resources with a diagnosis of autism, and with 94% specificity on a collection of observed and simulated non-spectrum controls. The classifier contained several elements found in the ADOS algorithm, demonstrating high test validity, and also resulted in a quantitative score that measures classification confidence and extremeness of the phenotype. With incidence rates rising, the ability to classify autism effectively and quickly requires careful design of assessment and diagnostic tools. Given the brevity, accuracy and quantitative nature of the classifier, results from this study may prove valuable in the development of mobile tools for preliminary evaluation and clinical prioritization-in particular those focused on assessment of short home videos of children--that speed the pace of initial evaluation
Wong, Kam Cheong
2011-01-01
Abstract Studying medical cases is an effective way to enhance clinical reasoning skills and reinforce clinical knowledge. An Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is often used in quality management in manufacturing industries. In this report, an Ishikawa diagram is used to demonstrate how to relate potential causes of a major presenting problem in a clinical setting. This tool can be used by teams in problem-based learning or in self-directed learni...
New detectors for powders diagrams
International Nuclear Information System (INIS)
Convert, P.
1975-01-01
During the last few years, all the classical neutron diffractometers for powders have used one or maybe a few counters. So, it takes a long time to obtain a diagram which causes many disadvantages: 1) very long experiments: one or two days (or flux on the sample about 10 6 n/cm 2 /a); 2) necessity of big samples: many cm 3 ; 3) necessity of having the whole diagram before changing anything in the experiment: magnetic field, temperature, quality of the sample; 4) necessity of having collimators of a few times ten minutes to obtain correct statistics in the diagram. Because of these disadvantages, several attempts have been made to speed up the experimental procedure such as using more counters, the detection of neutrons on a resistive wire, etc. In Grenoble, new position-sensitive detectors have been constructed using a digital technique
Expert Systems: Implications for the Diagnosis and Treatment of Learning Disabilities.
Hofmeister, Alan M.; Lubke, Margaret M.
1986-01-01
Expert systems are briefly reviewed and applications in special education diagnosis and classification are described. Future applications are noted to include text interpretation and pupil performance monitoring. (CL)
Multi-currency Influence Diagrams
DEFF Research Database (Denmark)
Nielsen, Søren Holbech; Nielsen, Thomas Dyhre; Jensen, Finn V.
2007-01-01
When using the influence diagrams framework for solving a decision problem with several different quantitative utilities, the traditional approach has been to convert the utilities into one common currency. This conversion is carried out using a tacit transformation, under the assumption...... that the converted problem is equivalent to the original one. In this paper we present an extension of the influence diagram framework. The extension allows for these decision problems to be modelled in their original form. We present an algorithm that, given a linear conversion function between the currencies...
Diagrams for symmetric product orbifolds
International Nuclear Information System (INIS)
Pakman, Ari; Rastelli, Leonardo; Razamat, Shlomo S.
2009-01-01
We develop a diagrammatic language for symmetric product orbifolds of two-dimensional conformal field theories. Correlation functions of twist operators are written as sums of diagrams: each diagram corresponds to a branched covering map from a surface where the fields are single-valued to the base sphere where twist operators are inserted. This diagrammatic language facilitates the study of the large N limit and makes more transparent the analogy between symmetric product orbifolds and free non-abelian gauge theories. We give a general algorithm to calculate the leading large N contribution to four-point correlators of twist fields.
International Nuclear Information System (INIS)
Smondyrev, M.A.
1985-01-01
The perturbation theory for the polaron energy is systematically treated on the diagrammatic basis. Feynman diagrams being constructed allow to calculate the polaron energy up to the third order in powers of the coupling constant. Similar calculations are performed for the average number of virtual phonons
Algorithmic approach to diagram techniques
International Nuclear Information System (INIS)
Ponticopoulos, L.
1980-10-01
An algorithmic approach to diagram techniques of elementary particles is proposed. The definition and axiomatics of the theory of algorithms are presented, followed by the list of instructions of an algorithm formalizing the construction of graphs and the assignment of mathematical objects to them. (T.A.)
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...
Science and Engineering Students' Use of Diagrams during Note Taking versus Explanation
Manalo, Emmanuel; Uesaka, Yuri; Perez-Kriz, Sarah; Kato, Masashi; Fukaya, Tatsushi
2013-01-01
The use of diagrams in learning and communication is generally considered efficacious and an important skill to cultivate, especially among science students. At the same time, previous research has revealed many problems in student diagram use, including a lack of spontaneity in such use, but the extent to which these problems persist into the…
Nakanishi, Hiroyoshi; Doyama, Hisashi; Ishikawa, Hideki; Uedo, Noriya; Gotoda, Takuji; Kato, Mototsugu; Nagao, Shigeaki; Nagami, Yasuaki; Aoyagi, Hiroyuki; Imagawa, Atsushi; Kodaira, Junichi; Mitsui, Shinya; Kobayashi, Nozomu; Muto, Manabu; Takatori, Hajime; Abe, Takashi; Tsujii, Masahiko; Watari, Jiro; Ishiyama, Shuhei; Oda, Ichiro; Ono, Hiroyuki; Kaneko, Kazuhiro; Yokoi, Chizu; Ueo, Tetsuya; Uchita, Kunihisa; Matsumoto, Kenshi; Kanesaka, Takashi; Morita, Yoshinori; Katsuki, Shinichi; Nishikawa, Jun; Inamura, Katsuhisa; Kinjo, Tetsu; Yamamoto, Katsumi; Yoshimura, Daisuke; Araki, Hiroshi; Kashida, Hiroshi; Hosokawa, Ayumu; Mori, Hirohito; Yamashita, Haruhiro; Motohashi, Osamu; Kobayashi, Kazuhiko; Hirayama, Michiaki; Kobayashi, Hiroyuki; Endo, Masaki; Yamano, Hiroo; Murakami, Kazunari; Koike, Tomoyuki; Hirasawa, Kingo; Miyaoka, Youichi; Hamamoto, Hidetaka; Hikichi, Takuto; Hanabata, Norihiro; Shimoda, Ryo; Hori, Shinichiro; Sato, Tadashi; Kodashima, Shinya; Okada, Hiroyuki; Mannami, Tomohiko; Yamamoto, Shojiro; Niwa, Yasumasa; Yashima, Kazuo; Tanabe, Satoshi; Satoh, Hiro; Sasaki, Fumisato; Yamazato, Tetsuro; Ikeda, Yoshiou; Nishisaki, Hogara; Nakagawa, Masahiro; Matsuda, Akio; Tamura, Fumio; Nishiyama, Hitoshi; Arita, Keiko; Kawasaki, Keisuke; Hoppo, Kazushige; Oka, Masashi; Ishihara, Shinichi; Mukasa, Michita; Minamino, Hiroaki; Yao, Kenshi
2017-10-01
Background and study aim Magnifying narrow-band imaging (M-NBI) is useful for the accurate diagnosis of early gastric cancer (EGC). However, acquiring skill at M-NBI diagnosis takes substantial effort. An Internet-based e-learning system to teach endoscopic diagnosis of EGC using M-NBI has been developed. This study evaluated its effectiveness. Participants and methods This study was designed as a multicenter randomized controlled trial. We recruited endoscopists as participants from all over Japan. After completing Test 1, which consisted of M-NBI images of 40 gastric lesions, participants were randomly assigned to the e-learning or non-e-learning groups. Only the e-learning group was allowed to access the e-learning system. After the e-learning period, both groups received Test 2. The analysis set was participants who scored e-learning group and 197 in the non-e-learning group). After the e-learning period, all 395 completed Test 2. The analysis sets were e-learning group: n = 184; and non-e-learning group: n = 184. The mean Test 1 score was 59.9 % for the e-learning group and 61.7 % for the non-e-learning group. The change in accuracy in Test 2 was significantly higher in the e-learning group than in the non-e-learning group (7.4 points vs. 0.14 points, respectively; P e-learning system in improving practitioners' capabilities to diagnose EGC using M-NBI.Trial registered at University Hospital Medical Information Network Clinical Trials Registry (UMIN000008569). © Georg Thieme Verlag KG Stuttgart · New York.
Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T. C.
2017-10-01
Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.
The Butterfly Diagram Internal Structure
International Nuclear Information System (INIS)
Ternullo, Maurizio
2013-01-01
A time-latitude diagram, where the spotgroup area is taken into account, is presented for cycles 12 through 23. The results show that the spotted area is concentrated in few, small portions ( k nots ) of the Butterfly Diagram (BD). The BD may be described as a cluster of knots. Knots are distributed in the butterfly wings in a seemingly randomly way. A knot may appear at either lower or higher latitudes than previous ones, in spite of the prevalent tendency to appear at lower and lower latitudes. Accordingly, the spotted area centroid, far from continuously drifting equatorward, drifts poleward or remains stationary in any hemisphere for significant fractions (≈ 1/3) of the cycle total duration. In a relevant number of semicycles, knots seem to form two roughly parallel, oblique c hains , separated by an underspotted band. This picture suggests that two (or more) ''activity streams'' approach the equator at a rate higher than the spot zone as a whole.
Directory of Open Access Journals (Sweden)
Susanna Bisogni
2018-01-01
Full Text Available The cosmological model is at present not tested between the redshift of the farthest observed supernovae (z ~ 1.4 and that of the Cosmic Microwave Background (z ~ 1,100. Here we introduce a new method to measure the cosmological parameters: we show that quasars can be used as “standard candles” by employing the non-linear relation between their intrinsic UV and X-ray emission as an absolute distance indicator. We built a sample of ~1,900 quasars with available UV and X-ray observations, and produced a Hubble Diagram up to z ~ 5. The analysis of the quasar Hubble Diagram, when used in combination with supernovae, provides robust constraints on the matter and energy content in the cosmos. The application of this method to forthcoming, larger quasar samples, will also provide tight constraints on the dark energy equation of state and its possible evolution with time.
Causal diagrams in systems epidemiology
Directory of Open Access Journals (Sweden)
Joffe Michael
2012-03-01
Full Text Available Abstract Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s. Transmitted causes ("causes of causes" tend not to be systematically analysed. The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties. The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets. Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.
Causal diagrams in systems epidemiology.
Joffe, Michael; Gambhir, Manoj; Chadeau-Hyam, Marc; Vineis, Paolo
2012-03-19
Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed.The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties.The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets.Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.
Scheil-Gulliver Constituent Diagrams
Pelton, Arthur D.; Eriksson, Gunnar; Bale, Christopher W.
2017-06-01
During solidification of alloys, conditions often approach those of Scheil-Gulliver cooling in which it is assumed that solid phases, once precipitated, remain unchanged. That is, they no longer react with the liquid or with each other. In the case of equilibrium solidification, equilibrium phase diagrams provide a valuable means of visualizing the effects of composition changes upon the final microstructure. In the present study, we propose for the first time the concept of Scheil-Gulliver constituent diagrams which play the same role as that in the case of Scheil-Gulliver cooling. It is shown how these diagrams can be calculated and plotted by the currently available thermodynamic database computing systems that combine Gibbs energy minimization software with large databases of optimized thermodynamic properties of solutions and compounds. Examples calculated using the FactSage system are presented for the Al-Li and Al-Mg-Zn systems, and for the Au-Bi-Sb-Pb system and its binary and ternary subsystems.
Using Affinity Diagrams to Evaluate Interactive Prototypes
DEFF Research Database (Denmark)
Lucero, Andrés
2015-01-01
our particular use of affinity diagramming in prototype evaluations. We reflect on a decade’s experience using affinity diagramming across a number of projects, both in industry and academia. Our affinity diagramming process in interaction design has been tailored and consists of four stages: creating...
Directory of Open Access Journals (Sweden)
Qing Ye
2015-01-01
Full Text Available This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach.
International Nuclear Information System (INIS)
Minowa, Hirotsugu; Gofuku, Akio
2014-01-01
Accidents of industrial plants cause large loss on human, economic, social credibility. In recent, studies of diagnostic methods using techniques of machine learning are expected to detect early and correctly abnormality occurred in a plant. However, the general diagnostic machines are generated generally to require all process signals (hereafter, signals) for plant diagnosis. Thus if trouble occurs such as process sensor is broken, the diagnostic machine cannot diagnose or may decrease diagnostic performance. Therefore, we propose an important process signal selection method to improve impact mitigation without reducing the diagnostic performance by reducing the adverse effect of noises on multi-agent diagnostic system. The advantage of our method is the general-purpose property that allows to be applied to various supervised machine learning and to set the various parameters to decide termination of search. The experiment evaluation revealed that diagnostic machines generated by our method using SVM improved the impact mitigation and did not reduce performance about the diagnostic accuracy, the velocity of diagnosis, predictions of plant state near accident occurrence, in comparison with the basic diagnostic machine which diagnoses by using all signals. This paper reports our proposed method and the results evaluated which our method was applied to the simulated abnormal of the fast-breeder reactor Monju. (author)
Directory of Open Access Journals (Sweden)
Ramesh Kumar Lama
2017-01-01
Full Text Available Alzheimer’s disease (AD is a progressive, neurodegenerative brain disorder that attacks neurotransmitters, brain cells, and nerves, affecting brain functions, memory, and behaviors and then finally causing dementia on elderly people. Despite its significance, there is currently no cure for it. However, there are medicines available on prescription that can help delay the progress of the condition. Thus, early diagnosis of AD is essential for patient care and relevant researches. Major challenges in proper diagnosis of AD using existing classification schemes are the availability of a smaller number of training samples and the larger number of possible feature representations. In this paper, we present and compare AD diagnosis approaches using structural magnetic resonance (sMR images to discriminate AD, mild cognitive impairment (MCI, and healthy control (HC subjects using a support vector machine (SVM, an import vector machine (IVM, and a regularized extreme learning machine (RELM. The greedy score-based feature selection technique is employed to select important feature vectors. In addition, a kernel-based discriminative approach is adopted to deal with complex data distributions. We compare the performance of these classifiers for volumetric sMR image data from Alzheimer’s disease neuroimaging initiative (ADNI datasets. Experiments on the ADNI datasets showed that RELM with the feature selection approach can significantly improve classification accuracy of AD from MCI and HC subjects.
Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.
Liang, Zhaohui; Liu, Jun; Ou, Aihua; Zhang, Honglai; Li, Ziping; Huang, Jimmy Xiangji
2018-05-04
Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospital information systems and disease surveillance systems, provides abundant data for CAMDM. However, the complexity of EMR data with abstract medical knowledge makes the conventional model incompetent for the analysis. Thus a deep belief networks (DBN) based model is proposed to simulate the information analysis and decision-making procedure in medical practice. The purpose of this paper is to evaluate a deep learning architecture as an effective solution for CAMDM. A two-step model is applied in our study. At the first step, an optimized seven-layer deep belief network (DBN) is applied as an unsupervised learning algorithm to perform model training to acquire feature representation. Then a support vector machine model is adopted to DBN at the second step of the supervised learning. There are two data sets used in the experiments. One is a plain text data set indexed by medical experts. The other is a structured dataset on primary hypertension. The data are randomly divided to generate the training set for the unsupervised learning and the testing set for the supervised learning. The model performance is evaluated by the statistics of mean and variance, the average precision and coverage on the data sets. Two conventional shallow models (support vector machine / SVM and decision tree / DT) are applied as the comparisons to show the superiority of our proposed approach. The deep learning (DBN + SVM) model outperforms simple SVM and DT on two data sets in terms of all the evaluation measures, which confirms our motivation that the deep model is good at capturing the key features with less dependence when the index is built up by manpower. Our study shows the two-step deep learning model achieves high performance for medical
A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis
Directory of Open Access Journals (Sweden)
Muhammad Sohaib
2017-12-01
Full Text Available Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE-based deep neural networks (DNNs to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs and backpropagation neural networks (BPNNs.
A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis.
Sohaib, Muhammad; Kim, Cheol-Hong; Kim, Jong-Myon
2017-12-11
Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE)-based deep neural networks (DNNs) to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs) and backpropagation neural networks (BPNNs).
Machine learning techniques for medical diagnosis of diabetes using iris images.
Samant, Piyush; Agarwal, Ravinder
2018-04-01
Complementary and alternative medicine techniques have shown their potential for the treatment and diagnosis of chronical diseases like diabetes, arthritis etc. On the same time digital image processing techniques for disease diagnosis is reliable and fastest growing field in biomedical. Proposed model is an attempt to evaluate diagnostic validity of an old complementary and alternative medicine technique, iridology for diagnosis of type-2 diabetes using soft computing methods. Investigation was performed over a close group of total 338 subjects (180 diabetic and 158 non-diabetic). Infra-red images of both the eyes were captured simultaneously. The region of interest from the iris image was cropped as zone corresponds to the position of pancreas organ according to the iridology chart. Statistical, texture and discrete wavelength transformation features were extracted from the region of interest. The results show best classification accuracy of 89.63% calculated from RF classifier. Maximum specificity and sensitivity were absorbed as 0.9687 and 0.988, respectively. Results have revealed the effectiveness and diagnostic significance of proposed model for non-invasive and automatic diabetes diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.
A web-based e-learning application for wound diagnosis and treatment.
Veredas, Francisco J; Ruiz-Bandera, Esperanza; Villa-Estrada, Francisca; Rufino-González, Juan F; Morente, Laura
2014-10-01
Pressure ulcers (PrU) are considered as one of the most challenging problems that Nursing professionals have to deal with in their daily practice. Nowadays, the education on PrUs is mainly based on traditional lecturing, seminars and face-to-face instruction, sometimes with the support of photographs of wounds being used as teaching material. This traditional educational methodology suffers from some important limitations, which could affect the efficacy of the learning process. This current study has been designed to introduce information and communication technologies (ICT) in the education on PrU for undergraduate students, with the main objective of evaluating the advantages an disadvantages of using ICT, by comparing the learning results obtained from using an e-learning tool with those from a traditional teaching methodology. In order to meet this major objective, a web-based learning system named ePULab has been designed and developed as an adaptive e-learning tool for the autonomous acquisition of knowledge on PrU evaluation. This innovative system has been validated by means of a randomized controlled trial that compares its learning efficacy with that from a control group receiving a traditional face-to-face instruction. Students using ePULab gave significantly better (p<0.01) learning acquisition scores (from pre-test mean 8.27 (SD 1.39) to post-test mean 15.83 (SD 2.52)) than those following traditional lecture-style classes (from pre-test mean 8.23 (SD 1.23) to post-test mean 11.6 (SD 2.52)). In this article, the ePULab software is described in detail and the results from that experimental educational validation study are also presented and analyzed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna
2015-01-27
To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.
Diagram Size vs. Layout Flaws: Understanding Quality Factors of UML Diagrams
DEFF Research Database (Denmark)
Störrle, Harald
2016-01-01
, though, is our third goal of extending our analysis aspects of diagram quality. Method: We improve our definition of diagram size and add a (provisional) definition of diagram quality as the number of topographic layout flaws. We apply these metrics on 60 diagrams of the five most commonly used types...... of UML diagram. We carefully analyze the structure of our diagram samples to ensure representativeness. We correlate diagram size and layout quality with modeler performance data obtained in previous experiments. The data set is the largest of its kind (n-156). Results: We replicate earlier findings......, and extend them to two new diagram types. We provide an improved definition of diagram size, and provide a definition of topographic layout quality, which is one more step towards a comprehensive definition of diagram quality as such. Both metrics are shown to be objectively applicable. We quantify...
Wajnsztejn, Alessandra Bernardes Caturani; Bianco, Bianca; Barbosa, Caio Parente
2016-01-01
To describe clinical and epidemiological features of children and adolescents with interdisciplinary diagnosis of non-verbal learning disorder and to investigate the prevalence of inter-hemispheric asymmetry in this population group. Cross-sectional study including children and adolescents referred for interdisciplinary assessment with learning difficulty complaints, who were given an interdisciplinary diagnosis of non-verbal learning disorder. The following variables were included in the analysis: sex-related prevalence, educational system, initial presumptive diagnoses and respective prevalence, overall non-verbal learning disorder prevalence, prevalence according to school year, age range at the time of assessment, major family complaints, presence of inter-hemispheric asymmetry, arithmetic deficits, visuoconstruction impairments and major signs and symptoms of non-verbal learning disorder. Out of 810 medical records analyzed, 14 were from individuals who met the diagnostic criteria for non-verbal learning disorder, including the presence of inter-hemispheric asymmetry. Of these 14 patients, 8 were male. The high prevalence of inter-hemispheric asymmetry suggests this parameter can be used to predict or support the diagnosis of non-verbal learning disorder. Descrever as características clínicas e epidemiológicas de crianças e adolescentes com transtorno de aprendizagem não verbal, e investigar a prevalência de assimetria inter-hemisférica neste grupo populacional. Estudo transversal que incluiu crianças e adolescentes encaminhados para uma avaliação interdisciplinar, com queixas de dificuldades de aprendizagem e que receberam diagnóstico interdisciplinar de transtorno de aprendizagem não verbal. As variáveis avaliadas foram prevalência por sexo, sistema de ensino, hipóteses diagnósticas iniciais e respectivas prevalências, prevalência de condições em relação à amostra total, prevalência geral do transtorno de aprendizagem não verbal
Voronoi Diagrams Without Bounding Boxes
Sang, E. T. K.
2015-10-01
We present a technique for presenting geographic data in Voronoi diagrams without having to specify a bounding box. The method restricts Voronoi cells to points within a user-defined distance of the data points. The mathematical foundation of the approach is presented as well. The cell clipping method is particularly useful for presenting geographic data that is spread in an irregular way over a map, as for example the Dutch dialect data displayed in Figure 2. The automatic generation of reasonable cell boundaries also makes redundant a frequently used solution to this problem that requires data owners to specify region boundaries, as in Goebl (2010) and Nerbonne et al (2011).
Multi-currency Influence Diagrams
DEFF Research Database (Denmark)
Nielsen, Søren Holbech; Nielsen, Thomas Dyhre; Jensen, Finn Verner
2004-01-01
Solution of decision problems, which involve utilities of several currencies, have traditionally required the problems to be converted into decision problems involving utilities of only one currency. This conversion are carried out using a tacit transformation, under the assumption...... that the converted problem is equivalent to the original one. In this paper we present an extension of the Influence Diagram framework, which allows for these decision problems to be modelled in their original form. We present an algorithm that, given a conversion function between the currencies, discovers...
Phase diagrams for surface alloys
DEFF Research Database (Denmark)
Christensen, Asbjørn; Ruban, Andrei; Stoltze, Per
1997-01-01
We discuss surface alloy phases and their stability based on surface phase diagrams constructed from the surface energy as a function of the surface composition. We show that in the simplest cases of pseudomorphic overlayers there are four generic classes of systems, characterized by the sign...... is based on density-functional calculations using the coherent-potential approximation and on effective-medium theory. We give self-consistent density-functional results for the segregation energy and surface mixing energy for all combinations of the transition and noble metals. Finally we discuss...
FindZebra - using machine learning to aid diagnosis of rare diseases
DEFF Research Database (Denmark)
Svenstrup, Dan Tito
FindZebra is a search engine for rare diseases intended to act as a diagnosis decision support system (DDSS) capable of assisting the user both during and after a search. Rare diseases are diseases that aﬀect only a small part of the population (less than one in two thousand). Currently around...... retrieval systems. Improving retrieval performance is important, but is not the only way of improving the success rate of a DDSS such as FindZebra. Following an unsuccessful search, the search engine should assist the user by indicating what information is likely to be missing. This idea is called...... language and the search engine should then give a suggestion for a diﬀerential diagnosis based on all the information contained in a multilingual corpus, not only in the native corpus. Methods for performing multilingual search will be the fourth line of research explored in this dissertation. ...
Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin
2017-01-01
To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process.
Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin
2017-01-01
PURPOSE To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. METHODS An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. RESULTS The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. CONCLUSIONS This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process. PMID:28436410
Diagrams benefit symbolic problem-solving.
Chu, Junyi; Rittle-Johnson, Bethany; Fyfe, Emily R
2017-06-01
The format of a mathematics problem often influences students' problem-solving performance. For example, providing diagrams in conjunction with story problems can benefit students' understanding, choice of strategy, and accuracy on story problems. However, it remains unclear whether providing diagrams in conjunction with symbolic equations can benefit problem-solving performance as well. We tested the impact of diagram presence on students' performance on algebra equation problems to determine whether diagrams increase problem-solving success. We also examined the influence of item- and student-level factors to test the robustness of the diagram effect. We worked with 61 seventh-grade students who had received 2 months of pre-algebra instruction. Students participated in an experimenter-led classroom session. Using a within-subjects design, students solved algebra problems in two matched formats (equation and equation-with-diagram). The presence of diagrams increased equation-solving accuracy and the use of informal strategies. This diagram benefit was independent of student ability and item complexity. The benefits of diagrams found previously for story problems generalized to symbolic problems. The findings are consistent with cognitive models of problem-solving and suggest that diagrams may be a useful additional representation of symbolic problems. © 2017 The British Psychological Society.
Directory of Open Access Journals (Sweden)
Mohammad R. Mohebian
Full Text Available Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread to the body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breast cancer recurrence prediction is presented in this manuscript. Clinicopathologic characteristics of 579 breast cancer patients (recurrence prevalence of 19.3% were analyzed and discriminative features were selected using statistical feature selection methods. They were further refined by Particle Swarm Optimization (PSO as the inputs of the classification system with ensemble learning (Bagged Decision Tree: BDT. The proper combination of selected categorical features and also the weight (importance of the selected interval-measurement-scale features were identified by the PSO algorithm. The performance of HPBCR (hybrid predictor of breast cancer recurrence was assessed using the holdout and 4-fold cross-validation. Three other classifiers namely as supported vector machines, DT, and multilayer perceptron neural network were used for comparison. The selected features were diagnosis age, tumor size, lymph node involvement ratio, number of involved axillary lymph nodes, progesterone receptor expression, having hormone therapy and type of surgery. The minimum sensitivity, specificity, precision and accuracy of HPBCR were 77%, 93%, 95% and 85%, respectively in the entire cross-validation folds and the hold-out test fold. HPBCR outperformed the other tested classifiers. It showed excellent agreement with the gold standard (i.e. the oncologist opinion after blood tumor marker and imaging tests, and tissue biopsy. This algorithm is thus a promising online tool for the prediction of breast cancer recurrence. Keywords: Breast cancer, Cancer recurrence, Computer-assisted diagnosis, Machine learning, Prognosis
Ultrasound imaging in medical student education: Impact on learning anatomy and physical diagnosis.
So, Sokpoleak; Patel, Rita M; Orebaugh, Steven L
2017-03-01
Ultrasound use has expanded dramatically among the medical specialties for diagnostic and interventional purposes, due to its affordability, portability, and practicality. This imaging modality, which permits real-time visualization of anatomic structures and relationships in vivo, holds potential for pre-clinical instruction of students in anatomy and physical diagnosis, as well as providing a bridge to the eventual use of bedside ultrasound by clinicians to assess patients and guide invasive procedures. In many studies, but not all, improved understanding of anatomy has been demonstrated, and in others, improved accuracy in selected aspects of physical diagnosis is evident. Most students have expressed a highly favorable impression of this technology for anatomy education when surveyed. Logistic issues or obstacles to the integration of ultrasound imaging into anatomy teaching appear to be readily overcome. The enthusiasm of students and anatomists for teaching with ultrasound has led to widespread implementation of ultrasound-based teaching initiatives in medical schools the world over, including some with integration throughout the entire curriculum; a trend that likely will continue to grow. Anat Sci Educ 10: 176-189. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.
Disconnected Diagrams in Lattice QCD
Gambhir, Arjun Singh
In this work, we present state-of-the-art numerical methods and their applications for computing a particular class of observables using lattice quantum chromodynamics (Lattice QCD), a discretized version of the fundamental theory of quarks and gluons. These observables require calculating so called "disconnected diagrams" and are important for understanding many aspects of hadron structure, such as the strange content of the proton. We begin by introducing the reader to the key concepts of Lattice QCD and rigorously define the meaning of disconnected diagrams through an example of the Wick contractions of the nucleon. Subsequently, the calculation of observables requiring disconnected diagrams is posed as the computationally challenging problem of finding the trace of the inverse of an incredibly large, sparse matrix. This is followed by a brief primer of numerical sparse matrix techniques that overviews broadly used methods in Lattice QCD and builds the background for the novel algorithm presented in this work. We then introduce singular value deflation as a method to improve convergence of trace estimation and analyze its effects on matrices from a variety of fields, including chemical transport modeling, magnetohydrodynamics, and QCD. Finally, we apply this method to compute observables such as the strange axial charge of the proton and strange sigma terms in light nuclei. The work in this thesis is innovative for four reasons. First, we analyze the effects of deflation with a model that makes qualitative predictions about its effectiveness, taking only the singular value spectrum as input, and compare deflated variance with different types of trace estimator noise. Second, the synergy between probing methods and deflation is investigated both experimentally and theoretically. Third, we use the synergistic combination of deflation and a graph coloring algorithm known as hierarchical probing to conduct a lattice calculation of light disconnected matrix elements
Disconnected Diagrams in Lattice QCD
Energy Technology Data Exchange (ETDEWEB)
Gambhir, Arjun [College of William and Mary, Williamsburg, VA (United States)
2017-08-01
In this work, we present state-of-the-art numerical methods and their applications for computing a particular class of observables using lattice quantum chromodynamics (Lattice QCD), a discretized version of the fundamental theory of quarks and gluons. These observables require calculating so called \\disconnected diagrams" and are important for understanding many aspects of hadron structure, such as the strange content of the proton. We begin by introducing the reader to the key concepts of Lattice QCD and rigorously define the meaning of disconnected diagrams through an example of the Wick contractions of the nucleon. Subsequently, the calculation of observables requiring disconnected diagrams is posed as the computationally challenging problem of finding the trace of the inverse of an incredibly large, sparse matrix. This is followed by a brief primer of numerical sparse matrix techniques that overviews broadly used methods in Lattice QCD and builds the background for the novel algorithm presented in this work. We then introduce singular value deflation as a method to improve convergence of trace estimation and analyze its effects on matrices from a variety of fields, including chemical transport modeling, magnetohydrodynamics, and QCD. Finally, we apply this method to compute observables such as the strange axial charge of the proton and strange sigma terms in light nuclei. The work in this thesis is innovative for four reasons. First, we analyze the effects of deflation with a model that makes qualitative predictions about its effectiveness, taking only the singular value spectrum as input, and compare deflated variance with different types of trace estimator noise. Second, the synergy between probing methods and deflation is investigated both experimentally and theoretically. Third, we use the synergistic combination of deflation and a graph coloring algorithm known as hierarchical probing to conduct a lattice calculation of light disconnected matrix elements
Lee, Jae-Hong; Kim, Do-Hyung; Jeong, Seong-Nyum; Choi, Seong-Ho
2018-04-01
The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.
Lu, Wei; Li, Zhe; Chu, Jinghui
2017-04-01
Breast cancer is a common cancer among women. With the development of modern medical science and information technology, medical imaging techniques have an increasingly important role in the early detection and diagnosis of breast cancer. In this paper, we propose an automated computer-aided diagnosis (CADx) framework for magnetic resonance imaging (MRI). The scheme consists of an ensemble of several machine learning-based techniques, including ensemble under-sampling (EUS) for imbalanced data processing, the Relief algorithm for feature selection, the subspace method for providing data diversity, and Adaboost for improving the performance of base classifiers. We extracted morphological, various texture, and Gabor features. To clarify the feature subsets' physical meaning, subspaces are built by combining morphological features with each kind of texture or Gabor feature. We tested our proposal using a manually segmented Region of Interest (ROI) data set, which contains 438 images of malignant tumors and 1898 images of normal tissues or benign tumors. Our proposal achieves an area under the ROC curve (AUC) value of 0.9617, which outperforms most other state-of-the-art breast MRI CADx systems. Compared with other methods, our proposal significantly reduces the false-positive classification rate. Copyright © 2017 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Herrmann, Enrico [Walter Burke Institute for Theoretical Physics, California Institute of Technology,Pasadena, CA 91125 (United States); Trnka, Jaroslav [Center for Quantum Mathematics and Physics (QMAP),Department of Physics, University of California,Davis, CA 95616 (United States)
2016-11-22
We study on-shell diagrams for gravity theories with any number of supersymmetries and find a compact Grassmannian formula in terms of edge variables of the graphs. Unlike in gauge theory where the analogous form involves only dlog-factors, in gravity there is a non-trivial numerator as well as higher degree poles in the edge variables. Based on the structure of the Grassmannian formula for N=8 supergravity we conjecture that gravity loop amplitudes also possess similar properties. In particular, we find that there are only logarithmic singularities on cuts with finite loop momentum and that poles at infinity are present, in complete agreement with the conjecture presented in http://dx.doi.org/10.1007/JHEP06(2015)202.
Phase diagram of ammonium nitrate
International Nuclear Information System (INIS)
Dunuwille, Mihindra; Yoo, Choong-Shik
2013-01-01
Ammonium Nitrate (AN) is a fertilizer, yet becomes an explosive upon a small addition of chemical impurities. The origin of enhanced chemical sensitivity in impure AN (or AN mixtures) is not well understood, posing significant safety issues in using AN even today. To remedy the situation, we have carried out an extensive study to investigate the phase stability of AN and its mixtures with hexane (ANFO–AN mixed with fuel oil) and Aluminum (Ammonal) at high pressures and temperatures, using diamond anvil cells (DAC) and micro-Raman spectroscopy. The results indicate that pure AN decomposes to N 2 , N 2 O, and H 2 O at the onset of the melt, whereas the mixtures, ANFO and Ammonal, decompose at substantially lower temperatures. The present results also confirm the recently proposed phase IV-IV ′ transition above 17 GPa and provide new constraints for the melting and phase diagram of AN to 40 GPa and 400°C
VORONOI DIAGRAMS WITHOUT BOUNDING BOXES
Directory of Open Access Journals (Sweden)
E. T. K. Sang
2015-10-01
Full Text Available We present a technique for presenting geographic data in Voronoi diagrams without having to specify a bounding box. The method restricts Voronoi cells to points within a user-defined distance of the data points. The mathematical foundation of the approach is presented as well. The cell clipping method is particularly useful for presenting geographic data that is spread in an irregular way over a map, as for example the Dutch dialect data displayed in Figure 2. The automatic generation of reasonable cell boundaries also makes redundant a frequently used solution to this problem that requires data owners to specify region boundaries, as in Goebl (2010 and Nerbonne et al (2011.
Anatomy of geodesic Witten diagrams
Energy Technology Data Exchange (ETDEWEB)
Chen, Heng-Yu; Kuo, En-Jui [Department of Physics and Center for Theoretical Sciences, National Taiwan University,Taipei 10617, Taiwan (China); Kyono, Hideki [Department of Physics, Kyoto University,Kitashirakawa Oiwake-cho, Kyoto 606-8502 (Japan)
2017-05-12
We revisit the so-called “Geodesic Witten Diagrams” (GWDs) https://www.doi.org/10.1007/JHEP01(2016)146, proposed to be the holographic dual configuration of scalar conformal partial waves, from the perspectives of CFT operator product expansions. To this end, we explicitly consider three point GWDs which are natural building blocks of all possible four point GWDs, discuss their gluing procedure through integration over spectral parameter, and this leads us to a direct identification with the integral representation of CFT conformal partial waves. As a main application of this general construction, we consider the holographic dual of the conformal partial waves for external primary operators with spins. Moreover, we consider the closely related “split representation” for the bulk to bulk spinning propagator, to demonstrate how ordinary scalar Witten diagram with arbitrary spin exchange, can be systematically decomposed into scalar GWDs. We also discuss how to generalize to spinning cases.
Amaral, Jorge L M; Lopes, Agnaldo J; Jansen, José M; Faria, Alvaro C D; Melo, Pedro L
2013-12-01
The purpose of this study was to develop an automatic classifier to increase the accuracy of the forced oscillation technique (FOT) for diagnosing early respiratory abnormalities in smoking patients. The data consisted of FOT parameters obtained from 56 volunteers, 28 healthy and 28 smokers with low tobacco consumption. Many supervised learning techniques were investigated, including logistic linear classifiers, k nearest neighbor (KNN), neural networks and support vector machines (SVM). To evaluate performance, the ROC curve of the most accurate parameter was established as baseline. To determine the best input features and classifier parameters, we used genetic algorithms and a 10-fold cross-validation using the average area under the ROC curve (AUC). In the first experiment, the original FOT parameters were used as input. We observed a significant improvement in accuracy (KNN=0.89 and SVM=0.87) compared with the baseline (0.77). The second experiment performed a feature selection on the original FOT parameters. This selection did not cause any significant improvement in accuracy, but it was useful in identifying more adequate FOT parameters. In the third experiment, we performed a feature selection on the cross products of the FOT parameters. This selection resulted in a further increase in AUC (KNN=SVM=0.91), which allows for high diagnostic accuracy. In conclusion, machine learning classifiers can help identify early smoking-induced respiratory alterations. The use of FOT cross products and the search for the best features and classifier parameters can markedly improve the performance of machine learning classifiers. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Machine learning approaches to diagnosis and laterality effects in semantic dementia discourse.
Garrard, Peter; Rentoumi, Vassiliki; Gesierich, Benno; Miller, Bruce; Gorno-Tempini, Maria Luisa
2014-06-01
Advances in automatic text classification have been necessitated by the rapid increase in the availability of digital documents. Machine learning (ML) algorithms can 'learn' from data: for instance a ML system can be trained on a set of features derived from written texts belonging to known categories, and learn to distinguish between them. Such a trained system can then be used to classify unseen texts. In this paper, we explore the potential of the technique to classify transcribed speech samples along clinical dimensions, using vocabulary data alone. We report the accuracy with which two related ML algorithms [naive Bayes Gaussian (NBG) and naive Bayes multinomial (NBM)] categorized picture descriptions produced by: 32 semantic dementia (SD) patients versus 10 healthy, age-matched controls; and SD patients with left- (n = 21) versus right-predominant (n = 11) patterns of temporal lobe atrophy. We used information gain (IG) to identify the vocabulary features that were most informative to each of these two distinctions. In the SD versus control classification task, both algorithms achieved accuracies of greater than 90%. In the right- versus left-temporal lobe predominant classification, NBM achieved a high level of accuracy (88%), but this was achieved by both NBM and NBG when the features used in the training set were restricted to those with high values of IG. The most informative features for the patient versus control task were low frequency content words, generic terms and components of metanarrative statements. For the right versus left task the number of informative lexical features was too small to support any specific inferences. An enriched feature set, including values derived from Quantitative Production Analysis (QPA) may shed further light on this little understood distinction. Copyright © 2013 Elsevier Ltd. All rights reserved.
Stehle, A; Gross, M
1998-12-01
With the increasing capacity of personal computers more and more multimedia training programs are becoming available which make use of these possibilities. Computer-based presentation is usually interesting because it is visually attractive. However, the extent to which computer-based training programs correspond to international standards of quality of software ergonomics has never been the subject of systematic research. Another question is how much these programs motivate learning and what increase in knowledge can be achieved by using them. Using a multimedia interactive training program developed in our facility, 100 medical students were asked to evaluate the program after they had been using it for about one hour. In a questionnaire they first rated suitability for the task, self-descriptiveness, controllability, conformity with user expectation, error tolerance, suitability for individualization, and suitability for learning on a bipolar scale from "---" to "+3" (in numbers 1, worst result, to 7, best result). The median values achieved were rated between 6.0 and 6.2--software ergonomic criteria of the program ranged from good to very good. The second part was a subjective evaluation of the program's ability to deliver "medical knowledge which is relevant for the exam" (median = 6.0), "knowledge about systematic procedure in medicine" (median = 5.5), "knowledge about sensible use of diagnostic methods" (median = 6.0), "knowledge about clinical methods", and "experience with selective learning" (median = 6.0). This part was also rated good to very good. The third part of the questionnaire involved a pretest-posttest comparison. Two groups of students were asked how much benefit they had achieved by using the program. It was shown that the students were able to answer the exam questions significantly better than the control questions after they had used the program. This study confirms that the interactive computer-based training program is very well suited
Use of machine learning to shorten observation-based screening and diagnosis of autism
Wall, D P; Kosmicki, J; DeLuca, T F; Harstad, E; Fusaro, V A
2012-01-01
The Autism Diagnostic Observation Schedule-Generic (ADOS) is one of the most widely used instruments for behavioral evaluation of autism spectrum disorders. It is composed of four modules, each tailored for a specific group of individuals based on their language and developmental level. On average, a module takes between 30 and 60 min to deliver. We used a series of machine-learning algorithms to study the complete set of scores from Module 1 of the ADOS available at the Autism Genetic Resour...
Stereo 3D spatial phase diagrams
Energy Technology Data Exchange (ETDEWEB)
Kang, Jinwu, E-mail: kangjw@tsinghua.edu.cn; Liu, Baicheng, E-mail: liubc@tsinghua.edu.cn
2016-07-15
Phase diagrams serve as the fundamental guidance in materials science and engineering. Binary P-T-X (pressure–temperature–composition) and multi-component phase diagrams are of complex spatial geometry, which brings difficulty for understanding. The authors constructed 3D stereo binary P-T-X, typical ternary and some quaternary phase diagrams. A phase diagram construction algorithm based on the calculated phase reaction data in PandaT was developed. And the 3D stereo phase diagram of Al-Cu-Mg ternary system is presented. These phase diagrams can be illustrated by wireframe, surface, solid or their mixture, isotherms and isopleths can be generated. All of these can be displayed by the three typical display ways: electronic shutter, polarization and anaglyph (for example red-cyan glasses). Especially, they can be printed out with 3D stereo effect on paper, and watched by the aid of anaglyph glasses, which makes 3D stereo book of phase diagrams come to reality. Compared with the traditional illustration way, the front of phase diagrams protrude from the screen and the back stretches far behind of the screen under 3D stereo display, the spatial structure can be clearly and immediately perceived. These 3D stereo phase diagrams are useful in teaching and research. - Highlights: • Stereo 3D phase diagram database was constructed, including binary P-T-X, ternary, some quaternary and real ternary systems. • The phase diagrams can be watched by active shutter or polarized or anaglyph glasses. • The print phase diagrams retains 3D stereo effect which can be achieved by the aid of anaglyph glasses.
Selected topics on the nonrelativistic diagram technique
International Nuclear Information System (INIS)
Blokhintsev, L.D.; Narodetskij, I.M.
1983-01-01
The construction of the diagrams describing various processes in the four-particle systems is considered. It is shown that these diagrams, in particular the diagrams corresponding to the simple mechanisms often used in nuclear and atomic reaction theory, are readily obtained from the Faddeev-Yakubovsky equations. The covariant four-dimensional formalism of nonrelativistic Feynman graphs and its connection to the three-dimensional graph technique are briefly discussed
Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira
2016-04-01
This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. All rights reserved.
Zhao, Kanxing; Shi, Xuefeng
2014-07-01
The introduction of Preferred Practice Patterns (PPP) into China has given ophthalmologists in China more opportunities to acquaint themselves with international clinical guidelines for eye care, including its developing principles, methods and the application value. It had brought significant effects on the fast improvement of clinical eye care and standardization of diagnosis and treatment of eye diseases in China, and promoted the international academic exchanges. The 2nd Chinese version of PPPs translated by Prof. Jialiang Zhao was officially published in November, 2013. The new version of PPP for amblyopia adopted the newest standard for grading of evidence strength and recommendation assessment, and emphasizes the practicability based on evidence. New explanations of the definition of amblyopia are added according to the recent research progresses in amblyopia. The diagnostic criteria of best visual acuity for bilateral amblyopia at different ages is given with new specifications. Comprehensive and practical suggestions on the examination methods for amblyopia are provided from the qualitative assessment of visual acuity, the choice of eye chart, to the use of cycloplegic agents. In the aspect of the treatment of amblyopia, based on the findings of recent multi-central random controlled clinical trials, not only strong recommendations are provided, but also the insufficiency of evidence supporting for some choices of therapy is pointed out. The necessity of the follow-up evaluation after the cessation of the treatment of amblyopia is emphasized too. In the aspect of the prevention of amblyopia, the new amblyopia PPP points out the importance of the early-period screening of amblyopia, and that the healthcare insurance plans should cover timely screening, treatment, and monitoring for recurrence of amblyopia. This article deciphers the essential contents of the new version of Chinese PPP for amblyopia, and aims to promote the standardization of the diagnosis
Land, Walker H., Jr.; Embrechts, Mark J.; Anderson, Frances R.; Smith, Tom; Wong, Lut; Fahlbusch, Steve; Choma, Robert
2005-03-01
Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of breast cancer, its positive predictive value (PPV) is low. One of the main deterrents to achieving high computer aided diagnostic (CAD) accuracy is carelessly developed databases. These "noisy" data sets have always appeared to disrupt learning agents from learning correctly. A new statistical method for cleaning data sets was developed that improves the performance of CAD systems. Initial research efforts showed the following: PLS Az value improved by 8.79% and partial Az improved by 49.71%. The K-PLS Az value at Sigma 4.1 improved by 9.18% and the partial Az by 43.47%. The K-PLS at Sigma 3.6 (best fit sigma with this data set) Az value improved by 9.24% and the partial Az by 44.29%. With larger data sets, the ROC curves potentially could look much better than they do now. The Az value for K-PLS (0.892565) is better than PLS, PNN, and most SVMs. The SVM-rbf kernel was the only agent that out performed the K-PLS with an Az value of 0.895362. However, K-PLS runs much faster and appears to be just as accurate as the SVM-rbf kernel.
Supervised deep learning embeddings for the prediction of cervical cancer diagnosis
Directory of Open Access Journals (Sweden)
Kelwin Fernandes
2018-05-01
Full Text Available Cervical cancer remains a significant cause of mortality all around the world, even if it can be prevented and cured by removing affected tissues in early stages. Providing universal and efficient access to cervical screening programs is a challenge that requires identifying vulnerable individuals in the population, among other steps. In this work, we present a computationally automated strategy for predicting the outcome of the patient biopsy, given risk patterns from individual medical records. We propose a machine learning technique that allows a joint and fully supervised optimization of dimensionality reduction and classification models. We also build a model able to highlight relevant properties in the low dimensional space, to ease the classification of patients. We instantiated the proposed approach with deep learning architectures, and achieved accurate prediction results (top area under the curve AUC = 0.6875 which outperform previously developed methods, such as denoising autoencoders. Additionally, we explored some clinical findings from the embedding spaces, and we validated them through the medical literature, making them reliable for physicians and biomedical researchers.
Wong, Kam Cheong
2011-03-29
Studying medical cases is an effective way to enhance clinical reasoning skills and reinforce clinical knowledge. An Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is often used in quality management in manufacturing industries.In this report, an Ishikawa diagram is used to demonstrate how to relate potential causes of a major presenting problem in a clinical setting. This tool can be used by teams in problem-based learning or in self-directed learning settings.An Ishikawa diagram annotated with references to relevant medical cases and literature can be continually updated and can assist memory and retrieval of relevant medical cases and literature. It could also be used to cultivate a lifelong learning habit in medical professionals.
Directory of Open Access Journals (Sweden)
Wong Kam Cheong
2011-03-01
Full Text Available Abstract Studying medical cases is an effective way to enhance clinical reasoning skills and reinforce clinical knowledge. An Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is often used in quality management in manufacturing industries. In this report, an Ishikawa diagram is used to demonstrate how to relate potential causes of a major presenting problem in a clinical setting. This tool can be used by teams in problem-based learning or in self-directed learning settings. An Ishikawa diagram annotated with references to relevant medical cases and literature can be continually updated and can assist memory and retrieval of relevant medical cases and literature. It could also be used to cultivate a lifelong learning habit in medical professionals.
Drawing theories apart the dispersion of Feynman diagrams in postwar physics
Kaiser, David
2005-01-01
Winner of the 2007 Pfizer Prize from the History of Science Society. Feynman diagrams have revolutionized nearly every aspect of theoretical physics since the middle of the twentieth century. Introduced by the American physicist Richard Feynman (1918-88) soon after World War II as a means of simplifying lengthy calculations in quantum electrodynamics, they soon gained adherents in many branches of the discipline. Yet as new physicists adopted the tiny line drawings, they also adapted the diagrams and introduced their own interpretations. Drawing Theories Apart traces how generations of young theorists learned to frame their research in terms of the diagrams—and how both the diagrams and their users were molded in the process.Drawing on rich archival materials, interviews, and more than five hundred scientific articles from the period, Drawing Theories Apart uses the Feynman diagrams as a means to explore the development of American postwar physics. By focusing on the ways young physicists learned new calcul...
A Just-in-Time Learning based Monitoring and Classification Method for Hyper/Hypocalcemia Diagnosis.
Peng, Xin; Tang, Yang; He, Wangli; Du, Wenli; Qian, Feng
2017-01-20
This study focuses on the classification and pathological status monitoring of hyper/hypo-calcemia in the calcium regulatory system. By utilizing the Independent Component Analysis (ICA) mixture model, samples from healthy patients are collected, diagnosed, and subsequently classified according to their underlying behaviors, characteristics, and mechanisms. Then, a Just-in-Time Learning (JITL) has been employed in order to estimate the diseased status dynamically. In terms of JITL, for the purpose of the construction of an appropriate similarity index to identify relevant datasets, a novel similarity index based on the ICA mixture model is proposed in this paper to improve online model quality. The validity and effectiveness of the proposed approach have been demonstrated by applying it to the calcium regulatory system under various hypocalcemic and hypercalcemic diseased conditions.
Using Five Machine Learning for Breast Cancer Biopsy Predictions Based on Mammographic Diagnosis
Oyewola, David; Hakimi, Danladi; Adeboye, Kayode; Shehu, Musa Danjuma
2017-01-01
Breast cancer is one of thecauses of female death in the world. Mammography is commonly used for distinguishing malignant tumors from benign ones. In this research, a mammographic diagnostic method is presented for breast cancer biopsy outcome predictions using fivemachine learning which includes: Logistic Regression(LR), Linear DiscriminantAnalysis(LDA), Quadratic Discriminant Analysis(QDA), Random Forest(RF) andSupport Vector Machine(SVM) classification. The testing result...
Model of components in a process of acoustic diagnosis correlated with learning
International Nuclear Information System (INIS)
Seballos, S.; Costabal, H.; Matamala, P.
1992-06-01
Using Linden's functional scheme as a theoretical reference framework, we define a matrix of component for clinical and field applications in the acoustic diagnostic process and correlations with audiologic, learning and behavioral problems. It is expected that the model effectively contributes to classify and provide a greater knowledge about this multidisciplinary problem. Although the exact nature of this component is at present a matter to be defined, its correlation can be hypothetically established. Applying this descriptive and integral approach in the diagnostic process it is possible if not to avoid, at least to decrease, the uncertainties and assure the proper solutions becoming a powerful tool applicable to environmental studies and/or social claims. (author). 8 refs, 2 figs
Stage line diagram: An age-conditional reference diagram for tracking development
Buuren, S. van; Ooms, J.C.L.
2009-01-01
This paper presents a method for calculating stage line diagrams, a novel type of reference diagram useful for tracking developmental processes over time. Potential fields of applications include: dentistry (tooth eruption), oncology (tumor grading, cancer staging), virology (HIV infection and
Stage line diagram: an age-conditional reference diagram for tracking development.
Van Buuren, S.; Ooms, J.C.L.
2009-01-01
This paper presents a method for calculating stage line diagrams, a novel type of reference diagram useful for tracking developmental processes over time. Potential fields of applications include: dentistry (tooth eruption), oncology (tumor grading, cancer staging), virology (HIV infection and
Maries, Alexandru; Singh, Chandralekha
2018-01-01
Drawing appropriate diagrams is a useful problem solving heuristic that can transform a problem into a representation that is easier to exploit for solving it. One major focus while helping introductory physics students learn effective problem solving is to help them understand that drawing diagrams can facilitate problem solution. We conducted an…
Formal verification of Simulink/Stateflow diagrams a deductive approach
Zhan, Naijun; Zhao, Hengjun
2017-01-01
This book presents a state-of-the-art technique for formal verification of continuous-time Simulink/Stateflow diagrams, featuring an expressive hybrid system modelling language, a powerful specification logic and deduction-based verification approach, and some impressive, realistic case studies. Readers will learn the HCSP/HHL-based deductive method and the use of corresponding tools for formal verification of Simulink/Stateflow diagrams. They will also gain some basic ideas about fundamental elements of formal methods such as formal syntax and semantics, and especially the common techniques applied in formal modelling and verification of hybrid systems. By investigating the successful case studies, readers will realize how to apply the pure theory and techniques to real applications, and hopefully will be inspired to start to use the proposed approach, or even develop their own formal methods in their future work.
CERPHASE: Computer-generated phase diagrams
International Nuclear Information System (INIS)
Ruys, A.J.; Sorrell, C.C.; Scott, F.H.
1990-01-01
CERPHASE is a collection of computer programs written in the programming language basic and developed for the purpose of teaching the principles of phase diagram generation from the ideal solution model of thermodynamics. Two approaches are used in the generation of the phase diagrams: freezing point depression and minimization of the free energy of mixing. Binary and ternary phase diagrams can be generated as can diagrams containing the ideal solution parameters used to generate the actual phase diagrams. Since the diagrams generated utilize the ideal solution model, data input required from the operator is minimal: only the heat of fusion and melting point of each component. CERPHASE is menu-driven and user-friendly, containing simple instructions in the form of screen prompts as well as a HELP file to guide the operator. A second purpose of CERPHASE is in the prediction of phase diagrams in systems for which no experimentally determined phase diagrams are available, enabling the estimation of suitable firing or sintering temperatures for otherwise unknown systems. Since CERPHASE utilizes ideal solution theory, there are certain limitations imposed on the types of systems that can be predicted reliably. 6 refs., 13 refs
Diagram of state of stiff amphiphilic macromolecules
Markov, Vladimir A.; Vasilevskaya, Valentina V.; Khalatur, Pavel G.; ten Brinke, Gerrit; Khokhlov, Alexei R.
2007-01-01
We studied coil-globule transitions in stiff-chain amphiphilic macromolecules via computer modeling and constructed phase diagrams for such molecules in terms of solvent quality and persistence length. We showed that the shape of the phase diagram essentially depends on the macromolecule degree of
Compact flow diagrams for state sequences
Buchin, Kevin; Buchin, Maike; Gudmundsson, Joachim; Horton, Michael; Sijben, Stef
2017-01-01
We introduce the concept of using a flow diagram to compactly represent the segmentation of a large number of state sequences according to a set of criteria. We argue that this flow diagram representation gives an intuitive summary that allows the user to detect patterns within the segmentations. In
Compact flow diagrams for state sequences
Buchin, K.A.; Buchin, M.E.; Gudmundsson, J.; Horton, M.J.; Sijben, S.
2016-01-01
We introduce the concept of compactly representing a large number of state sequences, e.g., sequences of activities, as a flow diagram. We argue that the flow diagram representation gives an intuitive summary that allows the user to detect patterns among large sets of state sequences. Simplified,
Stationary Wavelet Singular Entropy and Kernel Extreme Learning for Bearing Multi-Fault Diagnosis
Directory of Open Access Journals (Sweden)
Nibaldo Rodriguez
2017-10-01
Full Text Available The behavioural diagnostics of bearings play an essential role in the management of several rotation machine systems. However, current diagnostic methods do not deliver satisfactory results with respect to failures in variable speed rotational phenomena. In this paper, we consider the Shannon entropy as an important fault signature pattern. To compute the entropy, we propose combining stationary wavelet transform and singular value decomposition. The resulting feature extraction method, that we call stationary wavelet singular entropy (SWSE, aims to improve the accuracy of the diagnostics of bearing failure by finding a small number of high-quality fault signature patterns. The features extracted by the SWSE are then passed on to a kernel extreme learning machine (KELM classifier. The proposed SWSE-KELM algorithm is evaluated using two bearing vibration signal databases obtained from Case Western Reserve University. We compare our SWSE feature extraction method to other well-known methods in the literature such as stationary wavelet packet singular entropy (SWPSE and decimated wavelet packet singular entropy (DWPSE. The experimental results show that the SWSE-KELM consistently outperforms both the SWPSE-KELM and DWPSE-KELM methods. Further, our SWSE method requires fewer features than the other two evaluated methods, which makes our SWSE-KELM algorithm simpler and faster.
Phase diagram of ammonium nitrate
Energy Technology Data Exchange (ETDEWEB)
Dunuwille, Mihindra; Yoo, Choong-Shik, E-mail: csyoo@wsu.edu [Department of Chemistry and Institute for Shock Physics, Washington State University, Pullman, Washington 99164 (United States)
2013-12-07
Ammonium Nitrate (AN) is a fertilizer, yet becomes an explosive upon a small addition of chemical impurities. The origin of enhanced chemical sensitivity in impure AN (or AN mixtures) is not well understood, posing significant safety issues in using AN even today. To remedy the situation, we have carried out an extensive study to investigate the phase stability of AN and its mixtures with hexane (ANFO–AN mixed with fuel oil) and Aluminum (Ammonal) at high pressures and temperatures, using diamond anvil cells (DAC) and micro-Raman spectroscopy. The results indicate that pure AN decomposes to N{sub 2}, N{sub 2}O, and H{sub 2}O at the onset of the melt, whereas the mixtures, ANFO and Ammonal, decompose at substantially lower temperatures. The present results also confirm the recently proposed phase IV-IV{sup ′} transition above 17 GPa and provide new constraints for the melting and phase diagram of AN to 40 GPa and 400°C.
De Forcrand, Philippe; Forcrand, Philippe de; Philipsen, Owe
2006-01-01
We summarize our recent results on the phase diagram of QCD with N_f=2+1 quark flavors, as a function of temperature T and quark chemical potential \\mu. Using staggered fermions, lattices with temporal extent N_t=4, and the exact RHMC algorithm, we first determine the critical line in the quark mass plane (m_{u,d},m_s) where the finite temperature transition at \\mu=0 is second order. We confirm that the physical point lies on the crossover side of this line. Our data are consistent with a tricritical point at (m_{u,d},m_s) = (0,\\sim 500) MeV. Then, using an imaginary chemical potential, we determine in which direction this second-order line moves as the chemical potential is turned on. Contrary to standard expectations, we find that the region of first-order transitions shrinks in the presence of a chemical potential, which is inconsistent with the presence of a QCD critical point at small chemical potential. The emphasis is put on clarifying the translation of our results from lattice to physical units, and ...
Operations space diagram for ECRH and ECCD
International Nuclear Information System (INIS)
Bindslev, Henrik
2004-01-01
A Clemmov-Mullaly-Allis (CMA) type diagram, the ECW-CMA diagram, for representing the operational possibilities of electron cyclotron heating and current drive (ECRH/ECCD) systems for fusion plasmas is presented. In this diagram, with normalized density and normalized magnetic field coordinates, the parameter range in which it is possible to achieve a given task (e.g. O-mode current drive for stabilizing a neoclassical tearing mode) appears as a region. With also the Greenwald density limit shown, this diagram condenses the information on operational possibilities, facilitating the overview required at the design phase. At the operations phase it may also prove useful in setting up experimental scenarios by showing operational possibilities, avoiding the need for survey type ray-tracing at the initial planning stages. The diagram may also serve the purpose of communicating operational possibilities to non-experts. JET and ITER like plasmas are used, but the method is generic. (author)
Operations space diagram for ECRH and ECCD
DEFF Research Database (Denmark)
Bindslev, H.
2004-01-01
at the design phase. At the operations phase it may also prove useful in setting up experimental scenarios by showing operational possibilities, avoiding the need for survey type ray-tracing at the initial planning stages. The diagram may also serve the purpose of communicating operational possibilities to non......A Clemmov-Mullaly-Allis (CMA) type diagram, the ECW-CMA diagram, for representing the operational possibilities of electron cyclotron heating and current drive (ECRH/ECCD) systems for fusion plasmas is presented. In this diagram, with normalized density and normalized magnetic field coordinates......, the parameter range in which it is possible to achieve a given task (e.g. O-mode current drive for stabilizing a neoclassical tearing mode) appears as a region. With also the Greenwald density limit shown, this diagram condenses the information on operational possibilities, facilitating the overview required...
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.
Multiple representations and free-body diagrams: Do students benefit from using them?
Rosengrant, David R.
2007-12-01
Introductory physics students have difficulties understanding concepts and solving problems. When they solve problems, they use surface features of the problems to find an equation to calculate a numerical answer often not understanding the physics in the problem. How do we help students approach problem solving in an expert manner? A possible answer is to help them learn to represent knowledge in multiple ways and then use these different representations for conceptual understanding and problem solving. This solution follows from research in cognitive science and in physics education. However, there are no studies in physics that investigate whether students who learn to use multiple representations are in fact better problem solvers. This study focuses on one specific representation used in physics--a free body diagram. A free-body diagram is a graphical representation of forces exerted on an object of interest by other objects. I used the free-body diagram to investigate five main questions: (1) If students are in a course where they consistently use free body diagrams to construct and test concepts in mechanics, electricity and magnetism and to solve problems in class and in homework, will they draw free-body diagrams on their own when solving exam problems? (2) Are students who use free-body diagrams to solve problems more successful then those who do not? (3) Why do students draw free-body diagrams when solving problems? (4) Are students consistent in constructing diagrams for different concepts in physics and are they consistent in the quality of their diagrams? (5) What are possible relationships between features of a problem and how likely a student will draw a free body diagram to help them solve the problem? I utilized a mixed-methods approach to answer these questions. Questions 1, 2, 4 and 5 required a quantitative approach while question 3 required a qualitative approach, a case study. When I completed my study, I found that if students are in an
Teaching Metatheory through Venn Diagramming
Linvill, Darren L.; Kendall, Brenden E.
2015-01-01
Communication theory courses are among the most difficult courses in communication curricula. The breadth and complexity of the discipline requires instructors to confront material with which they may have limited familiarity. Such courses are crucial, however, because learning communication theories cultivates critical thinking, helps students to…
Near threshold expansion of Feynman diagrams
International Nuclear Information System (INIS)
Mendels, E.
2005-01-01
The near threshold expansion of Feynman diagrams is derived from their configuration space representation, by performing all x integrations. The general scalar Feynman diagram is considered, with an arbitrary number of external momenta, an arbitrary number of internal lines and an arbitrary number of loops, in n dimensions and all masses may be different. The expansions are considered both below and above threshold. Rules, giving real and imaginary part, are derived. Unitarity of a sunset diagram with I internal lines is checked in a direct way by showing that its imaginary part is equal to the phase space integral of I particles
Between Analogue and Digital Diagrams
Directory of Open Access Journals (Sweden)
Zoltan Bun
2012-10-01
Full Text Available This essay is about the interstitial. About how the diagram, as a method of design, has lead fromthe analogue deconstruction of the eighties to the digital processes of the turn of the millennium.Specifically, the main topic of the text is the interpretation and the critique of folding (as a diagramin the beginning of the nineties. It is necessary then to unfold its relationship with immediatelypreceding and following architectural trends, that is to say we have to look both backwards andforwards by about a decade. The question is the context of folding, the exchange of the analogueworld for the digital. To understand the process it is easier to investigate from the fields of artand culture, rather than from the intentionally perplicated1 thoughts of Gilles Deleuze. Both fieldsare relevant here because they can similarly be used as the yardstick against which the era itselfit measured. The cultural scene of the eighties and nineties, including performing arts, movies,literature and philosophy, is a wide milieu of architecture. Architecture responds parallel to itsera; it reacts to it, and changes with it and within it. Architecture is a medium, it has always beena medium, yet the relations are transformed. That’s not to say that technical progress, for exampleusing CAD-software and CNC-s, has led to the digital thinking of certain movements ofarchitecture, (it is at most an indirect tool. But the ‘up-to-dateness’ of the discipline, however,a kind of non-servile reading of an ‘applied culture’ or ‘used philosophy’2 could be the key.(We might recall here, parenthetically, the fortunes of the artistic in contemporary mass society.The proliferation of museums, the magnification of the figure of the artist, the existence of amassive consumption of printed and televised artistic images, the widespread appetite for informationabout the arts, all reflect, of course, an increasingly leisured society, but also relateprecisely to the fact
IJspeert, Joep E G; Madani, Ariana; Overbeek, Lucy I H; Dekker, Evelien; Nagtegaal, Iris D
2017-05-01
Distinguishing premalignant sessile serrated lesions (SSLs) from hyperplastic polyps (HPs) is difficult for pathologists in daily practice. We aimed to evaluate nationwide variability within histopathology laboratories in the frequency of diagnosing an SSL as compared with an HP within the Dutch population-based screening programme for colorectal cancer and to assess the effect of an e-learning module on interlaboratory consistency. Data were retrieved from the Dutch Pathology Registry from the start of the nationwide population screening programme, January 2014, until December 2015. An obligatory e-learning module was implemented among pathologists in October 2014. The ratio between SSL and HP diagnosis was determined per laboratory. Odds ratios (ORs) for the diagnosis of an SSL per laboratory were compared with the laboratory with the median odds (median laboratory), before and after implementation of the e-learning module. In total, 14 997 individuals with 27 879 serrated polyps were included; 6665 (23.9%) were diagnosed as SSLs, and 21 214 as HPs (76.1%). The ratio of diagnosing an SSL ranged from 5% to 47% (median 23%) within 44 laboratories. Half of the laboratories showed a significantly different OR (range 3.47-0.16) for diagnosing an SSL than the median laboratory. Variability decreased after implementation of the e-learning module (P = 0.02). Of all pathology laboratories, 70% became more consistent with the median laboratory after e-learning implementation. We demonstrated substantial interlaboratory variability in the histopathological diagnosis of SSLs, which significantly decreased after implementation of a structured e-learning module. Widespread implementation of education might contribute to more homogeneous practice among pathologists. © 2016 John Wiley & Sons Ltd.
Voronoi diagram and microstructure of weldment
Energy Technology Data Exchange (ETDEWEB)
Cho, Jung Ho [Chungbuk National University, Cheongju (Korea, Republic of)
2015-01-15
Voronoi diagram, one of the well-known space decomposition algorithms has been applied to express the microstructure of a weldment for the first time due to the superficial analogy between a Voronoi cell and a metal's grain. The area of the Voronoi cells can be controlled by location and the number of the seed points. This can be correlated to the grain size in the microstructure and the number of nuclei formed. The feasibility of representing coarse and fine grain structures were tested through Voronoi diagrams and it is applied to expression of cross-sectional bead shape of a typical laser welding. As result, it successfully described coarsened grain size of heat affected zone and columnar crystals in fusion zone. Although Voronoi diagram showed potential as a microstructure prediction tool through this feasible trial but direct correlation control variable of Voronoi diagram to solidification process parameter is still remained as further works.
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2016-10-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
A novel decision diagrams extension method
International Nuclear Information System (INIS)
Li, Shumin; Si, Shubin; Dui, Hongyan; Cai, Zhiqiang; Sun, Shudong
2014-01-01
Binary decision diagram (BDD) is a graph-based representation of Boolean functions. It is a directed acyclic graph (DAG) based on Shannon's decomposition. Multi-state multi-valued decision diagram (MMDD) is a natural extension of BDD for the symbolic representation and manipulation of the multi-valued logic functions. This paper proposes a decision diagram extension method based on original BDD/MMDD while the scale of a reliability system is extended. Following a discussion of decomposition and physical meaning of BDD and MMDD, the modeling method of BDD/MMDD based on original BDD/MMDD is introduced. Three case studies are implemented to demonstrate the presented methods. Compared with traditional BDD and MMDD generation methods, the decision diagrams extension method is more computationally efficient as shown through the running time
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Center for Theoretical Physics (MCTP), University of Michigan,450 Church Street, Ann Arbor, MI 48109 (United States); Deutsches Elektronen-Synchrotron (DESY),Notkestraße 85, 22607 Hamburg (Germany)
2017-05-30
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2016-10-15
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2017-01-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Compatible growth models and stand density diagrams
International Nuclear Information System (INIS)
Smith, N.J.; Brand, D.G.
1988-01-01
This paper discusses a stand average growth model based on the self-thinning rule developed and used to generate stand density diagrams. Procedures involved in testing are described and results are included
Directory of Open Access Journals (Sweden)
Cao Junxiang
2015-01-01
Full Text Available Teaching-Learning-Based Optimization (TLBO is a new swarm intelligence optimization algorithm that simulates the class learning process. According to such problems of the traditional TLBO as low optimizing efficiency and poor stability, this paper proposes an improved TLBO algorithm mainly by introducing the elite thought in TLBO and adopting different inertia weight decreasing strategies for elite and ordinary individuals of the teacher stage and the student stage. In this paper, the validity of the improved TLBO is verified by the optimizations of several typical test functions and the SVM optimized by the weighted elitist TLBO is used in the diagnosis and classification of common failure data of the TE chemical process. Compared with the SVM combining other traditional optimizing methods, the SVM optimized by the weighted elitist TLBO has a certain improvement in the accuracy of fault diagnosis and classification.
Lattice and Phase Diagram in QCD
International Nuclear Information System (INIS)
Lombardo, Maria Paola
2008-01-01
Model calculations have produced a number of very interesting expectations for the QCD Phase Diagram, and the task of a lattice calculations is to put these studies on a quantitative grounds. I will give an overview of the current status of the lattice analysis of the QCD phase diagram, from the quantitative results of mature calculations at zero and small baryochemical potential, to the exploratory studies of the colder, denser phase.
Finding and Accessing Diagrams in Biomedical Publications
Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael
2012-01-01
Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar...
Ferroelectric Phase Diagram of PVDF:PMMA
Li, Mengyuan; Stingelin, Natalie; Michels, Jasper J.; Spijkman, Mark-Jan; Asadi, Kamal; Feldman, Kirill; Blom, Paul W. M.; de Leeuw, Dago M.
2012-01-01
We have investigated the ferroelectric phase diagram of poly(vinylidene fluoride) (PVDF) and poly(methyl methacrylate) (PMMA). The binary nonequilibrium temperature composition diagram was determined and melting of alpha- and beta-phase PVDF was identified. Ferroelectric beta-PVDF:PMMA blend films were made by melting, ice quenching, and subsequent annealing above the glass transition temperature of PMMA, close to the melting temperature of PVDF. Addition of PMMA suppresses the crystallizatio...
CERN. Geneva
2013-01-01
For decades the central theoretical tool for computing scattering amplitudes has been the Feynman diagram. However, Feynman diagrams are just too slow, even on fast computers, to be able to go beyond the leading order in QCD, for complicated events with many jets of hadrons in the final state. Such events are produced copiously at the LHC, and constitute formidable backgrounds to many searches for new physics. Over the past few years, alternative methods that go beyond ...
The application of diagrams in architectural design
Directory of Open Access Journals (Sweden)
Dulić Olivera
2014-01-01
Full Text Available Diagrams in architecture represent the visualization of the thinking process, or selective abstraction of concepts or ideas translated into the form of drawings. In addition, they provide insight into the way of thinking about and in architecture, thus creating a balance between the visual and the conceptual. The subject of research presented in this paper are diagrams as a specific kind of architectural representation, and possibilities and importance of their application in the design process. Diagrams are almost old as architecture itself, and they are an element of some of the most important studies of architecture during all periods of history - which results in a large number of different definitions of diagrams, but also very different conceptualizations of their features, functions and applications. The diagrams become part of contemporary architectural discourse during the eighties and nineties of the twentieth century, especially through the work of architects like Bernard Tschumi, Peter Eisenman, Rem Koolhaas, SANAA and others. The use of diagrams in the design process allows unification of some of the essential aspects of the profession: architectural representation and design process, as well as the question of the concept of architectural and urban design at a time of rapid changes at all levels of contemporary society. The aim of the research is the analysis of the diagram as a specific medium for processing large amounts of information that the architect should consider and incorporate into the architectural work. On that basis, it is assumed that an architectural diagram allows the creator the identification and analysis of specific elements or ideas of physical form, thereby constantly maintaining concept of the integrity of the architectural work.
Atomic energy levels and Grotrian diagrams
Bashkin, Stanley
1975-01-01
Atomic Energy Levels and Grotrian Diagrams, Volume I: Hydrogen I - Phosphorus XV presents diagrams of various elements that show their energy level and electronic transitions. The book covers the first 15 elements according to their atomic number. The text will be of great use to researchers and practitioners of fields such as astrophysics that requires pictorial representation of the energy levels and electronic transitions of elements.
An Introduction to Binary Decision Diagrams
DEFF Research Database (Denmark)
Andersen, Henrik Reif
1996-01-01
This note is a short introduction to Binary Decision Diagrams (BDDs). It provides some background knowledge and describes the core algorithms. It is used in the course "C4340 Advanced Algorithms" at the Technical University of Denmark, autumn 1996.......This note is a short introduction to Binary Decision Diagrams (BDDs). It provides some background knowledge and describes the core algorithms. It is used in the course "C4340 Advanced Algorithms" at the Technical University of Denmark, autumn 1996....
Gluing Ladder Feynman Diagrams into Fishnets
International Nuclear Information System (INIS)
Basso, Benjamin; Dixon, Lance J.; Stanford University, CA; University of California, Santa Barbara, CA
2017-01-01
We use integrability at weak coupling to compute fishnet diagrams for four-point correlation functions in planar Φ "4 theory. Our results are always multilinear combinations of ladder integrals, which are in turn built out of classical polylogarithms. The Steinmann relations provide a powerful constraint on such linear combinations, which leads to a natural conjecture for any fishnet diagram as the determinant of a matrix of ladder integrals.
Random Young diagrams in a Rectangular Box
DEFF Research Database (Denmark)
Beltoft, Dan; Boutillier, Cédric; Enriquez, Nathanaël
We exhibit the limit shape of random Young diagrams having a distribution proportional to the exponential of their area, and confined in a rectangular box. The Ornstein-Uhlenbeck bridge arises from the fluctuations around the limit shape.......We exhibit the limit shape of random Young diagrams having a distribution proportional to the exponential of their area, and confined in a rectangular box. The Ornstein-Uhlenbeck bridge arises from the fluctuations around the limit shape....
Reading fitness landscape diagrams through HSAB concepts
Energy Technology Data Exchange (ETDEWEB)
Vigneresse, Jean-Louis, E-mail: jean-louis.vigneresse@univ-lorraine.fr
2014-10-31
Highlights: • Qualitative information from HSAB descriptors. • 2D–3D diagrams using chemical descriptors (χ, η, ω, α) and principles (MHP, mEP, mPP). • Estimate of the energy exchange during reaction paths. • Examples from complex systems (geochemistry). - Abstract: Fitness landscapes are conceived as range of mountains, with local peaks and valleys. In terms of potential, such topographic variations indicate places of local instability or stability. The chemical potential, or electronegativity, its value changed of sign, carries similar information. In addition to chemical descriptors defined through hard-soft acid-base (HSAB) concepts and computed through density functional theory (DFT), the principles that rule chemical reactions allow the design of such landscape diagrams. The simplest diagram uses electrophilicity and hardness as coordinates. It allows examining the influence of maximum hardness or minimum electrophilicity principles. A third dimension is introduced within such a diagram by mapping the topography of electronegativity, polarizability or charge exchange. Introducing charge exchange during chemical reactions, or mapping a third parameter (f.i. polarizability) reinforces the information carried by a simple binary diagram. Examples of such diagrams are provided, using data from Earth Sciences, simple oxides or ligands.
The amplituhedron from momentum twistor diagrams
International Nuclear Information System (INIS)
Bai, Yuntao; He, Song
2015-01-01
We propose a new diagrammatic formulation of the all-loop scattering amplitudes/Wilson loops in planar N=4 SYM, dubbed the “momentum-twistor diagrams”. These are on-shell-diagrams obtained by gluing trivalent black and white vertices in momentum twistor space, which, in the reduced diagram case, are known to be related to diagrams in the original twistor space. The new diagrams are manifestly Yangian invariant, and they naturally represent factorization and forward-limit contributions in the all-loop BCFW recursion relations in momentum twistor space, in a fashion that is completely different from those in momentum space. We show how to construct and evaluate momentum-twistor diagrams, and how to use them to obtain tree-level amplitudes and loop-level integrands; in particular the latter involve isolated bubble-structures for loop variables arising from forward limits, or the entangled removal of particles. From each diagram, the generalized “boundary measurement” directly gives the C, D matrices, thus a cell in the amplituhedron associated with the amplitude, and we expect that our diagrammatic representations of the amplitude provide triangulations of the amplituhedron. To demonstrate the computational power of the formalism, we give explicit results for general two-loop integrands, and the cells of the amplituhedron for two-loop MHV amplitudes.
Asymptotic laws for random knot diagrams
Chapman, Harrison
2017-06-01
We study random knotting by considering knot and link diagrams as decorated, (rooted) topological maps on spheres and pulling them uniformly from among sets of a given number of vertices n, as first established in recent work with Cantarella and Mastin. The knot diagram model is an exciting new model which captures both the random geometry of space curve models of knotting as well as the ease of computing invariants from diagrams. We prove that unknot diagrams are asymptotically exponentially rare, an analogue of Sumners and Whittington’s landmark result for self-avoiding polygons. Our proof uses the same key idea: we first show that knot diagrams obey a pattern theorem, which describes their fractal structure. We examine how quickly this behavior occurs in practice. As a consequence, almost all diagrams are asymmetric, simplifying sampling from this model. We conclude with experimental data on knotting in this model. This model of random knotting is similar to those studied by Diao et al, and Dunfield et al.
Directory of Open Access Journals (Sweden)
Hongmin Cai
Full Text Available PURPOSE: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported. MATERIALS AND METHODS: The study comprised of 234 female patients with 85 benign and 149 malignant lesions. Four distinct groups of features, coupling with pathological tests, were estimated to comprehensively characterize the pictorial properties of each lesion, which was obtained by a semi-automated segmentation method. Classical machine learning scheme including feature subset selection and various classification schemes were employed to build prognostic model, which served as a foundation for evaluating the combined effects of the multi-sided features for predicting of the types of lesions. Various measurements including cross validation and receiver operating characteristics were used to quantify the diagnostic performances of each feature as well as their combination. RESULTS: Seven features were all found to be statistically different between the malignant and the benign groups and their combination has achieved the highest classification accuracy. The seven features include one pathological variable of age, one morphological variable of slope, three texture features of entropy, inverse difference and information correlation, one kinetic feature of SER and one DWI feature of apparent diffusion coefficient (ADC. Together with the selected diagnostic features, various classical classification schemes were used to test their discrimination power through cross validation scheme. The averaged measurements of sensitivity, specificity, AUC and accuracy are 0.85, 0.89, 90.9% and 0.93, respectively. CONCLUSION: Multi-sided variables which characterize the morphological, kinetic, pathological
Cai, Hongmin; Peng, Yanxia; Ou, Caiwen; Chen, Minsheng; Li, Li
2014-01-01
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI) of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported. The study comprised of 234 female patients with 85 benign and 149 malignant lesions. Four distinct groups of features, coupling with pathological tests, were estimated to comprehensively characterize the pictorial properties of each lesion, which was obtained by a semi-automated segmentation method. Classical machine learning scheme including feature subset selection and various classification schemes were employed to build prognostic model, which served as a foundation for evaluating the combined effects of the multi-sided features for predicting of the types of lesions. Various measurements including cross validation and receiver operating characteristics were used to quantify the diagnostic performances of each feature as well as their combination. Seven features were all found to be statistically different between the malignant and the benign groups and their combination has achieved the highest classification accuracy. The seven features include one pathological variable of age, one morphological variable of slope, three texture features of entropy, inverse difference and information correlation, one kinetic feature of SER and one DWI feature of apparent diffusion coefficient (ADC). Together with the selected diagnostic features, various classical classification schemes were used to test their discrimination power through cross validation scheme. The averaged measurements of sensitivity, specificity, AUC and accuracy are 0.85, 0.89, 90.9% and 0.93, respectively. Multi-sided variables which characterize the morphological, kinetic, pathological properties and DWI measurement of ADC can dramatically improve the
Mohebian, Mohammad R; Marateb, Hamid R; Mansourian, Marjan; Mañanas, Miguel Angel; Mokarian, Fariborz
2017-01-01
Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread to the body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breast cancer recurrence prediction is presented in this manuscript. Clinicopathologic characteristics of 579 breast cancer patients (recurrence prevalence of 19.3%) were analyzed and discriminative features were selected using statistical feature selection methods. They were further refined by Particle Swarm Optimization (PSO) as the inputs of the classification system with ensemble learning (Bagged Decision Tree: BDT). The proper combination of selected categorical features and also the weight (importance) of the selected interval-measurement-scale features were identified by the PSO algorithm. The performance of HPBCR (hybrid predictor of breast cancer recurrence) was assessed using the holdout and 4-fold cross-validation. Three other classifiers namely as supported vector machines, DT, and multilayer perceptron neural network were used for comparison. The selected features were diagnosis age, tumor size, lymph node involvement ratio, number of involved axillary lymph nodes, progesterone receptor expression, having hormone therapy and type of surgery. The minimum sensitivity, specificity, precision and accuracy of HPBCR were 77%, 93%, 95% and 85%, respectively in the entire cross-validation folds and the hold-out test fold. HPBCR outperformed the other tested classifiers. It showed excellent agreement with the gold standard (i.e. the oncologist opinion after blood tumor marker and imaging tests, and tissue biopsy). This algorithm is thus a promising online tool for the prediction of breast cancer recurrence.
Examining competing hypotheses for the effects of diagrams on recall for text.
Ortegren, Francesca R; Serra, Michael J; England, Benjamin D
2015-01-01
Supplementing text-based learning materials with diagrams typically increases students' free recall and cued recall of the presented information. In the present experiments, we examined competing hypotheses for why this occurs. More specifically, although diagrams are visual, they also serve to repeat information from the text they accompany. Both visual presentation and repetition are known to aid students' recall of information. To examine to what extent diagrams aid recall because they are visual or repetitive (or both), we had college students in two experiments (n = 320) read a science text about how lightning storms develop before completing free-recall and cued-recall tests over the presented information. Between groups, we manipulated the format and repetition of target pieces of information in the study materials using a 2 (visual presentation of target information: diagrams present vs. diagrams absent) × 2 (repetition of target information: present vs. absent) between-participants factorial design. Repetition increased both the free recall and cued recall of target information, and this occurred regardless of whether that repetition was in the form of text or a diagram. In contrast, the visual presentation of information never aided free recall. Furthermore, visual presentation alone did not significantly aid cued recall when participants studied the materials once before the test (Experiment 1) but did when they studied the materials twice (Experiment 2). Taken together, the results of the present experiments demonstrate the important role of repetition (i.e., that diagrams repeat information from the text) over the visual nature of diagrams in producing the benefits of diagrams for recall.
New web-based applications for mechanistic case diagramming
Directory of Open Access Journals (Sweden)
Fred R. Dee
2014-07-01
Full Text Available The goal of mechanistic case diagraming (MCD is to provide students with more in-depth understanding of cause and effect relationships and basic mechanistic pathways in medicine. This will enable them to better explain how observed clinical findings develop from preceding pathogenic and pathophysiological events. The pedagogic function of MCD is in relating risk factors, disease entities and morphology, signs and symptoms, and test and procedure findings in a specific case scenario with etiologic pathogenic and pathophysiological sequences within a flow diagram. In this paper, we describe the addition of automation and predetermined lists to further develop the original concept of MCD as described by Engelberg in 1992 and Guerrero in 2001. We demonstrate that with these modifications, MCD is effective and efficient in small group case-based teaching for second-year medical students (ratings of ~3.4 on a 4.0 scale. There was also a significant correlation with other measures of competency, with a ‘true’ score correlation of 0.54. A traditional calculation of reliability showed promising results (α =0.47 within a low stakes, ungraded environment. Further, we have demonstrated MCD's potential for use in independent learning and TBL. Future studies are needed to evaluate MCD's potential for use in medium stakes assessment or self-paced independent learning and assessment. MCD may be especially relevant in returning students to the application of basic medical science mechanisms in the clinical years.
[Etiological diagnosis of leg ulcers].
Debure, Clélia
2010-09-20
Etiological diagnosis of leg ulcers must be the first step of treatment, even if we know that veinous disease is often present. We can build a clinical decisional diagram, which helps us to understand and not forget the other causes of chronic wounds and choose some basic examination, like ultrasound and histological findings. This diagnosis helps to choose the right treatment in order to cure even the oldest venous ulcers. Educational programs should be improved to prevent recurrence.
The Semiotic Structure of Geometry Diagrams: How Textbook Diagrams Convey Meaning
Dimmel, Justin K.; Herbst, Patricio G.
2015-01-01
Geometry diagrams use the visual features of specific drawn objects to convey meaning about generic mathematical entities. We examine the semiotic structure of these visual features in two parts. One, we conduct a semiotic inquiry to conceptualize geometry diagrams as mathematical texts that comprise choices from different semiotic systems. Two,…
Fishbone Diagrams: Organize Reading Content with a "Bare Bones" Strategy
Clary, Renee; Wandersee, James
2010-01-01
Fishbone diagrams, also known as Ishikawa diagrams or cause-and-effect diagrams, are one of the many problem-solving tools created by Dr. Kaoru Ishikawa, a University of Tokyo professor. Part of the brilliance of Ishikawa's idea resides in the simplicity and practicality of the diagram's basic model--a fish's skeleton. This article describes how…
Visualizing Metrics on Areas of Interest in Software Architecture Diagrams
Byelas, Heorhiy; Telea, Alexandru; Eades, P; Ertl, T; Shen, HW
2009-01-01
We present a new method for the combined visualization of software architecture diagrams, Such as UML class diagrams or component diagrams, and software metrics defined on groups of diagram elements. Our method extends an existing rendering technique for the so-called areas of interest in system
Abbott, Kathy
1990-01-01
The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to
Phase diagram of classical electronic bilayers
International Nuclear Information System (INIS)
Ranganathan, S; Johnson, R E
2006-01-01
Extensive molecular dynamics calculations have been performed on classical, symmetric electronic bilayers at various values of the coupling strength Γ and interlayer separation d to delineate its phase diagram in the Γ-d plane. We studied the diffusion, the amplitude of the main peak of the intralayer static structure factor and the peak positions of the intralayer pair correlation function with the aim of defining equivalent signatures of freezing and constructing the resulting phase diagram. It is found that for Γ greater than 75, crystalline structures exist for a certain range of interlayer separations, while liquid phases are favoured at smaller and larger d. It is seen that there is good agreement between our phase diagram and previously published ones
Phase diagram of classical electronic bilayers
Energy Technology Data Exchange (ETDEWEB)
Ranganathan, S [Department of Physics, Royal Military College of Canada, Kingston, Ontario K7K 7B4 (Canada); Johnson, R E [Department of Mathematics and Computer Science, Royal Military College of Canada, Kingston, Ontario K7K 7B4 (Canada)
2006-04-28
Extensive molecular dynamics calculations have been performed on classical, symmetric electronic bilayers at various values of the coupling strength {gamma} and interlayer separation d to delineate its phase diagram in the {gamma}-d plane. We studied the diffusion, the amplitude of the main peak of the intralayer static structure factor and the peak positions of the intralayer pair correlation function with the aim of defining equivalent signatures of freezing and constructing the resulting phase diagram. It is found that for {gamma} greater than 75, crystalline structures exist for a certain range of interlayer separations, while liquid phases are favoured at smaller and larger d. It is seen that there is good agreement between our phase diagram and previously published ones.
The Butterfly diagram leopard skin pattern
Ternullo, Maurizio
2011-08-01
A time-latitude diagram where spotgroups are given proportional relevance to their area is presented. The diagram reveals that the spotted area distribution is higly dishomogeneous, most of it being concentrated in few, small portions (``knots'') of the Butterfly Diagram; because of this structure, the BD may be properly described as a cluster of knots. The description, assuming that spots scatter around the ``spot mean latitude'' steadily drifting equatorward, is challenged. Indeed, spots cluster around at as many latitudes as knots; a knot may appear at either lower or higher latitudes than previous ones, in a seemingly random way; accordingly, the spot mean latitude abruptly drifts equatorward or even poleward at any knot activation, in spite of any smoothing procedure. Preliminary analyses suggest that the activity splits, in any hemisphere, into two or more distinct ``activity waves'', drifting equatorward at a rate higher than the spot zone as a whole.
Phase diagrams of diluted transverse Ising nanowire
Energy Technology Data Exchange (ETDEWEB)
Bouhou, S.; Essaoudi, I. [Laboratoire de Physique des Matériaux et Modélisation, des Systèmes, (LP2MS), Unité Associée au CNRST-URAC 08, University of Moulay Ismail, Physics Department, Faculty of Sciences, B.P. 11201 Meknes (Morocco); Ainane, A., E-mail: ainane@pks.mpg.de [Laboratoire de Physique des Matériaux et Modélisation, des Systèmes, (LP2MS), Unité Associée au CNRST-URAC 08, University of Moulay Ismail, Physics Department, Faculty of Sciences, B.P. 11201 Meknes (Morocco); Max-Planck-Institut für Physik Complexer Systeme, Nöthnitzer Str. 38 D-01187 Dresden (Germany); Saber, M. [Laboratoire de Physique des Matériaux et Modélisation, des Systèmes, (LP2MS), Unité Associée au CNRST-URAC 08, University of Moulay Ismail, Physics Department, Faculty of Sciences, B.P. 11201 Meknes (Morocco); Max-Planck-Institut für Physik Complexer Systeme, Nöthnitzer Str. 38 D-01187 Dresden (Germany); Ahuja, R. [Condensed Matter Theory Group, Department of Physics and Astronomy, Uppsala University, 75120 Uppsala (Sweden); Dujardin, F. [Laboratoire de Chimie et Physique des Milieux Complexes (LCPMC), Institut de Chimie, Physique et Matériaux (ICPM), 1 Bd. Arago, 57070 Metz (France)
2013-06-15
In this paper, the phase diagrams of diluted Ising nanowire consisting of core and surface shell coupling by J{sub cs} exchange interaction are studied using the effective field theory with a probability distribution technique, in the presence of transverse fields in the core and in the surface shell. We find a number of characteristic phenomena. In particular, the effect of concentration c of magnetic atoms, the exchange interaction core/shell, the exchange in surface and the transverse fields in core and in surface shell of phase diagrams are investigated. - Highlights: ► We use the EFT to investigate the phase diagrams of Ising transverse nanowire. ► Ferrimagnetic and ferromagnetic cases are investigated. ► The effects of the dilution and the transverse fields in core and shell are studied. ► Behavior of the transition temperature with the exchange interaction is given.
Phase diagrams of diluted transverse Ising nanowire
International Nuclear Information System (INIS)
Bouhou, S.; Essaoudi, I.; Ainane, A.; Saber, M.; Ahuja, R.; Dujardin, F.
2013-01-01
In this paper, the phase diagrams of diluted Ising nanowire consisting of core and surface shell coupling by J cs exchange interaction are studied using the effective field theory with a probability distribution technique, in the presence of transverse fields in the core and in the surface shell. We find a number of characteristic phenomena. In particular, the effect of concentration c of magnetic atoms, the exchange interaction core/shell, the exchange in surface and the transverse fields in core and in surface shell of phase diagrams are investigated. - Highlights: ► We use the EFT to investigate the phase diagrams of Ising transverse nanowire. ► Ferrimagnetic and ferromagnetic cases are investigated. ► The effects of the dilution and the transverse fields in core and shell are studied. ► Behavior of the transition temperature with the exchange interaction is given
Sampurno, A. W.; Rahmat, A.; Diana, S.
2017-09-01
Diagrams/pictures conventions is one form of visual media that often used to assist students in understanding the biological concepts. The effectiveness of use diagrams/pictures in biology learning at school level has also been mostly reported. This study examines the ability of high school students in reading diagrams/pictures biological convention which is described by Mental Representation based on formation of causal networks. The study involved 30 students 11th grade MIA senior high school Banten Indonesia who are studying the excretory system. MR data obtained by Instrument worksheet, developed based on CNET-protocol, in which there are diagrams/drawings of nephron structure and urinary mechanism. Three patterns formed MR, namely Markov chain, feedback control with a single measurement, and repeated feedback control with multiple measurement. The third pattern is the most dominating pattern, differences in the pattern of MR reveal the difference in how and from which point the students begin to uncover important information contained in the diagram to establish a causal networks. Further analysis shows that a difference in the pattern of MR relate to how complex the students process the information contained in the diagrams/pictures.
Reiner, Miriam; And Others
1995-01-01
Observations of high school physics students in an instructional experiment with an interactive learning environment in geometrical optics indicated that students in the Optics Dynagrams Project went through major conceptual developments as reflected in the diagrams they constructed. (Author/MKR)
Formal Analysis Of Use Case Diagrams
Directory of Open Access Journals (Sweden)
Radosław Klimek
2010-01-01
Full Text Available Use case diagrams play an important role in modeling with UML. Careful modeling is crucialin obtaining a correct and efficient system architecture. The paper refers to the formalanalysis of the use case diagrams. A formal model of use cases is proposed and its constructionfor typical relationships between use cases is described. Two methods of formal analysis andverification are presented. The first one based on a states’ exploration represents a modelchecking approach. The second one refers to the symbolic reasoning using formal methodsof temporal logic. Simple but representative example of the use case scenario verification isdiscussed.
International Nuclear Information System (INIS)
Abulkhaev, V.L.; Ganiev, I.N.
1994-01-01
By means of thermal differential analysis, X-ray and microstructural analysis the state diagram of Pr-Bi system was studied. Following intermetallic compounds were defined in the system: Pr 2 Bi, Pr 5 Bi 3 , Pr 4 Bi 3 , Pr Bi, PrBi 2 , Pr 2 Bi, Pr 5 Bi 3 , Pr 4 Bi 3 and PrBi 2 . The data analysis on Ln-Bi diagram allowed to determine the regularity of change of properties of intermetallic compounds in the line of rare earth elements of cerium subgroup.
Fusion Diagrams in the - and - Systems
Asadov, M. M.; Akhmedova, N. A.
2014-10-01
A calculation model of the Gibbs energy of ternary oxide compounds from the binary components was used. Thermodynamic properties of -- ternary systems in the condensed state were calculated. Thermodynamic data of binary and ternary compounds were used to determine the stable sections. The probability of reactions between the corresponding components in the -- system was estimated. Fusibility diagrams of systems - and - were studied by physical-chemical analysis. The isothermal section of the phase diagram of -- at 298 K is built, as well as the projection of the liquid surface of --.
Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.
2017-12-01
Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p = 0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.
Enumeration of diagonally colored Young diagrams
Gyenge, Ádám
2015-01-01
In this note we give a new proof of a closed formula for the multivariable generating series of diagonally colored Young diagrams. This series also describes the Euler characteristics of certain Nakajima quiver varieties. Our proof is a direct combinatorial argument, based on Andrews' work on generalized Frobenius partitions. We also obtain representations of these series in some particular cases as infinite products.
Partial chord diagrams and matrix models
DEFF Research Database (Denmark)
Andersen, Jørgen Ellegaard; Fuji, Hiroyuki; Manabe, Masahide
In this article, the enumeration of partial chord diagrams is discussed via matrix model techniques. In addition to the basic data such as the number of backbones and chords, we also consider the Euler characteristic, the backbone spectrum, the boundary point spectrum, and the boundary length spe...
Characteristic Dynkin diagrams and W algebras
International Nuclear Information System (INIS)
Ragoucy, E.
1993-01-01
We present a classification of characteristic Dynkin diagrams for the A N , B N , C N and D N algebras. This classification is related to the classification of W(G, K) algebras arising from non-abelian Toda models, and we argue that it can give new insight on the structure of W algebras. (orig.)
Diagram of a LEP superconducting cavity
1991-01-01
This diagram gives a schematic representation of the superconducting radio-frequency cavities at LEP. Liquid helium is used to cool the cavity to 4.5 degrees above absolute zero so that very high electric fields can be produced, increasing the operating energy of the accelerator. Superconducting cavities were used only in the LEP-2 phase of the accelerator, from 1996 to 2000.
Extended sequence diagram for human system interaction
International Nuclear Information System (INIS)
Hwang, Jong Rok; Choi, Sun Woo; Ko, Hee Ran; Kim, Jong Hyun
2012-01-01
Unified Modeling Language (UML) is a modeling language in the field of object oriented software engineering. The sequence diagram is a kind of interaction diagram that shows how processes operate with one another and in what order. It is a construct of a message sequence chart. It depicts the objects and classes involved in the scenario and the sequence of messages exchanged between the objects needed to carry out the functionality of the scenario. This paper proposes the Extended Sequence Diagram (ESD), which is capable of depicting human system interaction for nuclear power plants, as well as cognitive process of operators analysis. In the conventional sequence diagram, there is a limit to only identify the activities of human and systems interactions. The ESD is extended to describe operators' cognitive process in more detail. The ESD is expected to be used as a task analysis method for describing human system interaction. The ESD can also present key steps causing abnormal operations or failures and diverse human errors based on cognitive condition
Kelp diagrams : Point set membership visualization
Dinkla, K.; Kreveld, van M.J.; Speckmann, B.; Westenberg, M.A.
2012-01-01
We present Kelp Diagrams, a novel method to depict set relations over points, i.e., elements with predefined positions. Our method creates schematic drawings and has been designed to take aesthetic quality, efficiency, and effectiveness into account. This is achieved by a routing algorithm, which
Mixed wasted integrated program: Logic diagram
International Nuclear Information System (INIS)
Mayberry, J.; Stelle, S.; O'Brien, M.; Rudin, M.; Ferguson, J.; McFee, J.
1994-01-01
The Mixed Waste Integrated Program Logic Diagram was developed to provide technical alternative for mixed wastes projects for the Office of Technology Development's Mixed Waste Integrated Program (MWIP). Technical solutions in the areas of characterization, treatment, and disposal were matched to a select number of US Department of Energy (DOE) treatability groups represented by waste streams found in the Mixed Waste Inventory Report (MWIR)
Phase Diagrams of Strongly Interacting Theories
DEFF Research Database (Denmark)
Sannino, Francesco
2010-01-01
We summarize the phase diagrams of SU, SO and Sp gauge theories as function of the number of flavors, colors, and matter representation as well as the ones of phenomenologically relevant chiral gauge theories such as the Bars-Yankielowicz and the generalized Georgi-Glashow models. We finally report...
Spin wave Feynman diagram vertex computation package
Price, Alexander; Javernick, Philip; Datta, Trinanjan
Spin wave theory is a well-established theoretical technique that can correctly predict the physical behavior of ordered magnetic states. However, computing the effects of an interacting spin wave theory incorporating magnons involve a laborious by hand derivation of Feynman diagram vertices. The process is tedious and time consuming. Hence, to improve productivity and have another means to check the analytical calculations, we have devised a Feynman Diagram Vertex Computation package. In this talk, we will describe our research group's effort to implement a Mathematica based symbolic Feynman diagram vertex computation package that computes spin wave vertices. Utilizing the non-commutative algebra package NCAlgebra as an add-on to Mathematica, symbolic expressions for the Feynman diagram vertices of a Heisenberg quantum antiferromagnet are obtained. Our existing code reproduces the well-known expressions of a nearest neighbor square lattice Heisenberg model. We also discuss the case of a triangular lattice Heisenberg model where non collinear terms contribute to the vertex interactions.
Phase diagram distortion from traffic parameter averaging.
Stipdonk, H. Toorenburg, J. van & Postema, M.
2010-01-01
Motorway traffic congestion is a major bottleneck for economic growth. Therefore, research of traffic behaviour is carried out in many countries. Although well describing the undersaturated free flow phase as an almost straight line in a (k,q)-phase diagram, congested traffic observations and
A Generalized Wave Diagram for Moving Sources
Alt, Robert; Wiley, Sam
2004-12-01
Many introductory physics texts1-5 accompany the discussion of the Doppler effect and the formation of shock waves with diagrams illustrating the effect of a source moving through an elastic medium. Typically these diagrams consist of a series of equally spaced dots, representing the location of the source at different times. These are surrounded by a series of successively smaller circles representing wave fronts (see Fig. 1). While such a diagram provides a clear illustration of the shock wave produced by a source moving at a speed greater than the wave speed, and also the resultant pattern when the source speed is less than the wave speed (the Doppler effect), the texts do not often show the details of the construction. As a result, the key connection between the relative distance traveled by the source and the distance traveled by the wave is not explicitly made. In this paper we describe an approach emphasizing this connection that we have found to be a useful classroom supplement to the usual text presentation. As shown in Fig. 2 and Fig. 3, the Doppler effect and the shock wave can be illustrated by diagrams generated by the construction that follows.
Planar quark diagrams and binary spin processes
International Nuclear Information System (INIS)
Grigoryan, A.A.; Ivanov, N.Ya.
1986-01-01
Contributions of planar diagrams to the binary scattering processes are analyzed. The analysis is based on the predictions of quark-gluon picture of strong interactions for the coupling of reggeons with quarks as well as on the SU(6)-classification of hadrons. The dependence of contributions of nonplanar corrections on spins and quark composition of interacting particles is discussed
Phase diagram of spiking neural networks.
Seyed-Allaei, Hamed
2015-01-01
In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probability of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations, and trials and errors, but here, I take a different perspective, inspired by evolution, I systematically simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable. I stimulate networks with pulses and then measure their: dynamic range, dominant frequency of population activities, total duration of activities, maximum rate of population and the occurrence time of maximum rate. The results are organized in phase diagram. This phase diagram gives an insight into the space of parameters - excitatory to inhibitory ratio, sparseness of connections and synaptic weights. This phase diagram can be used to decide the parameters of a model. The phase diagrams show that networks which are configured according to the common values, have a good dynamic range in response to an impulse and their dynamic range is robust in respect to synaptic weights, and for some synaptic weights they oscillates in α or β frequencies, independent of external stimuli.
Muonium and the Breit-Rabi diagram
International Nuclear Information System (INIS)
Cox, S.F.J.
1984-01-01
This chapter introduces the study of muonium, as opposed to that of unbound muons. The properties and behaviour of muonium are compared and contrasted with those of hydrogen and of positronium. The special significance of muonium in atomic and molecular physics is explained, and its utility as a lightweight or radioactive isotope of hydrogen in solid state physics and chemistry illustrated. The identification of atomic muonium by means of its ground state magnetic properties is described with reference to the Breit-Rabi diagram. This diagram is invaluable for interpreting or predicting MuSR observations, both in transverse and longitudinal magnetic fields, so its construction and properties are explained in some detail. The precession signals observed in transverse-field MuSR correspond to transitions allowed between the energy levels in this diagram; particular attention is paid to the spectra characteristic of the high and low field regimes. The different states of muonium observed in dielectric, semiconducting and metallic materials are introduced. The influence of the host medium on the spectral parameters, hyperfine interaction and linewidth, is considered both for atomic muonium and for muonium which is chemically bound in paramagnetic molecules, for which the Breit-Rabi diagram also applies. (orig.)
The classification of diagrams in perturbation theory
International Nuclear Information System (INIS)
Phillips, D.R.; Afnan, I.R.
1995-01-01
The derivation of scattering equations connecting the amplitudes obtained from diagrammatic expansions is of interest in many branches of physics. One method for deriving such equations is the classification-of-diagrams technique of Taylor. However, as we shall explain in this paper, there are certain points of Taylor's method which require clarification. First, it is not clear whether Taylor's original method is equivlant to the simpler classification-of-diagrams scheme used by Thomas, Rinat, Afnan, and Blankleider (TRAB). Second, when the Taylor method is applied to certain problems in a time-dependent perturbation theory it leads to the over-counting of some diagrams. This paper first restates Taylor's method, in the process uncovering reasons why certain diagrams might be double-counted in the Taylor method. In then explores how far Taylor's method is equivalent to the simpler TRAB method. Finally, it examines precisely why the double-counting occurs in Taylor's method and derives corrections which compensate for this double-counting. copyright 1995 Academic Press, Inc
Influence diagram in evaluating the subjective judgment
International Nuclear Information System (INIS)
Hong, Y.
1997-01-01
The author developed the idea of the subjective influence diagrams to evaluate subjective judgment. The subjective judgment of a stake holder is a primary decision making proposition. It involves a basic decision process an the individual attitude of the stake holder for his decision purpose. The subjective judgment dominates the some final decisions. A complex decision process may include the subjective judgment. An influence diagram framework is a simplest tool for analyzing subjective judgment process. In the framework, the characters of influence diagrams generate the describing the analyzing, and the evaluating of the subjective judgment. The relationship between the information and the decision, such as independent character between them, is the main issue. Then utility function is the calculating tool to evaluation, the stake holder can make optimal decision. Through the analysis about the decision process and relationship, the building process of the influence diagram identically describes the subjective judgment. Some examples are given to explain the property of subjective judgment and the analysis process
International Nuclear Information System (INIS)
Kaler, J.B.
1988-01-01
The evolution of various types of stars along the H-R diagram is discussed. Star birth and youth is addressed, and the events that occur due to core contraction, shell burning, and double-shell burning are described. The evolutionary courses of planetary nebulae, white dwarfs, and supernovas are examined
The Keynesian Diagram: A Cross to Bear?
Fleck, Juergen
In elementary economics courses students are often introduced to the basic concepts of macroeconomics through very simplified static models, and the concept of a macroeconomic equilibrium is generally explained with the help of an aggregate demand/aggregate supply (AD/AS) model and an income/expenditure model (via the Keynesian cross diagram).…
Magnetic phase diagram of a nanocone
International Nuclear Information System (INIS)
Suarez, O; Vargas, P; Escrig, J; Landeros, P; Albir, D; Laroze, D
2008-01-01
In this work we analyze the magnetic properties of truncated conical nanoparticles. Based on the continuous magnetic model we find expressions for the total energy in three different magnetic configurations. Finally, we calculate the magnetic phase diagram as function of the geometrical parameters.
Magnetic phase diagram of a nanocone
Energy Technology Data Exchange (ETDEWEB)
Suarez, O; Vargas, P [Departamento de Fisica, Universidad Tecnica Federico Santa MarIa, P. O. Box 110-V, Valparaiso (Chile); Escrig, J; Landeros, P; Albir, D [Universidad de Santiago de Chile, Depatamento de Fisica, Casilla 307, Correo 2, Santiago (Chile); Laroze, D [Instituto de Fisica, Pontificia Universidad Catolica de Valparaiso, P. O. Box 4059, Valparaiso (Chile)], E-mail: omar.suarez@postgrado.usm.cl
2008-11-01
In this work we analyze the magnetic properties of truncated conical nanoparticles. Based on the continuous magnetic model we find expressions for the total energy in three different magnetic configurations. Finally, we calculate the magnetic phase diagram as function of the geometrical parameters.
Solution space diagram in conflict detection scenarios
Rahman, S.M.A.; Borst, C.; Mulder, M.; Van Paassen, M.M.
2015-01-01
This research investigates the use of Solution Space Diagram (SSD) as a measure of sector complexity and also as a predictor of performance and workload, focusing on the scenarios regarding Air Traffic Controller (ATCO)’s ability to detect future conflicts. A human-in-the-loop experiment with
Phase diagram of an extended Agassi model
García-Ramos, J. E.; Dukelsky, J.; Pérez-Fernández, P.; Arias, J. M.
2018-05-01
Background: The Agassi model [D. Agassi, Nucl. Phys. A 116, 49 (1968), 10.1016/0375-9474(68)90482-X] is an extension of the Lipkin-Meshkov-Glick (LMG) model [H. J. Lipkin, N. Meshkov, and A. J. Glick, Nucl. Phys. 62, 188 (1965), 10.1016/0029-5582(65)90862-X] that incorporates the pairing interaction. It is a schematic model that describes the interplay between particle-hole and pair correlations. It was proposed in the 1960s by D. Agassi as a model to simulate the properties of the quadrupole plus pairing model. Purpose: The aim of this work is to extend a previous study by Davis and Heiss [J. Phys. G: Nucl. Phys. 12, 805 (1986), 10.1088/0305-4616/12/9/006] generalizing the Agassi model and analyze in detail the phase diagram of the model as well as the different regions with coexistence of several phases. Method: We solve the model Hamiltonian through the Hartree-Fock-Bogoliubov (HFB) approximation, introducing two variational parameters that play the role of order parameters. We also compare the HFB calculations with the exact ones. Results: We obtain the phase diagram of the model and classify the order of the different quantum phase transitions appearing in the diagram. The phase diagram presents broad regions where several phases, up to three, coexist. Moreover, there is also a line and a point where four and five phases are degenerated, respectively. Conclusions: The phase diagram of the extended Agassi model presents a rich variety of phases. Phase coexistence is present in extended areas of the parameter space. The model could be an important tool for benchmarking novel many-body approximations.
STUDY TO DETERMINE A NEW MODEL OF THE ISHIKAWA DIAGRAM FOR QUALITY IMPROVEMENT
Directory of Open Access Journals (Sweden)
Liliana LUCA
2017-05-01
Full Text Available The paper presents the results of a study concerning the use of the Ishikawa diagram in analyzing the causes that determine the improvement of the quality of education in a university. All the possible, main and secondary causes that could generate the studied problem were identified. We determined six possible main causes: Man-professor, Man- student, Methods, Materials, Environment for Teaching and Learning, Quality Management. All main causes and secondary causes described a new Ishikawa diagram, a new model with 4 M + 1E + 1Q.
Expanding application of the Wiggers diagram to teach cardiovascular physiology
Wang, Jiun-Jr
2014-01-01
Dr. Carl Wiggers' careful observations have provided a meaningful resource for students to learn how the heart works. Throughout the many years from his initial reports, the Wiggers diagram has been used, in various degrees of complexity, as a fundamental tool for cardiovascular instruction. Often, the various electrical and mechanical plots are the novice learner's first exposure to simulated data. As the various temporal relationships throughout a heartbeat could simply be memorized, the challenge for the cardiovascular instructor is to engage the learner so the underlying mechanisms governing the changing electrical and mechanical events are truly understood. Based on experience, we suggest some additions to the Wiggers diagram that are not commonly used to enhance cardiovascular pedagogy. For example, these additions could be, but are not limited to, introducing the concept of energy waves and their role in influencing pressure and flow in health and disease. Also, integrating concepts of exercise physiology, and the differences in cardiac function and hemodynamics between an elite athlete and normal subject, can have a profound impact on student engagement. In describing the relationship between electrical and mechanical events, the instructor may find the introduction of premature ventricular contractions as a useful tool to further understanding of this important principle. It is our hope that these examples can aid cardiovascular instructors to engage their learners and promote fundamental understanding at the expense of simple memorization. PMID:24913453
Directory of Open Access Journals (Sweden)
Simon Steven R
2002-01-01
Full Text Available Abstract Background Little is known about using the Objective Structured Clinical Examination (OSCE in physical diagnosis courses. The purpose of this study was to describe student performance on an OSCE in a physical diagnosis course. Methods Cross-sectional study at Harvard Medical School, 1997–1999, for 489 second-year students. Results Average total OSCE score was 57% (range 39–75%. Among clinical skills, students scored highest on patient interaction (72%, followed by examination technique (65%, abnormality identification (62%, history-taking (60%, patient presentation (60%, physical examination knowledge (47%, and differential diagnosis (40% (p Conclusions Students scored higher on interpersonal and technical skills than on interpretive or integrative skills. Station scores identified specific content that needs improved teaching.
A Critical Appraisal of the `Day' Diagram
Roberts, A. P.; Tauxe, L.; Heslop, D.
2017-12-01
The `Day' diagram [Day et al., 1977; doi:10.1016/0031-9201(77)90108-X] is used widely to infer the mean domain state of magnetic mineral assemblages. The Day plot coordinates are the ratios of the saturation remanent magnetization to saturation magnetization (Mrs/Ms) and the coercivity of remanence to coercivity (Bcr/Bc), as determined from a major hysteresis loop and a backfield demagnetization curve. Based on theoretical and empirical arguments, Day plots are typically demarcated into stable single domain (SD), `pseudosingle domain' (`PSD'), and multidomain (MD) zones. It is a simple task to determine Mrs/Ms and Bcr/Bc for a sample and to assign a mean domain state based on the boundaries defined by Day et al. [1977]. Many other parameters contribute to variability in a Day diagram, including surface oxidation, mineral stoichiometry, stress state, magnetostatic interactions, and mixtures of magnetic particles with different sizes and shapes. Bulk magnetic measurements usually lack detailed independent evidence to constrain each free parameter, which makes the Day diagram fundamentally ambiguous. This raises questions about its usefulness for diagnosing magnetic particle size variations. The Day diagram is also used to make inferences about binary mixing of magnetic particles, where, for example, mixtures of SD and MD particles give rise to a bulk `PSD' response even though the concentration of `PSD' grains could be zero. In our assessment of thousands of hysteresis measurements of geological samples, binary mixing occurs in a tiny number of cases. Ternary, quaternary, and higher order mixing are usually observed. Also, uniaxial SD and MD end-members are nearly always inappropriate for considering mixing because uniaxial SD particles are virtually non-existent in igneous rocks. Thus, use of mixing lines in Day diagrams routinely provides unsatisfactory representations of particle size variations. We critically appraise the Day diagram and argue that its many
Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming
2016-04-15
This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.
The mean squared writhe of alternating random knot diagrams
Energy Technology Data Exchange (ETDEWEB)
Diao, Y; Hinson, K [Department of Mathematics and Statistics University of North Carolina at Charlotte, NC 28223 (United States); Ernst, C; Ziegler, U, E-mail: ydiao@uncc.ed [Department of Mathematics and Computer Science, Western Kentucky University, Bowling Green, KY 42101 (United States)
2010-12-10
The writhe of a knot diagram is a simple geometric measure of the complexity of the knot diagram. It plays an important role not only in knot theory itself, but also in various applications of knot theory to fields such as molecular biology and polymer physics. The mean squared writhe of any sample of knot diagrams with n crossings is n when for each diagram at each crossing one of the two strands is chosen as the overpass at random with probability one-half. However, such a diagram is usually not minimal. If we restrict ourselves to a minimal knot diagram, then the choice of which strand is the over- or under-strand at each crossing is no longer independent of the neighboring crossings and a larger mean squared writhe is expected for minimal diagrams. This paper explores the effect on the correlation between the mean squared writhe and the diagrams imposed by the condition that diagrams are minimal by studying the writhe of classes of reduced, alternating knot diagrams. We demonstrate that the behavior of the mean squared writhe heavily depends on the underlying space of diagram templates. In particular this is true when the sample space contains only diagrams of a special structure. When the sample space is large enough to contain not only diagrams of a special type, then the mean squared writhe for n crossing diagrams tends to grow linearly with n, but at a faster rate than n, indicating an intrinsic property of alternating knot diagrams. Studying the mean squared writhe of alternating random knot diagrams also provides some insight into the properties of the diagram generating methods used, which is an important area of study in the applications of random knot theory.
ROLE OF UML SEQUENCE DIAGRAM CONSTRUCTS IN OBJECT LIFECYCLE CONCEPT
Directory of Open Access Journals (Sweden)
Miroslav Grgec
2007-06-01
Full Text Available When modeling systems and using UML concepts, a real system can be viewed in several ways. The RUP (Rational Unified Process defines the "4 + 1 view": 1. Logical view (class diagram (CD, object diagram (OD, sequence diagram (SD, collaboration diagram (COD, state chart diagram (SCD, activity diagram (AD, 2.Process view (use case diagram, CD, OD, SD, COD, SCD, AD, 3. Development view (package diagram, component diagram, 4. Physical view (deployment diagram, and 5. Use case view (use case diagram, OD, SD, COD, SCD, AD which combines the four mentioned above. With sequence diagram constructs we are describing object behavior in scope of one use case and their interaction. Each object in system goes through a so called lifecycle (create, supplement object with data, use object, decommission object. The concept of the object lifecycle is used to understand and formalize the behavior of objects from creation to deletion. With help of sequence diagram concepts our paper will describe the way of interaction modeling between objects through lifeline of each of them, and their importance in software development.
Directory of Open Access Journals (Sweden)
Alexandru Maries
2018-03-01
Full Text Available Drawing appropriate diagrams is a useful problem solving heuristic that can transform a problem into a representation that is easier to exploit for solving it. One major focus while helping introductory physics students learn effective problem solving is to help them understand that drawing diagrams can facilitate problem solution. We conducted an investigation in which two different interventions were implemented during recitation quizzes in a large enrollment algebra-based introductory physics course. Students were either (i asked to solve problems in which the diagrams were drawn for them or (ii explicitly told to draw a diagram. A comparison group was not given any instruction regarding diagrams. We developed rubrics to score the problem solving performance of students in different intervention groups and investigated ten problems. We found that students who were provided diagrams never performed better and actually performed worse than the other students on three problems, one involving standing sound waves in a tube (discussed elsewhere and two problems in electricity which we focus on here. These two problems were the only problems in electricity that involved considerations of initial and final conditions, which may partly account for why students provided with diagrams performed significantly worse than students who were not provided with diagrams. In order to explore potential reasons for this finding, we conducted interviews with students and found that some students provided with diagrams may have spent less time on the conceptual analysis and planning stage of the problem solving process. In particular, those provided with the diagram were more likely to jump into the implementation stage of problem solving early without fully analyzing and understanding the problem, which can increase the likelihood of mistakes in solutions.
Maries, Alexandru; Singh, Chandralekha
2018-06-01
Drawing appropriate diagrams is a useful problem solving heuristic that can transform a problem into a representation that is easier to exploit for solving it. One major focus while helping introductory physics students learn effective problem solving is to help them understand that drawing diagrams can facilitate problem solution. We conducted an investigation in which two different interventions were implemented during recitation quizzes in a large enrollment algebra-based introductory physics course. Students were either (i) asked to solve problems in which the diagrams were drawn for them or (ii) explicitly told to draw a diagram. A comparison group was not given any instruction regarding diagrams. We developed rubrics to score the problem solving performance of students in different intervention groups and investigated ten problems. We found that students who were provided diagrams never performed better and actually performed worse than the other students on three problems, one involving standing sound waves in a tube (discussed elsewhere) and two problems in electricity which we focus on here. These two problems were the only problems in electricity that involved considerations of initial and final conditions, which may partly account for why students provided with diagrams performed significantly worse than students who were not provided with diagrams. In order to explore potential reasons for this finding, we conducted interviews with students and found that some students provided with diagrams may have spent less time on the conceptual analysis and planning stage of the problem solving process. In particular, those provided with the diagram were more likely to jump into the implementation stage of problem solving early without fully analyzing and understanding the problem, which can increase the likelihood of mistakes in solutions.
Finding and accessing diagrams in biomedical publications.
Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael
2012-01-01
Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts.
Interactive Cost Configuration Over Decision Diagrams
DEFF Research Database (Denmark)
Andersen, Henrik Reif; Hadzic, Tarik; Pisinger, David
2010-01-01
interaction online. In particular,binary decision diagrams (BDDs) have been successfully used as a compilation target for product and service configuration. In this paper we discuss how to extend BDD-based configuration to scenarios involving cost functions which express user preferences. We first show...... that an efficient, robust and easy to implement extension is possible if the cost function is additive, and feasible solutions are represented using multi-valued decision diagrams (MDDs). We also discuss the effect on MDD size if the cost function is non-additive or if it is encoded explicitly into MDD. We...... then discuss interactive configuration in the presence of multiple cost functions. We prove that even in its simplest form, multiple-cost configuration is NP-hard in the input MDD. However, for solving two-cost configuration we develop a pseudo-polynomial scheme and a fully polynomial approximation scheme...
Phase diagram for interacting Bose gases
International Nuclear Information System (INIS)
Morawetz, K.; Maennel, M.; Schreiber, M.
2007-01-01
We propose a modified form of the inversion method in terms of a self-energy expansion to access the phase diagram of the Bose-Einstein transition. The dependence of the critical temperature on the interaction parameter is calculated. This is discussed with the help of a condition for Bose-Einstein condensation in interacting systems which follows from the pole of the T matrix in the same way as from the divergence of the medium-dependent scattering length. A many-body approximation consisting of screened ladder diagrams is proposed, which describes the Monte Carlo data more appropriately. The specific results are that a non-self-consistent T matrix leads to a linear coefficient in leading order of 4.7, the screened ladder approximation to 2.3, and the self-consistent T matrix due to the effective mass to a coefficient of 1.3 close to the Monte Carlo data
Geometry Helps to Compare Persistence Diagrams
Energy Technology Data Exchange (ETDEWEB)
Kerber, Michael; Morozov, Dmitriy; Nigmetov, Arnur
2015-11-16
Exploiting geometric structure to improve the asymptotic complexity of discrete assignment problems is a well-studied subject. In contrast, the practical advantages of using geometry for such problems have not been explored. We implement geometric variants of the Hopcroft--Karp algorithm for bottleneck matching (based on previous work by Efrat el al.), and of the auction algorithm by Bertsekas for Wasserstein distance computation. Both implementations use k-d trees to replace a linear scan with a geometric proximity query. Our interest in this problem stems from the desire to compute distances between persistence diagrams, a problem that comes up frequently in topological data analysis. We show that our geometric matching algorithms lead to a substantial performance gain, both in running time and in memory consumption, over their purely combinatorial counterparts. Moreover, our implementation significantly outperforms the only other implementation available for comparing persistence diagrams.
The geometry of on-shell diagrams
Franco, Sebastián; Galloni, Daniele; Mariotti, Alberto
2014-08-01
The fundamental role of on-shell diagrams in quantum field theory has been recently recognized. On-shell diagrams, or equivalently bipartite graphs, provide a natural bridge connecting gauge theory to powerful mathematical structures such as the Grassmannian. We perform a detailed investigation of the combinatorial and geometric objects associated to these graphs. We mainly focus on their relation to polytopes and toric geometry, the Grassmannian and its stratification. Our work extends the current understanding of these connections along several important fronts, most notably eliminating restrictions imposed by planarity, positivity, reducibility and edge removability. We illustrate our ideas with several explicit examples and introduce concrete methods that considerably simplify computations. We consider it highly likely that the structures unveiled in this article will arise in the on-shell study of scattering amplitudes beyond the planar limit. Our results can be conversely regarded as an expansion in the understanding of the Grassmannian in terms of bipartite graphs.
A dynamical mechanism for the hairpin diagram
International Nuclear Information System (INIS)
Chang Chaohsi; Guo Xinheng; Li Xueqian.
1989-09-01
Based on the non-valence quark-antiquark and gluon constituent structure of mesons we give a reasonable dynamical mechanism which can induce the hairpin diagram without violating the well-observed OZI rule. We calculate the hairpin amplitudes of D deg. → K-bar deg.η and K-bar deg.η' normalized by D deg. → K-bar deg.π deg. and have found that the hairpin diagram can give rise to substantial contribution to the decays where a meson with a SU(3) flavor singlet component is involved in the final state. In this scenario, we also obtain the branching ratio of D deg. → K-bar deg. φ as 0.55% in comparison with the experimental data of 0.83%. (autor). 33 refs, 3 figs
Samrejrongroj, Phakakrong; Boonsiri, Tanit; Thunyaharn, Sudaluck; Sangarun, Preeyapan
2014-01-01
Currently very few Thai Immunology e-Books are available online. The authors created an online e-Book titled, "Antigen and Antibody Reaction for Diagnosis of Diseases" and used a quasi experimental research design to assess the effectiveness of its implementation in terms of knowledge gained, written exam scores and student satisfaction.…
Worldline Green functions for multiloop diagrams
International Nuclear Information System (INIS)
Schmidt, M.G.; Heidelberg Univ.; Schubert, C.
1994-03-01
We propose a multiloop generalization of the Bern-Kosower formalism, based on Strassler's approach of evaluating worldline path integrals by worldline Green functions. Those Green functions are explicitly constructed for the basic two-loop graph, and for a loop with an arbitrary number of propagator insertions. For scalar and abelian gauge theories, the resulting integral representations allow to combine whole classes of Feynman diagrams into compact expressions. (orig.)
Mixed wasted integrated program: Logic diagram
Energy Technology Data Exchange (ETDEWEB)
Mayberry, J.; Stelle, S. [Science Applications International Corp., Idaho Falls, ID (United States); O`Brien, M. [Univ. of Arizona, Tucson, AZ (United States); Rudin, M. [Univ. of Nevada, Las Vegas, NV (United States); Ferguson, J. [Lockheed Idaho Technologies Co., Idaho Falls, ID (United States); McFee, J. [I.T. Corp., Albuquerque, NM (United States)
1994-11-30
The Mixed Waste Integrated Program Logic Diagram was developed to provide technical alternative for mixed wastes projects for the Office of Technology Development`s Mixed Waste Integrated Program (MWIP). Technical solutions in the areas of characterization, treatment, and disposal were matched to a select number of US Department of Energy (DOE) treatability groups represented by waste streams found in the Mixed Waste Inventory Report (MWIR).
Diagram of the uranium prospection perforation
International Nuclear Information System (INIS)
Perrin, J.
1982-01-01
We call diagrams to the drawn up one continuous of parameters physicists of the formation trimmed by a perforation based on the depth. The method is interesting not only for the putting in evidence of the mineralized levels but also it stops to determine the variations of lithology had by one part to the intrinsic properties of minerals (quartz, clays, carbonates) and to their variation of tenor and by another one, to variations of porosity and permeability of the formation
Simple Lie algebras and Dynkin diagrams
International Nuclear Information System (INIS)
Buccella, F.
1983-01-01
The following theorem is studied: in a simple Lie algebra of rank p there are p positive roots such that all the other n-3p/2 positive roots are linear combinations of them with integer non negative coefficients. Dykin diagrams are built by representing the simple roots with circles and drawing a junction between the roots. Five exceptional algebras are studied, focusing on triple junction algebra, angular momentum algebra, weights of the representation, antisymmetric tensors, and subalgebras
Turbine flow diagram of Paks-1 reactor
International Nuclear Information System (INIS)
Vancso, Tamas
1983-01-01
Computer calculations and programs are presented which inform the operators on the effect projected on the turbine and thermal efficiency of the modification in the flow diagram and in the starting parameters of the power cycle. In the program the expansion line of steam turbine type K-220-44 and the thermo-technical parameters of the elements of the feed-water heater system are determined. Detailed degree calculations for turbine unit of high pressure can be made. (author)
Specialization in i* strategic rationale diagrams
López Cuesta, Lidia; Franch Gutiérrez, Javier; Marco Gómez, Jordi
2012-01-01
ER 2012 Best Student Paper Award The specialization relationship is offered by the i* modeling language through the is-a construct defined over actors (a subactor is-a superactor). Although the overall meaning of this construct is highly intuitive, its semantics when it comes to the fine-grained level of strategic rationale (SR) diagrams is not defined, hampering seriously its appropriate use. In this paper we provide a formal definition of the specialization relationship at the lev...
Refined phase diagram of boron nitride
International Nuclear Information System (INIS)
Solozhenko, V.; Turkevich, V.Z.
1999-01-01
The equilibrium phase diagram of boron nitride thermodynamically calculated by Solozhenko in 1988 has been now refined on the basis of new experimental data on BN melting and extrapolation of heat capacities of BN polymorphs into high-temperature region using the adapted pseudo-Debye model. As compared with the above diagram, the hBN left-reversible cBN equilibrium line is displaced by 60 K toward higher temperatures. The hBN-cBN-L triple point has been calculated to be at 3480 ± 10 K and 5.9 ± 0.1 GPa, while the hBN-L-V triple point is at T = 3400 ± 20 K and p = 400 ± 20 Pa, which indicates that the region of thermodynamic stability of vapor in the BN phase diagram is extremely small. It has been found that the slope of the cBN melting curve is positive whereas the slope of hBN melting curve varies from positive between ambient pressure and 3.4 GPa to negative at higher pressures
The Critical Importance of Russell's Diagram
Gingerich, O.
2013-04-01
The idea of dwarf and giants stars, but not the nomenclature, was first established by Eijnar Hertzsprung in 1905; his first diagrams in support appeared in 1911. In 1913 Henry Norris Russell could demonstrate the effect far more strikingly because he measured the parallaxes of many stars at Cambridge, and could plot absolute magnitude against spectral type for many points. The general concept of dwarf and giant stars was essential in the galactic structure work of Harlow Shapley, Russell's first graduate student. In order to calibrate the period-luminosity relation of Cepheid variables, he was obliged to fall back on statistical parallax using only 11 Cepheids, a very sparse sample. Here the insight provided by the Russell diagram became critical. The presence of yellow K giant stars in globular clusters credentialed his calibration of the period-luminosity relation by showing that the calibrated luminosity of the Cepheids was comparable to the luminosity of the K giants. It is well known that in 1920 Shapley did not believe in the cosmological distances of Heber Curtis' spiral nebulae. It is not so well known that in 1920 Curtis' plot of the period-luminosity relation suggests that he didn't believe it was a physical relation and also he failed to appreciate the significance of the Russell diagram for understanding the large size of the Milky Way.
Asteroseismic Diagram for Subgiants and Red Giants
Energy Technology Data Exchange (ETDEWEB)
Gai, Ning; Tang, Yanke [College of Physics and Electronic information, Dezhou University, Dezhou 253023 (China); Yu, Peng [College of Physics and Electronic Engineering, Chongqing Normal University, Chongqing 401331 (China); Dou, Xianghua, E-mail: ning_gai@163.com, E-mail: tyk450@163.com [Shandong Provincial Key Laboratory of Biophysics, Dezhou University, Dezhou 253023 (China)
2017-02-10
Asteroseismology is a powerful tool for constraining stellar parameters. NASA’s Kepler mission is providing individual eigenfrequencies for a huge number of stars, including thousands of red giants. Besides the frequencies of acoustic modes, an important breakthrough of the Kepler mission is the detection of nonradial gravity-dominated mixed-mode oscillations in red giants. Unlike pure acoustic modes, mixed modes probe deeply into the interior of stars, allowing the stellar core properties and evolution of stars to be derived. In this work, using the gravity-mode period spacing and the large frequency separation, we construct the ΔΠ{sub 1}–Δ ν asteroseismic diagram from models of subgiants and red giants with various masses and metallicities. The relationship ΔΠ{sub 1}–Δ ν is able to constrain the ages and masses of the subgiants. Meanwhile, for red giants with masses above 1.5 M {sub ⊙}, the ΔΠ{sub 1}–Δ ν asteroseismic diagram can also work well to constrain the stellar age and mass. Additionally, we calculate the relative “isochrones” τ , which indicate similar evolution states especially for similar mass stars, on the ΔΠ{sub 1}–Δ ν diagram.
Colour-magnitude diagram of NGC 5053
Energy Technology Data Exchange (ETDEWEB)
Walker, M F; Pike, C D [California Univ., Santa Cruz (USA). Lick Observatory; McGee, J D
1976-06-01
The colour-magnitude diagram of NGC 5053 has been derived to V = 21.1 from photographic and electronographic observations. The electronographic observations were obtained with an experimental Spectracon image-converter, having photocathode and exit window dimensions of 20 x 30 mm, mounted at the prime-focus of the 120-in. Lick reflector. The photographic observations were obtained with the 20-in. Carnegie astrograph and the 36-in. Crossley reflector. The colour-magnitude diagram resembles that of M92, with the difference that a red horizontal branch is more pronounced than the asymptotic branch in NGC 5053. The topology of the horizontal branch is that of clusters with an intermediate metal content and is thus at variance with the mean period of the RR Lyr stars and the unreddened colour of the subgiant branch read at the magnitude level of the horizontal branch, both of which would indicate an extremely low metal content. If comparison of the colour-magnitude diagrams of NGC 5053 and M92 is valid, then the reddening of NGC 5053 is Esub(B-V) = 0.02 and the apparent distance modulus is m-M = 16.08 +- 0.08.
Random matrix models for phase diagrams
International Nuclear Information System (INIS)
Vanderheyden, B; Jackson, A D
2011-01-01
We describe a random matrix approach that can provide generic and readily soluble mean-field descriptions of the phase diagram for a variety of systems ranging from quantum chromodynamics to high-T c materials. Instead of working from specific models, phase diagrams are constructed by averaging over the ensemble of theories that possesses the relevant symmetries of the problem. Although approximate in nature, this approach has a number of advantages. First, it can be useful in distinguishing generic features from model-dependent details. Second, it can help in understanding the 'minimal' number of symmetry constraints required to reproduce specific phase structures. Third, the robustness of predictions can be checked with respect to variations in the detailed description of the interactions. Finally, near critical points, random matrix models bear strong similarities to Ginsburg-Landau theories with the advantage of additional constraints inherited from the symmetries of the underlying interaction. These constraints can be helpful in ruling out certain topologies in the phase diagram. In this Key Issues Review, we illustrate the basic structure of random matrix models, discuss their strengths and weaknesses, and consider the kinds of system to which they can be applied.
On-shell diagrams for N=8 supergravity amplitudes
Energy Technology Data Exchange (ETDEWEB)
Heslop, Paul; Lipstein, Arthur E. [Department of Mathematical Sciences, Durham University,Lower Mountjoy, Stockton Road, Durham, DH1 3LE (United Kingdom)
2016-06-10
We define recursion relations for N=8 supergravity amplitudes using a generalization of the on-shell diagrams developed for planar N=4 super-Yang-Mills. Although the recursion relations generically give rise to non-planar on-shell diagrams, we show that at tree-level the recursion can be chosen to yield only planar diagrams, the same diagrams occurring in the planar N=4 theory. This implies non-trivial identities for non-planar diagrams as well as interesting relations between the N=4 and N=8 theories. We show that the on-shell diagrams of N=8 supergravity obey equivalence relations analogous to those of N=4 super-Yang-Mills, and we develop a systematic algorithm for reading off Grassmannian integral formulae directly from the on-shell diagrams. We also show that the 1-loop 4-point amplitude of N=8 supergravity can be obtained from on-shell diagrams.
Impact of Diagrams on Recalling Sequential Elements in Expository Texts.
Guri-Rozenblit, Sarah
1988-01-01
Examines the instructional effectiveness of abstract diagrams on recall of sequential relations in social science textbooks. Concludes that diagrams assist significantly the recall of sequential relations in a text and decrease significantly the rate of order mistakes. (RS)
Proof test diagrams for Zerodur glass-ceramic
Tucker, D. S.
1991-01-01
Proof test diagrams for Zerodur glass-ceramics are calculated from available fracture mechanics data. It is shown that the environment has a large effect on minimum time-to-failure as predicted by proof test diagrams.
Triangular Diagrams Teach Steady and Dynamic Behaviour of Catalytic Reactions.
Klusacek, K.; And Others
1989-01-01
Illustrates how triangular diagrams can aid in presenting some of the rather complex transient interactions that occur among gas and surface species during heterogeneous catalytic reactions. The basic equations and numerical examples are described. Classroom use of the triangular diagram is discussed. Several diagrams and graphs are provided. (YP)
Atlas of hot isostatic beryllium powder pressing diagrams
International Nuclear Information System (INIS)
Stoev, P.I.; Papirov, I.I.; Tikhinskij, G.F.; Vasil'ev, A.A.
1995-01-01
Diagrams of hot isotopic pressing (HIP) of beryllium powder with different grain size in a wide range of pressing parameters are built by mathematical modeling methods. The HIP diagrams presented are divided into 3 groups: parametric dependencies D=f(P,T); technological HIP diagrams; compacting mechanisms. The created data bank permits to optimise beryllium powder HIP with changing parameters. 4 refs., 23 figs
Safety-barrier diagrams as a safety management tool
DEFF Research Database (Denmark)
Duijm, Nijs Jan
2009-01-01
Safety-barrier diagrams and “bow-tie” diagrams have become popular methods in risk analysis and safety management. This paper describes the syntax and principles for constructing consistent and valid safety-barrier diagrams. The latter's relation to other methods such as fault trees and Bayesian...
Developing Tool Support for Problem Diagrams with CPN and VDM++
DEFF Research Database (Denmark)
Tjell, Simon; Lassen, Kristian Bisgaard
2008-01-01
In this paper, we describe ongoing work on the development of tool support for formal description of domains found in Problem Diagrams. The purpose of the tool is to handle the generation of a CPN model based on a collection of Problem Diagrams. The Problem Diagrams are used for representing the ...
A geometric proof of confluence by decreasing diagrams
Klop, J.W.; Oostrom, V. van; Vrijer, R. de
The criterion for confluence using decreasing diagrams is a generalization of several well-known confluence criteria in abstract rewriting, such as the strong confluence lemma. We give a new proof of the decreasing diagram theorem based on a geometric study of in finite reduction diagrams, arising
The role of perceptual cues in matrix diagrams
van der Meij, Jan; van Amelsvoort, Marije; Anjewierden, A.
An experiment was conducted to assess whether the design of a matrix diagram influences how people study the diagram and whether this has an effect on recall of the presented information. We compared four versions of a matrix diagram on antisocial personality disorder. It consisted of four header
The role of perceptual cues in matrix diagrams
van der Meij, Jan; Amelsvoort, Marije; Anjewierden, Anjo Allert
2015-01-01
An experiment was conducted to assess whether the design of a matrix diagram influences how people study the diagram and whether this has an effect on recall of the presented information. We compared four versions of a matrix diagram on antisocial personality disorder. It consisted of four header
Stage line diagram: an age-conditional reference diagram for tracking development.
van Buuren, Stef; Ooms, Jeroen C L
2009-05-15
This paper presents a method for calculating stage line diagrams, a novel type of reference diagram useful for tracking developmental processes over time. Potential fields of applications include: dentistry (tooth eruption), oncology (tumor grading, cancer staging), virology (HIV infection and disease staging), psychology (stages of cognitive development), human development (pubertal stages) and chronic diseases (stages of dementia). Transition probabilities between successive stages are modeled as smoothly varying functions of age. Age-conditional references are calculated from the modeled probabilities by the mid-P value. It is possible to eliminate the influence of age by calculating standard deviation scores (SDS). The method is applied to the empirical data to produce reference charts on secondary sexual maturation. The mean of the empirical SDS in the reference population is close to zero, whereas the variance depends on age. The stage line diagram provides quick insight into both status (in SDS) and tempo (in SDS/year) of development of an individual child. Other measures (e.g. height SDS, body mass index SDS) from the same child can be added to the chart. Diagrams for sexual maturation are available as a web application at http://vps.stefvanbuuren.nl/puberty. The stage line diagram expresses status and tempo of discrete changes on a continuous scale. Wider application of these measures scores opens up new analytic possibilities. (c) 2009 John Wiley & Sons, Ltd.
Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Richter, Caleb; Cha, Kenny
2018-05-01
Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p > 0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.
Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Richter, Caleb; Cha, Kenny
2018-05-01
Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p > 0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.
Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won
2017-12-12
Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.
Phase diagram of strongly correlated Fermi systems
International Nuclear Information System (INIS)
Zverev, M.V.; Khodel', V.A.; Baldo, M.
2000-01-01
Phase transitions in uniform Fermi systems with repulsive forces between the particles caused by restructuring of quasiparticle filling n(p) are analyzed. It is found that in terms of variables, i.e. density ρ, nondimensional binding constant η, phase diagram of a strongly correlated Fermi system for rather a wide class of interactions reminds of a puff-pastry pie. Its upper part is filled with fermion condensate, the lower one - with normal Fermi-liquid. They are separated by a narrow interlayer - the Lifshits phase, characterized by the Fermi multibound surface [ru
More on boundary holographic Witten diagrams
Sato, Yoshiki
2018-01-01
In this paper we discuss geodesic Witten diagrams in general holographic conformal field theories with boundary or defect. In boundary or defect conformal field theory, two-point functions are nontrivial and can be decomposed into conformal blocks in two distinct ways; ambient channel decomposition and boundary channel decomposition. In our previous work [A. Karch and Y. Sato, J. High Energy Phys. 09 (2017) 121., 10.1007/JHEP09(2017)121] we only consider two-point functions of same operators. We generalize our previous work to a situation where operators in two-point functions are different. We obtain two distinct decomposition for two-point functions of different operators.
Influence Diagrams for Optimal Maintenance Planning
DEFF Research Database (Denmark)
Friis-Hansen, Andreas
2000-01-01
Over the last two decades Bayesian networks and influence diagrams have received notable attention within the field of artificial intelligence and expert systems. During the last few years the technology has been further developed for problem solving within other engineering fields. The objective...... of this study is to present a conceptual bayesian network model for probabilistic prediction of fatigue crack growth in welded steel tubes. It is shown that despite discretization of the variable domain, the prediction is in good agreement with results obtained by the well-established structural reliability...
Topological phase diagram of superconducting carbon nanotubes
Energy Technology Data Exchange (ETDEWEB)
Milz, Lars; Marganska-Lyzniak, Magdalena; Grifoni, Milena [Institut I - Theoretische Physik Universitaet Regensburg (Germany)
2016-07-01
The topological superconducting phase diagram of superconducting carbon nanotubes is discussed. Under the assumption of a short-ranged pairing potential, there are two spin-singlet states: an s-wave and an exotic p + ip-wave that are possible because of the special structure of the honeycomb lattice. The consequences for the possible presence of Majorana edge states in carbon nanotubes are addressed. In particular, regions in the magnetic field-chemical potential plane possibly hosting localized Majorana modes are discussed.
Algorithms for Disconnected Diagrams in Lattice QCD
Energy Technology Data Exchange (ETDEWEB)
Gambhir, Arjun Singh [College of William and Mary, Williamsburg, VA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Stathopoulos, Andreas [College of William and Mary, Williamsburg, VA (United States); Orginos, Konstantinos [College of William and Mary, Williamsburg, VA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Yoon, Boram [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gupta, Rajan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Syritsyn, Sergey [Stony Brook Univ., NY (United States)
2016-11-01
Computing disconnected diagrams in Lattice QCD (operator insertion in a quark loop) entails the computationally demanding problem of taking the trace of the all to all quark propagator. We first outline the basic algorithm used to compute a quark loop as well as improvements to this method. Then, we motivate and introduce an algorithm based on the synergy between hierarchical probing and singular value deflation. We present results for the chiral condensate using a 2+1-flavor clover ensemble and compare estimates of the nucleon charges with the basic algorithm.
International Nuclear Information System (INIS)
Mironov, K.E.
1981-01-01
An area of the Pr-P system, adjoining to the Pr ordinate, is plotted up by the DTA method. Presence of P solid solution in Pr is established. Data on thermal stability of PrP, PrP 2 , PrP 5 and PrP 7 are generalized. The diagram of phase transformations in Pr-P system is plotted up proceeding from the whole complex of the data, presented. A supposition is made on a possible formation of solid solutions between the highest polyphosphide and phosphorus [ru
High temperature phase equilibria and phase diagrams
Kuo, Chu-Kun; Yan, Dong-Sheng
2013-01-01
High temperature phase equilibria studies play an increasingly important role in materials science and engineering. It is especially significant in the research into the properties of the material and the ways in which they can be improved. This is achieved by observing equilibrium and by examining the phase relationships at high temperature. The study of high temperature phase diagrams of nonmetallic systems began in the early 1900s when silica and mineral systems containing silica were focussed upon. Since then technical ceramics emerged and more emphasis has been placed on high temperature
Applications of zero-suppressed decision diagrams
Sasao, Tsutomu
2014-01-01
A zero-suppressed decision diagram (ZDD) is a data structure to represent objects that typically contain many zeros. Applications include combinatorial problems, such as graphs, circuits, faults, and data mining. This book consists of four chapters on the applications of ZDDs. The first chapter by Alan Mishchenko introduces the ZDD. It compares ZDDs to BDDs, showing why a more compact representation is usually achieved in a ZDD. The focus is on sets of subsets and on sum-of-products (SOP) expressions. Methods to generate all the prime implicants (PIs), and to generate irredundant SOPs are show
Influence diagrams for speed profile optimization
Czech Academy of Sciences Publication Activity Database
Kratochvíl, Václav; Vomlel, Jiří
2017-01-01
Roč. 88, č. 1 (2017), s. 567-586 ISSN 0888-613X R&D Projects: GA ČR(CZ) GA16-12010S Institutional support: RVO:67985556 Keywords : Influence diagrams * Optimal control * Vehicle control Subject RIV: JD - Computer Applications, Robotics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.845, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/kratochvil-0476597.pdf
Twistor diagrams and massless Moeller scattering
International Nuclear Information System (INIS)
Hodges, A.P.
1983-01-01
The theory of twistor diagrams, as devised by Penrose, is intended to lead to a manifestly finite account of scattering amplitudes in quantum field theory. The theory is here extended to a more general type of interaction between massless fields than has hitherto been described. It is applied to the example of first-order massless Moeller scattering in quantum electrodynamics. It is shown that earlier studies of this example have failed to render a correct account, in particular by overlooking an infrared divergency, but that the scattering data can nevertheless be represented within the twistor formalism. (author)
Diagram of Saturn V Launch Vehicle
1971-01-01
This is a good cutaway diagram of the Saturn V launch vehicle showing the three stages, the instrument unit, and the Apollo spacecraft. The chart on the right presents the basic technical data in clear detail. The Saturn V is the largest and most powerful launch vehicle in the United States. The towering 363-foot Saturn V was a multistage, multiengine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams. Development of the Saturn V was the responsibility of the Marshall Space Flight Center at Huntsville, Alabama, directed by Dr. Wernher von Braun.
Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-Ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R; Eils, Roland; Grabe, Niels
2017-04-25
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ductal carcinoma in situ (DCIS). Using a machine learning system, we succeeded in classifying the four histological types with 90.9% accuracy. Electron microscopy observations suggested that the activity of typical myoepithelial cells in DCIS was lowered. Through these observations as well as meta-analytic database analyses, we developed a paracrine cross-talk-based biological mechanism of DCIS progressing to invasive cancer. Our observations support novel approaches in clinical computational diagnostics as well as in therapy development against progression.
On the Impact of Layout Quality to Understanding UML Diagrams: Diagram Type and Expertise
DEFF Research Database (Denmark)
Störrle, Harald
2012-01-01
Practical experience suggests that the use and understanding of UML diagrams is greatly affected by the quality of their layout. In previous work, we have presented evidence supporting this intuition. This contrasts with earlier experiments that yielded weak or inconclusive evidence only. In the ......Practical experience suggests that the use and understanding of UML diagrams is greatly affected by the quality of their layout. In previous work, we have presented evidence supporting this intuition. This contrasts with earlier experiments that yielded weak or inconclusive evidence only...
On the question of calculation methods of phase diagrams
International Nuclear Information System (INIS)
Vasil'ev, M.V.
1983-01-01
The technique of determining interaction parameters of components of binary alloys is suggested. U-Mo and Cu-Al systems are used as example with the aid of experimental state diagrams. It is shown that the search for new regularities is necessary with the aim of analytical description of state diagrams and forecast of the shape of phase equilibria curves in real systems. Optimum combinations of experimental investigations with the aim of reliable determination of supporting points and forecasting possibilities of typical equations can considerably decrease the volume of experimental work when preparing state diagrams, in cases of repeated state diagrams of more reliable state diagrams with the application of more advanced methods of investigation. The translation of state diagrams from geometric to analytical language with the use of typical equations opens up new possibilities for establishing a compact information bank for state diagrams
Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R.; Eils, Roland; Grabe, Niels
2017-01-01
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade du...
Guo, Le-Hang; Wang, Dan; Qian, Yi-Yi; Zheng, Xiao; Zhao, Chong-Ke; Li, Xiao-Long; Bo, Xiao-Wan; Yue, Wen-Wen; Zhang, Qi; Shi, Jun; Xu, Hui-Xiong
2018-04-04
With the fast development of artificial intelligence techniques, we proposed a novel two-stage multi-view learning framework for the contrast-enhanced ultrasound (CEUS) based computer-aided diagnosis for liver tumors, which adopted only three typical CEUS images selected from the arterial phase, portal venous phase and late phase. In the first stage, the deep canonical correlation analysis (DCCA) was performed on three image pairs between the arterial and portal venous phases, arterial and delayed phases, and portal venous and delayed phases respectively, which then generated total six-view features. While in the second stage, these multi-view features were then fed to a multiple kernel learning (MKL) based classifier to further promote the diagnosis result. Two MKL classification algorithms were evaluated in this MKL-based classification framework. We evaluated proposed DCCA-MKL framework on 93 lesions (47 malignant cancers vs. 46 benign tumors). The proposed DCCA-MKL framework achieved the mean classification accuracy, sensitivity, specificity, Youden index, false positive rate, and false negative rate of 90.41 ± 5.80%, 93.56 ± 5.90%, 86.89 ± 9.38%, 79.44 ± 11.83%, 13.11 ± 9.38% and 6.44 ± 5.90%, respectively, by soft margin MKL classifier. The experimental results indicate that the proposed DCCA-MKL framework achieves best performance for discriminating benign liver tumors from malignant liver cancers. Moreover, it is also proved that the three-phase CEUS image based CAD is feasible for liver tumors with the proposed DCCA-MKL framework.
Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing
2018-02-01
Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.
Krinzinger, Helga
2016-09-01
Studies in children with AD(H)D without mathematical learning disability (MLD) as well as studies on the effects of methylphenidate on arithmetic have shown that most deficits in mathematics and most error types commonly described as specific to developmental dyscalculia (e. g., finger-counting, fact-retrieval deficit, complex counting, difficulties with carry/borrow procedures, self-corrections) cannot be classified as such and should thus not be used for the differential diagnosis of primary dyscalculia and secondary MLD. This article proposes using the overall score in the dyscalculia test Basis-Math 4-8 (Moser Opitz et al., 2010) as well as implausible subtraction errors as a marker for dyscalculia and the number of self-corrections made during the test as a cognitive marker for attention deficits. Hierarchical cluster analyses were calculated in a sample of 51 clinically referred children with normal IQ and suspicion of MLD, using IQ, years of schooling, overall score of the Basis-Math 4–8 and number of self-corrections in this test as variables. The results revealed a subgroup with primary dyscalculia as well as three subgroups with secondary MLD (two with attention deficit hyperactivity disorder, one with depression and one small subgroup with high IQ). In conclusion, the Basis-Math 4–8 (Moser Opitz et al., 2010) can offer substantial information for the differential diagnosis of dyscalculia and secondary deficits in mathematics due to attention problems and enable optimization of treatment decisions for the different groups.
Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min
2017-06-02
Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.
Billett, Stephen
2000-01-01
Guided learning (questioning, diagrams/analogies, modeling, coaching) was studied through critical incident interviews in five workplaces. Participation in everyday work activities was the most effective contributor to workplace learning. Organizational readiness and the efficacy of guided learning in resolving novel tasks were also important. (SK)
STUDY TO DETERMINE A NEW MODEL OF THE ISHIKAWA DIAGRAM FOR QUALITY IMPROVEMENT
Liliana LUCA; Minodora PASARE; Alin STANCIOIU
2017-01-01
The paper presents the results of a study concerning the use of the Ishikawa diagram in analyzing the causes that determine the improvement of the quality of education in a university. All the possible, main and secondary causes that could generate the studied problem were identified. We determined six possible main causes: Man-professor, Man- student, Methods, Materials, Environment for Teaching and Learning, Quality Management. All main causes and secondary causes described a ne...
Critical point analysis of phase envelope diagram
Energy Technology Data Exchange (ETDEWEB)
Soetikno, Darmadi; Siagian, Ucok W. R. [Department of Petroleum Engineering, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132 (Indonesia); Kusdiantara, Rudy, E-mail: rkusdiantara@s.itb.ac.id; Puspita, Dila, E-mail: rkusdiantara@s.itb.ac.id; Sidarto, Kuntjoro A., E-mail: rkusdiantara@s.itb.ac.id; Soewono, Edy; Gunawan, Agus Y. [Department of Mathematics, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132 (Indonesia)
2014-03-24
Phase diagram or phase envelope is a relation between temperature and pressure that shows the condition of equilibria between the different phases of chemical compounds, mixture of compounds, and solutions. Phase diagram is an important issue in chemical thermodynamics and hydrocarbon reservoir. It is very useful for process simulation, hydrocarbon reactor design, and petroleum engineering studies. It is constructed from the bubble line, dew line, and critical point. Bubble line and dew line are composed of bubble points and dew points, respectively. Bubble point is the first point at which the gas is formed when a liquid is heated. Meanwhile, dew point is the first point where the liquid is formed when the gas is cooled. Critical point is the point where all of the properties of gases and liquids are equal, such as temperature, pressure, amount of substance, and others. Critical point is very useful in fuel processing and dissolution of certain chemicals. Here in this paper, we will show the critical point analytically. Then, it will be compared with numerical calculations of Peng-Robinson equation by using Newton-Raphson method. As case studies, several hydrocarbon mixtures are simulated using by Matlab.
Critical point analysis of phase envelope diagram
International Nuclear Information System (INIS)
Soetikno, Darmadi; Siagian, Ucok W. R.; Kusdiantara, Rudy; Puspita, Dila; Sidarto, Kuntjoro A.; Soewono, Edy; Gunawan, Agus Y.
2014-01-01
Phase diagram or phase envelope is a relation between temperature and pressure that shows the condition of equilibria between the different phases of chemical compounds, mixture of compounds, and solutions. Phase diagram is an important issue in chemical thermodynamics and hydrocarbon reservoir. It is very useful for process simulation, hydrocarbon reactor design, and petroleum engineering studies. It is constructed from the bubble line, dew line, and critical point. Bubble line and dew line are composed of bubble points and dew points, respectively. Bubble point is the first point at which the gas is formed when a liquid is heated. Meanwhile, dew point is the first point where the liquid is formed when the gas is cooled. Critical point is the point where all of the properties of gases and liquids are equal, such as temperature, pressure, amount of substance, and others. Critical point is very useful in fuel processing and dissolution of certain chemicals. Here in this paper, we will show the critical point analytically. Then, it will be compared with numerical calculations of Peng-Robinson equation by using Newton-Raphson method. As case studies, several hydrocarbon mixtures are simulated using by Matlab
Using influence diagrams for data worth analysis
International Nuclear Information System (INIS)
Sharif Heger, A.; White, Janis E.
1997-01-01
Decision-making under uncertainty describes most environmental remediation and waste management problems. Inherent limitations in knowledge concerning contaminants, environmental fate and transport, remedies, and risks force decision-makers to select a course of action based on uncertain and incomplete information. Because uncertainties can be reduced by collecting additional data., uncertainty and sensitivity analysis techniques have received considerable attention. When costs associated with reducing uncertainty are considered in a decision problem, the objective changes; rather than determine what data to collect to reduce overall uncertainty, the goal is to determine what data to collect to best differentiate between possible courses of action or decision alternatives. Environmental restoration and waste management requires cost-effective methods for characterization and monitoring, and these methods must also satisfy regulatory requirements. Characterization and monitoring activities imply that, sooner or later, a decision must be made about collecting new field data. Limited fiscal resources for data collection should be committed only to those data that have the most impact on the decision at lowest possible cost. Applying influence diagrams in combination with data worth analysis produces a method which not only satisfies these requirements but also gives rise to an intuitive representation of complex structures not possible in the more traditional decision tree representation. This paper demonstrates the use of influence diagrams in data worth analysis by applying to a monitor-and-treat problem often encountered in environmental decision problems
Phase Diagram of Spiking Neural Networks
Directory of Open Access Journals (Sweden)
Hamed eSeyed-Allaei
2015-03-01
Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.
Magnetic phase diagrams of UNiGe
International Nuclear Information System (INIS)
Nakotte, H.; Hagmusa, I.H.; Klaasse, J.C.P.; Hagmusa, I.H.; Klaasse, J.C.P.
1997-01-01
UNiGe undergoes two magnetic transitions in zero field. Here, the magnetic diagrams of UNiGe for B parallel b and B parallel c are reported. We performed temperatures scans of the magnetization in static magnetic fields up to 19.5T applied along the b and c axes. For both orientations 3 magnetic phases have been identified in the B-T diagrams. We confirmed the previously reported phase boundaries for B parallel c, and in addition we determined the location of the phase boundaries for B parallel b. We discuss a possible relationship of the two zero-field antiferromagnetic phases (commensurate: T<42K; incommensurate: 42K< T<50K) and the field-induced phase, which, at low temperatures, occurs between 18 and 25T or 4 and 10T for B parallel b or B parallel c, respectively. Finally, we discuss the field dependence of the electronic contribution γ to the specific heat for B parallel c up to 17.5T, and we find that its field dependence is similar to the one found in more itinerant uranium compounds
VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R.
Chen, Hanbo; Boutros, Paul C
2011-01-26
Visualization of orthogonal (disjoint) or overlapping datasets is a common task in bioinformatics. Few tools exist to automate the generation of extensively-customizable, high-resolution Venn and Euler diagrams in the R statistical environment. To fill this gap we introduce VennDiagram, an R package that enables the automated generation of highly-customizable, high-resolution Venn diagrams with up to four sets and Euler diagrams with up to three sets. The VennDiagram package offers the user the ability to customize essentially all aspects of the generated diagrams, including font sizes, label styles and locations, and the overall rotation of the diagram. We have implemented scaled Venn and Euler diagrams, which increase graphical accuracy and visual appeal. Diagrams are generated as high-definition TIFF files, simplifying the process of creating publication-quality figures and easing integration with established analysis pipelines. The VennDiagram package allows the creation of high quality Venn and Euler diagrams in the R statistical environment.
VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R
Directory of Open Access Journals (Sweden)
Boutros Paul C
2011-01-01
Full Text Available Abstract Background Visualization of orthogonal (disjoint or overlapping datasets is a common task in bioinformatics. Few tools exist to automate the generation of extensively-customizable, high-resolution Venn and Euler diagrams in the R statistical environment. To fill this gap we introduce VennDiagram, an R package that enables the automated generation of highly-customizable, high-resolution Venn diagrams with up to four sets and Euler diagrams with up to three sets. Results The VennDiagram package offers the user the ability to customize essentially all aspects of the generated diagrams, including font sizes, label styles and locations, and the overall rotation of the diagram. We have implemented scaled Venn and Euler diagrams, which increase graphical accuracy and visual appeal. Diagrams are generated as high-definition TIFF files, simplifying the process of creating publication-quality figures and easing integration with established analysis pipelines. Conclusions The VennDiagram package allows the creation of high quality Venn and Euler diagrams in the R statistical environment.
Ataer-Cansizoglu, E; Kalpathy-Cramer, J; You, S; Keck, K; Erdogmus, D; Chiang, M F
2015-01-01
Inter-expert variability in image-based clinical diagnosis has been demonstrated in many diseases including retinopathy of prematurity (ROP), which is a disease affecting low birth weight infants and is a major cause of childhood blindness. In order to better understand the underlying causes of variability among experts, we propose a method to quantify the variability of expert decisions and analyze the relationship between expert diagnoses and features computed from the images. Identification of these features is relevant for development of computer-based decision support systems and educational systems in ROP, and these methods may be applicable to other diseases where inter-expert variability is observed. The experiments were carried out on a dataset of 34 retinal images, each with diagnoses provided independently by 22 experts. Analysis was performed using concepts of Mutual Information (MI) and Kernel Density Estimation. A large set of structural features (a total of 66) were extracted from retinal images. Feature selection was utilized to identify the most important features that correlated to actual clinical decisions by the 22 study experts. The best three features for each observer were selected by an exhaustive search on all possible feature subsets and considering joint MI as a relevance criterion. We also compared our results with the results of Cohen's Kappa [36] as an inter-rater reliability measure. The results demonstrate that a group of observers (17 among 22) decide consistently with each other. Mean and second central moment of arteriolar tortuosity is among the reasons of disagreement between this group and the rest of the observers, meaning that the group of experts consider amount of tortuosity as well as the variation of tortuosity in the image. Given a set of image-based features, the proposed analysis method can identify critical image-based features that lead to expert agreement and disagreement in diagnosis of ROP. Although tree
Kose, Kivanc; Bozkurt, Alican; Ariafar, Setareh; Alessi-Fox, Christi A.; Gill, Melissa; Dy, Jennifer G.; Brooks, Dana H.; Rajadhyaksha, Milind
2017-02-01
In this study we present a deep learning based classification algorithm for discriminating morphological patterns that appear in RCM mosaics of melanocytic lesions collected at the dermal epidermal junction (DEJ). These patterns are classified into 6 distinct types in the literature: background, meshwork, ring, clod, mixed, and aspecific. Clinicians typically identify these morphological patterns by examination of their textural appearance at 10X magnification. To mimic this process we divided mosaics into smaller regions, which we call tiles, and classify each tile in a deep learning framework. We used previously acquired DEJ mosaics of lesions deemed clinically suspicious, from 20 different patients, which were then labelled according to those 6 types by 2 expert users. We tried three different approaches for classification, all starting with a publicly available convolutional neural network (CNN) trained on natural image, consisting of a series of convolutional layers followed by a series of fully connected layers: (1) We fine-tuned this network using training data from the dataset. (2) Instead, we added an additional fully connected layer before the output layer network and then re-trained only last two layers, (3) We used only the CNN convolutional layers as a feature extractor, encoded the features using a bag of words model, and trained a support vector machine (SVM) classifier. Sensitivity and specificity were generally comparable across the three methods, and in the same ranges as our previous work using SURF features with SVM . Approach (3) was less computationally intensive to train but more sensitive to unbalanced representation of the 6 classes in the training data. However we expect CNN performance to improve as we add more training data because both the features and the classifier are learned jointly from the data. *First two authors share first authorship.
Diagrams: A Visual Survey of Graphs, Maps, Charts and Diagrams for the Graphic Designer.
Lockwood, Arthur
Since the ultimate success of any diagram rests in its clarity, it is important that the designer select a method of presentation which will achieve this aim. He should be aware of the various ways in which statistics can be shown diagrammatically, how information can be incorporated in maps, and how events can be plotted in chart or graph form.…
The Diagram as Story: Unfolding the Event-Structure of the Mathematical Diagram
de Freitas, Elizabeth
2012-01-01
This paper explores the role of narrative in decoding diagrams. I focus on two fundamental facets of narrative: (1) the recounting of causally related sequences of events, and (2) the positioning of the narrator through point-of-view and voice. In the first two sections of the paper I discuss philosophical and semiotic frameworks for making sense…
Directory of Open Access Journals (Sweden)
José de Alencar Simoni
2007-04-01
Full Text Available The main subject of this article is to show the parallelism betwen the Ellingham and Van't Hoff diagrams. The first one is a graphic representation of the changes in the standard Gibbs free energy (deltarGtheta as a function of T and was introduced by Ellingham in 1944, in order to study metallurgic processes involving oxides and sulphides. On the other hand, the Van't Hoff diagram is a representation of the function ln K versus (1/T. The equivalence between both diagrams is easily demonstrated, making simple mathematical manipulations. In order to show the parallelism between both diagrams, they are presented briefly and two examples are discussed. The comparison of the both diagrams surely will be helpful to students and teachers in their learning and teaching activities, and will certainly enrich important aspects of chemical thermodynamics.
Energy level diagrams for black hole orbits
Levin, Janna
2009-12-01
A spinning black hole with a much smaller black hole companion forms a fundamental gravitational system, like a colossal classical analog to an atom. In an appealing if imperfect analogy with atomic physics, this gravitational atom can be understood through a discrete spectrum of periodic orbits. Exploiting a correspondence between the set of periodic orbits and the set of rational numbers, we are able to construct periodic tables of orbits and energy level diagrams of the accessible states around black holes. We also present a closed-form expression for the rational q, thereby quantifying zoom-whirl behavior in terms of spin, energy and angular momentum. The black hole atom is not just a theoretical construct, but corresponds to extant astrophysical systems detectable by future gravitational wave observatories.
Energy level diagrams for black hole orbits
International Nuclear Information System (INIS)
Levin, Janna
2009-01-01
A spinning black hole with a much smaller black hole companion forms a fundamental gravitational system, like a colossal classical analog to an atom. In an appealing if imperfect analogy with atomic physics, this gravitational atom can be understood through a discrete spectrum of periodic orbits. Exploiting a correspondence between the set of periodic orbits and the set of rational numbers, we are able to construct periodic tables of orbits and energy level diagrams of the accessible states around black holes. We also present a closed-form expression for the rational q, thereby quantifying zoom-whirl behavior in terms of spin, energy and angular momentum. The black hole atom is not just a theoretical construct, but corresponds to extant astrophysical systems detectable by future gravitational wave observatories.
Database design using entity-relationship diagrams
Bagui, Sikha
2011-01-01
Data, Databases, and the Software Engineering ProcessDataBuilding a DatabaseWhat is the Software Engineering Process?Entity Relationship Diagrams and the Software Engineering Life Cycle Phase 1: Get the Requirements for the Database Phase 2: Specify the Database Phase 3: Design the DatabaseData and Data ModelsFiles, Records, and Data ItemsMoving from 3 × 5 Cards to ComputersDatabase Models The Hierarchical ModelThe Network ModelThe Relational ModelThe Relational Model and Functional DependenciesFundamental Relational DatabaseRelational Database and SetsFunctional
Visualizing Mortality Dynamics in the Lexis Diagram
DEFF Research Database (Denmark)
Rau, Roland; Bohk-Ewald, Christina; Muszynska, Magdalena M
This book visualizes mortality dynamics in the Lexis diagram. While the standard approach of plotting death rates is also covered, the focus in this book is on the depiction of rates of mortality improvement over age and time. This rather novel approach offers a more intuitive understanding...... of the underlying dynamics, enabling readers to better understand whether period- or cohort-effects were instrumental for the development of mortality in a particular country. Besides maps for single countries, the book includes maps on the dynamics of selected causes of death in the United States...... Software to produce these types of surface maps. Readers are encouraged to use the presented tools to visualize other demographic data or any event that can be measured by age and calendar time, allowing them to adapt the methods to their respective research interests. The intended audience is anyone who...
Calculation of superalloy phase diagrams. IV
International Nuclear Information System (INIS)
Kaufman, L.; Nesor, H.
1975-01-01
Explicit descriptions of the Fe--Mo, Fe--W, Fe--Nb, W--Cr and Ti--W binary systems have been developed in line with lattice stability, thermochemical and phase diagram data. These descriptions, along with similar results derived previously, have been employed to calculate isothermal sections in the Cr--Al--Fe, Fe--Mo--Cr, Fe--W--Cr, Ni--Al--Co, Nb--Ti--W, Ti--W--Mo, Cr--W--Mo, Ni--Mo--W, and Ni--W--Ti systems for comparison with experimental results. The effects of carbon impurities on miscibility gap formation in the Ti--W, Nb--Ti--W, Ti--W--Mo and Cr--W--Mo systems are discussed
Logic verification system for power plant sequence diagrams
International Nuclear Information System (INIS)
Fukuda, Mitsuko; Yamada, Naoyuki; Teshima, Toshiaki; Kan, Ken-ichi; Utsunomiya, Mitsugu.
1994-01-01
A logic verification system for sequence diagrams of power plants has been developed. The system's main function is to verify correctness of the logic realized by sequence diagrams for power plant control systems. The verification is based on a symbolic comparison of the logic of the sequence diagrams with the logic of the corresponding IBDs (interlock Block Diagrams) in combination with reference to design knowledge. The developed system points out the sub-circuit which is responsible for any existing mismatches between the IBD logic and the logic realized by the sequence diagrams. Applications to the verification of actual sequence diagrams of power plants confirmed that the developed system is practical and effective. (author)
Graphical matching rules for cardinality based service feature diagrams
Directory of Open Access Journals (Sweden)
Faiza Kanwal
2017-03-01
Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.
Oak Ridge National Laboratory Technology Logic Diagram
International Nuclear Information System (INIS)
1993-09-01
The Oak Ridge National Laboratory Technology Logic Diagram (TLD) was developed to provide a decision support tool that relates environmental restoration (ER) and waste management (WM) problems at Oak Ridge National Laboratory (ORNL) to potential technologies that can remediate these problems. The TLD identifies the research, development, demonstration testing, and evaluation needed to develop these technologies to a state that allows technology transfer and application to decontamination and decommissioning (D ampersand D), remedial action (RA), and WM activities. The TLD consists of three fundamentally separate volumes: Vol. 1, Technology Evaluation; Vol. 2, Technology Logic Diagram and Vol. 3, Technology EvaLuation Data Sheets. Part A of Vols. 1 and 2 focuses on RA. Part B of Vols. 1 and 2 focuses on the D ampersand D of contaminated facilities. Part C of Vols. 1 and 2 focuses on WM. Each part of Vol. 1 contains an overview of the TM, an explanation of the problems facing the volume-specific program, a review of identified technologies, and rankings of technologies applicable to the site. Volume 2 (Pts. A. B. and C) contains the logic linkages among EM goals, environmental problems, and the various technologies that have the potential to solve these problems. Volume 3 (Pts. A. B, and C) contains the TLD data sheets. This volume provides the technology evaluation data sheets (TEDS) for ER/WM activities (D ampersand D, RA and WM) that are referenced by a TEDS code number in Vol. 2 of the TLD. Each of these sheets represents a single logic trace across the TLD. These sheets contain more detail than is given for the technologies in Vol. 2
Leak before break piping evaluation diagram
International Nuclear Information System (INIS)
Fabi, R.J.; Peck, D.A.
1994-01-01
Traditionally Leak Before Break (LBB) has been applied to the evaluation of piping in existing nuclear plants. This paper presents a simple method for evaluating piping systems for LBB during the design process. This method produces a piping evaluation diagram (PED) which defines the LBB requirements to the piping designer for use during the design process. Several sets of LBB analyses are performed for each different pipe size and material considered in the LBB application. The results of this method are independent of the actual pipe routing. Two complete LBB evaluations are performed to determine the maximum allowable stability load, one evaluation for a low normal operating load, and the other evaluation for a high normal operating load. These normal operating loads span the typical loads for the particular system being evaluated. In developing the allowable loads, the appropriate LBB margins are included in the PED preparation. The resulting LBB solutions are plotted as a set of allowable curves for the maximum design basis load, such is the seismic load versus the normal operating load. Since the required margins are already accounted for in the LBB PED, the piping designer can use the diagram directly with the results of the piping analysis and determine immediately if the current piping arrangement passes LBB. Since the LBB PED is independent of pipe routing, changes to the piping system can be evaluated using the existing PED. For a particular application, all that remains is to confirm that the actual materials and pipe sizes assumed in creating the particular design are built into the plant
Oak Ridge National Laboratory Technology Logic Diagram
International Nuclear Information System (INIS)
1993-09-01
The Oak Ridge National Laboratory Technology Logic Diagram (TLD) was developed to provide a decision-support tool that relates environmental restoration (ER) and waste management (WM) problems at Oak Ridge National Laboratory (ORNL) to potential technologies that can remediate these problems. The TLD identifies the research, development, demonstration, testing, and evaluation needed to develop these technologies to a state that allows technology transfer and application to decontamination and decommissioning (D ampersand D), remedial action (RA), and WM activities. The TLD consists of three fundamentally separate volumes: Vol. 1 (Technology Evaluation), Vol. 2 (Technology Logic Diagram), and Vol. 3 (Technology Evaluation Data Sheets). Part A of Vols. 1 and 2 focuses on D ampersand D. Part B of Vols. 1 and 2 focuses on RA of contaminated facilities. Part C of Vols. 1 and 2 focuses on WM. Each part of Vol. 1 contains an overview of the TLD, an explanation of the program-specific responsibilities, a review of identified technologies, and the ranking os remedial technologies. Volume 2 (Pts. A, B, and C) contains the logic linkages among EM goals, environmental problems, and the various technologies that have the potential to solve these problems. Volume 3 (Pts. A, B, and C) contains the TLD data sheets. The focus of Vol. 1, Pt. B, is RA, and it has been divided into six chapters. The first chapter is an introduction, which defines problems specific to the ER Program for ORNL. Chapter 2 provides a general overview of the TLD. Chapters 3 through 5 are organized into necessary subelement categories: RA, characterization, and robotics and automation. The final chapter contains regulatory compliance information concerning RA
Common phase diagram for low-dimensional superconductors
International Nuclear Information System (INIS)
Michalak, Rudi
2003-01-01
A phenomenological phase diagram which has been derived for high-temperature superconductors from NMR Knight-shift measurements of the pseudogap is compared to the phase diagram that is obtained for organic superconductors and spin-ladder superconductors, both low-dimensional systems. This is contrasted to the phase diagram of some Heavy Fermion superconductors, i.e. superconductors not constrained to a low dimensionality
Updating the Nomographical Diagrams for Dimensioning the Beams
Pop Maria T.
2015-01-01
In order to reduce the time period needed for structures design it is strongly recommended to use nomographical diagrams. The base for formation and updating the nomographical diagrams, stands on the charts presented by different technical publications. The updated charts use the same algorithm and calculation elements as the former diagrams in accordance to the latest prescriptions and European standards. The result consists in a chart, having the same properties, similar with the nomogragra...
XLOOPS - a package calculating one- and two-loop diagrams
International Nuclear Information System (INIS)
Bruecher, L.
1997-01-01
A program package for calculating massive one- and two-loop diagrams is introduced. It consists of five parts: - a graphical user interface, - routines for generating diagrams from particle input, - procedures for calculating one-loop integrals both analytically and numerically, - routines for massive two-loop integrals, - programs for numerical integration of two-loop diagrams. Here the graphical user interface and the text interface to Maple are presented. (orig.)
Satake diagrams of affine Kac-Moody algebras
Energy Technology Data Exchange (ETDEWEB)
Tripathy, L K [S B R Government Womens' College, Berhampur, Orissa 760 001 (India); Pati, K C [Department of Physics, Khallikote College, Berhampur, Orissa 760 001 (India)
2006-02-10
Satake diagrams of affine Kac-Moody algebras (untwisted and twisted) are obtained from their Dynkin diagrams. These diagrams give a classification of restricted root systems associated with these algebras. In the case of simple Lie algebras, these root systems and Satake diagrams correspond to symmetric spaces which have recently found many physical applications in quantum integrable systems, quantum transport problems, random matrix theories etc. We hope these types of root systems may have similar applications in theoretical physics in future and may correspond to symmetric spaces analogue of affine Kac-Moody algebras if they exist.
Fernandez-San Jose, Patricia; Liu, Yichuan; March, Michael; Pellegrino, Renata; Golhar, Ryan; Corton, Marta; Blanco-Kelly, Fiona; López-Molina, Maria Isabel; García-Sandoval, Blanca; Guo, Yiran; Tian, Lifeng; Liu, Xuanzhu; Guan, Liping; Zhang, Jianguo; Keating, Brendan; Xu, Xun
2015-01-01
This study aimed to identify the genetics underlying dominant forms of inherited retinal dystrophies using whole exome sequencing (WES) in six families extensively screened for known mutations or genes. Thirty-eight individuals were subjected to WES. Causative variants were searched among single nucleotide variants (SNVs) and insertion/deletion variants (indels) and whenever no potential candidate emerged, copy number variant (CNV) analysis was performed. Variants or regions harboring a candidate variant were prioritized and segregation of the variant with the disease was further assessed using Sanger sequencing in case of SNVs and indels, and quantitative PCR (qPCR) for CNVs. SNV and indel analysis led to the identification of a previously reported mutation in PRPH2. Two additional mutations linked to different forms of retinal dystrophies were identified in two families: a known frameshift deletion in RPGR, a gene responsible for X-linked retinitis pigmentosa and p.Ser163Arg in C1QTNF5 associated with Late-Onset Retinal Degeneration. A novel heterozygous deletion spanning the entire region of PRPF31 was also identified in the affected members of a fourth family, which was confirmed with qPCR. This study allowed the identification of the genetic cause of the retinal dystrophy and the establishment of a correct diagnosis in four families, including a large heterozygous deletion in PRPF31, typically considered one of the pitfalls of this method. Since all findings in this study are restricted to known genes, we propose that targeted sequencing using gene-panel is an optimal first approach for the genetic screening and that once known genetic causes are ruled out, WES might be used to uncover new genes involved in inherited retinal dystrophies. PMID:26197217
Venkatesh, Santosh S; Levenback, Benjamin J; Sultan, Laith R; Bouzghar, Ghizlane; Sehgal, Chandra M
2015-12-01
The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two independent feature sets consisting of visual features based on a radiologist's interpretation of images and computer-extracted features when used as first and second readers and combined by adaptive boosting (AdaBoost) and a pruning classifier resulted in a very high level of diagnostic performance (area under the receiver operating characteristic curve = 0.98) at a cost of pruning a fraction (20%) of the cases for further evaluation by independent methods. AdaBoost also improved the diagnostic performance of the individual human observers and increased the agreement between their analyses. Pairing AdaBoost with selective pruning is a principled methodology for achieving high diagnostic performance without the added cost of an additional reader for differentiating solid breast masses by ultrasound. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
Oak Ridge K-25 Site Technology Logic Diagram. Volume 2, Technology Logic Diagrams
Energy Technology Data Exchange (ETDEWEB)
Fellows, R.L. [ed.
1993-02-26
The Oak Ridge K-25 Technology Logic Diagram (TLD), a decision support tool for the K-25 Site, was developed to provide a planning document that relates envirorunental restoration and waste management problems at the Oak Ridge K-25 Site to potential technologies that can remediate these problems. The TLD technique identifies the research necessary to develop these technologies to a state that allows for technology transfer and application to waste management, remedial action, and decontamination and decommissioning activities. The TLD consists of four separate volumes-Vol. 1, Vol. 2, Vol. 3A, and Vol. 3B. Volume 1 provides introductory and overview information about the TLD. This volume, Volume 2, contains logic diagrams with an index. Volume 3 has been divided into two separate volumes to facilitate handling and use.
Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian
2014-06-27
Pulmonary acoustic parameters extracted from recorded respiratory sounds provide valuable information for the detection of respiratory pathologies. The automated analysis of pulmonary acoustic signals can serve as a differential diagnosis tool for medical professionals, a learning tool for medical students, and a self-management tool for patients. In this context, we intend to evaluate and compare the performance of the support vector machine (SVM) and K-nearest neighbour (K-nn) classifiers in diagnosis respiratory pathologies using respiratory sounds from R.A.L.E database. The pulmonary acoustic signals used in this study were obtained from the R.A.L.E lung sound database. The pulmonary acoustic signals were manually categorised into three different groups, namely normal, airway obstruction pathology, and parenchymal pathology. The mel-frequency cepstral coefficient (MFCC) features were extracted from the pre-processed pulmonary acoustic signals. The MFCC features were analysed by one-way ANOVA and then fed separately into the SVM and K-nn classifiers. The performances of the classifiers were analysed using the confusion matrix technique. The statistical analysis of the MFCC features using one-way ANOVA showed that the extracted MFCC features are significantly different (p < 0.001). The classification accuracies of the SVM and K-nn classifiers were found to be 92.19% and 98.26%, respectively. Although the data used to train and test the classifiers are limited, the classification accuracies found are satisfactory. The K-nn classifier was better than the SVM classifier for the discrimination of pulmonary acoustic signals from pathological and normal subjects obtained from the RALE database.
RNA secondary structure diagrams for very large molecules: RNAfdl
DEFF Research Database (Denmark)
Hecker, Nikolai; Wiegels, Tim; Torda, Andrew E.
2013-01-01
There are many programs that can read the secondary structure of an RNA molecule and draw a diagram, but hardly any that can cope with 10 3 bases. RNAfdl is slow but capable of producing intersection-free diagrams for ribosome-sized structures, has a graphical user interface for adjustments...
Exploring the QCD phase diagram through relativistic heavy ion collisions
Directory of Open Access Journals (Sweden)
Mohanty Bedangadas
2014-03-01
Full Text Available We present a review of the studies related to establishing the QCD phase diagram through high energy nucleus-nucleus collisions. We particularly focus on the experimental results related to the formation of a quark-gluon phase, crossover transition and search for a critical point in the QCD phase diagram.
Modeling cancer registration processes with an enhanced activity diagram.
Lyalin, D; Williams, W
2005-01-01
Adequate instruments are needed to reflect the complexity of routine cancer registry operations properly in a business model. The activity diagram is a key instrument of the Unified Modeling Language (UML) for the modeling of business processes. The authors aim to improve descriptions of processes in cancer registration, as well as in other public health domains, through the enhancements of an activity diagram notation within the standard semantics of UML. The authors introduced the practical approach to enhance a conventional UML activity diagram, complementing it with the following business process concepts: timeline, duration for individual activities, responsibilities for individual activities within swimlanes, and descriptive text. The authors used an enhanced activity diagram for modeling surveillance processes in the cancer registration domain. Specific example illustrates the use of an enhanced activity diagram to visualize a process of linking cancer registry records with external mortality files. Enhanced activity diagram allows for the addition of more business concepts to a single diagram and can improve descriptions of processes in cancer registration, as well as in other domains. Additional features of an enhanced activity diagram allow to advance the visualization of cancer registration processes. That, in turn, promotes the clarification of issues related to the process timeline, responsibilities for particular operations, and collaborations among process participants. Our first experiences in a cancer registry best practices development workshop setting support the usefulness of such an approach.
Spacelike penguin diagram effects in B implies PP decays
International Nuclear Information System (INIS)
Du, D.; Yang, M.; Zhang, D.
1996-01-01
The spacelike penguin diagram contributions to branching ratios and CP asymmetries in charmless decays of B to two pseudoscalar mesons are studied using the next-to-leading order low energy effective Hamiltonian. Both the gluonic penguin and the electroweak penguin diagrams are considered. We find that the effects are significant. copyright 1995 The American Physical Society
Diagram, Gesture, Agency: Theorizing Embodiment in the Mathematics Classroom
de Freitas, Elizabeth; Sinclair, Nathalie
2012-01-01
In this paper, we use the work of philosopher Gilles Chatelet to rethink the gesture/diagram relationship and to explore the ways mathematical agency is constituted through it. We argue for a fundamental philosophical shift to better conceptualize the relationship between gesture and diagram, and suggest that such an approach might open up new…
Drawing Euler Diagrams with Circles: The Theory of Piercings.
Stapleton, Gem; Leishi Zhang; Howse, John; Rodgers, Peter
2011-07-01
Euler diagrams are effective tools for visualizing set intersections. They have a large number of application areas ranging from statistical data analysis to software engineering. However, the automated generation of Euler diagrams has never been easy: given an abstract description of a required Euler diagram, it is computationally expensive to generate the diagram. Moreover, the generated diagrams represent sets by polygons, sometimes with quite irregular shapes that make the diagrams less comprehensible. In this paper, we address these two issues by developing the theory of piercings, where we define single piercing curves and double piercing curves. We prove that if a diagram can be built inductively by successively adding piercing curves under certain constraints, then it can be drawn with circles, which are more esthetically pleasing than arbitrary polygons. The theory of piercings is developed at the abstract level. In addition, we present a Java implementation that, given an inductively pierced abstract description, generates an Euler diagram consisting only of circles within polynomial time.
A comparison of two approaches for solving unconstrained influence diagrams
DEFF Research Database (Denmark)
Ahlmann-Ohlsen, Kristian S.; Jensen, Finn V.; Nielsen, Thomas Dyhre
2009-01-01
Influence diagrams and decision trees represent the two most common frameworks for specifying and solving decision problems. As modeling languages, both of these frameworks require that the decision analyst specifies all possible sequences of observations and decisions (in influence diagrams, thi...
Heuristic Diagrams as a Tool to Teach History of Science
Chamizo, Jose A.
2012-01-01
The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The…
... Information Publications Awards Partners Contact Us ¿Qué es Autismo? Donate Home What is Autism? What is Autism? ... Information Publications Awards Partners Contact Us ¿Qué es Autismo? Diagnosis Home / What is Autism? / Diagnosis Expand Medical ...
Stability diagram for the forced Kuramoto model.
Childs, Lauren M; Strogatz, Steven H
2008-12-01
We analyze the periodically forced Kuramoto model. This system consists of an infinite population of phase oscillators with random intrinsic frequencies, global sinusoidal coupling, and external sinusoidal forcing. It represents an idealization of many phenomena in physics, chemistry, and biology in which mutual synchronization competes with forced synchronization. In other words, the oscillators in the population try to synchronize with one another while also trying to lock onto an external drive. Previous work on the forced Kuramoto model uncovered two main types of attractors, called forced entrainment and mutual entrainment, but the details of the bifurcations between them were unclear. Here we present a complete bifurcation analysis of the model for a special case in which the infinite-dimensional dynamics collapse to a two-dimensional system. Exact results are obtained for the locations of Hopf, saddle-node, and Takens-Bogdanov bifurcations. The resulting stability diagram bears a striking resemblance to that for the weakly nonlinear forced van der Pol oscillator.
The phase diagram of ammonium nitrate
Chellappa, Raja S.; Dattelbaum, Dana M.; Velisavljevic, Nenad; Sheffield, Stephen
2012-08-01
The pressure-temperature (P-T) phase diagram of ammonium nitrate (AN) [NH4NO3] has been determined using synchrotron x-ray diffraction (XRD) and Raman spectroscopy measurements. Phase boundaries were established by characterizing phase transitions to the high temperature polymorphs during multiple P-T measurements using both XRD and Raman spectroscopy measurements. At room temperature, the ambient pressure orthorhombic (Pmmn) AN-IV phase was stable up to 45 GPa and no phase transitions were observed. AN-IV phase was also observed to be stable in a large P-T phase space. The phase boundaries are steep with a small phase stability regime for high temperature phases. A P-V-T equation of state based on a high temperature Birch-Murnaghan formalism was obtained by simultaneously fitting the P-V isotherms at 298, 325, 446, and 467 K, thermal expansion data at 1 bar, and volumes from P-T ramping experiments. Anomalous thermal expansion behavior of AN was observed at high pressure with a modest negative thermal expansion in the 3-11 GPa range for temperatures up to 467 K. The role of vibrational anharmonicity in this anomalous thermal expansion behavior has been established using high P-T Raman spectroscopy.
Lattice investigations of the QCD phase diagram
International Nuclear Information System (INIS)
Guenther, Jana
2016-01-01
To understand the physics in the early universe as well as in heavy ion collisions a throughout understanding of the theory of strong interaction, quantum chromodynamics (QCD), is important. Lattice QCD provides a tool to study it from first principles. However due to the sign problem direct simulations with physical conditions are at the moment limited to zero chemical potential. In this thesis I present a circumvention of this problem. We can gain information on the QCD phase diagram and the equation of state from analytical continuation of results extracted from simulations at imaginary chemical potential. The topological susceptibility is very expensive to compute in Lattice QCD. However it provides an important ingredient for the estimation of the axion mass. The axion is a possible candidate for a dark matter, which plays in important role in the understanding of our universe. In this thesis I discuss two techniques that make it possible to determine the topological susceptibility and allow for an estimation of the axion mass. I then use this mass restrain to analyze the idea of an experiment to detect axions with a dielectric mirror.
Lattice investigations of the QCD phase diagram
Energy Technology Data Exchange (ETDEWEB)
Guenther, Jana
2016-12-15
To understand the physics in the early universe as well as in heavy ion collisions a throughout understanding of the theory of strong interaction, quantum chromodynamics (QCD), is important. Lattice QCD provides a tool to study it from first principles. However due to the sign problem direct simulations with physical conditions are at the moment limited to zero chemical potential. In this thesis I present a circumvention of this problem. We can gain information on the QCD phase diagram and the equation of state from analytical continuation of results extracted from simulations at imaginary chemical potential. The topological susceptibility is very expensive to compute in Lattice QCD. However it provides an important ingredient for the estimation of the axion mass. The axion is a possible candidate for a dark matter, which plays in important role in the understanding of our universe. In this thesis I discuss two techniques that make it possible to determine the topological susceptibility and allow for an estimation of the axion mass. I then use this mass restrain to analyze the idea of an experiment to detect axions with a dielectric mirror.
Cost-effectiveness Analysis with Influence Diagrams.
Arias, M; Díez, F J
2015-01-01
Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost. Decision trees, the standard decision modeling technique for non-temporal domains, can only perform CEA for very small problems. To develop a method for CEA in problems involving several dozen variables. We explain how to build influence diagrams (IDs) that explicitly represent cost and effectiveness. We propose an algorithm for evaluating cost-effectiveness IDs directly, i.e., without expanding an equivalent decision tree. The evaluation of an ID returns a set of intervals for the willingness to pay - separated by cost-effectiveness thresholds - and, for each interval, the cost, the effectiveness, and the optimal intervention. The algorithm that evaluates the ID directly is in general much more efficient than the brute-force method, which is in turn more efficient than the expansion of an equivalent decision tree. Using OpenMarkov, an open-source software tool that implements this algorithm, we have been able to perform CEAs on several IDs whose equivalent decision trees contain millions of branches. IDs can perform CEA on large problems that cannot be analyzed with decision trees.
Community detection by graph Voronoi diagrams
Deritei, Dávid; Lázár, Zsolt I.; Papp, István; Járai-Szabó, Ferenc; Sumi, Róbert; Varga, Levente; Ravasz Regan, Erzsébet; Ercsey-Ravasz, Mária
2014-06-01
Accurate and efficient community detection in networks is a key challenge for complex network theory and its applications. The problem is analogous to cluster analysis in data mining, a field rich in metric space-based methods. Common to these methods is a geometric, distance-based definition of clusters or communities. Here we propose a new geometric approach to graph community detection based on graph Voronoi diagrams. Our method serves as proof of principle that the definition of appropriate distance metrics on graphs can bring a rich set of metric space-based clustering methods to network science. We employ a simple edge metric that reflects the intra- or inter-community character of edges, and a graph density-based rule to identify seed nodes of Voronoi cells. Our algorithm outperforms most network community detection methods applicable to large networks on benchmark as well as real-world networks. In addition to offering a computationally efficient alternative for community detection, our method opens new avenues for adapting a wide range of data mining algorithms to complex networks from the class of centroid- and density-based clustering methods.
Finocchario-Kessler, S; Odera, I; Okoth, V; Bawcom, C; Gautney, B; Khamadi, S; Clark, K; Goggin, K
2015-12-01
Guided by the RE-AIM model, we describe preliminary data and lessons learned from multiple serial implementations of an eHealth intervention to improve early infant diagnosis (EID) of HIV in Kenya. We describe the reach, effectiveness, adoption, implementation and maintenance of the HITSystem, an eHealth intervention that links key stakeholders to improve retention and outcomes in EID. Our target community includes mother-infant pairs utilizing EID services and government health care providers and lab personnel. We also explore our own role as program and research personnel supporting the dissemination and scale up of the HITSystem in Kenya. Key findings illustrate the importance of continual adaptation of the HITSystem interface to accommodate varied stakeholders' workflows in different settings. Surprisingly, technology capacity and internet connectivity posed minimal short-term challenges. Early and sustained ownership of the HITSystem among stakeholders proved critical to reach, effectiveness and successful adoption, implementation and maintenance. Preliminary data support the ability of the HITSystem to improve EID outcomes in Kenya. Strong and sustained collaborations with stakeholders improve the quality and reach of eHealth public health interventions. Copyright © 2015 Elsevier Inc. All rights reserved.
Updating the Nomographical Diagrams for Dimensioning the Beams
Directory of Open Access Journals (Sweden)
Pop Maria T.
2015-12-01
Full Text Available In order to reduce the time period needed for structures design it is strongly recommended to use nomographical diagrams. The base for formation and updating the nomographical diagrams, stands on the charts presented by different technical publications. The updated charts use the same algorithm and calculation elements as the former diagrams in accordance to the latest prescriptions and European standards. The result consists in a chart, having the same properties, similar with the nomogragraphical diagrams already in us. As a general conclusion, even in our days, the nomographical diagrams are very easy to use. Taking into consideration the value of the moment it’s easy to find out the necessary reinforcement area and vice-verse, having the reinforcement area you can find out the capable moment. It still remains a useful opportunity for pre-sizing and designs the reinforced concrete sections.
Analysis of Sequence Diagram Layout in Advanced UML Modelling Tools
Directory of Open Access Journals (Sweden)
Ņikiforova Oksana
2016-05-01
Full Text Available System modelling using Unified Modelling Language (UML is the task that should be solved for software development. The more complex software becomes the higher requirements are stated to demonstrate the system to be developed, especially in its dynamic aspect, which in UML is offered by a sequence diagram. To solve this task, the main attention is devoted to the graphical presentation of the system, where diagram layout plays the central role in information perception. The UML sequence diagram due to its specific structure is selected for a deeper analysis on the elements’ layout. The authors research represents the abilities of modern UML modelling tools to offer automatic layout of the UML sequence diagram and analyse them according to criteria required for the diagram perception.
Efficient computation of clipped Voronoi diagram for mesh generation
Yan, Dongming
2013-04-01
The Voronoi diagram is a fundamental geometric structure widely used in various fields, especially in computer graphics and geometry computing. For a set of points in a compact domain (i.e. a bounded and closed 2D region or a 3D volume), some Voronoi cells of their Voronoi diagram are infinite or partially outside of the domain, but in practice only the parts of the cells inside the domain are needed, as when computing the centroidal Voronoi tessellation. Such a Voronoi diagram confined to a compact domain is called a clipped Voronoi diagram. We present an efficient algorithm to compute the clipped Voronoi diagram for a set of sites with respect to a compact 2D region or a 3D volume. We also apply the proposed method to optimal mesh generation based on the centroidal Voronoi tessellation. Crown Copyright © 2011 Published by Elsevier Ltd. All rights reserved.
Efficient computation of clipped Voronoi diagram for mesh generation
Yan, Dongming; Wang, Wen Ping; Lé vy, Bruno L.; Liu, Yang
2013-01-01
The Voronoi diagram is a fundamental geometric structure widely used in various fields, especially in computer graphics and geometry computing. For a set of points in a compact domain (i.e. a bounded and closed 2D region or a 3D volume), some Voronoi cells of their Voronoi diagram are infinite or partially outside of the domain, but in practice only the parts of the cells inside the domain are needed, as when computing the centroidal Voronoi tessellation. Such a Voronoi diagram confined to a compact domain is called a clipped Voronoi diagram. We present an efficient algorithm to compute the clipped Voronoi diagram for a set of sites with respect to a compact 2D region or a 3D volume. We also apply the proposed method to optimal mesh generation based on the centroidal Voronoi tessellation. Crown Copyright © 2011 Published by Elsevier Ltd. All rights reserved.
VennDiagramWeb: a web application for the generation of highly customizable Venn and Euler diagrams.
Lam, Felix; Lalansingh, Christopher M; Babaran, Holly E; Wang, Zhiyuan; Prokopec, Stephenie D; Fox, Natalie S; Boutros, Paul C
2016-10-03
Visualization of data generated by high-throughput, high-dimensionality experiments is rapidly becoming a rate-limiting step in computational biology. There is an ongoing need to quickly develop high-quality visualizations that can be easily customized or incorporated into automated pipelines. This often requires an interface for manual plot modification, rapid cycles of tweaking visualization parameters, and the generation of graphics code. To facilitate this process for the generation of highly-customizable, high-resolution Venn and Euler diagrams, we introduce VennDiagramWeb: a web application for the widely used VennDiagram R package. VennDiagramWeb is hosted at http://venndiagram.res.oicr.on.ca/ . VennDiagramWeb allows real-time modification of Venn and Euler diagrams, with parameter setting through a web interface and immediate visualization of results. It allows customization of essentially all aspects of figures, but also supports integration into computational pipelines via download of R code. Users can upload data and download figures in a range of formats, and there is exhaustive support documentation. VennDiagramWeb allows the easy creation of Venn and Euler diagrams for computational biologists, and indeed many other fields. Its ability to support real-time graphics changes that are linked to downloadable code that can be integrated into automated pipelines will greatly facilitate the improved visualization of complex datasets. For application support please contact Paul.Boutros@oicr.on.ca.
Energy Technology Data Exchange (ETDEWEB)
1993-09-01
The Oak Ridge National Laboratory Technology Logic Diagram (TLD) was developed to provide a decision support tool that relates environmental restoration (ER) and waste management (WM) problems at Oak Ridge National Laboratory (ORNL) to potential technologies that can remediate these problems. The TLD identifies the research, development, demonstration, testing, and evaluation needed to develop these technologies to a state that allows technology transfer and application to decontamination and decommissioning (D&D), remedial action (RA), and WM activities. The TLD consists of three fundamentally separate volumes: Vol. 1 (Technology Evaluation), Vol. 2 (Technology Logic Diagram), and Vol. 3 (Technology Evaluation Data Sheets). Part A of Vols. 1. and 2 focuses on D&D. Part B of Vols. 1 and 2 focuses on the RA of contaminated facilities. Part C of Vols. 1 and 2 focuses on WM. Each part of Vol. 1 contains an overview of the TLD, an explanation of the program-specific responsibilities, a review of identified technologies, and the rankings of remedial technologies. Volume 2 (Pts. A, B, and C) contains the logic linkages among EM goals, environmental problems, and the various technologies that have the potential to solve these problems. Volume 3 (Pts. A, B, and C) contains the TLD data sheets. Remedial action is the focus of Vol. 2, Pt. B, which has been divided into the three necessary subelements of the RA: characterization, RA, and robotics and automation. Each of these sections address general ORNL problems, which are then broken down by problem area/constituents and linked to potential remedial technologies. The diagrams also contain summary information about a technology`s status, its science and technology needs, and its implementation needs.
The Eh-pH Diagram and Its Advances
Directory of Open Access Journals (Sweden)
Hsin-Hsiung Huang
2016-01-01
Full Text Available Since Pourbaix presented Eh versus pH diagrams in his “Atlas of Electrochemical Equilibria in Aqueous Solution”, diagrams have become extremely popular and are now used in almost every scientific area related to aqueous chemistry. Due to advances in personal computers, such diagrams can now show effects not only of Eh and pH, but also of variables, including ligand(s, temperature and pressure. Examples from various fields are illustrated in this paper. Examples include geochemical formation, corrosion and passivation, precipitation and adsorption for water treatment and leaching and metal recovery for hydrometallurgy. Two basic methods were developed to construct an Eh-pH diagram concerning the ligand component(s. The first method calculates and draws a line between two adjacent species based on their given activities. The second method performs equilibrium calculations over an array of points (500 × 800 or higher are preferred, each representing one Eh and one pH value for the whole system, then combines areas of each dominant species for the diagram. These two methods may produce different diagrams. The fundamental theories, illustrated results, comparison and required conditions behind these two methods are presented and discussed in this paper. The Gibbs phase rule equation for an Eh-pH diagram was derived and verified from actual plots. Besides indicating the stability area of water, an Eh-pH diagram normally shows only half of an overall reaction. However, merging two or more related diagrams together reveals more clearly the possibility of the reactions involved. For instance, leaching of Au with cyanide followed by cementing Au with Zn (Merrill-Crowe process can be illustrated by combining Au-CN and Zn-CN diagrams together. A second example of the galvanic conversion of chalcopyrite can be explained by merging S, Fe–S and Cu–Fe–S diagrams. The calculation of an Eh-pH diagram can be extended easily into another dimension, such
International Nuclear Information System (INIS)
Eremenko, V.N.; Velikanova, T.Ya.; Gordijchuk, O.V.
1988-01-01
Results of the X-ray phase, metallographic and high-temperature differential thermal analysis are used for the first time to plot a diagram of the Pr-C system state. Carbides are formed in the system: Pr 2 C 3 with the bcc-structure of the Pu 2 C 3 type and with the period a 0 = 0.85722+-0.00026 within the phase region + 2 C 3 >, a 0 0.86078+-0.00016 nm - within the region 2 C 3 >+α-PrC 2 ; dimorphous PrC 2 : α-PrC 2 with the bct-structure of the CaC 2 type and periods a 0.38517+-0.00011, c 0 = 0.64337+-0.00019 nm; β-PrC 2 with the fcc-structure, probably, of KCN type. Dicarbide melts congruently at 2320 grad. C, forming eutectics with graphite at 2254+-6 grad. C and composition of 71.5% (at.)C. It is polymorphously transformed in the phase region 2 C 3 > + 2 > at 1145+-4 grad. C, and in the region 2 >+C at 1134+-4 grad. C. Sesquicarbide melts incongruently at 1545+-4 grad. C. The eutectic reaction L ↔ + 2 C 3 > occurs at 800+-4 grad. C, the eutectic composition ∼ 15% (at.)C. The temperature of the eutectoid reaction ↔ + 2 C 3 > is 675+-6 grad C. The limiting carbon solubility in β-Pr is about 8 and in α-Pr it is about 5% (at.)
Classical Process diagrams and Service oriented Architecture
Directory of Open Access Journals (Sweden)
Milan Mišovič
2013-01-01
services communicate with each other. The communication can involve either simple data or it could two or more services coordinating some activity. From the above mentioned we can pronounce a brief description of SOA. “SOA is an architectural style for consistency of business process logic and service architecture of the target software.”It is a complex of means for solution of special analysis, design, and integration of enterprise applications based on the use of enterprise services. The service solutions of the classic business process logic are, of course, based on the application of at least seven key principles of SOA (free relations, service contract, autonomy, abstraction, reusing, composition, no states. Key attributes of SOA are verbally described in (Erl, 2006. They are so important that a separate article should be devoted to their nature and formalization. On the other hand, there is also clear that each service solution of business logic should respect the principles published in SOA Manifesto, 2009, which are essentially derived from the key principles of SOA.In many publications there are given the SOA reference models usually composed of several layers (presentation layer, business process layer, composite services layer, application layer giving a meta idea of SOA implementation. Perfect knowledge of the business process logic is a necessary condition for the development of a proper service solution. The different types of business processes should be described in the necessary details and contexts.Interestingly, the SOA paradigm does not provide its own method of finding and describing business processes by giving a layered transparent business process diagram. On the other hand, the methodology provides deep understanding of not only the characteristics of services, but also their functionality and implementation of the key principles of SOA (Erl, 2006.Let us assume that the required process diagrams can be achieved by using some of the advanced
Homotopy theory of modules over diagrams of rings
Directory of Open Access Journals (Sweden)
J. P. C. Greenlees
2014-09-01
Full Text Available Given a diagram of rings, one may consider the category of modules over them. We are interested in the homotopy theory of categories of this type: given a suitable diagram of model categories ℳ( (as runs through the diagram, we consider the category of diagrams where the object ( at comes from ℳ(. We develop model structures on such categories of diagrams and Quillen adjunctions that relate categories based on different diagram shapes. Under certain conditions, cellularizations (or right Bousfield localizations of these adjunctions induce Quillen equivalences. As an application we show that a cellularization of a category of modules over a diagram of ring spectra (or differential graded rings is Quillen equivalent to modules over the associated inverse limit of the rings. Another application of the general machinery here is given in work by the authors on algebraic models of rational equivariant spectra. Some of this material originally appeared in the preprint “An algebraic model for rational torus-equivariant stable homotopy theory”, arXiv:1101.2511, but has been generalized here.
Penguin-like diagrams from the standard model
International Nuclear Information System (INIS)
Ping, Chia Swee
2015-01-01
The Standard Model is highly successful in describing the interactions of leptons and quarks. There are, however, rare processes that involve higher order effects in electroweak interactions. One specific class of processes is the penguin-like diagram. Such class of diagrams involves the neutral change of quark flavours accompanied by the emission of a gluon (gluon penguin), a photon (photon penguin), a gluon and a photon (gluon-photon penguin), a Z-boson (Z penguin), or a Higgs-boson (Higgs penguin). Such diagrams do not arise at the tree level in the Standard Model. They are, however, induced by one-loop effects. In this paper, we present an exact calculation of the penguin diagram vertices in the ‘tHooft-Feynman gauge. Renormalization of the vertex is effected by a prescription by Chia and Chong which gives an expression for the counter term identical to that obtained by employing Ward-Takahashi identity. The on-shell vertex functions for the penguin diagram vertices are obtained. The various penguin diagram vertex functions are related to one another via Ward-Takahashi identity. From these, a set of relations is obtained connecting the vertex form factors of various penguin diagrams. Explicit expressions for the gluon-photon penguin vertex form factors are obtained, and their contributions to the flavor changing processes estimated
Penguin-like diagrams from the standard model
Energy Technology Data Exchange (ETDEWEB)
Ping, Chia Swee [High Impact Research, University of Malaya, 50603 Kuala Lumpur (Malaysia)
2015-04-24
The Standard Model is highly successful in describing the interactions of leptons and quarks. There are, however, rare processes that involve higher order effects in electroweak interactions. One specific class of processes is the penguin-like diagram. Such class of diagrams involves the neutral change of quark flavours accompanied by the emission of a gluon (gluon penguin), a photon (photon penguin), a gluon and a photon (gluon-photon penguin), a Z-boson (Z penguin), or a Higgs-boson (Higgs penguin). Such diagrams do not arise at the tree level in the Standard Model. They are, however, induced by one-loop effects. In this paper, we present an exact calculation of the penguin diagram vertices in the ‘tHooft-Feynman gauge. Renormalization of the vertex is effected by a prescription by Chia and Chong which gives an expression for the counter term identical to that obtained by employing Ward-Takahashi identity. The on-shell vertex functions for the penguin diagram vertices are obtained. The various penguin diagram vertex functions are related to one another via Ward-Takahashi identity. From these, a set of relations is obtained connecting the vertex form factors of various penguin diagrams. Explicit expressions for the gluon-photon penguin vertex form factors are obtained, and their contributions to the flavor changing processes estimated.
Plotting and Analyzing Data Trends in Ternary Diagrams Made Easy
John, Cédric M.
2004-04-01
Ternary plots are used in many fields of science to characterize a system based on three components. Triangular plotting is thus useful to a broad audience in the Earth sciences and beyond. Unfortunately, it is typically the most expensive commercial software packages that offer the option to plot data in ternary diagrams, and they lack features that are paramount to the geosciences, such as the ability to plot data directly into a standardized diagram and the possibility to analyze temporal and stratigraphic trends within this diagram. To address these issues, δPlot was developed with a strong emphasis on ease of use, community orientation, and availability free of charges. This ``freeware'' supports a fully graphical user interface where data can be imported as text files, or by copying and pasting. A plot is automatically generated, and any standard diagram can be selected for plotting in the background using a simple pull-down menu. Standard diagrams are stored in an external database of PDF files that currently holds some 30 diagrams that deal with different fields of the Earth sciences. Using any drawing software supporting PDF, one can easily produce new standard diagrams to be used with δPlot by simply adding them to the library folder. An independent column of values, commonly stratigraphic depths or ages, can be used to sort the data sets.
Visualizing the Bayesian 2-test case: The effect of tree diagrams on medical decision making.
Binder, Karin; Krauss, Stefan; Bruckmaier, Georg; Marienhagen, Jörg
2018-01-01
In medicine, diagnoses based on medical test results are probabilistic by nature. Unfortunately, cognitive illusions regarding the statistical meaning of test results are well documented among patients, medical students, and even physicians. There are two effective strategies that can foster insight into what is known as Bayesian reasoning situations: (1) translating the statistical information on the prevalence of a disease and the sensitivity and the false-alarm rate of a specific test for that disease from probabilities into natural frequencies, and (2) illustrating the statistical information with tree diagrams, for instance, or with other pictorial representation. So far, such strategies have only been empirically tested in combination for "1-test cases", where one binary hypothesis ("disease" vs. "no disease") has to be diagnosed based on one binary test result ("positive" vs. "negative"). However, in reality, often more than one medical test is conducted to derive a diagnosis. In two studies, we examined a total of 388 medical students from the University of Regensburg (Germany) with medical "2-test scenarios". Each student had to work on two problems: diagnosing breast cancer with mammography and sonography test results, and diagnosing HIV infection with the ELISA and Western Blot tests. In Study 1 (N = 190 participants), we systematically varied the presentation of statistical information ("only textual information" vs. "only tree diagram" vs. "text and tree diagram in combination"), whereas in Study 2 (N = 198 participants), we varied the kinds of tree diagrams ("complete tree" vs. "highlighted tree" vs. "pruned tree"). All versions were implemented in probability format (including probability trees) and in natural frequency format (including frequency trees). We found that natural frequency trees, especially when the question-related branches were highlighted, improved performance, but that none of the corresponding probabilistic visualizations did.
Mollier-h,x diagram for moist flue gas
Energy Technology Data Exchange (ETDEWEB)
Mueller, H; Hultsch, T; Suder, M
1984-07-01
Diagrams and formulae are presented for calculation of enthalpy and moisture content of flue gas from brown coal, heating oil, black coal and brown coal briquet combustion. The enthalpy (in kJ/kg) and moisture (g/kg) diagrams were established by computer graphics for pressure 0.1 MPa. A further diagram is provided for enthalpy and flue gas moisture, varying the combustion air supply according to coal dust and to grate firing. These thermodynamic calculations are regarded as significant for assessing methods of flue gas cooling below the moisture dew point and for waste heat recovery. 3 references.
A Three-dimensional Topological Model of Ternary Phase Diagram
International Nuclear Information System (INIS)
Mu, Yingxue; Bao, Hong
2017-01-01
In order to obtain a visualization of the complex internal structure of ternary phase diagram, the paper realized a three-dimensional topology model of ternary phase diagram with the designed data structure and improved algorithm, under the guidance of relevant theories of computer graphics. The purpose of the model is mainly to analyze the relationship between each phase region of a ternary phase diagram. The model not only obtain isothermal section graph at any temperature, but also extract a particular phase region in which users are interested. (paper)
Research principles and the construction of mnemonic diagrams
Venda, V. F.; Mitkin, A. A.
1973-01-01
Mnemonic diagrams are defined as a variety of information display devices, the essential element of which is conventional graphical presentation of technological or functional-operational links in a controlled system or object. Graphically displaying the operational structure of an object, the interd dependence between different parameters, and the interdependence between indicators and control organs, the mneomonic diagram reduces the load on the operator's memory and facilitates perception and reprocessing of information and decision making, while at the same time playing the role of visual support to the information activity of the operator. The types of mnemonic diagrams are listed.
Ferrian Ilmenites: Investigating the Magnetic Phase Diagram
Lagroix, F.
2007-12-01
The main objective of this study is to investigate the magnetic phase changes within the hematite-ilmenite solid solution, yFeTiO3·(1-y)·Fe2O3. Two sets of synthetic ferrian ilmenites of y-values equal to 0.7, 0.8, 0.9, and 1.0 were available for this study. As currently drawn, the magnetic phase diagram, proposed by Ishikawa et al. [1985, J. Phys. Soc. Jpn. v.54, 312-325], predicts for increasing y values (0.5
An updated Type II supernova Hubble diagram
Gall, E. E. E.; Kotak, R.; Leibundgut, B.; Taubenberger, S.; Hillebrandt, W.; Kromer, M.; Burgett, W. S.; Chambers, K.; Flewelling, H.; Huber, M. E.; Kaiser, N.; Kudritzki, R. P.; Magnier, E. A.; Metcalfe, N.; Smith, K.; Tonry, J. L.; Wainscoat, R. J.; Waters, C.
2018-03-01
We present photometry and spectroscopy of nine Type II-P/L supernovae (SNe) with redshifts in the 0.045 ≲ z ≲ 0.335 range, with a view to re-examining their utility as distance indicators. Specifically, we apply the expanding photosphere method (EPM) and the standardized candle method (SCM) to each target, and find that both methods yield distances that are in reasonable agreement with each other. The current record-holder for the highest-redshift spectroscopically confirmed supernova (SN) II-P is PS1-13bni (z = 0.335-0.012+0.009), and illustrates the promise of Type II SNe as cosmological tools. We updated existing EPM and SCM Hubble diagrams by adding our sample to those previously published. Within the context of Type II SN distance measuring techniques, we investigated two related questions. First, we explored the possibility of utilising spectral lines other than the traditionally used Fe IIλ5169 to infer the photospheric velocity of SN ejecta. Using local well-observed objects, we derive an epoch-dependent relation between the strong Balmer line and Fe IIλ5169 velocities that is applicable 30 to 40 days post-explosion. Motivated in part by the continuum of key observables such as rise time and decline rates exhibited from II-P to II-L SNe, we assessed the possibility of using Hubble-flow Type II-L SNe as distance indicators. These yield similar distances as the Type II-P SNe. Although these initial results are encouraging, a significantly larger sample of SNe II-L would be required to draw definitive conclusions. Tables A.1, A.3, A.5, A.7, A.9, A.11, A.13, A.15 and A.17 are also available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/611/A25
Adding Value to Force Diagrams: Representing Relative Force Magnitudes
Wendel, Paul
2011-05-01
Nearly all physics instructors recognize the instructional value of force diagrams, and this journal has published several collections of exercises to improve student skill in this area.1-4 Yet some instructors worry that too few students perceive the conceptual and problem-solving utility of force diagrams,4-6 and over recent years a rich variety of approaches has been proposed to add value to force diagrams. Suggestions include strategies for identifying candidate forces,6,7 emphasizing the distinction between "contact" and "noncontact" forces,5,8 and the use of computer-based tutorials.9,10 Instructors have suggested a variety of conventions for constructing force diagrams, including approaches to arrow placement and orientation2,11-13 and proposed notations for locating forces or marking action-reaction force pairs.8,11,14,15
Feynman diagrams coupled to three-dimensional quantum gravity
International Nuclear Information System (INIS)
Barrett, John W
2006-01-01
A framework for quantum field theory coupled to three-dimensional quantum gravity is proposed. The coupling with quantum gravity regulates the Feynman diagrams. One recovers the usual Feynman amplitudes in the limit as the cosmological constant tends to zero
Cu–Ni nanoalloy phase diagram – Prediction and experiment
Czech Academy of Sciences Publication Activity Database
Sopoušek, J.; Vřešťál, J.; Pinkas, J.; Brož, P.; Buršík, Jiří; Stýskalík, A.; Škoda, D.; Zobač, O.; Lee, J.
2014-01-01
Roč. 45, June (2014), s. 33-39 ISSN 0364-5916 Institutional support: RVO:68081723 Keywords : nanoalloy * phase diagram * thermodynamic modeling Subject RIV: BJ - Thermodynamics Impact factor: 1.370, year: 2014
Revised Pourbaix diagrams for Copper at 5-150 C
International Nuclear Information System (INIS)
Beverskog, B.; Puigdomenech, I.
1995-10-01
Pourbaix diagrams have been revised. Predominance diagrams for dissolved copper species have also been calculated. Five different total concentrations for dissolved copper have been used in the calculations (from 10 -3 to 10 -9 ). The complete hydrolysis series of copper(I) and (II) have not been included in earlier published Pourbaix diagrams, and these species are covered for the first time in this work. At acidic pH, increasing temperature decreases the immunity area, and therefore, it increases the corrosion of the copper. At alkaline pH-values corrosion also increases with the temperature due to the decrease of both passivity and immunity areas. The calculated diagrams are used as a base for the discussion of the corrosion behaviour of the copper canisters in the Swedish radioactive waste management program. 62 refs, 37 figs, 3 tabs
Solid gas reaction phase diagram under high gas pressure
International Nuclear Information System (INIS)
Ishizaki, K.
1992-01-01
This paper reports that to evaluate which are the stable phases under high gas pressure conditions, a solid-gas reaction phase diagram under high gas pressure (HIP phase diagram) has been proposed by the author. The variables of the diagram are temperature, reactant gas partial pressure and total gas pressure. Up to the present time the diagrams have been constructed using isobaric conditions. In this work, the stable phases for a real HIP process were evaluated assuming an isochoric condition. To understand the effect of the total gas pressure on stability is of primary importance. Two possibilities were considered and evaluated, those are: the total gas pressure acts as an independent variable, or it only affects the fugacity values. The results of this work indicate that the total gas pressure acts as an independent variable, and in turn also affects the fugacity values
Approximation of hadron interactions by Regge diagrams with multipomeron exchange
International Nuclear Information System (INIS)
Barashenkov, V.S.
1988-01-01
A good agreement of hadron diffraction interaction total cross section and their elastic scattering at small angles calculated by summarizing Regge multipomeron exchange diagrams with experiment mentioned by a number of authors results from the fitting of a great variety of the parameters contained in the formulas. The agreement of the other hadron characteristcs with experiment is worse. Distribution of hadron interactions over the number of fragmenting quark-gluon strings calculated by utilizing Regge diagrams is discussed
Algorithms and programs for consequence diagram and fault tree construction
International Nuclear Information System (INIS)
Hollo, E.; Taylor, J.R.
1976-12-01
A presentation of algorithms and programs for consequence diagram and sequential fault tree construction that are intended for reliability and disturbance analysis of large systems. The system to be analyzed must be given as a block diagram formed by mini fault trees of individual system components. The programs were written in LISP programming language and run on a PDP8 computer with 8k words of storage. A description is given of the methods used and of the program construction and working. (author)
Irradiation distribution diagrams and their use for estimating collectable energy
International Nuclear Information System (INIS)
Ronnelid, M.; Karlsson, B.
1997-01-01
A method for summarising annual or seasonal solar irradiation data in irradiation distribution diagrams, including both direct and diffuse irradiation, is outlined. The practical use of irradiation distribution diagrams is discussed in the paper. Examples are given for the calculation of collectable irradiation on flat plate collectors or trough-like concentrators like the compound parabolic concentrator (CPC), and for the calculation of overhang geometries for windows to prevent overheating of buildings. (author)
49 CFR Appendix B to Part 230 - Diagrams and Drawings
2010-10-01
... 49 Transportation 4 2010-10-01 2010-10-01 false Diagrams and Drawings B Appendix B to Part 230 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... to Part 230—Diagrams and Drawings ER17No99.015 ER17No99.016 ER17No99.017 ER17No99.018 ER17No99.019...
On Hardy's paradox, weak measurements, and multitasking diagrams
International Nuclear Information System (INIS)
Meglicki, Zdzislaw
2011-01-01
We discuss Hardy's paradox and weak measurements by using multitasking diagrams, which are introduced to illustrate the progress of quantum probabilities through the double interferometer system. We explain how Hardy's paradox is avoided and elaborate on the outcome of weak measurements in this context. -- Highlights: → Hardy's paradox explained and eliminated. → Weak measurements: what is really measured? → Multitasking diagrams: introduced and used to discuss quantum mechanical processes.
Creating Royal Australian Navy Standard Operating Procedures using Flow Diagrams
2015-08-01
departments and check the naming and number conventions have been adhered to. They will also coordinate the review process and check that the definitive ...possible. If the performer is a team the composition of the team should be described in the SOP, either as a definition or in the description of a...diagram a video could be used. A hyperlink to a video of the process to follow could be added to the flow diagram or the description section of the
Diagrams of ion stability in radio-frequency mass spectrometry
International Nuclear Information System (INIS)
Sudakov, M.Yu.
1994-01-01
For solving radio-frequency mass spectrometry problems and dynamic ion containment are studied and systematized different ways for constructing the ion stability diagrams. A new universal set of parameters is proposed for diagram construction-angular variables, which are the phase raid of ion oscillational motion during positive and negative values of the supplying voltage. An effective analytical method is proposed for optimization of the parameters of the pulsed supplying voltage, in particular its repetition rate
On the phase diagram of non-spherical nanoparticles
Wautelet, M; Hecq, M
2003-01-01
The phase diagram of nanoparticles is known to be a function of their size. In the literature, this is generally demonstrated for cases where their shape is spherical. Here, it is shown theoretically that the phase diagram of non-spherical particles may be calculated from the spherical case, at the same surface area/volume ratio, both with and without surface segregation, provided the surface tension is considered to be isotropic.
COCCIA, Mario
2017-01-01
Abstract. This study suggests the fishbone diagram for technological analysis. Fishbone diagram (also called Ishikawa diagrams or cause-and-effect diagrams) is a graphical technique to show the several causes of a specific event or phenomenon. In particular, a fishbone diagram (the shape is similar to a fish skeleton) is a common tool used for a cause and effect analysis to identify a complex interplay of causes for a specific problem or event. The fishbone diagram can be a comprehensive theo...
Construction of UML class diagram with Model-Driven Development
Directory of Open Access Journals (Sweden)
Tomasz Górski
2016-03-01
Full Text Available Model transformations play a key role in software development projects based on Model--Driven Development (MDD principles. Transformations allow for automation of repetitive and well-defined steps, thus shortening design time and reducing a number of errors. In the object-oriented approach, the key elements are use cases. They are described, modelled and later designed until executable application code is obtained. The aim of the paper is to present transformation of a model-to-model type, Communication-2-Class, which automates construction of Unified Modelling Language (UML class diagram in the context of the analysis/design model. An UML class diagram is created based on UML communication diagram within use case realization. As a result, a class diagram shows all of the classes involved in the use case realization and the relationships among them. The plug-in which implements Communication-2-Class transformation was implemented in the IBM Rational Software Architect. The article presents the tests results of developed plug-in, which realizes Communication-2-Class transformation, showing capabilities of shortening use case realization’s design time.[b]Keywords[/b]: Model-Driven Development, transformations, Unified Modelling Language, analysis/design model, UML class diagram, UML communication diagram
Vesicle computers: Approximating a Voronoi diagram using Voronoi automata
International Nuclear Information System (INIS)
Adamatzky, Andrew; De Lacy Costello, Ben; Holley, Julian; Gorecki, Jerzy; Bull, Larry
2011-01-01
Highlights: → We model irregular arrangements of vesicles filled with chemical systems. → We examine influence of precipitation threshold on the system's computational potential. → We demonstrate computation of Voronoi diagram and skeleton. - Abstract: Irregular arrangements of vesicles filled with excitable and precipitating chemical systems are imitated by Voronoi automata - finite-state machines defined on a planar Voronoi diagram. Every Voronoi cell takes four states: resting, excited, refractory and precipitate. A resting cell excites if it has at least one neighbour in an excited state. The cell precipitates if the ratio of excited cells in its neighbourhood versus the number of neighbours exceeds a certain threshold. To approximate a Voronoi diagram on Voronoi automata we project a planar set onto the automaton lattice, thus cells corresponding to data-points are excited. Excitation waves propagate across the Voronoi automaton, interact with each other and form precipitate at the points of interaction. The configuration of the precipitate represents the edges of an approximated Voronoi diagram. We discover the relationship between the quality of the Voronoi diagram approximation and the precipitation threshold, and demonstrate the feasibility of our model in approximating Voronoi diagrams of arbitrary-shaped objects and in constructing a skeleton of a planar shape.
Simple method for evaluating Goldstone diagrams in an angular momentum coupled representation
International Nuclear Information System (INIS)
Kuo, T.T.S.; Shurpin, J.; Tam, K.C.; Osnes, E.; Ellis, P.J.
1981-01-01
A simple and convenient method is derived for evaluating linked Goldstone diagrams in an angular momentum coupled representation. Our method is general, and can be used to evaluate any effective interaction and/or effective operator diagrams for both closed-shell nuclei (vacuum to vacuum linked diagrams) and open-shell nuclei (valence linked diagrams). The techniques of decomposing diagrams into ladder diagrams, cutting open internal lines and cutting off one-body insertions are introduced. These enable us to determine angular momentum factors associated with diagrams in the coupled representation directly, without the need for carrying out complicated angular momentum algebra. A summary of diagram rules is given
Infrared thermography method for fast estimation of phase diagrams
Energy Technology Data Exchange (ETDEWEB)
Palomo Del Barrio, Elena [Université de Bordeaux, Institut de Mécanique et d’Ingénierie, Esplanade des Arts et Métiers, 33405 Talence (France); Cadoret, Régis [Centre National de la Recherche Scientifique, Institut de Mécanique et d’Ingénierie, Esplanade des Arts et Métiers, 33405 Talence (France); Daranlot, Julien [Solvay, Laboratoire du Futur, 178 Av du Dr Schweitzer, 33608 Pessac (France); Achchaq, Fouzia, E-mail: fouzia.achchaq@u-bordeaux.fr [Université de Bordeaux, Institut de Mécanique et d’Ingénierie, Esplanade des Arts et Métiers, 33405 Talence (France)
2016-02-10
Highlights: • Infrared thermography is proposed to determine phase diagrams in record time. • Phase boundaries are detected by means of emissivity changes during heating. • Transition lines are identified by using Singular Value Decomposition techniques. • Different binary systems have been used for validation purposes. - Abstract: Phase change materials (PCM) are widely used today in thermal energy storage applications. Pure PCMs are rarely used because of non adapted melting points. Instead of them, mixtures are preferred. The search of suitable mixtures, preferably eutectics, is often a tedious and time consuming task which requires the determination of phase diagrams. In order to accelerate this screening step, a new method for estimating phase diagrams in record time (1–3 h) has been established and validated. A sample composed by small droplets of mixtures with different compositions (as many as necessary to have a good coverage of the phase diagram) deposited on a flat substrate is first prepared and cooled down to ambient temperature so that all droplets crystallize. The plate is then heated at constant heating rate up to a sufficiently high temperature for melting all the small crystals. The heating process is imaged by using an infrared camera. An appropriate method based on singular values decomposition technique has been developed to analyze the recorded images and to determine the transition lines of the phase diagram. The method has been applied to determine several simple eutectic phase diagrams and the reached results have been validated by comparison with the phase diagrams obtained by Differential Scanning Calorimeter measurements and by thermodynamic modelling.
Reactome diagram viewer: data structures and strategies to boost performance.
Fabregat, Antonio; Sidiropoulos, Konstantinos; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning
2018-04-01
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community. The pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partitioning data structure minimizes CPU workload, enabling the introduction of new features that further enhance user experience. Through the use of highly optimized data structures and algorithms, Reactome has boosted the performance and usability of the new pathway diagram viewer, providing a robust, scalable and easy-to-integrate solution to pathway visualization. As graph-based visualization of complex data is a frequent challenge in bioinformatics, many of the individual strategies presented here are applicable to a wide range of web-based bioinformatics resources. Reactome is available online at: https://reactome.org. The diagram viewer is part of the Reactome pathway browser (https://reactome.org/PathwayBrowser/) and also available as a stand-alone widget at: https://reactome.org/dev/diagram/. The source code is freely available at: https://github.com/reactome-pwp/diagram. fabregat@ebi.ac.uk or hhe@ebi.ac.uk. Supplementary data are available at Bioinformatics online.
Directory of Open Access Journals (Sweden)
Mohsen Laabidi
2014-01-01
Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.
Yao, K; Uedo, N; Muto, M; Ishikawa, H; Cardona, H J; Filho, E C Castro; Pittayanon, R; Olano, C; Yao, F; Parra-Blanco, A; Ho, S H; Avendano, A G; Piscoya, A; Fedorov, E; Bialek, A P; Mitrakov, A; Caro, L; Gonen, C; Dolwani, S; Farca, A; Cuaresma, L F; Bonilla, J J; Kasetsermwiriya, W; Ragunath, K; Kim, S E; Marini, M; Li, H; Cimmino, D G; Piskorz, M M; Iacopini, F; So, J B; Yamazaki, K; Kim, G H; Ang, T L; Milhomem-Cardoso, D M; Waldbaum, C A; Carvajal, W A Piedra; Hayward, C M; Singh, R; Banerjee, R; Anagnostopoulos, G K; Takahashi, Y
2016-07-01
In many countries, gastric cancer is not diagnosed until an advanced stage. An Internet-based e-learning system to improve the ability of endoscopists to diagnose gastric cancer at an early stage was developed and was evaluated for its effectiveness. The study was designed as a randomized controlled trial. After receiving a pre-test, participants were randomly allocated to either an e-learning or non-e-learning group. Only those in the e-learning group gained access to the e-learning system. Two months after the pre-test, both groups received a post-test. The primary endpoint was the difference between the two groups regarding the rate of improvement of their test results. 515 endoscopists from 35 countries were assessed for eligibility, and 332 were enrolled in the study, with 166 allocated to each group. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group were included in the analysis. The mean improvement rate (standard deviation) in the e-learning and non-e-learning groups was 1·24 (0·26) and 1·00 (0·16), respectively (Pe-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039). Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
... Diagnosis Language: English (US) Español (Spanish) Recommend on Facebook Tweet Share Compartir Doctors in the United States rarely see a patient with anthrax. CDC Guidance and case definitions are available to help doctors diagnose anthrax, take ...
Sien, Ven Yu
2011-12-01
Object-oriented analysis and design (OOAD) is not an easy subject to learn. There are many challenges confronting students when studying OOAD. Students have particular difficulty abstracting real-world problems within the context of OOAD. They are unable to effectively build object-oriented (OO) models from the problem domain because they essentially do not know "what" to model. This article investigates the difficulties and misconceptions undergraduate students have with analysing systems using unified modelling language analysis class and sequence diagrams. These models were chosen because they represent important static and dynamic aspects of the software system under development. The results of this study will help students produce effective OO models, and facilitate software engineering lecturers design learning materials and approaches for introductory OOAD courses.
A Community Based Systems Diagram of Obesity Causes.
Directory of Open Access Journals (Sweden)
Steven Allender
Full Text Available Application of system thinking to the development, implementation and evaluation of childhood obesity prevention efforts represents the cutting edge of community-based prevention. We report on an approach to developing a system oriented community perspective on the causes of obesity.Group model building sessions were conducted in a rural Australian community to address increasing childhood obesity. Stakeholders (n = 12 built a community model that progressed from connection circles to causal loop diagrams using scripts from the system dynamics literature. Participants began this work in identifying change over time in causes and effects of childhood obesity within their community. The initial causal loop diagram was then reviewed and elaborated by 50 community leaders over a full day session.The process created a causal loop diagram representing community perceptions of determinants and causes of obesity. The causal loop diagram can be broken down into four separate domains; social influences; fast food and junk food; participation in sport; and general physical activity.This causal loop diagram can provide the basis for community led planning of a prevention response that engages with multiple levels of existing settings and systems.
Merit exponents and control area diagrams in materials selection
International Nuclear Information System (INIS)
Zander, Johan; Sandstroem, Rolf
2011-01-01
Highlights: → Merit exponents are introduced to generalise the merit indices commonly used in materials selection. → The merit exponents can rank materials in general design situations. → To allow identification of the active merit exponent(s), control area diagrams are used. → Principles for generating the control area diagrams are presented. -- Abstract: Merit indices play a fundamental role in materials selection, since they enable ranking of materials. However, the conventional formulation of merit indices is associated with severe limitations. They are dependent on the explicit solution of the variables in the equations for the constraints from the design criteria. Furthermore, it is not always easy to determine which the controlling merit index is. To enable the ranking of materials in more general design cases, merit exponents are introduced as generalisations of the merit indices. Procedures are presented for how to compute the merit exponents numerically without having to solve equations algebraically. Merit exponents (and indices) are only valid in a certain range of property values. To simplify the identification of the controlling merit exponent, it is suggested that so called control area diagrams are used. These diagrams consist of a number of domains, each showing the active constraints and the controlling merit exponent. It is shown that the merit exponents play a crucial role when the control area diagram (CAD) is set up. The principles in the paper are developed for mechanically loaded components and are illustrated for engineering beams with two or three geometric variables.
JaxoDraw: A graphical user interface for drawing Feynman diagrams
Binosi, D.; Theußl, L.
2004-08-01
JaxoDraw is a Feynman graph plotting tool written in Java. It has a complete graphical user interface that allows all actions to be carried out via mouse click-and-drag operations in a WYSIWYG fashion. Graphs may be exported to postscript/EPS format and can be saved in XML files to be used for later sessions. One of JaxoDraw's main features is the possibility to create ? code that may be used to generate graphics output, thus combining the powers of ? with those of a modern day drawing program. With JaxoDraw it becomes possible to draw even complicated Feynman diagrams with just a few mouse clicks, without the knowledge of any programming language. Program summaryTitle of program: JaxoDraw Catalogue identifier: ADUA Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUA Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar gzip file Operating system: Any Java-enabled platform, tested on Linux, Windows ME, XP, Mac OS X Programming language used: Java License: GPL Nature of problem: Existing methods for drawing Feynman diagrams usually require some 'hard-coding' in one or the other programming or scripting language. It is not very convenient and often time consuming, to generate relatively simple diagrams. Method of solution: A program is provided that allows for the interactive drawing of Feynman diagrams with a graphical user interface. The program is easy to learn and use, produces high quality output in several formats and runs on any operating system where a Java Runtime Environment is available. Number of bytes in distributed program, including test data: 2 117 863 Number of lines in distributed program, including test data: 60 000 Restrictions: Certain operations (like internal latex compilation, Postscript preview) require the execution of external commands that might not work on untested operating systems. Typical running time: As an interactive program, the running time depends on the complexity
Generalized internal multiple imaging (GIMI) using Feynman-like diagrams
Zuberi, M. A. H.
2014-05-19
Single scattering events recorded in surface seismic data do not fully illuminate the subsurface structure, especially if it is complicated. In such cases, multiple internal scatterings (internal multiples) can help improve the illumination. We devise a generalized internal multiple imaging (GIMI) procedure that maps internal multiple energy to their true location with a relatively mild addition to the computational cost. GIMI theory relies heavily on seismic interferometry, which often involves cumbersome algebra, especially when one is dealing with high-order terms in the perturbation series. To make the derivations, and inference of the results easier, we introduce Feynman-like diagrams to represent different terms of the perturbation series (solution to the Lippman–Schwinger equation). The rules we define for the diagrams allow operations like convolution and cross-correlation in the series to be compressed in diagram form. The application of the theory to a double scattering example demonstrates the power of the method.
The limit shape problem for ensembles of Young diagrams
Hora, Akihito
2016-01-01
This book treats ensembles of Young diagrams originating from group-theoretical contexts and investigates what statistical properties are observed there in a large-scale limit. The focus is mainly on analyzing the interesting phenomenon that specific curves appear in the appropriate scaling limit for the profiles of Young diagrams. This problem is regarded as an important origin of recent vital studies on harmonic analysis of huge symmetry structures. As mathematics, an asymptotic theory of representations is developed of the symmetric groups of degree n as n goes to infinity. The framework of rigorous limit theorems (especially the law of large numbers) in probability theory is employed as well as combinatorial analysis of group characters of symmetric groups and applications of Voiculescu's free probability. The central destination here is a clear description of the asymptotic behavior of rescaled profiles of Young diagrams in the Plancherel ensemble from both static and dynamic points of view.
Project Management Plan for the INEL technology logic diagrams
International Nuclear Information System (INIS)
Rudin, M.J.
1992-10-01
This Project Management Plan (PjMP) describes the elements of project planning and control that apply to activities outlined in Technical Task Plan (TTP) ID-121117, ''Technology Logic Diagrams For The INEL.'' The work on this project will be conducted by personnel in EG ampersand G Idaho, Inc.'s Waste Technology Development Program. Technology logic diagrams represent a formal methodology to identify technology gaps or needs within Environmental Restoration/Waste Management Operations, which will focus on Office of Environmental Restoration and Waste Management (EM-50) research and development, demonstration, test, and evaluation efforts throughout the US Department of Energy complex. This PjMP describes the objectives, organization, roles and responsibilities, workscope and processes for implementing and managing the technology logic diagram for the Idaho National Engineering Laboratory project
Unified Phase Diagram for Iron-Based Superconductors.
Gu, Yanhong; Liu, Zhaoyu; Xie, Tao; Zhang, Wenliang; Gong, Dongliang; Hu, Ding; Ma, Xiaoyan; Li, Chunhong; Zhao, Lingxiao; Lin, Lifang; Xu, Zhuang; Tan, Guotai; Chen, Genfu; Meng, Zi Yang; Yang, Yi-Feng; Luo, Huiqian; Li, Shiliang
2017-10-13
High-temperature superconductivity is closely adjacent to a long-range antiferromagnet, which is called a parent compound. In cuprates, all parent compounds are alike and carrier doping leads to superconductivity, so a unified phase diagram can be drawn. However, the properties of parent compounds for iron-based superconductors show significant diversity and both carrier and isovalent dopings can cause superconductivity, which casts doubt on the idea that there exists a unified phase diagram for them. Here we show that the ordered moments in a variety of iron pnictides are inversely proportional to the effective Curie constants of their nematic susceptibility. This unexpected scaling behavior suggests that the magnetic ground states of iron pnictides can be achieved by tuning the strength of nematic fluctuations. Therefore, a unified phase diagram can be established where superconductivity emerges from a hypothetical parent compound with a large ordered moment but weak nematic fluctuations, which suggests that iron-based superconductors are strongly correlated electron systems.
Unified Phase Diagram for Iron-Based Superconductors
Gu, Yanhong; Liu, Zhaoyu; Xie, Tao; Zhang, Wenliang; Gong, Dongliang; Hu, Ding; Ma, Xiaoyan; Li, Chunhong; Zhao, Lingxiao; Lin, Lifang; Xu, Zhuang; Tan, Guotai; Chen, Genfu; Meng, Zi Yang; Yang, Yi-feng; Luo, Huiqian; Li, Shiliang
2017-10-01
High-temperature superconductivity is closely adjacent to a long-range antiferromagnet, which is called a parent compound. In cuprates, all parent compounds are alike and carrier doping leads to superconductivity, so a unified phase diagram can be drawn. However, the properties of parent compounds for iron-based superconductors show significant diversity and both carrier and isovalent dopings can cause superconductivity, which casts doubt on the idea that there exists a unified phase diagram for them. Here we show that the ordered moments in a variety of iron pnictides are inversely proportional to the effective Curie constants of their nematic susceptibility. This unexpected scaling behavior suggests that the magnetic ground states of iron pnictides can be achieved by tuning the strength of nematic fluctuations. Therefore, a unified phase diagram can be established where superconductivity emerges from a hypothetical parent compound with a large ordered moment but weak nematic fluctuations, which suggests that iron-based superconductors are strongly correlated electron systems.
Generalized internal multiple imaging (GIMI) using Feynman-like diagrams
Zuberi, M. A. H.; Alkhalifah, Tariq Ali
2014-01-01
Single scattering events recorded in surface seismic data do not fully illuminate the subsurface structure, especially if it is complicated. In such cases, multiple internal scatterings (internal multiples) can help improve the illumination. We devise a generalized internal multiple imaging (GIMI) procedure that maps internal multiple energy to their true location with a relatively mild addition to the computational cost. GIMI theory relies heavily on seismic interferometry, which often involves cumbersome algebra, especially when one is dealing with high-order terms in the perturbation series. To make the derivations, and inference of the results easier, we introduce Feynman-like diagrams to represent different terms of the perturbation series (solution to the Lippman–Schwinger equation). The rules we define for the diagrams allow operations like convolution and cross-correlation in the series to be compressed in diagram form. The application of the theory to a double scattering example demonstrates the power of the method.
Electroweak penguin diagrams and two-body B decays
International Nuclear Information System (INIS)
Gronau, M.; Hernandez, O.F.; London, D.; Rosner, J.L.
1995-01-01
We discuss the role of electroweak penguin diagrams in B decays to two light pseudoscalar mesons. We confirm that the extraction of the weak phase α through the isospin analysis involving B→ππ decays is largely unaffected by such operators. However, the methods proposed to obtain weak and strong phases by relating B→ππ, B→πK, and B→K bar K decays through flavor SU(3) will be invalidated if eletroweak penguin diagrams are large. We show that, although the introduction of electroweak penguin contributions introduces no new amplitudes of flavor SU(3), there are a number of ways to experimentally measure the size of such effects. Finally, using SU(3) amplitude relations we present a new way of measuring the weak angle γ which holds even in the presence of electroweak penguin diagrams
Sequence Algebra, Sequence Decision Diagrams and Dynamic Fault Trees
International Nuclear Information System (INIS)
Rauzy, Antoine B.
2011-01-01
A large attention has been focused on the Dynamic Fault Trees in the past few years. By adding new gates to static (regular) Fault Trees, Dynamic Fault Trees aim to take into account dependencies among events. Merle et al. proposed recently an algebraic framework to give a formal interpretation to these gates. In this article, we extend Merle et al.'s work by adopting a slightly different perspective. We introduce Sequence Algebras that can be seen as Algebras of Basic Events, representing failures of non-repairable components. We show how to interpret Dynamic Fault Trees within this framework. Finally, we propose a new data structure to encode sets of sequences of Basic Events: Sequence Decision Diagrams. Sequence Decision Diagrams are very much inspired from Minato's Zero-Suppressed Binary Decision Diagrams. We show that all operations of Sequence Algebras can be performed on this data structure.
How to Draw Energy Level Diagrams in Excitonic Solar Cells.
Zhu, X-Y
2014-07-03
Emerging photovoltaic devices based on molecular and nanomaterials are mostly excitonic in nature. The initial absorption of a photon in these materials creates an exciton that can subsequently dissociate in each material or at their interfaces to give charge carriers. Any attempt at mechanistic understanding of excitonic solar cells must start with drawing energy level diagrams. This seemingly elementary exercise, which is described in textbooks for inorganic solar cells, has turned out to be a difficult subject in the literature. The problem stems from conceptual confusion of single-particle energy with quasi-particle energy and the misleading practice of mixing the two on the same energy level diagram. Here, I discuss how to draw physically accurate energy diagrams in excitonic solar cells using only single-particle energies (ionization potentials and electron affinities) of both ground and optically excited states. I will briefly discuss current understanding on the electronic energy landscape responsible for efficient charge separation in excitonic solar cells.
Basics of introduction to Feynman diagrams and electroweak interactions physics
International Nuclear Information System (INIS)
Bilenky, S.M.; Mikhov, S.G.
1994-01-01
The Feynman diagrams are the main computational method for the evaluation of the matrix elements of different processes. Although it is a perturbative method, its significance is not restricted to perturbation theory only. In this book, the elements of quantum field theory, the Feynman diagram method, the theory of electroweak interactions and other topics are discussed. A number of classical weak and electroweak processes are considered in details. This involves, first of all, the construction of the matrix elements of the process using both the Feynman diagram method (when perturbation theory can be applied) and the invariance principles (when perturbation theory fails). Then the cross sections and the decay probabilities are computed. The text is providing widely used computational techniques and some experimental data. (A.B.). 32 refs., 7 appendix
Re-determination of succinonitrile (SCN) camphor phase diagram
Teng, Jing; Liu, Shan
2006-04-01
Low-melting temperature transparent organic materials have been extensively used to study the pattern formation and microstructure evolution. It proves to be very challenging to accurately determine the phase diagram since there is no viable way to measure the composition microscopically. In this paper, we presented the detailed experimental characterization of the phase diagram of succinonitrile (SCN)-camphor binary system. Differential scanning calorimetry, a ring-heater, and the directional solidification technique have been combined to determine the details of the phase diagram by using the purified materials. The advantages and disadvantages have been discussed for the different experimental techniques. SCN and camphor constitute a simple binary eutectic system with the eutectic composition at 23.6 wt% camphor and eutectic temperature at 37.65 °C. The solidus and the solubility of the SCN base solid solution have been precisely determined for the first time in this binary system.
Phase diagram of supercooled water confined to hydrophilic nanopores
Limmer, David T.; Chandler, David
2012-07-01
We present a phase diagram for water confined to cylindrical silica nanopores in terms of pressure, temperature, and pore radius. The confining cylindrical wall is hydrophilic and disordered, which has a destabilizing effect on ordered water structure. The phase diagram for this class of systems is derived from general arguments, with parameters taken from experimental observations and computer simulations and with assumptions tested by computer simulation. Phase space divides into three regions: a single liquid, a crystal-like solid, and glass. For large pores, radii exceeding 1 nm, water exhibits liquid and crystal-like behaviors, with abrupt crossovers between these regimes. For small pore radii, crystal-like behavior is unstable and water remains amorphous for all non-zero temperatures. At low enough temperatures, these states are glasses. Several experimental results for supercooled water can be understood in terms of the phase diagram we present.
Decorated-box-diagram contributions to Bhabha scattering. Pt. 1
International Nuclear Information System (INIS)
Faeldt, G.; Osland, P.
1994-01-01
We evaluate, in the light-energy limit, s>>vertical stroke tvertical stroke >>m 2 >>λ 2 , the sum of amplitudes corresponding to a class of Feynman diagrams describing two-loop virtual photonic corrections to Bhabha scattering. The diagrams considered are box and crossed-box diagrams with an extra photon decorating one of the fermion lines. The mathematical method employed is that of Mellin transforms. In the eikonal approximation, this sum of two-loop amplitudes has previously been evaluated, and found to be equal to the sum of the box and crossed-box amplitudes, multiplied by the electric form factor of the electron. We obtain a similar factorization, but with the form factor replaced by another expression involving the logarithms log(λ 2 /m 2 ) and log(λ 2 /vertical stroke tvertical stroke ). (orig.)
Anytime decision making based on unconstrained influence diagrams
DEFF Research Database (Denmark)
Luque, Manuel; Nielsen, Thomas Dyhre; Jensen, Finn Verner
2016-01-01
. This paper addresses this problem by proposing an anytime algorithm that at any time provides a qualified recommendation for the first decisions of the problem. The algorithm performs a heuristic-based search in a decision tree representation of the problem. We provide a framework for analyzing......Unconstrained influence diagrams extend the language of influence diagrams to cope with decision problems in which the order of the decisions is unspecified. Thus, when solving an unconstrained influence diagram we not only look for an optimal policy for each decision, but also for a so-called step......-policy specifying the next decision given the observations made so far. However, due to the complexity of the problem, temporal constraints can force the decision maker to act before the solution algorithm has finished, and, in particular, before an optimal policy for the first decision has been computed...
Influence Diagram Use With Respect to Technology Planning and Investment
Levack, Daniel J. H.; DeHoff, Bryan; Rhodes, Russel E.
2009-01-01
Influence diagrams are relatively simple, but powerful, tools for assessing the impact of choices or resource allocations on goals or requirements. They are very general and can be used on a wide range of problems. They can be used for any problem that has defined goals, a set of factors that influence the goals or the other factors, and a set of inputs. Influence diagrams show the relationship among a set of results and the attributes that influence them and the inputs that influence the attributes. If the results are goals or requirements of a program, then the influence diagram can be used to examine how the requirements are affected by changes to technology investment. This paper uses an example to show how to construct and interpret influence diagrams, how to assign weights to the inputs and attributes, how to assign weights to the transfer functions (influences), and how to calculate the resulting influences of the inputs on the results. A study is also presented as an example of how using influence diagrams can help in technology planning and investment. The Space Propulsion Synergy Team (SPST) used this technique to examine the impact of R&D spending on the Life Cycle Cost (LCC) of a space transportation system. The question addressed was the effect on the recurring and the non-recurring portions of LCC of the proportion of R&D resources spent to impact technology objectives versus the proportion spent to impact operational dependability objectives. The goals, attributes, and the inputs were established. All of the linkages (influences) were determined. The weighting of each of the attributes and each of the linkages was determined. Finally the inputs were varied and the impacts on the LCC determined and are presented. The paper discusses how each of these was accomplished both for credibility and as an example for future studies using influence diagrams for technology planning and investment planning.
Kalron, Alon; Frid, Lior
2015-11-15
People with multiple sclerosis (PwMS) frequently experience walking and balance impairments. In our previous report, we demonstrated that spatio-temporal gait parameters, collected by the Zebris FDM-T instrumented treadmill (Zebris Medical GmbH, Germany), serve as valid markers of neurological impairment in the MS population. In the current study, we focused on a unique outcome statistic of the instrumented treadmill, the "butterfly" diagram which reflects the variability of the center of pressure trajectory during walking. Therefore, the aim of the study was to examine the relationship between parameters related to the gait butterfly diagram and the level of neurological impairment in PwMS. Specifically we examined whether the gait butterfly parameters can differentiate between MS patients with normal cerebellar function and those suffering from ataxia. Demographic, neurological and gait parameters were collected from 341 PwMS, 213 women, aged 42.3 (S.D.=13.8). MS participants with ataxia demonstrated higher scores relating to the butterfly gait variability parameters compared to PwMS with normal or slightly abnormal cerebellar function. According to the results of the binary regression analysis, gait variability in the ant-post direction was found to explain 18.1% of the variance related to cerebellar function; R(2)=0.181, χ(2)(1)=67.852, P<0.001. Measurements derived from the butterfly diagram are proper estimators for important neurological functions in PwMS and should be considered in order to improve diagnosis and assessment of the MS population. Copyright © 2015 Elsevier B.V. All rights reserved.
Lancioni, Giulio E.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Buonocunto, Francesca; Sacco, Valentina; Colonna, Fabio; Navarro, Jorge; Lanzilotti, Crocifissa; Bosco, Andrea; Megna, Gianfranco; De Tommaso, Marina
2009-01-01
Post-coma persons in an apparent condition of vegetative state and pervasive motor impairment pose serious problems in terms of assessment and intervention options. A technology-based learning assessment procedure might serve for them as a diagnostic supplement with possible implications for rehabilitation intervention. The learning assessment…
CALPHAD calculation of phase diagrams : a comprehensive guide
Saunders, N; Miodownik, A P
1998-01-01
This monograph acts as a benchmark to current achievements in the field of Computer Coupling of Phase Diagrams and Thermochemistry, often called CALPHAD which is an acronym for Computer CALculation of PHAse Diagrams. It also acts as a guide to both the basic background of the subject area and the cutting edge of the topic, combining comprehensive discussions of the underlying physical principles of the CALPHAD method with detailed descriptions of their application to real complex multi-component materials. Approaches which combine both thermodynamic and kinetic models to interpret non-equilibrium phase transformations are also reviewed.
INFRARED COLOR-COLOR DIAGRAMS FOR AGB STARS
Directory of Open Access Journals (Sweden)
Kyung-Won Suh
2007-09-01
Full Text Available We present infrared color-color diagrams of AGB stars from the observations at near and mid infrared bands. We compile the observations for hundreds of OH/IR stars and carbon stars using the data from the Midcourse Space Experiment (MSX, the two micron sky survey (2MASS, and the IRAS point source catalog (PSC. We compare the observations with the theoretical evolutionary tracks of AGB stars. From the new observational data base and the theoretical evolution tracks, we discuss the meaning of the infrared color-color diagrams at different wavelengths.
Basic principles of Hasse diagram technique in chemistry.
Brüggemann, Rainer; Voigt, Kristina
2008-11-01
Principles of partial order applied to ranking are explained. The Hasse diagram technique (HDT) is the application of partial order theory based on a data matrix. In this paper, HDT is introduced in a stepwise procedure, and some elementary theorems are exemplified. The focus is to show how the multivariate character of a data matrix is realized by HDT and in which cases one should apply other mathematical or statistical methods. Many simple examples illustrate the basic theoretical ideas. Finally, it is shown that HDT is a useful alternative for the evaluation of antifouling agents, which was originally performed by amoeba diagrams.
Phase diagram of the ternary Zr-Ti-Sn system
International Nuclear Information System (INIS)
Arias, D.; Gonzalez Camus, M.
1987-01-01
It is well known that Ti stabilizes the high temperature cubic phase of Zr and that Sn stabilizes the low temperature hexagonal phase of Zr. The effect of Sn on the Zr-Ti diagram has been studied in the present paper. Using high purity metals, nine different alloys have been prepared, with 4-32 at % Ti, 0.7-2.2 at % Sn and Zr till 100%. Resistivity and optical and SEM metallography techniques have been employed. Effect of some impurities have been analyzed. The results are discussed and different isothermic sections of the ternary Zr-Ti-Sn diagram are presented. (Author) [es
Microsoft Visio 2013 business process diagramming and validation
Parker, David
2013-01-01
Microsoft Visio 2013 Business Process Diagramming and Validation provides a comprehensive and practical tutorial including example code and demonstrations for creating validation rules, writing ShapeSheet formulae, and much more.If you are a Microsoft Visio 2013 Professional Edition power user or developer who wants to get to grips with both the essential features of Visio 2013 and the validation rules in this edition, then this book is for you. A working knowledge of Microsoft Visio and optionally .NET for the add-on code is required, though previous knowledge of business process diagramming
Directory of Open Access Journals (Sweden)
Ozge Ozalp Yuregir
2012-02-01
Full Text Available Prenatal diagnosis is the process of determining the health or disease status of the fetus or embryo before birth. The purpose is early detection of diseases and early intervention when required. Prenatal genetic tests comprise of cytogenetic (chromosome assessment and molecular (DNA mutation analysis tests. Prenatal testing enables the early diagnosis of many diseases in risky pregnancies. Furthermore, in the event of a disease, diagnosing prenatally will facilitate the planning of necessary precautions and treatments, both before and after birth. Upon prenatal diagnosis of some diseases, termination of the pregnancy could be possible according to the family's wishes and within the legal frameworks. [Archives Medical Review Journal 2012; 21(1.000: 80-94
Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny
2018-02-01
We propose a cross-domain, multi-task transfer learning framework to transfer knowledge learned from non-medical images by a deep convolutional neural network (DCNN) to medical image recognition task while improving the generalization by multi-task learning of auxiliary tasks. A first stage cross-domain transfer learning was initiated from ImageNet trained DCNN to mammography trained DCNN. 19,632 regions-of-interest (ROI) from 2,454 mass lesions were collected from two imaging modalities: digitized-screen film mammography (SFM) and full-field digital mammography (DM), and split into training and test sets. In the multi-task transfer learning, the DCNN learned the mass classification task simultaneously from the training set of SFM and DM. The best transfer network for mammography was selected from three transfer networks with different number of convolutional layers frozen. The performance of single-task and multitask transfer learning on an independent SFM test set in terms of the area under the receiver operating characteristic curve (AUC) was 0.78+/-0.02 and 0.82+/-0.02, respectively. In the second stage cross-domain transfer learning, a set of 12,680 ROIs from 317 mass lesions on DBT were split into validation and independent test sets. We first studied the data requirements for the first stage mammography trained DCNN by varying the mammography training data from 1% to 100% and evaluated its learning on the DBT validation set in inference mode. We found that the entire available mammography set provided the best generalization. The DBT validation set was then used to train only the last four fully connected layers, resulting in an AUC of 0.90+/-0.04 on the independent DBT test set.
Directory of Open Access Journals (Sweden)
N.M. Ghasem
2003-12-01
Full Text Available In this paper, the simulink block diagram is used to solve a model consists of a set of ordinary differential and algebraic equations to control the temperature inside a simple stirred tank heater. The flexibility of simulink block diagram gives students a better understanding of the control systems. The simulink also allows solution of mathematical models and easy visualization of the system variables. A polyethylene fluidized bed reactor is considered as an industrial example and the effect of the Proportional, Integral and Derivative control policy is presented for comparison.
Indian Academy of Sciences (India)
SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.
Phase diagram of the disordered Bose-Hubbard model
International Nuclear Information System (INIS)
Gurarie, V.; Pollet, L.; Prokof'ev, N. V.; Svistunov, B. V.; Troyer, M.
2009-01-01
We establish the phase diagram of the disordered three-dimensional Bose-Hubbard model at unity filling which has been controversial for many years. The theorem of inclusions, proven by Pollet et al. [Phys. Rev. Lett. 103, 140402 (2009)] states that the Bose-glass phase always intervenes between the Mott insulating and superfluid phases. Here, we note that assumptions on which the theorem is based exclude phase transitions between gapped (Mott insulator) and gapless phases (Bose glass). The apparent paradox is resolved through a unique mechanism: such transitions have to be of the Griffiths type when the vanishing of the gap at the critical point is due to a zero concentration of rare regions where extreme fluctuations of disorder mimic a regular gapless system. An exactly solvable random transverse field Ising model in one dimension is used to illustrate the point. A highly nontrivial overall shape of the phase diagram is revealed with the worm algorithm. The phase diagram features a long superfluid finger at strong disorder and on-site interaction. Moreover, bosonic superfluidity is extremely robust against disorder in a broad range of interaction parameters; it persists in random potentials nearly 50 (!) times larger than the particle half-bandwidth. Finally, we comment on the feasibility of obtaining this phase diagram in cold-atom experiments, which work with trapped systems at finite temperature.
Interpreting Evolutionary Diagrams: When Topology and Process Conflict
Catley, Kefyn M.; Novick, Laura R.; Shade, Courtney K.
2010-01-01
The authors argue that some diagrams in biology textbooks and the popular press presented as depicting evolutionary relationships suggest an inappropriate (anagenic) conception of evolutionary history. The goal of this research was to provide baseline data that begin to document how college students conceptualize the evolutionary relationships…
The Use of Kruskal-Newton Diagrams for Differential Equations
International Nuclear Information System (INIS)
Fishaleck, T.; White, R.B.
2008-01-01
The method of Kruskal-Newton diagrams for the solution of differential equations with boundary layers is shown to provide rapid intuitive understanding of layer scaling and can result in the conceptual simplification of some problems. The method is illustrated using equations arising in the theory of pattern formation and in plasma physics.
ARBUS: A FORTRAN tool for generating tree structure diagrams
International Nuclear Information System (INIS)
Ferrero, C.; Zanger, M.
1992-02-01
The FORTRAN77 stand-alone code ARBUS has been designed to aid the user by providing a tree structure diagram generating utility for computer programs written in FORTRAN language. This report is intended to describe the main purpose and features of ARBUS and to highlight some additional applications of the code by means of practical test cases. (orig.) [de
Using Photographs and Diagrams to Test Young Children's Mass Thinking
Cheeseman, Jill; McDonough, Andrea
2013-01-01
This paper reports the results of a pencil-and-paper test developed to assess young children's understanding of mass measurement. The innovative element of the test was its use of photographs. We found many children of the 295 6-8 year-old children tested could "read" the photographs and diagrams and recognise the images as…
Phase Stability Diagrams for High Temperature Corrosion Processes
Directory of Open Access Journals (Sweden)
J. J. Ramos-Hernandez
2013-01-01
Full Text Available Corrosion phenomena of metals by fused salts depend on chemical composition of the melt and environmental conditions of the system. Detail knowledge of chemistry and thermodynamic of aggressive species formed during the corrosion process is essential for a better understanding of materials degradation exposed to high temperature. When there is a lack of kinetic data for the corrosion processes, an alternative to understand the thermodynamic behavior of chemical species is to utilize phase stability diagrams. Nowadays, there are several specialized software programs to calculate phase stability diagrams. These programs are based on thermodynamics of chemical reactions. Using a thermodynamic data base allows the calculation of different types of phase diagrams. However, sometimes it is difficult to have access to such data bases. In this work, an alternative way to calculate phase stability diagrams is presented. The work is exemplified in the Na-V-S-O and Al-Na-V-S-O systems. This system was chosen because vanadium salts is one of the more aggressive system for all engineering alloys, especially in those processes where fossil fuels are used.
Approximate Solutions of Interactive Dynamic Influence Diagrams Using Model Clustering
DEFF Research Database (Denmark)
Zeng, Yifeng; Doshi, Prashant; Qiongyu, Cheng
2007-01-01
Interactive dynamic influence diagrams (I-DIDs) offer a transparent and semantically clear representation for the sequential decision-making problem over multiple time steps in the presence of other interacting agents. Solving I-DIDs exactly involves knowing the solutions of possible models...
Generalized balanced power diagrams for 3D representations of polycrystals
DEFF Research Database (Denmark)
Alpers, Andreas; Brieden, Andreas; Gritzmann, Peter
2015-01-01
Characterizing the grain structure of polycrystalline material is an important task in material science. The present paper introduces the concept of generalized balanced power diagrams as a concise alternative to voxelated mappings. Here, each grain is represented by (measured approximations of...
Introducing the Circular Flow Diagram to Business Students
Daraban, Bogdan
2010-01-01
The circular flow of income diagram is a simplified representation of the functioning of a free-market economic system. It illustrates how businesses interact with the other economic participants within the key macroeconomic markets that coordinate the flow of income through the national economy. Therefore, it can provide students of business with…
An automatic system for elaboration of chip breaking diagrams
DEFF Research Database (Denmark)
Andreasen, Jan Lasson; De Chiffre, Leonardo
1998-01-01
A laboratory system for fully automatic elaboration of chip breaking diagrams has been developed and tested. The system is based on automatic chip breaking detection by frequency analysis of cutting forces in connection with programming of a CNC-lathe to scan different feeds, speeds and cutting...
Macroscopic Fundamental Diagram for pedestrian networks : Theory and applications
Hoogendoorn, S.P.; Daamen, W.; Knoop, V.L.; Steenbakkers, Jeroen; Sarvi, Majid
2017-01-01
The Macroscopic Fundamental diagram (MFD) has proven to be a powerful concept in understanding and managing vehicular network dynamics, both from a theoretical angle and from a more application-oriented perspective. In this contribution, we explore the existence and the characteristics of the
Continuous cooling transformation diagrams for 6XXX aluminium alloys
International Nuclear Information System (INIS)
Bryantsev, P Yu
2009-01-01
Continuous cooling transformation diagrams of aluminum solid solution decomposition in range of cooling rates 100-1900 deg. C/h were built for some alloys of Al-Mg-Si-Fe system. Influence of cooling rate and chemical composition on temperatures of start and finish of solution decomposition was determined.
Integrating Mathematics and Science: Ecology and Venn Diagrams
Leszczynski, Eliza; Munakata, Mika; Evans, Jessica M.; Pizzigoni, Francesca
2014-01-01
Efforts to integrate mathematics and science have been widely recognized by mathematics and science educators. However, successful integration of these two important school disciplines remains a challenge. In this article, a mathematics and science activity extends the use of Venn diagrams to a life science context and then circles back to a…
Emergence of an urban traffic macroscopic fundamental diagram
DEFF Research Database (Denmark)
Ranjan, Abhishek; Fosgerau, Mogens; Jenelius, Erik
2016-01-01
This paper examines mild conditions under which a macroscopic fundamental diagram (MFD) emerges, relating space-averaged speed to occupancy in some area. These conditions are validated against empirical data. We allow local speedoccupancy relationships and, in particular, require no equilibrating...
Resonant count diagram and solar g mode oscillations
International Nuclear Information System (INIS)
Guenther, D.B.; Demarque, P.
1984-01-01
Evidence is provided to support the hypothesis that, because of the particular frequency separations of the solar g modes, resonant three-wave interactions stimulate only a selected few g modes. A resonant count diagram was obtained by plotting the total number of possible resonant three-wave interactions or a given beat frequency against the inverse of the beat frequency (the beat period), within a given frequency tolerance. The 1 = 1, 2, 3, 4 g modes calculated by Christensen-Dalsgaard, Gough and Morgan (1979) for a standard model of the Sun were used. The diagram has a significant peak at 160 minutes as well as other peaks at longer periods. The g modes that Delache and Scherrer (1983) tentatively identified from the Crimea-Stanford data were also plotted. These modes were found to correspond with the other peaks in the diagram. This coincidence between the observed g modes and the peaks in the resonant count diagram suggest that the observed g modes do owe their observability to resonant three-wave interactions
Quark-diagram analysis of charmed-baryon decays
International Nuclear Information System (INIS)
Kohara, Y.
1991-01-01
The Cabibbo-allowed two-body nonleptonic decays of charmed baryons to a SU(3)-octet (or -decuplet) baryon and a pseudoscalar meson are examined on the basis of the quark-diagram scheme. Some relations among the decay amplitudes or rates of various decay modes are derived. The decays of Ξ c + to a decuplet baryon are forbidden
FF. A package to evaluate one-loop Feynman diagrams
International Nuclear Information System (INIS)
Oldenborgh, G.J. van
1990-09-01
A short description and a user's guide of the FF package are given. This package contains routines to evaluate numerically the scalar one-loop integrals occurring in the evaluation in one-loop Feynman diagrams. The algorithms chosen are numerically stable over most parameter space. (author). 5 refs.; 1 tab
Equations of State and Phase Diagrams of Ammonia
Glasser, Leslie
2009-01-01
We present equations of state relating the phases and a three-dimensional phase diagram for ammonia with its solid, liquid, and vapor phases, based on fitted authentic experimental data and including recent information on the high-pressure solid phases. This presentation follows similar articles on carbon dioxide and water published in this…
Perturbation theory via Feynman diagrams in classical mechanics
Penco, R.; Mauro, D.
2006-01-01
In this paper we show how Feynman diagrams, which are used as a tool to implement perturbation theory in quantum field theory, can be very useful also in classical mechanics, provided we introduce also at the classical level concepts like path integrals and generating functionals.
Approximate Compilation of Constraints into Multivalued Decision Diagrams
DEFF Research Database (Denmark)
Hadzic, Tarik; Hooker, John N.; O’Sullivan, Barry
2008-01-01
We present an incremental refinement algorithm for approximate compilation of constraint satisfaction models into multivalued decision diagrams (MDDs). The algorithm uses a vertex splitting operation that relies on the detection of equivalent paths in the MDD. Although the algorithm is quite gene...
Phase shifts of the paired wings of butterfly diagrams
International Nuclear Information System (INIS)
Li Kejun; Liang Hongfei; Feng Wen
2010-01-01
Sunspot groups observed by the Royal Greenwich Observatory/US Air Force/NOAA from 1874 May to 2008 November and the Carte Synoptique solar filaments from 1919 March to 1989 December are used to investigate the relative phase shift of the paired wings of butterfly diagrams of sunspot and filament activities. Latitudinal migration of sunspot groups (or filaments) does asynchronously occur in the northern and southern hemispheres, and there is a relative phase shift between the paired wings of their butterfly diagrams in a cycle, making the paired wings spatially asymmetrical on the solar equator. It is inferred that hemispherical solar activity strength should evolve in a similar way within the paired wings of a butterfly diagram in a cycle, demonstrating the paired wings phenomenon and showing the phase relationship between the northern and southern hemispherical solar activity strengths, as well as a relative phase shift between the paired wings of a butterfly diagram, which should bring about almost the same relative phase shift of hemispheric solar activity strength. (research papers)
Energy Diagram for the Catalytic Decomposition of Hydrogen Peroxide
Tatsuoka, Tomoyuki; Koga, Nobuyoshi
2013-01-01
Drawing a schematic energy diagram for the decomposition of H[subscript 2]O[subscript 2] catalyzed by MnO[subscript 2] through a simple thermometric measurement outlined in this study is intended to integrate students' understanding of thermochemistry and kinetics of chemical reactions. The reaction enthalpy, delta[subscript r]H, is…
Ground state phase diagram of extended attractive Hubbard model
International Nuclear Information System (INIS)
Robaszkiewicz, S.; Chao, K.A.; Micnas, R.
1980-08-01
The ground state phase diagram of the extended Hubbard model with intraatomic attraction has been derived in the Hartree-Fock approximation formulated in terms of the Bogoliubov variational approach. For a given value of electron density, the nature of the ordered ground state depends essentially on the sign and the strength of the nearest neighbor coupling. (author)
Riparian Sediment Delivery Ratio: Stiff Diagrams and Artifical Neural Networks
Various methods are used to estimate sediment transport through riparian buffers and grass jilters with the sediment delivery ratio having been the most widely applied. The U.S. Forest Service developed a sediment delivery ratio using the stiff diagram and a logistic curve to int...
The Effect of Diagrams on Online Reading Processes and Memory
McCrudden, Matthew T.; Magliano, Joseph P.; Schraw, Gregory
2011-01-01
This work examined how adjunct displays influence college readers' moment-by-moment processing of text and the products of reading, using reading time (Experiments 1 & 2), and think-aloud methodologies (Experiment 3). Participants did or did not study a diagram before reading a text. Overall, the reading time data, think-aloud data, and recall…
Advanced quantum theory and its applications through Feynman diagrams
International Nuclear Information System (INIS)
Scadron, M.D.
1979-01-01
The two themes of scattering diagrams and the fundamental forces characterize this book. Transformation theory is developed to review the concepts of nonrelativistic quantum mechanics and to formulate the relativistic Klein-Gordon, Maxwell, and Dirac wave equations for relativistic spin-0, massless spin-1, and spin-1/2 particles, respectively. The language of group theory is used to write relativistic Lorentz transformations in a form similar to ordinary rotations and to describe the important discrete symmetries of C, P, and T. Then quantum mechanics is reformulated in the language of scattering theory, with the momentum-space S matrix replacing the coordinate-space hamiltonian as the central dynamical operator. Nonrelativistic perturbation scattering diagrams are then developed, and simple applications given for nuclear, atomic, and solid-state scattering problems. Next, relativistic scattering diagrams built up from covariant Feynman propagators and vertices in a manner consistent with the CPT theorem are considered. The theory is systematically applied to the lowest-order fundamental electromagnetic, strong, weak, and gravitational interactions. Finally, the use of higher-order Feynman diagrams to explain more detailed aspects of quantum electrodynamics (QED) and strong-interaction elementary-particle physics is surveyed. Throughout, the notion of currents is used to exploit the underlying symmetries and dynamical interactions of the various quantum forces. 258 references, 77 figures, 1 table
Calculation of Fe-B-V ternary phase diagram
Czech Academy of Sciences Publication Activity Database
Homolová, V.; Kroupa, Aleš; Výrostková, A.
2012-01-01
Roč. 520, APR (2012), s. 30-35 ISSN 0925-8388 R&D Projects: GA ČR(CZ) GAP108/10/1908 Institutional support: RVO:68081723 Keywords : phase diagram * thermodynamic modelling Subject RIV: BJ - Thermodynamics Impact factor: 2.390, year: 2012
Block diagrams of the radar interface and control unit
Collier, J. W.
1989-01-01
The Interface and Control Unit is the heart of the radar module, which occupies one complex channel of the High-Speed Data Acquisition System of the Goldstone Solar System Radar. Block diagrams of the interface unit are presented as an aid to understanding its operation and interconnections to the rest of the radar module.
A proposed phase equilibrium diagram for Pt-Zr system
International Nuclear Information System (INIS)
Arias, D.E.; Gribaudo, L.
1993-01-01
A revision of the phase diagram of the Pt-Zr system is presented using up to date information from recent publications. The proposed change concerning the invariant transformation in the Pt-rich zone is supported by simplified thermodynamic evaluations. (author). 12 refs., 1 fig
A cautionary tale of interpreting O-C diagrams
DEFF Research Database (Denmark)
Skarka, M.; Liska, J.; Dreveny, R.
2018-01-01
We present a comprehensive study of Z CVn, an RR Lyrae star that shows long-term cyclic variations of its pulsation period. A possible explanation suggested from the shape of the O-C diagram is the light travel-time effect, which we thoroughly examine. We used original photometric and spectroscop...
Phase stabilities at a glance: Stability diagrams of nickel dipnictides
International Nuclear Information System (INIS)
Bachhuber, F.; Rothballer, J.; Weihrich, R.; Söhnel, T.
2013-01-01
In the course of the recent advances in chemical structure prediction, a straightforward type of diagram to evaluate phase stabilities is presented based on an expedient example. Crystal structures and energetic stabilities of dipnictides NiPn 2 (Pn = N, P, As, Sb, Bi) are systematically investigated by first principles calculations within the framework of density functional theory using the generalized gradient approximation to treat exchange and correlation. These dipnictides show remarkable polymorphism that is not yet understood systematically and offers room for the discovery of new phases. Relationships between the concerned structures including the marcasite, the pyrite, the arsenopyrite/CoSb 2 , and the NiAs 2 types are highlighted by means of common structural fragments. Electronic stabilities of experimentally known and related AB 2 structure types are presented graphically in so-called stability diagrams. Additionally, competing binary phases are taken into consideration in the diagrams to evaluate the stabilities of the title compounds with respect to decomposition. The main purpose of the stability diagrams is the introduction of an image that enables the estimation of phase stabilities at a single glance. Beyond that, some of the energetically favored structure types can be identified as potential new phases
Stabilization diagrams using operational modal analysis and sliding filters
DEFF Research Database (Denmark)
Olsen, Peter; Juul, Martin Ørum Ørhem; Tarpø, Marius Glindtvad
2017-01-01
This paper presents a filtering technique for doing effective operational modal analysis. The result of the filtering method is construction of stabilization diagram that clearly separates physical poles from spurious noise poles needed for unbiased fitting. A band pass filter is moved slowly over...
Quest for the QCD phase diagram in extreme environments
Energy Technology Data Exchange (ETDEWEB)
Fukushima, Kenji, E-mail: fuku@rk.phys.keio.ac.jp [Keio University, Department of Physics (Japan)
2013-03-15
We review the state-of-the-art status of the research on the phase diagram of QCD matter out of quarks and gluons. Our discussions particularly include the extreme environments such as the high temperature, the high baryon density, and the strong magnetic field.
Investigating the QCD phase diagram with hadron multiplicities at NICA
Energy Technology Data Exchange (ETDEWEB)
Becattini, F. [Universita di Firenze (Italy); INFN, Firenze (Italy); Stock, R. [Goethe University, Frankfurt am Main (Germany)
2016-08-15
We discuss the potential of the experimental programme at NICA to investigate the QCD phase diagram and particularly the position of the critical line at large baryon-chemical potential with accurate measurements of particle multiplicities. We briefly review the present status and we outline the tasks to be accomplished both theoretically and the experimentally to make hadronic abundances a sensitive probe. (orig.)